By utilizing high-throughput technologies, precision medicine is being developed as a preventative, diagnostic and treatment tool to combat complex human diseases. It is therefore necessary to investigate how to integrate these multi-scale ‘omics datasets to distinguish the novel individual-specific disease causes from conventional cohort-common disease causes. Currently, machine learning plays an important role in biological and biomedical research, especially in the analysis of big ‘omics data. This Research Topic focuses on the application of wet ‘omics technology and dry machine learning approaches together to further develop precision medicine.Liu, R. et al. proposed a single-sample-based hidden Markov model approach to detect the dynamical differences between a normal and a pre-disease states, to detect the immediately upcoming critical transition from the pre-disease state. Lee et al. implemented a deep learning-based python package for multimodal longitudinal data integration, especially the numerical data including time series and non-time series data. Yu et al. implemented an adjusted individual-specific edge-network analysis (iENA) method when a limited number of samples from one individual are available, and made a proof-of-concept study on individual-specific disease classification based on microbiota compositional dynamics.Chen et al. analyzed the miRNA expression profiles in whole plasma, Extracellular Vesicle (EV) and EV-free plasma of lung cancer patients and identified several discriminative miRNAs and classification rules as potential non-invasive biomarkers by Monte-Carlo feature selection method and Repeated Incremental Pruning to Produce Error Reduction method. Liu, Z. et al. conducted a genome-wide analysis of allele-specific expression (ASE) in colorectal cancer patients, providing a systematic understanding of how ASE is implicated in both tumor and normal tissues. Hu et al. used RNA sequencing data to identify and quantify the circRNAs in atrial fibrillation (AF) by bioinformatics analysis and characterized their potential functions through the competing endogenous RNA network and protein-protein interaction network. Shi, X. et al. screened a cohort of Total anomalous pulmonary venous connection cases and healthy controls for rare copy number variants by whole exome sequencing, providing candidate genes associated with rare congenital birth defect. Wu et al. performed whole exome sequencing on seven members of an HSCR family, making a first report on the in-frameshift variant p.Phe147del in RET responsible for heritable HSCR. Xie et al. investigated rare Copy number variants (CNVs) in a recruited cohort of unrelated patients with pulmonary atresia and a population-matched control cohort of healthy children by whole-exome sequencing, helping elucidate critical disease genes and new insights of pathogenesis. Meng et al. made a brief research report on the driver gene mutations in Chinese patients with non-small cell lung cancer by target sequencing and Hotspot3D computational approach together.Ho et al. provided a review of polygenic risk scoring and machine learning in complex disease risk prediction with tissue-specific targets, expecting their power to manage complex diseases for customized preventive interventions. Li et al. identified target genes at Juvenile idiopathic arthritis risk loci in neutrophils by an integrated multi-omics approach, constructing a protein-protein interaction network on the basis of a machine learning approach. Dai et al. applied the mega-analysis of Odds Ratio (MegaOR) method to prioritize candidate genes of Crohn's Disease, based on a comprehensive collected multi-dimensional data. Wang, C.H. et al. detected differentially expressed lncRNAs and mRNAs in atherosclerosis by analyzing public datasets with the weighted gene co-expression network analysis, and this bioinformatics study would provide potential novel therapeutic and prognostic targets for atherosclerosis. Jiang, S. et al. collected and profiled the circRNA expressions of heart tissues from Atrial fibrillation patients and healthy controls, providing new insights of the circRNA roles in AF with highly potential interaction mechanisms among circRNAs, microRNAs, and mRNAs.Gu et al. reused the Surveillance, Epidemiology, and End Results registry database to conduct stratification analyses, univariable and multivariable analyses, indicating surgery is an important component of multidisciplinary treatment and sublober resection is not inferior to lobectomy for the specific patients. Zhang, J. et al. exploited the largest crohn's disease dataset and ulcerative colitis dataset by a two-step approach, exhaustively searching for epistasis with dense markers and exploiting marker dependencies. Du et al. analyzed the genome-wide splicing data in 16 cancer types with normal samples by a network-based and modularized approach and captured the pan-cancer splicing and modularized perturbation, which support the dominant patterns of cancer-associated splicing. Zhao et al. assessed the prognostic value of Apolipoprotein E and explored the potential relationship with tumor progression in colorectal cancer (CRC), by collecting the microarray data from the Gene Expression Omnibus and exploring the gene with prognostic significance from the TCGA database. Tang et al. proposed an effective data integration framework HCI (High-order Correlation Integration) to realize high-dimensional data feature extraction with extensive flexibility and applicability on sample clustering with RNA-seq data on bulk and single-cell levels. Chang et al. identified new susceptibility genes and causal sub-networks in schizophrenia by an integrated network-based approach, and reported the N-methyl-D-aspartate receptor interactome highly targeted by multiple types of genetic risk factors. Wang and Liu recognized potential diagnostic biomarkers of Alzheimer's disease by integrating gene expression profiles from six brain regions in a machine-learning manner and validating marker genes in multiple cross-validations and functional enrichment analyses. Xu et al. provided an effective way for the annotation of nuclear non-coding and mitochondrial genes and the identification of new steady RNAs, making a pan RNA-seq analysis to suggest the ubiquitous existence of both 5' and 3' end small RNAs.Yang et al. presented a new pathogen detection and strain typing method UltraStrain for Salmonella enterica based on whole genome sequencing data, which includes a noise filtering step, a strains identification step on the basis of statistical learning, and a final refinement step. Tan et al. conducted comprehensive and systematic experiments, including in vitro genetic assessments and an in vivo acute toxicity study, aiming to study safety issues associated with Bacteroides ovatus ELH-B2. Qiu et al. set up an in-silico model emerging or re-emerging dengue virus (DENV) based on possible antigenicity-dominant positions of envelope (E) protein, so that, the DENV serotyping may be re-considered antigenetically rather than genetically. Zhang, B. et al. collected and re-analyzed the published fecal 16S rDNA sequencing datasets to identify biomarkers to classify and predict colorectal tumors by random forest method, and the trained random forest model has good AUC performance for CRC when combined all samples, although the predication performed poorly for advance adenoma and adenoma.Luo et al. proposed a manifold learning-based method to predict disease-gene associations by assuming that the geodesic distance of related disease-gene pairs should be shorter than that of non-associated disease-gene pairs. Tkachev et al. proposed a heuristic technique termed FLOating Window Projective Separator (FloWPS) for data trimming with SVM and applied it for personalized predictions based on molecular data. Wang, W. et al. developed a new multiple-instance leaning algorithm derived from AdaBoost and accessed this algorithm on annotating proteins that bind DNA and RNA. Xiao et al. proposed a method called BPLLDA to predict lncRNA-disease associations from a heterogeneous lncRNA-disease association network assuming the association paths on network with fixed lengths. Zou et al. used decision tree, random forest and neural network to predict diabetes mellitus by the hospital physical examination data, and the best prediction could be achieved by random forest after dimensionality reduction by principal component analysis and minimum redundancy maximum relevance.Guo et al. proposed a new approach SGL-LMM for mining multivariate associations of quantitative traits by combining sparse group lasso and linear mixed model together, which can consider confounding effects and groups of SNPs simultaneously. Zhang, W. et al. developed a new calling method for differentially expressed genes as DECtp by integrating tumor purity information into a generalized least square procedure and a follow-up Wald test. Cheng et al. utilized a Mendelian randomization (MR) to test the influence of body mass index (BMI) on the risk of T2DM based on GWAS data, validating the causal effect of high BMI on the risk of T2DM. Feng et al. utilized one analysis procedure of feature selection and classification on both transcriptomes and methylomes cancer data, suggesting age should be an essential factor rather than confounding factor in the training and optimization of disease diagnosis model.Qin et al. developed a new joint gene set analysis statistical framework, aiming to improve the power of identifying enriched gene sets by integrating multiple similar disease datasets when the sample size is limited. Shi, Q. et al. proposed a new computational framework of “Multi-view Subspace Clustering Analysis” to capture the underlying heterogeneity of samples from multiple data types, by first measuring the local similarities of samples in the same subspace and then extracting the global consensus sample patterns. Jiang, P. et al. developed a new variants mining algorithm based on trio-based sequencing data, and applied this method on a Ventricular septal defect (VSD) trio and identified several genes and lncRNA highly related to VSD.Finally, we sincerely thank the reviewers for their great efforts to ensure the high quality of all contributing articles, and we hope this Research Topic can attract wide attention in these topics of precision medicine based on machine learning and omics data.TZ drafted the manuscript. TZ, TH, and CL revised the manuscript.This study was supported by the National Natural Science Foundation of China (11871456), the Shanghai Municipal Science and Technology Major Project (2017SHZDZX01), and the Natural Science Foundation of Shanghai (17ZR1446100).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In this review, we discuss the prevalence, molecular mechanisms, and functional evidence for androgen-regulated prostate cancer fusion genes and transcripts. We also discuss the clinical relevance of especially the most common prostate cancer fusion gene TMPRSS2-ERG, as well as present open questions of prostate cancer fusions requiring further investigation.Androgens are steroid hormones governing the male reproductive development and function. As such, androgens and the key mediator of their effects, androgen receptor (AR), have a leading role in many diseases. Prostate cancer is a major disease where AR and its transcription factor function affect a significant number of patients worldwide. While disease-related AR-driven transcriptional programs are connected to the presence and activity of the receptor itself, also novel modes of transcriptional regulation by androgens are exploited by cancer cells. One of the most intriguing and ingenious mechanisms is to bring previously unconnected genes under the control of AR. Most often this occurs through genetic rearrangements resulting in fusion genes where an androgen-regulated promoter area is combined to a protein-coding area of a previously androgen-unaffected gene. These gene fusions are distinctly frequent in prostate cancer compared to other common solid tumors, a phenomenon still requiring an explanation. Interestingly, also another mode of connecting androgen regulation to a previously unaffected gene product exists via transcriptional read-through mechanisms. Furthermore, androgen regulation of fusion genes and transcripts is not linked to only protein-coding genes. Pseudogenes and non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) can also be affected by androgens and  Androgens are steroid hormones governing the development of male reproductive tract organs and secondary male sex characteristics, as well as functioning in the regulation of muscle mass, fat deposition, and function of steroid hormone-sensitive neurons , also referred to as prostein, as a 5′ partner . The KLK4-KLKP1 fusion is formed either by a trans-splicing mechanism or an in-frame fusion due to a microdeletion, leading to the fusion of the first two exons of KLK4 with exon 4 and 5 of KLKP1. The resulting chimeric sequence predicts a 164–amino acid protein, of which the latter third is derived from KLKP1, leading to a conversion of the non-coding pseudogene to a protein-coding gene. Utilizing cell culture and chicken chorioallantoic membrane (CAM) assay, the expression of KLK4-KLKP1 fusion transcript was shown to affect cell proliferation, cell invasion, intravasation, and tumor formation  in prostate cancer. LncRNAs are >200 bp long RNAs that do not encode for protein end-products. They are known to play important roles in the regulation of gene expression and to be dysregulated in several types of human malignancies, including prostate cancer  was shown to be strongly correlated with ERG expression in ERG-positive primary tumors, as well as CRPCs  developed prostatic adenocarcinoma, whereas Pten+/− mice only showed HGPIN lesions. Moreover, two genes involved in promoting cell migration and invasion (CXCR4 and ADAMTS1) were found to be upregulated in the context of ERG overexpression , showed a significant reduction in tumorigenicity, concomitant reduction in the expression of the oncogene C-MYC and upregulation of prostate epithelial differentiation genes KLK3 and SLC45A3  in LNCaP and VCaP cells. The results revealed that ERG and AR can co-occupy the same target genes and ERG functions as a repressor of AR-driven lineage-specific differentiation program. ERG also directly regulates the expression of the histone methyltransferase EZH2, by binding to its promoter and activating EZH2-mediated cell de-differentiation program  transcriptional program, whereas ETV1 was found to upregulate genes involved in AR signaling and cooperates in its activation.Carver and colleagues also showed that in vitro and in vivo and pointed to a role of the ETV1 transcriptional program in the development of more aggressive disease and poorer clinical outcome . These authors, in contrast to what reported by Tomlins and colleagues  is a direct target of ERG in VCaP cells and that PAI-1 inhibited the invasion of VCaP cells  treatment of VCaP and LNCaP cells showed increased expression of both ERG and CXCR4 in VCaP, but not LNCaP, suggesting that, indeed, the androgen-mediated ERG overexpression caused by the TMPRSS2:ERG fusion drives CXCR4 expression in VCaP cells, confirmed by the lack of CXCR4 induction when siERG-VCaP cells were treated with R1881. Androgen-induced CXCR4 overexpression was also shown to increase invasiveness of VCaP cells . Moreover, ERG overexpression was shown to activate the Wnt signaling pathway via increased expression of the Wnt receptor FZD4  and upregulation of the EMT mediator integrin-linked kinase (ILK) and its downstream effectors Snail and LEF-1  lesions  and TMPRSS2:ERG has been shown to improve the sensitivity for prostate cancer diagnosis , derived from PC-3, to assess the role of the TMPRSS2:ERG fusion transcript in the formation of bone metastases. They used PC3c clones that overexpress the most common TMPRSS2:ERG transcript variant (TMPRSS2 exon 1 and ERG exon 4) at variable levels and also including the 72 bp exon 11 previously shown to be associated with more advanced stages of the disease . These genes were confirmed to be directly regulated by ERG overexpression. Knock-down experiments confirmed that PLXNA2 is directly involved in the increased migration and invasion capabilities of prostate cancer cells  and Endothelin-1 (ET-1), responsible for improved acquisition of a bone-like phenotype in cancer cells (osteomimicry), helping the cancer cells survive in the bone microenvironment  in separated foci of prostate cancers revealed interfocal heterogeneity and intrafocal homogeneity, indicating that individual foci are the result of clonal expansion (Mehra et al., Prostate cancer is a heterogeneous disease which very often harbors multiple cancer foci within the same gland. It is well-established that different foci are histologically and molecularly heterogeneous, suggesting that they are clonally independent (Wise et al., SPINK1 had been reported in a subset of ETS-negative prostate cancer samples exclusively (Tomlins et al., ERG and SPINK1 overexpression were mutually exclusive in all tumor foci (Fontugne et al., ERG and SPINK1 overexpression within different regions of either the same tumor focus or different foci, but not in the same tumor cells (Lu et al., CHD1 and MAP3K7, and mutations in SPOP, FOXA1, and IDH1 were also found to be associated with the ETS-fusion negative subtype (Liu et al., SKIL fusions described in Annala et al. (ERG. For example, correlative analysis with other ETS gene fusions showed that KLK4-KLKP1 expression is associated with ERG but not ETV1, ETV4, or ETV5 (Chakravarthi et al., Profiling studies of fusion genes in multifocal disease are also important to evaluate co-occurrence of these alterations. Other FISH analyses of recurrent ETS gene rearrangements in multifocal prostates showed complex patterns of alterations, with both rearranged and un-rearranged foci and multiple ETS rearrangements within the same gland (Clark et al., a et al.  and the a et al.  were idea et al. , the ERGTumor-specific gene fusions can serve as diagnostic biomarkers or help define molecular subtypes of tumors. For example, gene fusions involving ETS transcription factors have been utilized in diagnostic applications, such as with detection of TMPRSS2-ERG fusion transcripts in urine samples or CTCs from patients or ERG protein by immunostaining in biopsies [reviewed recently in Kumar-Sinha et al. , Berg 2, and Garin silico methods, demonstrating that a small molecule targeting the ERG-ETS domain suppressed its transcriptional activity and reverse transformed the characteristics of prostate cancers aberrantly expressing ERG (Butler et al., in vivo and in vitro, impaired the expression of genes enriched in ERG and prostate cancer relevant gene signatures, and inhibited growth of ERG-positive tumors in mouse xenograft models (Wang et al., As the TMPRSS2-ERG fusion is the most common alteration in prostate cancer, molecular targeting of it has gained attraction as a potential therapeutic strategy. Recent examples include the work of Wang and colleagues, who identified a series of peptides that interact specifically with the DNA binding domain of ERG, leading to proteolytic degradation of the ERG protein, and attenuation of ERG-mediated transcription, chromatin recruitment, protein-protein interactions, cell invasion and proliferation, and tumor growth (Wang et al., TNIK as a potential therapeutic target in ERG-fusion gene positive prostate cancer (Lee et al., On the basis of the interaction of ERG and other ETS fusions with the DNA repair proteins PARP1 and DNA-PKc, use of PARP inhibitors has shown initial promise and is being tested in ETS fusion-positive prostate cancers [reviewed in Kumar-Sinha et al.  and PedeSLC45A3 with FGFR2 in which the SLC45A3 non-coding exon 1 is fused to the intact coding region of FGFR2 has been found from a brain metastasis of a prostate cancer patient (Wu et al., While the therapeutic targeting of transcription factor oncogenes remains challenging, tumors with fusions involving therapeutically targetable genes, most often kinases, often have the strongest implications in personalized treatment of cancer patients. Amongst prostate cancer fusion genes, especially the effects of androgen-regulated SLC45A3-BRAF and a non-androgen-regulated ESRP1-RAF1 are targetable. The effects of ectopic expression of these fusion genes were studied in RWPE benign immortalized prostate epithelial cells and resulted in increased proliferation, invasion and anchorage-independent growth, which were sensitive to RAF and MEK inhibitors (Palanisamy et al., in vivo environment and is thus valuable in developing new drugs and selecting appropriate treatment strategies for prostate cancer patients. In terms of prostate cancer fusion genes, the expression of ERG has been shown to be retained in the PDXs along with other molecular, histopathologic, and genomic characteristics (Palanisamy et al., Prostate cancer xenografts play a central role in pharmacological testing of potential drugs. The VCaP cell line, due to the TMPRSS2-ERG fusion gene it harbors, has been widely utilized in xenograft drug studies. For example, TMPRSS2-ERG harboring VCaP bone xenograft models were shown to better respond to enzalutamide treatment, suggesting that ERG expression status in tumors could help stratify patients for enzalutamide therapy (Semaan et al., de novo expression of a cancer driver protein, for some fusions the advantage seems not as straightforwardly explained nor convincingly supported by functional data. Especially, despite a lot of effort, the field has yet to pinpoint why and how TMPRSS2-ERG fusion is an early event in prostate cancer development, yet the most significant functions of it seem concentrated in the phase of metastatic disease. The PCAWG Consortium recently reported that, amongst their 3,540 fusion events identified in 1,188 pan-cancer samples studied, 82% were associated with specific genomic rearrangements (PCAWG Transcriptome Core Group et al., The frequent gene fusions in prostate cancer are a curiosity amongst solid tumors. Why and how this particular tumor type benefits so much from these rearrangements for them to be so frequent are still open questions. While the benefit with certain fusions may clearly result from de novo structures and functions, it is possible that also some of the other fusion transcripts may have non-coding functions yet to be discovered. This is supported by the notion that up to 20% of expressed prostate cancer fusion transcripts are non-canonical, with one or both transcripts in antisense orientation (Vellichirammal et al., The case of SLC45A3-ELK4 fusion has proven that it is possible for a chimeric RNA to function as a ncRNA, even though the 3′ fusion partner is initially protein-coding. Considering that chimeric transcripts may have acquired MS and LL wrote the manuscript. SK designed the figures. MS, LL, and SK edited the manuscript. All authors have approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Circulating tumor cells (CTCs) are shed into the bloodstream from primary tumors and metastatic lesions and provide significant information about tumor progression and metastasis. CTCs contribute to tumor metastasis through the epithelial-to-mesenchymal transition (EMT). CTC clusters and stem-like phenotypes lead to a more aggressive and metastatic potential. CTCs retain the heterogeneity and imitate the nature of corresponding primary tumors. Therefore, it is important to use single-cell based analysis to obtain information on tumor heterogeneity and biology. CTCs are also good candidates for building preclinical models  for drug screening, disease modeling, genome editing, tumor immunity research, and organ-like biobank establishment. In this article, we summarize the current CTC capture technology, dissect the phenotypes associated with CTC metastasis, and review the progress in single-cell based analysis and preclinical modeling of the pattern and kinetics of CTCs. In particular, we discuss the use of CTCs to assess the progression of hepatocellular carcinoma (HCC). Circulating tumor cells (CTCs), which carry valuable tumor information, arise from the hematogenous diffusion of metastatic tumors in vitro and in vivo CTC culture approaches have provided significant insights into tumor development and metastasis With emerging technological developments, CTC research is not limited to enumeration. Different CTC phenotypes have been analyzed, including the epithelial, mesenchymal, and stem cell types and CTC clusters, which were associated with distinct kinetics and functions Hepatocellular carcinoma (HCC) is the seventh most common cancer and the second leading cause of cancer-related deaths worldwide In recent years, a series of “liquid biopsy” techniques have been developed to evaluate HCC biomarkers  Figure 1.CTCs, first discovered by Thomas Ashworth 150 years ago, can be obtained multiple times from tumor patients without an invasive approach. The recent development of new and powerful technologies has remarkably facilitated the precise capture of CTCs et al.et al. developed a novel Labyrinth microfluidic device, offering unique features over other inertial devices to efficiently isolate CTCs from the peripheral blood of HCC patients CTCs from HCC patients are primarily isolated based on their unique biological or physical properties. The biological methods include immune magnetic bead capture and nucleic acid aptamer capture. Court et al., “CTC-iChip”, an inertial focusing-enhanced microfluidic CTC capture platform, is capable of isolating CTCs with or without tumour membrane epitopes et al. proposed an on‐chip strategy combining multiplex SERS nano-vectors and multivariate analysis for in situ profiling of circulating tumor cell phenotypes on microfluidic chips et al. reported a magnetically assisted surface‐enhanced Raman scattering (SERS) biosensor for HCC CTC detection et al.Currently, nanomaterials and microfluidic chips are widely used for CTC capture. According to the study by Ozkumur et al. showed that tumor cells undergo gradual or complete EMT  that is associated with slow proliferation, loss of epithelial cell adhesion molecule EpCAM expression, and increased migration et al. showed that mixed CTCs might be vital for intrahepatic metastasis, and mesenchymal CTCs could predict extrahepatic metastasis et al. revealed that total CTC count and the proportion of M-CTCs are negative factors for postoperative HCC recurrence et al. mapped the distribution and characterized the biological features of HCC CTCs along the transportation route EMT is a process that initiates metastasis et al. that CTC clusters originate from oligoclonal tumor cell groupings rather than cell aggregation in the blood vessels et al. prospectively measured CTCs at five key vascular sites in patients with localized HCC  et al.Besides EMT, CTC clusters have been proposed to indicate the initiation of tumor metastasis et al. showed that ICAM-1 is a marker of HCC stem cells. They quantified circulating CD45-ICAM-1+ tumor cells from 60 HCC patients using flow cytometry and found that higher frequencies of circulating CD45-ICAM-1+ cells in HCC patients correlated with more aggressive tumor behavior and worse clinical outcomes et al. found that EpCAM+ CTCs show stem cell characteristics and indicate poor prognosis of HCC after curative resection It has been more than a century since Cohnheim proposed the “embryonic theory” of cancer. The cancer stem cell (CSC) hypothesis argues that cancers arise from a subset of malignant cells that possess stem cell characteristics et al.et al.et al.In animal models, CD90+CXCR4+ HCC cells could be CTSCs, as reported by Zhu et al. systematically investigated the clinical significance of diverse subtypes of CTCs and showed that the presence of EpCAM+ multiploid CTSCs (cut-off: ≥1 cell in 6 ml of blood), EpCAM- small triploid CTCs (≥5 cells), CTM (≥1), and increased triploid CTCs, were highly relevant for poor prognosis Although the tumor metastasis mechanism remains unclear Figure 2.Single-cell sequencing technology has been a major breakthrough in sequencing history. CTCs can be processed and analyzed as single cells and then subjected to single-cell sequencing. Given the considerable heterogeneity of CTCs, it is essential to analyze the molecular and genetic characteristics of single CTCs et al. developed a new technology combining image flow cytometry and high-density single-cell mRNA sequencing to identify CTCs in HCC patients et al. collected blood from the peripheral vein, peripheral artery, hepatic vein, inferior hepatic vena cava (IHIVC) and portal vein (PoV) before tumor resection. They analyzed the EMT phenotypes of CTCs using the 4-channel immunofluorescence CellSearch assay and microflow quantitative RT-PCR. The study demonstrated the heterogeneity of EMT status in CTCs across different vascular compartments With advances in the next-generation sequencing (NGS) and single-cell sequencing (SCS) technology, it is possible to obtain the complete genomes of CTCs and compare them with the corresponding primary and metastatic tumors. Several clinically relevant genomic alterations have been discovered, such as single nucleotide variations (SNV), microsatellite instability, and copy-number variations, providing valuable information for the companion diagnostics et al. established a CTC line using the peripheral blood from a mouse HCC model Epigenetic events, including histone modification and DNA base modifications (such as methylation and hydroxy-methylation), also contribute to tumor cell heterogeneity. ChIP-seq (Illumina) is used for studying histone modifications at the single-cell level et al. developed a microchip-assisted single-cell proteomic method for profiling CTC surface antigens facilitating the phenotypic and functional analysis of single CTCs Single-cell protein analysis identifies the heterogeneity of seemingly similar tumor cells, providing critical insights into the mechanisms underlying tumor heterogeneity et al. isolated CTCs from 31 patients and cultured them into spheroids Although the techniques mentioned above have provided abundant information about CTCs, their functions still need to be validated in preclinical models. CTC-based preclinical models include 2D cultures, CTC spheroids, CTC-derived organoids, and xenografts in vivo model in which CTCs enriched from patient blood are injected into immunocompromised mice to generate tumors and expand the number of original tumor cells et al. had developed a xenograft assay and shown that primary human luminal breast cancer CTCs contain metastasis-initiating cells (MICs) that cause metastasis in the bone, lung, and liver. These MIC-containing CTCs expressed EpCAM, CD44, CD47, and MET +CD44+CD47+MET+ CTCs correlated with increased metastatic sites and a poor survival rate. Recently, Vishnoi et al. established a novel triple- negative breast cancer (TNBC) liver metastasis‐specific CDX model that selectively recapitulates CTC biology for four sequential generations of mice CTC-derived xenograft (CDX) is an et al. was a significant advance et al.in situ capture method for ex vivo CTC expansion in a 3D co-culture model simulating tumor microenvironment. They successfully expanded CTCs from 14 out of 19 early-stage lung cancer patients and revealed several mutations, including TP53 in both cultured CTCs and primary lung cancer. This strategy sets the stage to further characterize CTC biology and metastatic factors in patients with early-stage cancers. Although CDOs have not been established from HCC patients yet, we propose a strategy for analyzing HCC CDOs .The establishment of CDX models is time-consuming and inapplicable to large-scale drug screening. CDO is the alternative that allows quick molecular analysis and high-throughput drug screening. An organoid is a special 3D culture model harboring a semisolid extracellular matrix supplemented with growth factors for tissues et al. used an advanced CanPatrol CTC-enrichment technique and in situ hybridization to sort and classify CTCs from blood samples and found 90.18% of HCC patients to be CTC positive, even at the early stage of HCC  et al. implicated CTCs in tumor staging There is considerable evidence for a crucial role of CTCs as initiators of metastasis, suggesting CTCs as a biomarker for the early detection of HCC. In previous CTC studies, early detection of HCC was mainly based on the assessment of CTC numbers, showing a significant positive correlation between the CTC number and the standard Barcelona Clinic Liver Cancer (BCLC) stage as well as the serum AFP level et al.et al. also reported the association of increased postoperative CTC numbers with worse prognosis of HCC patients et al., CTCs were classified using EMT markers and the presence of mesenchymal CTCs, together with mixed phenotypic and epithelial CTCs predicted the shortest relapse-free survival In patients diagnosed with HCC, CTCs not only contribute to neoplasm staging but are also useful for prognosis et al. used CanPatrol™ system to count CTCs 1 day prior to and 30 days after surgical excision of HCC et al. to detect the preoperative levels of EpCAMmRNA+ CTCs and CD4+CD25+Foxp3+ Treg cells in 49 HCC patients. The data showed that elevated CTC/Treg levels implied a higher risk of postoperative recurrence Since CTC numbers may change after anti-tumor treatment, they could be used for predicting or evaluating therapeutic efficacy before or after treatments. Ye et al. presented a novel system to provide quantitative information of sorafenib-related targets through simultaneously detecting phosphorylated ERK (pERK) and Akt (pAkt) in HCC CTCs Mutation profiles and drug-resistant molecular expression profiles have been widely identified in many solid tumors. In this context, CTC analysis allows the determination of therapeutic targets and resistance mechanisms to cancer therapies at the DNA, RNA, and protein levels and has great potential to identify the patient population most likely to respond to specific treatments. Li et al. that evaluation of PD-L1+ CTCs discriminated between HCC patients with early-stage and advanced/metastatic disease Table Immune checkpoint inhibitors have launched a new era in immunotherapy, with exceptional long-term remissions in some patients across diverse tumor entities. However, only a few patients respond to this modality, with many experiencing severe side effects Supplementary Figure.CTCs offer valuable diagnostic and therapeutic information on HCC, although some challenges still exist in their identification, quantification, and/or characterization. Currently, new CTC capture technologies are emerging, while the CellSearch system is still the only FDA-approved CTC detection and quantification method. So, we urgently need novel and certified tools for quick isolation and characterization of CTCs. There are various sources of CTCs including primary tumors and metastatic lesions. Identifying of the sources of captured CTCs is beneficial for a more in-depth analysis. For a comprehensive understanding of CTC biology, multiple omic disciplines should be combined for single-cell analysis. With the development of CDO approaches, we can co-culture CTCs with immune cells to simulate the tumor microenvironment to monitor tumor progression and associated molecular events. Furthermore, as part of liquid biopsy, CTC testing should be combined with other liquid biopsies such as analysis of ctDNA and exosomes to promote the efficiency of clinical CTC tests. Ongoing and future research on CTC capture technology, molecular profiling, sing-cell analysis, and preclinical models are expected to considerably improve CTC testing for early diagnosis, efficacious treatment, and effective prognostic management of HCC. The overview of CTC research is showed in the Supplementary figures and tables.Click here for additional data file.


Tau is a microtubule-associated protein (MAPT) that is highly expressed in neurons and implicated in several cellular processes. Tau misfolding and self-aggregation give rise to proteinaceous deposits known as neuro-fibrillary tangles. Tau tangles play a key role in the genesis of a group of diseases commonly referred to as tauopathies; notably, these aggregates start to form decades before any clinical symptoms manifest. Advanced imaging methodologies have clarified important structural and functional aspects of tau and could have a role as diagnostic tools in clinical research. In the present review, recent progresses in tau imaging will be discussed. We will focus mainly on super-resolution imaging methods and the development of near-infrared fluorescent probes. Tauopathy is a general term referring to a group of disorders characterized by the accumulation of misfolded tau protein. Highly heterogeneous from a clinical perspective, tauopathies can be further divided into primary tauopathies (where tau is the leading cause of neurodegeneration) and secondary tauopathies (where a tauopathy is associated with other pathologies). Progressive supranuclear palsy (PSP), Pick’s disease (PiD), and fronto-temporal dementia (FTD) are examples of primary tauopathies while, Alzheimer’s disease (AD), Lewy’s body disorder (LBD), and Down’s syndrome (DS) belong to the second group  STED experiments, revealed that in FTD neurons, an aberrant microtubular organization was responsible for the deformation of the nuclear lamina , and [11C]PBB3. These compounds represented a “proof of concept” in the process of tau PET imaging and their properties have extensively been examined  in the whole brain; in addition, MAO-B correlated with glial fibrillary acid protein (GFAP) a marker for astrocytes, and therefore they concluded that [18F]THK5351 PET could be useful to evaluate tau-associated neuroinflammatory states in AD rather than tau pathology. PET scanning using the tracer [18F]AV-1451 was performed on a 76-year-old female patient carrying the MAPT R406W mutation. This mutation leads to the presence of tau aggregates similar to those found in AD. Clinically, the patient presented a long history of cognitive deficits and behavioral abnormalities. Postmortem immunohistochemical staining for hyperphosphorylated tau protein showed a strong positive correlation between in vivo [18F]AV-1451 retention and the density of tau aggregates . In this study, no significant correlation was reported between in vivo PET and autoptic examination of tau deposits; therefore, the authors conclude that [18F]-AV-1451 may not be suited to detect tau aggregates in these non-AD tauopathies . Another big obstacle is represented by the heterogeneous structural organization of tau aggregates in AD and non-AD-related tauopathies. The need for dyes with better selectivity, affinity, and specificity is opening the door for the development of a second generation of tau tracers . In vitro experiments confirmed its ability to label intracellular tau aggregates; however, no experiments on mouse models of tauopathies nor on postmortem human AD tissues have been performed  with better fluorescence emission upon tau aggregates binding (λem = 650 nm) have been proposed  and a large Stokes shift (110 nm). When incubated with AD human brain slices, the probe 2e displayed a staining pattern that resembled that which was obtained with an antibody against ptau epitopes  experiments allowed a strong and stable signal from the brain of both JNPL3 and htau/PS1 mice to be detected. Very little signal was observed in control animals. Moreover, older mice from both genotypes showed higher signals compared with younger mice further suggesting the specificity of the scFv 235 antibody (Krishnaswamy et al., Several research groups are actively involved in developing affordable probes/methodologies that could be potentially used for the diagnosis of tau-based neurodegenerative disorders. A plethora of approaches using different chemical strategies have been proposed (Verwilst et al., in vitro aggregation of misfolded proteins in particular (Cosentino et al., in vitro and in vivo. Tau aggregates have recently been described in the retina of AD patients (Schön et al., Advanced imaging methodologies are providing valuable information about tau structure, interaction with proteins and organelles, localization, and mechanisms of self-aggregation. Far from being definitive, these techniques are still under active development as several limitations need to be overcome. A critical step for improvement is represented by protein labeling with fluorescent probes (Wang et al., All authors reviewed and discussed relevant literature, wrote sections, and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In this editorial, we briefly summarized the International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019) that was held on June 9–11, 2019 at Columbus, Ohio, USA. We further introduced the 19 research articles included in this supplement issue, covering four major areas, namely computational method development, genomics analysis, network-based analysis and biomarker prediction. The selected papers perform cutting edge computational research applied to a broad range of human diseases such as cancer, neural degenerative and chronic inflammatory disease. They also proposed solutions for fundamental medical genomics problems range from basic data processing and quality control to functional interpretation, biomarker and drug prediction, and database releasing. The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019) was co-hosted by the International Association for Intelligent Biology and Medicine (IAIBM) and the Department of Biomedical Informatics at The Ohio State University on June 9–11, 2019 in Columbus, OH. A total of 164 researchers attended the conference, of which 79 were faculty/staff and 84 were trainees. The conference included four keynote lectures, four eminent scholar talks, five tutorials and workshops, twelve concurrent regular scientific sessions, and one poster session. It covered a board range of topics, including but not limited to next-generation sequencing, single cell analyses, deep learning, metabolomics, genomics, and other omics research, systems biology, medical applications and translational research involving high-throughput data, computational methods and novel applications of computational tools, and others. Among 105 original manuscript submissions, 19 research articles of interests to computational method development and applications in medical genomics were selected for the ICIBM 2019 BMC Medical Genomics Supplement Issue after with careful peer reviews. The proposed computational methods and applications cover a broad range of biomedical topics and are innovative with significant biological and clinical implications. A more detailed summary of the conference arrangement, scientific programs, and achievements were published elsewhere [This supplement issue includes five papers that propose computational methods to  predict Li et al. developed a new computational method, namely SIMCCDA (Speedup Inductive Matrix Completion for CircRNA-8 Disease Associations prediction), which is the first work that apply the recommendation system based inductive matrix completion to predict circRNA-disease associations . The cirLi et al. developed a novel computational workflow for customized neoantigen prediction and selection . The worMostavi et al. conducted a novel application of convolutional neural network model for cancer type prediction by using gene expression data . Novel CCai et al. developed a new association test, namely weighted Adaptive Fisher (wAF) to test the association of common and rare SNVs and detect dense and sparse signals in GWAS . wAF is Foroughi pour et al. developed a new computational capability to conduct binary classification based on high dimensional SNP data . Binary Three genomics analysis are included in this supplement issue, two utilized network-assisted methods to explore new SNPs in multiple sclerosis and Cleft lip with/without cleft palate, while the other focused on somatic mutations in genetic regulatory elements in melanoma. Each of the two genomics data based study identified significant sets of biological and clinical associated genetic events.Zhang et al. explored the landscape of somatic synonymous mutations in genetic regulatory elements in melanoma . This stManuel et al. conducted a network-assisted search in two multiple sclerosis GWAS data sets to identify the gene networks that were associated with the disease . With apYan et al. conducted a integrative network-assisted GWAS study of the Cleft lip with/without cleft palate (CL/P) . By usinFour biological network based studies, including two differential co-expression analysis and two network based drug prediction, are included in this supplement issue. Two studies identified variations in co-expression networks through different disease stages of Alzheimer’s disease and chronic kidney disease, which can be potentially used as biomarkers of disease progression. Two novel network based drug prediction method was developed by predicting variations in signaling pathway activities in patient subgroups and applied to identify novel drug and targets in pancreatic and ovarian cancer.Upadhyaya et al. conducted a differential gene co-expression analysis of gene expression data collected from patients’ plasma samples of Alzheimer’s disease . The autnuclear SMAD2/3 signaling and signaling events mediated by focal adhesion kinase, 27 including Regulation of nuclear SMAD2/3 signaling. The study also identified a list of vanishing hub genes and disrupted correlations within and between key signaling pathways, on the pathophysiological mechanisms of CKD progression.Yu et al. conducted a differential co-expression analysis of the RNA-seq data of chronic kidney disease (CKD) collected from patients at different disease stages . Kidney Liu et al. conducted a network based study to identify possible drug targets in pancreatic ductal adenocarcinoma . A novelZhang et al. conducted an integrative network analysis to identify potential drug targets of ovarian cancer . In theiA substantial part of this supplement issue is composed by biomarker predictions, including seven works with utilizing  deep leaHuang et al. developed a novel auto-encoder based model, namely AECOX, to identify prognostic marker genes from cohort transcriptomics data . CompariLiu et al. developed a novel computational pipeline to predict colon cancer prognosis by using gene expression level of transcriptional factors . UnivariDong et al. developed a new computational pipeline to identify breast cancer patients’ prognosis associated transcriptional regulatory factors (TFs), by using estimated activity level of TFs . Data seSmerekanych et al. conducted a systematic identification of gene expression, pseudogene expression, miRNA expression, and pseudogene-gene interactions and clinical factors that were predictive to breast cancer patients’ prognosis . Based oAdnan et al. established a comparative evaluation of network features to predict the metastasis of breast cancer on data collected in 12 cohorts . The autZhang et al. conducted a pan-cancer study to demonstrate the clinical implication of class-3 semaphorins in the treatment of cancer . By compByun et al. conducted a study of the differential alternative splicing in HIV infected T cells . ApplicaICIBM conferences provide a friendly forum for researchers to present and publish cutting-edge biomedical studies. Stimulated by state-of-the-art biotechnologies, therapeutic strategies, biological hypotheses and interdisciplinary capabilities, computational scientists developed models to link biomedical data with biological hypothesis from different perspectives. Here, the 16 selected works illustrating innovative computational ideas or applications of new computational methods on important biomedical questions. Even though the high complexity of some models may limit their application in a broader domain and some observations still need further experimental validations, we anticipate some of these biomedical studies and computationally derived results can contribute in real clinical applications, as is discussed in this supplemental issue.


Oxidative stress plays an important role in the pathogenesis of several different neurodegenerative diseases (NDDs), such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease, amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) ,2. In paLin et al.  performeOther manuscripts reviewed the emerging role of oxidative stress-responsive proteins, such as sestrins, in various neurological diseases, protein DJ-1 in PD and mitofusin-2 (Mfn2) in AD. Chen et al.  reportedAmong neurodegenerative events, chronic inflammation can exacerbate the oxidative stress in the cells, leading to oxidation and damage of cellular components, increased inflammation and activation of neuronal death pathways . In thisAs previously highlighted, the identification and use of oxidative stress biomarkers in NDDs could be useful for the development of new drugs as well as for the early diagnosis and demonstration of drug efficacy in clinical studies. Padureanu et al.  evaluateAmong the research manuscripts of this Special Issue, some papers evaluated the antioxidant and anti-inflammatory effects of different molecules in several in vivo models of neurodegeneration. Hong et al.  evaluateIn conclusion, the manuscripts published in this Special Issue highlight recent advances in knowledge of the oxidative stress’s contribution to various NDDs as well as novel antioxidant strategies of neuroprotection for NDDs.


Recently, Ebmeyer and colleagues published a 28-day feeding study with six pyrrolizidine alkaloids in rats (Ebmeyer et al. Hepatotoxicity represents a major focus in current toxicological research (Jansen et al. Often risk evaluation is hampered by a lack of carefully performed subchronic or chronic animal studies with human relevant doses. Therefore, the present study of Ebmeyer et al. represents an important milestone in the current research on the hepatotoxicity of pyrrolizidine alkaloids.


Ficus elastica using transmission electron microscopy. As depicted in a model, an inner polysaccharide-rich layer and an outer cutin (or cutan)-rich layer may support the composite, heterogeneous concept of the leaf cuticle.Two distinct layers in terms of texture and electron density were observed in the leaf cuticle of  The cuticle represents the outermost surface structure of a variety of organisms such as plants and insects. As the interface between plants and their environment, the plant cuticle plays a number of roles mostly associated with protection against biotic and abiotic stresses including pathogen infection and water loss (Domínguez et al., Ficus elastica were fixed, dehydrated, and embedded in LR white resin (Kim, Leaves of the rubber tree sin Kim, . Energy-sin Kim, . Two difThe heterogeneous cuticle structure was strikingly similar to that of the model depicted by Heredia-Guerrero et al. . They pr


The ability to rapidly detect viable pathogens in food is important for public health and food safety reasons. Culture-based detection methods, the traditional means of demonstrating microbial viability, tend to be laborious, time consuming and slow to provide results. Several culture-independent methods to detect viable pathogens have been reported in recent years, including both nucleic acid–based (PCR combined with use of cell viability dyes or reverse-transcriptase PCR to detect messenger RNA) and phage-based  methods. Some of these newer methods, particularly phage-based methods, show promise in terms of speed, sensitivity of detection and cost compared with culture for food testing. This review provides an overview of these new approaches and their food testing applications, and discusses their current limitations and future prospects in relation to detection of viable pathogens in food.• Cultural methods may be ‘gold standard’ for assessing viability of pathogens, but they are too slow.• Nucleic acid–based methods offer speed of detection but not consistently proof of cell viability.• Phage-based methods appear to offer best alternative to culture for detecting viable pathogens. Salmonella spp., Campylobacter spp., Listeria monocytogenes, Staphylococcus aureus and pathogenic Escherichia coli are the main pathogens that cause the highest number of outbreaks linked to food sources , for example. Tests for foodborne pathogens have historically been culture-based, which is still considered the gold standard  methods.As stated earlier, culture-based methods are generally regarded as the ‘gold standard’ for microbiological analysis of food. Traditional culture relies on the ability of bacteria to grow and multiply on laboratory media and form visible colonies. These methods still represent the first choice for many food testing laboratories as they are sensitive, inexpensive, easy to use, and give either qualitative or quantitative information on the number and type of viable microorganisms present in the food samples Doyle . HoweverThere are essentially two culture-independent approaches that represent promising alternatives to culture-based approaches for detection of viable foodborne pathogens, namely nucleic acid–based and bacteriophage-based detection methods. The advantages and limitations of these culture-independent methods are summarised in Table Nucleic acid–based methods operate by detecting specific DNA or RNA sequences of the target pathogenic organism. Polymerase chain reaction, or PCR, is the most commonly used nucleic acid amplification method for detecting pathogenic microorganisms, and over the last two decades, many different advances on the original PCR protocol have been described  is considered a better indicator of cell viability than DNA, since this molecule is only present in metabolically active cells (Sheridan et al. The high specificity and natural affinity of bacteriophages, or simply phages, for their host cells make phage-based methods an attractive proposition. Bacteriophages can only replicate inside living cells, meaning that phage-based methods can be tests to demonstrate cell viability (Richter et al. . In this method samples are incubated with seed bacteriophages to start the lytic cycle. Just before the end of the latent period, a chemical virucide (McNerney et al. Salmonella Typhimurium and Staphylococcus aureus (Stewart et al. Salmonella Enteritidis and Escherichia coli 0157:H7 (Favrin et al. Listeria monocytogenes (Oliveira et al. Mycobacterium avium subsp. paratuberculosis (Foddai et al. Most phage-based tests employ lytic phages as lysing agents, and detection of the new progeny phages or intracellular material released from target bacterial cells provides the indication of cell viability. One of the simplest lytic phage-based tests is called the phage amplification assay or simply the plaque assay (Stewart et al. Listeria monocytogenes within 8 h (Stambach et al. Faster phage-based detection can be achieved by combining the lytic part of the plaque assay and an alternative end-point detection method, such as immunological (Stewart et al. A third type of lytic phage–based method to detect intracellular components released from bacteria also exists. After phage lysis, the quantity of released compounds is monitored through a bioluminescence assay using an enzyme and a substrate. The amount of light generated is proportional to the quantity of intracellular compound released and to the bacterial concentration originally present in samples. Examples of intracellular markers are adenosine-5 triphosphate or ATP (Griffiths More rapid and sensitive tests for detection of viable pathogens in food are continually being sought. Culture-based methods are becoming too laborious and time consuming to apply, and might have limited detection capability if pathogens in a VBNC state are present in food. Molecular tests, particularly mRNA-based tests, represent a potential solution for the rapid detection of living microorganisms. However, the perishable nature of mRNA still represents a barrier to the large-scale use of reverse transcriptase PCR for food testing purposes. A range of lytic phage–based methodologies have emerged over the last two decades, which are exhibiting high detection sensitivity for several foodborne pathogens in many different matrices including food and water. The combination of phage amplification and lysis with PCR/qPCR, immunoassay or enzyme assay endpoint detection approaches seems to be the most promising rapid alternative to cultural methods for detection of viable pathogens in food. Providing host cell metabolism is occurring, phage amplification will take place and pathogen cells will eventually burst to release measurable intracellular components such as ATP, enzymes, host DNA or progeny phages.


Irisin is a PGC-1α-dependent myokine that causes increased energy expenditure by driving the development of white adipose tissue into brown fat-like tissue. Exercise can improve irisin levels and lead to its release into the blood. In ischemic stroke, neurons are always sensitive to energy supply; after a series of pathophysiological processes, reactive oxygen species that are detrimental to cell survival via mitochondrial dysfunction are generated in large quantities. As a protein associated with exercise, irisin can alleviate brain injury in the pathogenesis of ischemic stroke. It is thought that irisin can upregulate the levels of brain-derived neurotrophic factor (BDNF), which protects nerve cells from injury during ischemic stroke. Furthermore, the release of irisin into the blood via exercise influences the mitochondrial dynamics crucial to maintaining the normal function of nerve cells. Consequently, we intended to summarize the known effects of irisin during ischemic stroke. The incidence of stroke has increased rapidly over the past few decades, causing it to become one of the main causes of death and long-term disability worldwide  in various ways by regulating sugar, lipid, and protein metabolism (Febbraio and Pedersen, The role of FNDC5/irisin in learning and memory is mediated by BDNF expression, which plays an important role in neural remodeling in conditions such as Alzheimer's disease (Wrann et al., in vivo (Peng et al., in vitro (Yu et al., A recent study has reported that irisin protects the blood-brain barrier from ischemic injury by decreasing the expression of MMP-9 (Guo et al., Notably, although Li et al.  have fouAs previously described, the discovery of irisin provides an alternative direction for studying the potential treatment methods for ischemic stroke. In 2017, Lidongjie et al. found that irisin synthesis reduces the infarct volume and the degree of brain edema and improves the neurobehavioral score in an oxygen-glucose deprivation model (Li et al., Mitochondrial dynamics mainly consist of fission and fusion. Fission is mediated by the proteins Drp1, Fis1, and MFF. Drp1 is recruited from the cytosol to the outer membrane of mitochondria and interacts with its receptor proteins MFF and Fis1 to create the fission complex. Drp1 is then oligomerized into filaments that wrap around mitochondria, leading to mitochondrial constriction and sequential separation of the inner and outer membrane. Drp1 reportedly has a crucial role in ischemic stroke; brain edema, the infarct area, and other neuronal injuries are alleviated following Drp1 downregulation (Anzell et al., Three different GTPases mediate fusion, including Opa1 and Mfn1/2. Mfn1/2 are anchored to the outer membrane of mitochondria, while inner membrane fusion is mediated by Opa1. A lack of mitofusins prevents fusion of both the outer and inner membrane of the mitochondria, while the loss of Opa1 only blocks fusion of the inner membrane. Mitochondrial fusion proteins are less studied in ischemic stroke. Mfn2 is reported to exert an anti-apoptotic effect, and its expression decreases in the presence of ROS. Opa1 can attenuate infarct volume in ischemic stroke, and its expression is increased after exercise (Anzell et al., In ischemic stroke, cell survival and pathobiology are involved in mitochondrial dynamics. As mitochondrial dynamics processes, fission and fusion are crucial to mitochondrial function. Fusion is presumed to be beneficial to cell survival, but studies show that fission facilitates cell death (Li and Liu, It is reported that mitochondrial homeostasis is closely related to AMPK upregulation associated with altered cell energy metabolism (Siteneski et al., AMPK is a heterotrimer including an α-subunit and two regulatory subunits, β and γ. The α-subunit is the main catalytic part of AMPK, containing a kinase domain and the key residue Thr172. When the ratio of ATP-AMP decreases, the AMPK complex is activated by phosphorylation on Thr172 in the α-subunit. The activated AMPK affects the mitochondrial dynamics by activating downstream substrates. When stresses, such as ischemia or hypoxia, are applied, the phosphorylated AMPK directly phosphorylates MFF. MFF then recruits Drp1 to the mitochondrial membrane, selectively causing fission of the damaged mitochondria and protecting normal mitochondrial function (Wang and Youle, It has been reported that exercise is a potential activator of AMPK, demonstrating the possibility that AMPK can affect mitochondrial dynamics via exercise (Trewin et al., Although treatment strategies for stroke have been explored over several decades, intravenous thrombolysis remains the primary and most effective method (Keizman et al., Irisin is reportedly induced by physical exercise to augment energy expenditure, according to the initial report (Boström et al., Irisin protects against endothelial injury and ameliorates atherosclerosis in Apo-E knockout mice (Lu et al., Many scholars have also suggested that irisin is an exercise-induced muscle factor, with exercise promoting its large-scale expression in skeletal muscles, the heart, and the brain. These brain regions include Purkinje cells in the cerebellum (Varela-Rodríguez et al., Evidence suggests that irisin levels are affected by a large number of stressors. It is well-established that acute exercise increases the levels of blood irisin (Jedrychowski et al., All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Childless older adults may be at risk for poorer health cross-nationally, yet most studies on this topic analyze only a small number of countries and only 1 or 2 health outcomes. To our knowledge, two papers exist that explore associations between childlessness and multiple indicators of health using data from a large number of regionally diverse countries , but neither study includes an examination of socioeconomic resources. The level of health risk faced by childless older adults is likely to be distinctly shaped by older adults’ socioeconomic resources . Associations between childlessness, socioeconomic resources, and health may also differ by country context. Using harmonized, cross-national data for adults aged 50 and older across 20 high- and middle-income countries (United States (HRS), European Union (SHARE), Mexico (MHAS), and China (CHARLS) from the Gateway to Global Aging data repository), we explore if and how individual-level socioeconomic resources  moderate associations between childlessness and five health indicators . Results suggest that associations between childlessness and health outcomes vary by individual socioeconomic resources in some country contexts, but not in others. We discuss these findings in light of the impact of individual-level socioeconomic resources on older adults’ support options and health outcomes cross-nationally.


B. Ngor et al.; Scientific Reports 10.1038/s41598-018-27340-1 (2018).3.As one of the richest sources of fisheries-related data in the lower Mekong basin, the Tonle Sap dai fishery has received considerable attention in the literature in recent years as concerns grow over the impacts of hydropower dams on fisheries, which are important for livelihoods and food security4 reported a decline since 2000 in the catch of larger species which tend to occupy higher trophic levels; compensatory increases in the catch of smaller species; and declines in the mean body weight (and length) of common species in the Tonle Sap dai fishery, as evidence of the effects of indiscriminate fishing or “fishing-down” of the multi-species fish assemblage in the lower Mekong basin. We provide evidence below that suggest that these apparent recent changes are more likely to reflect changing hydrological conditions than fishing-down effects, possibly caused by climate change and recently also by hydropower development.Ngor et al.6  of monitoring data which include one of the driest fishing seasons on record (1998–99). The authors thereby created a time series beginning with the three wettest seasons (largest floods) since monitoring began (2000–1 to 2002–3) that were followed by 12 seasons of variable, but decreasing flows caused by hydropower dam construction, low rainfalls possibly resulting from climate change, and abstractions for agricultureWithout reference to hydrological variation, Ngor et al. reported a temporal decline in the catch of larger, high-trophic level species; compensatory increases in the catch of smaller species; and declines in the mean body weight (and length) of six common species. The authors reported these findings as evidence of the effects of indiscriminate fishing (fishing-down) in the lower Mekong basin, without considering alternative explanations for the observed patterns.2. Moreover, the fishery itself is not standardised, with net types, mesh sizes and flow rates through the gears varying inter and intra-annually. Catches may therefore not reflect changes in underlying abundance7. Despite this, we re-examined the analysis of Ngor et al. at face value.Ngor et al. describe their dataset as being generated from a “standardized biological catch assessment”. In reality, this assessment is complex having undergone numerous changes through time, including to sampling efforte-transformed catch time series of larger species (TL > 45 cm) excluding those with zero catch in any year. These 28 species formed approximately 16% of the total catch during the study period. We also found negative regression coefficients for all 28 species, supporting the findings of Ngor et al. However, the combined annual catch of these 28 species did not decline significantly through time .Using the 15-season dataset that accompanied Ngor et al., we re-fitted regression models to the log2 = 0.46; p-value < 0.01) —a measure of flood extent and duration  with the FI. Rle Table . The fivHenicorhynchus, that formed 42% of the total catch during the study period, exhibited no significant trend through time .Contrary to Ngor et al. we found no clear evidence of a compensatory response by small species. The annual catch of the three most prolific small species of the genus 2. The time series analysis of mean fish weight illustrated in Figure 4 of Ngor et al. was subject to sampling-related bias because the number of observations of fish weight in each month varied significantly each year.The growth of species of fish caught by the dai fishery is non-linear and seasonale-transformed body weight using ‘year’ and the FI as alternative independent explanatory variables. To aid model comparisons we first standardised both independent variables.To avoid this bias, and minimise any gear selectivity effects, we examined how the mean body weight of the six common species examined by Ngor et al. varied in both December and January each year corresponding to the end of the flood, when any flood-related effects on fish growth would manifest. We compared regressions of mean logThe FI explained more of the variation in mean fish weight than ‘year’ in 9 of the 12 regressions compared  in Cambodia in 201213, we suspect that since then, an already fished-down assemblage has been further impacted by periods of low flow and limited flooding, possibly caused by climate change and hydropower dams6.While fishing pressure undoubtedly caused some fishing-down between 1970 and the 1990s corresponding to strong population growth and the spread of modern fishing methods


N-acylethanolamines (NAEs) and N-acyl amino acids belonging to the complex lipid signaling system termed endocannabinoidome. These molecules exert a variety of biological activities in the central nervous system, as they modulate physiological processes in neurons and glial cells and are involved in the pathophysiology of neurological and psychiatric disorders. Their effects on dopamine cells have attracted attention, as dysfunctions of dopamine systems characterize a range of psychiatric disorders, i.e., schizophrenia and substance use disorders (SUD). While canonical endocannabinoids are known to regulate excitatory and inhibitory synaptic inputs impinging on dopamine cells and modulate several dopamine-mediated behaviors, such as reward and addiction, the effects of other lipid neuromodulators are far less clear. Here, we review the emerging role of endocannabinoid-like neuromodulators in dopamine signaling, with a focus on non-cannabinoid N-acylethanolamines and their receptors. Mounting evidence suggests that these neuromodulators contribute to modulate synaptic transmission in dopamine regions and might represent a target for novel medications in alcohol and nicotine use disorder.The family of lipid neuromodulators has been rapidly growing, as the use of different -omics techniques led to the discovery of a large number of naturally occurring  N-arachidonoylethanolamide  family, also termed fatty acid ethanolamides. NAEs differ in the length and saturation of the hydrocarbon chain and their receptor affinity  are emerging as an intriguing class of neuromodulators, although largely uncharacterized so far  at physiologically relevant concentrations, the others display an affinity for peroxisome proliferator-activated receptor-α .Very little is known about the biosynthesis of N-acyl amino acids are hydrolyzed to free fatty acids and ethanolamine or amino acids  are synthesized following activation of metabotropic glutamate, muscarinic, or dopamine D2 receptors . Very little is known about the functional relevance of N-acyl amino acids and their receptors such as GPR18, GPR55, or GPR92; this topic is discussed in Burstein  evokes an increase in Ca2+ permeability and a rise in intracellular Ca2+, which is necessary for the activity of the Ca2+-dependent NAT isoform  .An extensive literature substantiates the role of the dopamine system in addiction and SUD. Dopamine facilitates the development of long-lasting forms of synaptic adaptations that determine the effectiveness of reward and reward predictors to control subsequent seeking behavior  depends on increased eCB levels within mesolimbic dopamine regions  were elevated in the plasma (Best et al., The role of NAEs in alcohol dependence has been extensively explored by studying the catabolic enzyme FAAH, both in rodents and humans. Several studies stress out the importance of FAAH genetic variants (Zhou et al., PPARα is upstream of diverse genes that are modulated by ethanol or involved in ethanol-induced effects (Ferguson et al., Tobacco use is associated with high morbidity and mortality, it being the most preventable cause of death in the world (World Health Organization, Both tobacco smoke and nicotine can affect the eCB system. Tobacco smoke alters FAAH, NAPE-PLD, and MAGL levels in the striatum (Torres et al., The involvement of the eCB system in nicotine dependence was demonstrated by the effect of FAAH inhibitors. FAAH inhibitors suppress many reward-related effects of nicotine in rats and non-human primates, such as nicotine self-administration and reinstatement of nicotine seeking (Scherma et al., via α7-nAChRs, and subsequent increase of intracellular Ca2+ (Melis et al., in vivo and in vitro strategies, Melis et al. (N-oleoyl glycine was shown by Donvito et al. (N-acyl amino acid is synthesized in dopamine cells and acts as an endogenous neuromodulator in a similar fashion of other NAEs with a dopamine moiety such as N-arachidonoyldopamine or N-oleoyldopamine (Ferreira et al., Besides the effect of the major eCBs, there is increasing evidence of the involvement of PEA and OEA in nicotine addiction, as they have a crucial role as endogenous modulators of cholinergic transmission (Melis et al., s et al.  confirmeo et al.  to countBased on the mechanisms described, the suppression of nicotine-induced responses of dopamine neurons by PPARα agonists raised the interest on these ligands as a promising strategy to prevent nicotine relapse (Melis and Pistis, A way to circumvent the limited brain permeability of fibrates is to increase brain levels of endogenous PPARα agonists, such as PEA and OEA. The recent development of brain-permeant selective NAAA inhibitors offers the advantage to modulate levels of PEA and OEA selectively, and not AEA, therefore concurrently limiting psychiatric side effects due to eCB-CB1 alteration. Similar to direct PPARα agonists, also NAAA inhibitors display potential as anti-smoking medications, as they block nicotine-induced excitation of dopamine cells, dopamine elevations in the nucleus accumbens, and conditioned place preference in a PPARα-dependent manner (Sagheddu et al., The expanded eCB system, the “endocannabinoidome,” is a hotbed for a large number of lipid signaling molecules, enzymes, and receptors and represents a Pandora’s box for drug discovery (Cristino et al., This review article summarizes evidence suggesting that NAE/PPARα signaling shows promise as a target in the treatment of SUD, particularly alcohol and nicotine use disorder. A parsimonious unifying hypothesis for this effect is NAE/PPARα’s ability to modulate dopamine cell activity by specifically dampening stress-evoked excitatory drive from cholinergic afferents on VTA dopamine cells. Hence, a heightened cholinergic transmission has long been postulated to contribute to detrimental effects induced by stress, such as depression (Janowsky et al., N-acyl amino acid family suggest that analogs of these lipid neuromodulators could become potential drug candidates.SUD represents an unmet clinical need, with drugs currently in use that show limited efficacy or untoward side effects. Indeed, results reported for members of the NAE and CS, LT, TM, and MP wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Genes. The topics of the selected manuscripts cover a wide range of current topics in biomedical research including cancer informatics, transcriptomic, computational algorithms, visualization and tools, deep learning, and microbiome research. In this editorial, we briefly introduce each of the manuscripts and discuss their contribution to the advance of science and technology.The International Association for Intelligent Biology and Medicine (IAIBM) is a nonprofit organization that promotes intelligent biology and medical science. It hosts an annual International Conference on Intelligent Biology and Medicine (ICIBM), which was established in 2012. The ICIBM 2019 was held from 9 to 11 June 2019 in Columbus, Ohio, USA. Out of the 105 original research manuscripts submitted to the conference, 18 were selected for publication in a Special Issue in  Genes were further reviewed by a minimum of two additional external reviewers. In the end, 18 manuscripts were selected for publication in the Special Issue, which covered the topics of cancer research, gene expression, single cell sequencing, novel computational algorithms, and microbiome research. In this editorial, we introduce the 18 selected research manuscripts.The International Conference on Intelligent Biology and Medicine ICIBM 2019) was organized and hosted by the International Association for Intelligent Biology and Medicine (IAIBM) and the Department of Biomedical Informatics at Ohio State University from 9 to 11 June 2019 in Columbus, Ohio, USA. The detailed description of the conference and its organization and achievements is summarized in [9 was orgChen et al. published “Computational Cancer Cell Models to Guide Precision Breast Cancer Medicine” . In thisA pathway is a summary of a set of genes that can be connected via their biological process, regulation, mechanism. or phenomenon. Pathways of important function can be alternatively activated in cancer. Wang et al. published “Identification of Alternatively-Activated Pathways between Primary Breast Cancer and Liver Metastatic Cancer Using Microarray Data”, in which the authors proposed an alternatively-activated pathway mining method  based onCirculating tumor DNA (ctDNA) has been found in the bloodstream which originated from cancerous cells. Research on ctDNA has been expanding over the last decade resulting in substantial advancement in the identification of single nucleotide variants from ctDNA. Copy number variation (CNV), which is also considered to be an important cancer biomarker, has been very difficult to detect from ctDNA due to the low amount and complex CNV features. Peng et al. published “CNV Detection from Circulating Tumor DNA in Late-Stage Non-Small Cell Lung Cancer Patients” to address the critical issue of CNV identification in ctDNA . Their mDNA methylation plays a variety of roles in cancer, including a critical role in the control of gene activity, which helps to convert gene expression in normal tissue to a cancerous pattern. Utilizing deep learning techniques, Liu et al. published “DNA Methylation Markers for Pan-Cancer Prediction by Deep Learning”, in which they studied the prognostic value of DNA methylation . Using dFOXO1 and PAX3/7 and observed substantial restructuring of co-expression networks related to fusion status and fusion type.Gene fusion describes hybrid genes that are formed from two independent genes. Gene fusion has been a common feature in cancer genomes and has served as a molecular target in therapeutic development. In Helm et al.’s “Gene Co-Expression Networks Restructured Gene Fusion in Rhabdomyosarcoma Cancers”, the authors studied gene fusion features in rhabdomyosarcoma . In thisTumor-infiltrating leukocytes (TILs) are immune cells surrounding tumor cells, and several studies have shown that TILs are potential survival predictors in several types of cancers including liver cancer, which is highly associated with a hepatitis virus. Hsiao et al. studied TIL abundance and compositions concerning hepatocellular carcinomas survival in their manuscript, entitled “Tumor-Infiltrating Leukocyte Composition and Prognostic Power in Hepatitis B- and Hepatitis C-Related Hepatocellular Carcinomas” . The autNetwork and biomarker analyses have been heavily utilized for cancer research. Liu et al. combined the concept of both a network and biomarker approach in their paper entitled “Network as a Biomarker: A Novel Network-Based Sparse Bayesian Machine for Pathway-Driven Drug Response Prediction” . The autIn the paper entitled “Kinetic Modeling of DUSP Regulation in Herceptin-Resistant HER2-Positive Breast Cancer”, Buiga et al. focused on the analysis of dual-specificity phosphatases (DUSPs) in HER2-positive breast cancer , a highlCompelling evidence has shown that microRNAs (miRNAs) can regulate genes and be associated with various cancers through a post-transcriptional suppression regulation mechanism. The dysregulation of miRNA can substantially alter the landscape of the transcriptome level of messenger RNAs (mRNAs). Dai et al. published “Identifying Interaction Clusters for miRNA and mRNA Pairs in TCGA Network”, which describes a novel cluster scoring method to identify mRNA and miRNA interaction pairs . Their aCryogenic electron microscopy (cryoEM) is an electron microscopy technique applied on samples cooled to cryogenic temperatures and embedded in an environment of vitreous water. It is often used to study structural biology. The analysis of cryoEM often involves a clustering algorithm. Al-Azzawi et al. published “A Super-Clustering Approach for Fully Automated Single Particle Picking in Cryo-EM”, a manuscript that describes a newly developed fully automated super-clustering algorithm for single particle picking in cyroEM micrographs. The authors focused on identifying, detecting, and picking particles of the complex and irregular shapes in micrographs with extremely low signal-to-noise ratio .While single cell sequencing has quickly emerged as a powerful technology for measuring DNA variants or transcriptome abundance at the single cell resolution, numerous challenges currently remain in this new field. One of the major shortcomings of single cell RNA-seq is the excessive zero counts, because only a small fraction of the transcripts sequenced in each cell. This problem can be alleviated by sequencing more, but it is at a high financial cost and also a lack of enough cells available for sequencing. The sparsity of the gene expression for each cell creates additional downstream analysis challenges such as cell type identification. Zand et al. introduced a network-based method, netImpute  to battlIn the era of big data, data visualization tools are essential for analyzing massive amounts of information and making data-driven decision. This is no difference in transcriptomic data analysis. Al-Ouran et al. published “A Portal to Visualize Transcriptome Profiles in Mouse Models of Neurological Disorders”, in which they described a new web-based platform for visualizing mouse transcriptome data . The webNon-coding RNA has been the focus of many research studies over the last decade. Porto et al. published “Long Non-Coding RNA Expression Levels Modulate Cell-Type-Specific Splicing Patterns by Altering Their Interaction Landscape with RNA-Binding Proteins”, a study  in whichLepisosteus oculatus)” [nfil3 and cry families are different between spotted gar and humans. These findings help decipher the repertoires of the spotted gar’s circadian system and shed light on how the vertebrate circadian clock systems have evolved.A circadian rhythm is a natural internal process that regulates the sleep-wake cycle. While the canonical circadian clock genes and their regulatory mechanisms appear highly conserved, the evolution of clock gene families is still unclear due to several rounds of whole genome duplication in vertebrates. Sun et al. studied circadian clock genes in spotted gar, a non-teleost ray-finned fish, and published their findings in the manuscript “The Molecular Evolution of Circadian Clock Genes in Spotted Gar (ulatus)” . PhylogeIn data science, a large dataset is often assembled from multiple smaller datasets with heterogeneity. The missing variable has become a common problem when combining datasets, which poses a major challenge for downstream analysis. Bartlett et al. published “Forming Big Datasets through Latent Class Concatenation of Imperfectly Matched Databases Features”, to address this problem . The autGenotyping data has been aiding researchers for large genetic association studies for the last two decades. Imputation is an important preprocessing step for combining genotyping data or increasing coverage. Traditional genotype imputation methods are typically based on haplotype-clustering algorithms, hidden Markov models (HMMs), and statistical inference. Chen et al. described their new deep learning-based imputation method  in theirThe microbiome studies many microorganisms in a particular environment. Microbiome research has been greatly enhanced by the advancement of 16S rRNA high throughput sequencing. Liu et al. published “Changes in the Microbial Community Diversity of Oil Exploitation”, a study on microbiome in several offshore petroleum production sites . The autICIBM is an annual international conference, which has been held every year since 2012 (except 2017). It promotes a highly interactive and friendly platform for both young and senior researchers to exchange their research, foster collaboration, as well as expand educational activities. Approximately one hundred and seventy researchers and trainees from around the world joined the 2019 conference and contributed to a rich conference program, which included four keynote lectures, four eminent scholar talks, five tutorials and workshops, twelve concurrent sessions, a poster session, and other conference activities. Among the 105 original research manuscripts, we selected 18 for the Special Issue after two rounds of peer reviews. These 18 manuscripts describe innovative, computational works in the field. We expect these manuscripts to promote further investigation in the same or similar topics, and lead to more research toward translational clinical applications.


Objective: Mild cognitive impairment (MCI) is an important risk state for dementia, particularly Alzheimer’s disease (AD). Depression, anxiety, and apathy are commonly observed neuropsychiatric features in MCI, which have been linked to cognitive and functional decline in daily activities, as well as disease progression. Accordingly, the study’s objective is to review the prevalence, neuropsychological characteristics, and conversion rates to dementia between MCI patients with and without depression, anxiety, and apathy.Methods: A PubMed search and critical review were performed relating to studies of MCI, depression, anxiety, and apathy.Results: MCI patients have a high prevalence of depression/anxiety/apathy; furthermore, patients with MCI and concomitant depression/anxiety/apathy have more pronounced cognitive deficits and progress more often to dementia than MCI patients without depression/anxiety/apathy.Conclusions and Implications: Depression, anxiety, and apathy are common in MCI and represent possible risk factors for cognitive decline and progression to dementia. Further studies are needed to better understand the role and neurobiology of depression, anxiety, and apathy in MCI. Mild cognitive impairment (MCI) represents a transitional stage between healthy aging and dementia. Subjects with MCI complain about cognitive impairments, have documented cognitive deficits relative to age- and education-matched controls—although they are less impaired than patients with dementia—and have largely intact activities of daily living Sanford, . Dependiin vivo by biomarkers in the National Institute on Aging and Alzheimer’s Association Research Framework in Jack et al.  presented a reanalysis of subpopulations already included in other studies; (b) reported a patient population of less than 10 patients; or (c) were commentaries, technical notes, or review articles summarizing the results of previous studies.We included original studies from tertiary referrals and population-based studies written in English that examined populations with MCI, depression, anxiety and apathy. A systematic literature search was performed using the PubMed database. Search terms were via depression  compared to MCI patients without depression (13.5%; Lee G. J. et al., However, there is research that demonstrated contrary conclusions. A 3-year prospective study of MCI outpatients demonstrated no increased risk of AD in patients with symptoms of depression (Palmer et al., Vascular factors play an important role in depression within preclinical dementia. In MCI patients, new onset of depression was associated with deep subcortical cerebral white matter hyperintensity severity (Kim et al., The reported prevalence of apathy in MCI is between 10.7% and 44.8% (Palmer et al., Patients with MCI with apathy have an increased risk of dementia, independent of depression. A systematic review found that apathy was associated with an approximately two-fold increased risk of dementia in memory clinic patients (van Dalen et al., Anxiety symptoms have been studied less than depression, and the relationship between anxiety and cognition is complex. The reported prevalence of anxiety in MCI patients ranged between 9.9%–52% (Lyketsos et al., Generalized anxiety disorder is the main anxiety disorder associated with poor global cognitive functioning, and this association is moderated by sex but not by the presence of depressive episodes (Potvin et al., Anticipatory anxiety is significantly associated with earlier conversion to AD, but this association does not remain significant following an adjustment for cognitive status at the baseline; anxiety for upcoming events and purposeless activity frequently co-occur, which indicates anticipatory anxiety may be a marker of severity rather than an independent predictor of disease progression (Gallagher et al., Other investigators have failed to find an association between anxiety symptoms in patients with MCI and an increased risk of conversion to AD (Robert et al., Depression, anxiety, and apathy are common in MCI patients and are important indicators in the progression to dementia in MCI patients, which emphasizes the importance of assessing depressive symptoms as well as anxiety and apathy in the early stages of cognitive impairment. Further studies are needed to better understand the role and neurobiology of depression, anxiety, and apathy in MCI. Indeed, further studies on observation of larger patient populations and long follow-up are needed.LM designed and wrote the manuscript.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Meanwhile, the Editors became aware of adenouncement published by independent journalists from the “For Better Science” websiteincluding this paper. This denouncement consisted of potential data falsification and/orinaccuracy of results in western blots and flow cytometry plots.As per consensus between the Authors and the Editors-in-Chief of the Brazilian Journal ofMedical and Biological Research (BJMBR), the article titled “Effect of lncRNA HULCknockdown on rat secreting pituitary adenoma GH3 cells” that was published in year 2019,volume 52, issue 4,  has been retracted.


APOE) is the best-known and has the strongest association with AD development. AD probability decreases in carriers of the e2 variant of the APOE gene (APOE-e2), whereas APOE-e4 is believed to be a strong risk factor  is a neurodegenerative condition that inevitably impairs cognitive functions and influences a patient's behavior, mood, and self-reliance. Due to demographic changes, AD and other age-associated diseases have become increasingly common and burdensome for families, as well as entire societies. It is extremely important that we learn more about specific mechanisms that can be linked to the development of the disease. The main symptoms of AD, observed in the central nervous system, are brain atrophy and loss of neurons and synapses. They are believed to result from excessive aggregation of tau protein and amyloid plaques (composed of ß-amyloid). However, neither the initial cause nor the detailed chain of events that lead to this type of neurodegeneration are known. No deterministic genes were identified for late-onset Alzheimer's disease (LOAD), but several risk genes seem to be involved in its pathogenesis. The gene coding apolipoprotein E  of negative impact on human brain function in AD. Results indicating enhanced APP synthesis are in agreement with studies showing higher levels of Aβ in brains of APOE-e4 carriers, examined post-mortem  and other risk-genes. Moreover, it was shown that neurons need astrocytes and microglia to eliminate redundant synapses  homeostasis and synaptic stability maintenance, with APOE-e4 having the most negative impact on the brain. APOE-e4 limits the astrocytes' ability to recycle and clear extracellular cholesterol (Fernandez et al., APOE-e4 showed accumulation of cholesterol and could not efficiently fulfill their role related to clearance of Aβ (Lin et al., The question arises: how is it possible to link these cell-level studies with the same ranking (g et al. , and preg et al. , showed g et al. . APOE haAPOE-e4 that leads to an increase in toxic Aβ forms and impairs astrocytes' function, which can initiate the whole cascade of changes related to later loss of synapses and cognitive functions. It may indicate that, in the brains of APOE-e4 carriers, AD risks begin to accumulate from early developmental stages when too many synapses are formed and not enough of them are pruned (Chung et al., APOE-e4 risk related to loss of cognitive functions is predominant for persons older than 50 years of age, people homozygous for APOE-e4 may experience the risk much earlier, just after 40 years of age (Liu et al., APOE-e4 could affect the brain even earlier, changing its structure, function and neurochemistry (see DiBattista et al., APOE-e4 young carriers perform equally well or even much better in a variety of cognitive tasks compared to non-carriers (Mondadori et al., APOE-e4 on neuronal signaling pathways throughout the lifespan may help us to identify early biomarkers and target therapy against AD in the future.Perhaps it is the initial higher number of synapses and APP in neurons with PD wrote the first draft. EK critically edited and improved the manuscript. PD and EK read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.