There is literature describing unilateral or focal pulmonary edema due to mitral regurgitation. The proposed mechanism is a regurgitant jet propelling blood towards the orifice of a particular pulmonary vein within the left atrium, which selectively pressurizes that vein. The increased hydrostatic pressure is transmitted to the pulmonary capillaries that drain into that vein, causing focal consolidation. A 62-year-old female presented with acute hypoxic respiratory failure. Her dyspnea started suddenly and she was unresponsive when she arrived at the emergency department via emergency medical services. Her initial oxygen saturation was 23% and she was immediately intubated. Sequential chest radiographs demonstrated dense consolidation in the right upper lung field and then opacification of the right hemithorax. These asymmetric lung findings were suspicious for infectious etiology but she was afebrile with no respiratory secretions and had normal inflammatory markers. Echocardiography showed a ruptured anterior papillary muscle causing a flail mitral valve leaflet with severe mitral regurgitation. The patient developed cardiogenic shock; she had an intra-aortic balloon pump placed for afterload reduction and was taken to the operating room for an emergency mitral valve replacement. Her clinical status rapidly improved and she made a full recovery. As in this case, acute mitral regurgitation can present with sudden life-threatening respiratory failure and cardiogenic shock so prompt diagnosis is critical. This is often misdiagnosed as pneumonia or other respiratory illnesses. Awareness, early diagnosis, and treatment of this entity could provide significant morbidity and mortality benefits for patients. Shortness of breath is a common chief complaint seen in the emergency department and carries a broad differential diagnosis. Chest radiography, a valuable and commonly used tool, can help clinicians narrow differential diagnoses and provide appropriate patient care. Unilateral infiltrates on chest radiography, often seen in bacterial pneumonia, may evoke an infectious etiology of dyspnea. However, focal or unilateral pulmonary edema has been described in patients with mitral regurgitation from numerous causes, including spontaneous valve perforation , valve pA 62-year-old female presented to the emergency department with acute respiratory failure. Her past medical history included obstructive sleep apnea with the use of bilevel positive airway pressure at night, obesity hypoventilation syndrome, systemic hypertension, pulmonary hypertension, mild to moderate mitral regurgitation complicated by pulmonary edema, asthma, and the use of home oxygen . A transthoracic echocardiogram performed five months before the presentation during hospitalization for dyspnea showed normal biventricular size and function, mild left atrial dilation, normal mitral valve structure with mild to moderate regurgitation, and a mildly elevated pulmonary artery systolic pressure. A chest radiograph performed one month before the presentation showed no evidence of pulmonary edema. Her home medications included furosemide, losartan, inhaled fluticasone and vilanterol, promethazine syrup, nebulized albuterol, and benzonatate.Per the patient’s husband, she was in her normal state of health until awakening in the morning and feeling short of breath after using the restroom; the shortness of breath was refractory to albuterol nebulizer treatments self-administered at home for a presumed asthma exacerbation. At that time, she appeared to have labored breathing, prompting the patient and her husband to call emergency medical services (EMS). In the ambulance, she was initially alert and awake with a normal mental status but suddenly became unresponsive; her oxygen saturation dropped to 20% and her heart rate increased to 160 beats per minute. She arrived at the emergency department via EMS, unresponsive, with an oxygen saturation of 23% and sinus tachycardia; initial examination revealed diffuse rhonchi and a Glasgow Coma Scale (GCS) score of six. She was immediately intubated; she required high ventilator settings (fraction of inspired oxygen (FiO2) at 100%, positive end-expiratory pressure (PEEP) at 16 mbar), and neuromuscular blockade to achieve adequate oxygenation.Initial chest radiography demonstrated mild cardiomegaly, background interstitial pulmonary edema, and a dense consolidation in the right upper lobe with a patchy opacity at the right lung base. Figure .A subsequent chest radiograph showed nearly complete opacification of the right hemithorax and progressive opacification of the left lung base Figure .These asymmetric lung findings were suspicious for an infectious etiology, including coronavirus disease 2019 (COVID-19) and bacterial pneumonia. She tested negative for COVID-19 . She had a mild leukocytosis without neutrophilic predominance, and inflammatory markers were not consistent with severe infection  confirmed severe mitral regurgitation and showed a ruptured anterior papillary muscle Figure .The TEE showed severe systolic flow reversal in the right upper pulmonary vein and only mild systolic flow reversal in the other three pulmonary veins. Figure The pulsed-wave Doppler images demonstrate pulmonary vein flow reversal, noting the highest degree of flow reversal in the right superior pulmonary vein Figures -9.She was taken to the operating room for emergent bioprosthetic mitral valve replacement. Afterward, her clinical status improved; she began to void, her pulmonary artery pressures were corrected, and she was extubated 72 hours after the presentation. Subsequent chest radiography showed rapid resolution of the asymmetric infiltrates Figure .This was a dramatic presentation of spontaneous, non-ischemic papillary muscle rupture, causing severe acute mitral regurgitation and respiratory failure from the resulting flash pulmonary edema. The patient was critically ill within one to two hours of symptom onset. Of particular interest is the initial chest radiograph showing asymmetric opacification with dense consolidation of the right upper lobe. This appearance was initially concerning for an infectious etiology, which could have delayed the diagnosis.Focal or unilateral pulmonary edema has been described in patients with mitral regurgitation from numerous causes, including spontaneous valve perforation , valve pSchnyder et al. found that 9% of patients with severe mitral regurgitation had chest radiography findings that were "localized or predominant" in the right upper lobe . Attias There is a proposed mechanism for localized pulmonary edema due to mitral regurgitation. Typically, systolic or diastolic left ventricular failure leads to increased pressure within the left atrium, which is transmitted symmetrically to each of the pulmonary veins. This leads to increased hydrostatic pressure within pulmonary capillaries, causing a uniform degree of pulmonary edema throughout the lungs. It is thought that asymmetric pulmonary edema is due to a mitral regurgitant jet that propels blood selectively towards the orifice of a particular pulmonary vein within the left atrium. If a regurgitant jet causes increased pressure within that pulmonary vein, it would transmit increased hydrostatic pressure selectively to the pulmonary capillaries that drain into that pulmonary vein, causing focal edema.This mechanism is supported by Kashiura et al., who described two cases of unilateral pulmonary edema from severe acute mitral regurgitation. The first case involved an eccentric jet blowing towards the right side of the left atrium and a patient who presented with right-sided opacities. The second case involved a jet blowing towards the left side of the left atrium and a patient who presented with left-sided opacities . In thisAs in this case, acute mitral regurgitation can present with sudden life-threatening respiratory failure and cardiogenic shock, so prompt diagnosis is critical. This is often misdiagnosed as pneumonia or other respiratory illnesses. Patients with unilateral lung opacification due to mitral regurgitation have delays in diagnosis and worse outcomes compared to similar patients with bilateral pulmonary edema. In this case, the key to the diagnosis was the reported history of sudden-onset dyspnea that rapidly progressed to respiratory failure.In conclusion, acute mitral regurgitation should be considered in the differential diagnosis for patients with focal pulmonary opacities or complete opacification of a hemithorax in the appropriate clinical context, such as sudden-onset hypoxic respiratory failure, especially if vitals, examination, and laboratory biomarkers are inconsistent with severe infection. Awareness, early diagnosis, and treatment of this entity could provide significant morbidity and mortality benefits for patients. In this case, the findings support the previously proposed mechanism of a regurgitant jet selectively pressurizing a pulmonary vein, leading to focal consolidation.


It is often challenging to engage and retain rural Latinx and Native Americans in psychosocial interventions after stroke, despite the fact that these populations tend to experience poorer health outcomes. Although strategies for effective patient-provider communication exist, few studies focus on the cultural aspects of engagement and retention of diverse dyads in a rural context. The aim of this study is to describe barriers to engagement and retention of diverse rural dyads in post-stroke psychosocial interventions, as well as to elucidate specific strategies to address these barriers. Semi-structured interviews were conducted with Nf14 clinical providers with extensive experience serving diverse rural couples and families. Qualitative data were analyzed using interpretive description methods. Seven key barriers were identified, grouped broadly into: 1. Those presented by providers  and 2. Those existing within dyads themselves . Providers offered specific culturally-informed strategies to overcome barriers which in turn may increase engagement and minimize attrition. Providers and researchers may benefit from these insights as they work to communicate with, build trust, and meet the unique needs of these populations.


More specifically, they found that university students are more likely to update beliefs concerning grade expectations following positive rather than negative prediction errors.Behavioral results suggest that learning by trial-and-error  relies on a teaching signal, the prediction error, which quantifies the difference between the obtained and the expected reward. Evidence suggests that distinct cortico-striatal circuits are recruited to encode better-than-expected (positive prediction error) and worst-than-expected (negative prediction error) outcomes. A recent study by Villano et al. Virtually all animals use past rewards and punishments to modify their future course of actions (a process referred to as reinforcement learning). Behavioral and computational theories suggest that reinforcement learning relies on a teaching signal, the prediction error (PE), which quantifies the difference between the obtained and the expected reward. PE minimization across trials and repetitions enables  to efficiently learn and adapt their behavior accordingly.2. A direct implication of these neurobiological observations is that learning from positive and negative PEs could be independently modulated at the behavioral level3.Neurophysiological studies across rodents, monkeys and humans collectively suggest that reinforcement learning processes are largely underpinned by dopamine-mediated neural plasticity of the cortical-subcortical connections and that positive and negative PEs are encoded across dissociable circuits that recruit different cortical and subcortical structures of the brainUntil recently, however, prior studies were carried out in relatively constrained and “aseptic” experimental settings. Most of the tasks employed implemented quite artificial learning scenarios, which potentially casts doubt on the ecological and real life validity of these findings.1 has overcome this limitation by investigating how humans integrate positive and negative PEs when updating their belief concerning consequential real life outcomes. More specifically, in a large scale study, they asked 625 university students to predict their grades during four consecutive semesters.A recent study from Villano et al.At the macroscopic level, participants learned to modify their expectations concerning future grades in a manner compatible with prediction error minimization. However, a more fine-grained analysis showed signs that could be considered as an “optimistic” bias: on average participants learned more following positive as opposed to negative PEs. The results support the idea of distinguishable neural networks for positive and negative prediction errors by showing an optimistic bias manifesting at the behavioral level.4.The authors also report that participants who presented symptoms consistent with anxiety and depression, also showed a reduction in optimistic learning bias. This finding is consistent with prior evidence showing similar learning rate modifications in depression and anxietyAltogether, this study provides evidence for prediction error-based learning outside of the laboratory, in real life scenarios. It also provides evidence for the fact that learning from positive and negative prediction errors are functionally dissociable. Both findings are consistent with decades-long neurobiological investigations of the computational mechanisms underlying reinforcement learning.


Certain neuropsychiatric symptoms (NPS), namely apathy, depression and anxiety demonstrated great value in predicting dementia progression representing eventually an opportunity window for timely diagnosis and treatment. However, sensitive and objective markers of these symptoms are still missing.To investigate the association between automatically extracted speech features and NPS in early-stage dementia patients.Speech of 141 patients aged 65 or older with neurocognitive disorder was recorded while performing two short narrative speech tasks. Presence of NPS was assessed by the Neuropsychiatric Inventory. Paralinguistic markers relating to prosodic, formant, source, and temporal qualities of speech were automatically extracted, correlated with NPS. Machine learning experiments were carried out to validate the diagnostic power of extracted markers.Different speech variables seem to be associated with specific neuropsychiatric symptoms of dementia; apathy correlates with temporal aspects, anxiety with voice quality and this was mostly consistent between male and female after correction for cognitive impairment. Machine learning regressors are able to extract information from speech features and perform above baseline in predicting anxiety, apathy and depression scores.Different NPS seem to be characterized by distinct speech features which in turn were easily extractable automatically from short vocal tasks. These findings support the use of speech analysis for detecting subtypes of NPS. This could have great implications for future clinical trials.No significant relationships.


To protect themselves from contracting the SARS-CoV-2 virus, many older adults managing multiple medical conditions experienced increased social isolation. The objective of our qualitative research study was to describe how older Veterans receiving care from the United States (US) Department of Veterans Affairs (VA) healthcare system, and their caregivers, managed increased social isolation during the pandemic. We recruited Veterans and their caregivers residing in rural and urban areas who received care from either a tele-palliative care or a tele-geriatrics clinic connected to one VA Medical Center, inviting them to participate in phone interviews. From May-September 2021, we interviewed N=23 participants (n=9 Veterans and n=14) caregivers. We applied a deductive and inductive approach to thematic analysis to analyze interview data. Findings revealed that while caregivers experienced increased anxiety, which they attributed to pandemic-related changes, they also expressed solidarity in that others were experiencing similar stressors. Many caregivers and Veterans shared experiences of increased loneliness, which some found difficult to manage as communication with their social networks was sparse. At the same time, the pandemic made them value relationships with others more than before. Some Veterans noted they kept busy with hobbies and did not feel much loneliness despite increased isolation. Caregivers caring for Veterans with dementia stated they experienced confusion about their narrower social networks because they could not remember reasons why they were not regularly spending time with them. Findings demonstrate the need to identify strategies and policies to better support caregivers and older Veterans during times of crisis.


Hospitalizations for severe injection related infections (SIRI) amongst persons who inject drugs (PWID) are often complicated by patient directed discharge (PDD), incomplete antibiotic treatment and 90-day readmission. Despite a strong association with improved clinical outcomes, medications for opioid use disorder (MOUD) remain significantly underutilized in this patient population. Beginning in January of 2022, our institution revised several key policies that had limited inpatient use of MOUD while also implementing a new order set to facilitate MOUD inductions. This study seeks to quantify the clinical impact of these interventions in PWID admitted with SIRI.We first performed a retrospective analysis of all PWID hospitalized with SIRI between January 2018 and December 2020 to establish baseline rates of PDD, antibiotic completion and 90-day readmission in patients who received MOUD compared to those who did not. Subsequent analyses will utilize a quasi-experimental design to compare the same clinical outcomes in patients admitted before and after institutional guideline revision and MOUD order set implementation.A total of 97 patients were included in our baseline assessment, of which 21 (21.6%) received MOUD while hospitalized. Of patients receiving MOUD, 11 (52.4%) were new inductions. Use of MOUD was associated with significantly lower rates of PDD  and significantly higher rates of antibiotic completion .Our baseline data agrees with existing literature in finding MOUD to be an effective way of reducing PDD and increasing antibiotic completion in PWID admitted with SIRI. However, overall MOUD utilization was low, particularly after accounting for the effect of individuals prescribed MOUD prior to admission. Forthcoming data will assess the impact of institutional guideline revision and MOUD order set implementation on PDD, antibiotic completion and hospital readmission in PWID admitted with SIRI.All Authors: No reported disclosures.


Many existing Alzheimer’s disease (AD) caregiving interventions focus narrowly on thechallenges and needs of a primary caregiver rather than the family systems in which they areembedded. We advance a family systems framework by invoking convoys of caregiving to adaptan existing AD caregiver intervention to Middle Eastern/Arab American families in metroDetroit (N=56). The composition of caregiving networks is described, followed by assessment ofcare burden, depressive symptoms, care satisfaction and family conflict. Results show thatsiblings and children are the predominate support network members who accompanied theprimary caregiver to the program. Paired t-tests show that care burden and family conflictdecreased while caregiving satisfaction increased following program participation. Depressivesymptoms did not change. Findings illuminate how convoys of care may serve as valuablesupport resources, yet may also be the source of stress and conflict.


The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. Android malware hackers adopt reverse engineering and repackage benign applications with their malicious code. Therefore, Android applications developers tend to use state-of-the-art obfuscation techniques to mitigate the risk of application plagiarism. The malware authors adopt the obfuscation and transformation techniques to defeat the anti-malware detections, which this paper refers to as evasions. Malware authors use obfuscation techniques to generate new malware variants from the same malicious code. The concern of encountering difficulties in malware reverse engineering motivates researchers to secure the source code of benign Android applications using evasion techniques. This study reviews the state-of-the-art evasion tools and techniques. The study criticizes the existing research gap of detection in the latest Android malware detection frameworks and challenges the classification performance against various evasion techniques. The study concludes the research gaps in evaluating the current Android malware detection framework robustness against state-of-the-art evasion techniques. The study concludes the recent Android malware detection-related issues and lessons learned which require researchers’ attention in the future. Since this study focused on Android malware obfuscation, we had selected ‘Android malware, ‘malware obfuscation’, and ‘malware evasion’ as our search terms. The search results in 511 research from journals and conferences’ proceeding database. The search results mainly records are from IEEE, journals and conferences distributions as per The list of collected articles represent the Android malware obfuscation and detection frameworks. It included the three types of the malware analysis techniques static, dynamic and hybrid techniques in the last decade from 2011 to early 2021. Hence, we collected Android malware frameworks for the last decade and innovative contributions that appeared in high-ranked journals or conferences such as IEEE, ACM, and Springer.Since, this paper explored the last 10 years’ research to evaluate the Android detection frameworks against evasion techniques, we focused on experimental malware detection articles using static, dynamic and hybrid analysis techniques, excluding the unrelated articles. We excluded articles that are not Android specific malware detection such as IOS and Windows based operating system. In addition, we excluded all other languages and include only English language research to avoid translation overhead in future.As shown in We scrutinise Android malware detection academic and commercial frameworks while a large portion of the past work concentrated on commercial anti-malware solutions. This study examines different evasion techniques that hinder detecting malicious parts of applications and affect detection accuracy by reviewing state-of-the-art Android malware studies and issues limiting the detection of evasion techniques. It is worth noting that this work differs from related works that examine detection methods, as we go through evasion techniques that let malware evades detection methods.In the section, we discussed the Android application architecture. Subsequently, we investigate the Android operating system (OS) weaknesses. This background highlights the seriousness of some drawbacks to rationalize the necessity of establishing this review and explain the essential terms to support the readers of this study.Android application, Android app, or APK refers to the Android application from now on and throughout this paper. APK is a compressed file; an unzipping program extracts its files and folders. This segment explains the APK components and their contents, as some terms are essential in this study. APK developers use development tools that occasionally require simple programming experience from young developers. The Android app runs on Dalvik or ART equivalent to Java Virtual Machine (JVM) in a desktop environment. The APK structure consists of many files and directories; the main file is Classes.dex Java bytecode; it includes the classes and is packed together in a single .dex file. The AndroidManifest.xml file contains deployment specifications and the required permissions from Android OS. Resources .arsc is compiled resources, and Res folder is un-compiled resources.The Android system must install the APK file so that the end-user can utilize the application’s functionalities. The Android system only accepts APK with a valid developer certificate, called developer identifier. Individual developers keep their certificate keys; there is no Central Authority (CA) server to maintain developers’ keys, and thus no chain of trust between app stores and developers.a)Activities: The user interface that end-users interact with and that communicates with other activities using intents.b)Services: Android application component runs as a background process and bonds or un-bonds with other Android system components.c)Broadcast and Receivers Intents: send messages that all other applications or individual applications receive.d)Content Providers: It is the intermediate unit to share data between applications.End-users need to run the installed applications, while other apps run as a service in the OS background. Therefore, the Android application’s main components are as follows:(a) Open Source:The advantage of Android source code’s openness helps developers’ communities enhance the OS and add more features. Therefore, the Android community improves Android OS daily. But, this contradicts with the security concerns when malware writers take this advantage. It makes their job more straightforward than in closed source firmware, which commonly triggers new vulnerabilities and malware attacks .(b) End-users Security Awareness:End-users understanding malware’s seriousness plays a vital role in early prevention and detection when using feedback and reviews. However, the end-users feedback system is insecure and easily polluted by fake comments . End-use(c) Third-party Apps Market:via tools such as the ADB tool in Android SDK, which increases the probability of installing malicious apps  The Coarse Granularity of Android Permissions:i.e., one permission that provides access to entire Internet protocols and all sites. There is no competent permission administration or sufficient permission documentation, leading to excess permissions  Developers’ Signatures:Android application developers have to sign their apps with their developer key before uploading the developed application to the market. There is no external party to authenticate developers’ signatures and thus no confidentiality or integrity . Hence, (f) Application Version Update:Android applications usually enhance their functionalities in the form of version updates. The security frameworks analyze the application during installation, and the update process downloads new services/features without security precautions or checks .(g) USB Debugging:USB debugging is a valuable feature for Android Application development; it helps developers be more productive and efficiently troubleshoot applications. It allows direct installation of an application to the Android device using Android SDK tools such as the ADB tool. In addition Expo framework  has the (h) Dynamic Code Loading (DCL):DCL is an Android OS feature that enables benign Android applications to call another APK or malicious code to compile and execute it in real-time. However, malware developers use this feature to load their malicious codes dynamically after the detection framework ranked the malicious app as benign.(i) Inter-application Communication (intent):Android OS uses the inter-application intent system to deliver a message from and to applications. Malware developers sniff, modify, or gain knowledge, compromising data integrity and privacy . The intWith some insight into the Android applications’ development design, we list the Android system’s weaknesses and definitions for the readers of this study. The following is a list of Android flaws and characteristics that malware authors and attackers abuse.This section represents our taxonomy of the currently used evasion techniques and research studies on detecting obfuscated malware. Our taxonomy focuses on classifying the related studies with the same objectives and goals to harvest a comprehensive collection of material and comparative conclusions. When scrutinizing many existing studies, we find it more appropriate to study the evasion detection capabilities of each studied framework after introducing the evasion techniques that hinder malware analysis and detection. This section presents the taxonomy of detection techniques for the ground truth relation between the detection methodology and the evasion ability. Android applications have powerful tools and techniques to secure and protect their applications from being reverse-engineered. Conversely, malware authors are using obfuscation tools and techniques to evade detection. Therefore, evasions, or in other terms, transformation techniques, are techniques that try to defeat Android malware detection and rank the malware applications as benign.As displayed in Polymorphic malware is the malware category that keeps changing its characteristics to generate different malware variants evading malware detectors. Polymorphic malware encrypts part of the code embedding malicious code. The polymorphic malwares encrypt itself with variable encryption keys but maintaining the malicious code body unaltered. Polymorphic malware is an advanced version of oligomorphic malware. The oligomorphic malware encrypts the malicious code to defeat source code static analysis based malware detection. Usually, the malware decrypts the malware using the same techniques. However, the oligomorphic malware decrypts the encrypted malicious code using different deyrptor to make decryptor analysis more difficult. The static analysis analyze the decryptor to find the encryption key that enable the detection of the malware. Hence, the static analysis approach is not effective with oligomorphic malware. Polymorphic malware continuously change the decryptor technique to make it more difficult to the source code static analysis approach. These symptoms are indications of the presence of malicious code in an application. In this section, we discuss the polymorphism evasions subcategories, which are package transformation and encryption.(a) Repacking (RPK): It is the process of unpacking the APK file and repacking the original application files but signing the APK file with a developer security key . This wa(b) Package Renaming (PKR): Every Android application has a unique package name. For instance, com.android.chrome is the package name of Google Chrome. PKR uses multilevel techniques to obfuscate the application classes except for the main Class, for instance, “FlattenPackageHireachey” or “RepackageClass” options . As showThis algorithm is applied relatedly to form the multilevel PKR obfuscation. The GinMaster family contains a malicious service that can root devices to escalate privileges, steal confidential information. Later, it receives instructions from a remote server to download and install applications without user interaction. The malware can successfully avoid detection by mobile anti-virus software by using polymorphic techniques to hide malicious code, obfuscating class names for each infected object, and randomizing package names and self-signed certificates for applications. Therefore, PKR evades the malware detection technique and causes false negatives, proven by (c) Identifier Renaming (IDR): Identifier is another APK parameter representing the application developer’s signature. Classes, methods, and fields consider bytecode identifiers, as a signature is generated based on. Malware authors change developer identifiers using many obfuscation tools such as ProGuard  and DexGIn this section, we study types of package transformation, which are Repacking (RPK), Package Renaming (PKR), and Identifier Renaming (IDR).Data Encryption as DEN, Bytecode Encryption as BEN, and Payload Encryption as PEN. This paper examines the following types of evasions:a)Data Encryption (DEN): This evasion technique tends to encrypt specific data vital for the malicious action and decrypt the encrypted data later, which modifies the malware application characteristics to evade the detection techniques . The datb)Bytecode Encryption (BEN): using ProGuard  or DashOc)Payload Encryption (PEN): Malware authors use payload encryption as in DroidDream  malware Some Android malware families encrypt data values inside the code, compiled code or payload, and decrypt the payload whenever desirable. This paper refers to Metamorphic malware is more complex than polymorphic malware that shows a better ability to evade detection frameworks. Malware authors adopt metamorphic malware so to make metamorphic malware detection harder than leveraging polymorphic malware. The metamorphic malware writes new malicious code that varies in each iteration using the same encryption and decryption key. For example, Opcode ngrams  adopts tCode Reordering (CRE), Call Indirection (CIN), and Dead Code Insertion (DCI).a)Code Reordering (CRE): This transformation changes the order of the code by inserting the standard “goto” command to maintain the proper program instruction order.b)Call Indirections (CIN): CIN is an object-oriented feature used dynamically to reference specific values inside the code; CIN creates code transformation evasion, obfuscating the call graph detection techniques . Malwarec)Dead Code Insertion (DCI): Malware inserts junk code into the sequence of the application to ruin its semantics. This type of transformation makes the malware more difficult to analyze . AnDarwiCode obfuscation is an evasion technique initially used to protect applications from piracy and illegal use by many obfuscation techniques. Conversely, malware authors use code obfuscation techniques to evade malware detections. In this study, we highlight three types of code obfuscation the Native Exploits (NEX), Function Inlining and Outlining (FIO), Reflection API (REF), Dynamic Code Loading/Modification (DCL/DCM), and Anti-debugging (ADE).a)Native Exploits (NEX): Android applications call native libraries to run system-related functions. The malware uses a native code exploit to escalate the root privilege while running . Unfortub)Function Inlining and Outlining (FIO): Inlining and outlining are compiler optimization techniques options. Inlining replaces the function call with the entire function body, and the outlining function divides the function into smaller functions. This type of transformation obfuscates the call graph detection technique by redirecting function calls and creating a maze of calls .c)Reflection API (REF): Reflection API is a technique to initiate a private method or get a list of parameters from another function or class, whether this class is private or public. Android developers legitimately use it to provide genericity, maintain backward compatibility, and reinforce application security. However, malware authors take advantage of this feature and use it to bypass detection methods. Reflection evasion facilitates the possibility to call private functions from any technique outside the main class. Recently few studies highlighted the reflection effect on code analysis and considered reflection during the analysis process .d)Dynamic Code Loading/Modification (DCL/DCM): Since Java has the capability of loading code at runtime using class loader methods, Android malware application dynamically download malicious code using the dynamic code loading (DCL). The DCL and DCM techniques provide advanced evasion capability to malware authors, and improper use can make benign applications vulnerable to inject malicious code. For instance, the Plankton malware family uses dynamic code loading to evade detection methods. As being the first malware with DCL that stealthy extend its capabilities on Android devices. It installs an auto-launching background application or service to the device, collecting device critical information to a server. The server sends the malicious class payload URL link to the background service using an HTTP_POST message containing a Dalvik Bytecode jar malicious payload file. In the following trigger of “init” event of the main application, the malicious payload is invoked using the “DexClassLoader” class. Due to the unavailability of the dynamically loaded code during Android malware static analysis, the DCL and DCM evasion technique is another transformation technique that is a big challenge for static analysis . Althouge)Anti-debugging (ADE): The malware developer presumes the limitation of Android that only one debugger can be attached to a process using ptrace functionality . Hence, This section explains the advanced code transformation techniques that are more sophisticated in hindering the malware detection frameworks. We include advanced evasion techniques, such as Virtual Machine Aware (VMA). Another side of anti-emulation evasion is detecting automatic user interaction emulation, which refers to as Programmed Interaction Detection like the monkeyrunner tool used in many frameworks, for instance, the Droidbox (a)Virtual Machine Aware (VMA): The dynamic analysis requires either an Android virtual machine emulator or a physical device to install the suspected application. Scientists studied the possibility of detecting the running environment fingerprints to differentiate between an emulator and a physical device . Androidb)Programmed Interaction Detection (PID): Android malware is an event-driven application that needs a particular series of user interactions to launch malicious actions. Therefore, dynamic analysis requires a running environment user/gesture interaction. Malware writer refers to PID obfuscation as code coverage. Some researchers have tried to address code coverage; however, it remains a challenge to detect it.The primary objective of anti-emulation evasion is to detect the running environment of the sandbox and benignly masquerade as a clean application instead of launching the malicious code, which we refer to as Droidbox  sandbox Droidbox .a)VirtuRepacking (RPK), Package Renaming (PKR), and Identifier Renaming (IDR). Encryption transformation includes Data Encryption (DEN), Bytecode Encryption (BEN), and Payload Encryption (PEN). The metamorphism subcategories are obfuscation transformation, advanced code transformation, and anti-emulations transformation. The code obfuscation subcategory includes Code Reordering (CRE), Call Indirection (CIN), and Dead Code Insertion (DCI). Advanced code transformation includes Native Exploits (NEX), Function Inlining and outlining (FIO), Reflection API (REF), Dynamic Code Loading/Modification (DCL/DCM), and Anti-debugging (ADE) evasion techniques. Last but not least, anti-emulation transformation includes Virtual Machine Aware (VMA) and Programmed Interaction Detection (PID).We scrutinize the top Android malware detection frameworks against the two main evasion categories based on the introduced definitions of Android malware evasion techniques. The first category is polymorphism, which consists of package transformation and encryption transformation. Package transformation includes Many researchers  examine first category is logic-based techniques  classification algorithms to classify the application as benign or malware Vulnerability Check: The vulnerability check method scans all existing Android apps and Android system versions against common security threats. APSET  collectsb)Monitoring Logs: Android systems use process monitoring tools and network monitoring tools. Mobile-Sandbox  uses theThis section explains the Android vulnerability check and monitors the system logs after installing the application. Therefore, post-installation analysis reports the security issues and malicious activity to the end-users.Android malware detection frameworks perform static, dynamic, or hybrid analyses to analyze features for malware detection techniques, which classify the apps as benign or malware. Hence, we identify the following application analysis methodologies.a)Signature-based: This paper classifies the signature-based method under static analysis detection because the signature-based detection approach builds its frameworks with static Android application characteristics. As such, DroidAnalytics  uses a sb)permission-based detection castoff decompressing the APK package; it extracts the malicious symptoms using permission and signature matching analysis. Likewise, Triggerscope (Permission-based: APK Auditor  is a stagerscope  uses pergerscope .c)Androidmanifest file and source code; it scrutinizes the code by listing the native calls, API calls, and URL addresses. It uses machine learning classification to discriminate between malware and benign apps. Likewise, DroidMat  or a scanning agent on an Android smartphone/device. Next is opening a suitable Android operating environment in a physical device or emulator, which we hereafter refer to as a sandbox. The sandbox isolates the application to protect the analysis device from possible malicious attacks. Later, the dynamic analysis starts system logging and network monitoring tools and captures the default system logs.Sandbox Emulator: Most researchers  Supervised Model:Supervised machine learning bases its model on a labelled dataset. The framework splits the dataset into two subsets; first subset is for training and creating the classification model, and the second subset is for testing and validating the trained classification model. Most researchers split the data into 70% training and 30% testing subsets, but some split the data into 50% for training and 50% for testing .(b) Unsupervised Model:In the unsupervised model, apps are unlabeled. The unsupervised model recognizes the class of the applications without knowing which App is malware or benign. Researchers use unsupervised models to learn the covert pattern of the unlabeled data .(c) Reinforcement Learning:The machine exposes itself to an environment where it trains itself continually using trial and error. This machine learns from experience and tries to capture the best possible knowledge to make accurate business decisions. An example of reinforcement learning is the Markov Decision Process .Based on collected characteristics or so-called features , differeTo understand the supervised model classification performance, ML introduces the confusion matrix to calculate the performance measures as per True Positive (TP) represents the number of malware correctly classified.False Positive (FP) accounts for the number of benign apps classified erroneously as malware.True Negative (TN) represents the number of correctly classified benign apps.False Negative (FN) accounts for the number of malware apps classified erroneously as benign.The ML performance measures represent the accuracy of the Android malware detection classification frameworks. y-axis and FPR is the x-axis. Every point in the ROC curve represents one confusion; it is all based on TP and FP values. Area Under the Curve (AUC) is the area under the ROC curve representing the aggregation of the ML trained model (The Receiver Operating Characteristic (ROC) curve plots the TPR against FPR where TRP is the ed model .Researchers or commercial companies have developed the evasion test benches to study the robustness of the currently available anti-malware applications or protect their software packages from piracy issues. The first test benches trials were ADAM  and DroiWe have explored the last 10 years’ research to evaluate the Android detection frameworks against evasion techniques discussed in evasion techniques section. We studied Android malware detection frameworks for the last decade from 2011 to early 2021, as listed in vs polymorphism evasions. We examine the three main static, dynamic, and hybrid frameworks (a) Package Transformation:– RPK - Repacking Evasion Detection:Detecting repacking evasion is possible using static analysis and detection techniques; Dempster–Shafe  investig– PKR - Package Renaming Detection:Static analysis frameworks such as DroidoLytics  and Droi– IDR Identifier Renaming Evasion Detection:DroidOlytics , AndroSiIn summary, most Android malware detection frameworks based on static analysis can detect package transformation techniques . However, most detection frameworks based on dynamic and hybrid analysis inadequately evaluate or report their resilience against IDR evasion techniques. The study spotted 20 papers that scrutinized the RPK evasion using static analysis, and only 10 papers scrutinized IDR. The study spotted nine papers that scrutinized the IDR evasion using static analysis, and only one paper scrutinized IDR using dynamic analysis.(b) Encryption Transformation Evasion Detection:Static analysis detects encryption evasion techniques; many studies, such as DexHunter , DroidKi(a) Code Obfuscation Detection:Code obfuscation consists of CRE, CIN, and DCI; we explain each evasion detection framework in the following list:– CRE - Code Reordering Evasion Detection:ResDroid , AnDarwi– CIN - Call Indirections Evasion Detection:As shown in – DCI - Dead Code Insertion Evasion Detection:AnDarwin  conducte(b) Advanced Code Transformation Detection:It consists of NEX, FIO, REF, DCL, and ADE evasions explained in this section.– NEX Evasion Detection:DroidAPIMiner  uses sta– FIO Evasion Detection:vs function inlining and outlining FIO evasion, as shown in AAMO  evaluate– REF Evasion Detection:As shown in – DCL Evasion Detection:Some Android malware detection frameworks propose and evaluate their methods to detect DCL evasion, for instance, DroidAPIMiner , PoeplauADE Evasion Detection: Only the static analysis DexHunter  consider– Anti-emulation DetectionAnti-emulation evasions consist of VMA and PID evasion techniques; the following is the insight of detection framework analysis:– VMA Evasion Detection:As a countermeasure for the VMA evasion technique, researchers  equip anIn general, the dynamic analysis framework Q-floid  introduc– PID Evasion Detection:Programmed Interaction Detection is fortunate to evade automated dynamic analysis using the inherent difference between key runner and human interaction patterns . InsteadSingh  enhancesIn this section, this paper synthesizes the last decade’s Android malware detection framework using three methodologies. First is identifying the evasions techniques requiring more attention from the research community. The second represents the potential evasion resilient detection techniques by reporting each framework’s number of considered evasion techniques. The third summarizes the three types of Android application analysis with the number of frameworks that evaluated evasions techniques by bubble plot chart. Finally, we provide a to-do list and learned lessons from all the examined frameworks.The static analysis radar graph shown in etc. Besides each point number representing the number of Android malware detection frameworks that evaluated its proposed model against this evasion technique or point in the radar graph. For example, 15 malware detection frameworks consider the RPR evasion technique; thus, the RPK label points to 15, as displayed in We selected the Radar graph to demonstrate that static detection studies could detect package transformation evasions and basic code obfuscation; however, advanced transformation techniques and anti-emulation were neither studied nor evaluated. Concerning DCL, Pektas , in 2014Until today, many static analysis researchers depends on permissions ; howeverResearchers assume that dynamic analysis covers all the simple obfuscations and transformation techniques. Hence many of the dynamic analysis frameworks  ignored However, a few researchers evaluate their frameworks against specific evasion techniques, as reflected in the radar graph of the hybrid malware detection frameworks, as shown in Most of the recent dynamic analysis researches  confirmeThe Hybrid analysis techniques are suggested by many researchers and have been set in their future plan to overcome the resiliency issue of complex obfuscation techniques. However, it is a shocking fact that the examined 26 Android malware detection frameworks using hybrid analysis, that only nine frameworks just consider few evasion techniques such as RiskRanker  that hasThe systematic evasion detection map is illustrated in Researchers have concentrated on Android malware static analysis in the last few years, which requires less time and effort than dynamic analysis. They tried to overcome the static analysis weaknesses against evasion attacks, which is why many researchers evaluated their frameworks to check the anti-obfuscation capabilities, as presented in (a) Obfuscation datasetAndroid malware development is always one step ahead of malware detection techniques, which means malware detection still requires many efforts to catch up with malware development. To achieve this objective, we share several insights drawn from our analysis.(b) Obfuscation detection framework performanceOne of the most important is to keep on updating and standardizing obfuscated malware datasets. We recommend standardizing this dataset by the research community trusted institutions and being available upon validated requests for research purposes. Despite some available obfuscated datasets such as PRAGuard  sharing (c) Metamorphism evasion:The performance of the Android malware framework degraded over time since new malware variants, and obfuscations techniques were generated PetaDroid . Hence, (d) Standard Evasion Benchmarking:Static detection is unable to detect most of the metamorphism evasion techniques because of the dynamic characteristics of metamorphism. However, there is still a lack of dynamic and hybrid frameworks to detect metamorphism evasions. It is therefore beneficial to focus more on developing dynamic and hybrid methods.(e) Android Exploits:We suggest building a comprehensive and collaborative benchmarking framework for Android malware detection evasion techniques that aims to improve the quality of research and add to the body of knowledge in Android malware detection studies. The benchmark consists of a list of evasion techniques based on the detection methods that have been evaluated. As a result, detection methods are tested against a standardized list of malware evasion techniques to determine whether they are capable of detecting malware evasions.(f) Code Integrity Verification:As mentioned earlier, Android is based on Linux OS; it has inherited Linux exploits. Recently, malware authors developed and published the Android exploit code Dirty-Cow CVE-2016-5195 . The Dir(g) Process Authentication:Verification means that the application integrity is authenticated against repackaging by guaranteed third-party authentication authorities. (h) Triggering Malicious Code Assurance:Some researchers leverage the process of model authentication to eliminate the need for an external Certification Authority (CA) that protects the system from many exploits . HoweverThe process of ensuring the malicious code runs during the dynamic analysis sandboxing. TriggerScope  staticalGlobal evasion techniques make Android malware more advanced and sophisticated, which was our motivation for this study. We aim to highlight the most critical weaknesses of Android malware detection frameworks, mainly when malware uses different evasions techniques. Therefore, this study scrutinizes top Android malware detection frameworks against 18 evaluation test benches to evaluate the effectiveness of the evasions detection techniques in Android malware detection frameworks. Therefore, the study introduces a new evasion taxonomy that categorizes the evasion techniques into two main groups, polymorphism and metamorphism, where each group has branches; the polymorphism group includes package transformation, and the encryption metamorphism group contains code obfuscation, advanced transformation, and anti-emulation branches. The study also pointed out the lack of research in evaluating the malware detection against different evasion techniques; hence we scrutinized the frameworks based on every evasion technique and categorized the evaluations based on the malware detection methods. Our analysis results conclude a lack of research evaluating the current Android malware detection framework robustness against state-of-the-art evasion techniques. We also concluded that static analysis based detection is easily evaded with simple obfuscation.On the contrary, dynamic and hybrid analyses address advanced code transformation techniques and other advanced evasions. However, preliminary studies have evaluated their frameworks against evasion techniques. The missing framework evaluations are due to the lack of standard benchmark evasion datasets with updated standard malware datasets and the lack of comprehensive test benches tools to assess the efficiency of the existing and future frameworks. This study advises the research community to exert more effort into detecting anti-emulation evasion as indicated in the map of evasions and detection techniques. We also plan to create a standard evaluation framework to include all types of evasion techniques and consider the new generation of malware that combines multiple evasion techniques.10.7717/peerj-cs.907/supp-1Supplemental Information 1It is the process of unpacking the APK file and repacking the original application files but signing the APK file with a developer security key.Click here for additional data file.10.7717/peerj-cs.907/supp-2Supplemental Information 2Click here for additional data file.


Social withdrawal is an early and common feature of psychiatric disorders. Hypothalamic-pituitary-adrenal (HPA)-axis activation through increased salivary cortisol (sC) and sympathetic activation through increased salivary alpha-amylase (sAA) may play a role.We aimed to study whether the link between increased sC and sAA on the one hand and depression on the other hand is mediated by social withdrawal.In this cross-sectional, observational study, sC and sAA measures were measured in seven saliva samples in 843 participants . Social withdrawal was assessed through the Brief Symptom Inventory (BSI)-, the Short Form 36-, and the Dutch Dimensional Assessment of Personality Pathology social withdrawal subscales, and analyzed using linear regression and mediation analyses. On average, participants were 44.0 years old .Basal and diurnal sAA were unrelated to any social withdrawal scale and depression. Certain sC measures were positively associated with the BSI social withdrawal subscale . We found limited support for statistical mediation by social withdrawal  on the relationship between evening sC and depression.Thus, although we found no support for a role of basal and diurnal sAA in social withdrawal, HPA-axis activation may partly aggravate social withdrawal in depressive disorders.


Dysfunction of both microglia and circuitry in the medial prefrontal cortex (mPFC) have been implicated in numerous neuropsychiatric disorders, but how microglia affect mPFC development in health and disease is not well understood. mPFC circuits undergo a prolonged maturation after birth that is driven by molecular programs and activity-dependent processes. Though this extended development is crucial to acquire mature cognitive abilities, it likely renders mPFC circuitry more susceptible to disruption by genetic and environmental insults that increase the risk of developing mental health disorders. Recent work suggests that microglia directly influence mPFC circuit maturation, though the biological factors underlying this observation remain unclear. In this review, we discuss these recent findings along with new studies on the cellular mechanisms by which microglia shape sensory circuits during postnatal development. We focus on the molecular pathways through which glial cells and immune signals regulate synaptogenesis and activity-dependent synaptic refinement. We further highlight how disruptions in these pathways are implicated in the pathogenesis of neurodevelopmental and psychiatric disorders associated with mPFC dysfunction, including schizophrenia and autism spectrum disorder (ASD). Using these disorders as a framework, we discuss microglial mechanisms that could link environmental risk factors including infections and stress with ongoing genetic programs to aberrantly shape mPFC circuitry. The medial prefrontal cortex (mPFC) controls complex cognitive and emotive functions, including decision making, memory, social interactions and mood . These fMicroglia are increasingly recognized as key players in synapse development and refinement . Microglvia membrane-bound receptors. This represents one key mechanism by which microglia engulf synaptic compartments  and C4B recently shed light on the molecule’s role in synaptic refinement within the retinogeniculate system  provided new insight into mechanisms through which C4-dependent pathways sculpt synapses . In thisvia aberrant microglial pruning. It is possible that yet undiscovered genetic variation in other pruning-relevant molecules  also contributes to disease risk or etiology. As such, we need a more precise understanding of how and when these molecules shape microglial pruning. It will be important to determine whether biological events can elevate C4 expression during adolescence or provoke C4 production outside of its developmentally appropriate time window, leading to pathological circuit modifications via microglial effectors. Individuals with a higher C4A copy number may exhibit particularly strong increases in C4 in certain situations, and, therefore, experience increased vulnerability in particular contexts. These findings also raise the intriguing possibility that an individual’s risk of developing schizophrenia might be mitigated via interventions that modify microglial pruning activity. Along this vein, minocycline, an antibiotic previously shown to reduce synapse pruning in rodent models  during which activity increases dendritic spine density in the dLGN . During In the past decade, numerous studies have corroborated the idea that microglia sculpt developing neuronal circuits . AligninNew work indicates that microglia use different signaling pathways to regulate dendritic spines depending on the stage of development . In bothMECP2 from all GABAergic interneurons recapitulated most behavioral features of Rett’s syndrome, a form of ASD, while deletion in specific regions or other broad cell types only recapitulated some features —non-toxic viruses that are commonly used to manipulate gene expression in the brain. To advance the field, new approaches are needed for spatially restricted manipulation of these cells. In the meantime, as we learn more about the molecular mechanisms guiding neuron-glia interactions in mPFC, we can use neuronally-targeted AAVs to manipulate their interactions in a spatially and temporally restricted manner. With such tools in hand, we can determine when and how microglia regulate specific classes of mPFC synapses. Future studies can investigate to what extent microglia play simultaneous roles in pruning and synaptogenesis within mPFC—potentially at different classes of synapses—and whether microglia may toggle between states that promote synapse formation vs. pruning.When investigating the roles of microglia in mPFC and sensory circuit development, it will also be important to consider potential contributions from astrocytes. Astrocytes shape circuit development in similar ways to microglia. Astrocyte-secreted proteins regulate synaptogenesis  and promIn addition to directly modulating synapse development, astrocytes signal to microglia to alter microglial function. For example, astrocyte-derived IL-33 signals to microglia to promote microglial synapse engulfment and neural circuit maturation in the thalamus and spinal cord . AstrocyStudies from the past decade corroborate the notion that microglia and other immune system factors sculpt developing neuronal circuits . The worAll authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.


Inflammatory or kidney-related metabolic biomarkers have been correlated with cognition and risk for developing dementia among older adults. Using the China Health And Retirement Longitudinal Study, we investigated the cross-sectional correlations between metabolic biomarkers and cognitive outcomes that were ascertained in the same wave, as well as measures lagged by data collection waves. After excluding participants with diagnoses of dementia, we analyzed the association of each biomarker  with scores from cognitive tests. We then identified biomarkers that showed consistent associations across waves. Having elevated CRP (1-3 mg/L) was positively associated with cognitive test scores; whereas abnormal levels of Creatinine  were associated with poorer outcomes. These results provide biomarker evidence of the importance of kidney function and inflammation in dementia research.


In 2020, we observed an increase in inpatient postoperative patient deteriorations. Preliminary case reviews suggested gaps in sepsis care.To identify key drivers associated with effective care escalation and sepsis care in the inpatient surgical setting as part of the initial planning phase of a large improvement initiative.Our multidisciplinary team included surgical nurses, surgical providers, medical providers, patient safety experts, subject matter experts in pediatric sepsis, and subject matter experts in escalation of care. This team formally reviewed cases involving postoperative deterioration to identify causes of gaps in sepsis care and applied its learnings to the development of a key driver diagram. Themes from the key driver diagram included (1) Enhance recognition of deterioration and subsequent escalation of care and (2) Optimize postoperative patient placement. The team hosted a mini-Kaizen event with frontline team members focused on the first theme, the output of which included consensus agreement on two focus areas  and a fishbone diagram to identify/prioritize opportunities in postoperative care escalation.Causes of gaps in sepsis care included barriers to care escalation that could limit generalizability of sepsis resources to the inpatient surgical setting. Figure 1 shows the key driver diagram.We aim to highlight challenges associated with postoperative sepsis care in an inpatient pediatric surgical setting.


Reports have documented national and state-level increases in drug overdose–related emergency department visits, emergency medical services incidents, and deaths among racial and ethnic minority groups in the United States during 2020 amid the COVID-19 pandemic , compared with 119.7% (from 66 to 145) among Hispanic persons . By sex To improve evidence-based drug overdose prevention and response efforts among persons who use opioids in Nevada, particularly among young male Hispanic persons who have experienced overdoses involving illicitly manufactured fentanyls, a better understanding of the underlying risks for the recent increase in overdose deaths is needed. Naloxone can reverse the effects of overdose from opioids, such as illicitly manufactured fentanyls. Although evidence of naloxone administration for opioid-involved deaths was higher among Hispanic persons in 2020, only approximately one in three of those Hispanic decedents had evidence


Recent reports are indicating an inverse association between lithium in drinking water and suicide mortality  observeThe inverse ecological association should be verified by individual data on the biological monitoring of lithium exposure, such as between the serum concentration of lithium and the number of suicide events. Case-control studies analyzing this have been reported. Kanehisa et al. (2017) reporteFinally, Szklarska and Rzymski (2019) reporteThe author declares no conflict of interest.None.


The extraction and exploration of cellulose-based polymers is an exciting area of research. For many years, wood  was considered the main source of cellulosic compounds because of its abundance in nature ,2. HowevRizal et al., in a very compelling and critical overview of the worlds’ current situation regarding cotton waste fibers and their ineffective processing mechanism to mitigate their environmental impact, provided evidence of new work being conducted to employ these wastes in functional products. Indeed, different pre-treatment techniques were identified for their efficiency in extracting cellulose nanocrystals from cotton wastes, and many applications in the packaging and biomedical fields were highlighted . Neto etNano-fibrillated cellulose extracted from waste peels of citrus sinensis by a chemical method involving alkali and acid hydrolysis and modified with silver nanoparticles also synthesized using extract of citrus sinensis skins as a reducing agent were engineered for heavy metal sorption. Data found these isolates and nanoparticles especially effective in removing cadmium and chromium particles from pharmaceutical effluent samples . Rizal eWang et al., engineered a flexible SERS substrate based on regenerated cellulose fibers, obtained from wastepaper, modified with gold nanoparticles through dry-jet wet spinning method, an approach turned eco-friendly by using ionic liquids. The gold nanoparticles were incorporated on the regenerated fibers through electrostatic interaction. The SERS scaffolding system was found very effective for identifying toxins and chemicals like dimetridazole in aqueous solutions . RecycleIn the field of drug delivery, Al-Rajabi et al., explored a green synthesis method for developing a thermo-responsive cellulose hydrogel using cellulose extracted from oil palm empty fruit bunches. The thermo-responsiveness was guaranteed by the incorporation of Pluronic F127 polymer onto the hydrogels. A sustained release of silver sulfadiazine was observed over time. In the end, it was seen that the thermo-responsive cellulose-based hydrogel could give rise to cost-effective and sustainable drug delivery systems using abundantly available agricultural biomass [


GSA’s revised KAER Toolkit for Primary Care Teams  provides useful information for referring individuals and families to community resources following a neurocognitive disorder diagnosis. Mental health practitioners must develop competencies and professional identities within integrated care teams to facilitate this process. This presentation outlines post-assessment suggestions for clinicians across disciplines  in building such teams. There may be needs for serial assessment of specific individual capacities, treatment plans to facilitate shared decision-making between individuals and family care partners, and evaluations of the family care partner’s capacity to provide care. Behavioral health providers assist patients, families, and health care teams across a range of residential settings in understanding and implementing treatment recommendations. Emerging science indicates the value of initiating planning discussions with lifestyle modifications to enhance functioning within dyads. Culturally responsive strategies will be suggested for engagement in planning for future care.


Somatic mutations are DNA variants that occur after the fertilization of zygotes and accumulate during the developmental and aging processes in the human lifespan. Somatic mutations have long been known to cause cancer, and more recently have been implicated in a variety of non-cancer diseases. The patterns of somatic mutations, or mutational signatures, also shed light on the underlying mechanisms of the mutational process. Advances in next-generation sequencing over the decades have enabled genome-wide profiling of DNA variants in a high-throughput manner; however, unlike germline mutations, somatic mutations are carried only by a subset of the cell population. Thus, sensitive bioinformatic methods are required to distinguish mutant alleles from sequencing and base calling errors in bulk tissue samples. An alternative way to study somatic mutations, especially those present in an extremely small number of cells or even in a single cell, is to sequence single-cell genomes after whole-genome amplification (WGA); however, it is critical and technically challenging to exclude numerous technical artifacts arising during error-prone and uneven genome amplification in current WGA methods. To address these challenges, multiple bioinformatic tools have been developed. In this review, we summarize the latest progress in methods for identification of somatic mutations and the challenges that remain to be addressed in the future. Previoulifespan . Somaticlifespan . Once filifespan . The scalifespan .Somatic mutations have increasingly been implicated in various diseases. Somatic mutations in oncogenes and tumor-suppressor genes are the major cause of cancer . Accumulet al. analyzed the tri-nucleotide sSNV profiles across 30 cancer types and successfully identified 27 mutational signatures (Different mutational processes generate distinct profiles of mutational genomic contexts, termed “mutational signatures,” and the landscape of somatic mutations observed in tissue samples or single cells often reflects the combined impact of multiple mutational processes . The largnatures . The catgnatures . A similgnatures  as well gnatures .Theoretically, sequencing reads from reference and mutant alleles of a given mutation should follow a binomial sampling process, where the expected number of mutant reads is positively correlated with total depth and mutant allele fraction. The mutant allele fraction is one of the key variables for somatic mutation detection, which is largely determined by the timing of the occurrence of the mutation and the selective pressure acting on the cell carrying the mutation . SomaticEarly attempts on somatic mutation calling were made in cancer studies, where the sequencing data from a tumor sample were typically compared to a matched normal control sample obtained from the same donor. Strelka  and VarSAlthough clonal expansion events led by driver mutations are not rare in healthy tissues, they usually involve relatively small clones, making it hard to attain high allele fractions in bulk tissue sequencing . MoreoveTargeted ultra-deep sequencing has been widely used as a cost-efficient strategy to increase sequencing depth and thus improve sensitivity in detecting somatic mutations, especially for screening mutations in cancer-related genes . HoweverSomatic mutation in single-cell data has emerged as a powerful endogenous marker to comprehend underlying mutational mechanisms across different cell types , and to Early pioneering works have demonstrated success in applying bulk-sequencing-based methods to sSNV calling in single cells , despitein silico mixture of multiple single cells, and outperformed other tools on calling clonal mutations.Single cells may share some somatic mutations if those mutations occurred in their common ancestral cell . CompareSomatic mutations can also be called from other types of sequencing data beyond DNA sequencing data. RNA-MuTect identified exonic somatic mutations from bulk RNA-seq data by comparing mutation calls against DNA sequencing of a matched control sample . SomaticMany bioinformatic methods have been developed to study somatic mutation in healthy and diseased human samples using bulk or single-cell sequencing . In bulkIn the past decade, genomic studies have benefited from the development of single-molecule sequencing technologies that can directly read nucleotide sequences from DNA or RNA molecules and deliver much longer reads than previously available NGS technologies . Long se


Organized by the Alzheimer's disease and related dementias (ADRD) Interest Group, this symposium aims to highlight unique approaches to address 1) ADRD risk reductions through social and biological factors, and 2) quality of life of those with dementia. The first two presentations introduce remote communication technologies used for behavioral interventions, one for preventing social isolation and the resultant cognitive decline using video-chats by recruiting socially isolated older adults with mild cognitive impairment (MCI). The results of the recently completed randomized controlled trial provide evidence of a positive effect on cognition suggesting enhanced cognitive reserve. Another is for delivering a behavioral symptom intervention for community-dwelling persons with ADRD using telehealth. Researchers will highlight the feasibility, opportunities, and challenges of remote behavioral interventions. The third presentation focuses on micro-level communication between persons living with dementia and their family caregivers. By examining video-recorded home care observations, findings suggest caregiver education on positive interactions could facilitate more meaningful interaction with persons with ADRD. The fourth presentation explores pain among those with ADRD, a multifaceted phenomenon with health and functional consequences. Using the NHATS dataset, researchers show a continued need to detect and address pain in clinical settings particularly among persons with ADRD. The symposium concludes with a presentation using the CHARLS study to investigate correlations between inflammation or kidney-related metabolic biomarkers and cognition. Results provide longitudinal evidence of an association of kidney function and inflammation with cognitive test scores supporting the need to broaden dementia etiology research beyond the amyloid-cascade theory.


This cross-sectional study investigates trends in out-of-pocket costs for unmixed and novel glucagon formulations among patients with Medicare Advantage and commercial insurance from 2010 to 2020. We assessed trends in wholesale acquisition cost (WAC), an estimate of the manufacturer’s list price, for glucagon formulations over time using the AnalySource drug pricing database. Next, we examined trends in OOPCs paid by patients using the Optum deidentified Clinformatics Data Mart, which includes administrative claims from large commercial and Medicare Advantage (MA) health plans. Analyzed claims included any formulation of glucagon from January 1, 2010, through September 30, 2020. Given that there were only 24 prescription fills of novel premixed liquid glucagon injection, it was excluded from analysis . There are multiple possible reasons that may underly this trend, including MA plans passing on higher WAC to beneficiaries or beneficiaries choosing plans with more cost sharing over time.Our study has several limitations. Results may not generalize to patients who are insured through traditional Medicare or Medicaid or are uninsured. In addition, we were unable to assess instances in which high OOPCs prevented patients from filling the prescription (primary nonadherence) or the association of manufacturer patient-assistance programs and coupons with OOPCs for commercial beneficiaries.Cost-sharing should not serve as a major barrier to accessing glucagon for MA and commercially insured patients. Further work should assess other barriers to guideline-concordant glucagon uptake among patients at risk of severe hypoglycemia. Such barriers may include awareness among patients and primary care, emergency, and diabetes clinicians of the availability of this potentially life-saving treatment. In addition, future studies may examine the association of novel glucagon formulations, which had similar OOPCs to those of unmixed glucagon and may be easier to administer, with uptake in the coming years.


Lower socioeconomic status African American older adults living with dementia and their family caregivers face unique advance care planning challenges, including achieving appropriate preference-consistent healthcare near the end of life. The purpose of this project within a larger multi-stakeholder study is to assess community stakeholder perspectives on the needs of African American older adults living with dementia and their family caregivers. Diverse community-based organization leaders (n=9) were interviewed and identified the following thematic needs: Reframing of Advance Care Planning, Clarification of Misinformation, and Expansion of Available Resources. Community leaders expressed strong desires to assist families with advance care planning. The use of creative, culturally-tailored, non-traditional approaches to this process offers innovative ways to promote advance care planning through community engagement. This will change the narrative on advance care planning from a cultural perspective while embracing diversity, enriching discovery, and reimaging aging in the community


Vitiligo is an autoimmune disease of the skin that results in localized or disseminated white macules. One common feature of several existing classification protocols is the distribution of the disease into two main subtypes, non-segmental vitiligo (NSV) and segmental vitiligo (SV). SV is characterized by depigmentation spreading within one or more skin segments while NSV is widespread. Several clinical-epidemiological observations suggest that SV has distinct autoimmune pathophysiology compared to NSV. Furthermore, the clinical distribution pattern of SV lesions closely resembles other melanocyte mosaicism diseases. These observations led us to hypothesize that SV is caused by a localized autoimmune reaction targeting epidermal mosaicism melanocytes. Here, we proposed examples of experimental approaches to assess mosaicism in SV patients. According to an international consensus, vitiligo is classified into three main groups: Segmental (SV), Non-Segmental (NSV), and mixed vitiligo (coexistence of SV and NSV).Reports suggest differences in the biological mechanisms underlying the pathogenesis of SV as compared to NSV. For example, serum levels of TWEAK (Tumor Necrosis Factor-like Weak inducer of Apoptosis) were significantly higher in SV compared to NSV patients.17de novo mutation or retrotransposition occurred delineates the extent of tissues/cells involved in the mosaicism. The hypothesis to be tested suggest that genetic mosaicism in SV occurred at some point during skin/melanocyte differentiation. Different approaches can be applied to test the mosaicism hypothesis in SV, each aiming to detect a distinct type of mosaicism. Here we proposed examples by adapting designs applied to study the host response to infections, detect somatic mutations in cancers and evaluate embryonic development.23Mosaicism designates individuals encompassing at least two cell populations derived from a single zygote but with distinct genotype or epigenetic profiles.de novo mutation occurred during skin differentiation in one segment, a contralateral healthy skin could be used to establish the melanocyte’s “normal” profile  would be performed using DNA extracted from melanocytes from hypochromic and contralateral skin from the same individuals. Variants detected in contralateral tissues would be used to exclude germline variants. Algorithms designed to detect tumor cells, such as MuTect2,None declared.Gerson Dellatorre: Study concept, writing and approval of the final manuscript.Vinicius Medeiros Fava: Study concept, writing and approval of the final manuscript.Marcelo Távora Mira: Writing and approval of the final manuscript.Caio Cesar Silva de Castro: Study concept, writing and approval of the final manuscript.None declared.


Developing efficient cognitive training for the older population is a major public health goal due to its potential cognitive benefits. A promising cognitive training target is executive control, critical for multitasking in everyday life. The aim of this pilot study was to establish the feasibility and acceptability of the Breakfast Task in older adults, a new web-based cognitive training platform that simulates real-life multitasking demands. Research Design andA community-based sample of 24 cognitively healthy participants aged between 60 and 75  underwent an online 5-session training protocol. Each session lasted 40 minutes and occurred twice a week at participant’s homes. Game performance was recorded, and participants completed questionnaires at baseline and after the intervention.Feasibility metrics showed overall high recruitment (82.7%), adherence and retention rates (100%). Acceptability was considered good based on participant`s quantitative and qualitative responses. On average, participants rated the game as interesting, enjoyable and did not report difficulties in accessing the game online or in understanding the instructions. Moreover, participants showed a learning curve across sessions, improvement in most game outcomes and benefits from the emphasis change approach. Discussion and Implications: The findings provide preliminary support for the feasibility and acceptability of the Breakfast Task training platform with community-dwelling older adults and demonstrate potential cognitive benefits. Results suggest the value of further research investigating the Breakfast Task features and dose-response relationship, as well as its efficacy in older adults via larger randomized controlled trials.


Acipenser fulvescens), during the early larval period in response to weekly treatments using chemotherapeutants commonly used in aquaculture  relative to untreated controls. The effects of founding microbial community origin (wild stream vs. hatchery water) were also evaluated. Gut communities were quantified using massively parallel next generation sequencing based on the V4 region of the 16S rRNA gene. Members of the phylum Firmicutes  and Proteobacteria were the dominant taxa in all gut samples regardless of treatment. The egg incubation environment (origin) and its interaction with chemotherapeutant treatment were significantly associated with indices of microbial taxonomic diversity. We observed large variation in the beta diversity of lake sturgeon gut microbiota between larvae from eggs incubated in hatchery and wild (stream) origins based on nonmetric dimensional scaling (NMDS). Permutational ANOVA indicated the effects of chemotherapeutic treatments on gut microbial community composition were dependent on the initial source of the founding microbial community. Influences of microbiota colonization during early ontogenetic stages and the resilience of gut microbiota to topical chemotherapeutic treatments are discussed.Antibiotics, drugs, and chemicals (collectively referred to as chemotherapeutants) are widely embraced in fish aquaculture as important tools to control or prevent disease outbreaks. Potential negative effects include changes in microbial community composition and diversity during early life stages, which can reverse the beneficial roles of gut microbiota for the maintenance of host physiological processes and homeostatic regulation. We characterized the gut microbial community composition and diversity of an ecologically and economically important fish species, the lake sturgeon ( Developing therapeutic regimes that limit stress-induced microbial infection or that reduces the occurrence of high mortality events in aquaculture is essential to successful fish production ,2,3. In 2O2), and sodium chloride (NaCl2)  diversity measures in the lake sturgeon larval GI tracts as a function of egg origin (wild vs. hatchery). The test was performed instead of parametric tests that assume a normal distribution. Next, the effects of chemotherapeutants and egg origin on measures of microbial gut community diversity were estimated based on a generalized linear model (GLM) using suitable probability distributions  in R program (v3.0.2) using glm. The GLM method has been shown to have high efficiency when estimating parameters, yielding interpretable estimates that also avoid transformation bias ,54. p-vaWe included several packages implemented in program R to estimate (beta [β]) diversity measures quantifying bacterial community compositional differences between samples and ecological statistics at the bacterial OTU level. Briefly, vegan  was usedNext, we performed multivariate hypothesis testing to quantify differences in community composition among samples originating from different groups based on locations of egg origins and exposed to different chemotherapeutant treatments using the adonis function  in progrAnalyses investigated whether host origin and/or chemotherapeutant treatment had a significant effect on microbial community structure. NMDS and PERMANOVA were performed on fish gut communities within each origin group to determine whether chemical treatments had effects on fish gut microbiota. Under the null hypothesis, chemotherapeutant treatments were not expected to significantly affect fish gut community taxonomic composition within an origin group, in part because eggs from both hatchery and wild origins were exposed to peroxide during incubation that was believed to reduce and taxonomically homogenize samples for all treatments and both origins. PERMANOVA analyses that indicated significant treatment effects were then analyzed using post hoc tests using betadisper and permutest functions followed by a Tukey test to determine which treatment(s) differ significantly in larval lake sturgeon gut bacterial taxonomic composition.To determine the operational taxonomic units (OTUs) that most likely explained differences in microbial larval lake sturgeon gut community composition between fish from different origins and among different chemotherapeutant treatment groups, we next employed linear discriminant analysis (LDA) effect size (LEfSe) methods . In geneThe algorithm first identified features (OTUs) that were statistically different among origin groups based on the nonparametric factorial Kruskal–Wallis (KW) rank sum test. Additional tests assessed the consistency of differences using unpaired Wilcoxon rank sum tests. In the final step, LEfSe used LDA to rank each differentially abundant taxon in order of the difference in abundance based on an LDA Score . Results represent a scale indicating “importance” of an OTU in origin group differences in microbiota composition .https://huttenhower.sph.harvard.edu/galaxy/, accessed 20 November 2014).To run LEfSe, a tabular file was generated from a shared file that contained no singletons in the program mothur v.1.39.5. The tabular file consisted of taxonomic relative abundance in gut community samples from the four different origin samples that were all exposed to four chemotherapeutant treatments. This tabular file was transferred using an online bioinformatics toolkit developed by the Huttenhower lab to perform LEfSe analyses . Phyla detected in the remainder of the gut community included Acidobacteria, Bacteroidetes, and Verrucomicrobia that collectively comprised 30% of gut communities. A total of 144 samples were retained after quality filtering was performed in the sequence pipeline analyses. Comparisons of lake sturgeon larvae gut microbial community composition at the level of phyla indicated that three major phyla dominated more than 65% of total community abundance across all fish samples . One exception was WB larvae exposed to salt (mean 58%) and WC fish exposed to peroxide (mean 50%) that were relatively low compared to other treatments  had a lower percentage of Firmicutes (mean range from 51–66%). Proteobacteria relative abundance was likewise relatively uniform across treatments  with the exception of WB fish that were treated with chloramine-T, CT (6%). Actinobacteria were present at 1% in fish that were not exposed to any chemotherapeutant (control) and only in fish from HA and WC origin groups. At the genus level, Firmicutes were represented by two genera, Clostridium_sensu_stricto & unclassified genera from family Clostridiaceae. We found that Clostridium_sensu_stricto were the most dominant genus  for all fish of hatchery origin (except for HA fish exposed to peroxide), whereas all fish of wild origin had unclassified taxa from Clostridiaceae family (mean range: 29–62%) as the most abundant genus across any treatment  and WC control fish (mean 1.4%).The relative abundance of the most dominant phylum, eatments a. When creatment b. Generaeatments b. The onp > 0.05). Statistical analyses based on the generalized linear model (GLM) indicated that gut communities of individuals exposed to certain treatments  had significantly different levels of taxa richness, but not on the inverse Simpson indices  ordination of BC dissimilarities in microbial taxonomic composition of gut communities was performed to visualize community compositional relationships among larval gut samples associated with fish from different egg origin and exposed to different chemotherapeutant treatments. Four NMDS plots were generated, including To quantitatively test for gut community compositional differences among chemotherapeutant treatment and origins, PERMANOVA was performed. Comparisons of microbial OTU beta diversity across samples from the controlled groups indicated that gut microbial communities from control groups were not significantly influenced by the egg origin . Subsequp = 0.012). However, the effect of chemotherapeutant treatment was not evident between fish from eggs collected in different regions of the stream , although a significant interaction was observed between origin group and treatment . Chemotherapeutant treatments had significant effects on larval gut microbiomes between individuals from different hatchery families  as indicated by PERMANOVA test results  and Methylocystis (Phylum Proteobacteria). Both genera were present in high abundance in the guts of fish exposed to the peroxide treatment, and for genus Clostridium_XVIII. The taxa were also abundant in the guts of fish from the salt treatment  in high abundance, while fish exposed to the salt treatment had Peptoniphlus and Luteimonas that were in higher abundance compared to individuals from other treatments  to other chemotherapeutant treatment groups . LEfSe analyses performed with fish from the wild group detected two differentially abundant taxa associated with genus ents see c.Understanding interactions between microbes and the host surfaces they colonize is important to aquatic animal health and aquacultural production ,35. PoteIn this study, we found little evidence for the influence of commonly used chemotherapeutant treatments applied topically in water baths to larval lake sturgeon prophylactically on gut microbiome composition. Data did indicate greater influence of microbial founder effects (hatchery vs. wild stream origin), which may be explained by exposure to environmental sources during earlier life stages or influences of genetic effects ,74. ResuAll chemotherapeutants used in our study are commonly used for the treatment of external pathogens rather than orally administered to fish. In fish aquaculture, prophylactic treatments are widely used to control pathogenic bacteria disease outbreaks that commonly occur in hatcheries during vulnerable early life stages. Chloramine-T and peroxide are widely used to control and eliminate infection associated with flavobacteriosis . OverallThere are several potential explanations for the comparatively small effects of chemotherapeutant treatments on larval gut microbial communities. One explanation is that the externally administered treatment did not enter the digestive tract in significant enough concentrations or duration to alter the gut community. When larval fish are provided chemotherapeutants prior to feeding, rather than during feeding, microbial compositional stasis suggested that the chemicals may not enter the gastrointestinal tract. Alternatively, the effect of the treatment may not have been evident due to the short treatment duration (15–60 min bath immersion) and weekly periodicity of chemotherapeutant treatments. Exposure to chemotherapeutants, consistent with our methodology, may not have been of sufficient concentration to result in quantifiable changes in gut community composition. In addition, fish were returned into their tank partition after treatments, and that may have allowed rapid recolonization of gut microbiota from the surrounding water. Further, chemotherapeutant treatments were administered at seven-day intervals, potentially allowing community recovery. The microbial communities may have exhibited resiliency to chemotherapeutant treatment; returning to a similar compositional state during the several day period between the timing of treatment and sampling for gut interrogation. Further studies are warranted to quantify the amount of any compound entering the gut during the treatment period to ascertain causal relationships.Thymus vulgaris essential oil (TVEO) on microbiota composition, compared with a control diet without TVEO over a 5 week period. Their study indicated high similarities between gut microbiota in treated and non-treated fish, and TVEO induced negligible changes in gut microbiota profiles. Essential oils include volatile liquid fractions produced by plants that contain the substances usually responsible for defenses against pathogens and pests due to their antibacterial, antiviral, antifungal, and insecticidal activities [In the LEfSe analyses, three out of thousands of microbial taxa appeared to be tied to differences between untreated fish in a hatchery and the wild. After fish were exposed to chemical treatments, different taxa were reported to be differentially abundant. Those taxa, however, are not among the dominant taxa. It is unclear how treatment differentially affected the relative abundance of these taxa. Results could indicate that the gut microbiota were either resistant or exhibited resilience in community composition, where treatment-based changes were short-lived and communities rapidly returned to their original state . The comtivities . We concFirmicutes, Proteobacteria, and Actinobacteria, that dominated the lake sturgeon larval gut community across all samples  are Gram-negative bacteria. Many studies have shown that Gram-negative bacteria are resistant to commercially available antibiotics partly due to their thick cell wall structure compared to Gram-positive bacteria [Enterobacteriaceae include a group of bacteria known as extended-spectrum beta-lactamase (ESBL) Enterobacteriaceae that can confer resistance to antibiotics via production of the β-lactamase enzyme, which can inactivate certain β-lactam antibiotics [We detected three major phyla  samples . The mosbacteria ,78. Enteibiotics .Firmicutes that were detected in fish guts across all families and treatments was primarily represented by Unclassified Clostridiaceae1 and taxa Clostridium sensu stricto. Although Clostridia are Gram-positive, these bacteria have been identified as part of commensal gut microbiota that plays major roles in the maintenance of the gut homeostasis. Several features associated with Clostridium spp. could explain why this taxon can thrive in the gut and can likewise be resistant to prophylactic treatments administered in our study. In humans, Clostridium spp. are involved in defenses inside the intestinal microecosystem along with gut-associated lymphoid tissue (GALT), and confer resistance against pathogen infections. This taxon is thought to have immunological tolerance [Clostridium spp. exhibit the ability to form endospores, which offers this bacteria ecological advantages for survival under adverse conditions [Another major phylum, olerance . In addinditions ,81.Comprehensive studies on adverse effects of antibiotic use to the gut microbiomes were reported in other fish species ,37,39 anCarassius auratus gibelito) [Aeromonas. The results were consistent with findings from another study conducted to evaluate the effects of orally administered antibiotics to gibel carp [Relatively few studies have been conducted addressing the effects of chemotherapeutants administered topically in water baths on fish gut microbial communities as conducted in this study. Most studies have been conducted on salmonids or tilapia ,45,75 anibelito) , and havibelito)  reportedbel carp . ImportaA prerequisite for developing a strategy for microbial pathogen control is a knowledge of resident aquatic microflora associated with fish larvae, and how interactions between larvae and microflora occur. De Schryver & Vadstein  suggesteFish produced from wild eggs show greater community diversity compared to artificially produced fish in the hatchery b. Thus, In fishes, microbial binding to host cell surfaces is often mediated through the interactions of bacterial carbohydrate binding proteins (lectins) with host cell surface carbohydrates ,85. StreSeveral studies of gut microbiota in fish with different genetic backgrounds have documented that host genotype (broadly defined) may contribute to compositional heterogeneity among individuals in fish gut microbiota, at least to some extent. Abdul Razak et al.  studied Coregonus spp.) species pairs and their reciprocal hybrids were reared in captivity under a controlled environment. Analyses revealed significant effects of the host genetic background on the taxonomic composition of the transient microbiota. Navarrete et al. [Onchorhynchus mykiss). Full-sibling fish from four non-related families were fed two diet regimes in comparison to the control group. Results showed that some relative abundance of several bacterial taxa differed among trout families, indicating that the host genotypes may influence gut microbiota composition. In addition, the authors reported that the effect of diet on microbiota composition was dependent on the trout family. Studies on other organisms, such as chickens, also showed that under a common diet and husbandry practices, gut microbiota composition differed between two lines  [Another study  demonstre et al.  assessedght, LW) . Findingght, LW)  indicateFindings in this study detail observed differences in microbial founding sources  and chemotherapeutic treatments to developing microbial communities during early ontogenetic stages. These results provide an insight into the consequences of prophylactic treatments and host-microbe interactions. Our study serves as a baseline providing information on the indirect effects of chemotherapeutant intervention that could either positively or negatively affect the normal gut microbiota. Results of minor effects associated with use of chemotherapeutants prophylactically suggest that topical use at the ontogenetic stage and concentration used may not have negative indirect effects on resident gut microbial communities. Thought should be given to the selection of locations to collect gametes to bring into culture. Future work could profitably focus on identifying microbial taxa that colonize the external surfaces of the fish  to see how external treatments impact the colonization of external microbes. Further studies are also warranted that would compare the effects of treatments when administered following pathogen infection.