Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches. In recent years, the topic “personalized medicine” has gained much attention. A famous example is the anticancer drug Cetuximab, which binds to the EGF receptor and, consequently, prevents activation of the downstream signaling pathway, thus inhibiting cell proliferation. However, it has been found that Cetuximab can work only if the K-RAS gene is not mutated. Testing patients for mutations of this gene in the European Union is thus prescribed before application of Cetuximab to prevent a costly and ultimately ineffective therapy. Another example is the anti-cancer drug Trastuzumab, which is only effective in patients that express highly the human epidermal growth factor (HER2) at the cell surface, to which the antibody binds.These examples underline the need for identifying reliable biomarkers that predict a patient’s response to therapy, including potential adverse effects, in order to avoid ineffective treatment and to reduce drug side-effects and associated costs. Towards that goal a large amount of work has been conducted within the last decade, which tries to stratify patients according to disease subtypes or different clinical prognosis. Nowadays modern high-throughput technologies allow for screening of massive amounts of OMICs-type data, and so one goal is to associate such data with a patient’s clinical prognosis or with the membership to a certain disease subtype. Based on OMICs data it has been even possible to identify novel disease subtypes. For example, based on gene expression profiles, five subtypes of breast cancer have been identified .et al. [Prognostic or diagnostic biomarker signatures  have been derived in numerous publications for various disease entities. One of the best known ones is a 70-gene signature for breast cancer prognosis (mammaprint) by van ’t Veer et al. , which hFor the construction of biomarker signatures, one typically uses supervised machine learning methods together with algorithms for variable/feature selection. This is because OMICs data is typically very high dimensional compared to the number of samples/patients in a typical study. The microarray technology nowadays enables measurement of tens of thousands of transcripts at the same time, whereas the sample size is typically in the order of 100–300 patients. This not only imposes high challenges for the interpretation of such data, but also for robust and stable statistical procedures, which are needed to detect those genes that are truly correlated with the clinical phenotype. In this context it should be mentioned that typical machine learning algorithms operating with far more variables/features than samples are prone to the so-called “overfitting” phenomenon: The classifier or Cox regressor can perfectly explain the data used for model construction, but fails in making good predictions on new test data . Therefoet al. [Well known algorithms for this purpose are PAM , SVM-RFEet al. . Moreoveet al. ,10,11. Fet al. ,13. Howeet al. . For thaet al. . In thisNowadays knowledge on protein-protein interactions (PPIs) as well as on canonical pathways can be retrieved easily in a computer readable format from databases, such as KEGG , HPRD 1, PathwayIn general one may divide existing methods integrating network knowledge broadly into two main classes: On one hand there are network centric approaches, which map gene expression data onto a PPI network reconstructed from the literature and then either try to identify discriminative/differential sub-networks between patient groups, or directly compute summary statistics (pathway activity) for pre-defined sub-networks . Afterwards often a conventional classifier  or Cox regressor is applied to make predictions based on the expression profiles of sub-network genes. On the other hand data centric approaches are closer to traditional machine learning methods. Here the idea is to bias the gene selection process within a machine learning framework in such a way that connected genes are preferably selected. There are two main techniques for this purpose: One is to construct a mathematical embedding of gene expression data into a network graph space via the so-called kernel trick . AfterwaIn the following we give a more detailed overview about these methods. et al. [i.e., proteins with an extraordinary high degree of interactions. In their paper Taylor et al. show that the average Pearson correlation of the expression of a hub protein and its interacting partners can be used to reliably predict survival of breast cancer patients without any further machine learning based variable or feature selection procedure. An approach, which is possibly most focusing on the network structure itself, is to purely select genes based on topological features of the protein-protein interaction network. An example is the method proposed in Taylor et al. . Here thAnother method to integrate network knowledge is to summarize the expression level of predefined canonical pathways obtained from databases, such as KEGG , into onet al. [Guo et al.  report tet al. ) categoret al. [Rather than simply looking at mean or median expression Vaske et al.  propose et al. [Teschendorff et al.  further et al. show that their “combined optimal response genes” (CORGs) approach yields better prediction performance than if pathway activity is simply estimated via the mean or median expression level. A further improvement of the method with respect to the selection of discriminative genes within each pathway is proposed in Yang et al. [Another approach following the same direction is proposed by Trey Ideker and co-workers . In theig et al. . et al. [et al. show that estimated pathway activities are predictive for the respective patient subgroups, and that in cell lines pathway activity also predicts the sensitivity to therapeutic compounds. An extension of the pathway activity classifier to identify oncogene-inducible modules is described in Bentink et al. [Bild et al.  estimatek et al. . et al. [Yu et al.  propose et al. . Afterwaet al. [The paper by Kammers et al.  focuses et al. . Penalizet al. [et al. [et al. [et al. [Rather than looking at predefined canonical pathways or GO groups, another idea that puts a little bit more emphasis on measured data is to reconstruct a protein-protein interaction network for all gene products and then use experimental data to identify differentially expressed sub-networks. One of the first approaches in this direction is described in Chuang et al. . The alget al. , Fortney [et al. , Su et a [et al. , Ahn et  [et al. . A particular interesting variant has recently been introduced by Dutkowski and Ideker . They mooptimal differential sub-network. Attempts to obtain an optimal sub-network are described in Chowdhury et al. [et al. [et al. [It has to be mentioned that despite their good performances, all so far mentioned approaches are heuristic and thus cannot guarantee to find the y et al.  via bran [et al.  via exha [et al. . After cet al. [et al. use a randomized approximation algorithm to obtain polynomial run time complexity. Afterwards the authors employ a 3-NN classifier on averaged expression levels of each sub-network to discriminate response to chemotherapy in breast cancer. In general, identification of an optimally discriminative sub-network is an NP-hard problem ,46 and tet al. , which aAll previously mentioned approaches deal with a PPI network as the central entity. In contrast, data centric approaches focus on the experimental data. Kernel techniques  allow fok :  can be thought of as a special similarity measure between arbitrary objects x ∈ , which fulfills additional mathematical requirements, namely symmetry  = k for all x,y ∈ ) and positive semi-definiteness  =  for all x,y, where (·) denotes the dot product in Hilbert space  and :  →  is some arbitrary map) [x and y, but weights each path in dependency on the path length. This is done in an exponentially decreasing way. Diffusion kernels are mathematically equivalent to the fundamental solution of the heat equation in physics, which describes the evolution of heat in a region under certain boundary conditions. If instead of exponentially decreasing weights for path lengths a linear weighting scheme is preferred, one arrives at the pseudo-inverse of the graph Laplacian [p. In general, a kernel function ary map) ,48. Amonary map)  is a speaplacian . In the x → y in the network by the similarity of the gene expression of x and y (using the dot product). This is equivalent to defining a kernel function between x and y as:x and y are the vectors of gene expression values for genes x and y, and Q is the graph kernel matrix between nodes in the network. Consequently the expression data is linearly mapped via the graph kernel matrix Q to some different space. The aforementioned graph kernels allow for easily incorporating measurement data, such as gene expression. This is done by weighting each edge et al. [et al. [et al. in particular emphasize the possibility to conduct unsupervised clustering analysis of gene expression data in this way besides more common supervised classification, which yields biologically interpretable results. Several other authors have used graph kernels to identify possibly disease causing genes [Combining gene expression data with network information in such a way has been described by Rapaport et al.  and Gao  [et al. . In geneng genes ,53. et al. [vs. late recurrence of ER positive breast cancer patients with comparably high accuracy. Moreover, the obtained sub-network markers appear to be biologically plausible. Recently, Chen et al.  have intet al. [Instead of augmenting the similarity measure of each pair of genes with network information via embedding techniques, another approach is to directly integrate network information into conventional variable/feature selection techniques. Zhu et al.  describeet al. [i.e., embedded into a different space. In their paper the authors demonstrate that SVM-RRFE is not only superior to the conventional SVM-RFE algorithm in predicting an early relapse in breast cancer patients, but can also compete with several other network based gene selection approaches. Moreover, the stability and interpretability of the obtained gene signatures are significantly improved. Johannes et al.  introducet al. , which iet al.  to identBinder and Schumacher  propose et al. [et al. show that this way miRNA and mRNA expression data can be combined in a straightforward way for predicting the risk of a relapse in prostate cancer via penalized Cox regression. Moreover, they demonstrate that their approach enhances prediction performance and gene selection stability compared to several other methods. In a recent paper Gade et al.  extend tet al.  by consiLasso regression models  have gaiIntegration of biological knowledge, specifically from protein-protein interaction networks and canonical pathways, is widely accepted as an important step to make biomarker signature discovery from high dimensional data more robust, stable and interpretable. Consequently there is an increasing amount of methodologies for this purpose. In this review we gave a general overview about these approaches and grouped them into categories. The majority of algorithms at the moment follow the network centric paradigm, specifically by looking for differentially expressed sub-networks. This approach certainly appears attractive, because the gene selection problem is solved in a very elegant and natural way. Moreover, learned sub-networks are usually better to interpret than gene signature obtained via conventional machine learning techniques. One difficulty, however, lies in the fact that usually sub-networks are found by connecting differentially expressed genes. If there are no differentially expressed genes, then the identification of discriminative sub-networks becomes difficult. Moreover, finding an optimally discriminative sub-network is a computationally difficult, NP-hard problem. i.e., the phenotype can be explained by the activity of defined canonical pathways. If this is not the case or if only a few genes within a pathway are slightly differential, then identifying a pathway’s activity to be associated to the clinical phenotype becomes difficult. Hence, smart filtering strategies to focus on the most relevant genes within a pathway, like in the CORGs algorithm [et al. [Estimating the total activity of canonical pathways appears to be comparably simpler from a computational point of view. However, the approach only works if many genes in a pathway change their expression in a coordinated way, lgorithm  or via t [et al. , are useThere are comparably few data centric approaches, which come from the machine learning field, specifically from the area of kernel based methods. Since OMICs data is very high dimensional, linear classifiers are usually sufficient and thus the biased feature selection framework appears to be more natural. Compared to network centric approaches, these methods have the potential advantage that they do not rely so much on the PPI network structure. That means false positives or false negative interactions in the network structure will affect the model less. In addition, they are able to detect sub-networks, which are not part of canonical pathways. Thus they can be seen as more generally applicable. On the other hand they use available biological knowledge in a much less effective way than network centric methods. vs. late relapse of breast cancer patients in 6 microarray datasets. They found a large variability of prediction performances of individual algorithms across datasets, but no general advantage of network based methods. Network based SVM approach by Zhu et al. [In conclusion we see that all approaches that have been proposed so far have specific advantages and disadvantages. Thus there is a strong need for systematic empirical comparisons. Cun and Fröhlich  conducteu et al.  yielded u et al.  had the In this context it has to be emphasized that most published methods have been evaluated for one specific clinical question  in one disease (mostly breast cancer), only. To get a more complete picture, more comprehensive studies including more clinical questions and more disease entities are needed in order to guide practitioners, under which conditions which method would be a good choice. Nonetheless, there will be always a dataset specific dependency of an algorithm’s performance, which can never be resolved. Careful checking of assumptions is therefore a prerequisite for the successful application of any algorithm.


Coastal biotechnology is developing fast with exciting achievements being realized in biological, chemical, and environmental sciences and technologies. The aim of the 1st International Conference on Coastal Biotechnology (1st ICCB) on “Coastal Biotechnology for Sustainable Development,” which was successfully held in the Australian winter of 2012 in Adelaide, Australia, was to bring together the international community working on coastal biotechnology issues, to help strengthen connections in this highly interdisciplinary field, and to inspire new research and development from the scientific and industrial sectors.The 1st ICCB had two themes: “the changing distribution pattern of coastal bioresources” and “coastal biotechnology: facing the global and regional changes.” Bioresources are the essence of biotechnology. We first need to understand the biodiversity of these bioresources before we choose the techniques needed to use them to our advantage. Products and industries that emerge from coastal biotechnologies influence research and the development of technologies and policies. We are living in a world with rapid global changes—both naturally and socially. Those changes could alter the patterns of biodiversity especially in marine and coastal environments. How we address the global questions of food, fuel, population, environment, and so forth with sustainable developments of coastal bioresources is an issue not only for marine biologists, but also for all people of insight both from academia and industry.Cloning and expression of a cytosolic HSP90 gene in Chlorella vulgaris” by Z. Liu et al.; “Biochemical and anatomical changes and yield reduction in rice (Oryza sativa L.) under varied salinity regimes,” by M. A. Hakim et al.; “Cultivation of Isochrysis galbana in phototrophic, heterotrophic, and mixotrophic conditions,” by Y. Alkhamis and J. G. Qin; “Photosystem II photochemistry and phycobiliprotein of the red algae Kappaphycus alvarezii and their implications for light adaptation,” by X. Guan et al.; “Extraction and separation of fucoidan from Laminaria japonica with chitosan as extractant,” by R. Xing et al.; “Pyrolytic and kinetic analysis of two coastal plant species: Artemisia annua and Chenopodium glaucum,” by L. Li et al.; and “Effects of seawater salinity and temperature on growth and pigment contents in Hypnea cervicornis J. Agardh ,” by L. Ding et al.This special issue is devoted to coastal biotechnology, containing 7 papers that pertain to our goals in the ICCB conference. Papers from L. Ding et al., R. Xing et al., and X. Guan et al. are on seaweeds ; the ones from Z. Liu et al and Y. Alkhamis et al. are on microalgae; the one from L. Li et al. focuses on halophyte; and the one from M. A. Hakim et al. is on coastal salt-tolerant crop, rice. These 7 papers are as follows: “The inspiration of this special issue has grown from the contributions from the combined conferences ICCB and the 8th Asia Pacific Conference on Algal Biotechnology (APCAB 2012). APCAB meetings date back to more than 20 years ago when the first was held in Malaysia in 1992. With its development over the years, APCAB is regarded as the major international forum in algal biotechnology R&D field, serving the Asia-Pacific region, offering not only an examination of achievements in algal biotechnology, but also a platform for discussing the roadmap for future developments.


This paper investigates the stability and change of etiological influences ondepression, panic, generalized, separation and social anxiety symptoms, and theirco-occurrence, across adolescence and young adulthood.Depression and anxiety persist within and across diagnostic boundaries. The manner inwhich common A total of 2619 twins/siblings prospectively reported symptoms of depression andanxiety at mean ages 15, 17 and 20 years.Each symptom scale showed a similar pattern of moderate continuity across development,largely underpinned by genetic stability. New genetic influences contributing to changein the developmental course of the symptoms emerged at each time point. All symptomscales correlated moderately with one another over time. Genetic influences, both stableand time-specific, overlapped considerably between the scales. Non-shared environmentalinfluences were largely time- and symptom-specific, but some contributed moderately tothe stability of depression and anxiety symptom scales. These stable, longitudinalenvironmental influences were highly correlated between the symptoms.The results highlight both stable and dynamic etiology of depression and anxietysymptom scales. They provide preliminary evidence that stable as well as newly emerginggenes contribute to the co-morbidity between depression and anxiety across adolescenceand young adulthood. Conversely, environmental influences are largely time-specific andcontribute to change in symptoms over time. The results inform molecular geneticsresearch and transdiagnostic treatment and prevention approaches. Theinclusion of siblings inevitably resulted in large age ranges; however, 72% of theparticipants were twins with a tighter age range . Attrition was predicted by socioeconomic status ,delinquency  and sex ,but not by zygosity and internalizing symptoms.The analyses use data from waves 2–4 (hereafter referred to as times 1–3 respectively) ofa longitudinal twin and sibling study, the Genesis 1219 (G1219). Full details are providedelsewhere .At each time the participants completed the Short Mood and Feelings Questionnaire  completed the Spence Children's Anxiety Scale Spence,; a 38-itet al.The internal consistencies and descriptive statistics of all measures were comparableto published samples and are presented elsewhere  and DZ(sharing on average 50% of their segregating genes) twin pairs. Differences in within-paircorrelations allows estimations of the influences of additive genetics (A), sharedenvironment (C) factors that contribute to phenotypic similarity between siblings) andnon-shared environment . Quantitative genetic methods are described comprehensively elsewhere . The fit of sub-models was assessed byχ2 difference tests, i.e. Akaike's Information Criterion(AIC) and Bayesian Information Criterion, with lower values suggesting a better fit. Ifthe difference between AIC of two models was <10, the more parsimonious model wasselected  of the observations. This is not an overall measure offit, but provides a relative measure of fit, since differences in –2LL between models aredistributed as et al.Univariate genetic analyses were conducted on all variables at each time. Males andfemales showed differences in variance on all variables except for social anxiety, and ascalar was fitted to account for this difference (Waszczuk a) was used to examine the homotypiccontinuity of etiological influences separately for each variable. The Choleskydecomposition assumes three distinct sets of genetic and environmental influences on avariable at each time point. A1 and E1 are common factors on the first variable (pathsa11 and e11) that can also influence the remaining two variables. A2 and E2 influence the second variable  and can also influence the third variable overand above the influences accounted for by A1 and E1 . A3 and E3 are uniqueinfluences specific to the third variable only . Total A and E effects on each individualmeasure can be obtained by summing all squared paths to that measure . Multivariate models best suited to investigate specific research questions were chosen apriori. The Cholesky decomposition a was useb) was fitted in order to investigate the stability and change ofthe etiological influences shared between depression and anxiety symptom scales acrossdevelopment, to inform the mechanisms underpinning heterotypic continuityacross time. The model is illustrated on Fig.1b (with just three variables for clarity); the model was runwith all five variables included, each measured at three time points. This model assumesfive latent factors; each underlying a variable assessed three times. For example, thedepression latent factor captures the stability of the depression symptoms across times1–3. Variance of each latent factor is then decomposed into genetic (Al) andenvironmental (El) influences to assess the etiological factors underpinningthe stability of each symptom. Of note, El is free from time-specificmeasurement error but not from shared measurement error. The genetic and environmentalcorrelations between the latent factors (rAl andrEl) represent the degree of developmental stability commonto depression and anxiety symptom scales. Any remaining variance (not explained by thelatent factor) is then calculated as variable-specific genetic and environmentalinfluences (As and Es). The variable-specific etiological influencesinclude genetic and environmental influences that emerge at later time points, and areallowed to correlate with the within-time influences on all other variables(rAs and rEs), capturingtime-specific associations between them.The common pathway model b was fitr = 0.35–0.58). The heterotypiccorrelations between the different anxiety symptom scales, and between depression and eachof the anxiety scales, were similar in magnitude and generally moderate.Homotypic correlations were generally larger than heterotypic correlations, but tended todecrease at longer time intervals (times 1–3). The longitudinal correlations between the variables across the three time points arepresented in 1 on Fig. 1a) accounted for 45% of thevariance in generalized anxiety symptoms at age 15, but reduced to 21% by age 17 (patha12) and 18% by age 20 (path a13). Third, new genetic factorsemerged at each age (paths a22 and a33). Genetic influences thatemerged at age 17 continued to influence symptoms at age 20 (path a23) ingeneralized anxiety, panic and social anxiety, but not in depression and separationanxiety. Separation anxiety was characterized by particularly high change in geneticinfluences over time. The Cholesky decompositions show the effect of stable and new genetic and environmentalfactors across the three times, separately for each of the five symptom scales. Theresults were similar for depression and each anxiety symptom scale . First, Non-shared environmental influences on all symptoms were largely age-specific. Forexample, the non-shared environmental factors influencing generalized anxiety symptoms atage 15 had a small effect at age 17, and no significant effect at age 20. For 95%confidence intervals see Supplementary Table S1.2, see l = 0.61–0.76),with the remaining variance explained by modest to moderate, significant non-sharedenvironmental influences (El = 0.24–0.39) (rphl = 0.58–0.83) (rAl = 0.60–0.86) and the non-shared environmentalcorrelations between the latent factors were also high(rEl = 0.46–0.76) (s = 0.01–0.26)(s = 0.31–0.56) and accounted for mostof the non-shared environmental influences on each variable (rphs = −0.12–0.56), as did the genetic and non-sharedenvironmental within-time correlations between them  . The lat58–0.83) . Genetic46–0.76) . The var01–0.26), since mvariable . The pheeen them . Table 2et al.et al.Model fit statistics for comparisons to the saturated models, and testing whetherparameters can be dropped, are presented in Supplementary Table S2. Model fit statisticscorroborate AE models and in the full models C estimates are very small. However, forcompleteness full ACE models are presented in Supplementary Tables S3–S5. Full ACECholesky decompositions suggest smaller genetic innovation than AE models (SupplementaryTable S3). Otherwise dropping C from the models did not have impact on the interpretationof the results. The within-time analyses of these variables, including univariate ACEresults, are presented elsewhere (Lau The current study is the first to investigate how etiological influences contribute todevelopmental stability and change of depression, four anxiety symptom scales, and theirco-occurrence across adolescence and young adulthood. The results provide support forlargely stable and broad genetic influences accounting for co-occurrence and continuity overtime. Environmental influences were generally more specific to time and symptom scales,contributing to change in symptoms over time.et al.et al.et al.et al.et al.et al.et al.et al.Moderate homotypic continuity of depression and each anxiety symptom scale across the5-year period was observed, as expected (Costello et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.The non-shared environmental influences on homotypic continuity of each symptom werelargely time-specific, as expected (Scourfield et al.et al.et al.et al.et al.et al.et al.et al.The current study extends previous findings by investigating longitudinal etiologicalinfluences on homotypic continuity of depression and anxiety symptoms scales separately.A similar pattern of substantial genetic stability and largely time-specificenvironmental influences was observed on all symptoms, possibly due to a substantialoverlap between the genes influencing depression and anxiety (Kendler et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.Heterotypic continuity across the symptom scales was significant, reflecting highco-morbidity between depression and anxiety symptoms (Merikangas, change in co-morbidity over time. However, a modestproportion of environmental influences contributed significantly to the stability ofeach symptom scale, albeit to a lesser extent than the genetic influences. The resultsare in line with some previous findings (O'Connor et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.et al.As expected, environmental influences were largely time- and symptom-specific, thuscontributing to the et al.et al.et al.et al.et al.et al.et al.et al.et al.The genetically informative, representative sample and multiple time points are strengthsof the current study. However, a number of limitations are noteworthy. First, our analysesused only self-report symptom scales and the results should be replicated in clinicalsamples with co-morbid diagnoses and using lifetime diagnostic interviews. This approachwas taken because clinical levels of internalizing disorders are rare in generaladolescent population and questionnaires might capture less severe symptoms of thesedisorders, for example self-reported panic might capture physical symptoms of anxietyrather than panic attacks. However, symptoms of internalizing disorders are importantmarkers of psychopathology (Pickles Our results suggest that both homotypic and heterotypic continuity of depression andanxiety symptoms across adolescence and young adulthood is underpinned largely by stablegenetic influences, while non-shared environmental effects tend to be time- andsymptom-specific. The results have multiple implications for future molecular geneticsresearch and clinical practice in the context of co-morbidity. They affirm the need tocontinue examining how the risk and maintenance factors for internalizing psychopathologyoperate across development to inform successful prevention and intervention strategies.


L-sensor linear dynamic systems. Firstly, the paper establishes the fuzzy model for measurement condition estimation. Then, Generalized Kalman Filter design is performed to incorporate the novel neighborhood function and the target motion information, improving with an increasing number of active sensors. The proposed measurement selection approach has some advantages in time cost. As such, if the desired accuracy has been achieved, the parameter initialization for optimization can be readily resolved, which maximizes the expected lifespan while preserving tracking accuracy. Through theoretical justifications and empirical studies, we demonstrate that the proposed scheme achieves substantially superior performances over conventional methods in terms of moving target tracking under the resource-constrained wireless sensor networks.Moving target tracking in wireless sensor networks is of paramount importance. This paper considers the problem of state estimation for  A wireless network consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments . These set al. [et al. [et al. [et al. [et al. [et al. [et al. [et al. [et al. [et al. [et al. [et al. [Moving target tracking continuously reports the position of the target in terms of its coordinates to a fusion center or a central base station. It transfers one piece of sensor data to its coordinator, and determines its physical location relative to other neighboring coordinators . Moving et al.  proposed [et al.  proposed [et al.  formaliz [et al.  proposed [et al.  develope [et al.  proposed [et al.  presente [et al.  describe [et al.  addresse [et al.  proposed [et al.  used two [et al.  detectedMotivated by the above scenarios and concerns, the design of our approach relies on the prediction structure. In this paper, we propose a linear dynamic system with multiple sensors to track the target and monitor its surrounding area. The task is to extend the WSN lifespan without compromising the desired tracking accuracy. First, the paper establishes the fuzzy model for measurement condition estimation. Then, Generalized Kalman Filter (GKF) design is performed to incorporate the novel neighborhood function and the target motion information, improving with an increasing number of active sensors. The proposed measurement selection approach has some advantages in time cost. As such, if the desired accuracy has been achieved, the parameter initialization for optimization can be readily resolved, which maximizes the expected lifespan while preserving tracking accuracy.The rest of the paper is organized as follows. In n identical sensor nodes are densely deployed over a 2D area using a uniform random distribution. All nodes can only get connectivity information in neighbor nodes and measure Received Signal Strength (RSS) [r. These nodes are connected, that is to say at least one routing path exists between any pair of nodes. Note that two nodes are neighbor nodes if and only if i. The network consists of n nodes, and there are m anchor nodes and L-sensor linear dynamic system [nth sensor at time instant k. kth timestep, nth sensor, and We assume that th (RSS)  in sensoc system .(1)znk=kth timestep is shown in the matrix form [In the practical application, the system that provides such detecting measurements at the rix form .(2)Zk=Hh and v in Equation 12), EquaThe value of Equation , we can i. σ is a correction parameter to make Equation Sij can buations  or other information.i, i and j. In order to make the test more comprehensive, we test the impact of different communication range and number of anchor nodes on the EDE. All results are averaged over 100 different network deployments.Estimated distance error (EDE) is the average absolute difference between the estimated distance and corresponding real inter-node distance. In this section, we compare the values of EDE on three algorithms, including the method based on distance vector in hops (DV-HOP) , LGR andThe impact of communication range on EDE is shown in σ in Equation  is defined by [We set fined by .(32)RMSM is the total number of Monte Carlo test. Here, L-sensor linear dynamic system for measurement selection. After analyzing the relationship between distance and intersection area of neighborhood nodes, we describe the novel neighborhood function as position estimation. The position optimization is smoothed by using the linear GKF to produce better positioning performance. The position prediction from the GKF is utilized for parameter initialization in the probability–possibility transformation. Numerical experiments show that the proposed approach outperforms the existing algorithms in terms of EDE and average RMSE. In the future, we will implement a real world wireless sensor network to track moving targets.In this article, we have described the implementation of energy efficient moving target tracking in wireless sensor networks where measurements from a subset of sensors are employed at each time step. The three-step moving target tracking scheme is proposed to maximize the expected lifespan while preserving tracking accuracy. A fuzzy modeling method is developed under


Until recently, the cross-modal consequences of unisensory deprivation have been extensively studied in almost every sensory domain other than nociception. In this issue of PAIN®, Slimani et al. Their study has provided evidence that congenitally blind participants are hypersensitive to pain. Slimani et al. Slimani et al. The novel finding of pain hypersensitivity in blindness has several important implications for both basic and clinical science. This study is noteworthy for research on multisensory interactions and plasticity because it shows a strong link between vision and pain. This link is supported by a previous report of increased pain sensitivity in sighted volunteers who were temporarily visually deprived The ‘hypersensitivity to threat’ hypothesis b predictThe study by Slimani et al. Unfortunately, the assessment of thermal sensitivity requires expensive equipment, which could thwart routine testing of large samples of people. However, there are several low-cost alternative methods (e.g., punctate probes to stimulate Aδ mechanical fibers The hope is that the work by Slimani et al. The author is aware of no conflicts of interest regarding this commentary.


H/D values in water from Monte Carlo simulations of a general-purpose beamline for proton energies from 100 to 250 MeV. We also configured and tested the model on in-air neutron equivalent doses measured for a 75 MeV ocular beamline. Predicted H/D values from the analytical model and Monte Carlo agreed well from 100 to 250 MeV (10% average difference). Predicted H/D values from the analytical model also agreed well with measurements at 75 MeV (15% average difference). The results indicate that analytical models can give fast, reliable calculations of neutron exposure after proton therapy. This ability is absent in treatment planning systems but vital to second cancer risk estimation.Exposure to stray neutrons increases the risk of second cancer development after proton therapy. Previously reported analytical models of this exposure were difficult to configure and had not been investigated below 100 MeV proton energy. The purposes of this study were to test an analytical model of neutron equivalent dose per therapeutic absorbed dose  In many cases, proton therapy is dosimetrically advantageous compared to other forms of external beam radiation therapy because it allows for uniform target coverage with lower doses to healthy tissues ,2,3. Howet al. [et al. [Polf and Newhauser  reportednt vault ,11. This [et al. . Anferov [et al.  reported [et al. , which tThe purpose of this study was to improve an analytical model of neutronet al. [Building upon the methods of Perez-Andujar et al. , we imprThe analytical model forIn this work, several improvements have been made to the model. Previously, the model required interpolation ofr closed .The previous model relied on lookup tables of 32  250 MeV . In the et al. [The epithermal regime was modeled asr et al.  requiredet al. [Previous studies ,14 utiliet al.  which utet al. . MCNPX iet al. ,20,21,22Centre de Proton thérapie d’Orsay (CPO) in France in a single-scattering proton beamline dedicated to ocular tumor treatments. During the neutron measurements, a closed patient collimator was used together with a pristine Bragg peak. We selected 75 MeV proton beam energy because it is representative of ocular treatments at CPO. Measurements were taken in air.Measurements of3He proportional counter . It is known to be suitable for ambient dose equivalent measurements in the energy range from thermal to 20 MeV [3He proportional counter [Two instrument types were used to acquire neutron ambient dose equivalent, LB 6411  is a cono 20 MeV . Additio counter . The modThe measurements ofPreviously, the model was trained separately at each proton beam energy considered . In thisH/D.The model was trained separately for the 75 MeV measurements. This was necessary because of the considerable differences between the beamlines. Because the measured data from the ocular beamline consist of a single proton beam energy and measurements were taken in air, some modifications were necessary. Theet al. [et al. [The parameters governingr et al.  that ther et al. . Use of et al. [. et al. . We founMeasured and calculatedWe have improved an analytical model for predicting et al. [The major finding of this work is that an analytical model of neutronr et al.  requireset al. [Another encouraging confirmatory finding is that the analytical model is applicable to low energy proton beams such as those used in ocular treatments. It is important that the model be easily adaptable to other passive scattering treatment systems, so that it can have the greatest possible impact and find use at many different institutions. Importantly, Farah et al.  previouset al. [The results of this work are consistent with the findings of other studies. Perez-Andujar et al.  found thA major strength of this study is that the improved model relies on far fewer free parameters than previous works. The inclusion of measured data from a second passively-scattered proton therapy beamline is another strength of this study. Specifically, the analytical model was configured for use at the lower energy (75 MeV) and compared against experimental data to validate its utility to predict stray radiation from an ocular beamline.One limitation of this study is that we only benchmarked the model with measured data at a single proton beam energy for the ocular beamline. Additionally, the measured data was taken in-air and not in a water phantom. These limitations are minor because we demonstrated good agreement for the model compared with Monte Carlo simulatedet al. [et al. [Future work on leakage radiation from proton therapy should include research and development to translate the analytical models to clinical practice. Specifically, the model should be integrated into treatment planning systems to facilitate routine clinical dose assessments for patients with heterogeneous anatomy and irregular external surfaces. A study from our group has yielded promising preliminary results indicating that the integration of a similar analytical model into a radiotherapy treatment planning system is technically feasible and the leakage-dose algorithm is sufficiently fast for routine clinical treatment planning applications . Specifiet al. , and dose et al. ), and ite et al. ,31, and e et al. .In this work, we improved an analytical model of neutron


Acta Cryst. (2009), E65, o1325–o1326.Erratum to  et al. , one H atom was placed incorrectly.In the paper by Rohlicek  Since s al. 2014 were ablet al. (2014In our defence, in the powder study, we placed the H atoms geometrically according to a reasonable chemical structure for capecitabine, which shows the tautomeric H atom attached to the N atom of the carbamate group and the plausible formation of an intermolecular N—H⋯O hydrogen bond. As shown by Malińska  al. 2014, the H a al. 2014, therebyet al. (2009et al. (2014With respect to the fact that structure solution from powder diffraction data is based on the proposed molecular structure, readers should beware of the incorrectly placed H atom in Rohlicek  al. 2009 and they al. 2014.


This review presents an overview of the different techniques developed over the last decade to regulate the temperature within microfluidic systems. A variety of different approaches has been adopted, from external heating sources to Joule heating, microwaves or the use of lasers to cite just a few examples. The scope of the technical solutions developed to date is impressive and encompasses for instance temperature ramp rates ranging from 0.1 to 2,000 °C/s leading to homogeneous temperatures from −3 °C to 120 °C, and constant gradients from 6 to 40 °C/mm with a fair degree of accuracy. We also examine some recent strategies developed for applications such as digital microfluidics, where integration of a heating source to generate a temperature gradient offers control of a key parameter, without necessarily requiring great accuracy. Conversely, Temperature Gradient Focusing requires high accuracy in order to control both the concentration and separation of charged species. In addition, the Polymerase Chain Reaction requires both accuracy (homogeneous temperature) and integration to carry out demanding heating cycles. The spectrum of applications requiring temperature regulation is growing rapidly with increasingly important implications for the physical, chemical and biotechnological sectors, depending on the relevant heating technique. The development of lab-on-a-chip requires the integration of multiple functions within a compact platform, which is readily transportable and can deliver rapid data output. One such functionality is the control of temperature, either in terms of profile (homogeneous or gradient) or in terms of the accessible range, and in both cases with the greatest accuracy possible. Indeed, the regulation of temperature is a critical parameter in managing many physical, chemical and biological applications. Prominent examples of applications requiring tight temperature control are Polymerase Chain Reaction (PCR) ,13,14,15The review is organized as follows: The first sections focus on the different techniques reported to date. These techniques are described along with the corresponding specifications if explicitly stated in the original report see . Techniqi.e., by means of commercial heaters with some degree of integration, but entirely external approaches (such as using hot-plates) are not considered here,, i.e., the liquid is directly heated in the bulk material. In All the reported techniques, as well as the conditions reported , are summarized in a table at the beginning of the paper. Generally, it seems that there is currently no consensus on any given technique that would satisfy all the requirements specified by the complete range of applications; however each of the techniques described here has successfully demonstrated the integration of temperature control for specific applications.Note also that temperature mapping techniques are beyond the scope of the current paper, for this we refer the reader to the recent review by Gosse, Bergaud and Löw . This section describes techniques based on commercial heaters, either to heat liquids prior to being injected into the microsystem, (pre-heated liquids), or the incorporation of commercial components such as Peltier elements. Depending on the final application it is possible to generate either uniform temperature control or temperature gradients, as outlined in the next subsections.A number of techniques using pre-heated liquids have been reported for microfluidic devices. These methods utilize microheaters such as Peltier elements to establish either a uniform temperature or a constant gradient in a given region. Velve Casquillas and co-workers ,37 develThe previous example shows the potential to exploit external Peltier elements, typically by positioning these elements underneath a microchip. Maltezos and co-workers ,3 reportet al. [More sophisticated set-ups have been described by Khandurina et al.  who haveet al. [E. Coli K12-specific gene fragment. During thermal cycling, the PCR device is sandwiched between two Peltier elements  on the temperature distribution and the power required to circulate the fluid in the heat exchanger. The heating/cooling ramp of the PCR heat exchanger is equal to 150.82 °C/s, which is considerably higher than results reported elsewhere in the literature.Mahjoob et al.  introducet al. [It is also possible to generate temperature gradients using the pre-heated liquids approach as reported by Mao et al. . A lineaet al.  and its In a similar approach, Matsui and co-workers  integratet al. [i.e., 2D-readable system: abscissa with temperature, and ordinate with concentration). The temperature field of the chip is controlled by two Peltier elements located underneath a silicon wafer which forms a chip support to optimize thermal transfers, and generates regular temperature gradients of about 0.7 °C/mm along the storage channels. This original technique is simple and cheap and could potentially be used in high throughput studies, given the small amount of reagents needed (around 250 μL).Finally, the generation of temperature gradients using Peltier elements can be applied to map-out solubility phase diagrams. Laval et al.  devised Peltier elements are widely used to create hot/cold zones, and are able to generate a spatial distribution of temperature with impressive accuracy. However, for many techniques, these elements are not considered as an integral part of the microfluidic chip because of their size, which is typically several millimeters. However, methods have been developed to integrate heating or cooling functionalities directly into microfluidic systems. These approaches are presented in the following sections.et al. [We now turn to integrated techniques, from which heat diffuses from/to the integrated heating/cooling source. The first example we present derives from the use of a chemical reaction. In 2002, Guijt et al.  made useet al. in 2006 [2 flux. They concluded that the most efficient solvent they tested was di-ethyl ether with an angle of 10°, which offers the possibility to cool down to −20°C with a steady state for several minutes. This method is again cheap and clearly suited for microfluidic applications but requires further refinement of the heating control to work efficiently in PDMS channels. This kind of approach was optimized by Maltezos  in 2006  for coolThe following section concerns the most widely reported technique in the literature, based on Joule heating temperature control approaches ,44,45,46et al. [Thermal actuation of microfluidic valves by generating a heating pulse has recently been reported. Pitchaimani et al.  used a Pet al. [Similarly, Gu et al.  used a Pin situ fabrication of wires and surface patterning of metal resistors using classical microelectronic techniques. These techniques are summarized in two larger categories: the generation of a homogeneous temperature profile and generation of a temperature gradient.Finally, different temperature profiles may be required: either homogeneous as in PCR applications, or gradient-like for TGF or droplet actuation techniques. In both cases, it may be crucial to perform a temperature profile with the best achievable accuracy, although some applications do not require a sharp control. In order to meet such stringent requirements, different heating techniques and geometries of heaters have been investigated: the use of ionic liquids, The next two subsections are dedicated to spatial control of the temperature.et al. [To our knowledge, the only reported work using a conductive liquid is from De Mello et al. . The autet al. [The serpentine-like geometry was also studied by Lao et al.  with intet al. [25 multiplication factor of DNA. Each thermal zone is about 25 mm × 10 mm. This study shows a characterization of the microheaters used through the resistance versus temperature plot . The microfluidic system contains three heating regions of different temperatures together with microfluidic channels. The temperature cycling is achieved by making a loop on the three regions. In 2009, Wang et al.  designedet al.  in approet al. [In the same spirit of shape optimization, Selva et al. ,45 proviet al. ,78, and By patterning the substrate with an optimized resistor, it is possible to generate a homogeneous temperature within a cavity with great accuracy and with short response times (standard deviation below 1 °C and asymptotic regime reached after 2.2 s).et al. [vs. Temperature is done with an IR camera and reveals a good spatial homogeneity in the middle of the serpentine. It also shows a good linearity in the 45–105 °C range. They achieved a heating rate of 20 °C/s and a steady state error of about ±0.5 °C. With an applied voltage varying from 0.9 to 2.2 V, the authors obtained a temperature from 45 to 110 °C  it is necessary to generate temperature gradients, either in a controlled way (controlled shape of the temperature profile) or not. For given applications . Nguyen et al.  presente [et al.  reported [et al.  investiget al. [Another 1D droplet handling can be performed using the integration of a serpentine-like micro-heater which locally generates a temperature gradient together with a local decrease in the continuous phase viscosity. Considering such an integration in a 1D geometry, it is possible to control the breakup or switching of a droplet arriving in a T-junction as reported by Yap et al. ,19. The et al. [Jiao et al. ,21 preseIn such a configuration, it is possible to drive droplets by imposing a succession of different temperature gradients along the 2D substrate. The four microheaters actuated independently generate variable surface tension gradients. The droplet can be positioned anywhere in the channel depending on the strength of individual heaters .et al. [At a more integrated level, Darhuber et al. ,25,26,27et al. [Selva et al.  also repet al. [et al. [Using this resistor pattern, another phenomenon has been emphasized by Selva et al. : thermomet al. . Under s [et al.  report aet al. [etc.) and is capable of more than 10000-fold concentration of a dilute analyte.In order to generate a temperature gradient, copper blocks can also be integrated within a microsystem. Ross et al.  describeet al. [An interesting technique of embedded heaters is reported by Vigolo et al. . The autet al. [This technique can be combined with the pre-heated liquid technique as reported by Vigolo et al.  for theret al. [ was used to determine the degree of mixing in the chamber, where I is the normalized intensity of each pixel.Temperature gradient can also be used to generate natural convection for mixing purposes. Rapid and homogeneous mixing is difficult to achieve in microscale. Indeed, even if diffusion processes are favored in miniature fluidic systems, a pure diffusion-based mixing can be very inefficient, especially in solutions where macromolecules have a diffusion coefficient several orders of magnitude lower than that of most liquids. However, micromixing in chambers remains challenging even though many in-line micromixers have been developed and successfully demonstrated ,34. Kim et al.  presentei.e., without using a thermal source. Up to now, we have seen that temperature control can be performed either in an external way or by integrating heating resistors. In both cases, heat diffuses from a source towards the liquid of interest. This section is devoted to techniques able to heat the liquid in the bulk, Microwave dielectric heating is a fundamentally different approach because of its preferential heating capability and non-contact delivery energy. Induced and intrinsic dipole moments align themselves with a time-varying electric field (from 3 to 20 GHz). The energy associated is viscously dissipated as heat into the surrounding media with no interference from the substrate materials. Compared to conventional techniques, enhanced thermocycling rates and reduced reaction times can be achieved . Heatinget al. [Microwave power at several GHz is delivered to the channel by transmission line integrated in the microfluidics device. In most cases, a coplanar waveguide configuration is used. Shah et al.  carried et al.  was aligvs. various microwave frequencies. Experimental data are compared to a theoretical model based on classical microwave absorption theory. They observed a 0.88 °C·mW−1 temperature rise at 12 GHz and 0.95 °C·mW−1 temperature rise at 15 GHz. In agreement with the theory, they concluded that the temperature rise of the fluid is predominantly due to the absorbed microwave power. These results have been confirmed by recent works done on microwave dielectric heating of fluids [The device is characterized by the scattering (S) parameter and the temperature. The S-parameters are the transmission and reflection coefficients. The fluid temperature is obtained by measuring the temperature dependent fluorescence intensity of a dilute fluorophore, Rhodamine B, added to the fluid . Figure f fluids .et al. [Kempitaya et al.  generateThey report two distinct heating/cooling behaviors , it offers a cheap and spatially reconfigurable heat source that can be precisely addressed.et al. [0 = 514.5 nm) on a PDMS microchannel by using an inverted microscope. The aqueous phase is heated by adding 0.1 wt% of fluorescein . The maximum thermal gradient that can be obtained at the edge of the beam is given by P/w0 (P is the power of the laser) and reaches (for P around 100 mW) 10 to 20 °C/mm. The temperature gradient localized at the front of a droplet creates a surface tension gradient and induces droplet displacement in order to sort them. In et al. [In their study, Robert de Saint Vincent et al.  used a ln et al.  used theet al. [Kim et al.  also useet al. [via thermocapillary forces. Contrary to other works, the temperature gradient is generated by the laser absorption in the silicon substrate and not in the liquid. In order to create optically actuated thermocapillary forces, they used an absorbing substrate consisting of a 0.85-mm-thick glass slide coated with a 100-nm-thick layer of indium tin oxide, followed by a 1-μm-thick layer of hydrogenated amorphous silicon (a-Si:H), which absorbs light in the visible and UV wavelengths. The laser power used is 10 mW, and its wavelength is 635 nm. The magnification is 20 and the beam obtained is a 6 μm-diameter spot on the surface of the absorbing substrate. They managed gradients in the surrounding oil up to 4 °C/mm. As one can see in Ohta et al.  used thiet al. [Another application stemming from the use of a laser was reported by Weinert et al. . The autet al. [Hettiarachchi et al.  presenteThis section introduces a series of applications to illustrate the efficiency of reported heating techniques. We have tried as much as is possible to cover a range of different fields from the chemical, physical and biological sciences, without being exhaustive in any one domain; our purpose is rather to explore the diversity of microfluidic applications exploiting thermal control. The strategies and approaches vary from one application to another; while spatial temperature homogeneity is imperative for many biological applications; a rough temperature gradient is sufficient for most applications in digital microfluidics and a net temperature gradient is required for Temperature Gradient Focusing (TGF) and thermophoresis.in vitro [For biological applications, two main requirements have been reported: 1) maintaining the temperature at 37 °C to keep cells alive , the eff maintainin vitro ,79. Two bona fide microreactors. The growing demand for handling picoliter to nanoliter volumes of biological samples has driven the development of droplet techniques where a variety of processes, including mixing, splitting and heating are efficiently controlled: these approaches have been designated as digital microfluidics. Such a prospective, demands tight control of fundamental operations such as droplet merging, fission, transport, exchanges, redirection, and storage. This has rekindled interest in the Marangoni surface effect, which refers to tangential stresses induced along an interface by a surface tension gradient [Another approach is the generation of temperature gradients to drive droplets. Indeed, the use of droplet-based microfluidics  is largegradient . The prigradient  which regradient .i.e., a constant temperature gradient. The detection of chemical species at small concentrations (nanomolar or lower) in small volumes  is a core functionality of miniaturized bioanalytical devices. Temperature Gradient Focusing (TGF), on the other hand, involves the application of a temperature gradient across a microchannel or capillary. With an appropriate buffer, the temperature differential creates a gradient in both the electric field and the electrophoretic velocity. Ionic species can thus either be concentrated by balancing the electrophoretic velocity against the bulk flow, or separated according to their individual electrophoretic mobilities. In other words, tuning the temperature allows modulation of the electrophoretic mobility at will. Another application centered on the migration of small particles, is thermophoresis. Thermophoresis (Soret effect) is the phenomenon wherein small particles suspended in a fluid with a temperature gradient, experience a force in the direction opposite to that gradient [Conversely, the following applications, which focus on chemical applications, demand a net temperature gradient, gradient ,89. ThisFinally, thermal control has found application in a broad gamut of diverse fields such as the development of efficient and rapid mixing techniques (for example solutions with low Reynolds number), or the screening of solubility diagrams to study protein crystallization.etc. that are summarized in the following table. This table underlines the fact that despite there being no paradigm to implement microheaters, a huge improvement has been performed in terms of level of integration, cost and response time showing very good ability to integrate the focused application. However, an important feature has been emphasized by several authors [Applications concerned with the control of temperature are numerous and focus on physical, chemical and biotechnological issues. This article shows the great variety of technologies that have been developed to achieve integrated temperature control. All these techniques present different advantages or drawbacks in terms of easiness of integration, cost, area of control, accuracy of the control,  authors ,30,45,82et al. [i.e., an accurate temperature profile is not necessary. For biological applications requiring a homogeneous temperature at the cavity level, Joule heating connected with shape optimization to avoid side effects has been shown to be very efficient with a high level of integration [−1·K−1 by adding 21% of silver powder. Such technology would avoid extra steps in the microfabrication process but would require optimization of thicknesses in order to proceed to optical measurements.As stated in the introduction, several strategies have been adopted to control the temperature within a microsystem, and most of the focused applications have been successfully achieved. It is thus difficult to isolate a technique that could be a paradigm. However, for some applications it is possible to extract a technique—that seems to be more accurate and show a high level of integration. In the case of droplet handling, Darhuber et al. ,25,26,27egration ,13,45. Aegration . Finallyegration , such anegration  succeede


Although subclinical hypothyroidism (SH) is a common clinical problem, its diagnosis tends to be incidental. According to the definition, it should be asymptomatic, only detectable by screening. The presence or coincidence of any symptoms leads to L-thyroxine treatment. The clinical presentation, especially in younger patients with subclinical hypothyroidism, is still under dispute. Accordingly, the aim of this paper was to review the literature from the past seven years. The literature search identified 1,594 potentially relevant articles, of which 24 met the inclusion criteria. Few studies focus on the symptomatology of subclinical hypothyroidism, and most of them analyzed a small number of subjects. A significant correlation was found by some authors between subclinical hypothyroidism and a higher risk of hypertension, dyslipidemia, and migraine. No evidence of the impact of subclinical hypothyroidism on weight, growth velocity, and puberty was revealed. As the quality of most studies is poor and no definite conclusions can be drawn, randomized, large-scale studies in children and adolescents are warranted to determine the best care for patients with SH. From the biochemical point of view, subclinical hypothyroidism (SH) is characterized by mildly elevated serum TSH concentrations, with normal concentrations of serum free and total triiodothyronine T3) and thyroxine T4), without the typical symptoms of thyroid disease. SH prevalence in adults ranges from 4 to 10% . Accordi and thyr, withoutIn the adult population with subclinical thyroid disease, SH is associated with a risk of progression to overt thyroid disease, lipid disorders, increased risk of atherosclerosis, and mortality due to cardiovascular diseases . The pubAccordingly, the aim of this paper was to analyze studies reporting signs and symptoms presented by children and adolescents diagnosed with subclinical hypothyroidism.In order to identify studies evaluating the clinical manifestations and symptoms of subclinical hypothyroidism in children, a systematic PubMed literature search was conducted. The search terms used in the medical subject headings (MeSH) included ) as well as  AND (“infant” [MeSH Terms] OR “child” [MeSH Terms] OR “adolescent” [MeSH Terms])) and SH hypothyroidism [All Fields] AND “humans” [MeSH Terms] AND (“infant” [MeSH Terms] OR “child” [MeSH Terms] OR “adolescent” [MeSH Terms]) and hyperthyrotropinemia [All Fields] AND “humans” [MeSH Terms] AND (“infant” [MeSH Terms] OR “child” [MeSH Terms] OR “adolescent” [MeSH Terms]). These terms were combined in various ways to generate a wider search.In addition, the references of selected articles were checked with a view to identify papers not detected by our search strategy. Only full-length publications that met the following criteria were included: (1) long-term prospective or retrospective studies regarding the clinical signs of SH in the pediatric cohort; (2) only studies in English; (3) studies published between January 2008 and December 2014. Exclusion criteria were the following: (1) studies including patients with chronic systematic diseases, genetic syndromes, or autoimmune disorders or under concomitant therapy with lithium salts, antiepileptic agents, glucocorticoids, or iodinated drugs; (2) studies regarding the treatment and effects of L-thyroxine replacement therapy. At least two authors independently selected articles for inclusion and exclusion criteria .After reviewing 1,594 titles, abstracts, and full-length texts, 24 articles meeting the inclusion criteria were selected for the final analysis –31. TherIn their cross-sectional controlled long-term study of 36 children with SH and controls, Cerbone et al.  assessedIn a case-control study, Kuiper and van der Gaag  demonstrSome studies have confirmed the relationship between the levels of TSH and FT3 and change of body weight. The level of FT4 remained stable during follow-up. Leptin was hypothesized to link the weight status with TSH. This would suggest that TSH and FT3 concentrations in obese subjects are a consequence rather than the cause of obesity –15.Reinehr et al.  analyzedSimilar conclusions were drawn by Baş et al. , who obsThe study by Grandone et al.  encompasThe association between TSH, FT3, FT4, and weight status, as well as their changes during and after a lifestyle intervention in obese children, was also studied by Wolters et al. . They evTwo other studies investigating the correlation between BMI in obese children and hyperthyrotropinemia have produced interesting findings. Hari Kumar et al.  comparedRadetti et al.  investigR = 0.31; P = 0.02) were independently caused by both younger age and overweight/obesity status.The multicenter study by Rapa et al.  was baseIn a study that included 30 SH children and 36 controls, Cerbone et al.  evaluateErgür et al.  conducteZ-scores were found to be higher in subjects with subclinical hypothyroidism than in euthyroid subjects; in males, the scores increased linearly with increasing TSH.In their cross-sectional trial, Chen et al.  investigIttermann et al.  evaluateCerbone et al.  in a croPositive correlation between the components of the metabolic syndrome and serum TSH was also found in Chinese adolescents by Zhang et al. .In their cross-sectional controlled long-term trial, Cerbone et al.  also anaZ-scores (BTT Z-scores).di Mase et al.  in theirOne cross-sectional study conducted by Fallah et al.  assessedP = 0.014) and female gender (P = 0.047). The conclusions were as follows: (1) initial normal or slightly elevated TSH levels are likely to remain normal or spontaneously normalize without treatment; (2) patients with initial levels higher than 7.5 mU/L, particularly girls, are at a greater risk for persistent abnormal TSH concentration.Lazar et al.  presenteAlso Wasniewska et al.  in theirIn their cross-sectional controlled long-term study, Cerbone et al.  found thRapa et al.  concludeCho et al.  investigRapa et al.  in theirTwo case-control studies , 30 asseSakka et al.  studied Kratzsch et al.  observedThe definition of SH is purely biochemical . The estThe analysis of SH-related symptoms was based on two different types of studies. In the first type, SH confirmation was sought as a result of symptoms/clinical presentation , 26–30. We only analyzed articles in which subjects presented biochemically pure SH. The prevalence of SH in children and adolescents in the analyzed literature was between 2.9% and 14.1% , 21, 25 SH should be distinguished from physiological or transiently increased TSH in the serum, especially during the recovery phase from nonthyroidal illnesses or after subacute, painless thyroiditis. For this reason, serum TSH should be checked after 3–6 months . This obRarely, higher serum TSH concentrations are seen in patients with TSH-receptor mutations causing mild TSH resistance. It can affect up to 0.6% of white population and should be suspected in positive family history of elevated TSH, not coexisting with thyroid autoimmunity .Subclinical hypothyroidism is a common clinical problem. According to the definition, SH is asymptomatic and detectable only by screening. However, there are a lot of controversies concerning population screening for SH as the benefits of therapy are not proven. Single placebo-controlled studies in older populations confirmed that screening and treatment by L-thyroxine improve the quality of life in only 1% of individuals . The symOur study limitation is searching in PubMed base only and restricting the search to English language. Probably a systematic search across multiple databases would yield more results. However, as the quality of most studies is poor and no definite conclusions can be drawn, randomized, large-scale studies in children and adolescents are warranted to determine the best care for patients with SH.


Root resorption (RR) is defined as the loss of dental hard tissues because of clastic activity inside or outside of tooth the root. In the permanent dentition, RR is a pathologic event; if untreated, it might result in the premature loss of the affected tooth. Several hypotheses have been suggested as the mechanisms of root resorption such as absence of the remnants of Hertwig's epithelial root sheath (HERS) and the absence of some intrinsic factors in cementum and predentin such as amelogenin or osteoprotegerin (OPG). It seems that a barrier is formed by the less-calcified intermediate cementum or the cementodentin junction that prevents external RR. There are several chemical strategies to manage root resorption. The purpose of this paper was to review several chemical agents to manage RR such as tetracycline, sodium hypochlorite, acids , acetazolamide, calcitonin, alendronate, fluoride, Ledermix and Emdogain. Root resorption (RR) is the loss of dental hard tissues as a result of clastic activities within the pulp or periodontium. It might occur as a physiologic or pathologic phenomenon. RR in the primary dentition is a normal physiologic process except when it occurs prematurely , 2. The Etiology of root resorptionRR occurs in two phases: injury and stimulation. Injury is related to non-mineralized tissues covering the external surface of the root (pre-cementum) or internal surface of the root canal (predentin) , 5. The Without further instigation of the clastic cells, resorption is self-limiting. If the damaged surface is small, repair with cementum-like tissue will occur within 2 to 3 weeks. If the damaged root surface is large, bone cells attach to the root in competition with cementum-producing cells and ankylosis takes place , 5. ContMechanisms of root resorptionet al. [Several hypotheses have been suggested regarding the mechanisms of RR. According to a hypothesis, the remnants of Hertwig's epithelial root sheath (HERS) surround the tooth root, like a net impart, which is resistant to resorption and subsequent ankylosis , 6. Haseet al.  showed tκB ligand (RANKL). Binding to OPG reduces RANKL concentration and thereby inhibits its ability to bind to receptor activator of nucleic factor κB (RANK) receptors on the surface of osteoclast precursors (circulating monocytes) and stimulate osteoclast production [OPG is a decoy receptor by binding to the receptor activator of nuclear factor oduction . Another hypothesis regarding some forms of external RR is the barrier formed by the less highly calcified intermediate cementum or the cementodentin junction. The intermediate cementum is the innermost layer of cementum which creates a barrier between the dentinal tubules and the periodontal ligament. Under normal conditions, this barrier does not allow irritants such as bacterial by-products to pass from an infected pulp space to stimulate an inflammatory response in the adjacent periodontal ligament. If the intermediate cementum is lost or damaged, pro-inflammatory mediators may diffuse from an infected pulp space into the periodontal ligament, setting up an inflammatory response and subsequent external inflammatory RR .Materials used to manage root resorptionTetracyclinesTetracyclines, including tetracycline-HCl, minocycline, demeclocycline and doxycycline, are a group of broad-spectrum antibiotics that are effective against a wide range of microorganisms . TetracyInflammatory diseases such as periodontitis include a pathological excess of tissue collagenases, which may be blocked by tetracyclines, leading to enhanced formation of collagen and bone formation .et al. [Based on the hypothesis that microorganisms reach the apical area of the recently replanted tooth from the oral cavity , and considering the inhibitory action of tetracyclines in preventing this route of bacterial contamination, Cvek et al.  developeet al. .et al. [Bryson et al.  evaluateTerranova  showed tSodium hypochloriteet al. [Because of its excellent antibacterial activity and its ability to dissolve necrotic tissues, various concentrations of sodium hypochlorite (NaOCl) have been recommended for removing necrotic periodontal ligament remnants . The beset al.  protocolAcidsHydrochloric acidet al. [Hydrochloric acid has also been used in association with an enzyme, hyaluronidase, with the aim of decalcifying the cementum without denaturing the collagen matrix and has been shown to significantly decrease RR . Nordenret al.  evaluatePhosphoric acid et al. [Phosphoric acid at 50% concentration has been used for the same purpose, and the results revealed that its use alone increased the occurrence of RR . Accordiet al.  protocolCitric acidIn an attempt to expose collagen fibers on root cementum and promote a contact surface for re-attachment of periodontal ligament collagen fibers, treatment of root surface with citric acid has been proposed. Large number of ankylotic areas and replacement resorption has been observed after treating the root surface with citric acid -25. AfteAscorbic acidAscorbic acid (vitamin C) is a fundamental vitamin in all body tissues. It is essential for the hydroxylation of proline and lysine, which are very important during the synthesis of collagen. Its absorption depends on tissue concentration. If available at an appropriate concentration, ascorbic acid is responsible for maintaining the efficacy and the phagocytosis activity of leucocytes .Vitamin C also plays a role in osteogenesis by the activation of alkaline phosphatase and increase in the functional activity of osteoblasts . VitaminAcetazolamide Acetazolamide is a carbonic anhydrase inhibitor that is used to treat several diseases such as glaucoma, epileptic seizures, cystinuria, periodic paralysis and dural ectasia . Mori anCalcitoninCalcitonin is a hormone synthesized by the thyroid gland which is a proven potent inhibitor of clastic cells and has been indicated for the treatment of external RR. The influence of this hormone as an intracanal dressing after tooth replantation has been investigated, and it has been observed that it causes a decrease in inflammatory RR and better control of the sequelae of dental trauma even in cases with uncertain prognosis .In an experimental study in dogs, Caldart  histometThe association of calcitonin and CH as an intracanal medication for replanted teeth has been advocated mainly because of the recognized capacity of reducing the osteoclastic activity, interfering in the proliferation, motility, and vitality of these cells, and reducing the resorption rate. However, this association has not provided better results than CH alone .Alendronate Alendronate is currently being used to inhibit pathologic osteoclast-mediated hard tissue resorption in diseases such as Paget's disease, osteoporosis and osteoclastic malignancies of bone . The affet al. [et al. [in vitro. Moreira et al. [in vitro as well as in vivo. Lustosa-Pereira et al. [et al. [et al. [et al. [Levin et al.  assessed [et al.  indicatea et al.  showed ta et al.  indicate [et al.  assessed [et al.  evaluate [et al.  showed tLedermixi.e. triamcinolone and demeclocycline) are capable of diffusing through dentinal tubules and cementum to reach the periodontal and periapical tissues [et al. [Ledermix is a glucocorticosteroid-antibiotic compound. Today, Ledermix paste remains a combination of the same tetracycline antibiotic, demeclocycline HCl (at a concentration of 3.2%), and a corticosteroid (1% triamcinolone acetonide), in a polyethylene glycol base . The two tissues . Abbott  [et al.  showed tin vivo [-3 to 10-6 mg/mL reversibly. Furthermore, mixing with Pulpdent paste did not modify this anti-mitotic effect [et al. [et al. [et al. [It has been demonstrated histologically that Ledermix eliminated experimentally induced external inflammatory RR in vivo . Furtherin vivo . Ledermic effect . Thong e [et al.  found th [et al.  evaluate [et al.  evaluate [et al.  evaluate [et al. . EmdogainEnamel matrix derivative (EMD) in the form of a purified acid extract of proteins from pig enamel matrix  has been successfully employed to restore functional periodontal ligament, cementum and alveolar bone in patients with severe attachment loss , 54.One attractive possibility for application of Emdogain is for their use in replantation procedures with avulsed teeth. The underpinning mechanism is that root surface conditioning with amelogenin could prevent RR and ankylosis, and stimulate periodontal ligament formation after repositioning of the avulsed tooth. Some early case-reports and animal experimental findings suggested that EMD could be used as a bioactive root conditioning for reintegration of avulsed teeth , but subIn summary, interesting data on the utilization of amelogenin for replantation of avulsed teeth has accumulated. It seems plausible that amelogenin can stimulate regeneration of the tooth attachment apparatus even in cases where the tooth has been stored for significant time outside the oral cavity. However, additional treatment is needed to ensure stable and predictive treatment outcomes, and new protocols for combination of amelogenin treatment with anti-inflammatory and anti-microbial drugs must be developed and tested before the full potential of amelogenin can be exploited in dental traumatology.FluorideSeveral studies have recommended the use of fluoride solutions in different forms and concentrations to treat the root surface in cases of delayed tooth replantation, assuming that the demineralized dentin surface would be more prone to fluoride incorporation and might become more resistant to resorption. et al. [et al. [et al. [Among the fluoride solutions, the use of 2% acidulated sodium phosphate fluoride has shown a decreased inflammatory RR and the predominance of areas of ankylosis and replacement resorption -62. Accoet al.  fluoride [et al.  showed t [et al.  did not et al. [et al. [2 to the root surface prior to replantation effectively reduces resorptive processes during the first postoperative weeks. By subsequently treating the root surface with tetracycline, the adverse effect of SnF2 on periodontal connective tissue repair reduced. In a study on dogs' teeth, Selvig et al. [2 followed by tetracycline resulted in complete absence of inflammatory resorption and ankylosis in the short-term experiment. In another study, Selvig et al. [2 solution from 1% to 0.1% may result in less persistent inflammation, however at the cost of less complete prevention of inflammatory resorption and ankylosis. Kameyama et al. [In a study on monkeys' teeth, Barbakow et al.  showed t [et al.  indicateg et al.  showed tg et al.  indicatea et al.  revealedet al. [2, saturated citric acid, or saline control in conjunction with periodontal flap surgery. According to their findings SnF2-treated teeth healed with significantly longer junctional epithelium, less connective tissue repair to the root surface, and less bone regeneration than citric acid and control teeth. New cementum formation was limited in all treatment groups. RR was observed in almost all teeth exhibiting connective tissue repair, however to a lesser amount and not as frequent in SnF2 treated teeth due to limited connective tissue repair. Poi et al. [et al. [Wikesjo et al.  evaluatei et al.  showed t [et al.  assessedi) Tetracyclines have antimicrobial and anti-resorptive activity.ii) Treatment of root surface with SnF2 followed by tetracycline resulted in complete absence of inflammatory resorption and ankylosis in short-term. iii) Ascorbic acid is capable of influencing tissue repair. iv) Acetazolamide is effective against root resorption. v) Combining calcium hydroxide with calcitonin seems to be effective in controlling inflammatory root resorption. vi) Alendronate is effective on inflammatory root resorption but has no effect on replacement resorption. vii) Ledermix prevents inflammatory root resorption.viii) Emdogain can support functional healing and periodontal regeneration after replantation, even when the avulsed teeth have a severely compromised cementum layer.


To the Editor,1 recently published in ArquivosBrasileiros de Cardiologia. The investigators reported that rates of atrialfibrillation (AF) recurrence were similar in hyperthyroid and euthyroid patients andthat the duration of AF was the only predictor of AF recurrence in both.I have read with great interest the article entitled "Predictors of Atrial FibrillationRecurrence in Hyperthyroid and Euthyroid Patients" by Gürdogan et al.,2 have reported that a lowserum thyroid-stimulating hormone (TSH) level is an independent risk factor for AF. Allother factors predisposing to AF were mentioned and discussed in that article.Hyperthyroidism is a well-known risk factor for paroxysmal and permanent AF. Marrakchi etal.3 have found astrong relationship between vitamin D deficiency and nonvalvular AF. Serum vitamin Dlevels correlated with high sensitive C-reactive protein levels and left atrialdiameter, and were significantly associated with AF in Chinese patients with nonvalvularpersistent AF.4 Hanafy et al.5 have revealed the directelectromechanical effects of vitamin D administration on the left atrium and found thatvitamin D could effectively prevent and terminate AF.Additionally, Demir et al.1 should have reported the vitamin D levels of the patients intheir study and discussed the association between the levels of this vitamin and AFrecurrence.In the light of this knowledge, Gürdogan et al. Arquivos Brasileiros deCardiologia.1We are pleased that Dr. Cerit showed great interest in our article entitled''Predictors of Atrial Fibrillation Recurrence in Hyperthyroid and EuthyroidPatients'' published in 3 However, the relationship between this deficiencyand nonvalvular AF is not dependent on the occurrence of thyroid disorder. In thestudy published by Demir et al.,2the TSH levels were normal in all AF groups. In addition, thyroid dysfunction was anexclusion criterion in the studies by both Demir et al.2 and Chen et al.3 We did not evaluate the vitamin D levels in our study'sparticipants, which we can add as a limitation of our research. However, theparticipants in our study did not report any symptom or treatment of vitamin Ddeficiency. After thyroid surgery, in particular, patients may have vitamin Ddeficiency and hypothyroidism, but none of the patients in our study had priorthyroid surgery.Recent studies have found that vitamin D deficiency is related to nonvalvularAF.Considering the above, large-scale trials are still necessary to evaluate therelationship between vitamin D levels, thyroid function, and AF. We thank Dr. Ceritfor this great contribution to our work.Dr. Hasan ARI


On the basis of the continuum theory of micromagnetics, the correlation function of the spin-misalignment small-angle neutron scattering cross section of bulk ferromagnets is computed and discussed. e.g. elemental polycrystalline ferromagnets, soft and hard magnetic nanocomposites, nanoporous ferromagnets, or magnetic steels) is computed. For such materials, the spin disorder which is related to spatial variations in the saturation magnetization and magnetic anisotropy field results in strong spin-misalignment scattering dΣM/dΩ along the forward direction. When the applied magnetic field is perpendicular to the incoming neutron beam, the characteristics of dΣM/dΩ  are determined by the ratio of magnetic anisotropy field strength Hp to the jump ΔM in the saturation magnetization at internal interfaces. Here, the corresponding one- and two-dimensional real-space correlations are analyzed as a function of applied magnetic field, the ratio Hp/ΔM, the single-particle form factor and the particle volume fraction. Finally, the theoretical results for the correlation function are compared with experimental data on nanocrystalline cobalt and nickel.On the basis of the continuum theory of micromagnetics, the correlation function of the spin-misalignment small-angle neutron scattering cross section of bulk ferromagnets ( Svergun & Koch, 2003e.g. in the analysis of polymers  is a very popular method for investigating nanoscale structural and magnetic inhomogeneities in the bulk of materials. In most situations, SANS data are analyzed in reciprocal space, by fitting a particular model to the experimental SANS cross section. An alternative real-space approach to analyzing SANS data is the computation of the (auto)correlation function of the system, for instance by means of the indirect Fourier transformation technique  shows a sketch of the nuclear (grain) microstructure of such a material, and Fig. 1b) displays qualitatively the magnetic (spin) distribution at a nearly saturating applied magnetic field.We consider polycrystalline statistically isotropic bulk ferromagnets. Examples of such materials are inert-gas condensed single-phase elemental ferromagnets , the elastic unpolarized SANS cross section V is the scattering volume, For the scattering geometry where the applied magnetic field via the function As shown by Honecker & Michels 2013, near mae.g. particle–matrix) interfaces. The corresponding (dimensionless) micromagnetic response functions can be expressed as A: exchange-stiffness parameter; q and e.g. Fig. 11 in §6.2et al., 2014The anisotropy-field scattering function (in units of h depend only on the magnitude i.e.By assuming that the functions 3.2.b), the total unpolarized SANS cross section et al., 1999For the scattering geometry where the external magnetic field 4.et al., 2003et al., 2004Before addressing the magnetic correlation functions, we will briefly recall the corresponding well known results from nuclear SANS theory Therefore, we define the correlation function We remind the reader that q and the direction θ of the scattering vector e.g. Fig. 11 in §6.2via the Fourier coefficients et al., 2012et al., 2014i.e. with j’, whereas Bessel functions are represented with an upper-case ‘J’. Equation (36)The spin-misalignment SANS cross section for the perpendicular scattering geometry depends on both the magnitude et al., 2014Since for statistically isotropic bulk ferromagnets In a SANS experiment, only the components of the momentum-transfer vector yz plane. By introducing the nth-order Bessel function AIn Appendix 5.q of the momentum-transfer vector i.e.In order to solve equation (36)i.e. the magnitude Under these assumptions (same size and shape), n ranging between 6 and 8  microstructure 6.The following materials parameters were used in the calculations: saturation magnetization 6.1.All results in this section are obtained by numerical integration of equations (45)i.e.Fig. 4b)]. For the chosen limiting case of Increasing et al., 2013b), we note that the correlation functions of bulk ferromagnets enter the origin et al., 2013k is a constant). This observation may be compared to the well known result for nuclear particle scattering, where (for isolated uniform particles) the first derivative of r, the correlation function can be expanded as  and 7−1 and For soft magnets , the following relation for R; length: L) .It is seen in Fig. 8a) and correlation length . In order to model the effect of dense packing, we have used the Percus–Yevick hard-sphere structure factor for R.Finally, Fig. 9th Fig. 9b. In ori.e. with increasing interparticle interactions, we progressively introduce, in addition to the original (diffuse) spin-misalignment length e.g. the hump in It is clearly seen that with increasing particle volume fraction η the range of the correlations decreases. However, the characteristic features of the structure factor only become visible at relatively large values of η (above about 20%), while at the lower end of η values both The field dependence of this feature is depicted in Fig. 106.2.a)–11d) show a)–11d), from a spike-type anisotropy at low fields (a) to a clover-leaf-shaped anisotropy at large fields (d), is related to the field dependence of the Fourier coefficients and demonstrates that different terms in the response functions  do not R of both materials are in the range 8–13 nm, slightly smaller than the ones estimated previously . Therefore, the finding et al., 2003A value for Co using equation (41)et al., 2003e.g. nanocomposites (Michels et al., 2006As is seen in Fig. 147.via a structure factor. The result for et al., 2013et al., 2013et al., 2014et al., 2015et al., 2015On the basis of a recent micromagnetic theory for the magnetic SANS cross section of inhomogeneous bulk ferromagnets, we have studied the corresponding magnetic field-dependent spin-misalignment correlations in real space. The correlation function