Outlier Regions Research Articles

Event-Based Anomaly Detection for Searches for New Physics

This paper discusses model-agnostic searches for new physics at the Large Hadron Collider using anomaly-detection techniques for the identification of event signatures that deviate from the Standard Model (SM). We investigate anomaly detection in the context of a machine-learning approach based on autoencoders. The analysis uses Monte Carlo simulations for the SM background and several selected exotic models. We also investigate the input space for the event-based anomaly detection and illustrate the shapes of invariant masses in the outlier region which will be used to perform searches for resonant phenomena beyond the SM. Challenges and conceptual limitations of this approach are discussed.

Underwater enhancement based on a self-learning strategy and attention mechanism for high-intensity regions

Images acquired during underwater activities suffer from environmental properties of the water, such as turbidity and light attenuation. These phenomena cause color distortion, blurring, and contrast reduction. In addition, irregular ambient light distribution causes color channel unbalance and regions with high-intensity pixels. Recent works related to underwater image enhancement, and based on deep learning approaches, tackle the lack of paired datasets generating synthetic ground-truth. In this paper, we present a self-supervised learning methodology for underwater image enhancement based on deep learning that requires no paired datasets. The proposed method estimates the degradation present in underwater images. Besides, an autoencoder reconstructs this image, and its output image is degraded using the estimated degradation information. Therefore, the strategy replaces the output image with the degraded version in the loss function during the training phase. This procedure misleads the neural network that learns to compensate the additional degradation. As a result, the reconstructed image is an enhanced version of the input image. Also, the algorithm presents an attention module to reduce high-intensity areas generated in enhanced images by color channel unbalances and outlier regions. Furthermore, the proposed methodology requires no ground-truth. Besides, only real underwater images were used to train the neural network, and the results indicate the effectiveness of the method in terms of color preservation, color cast reduction, and contrast improvement.

Comparative modeling, comparative molecular docking analyses, and revealing of potential binding pockets of MDM-2: A candidate cancer gene

MDM-2 is also known as E3 ubiquitin-protein ligase encoded by Mdm-2. MDM-2 is an important negative regulator of p53 tumor suppressor and performs key function as an inhibitor of p53 transcriptional activation and E3 ubiquitin ligase. MDM-2 also plays significant role in human cancers and therapeutic target. Hundred different structures were predicted through comparative modeling, threading and ab initio approaches followed by the evaluation of predicted structures through various evaluation tools including ERRAT, ProSa-web, Rampage, molprobidity, verify3D and Anolea. The selected 3D structure of MDM-2 showed 13 α- helix chains, 2 β-pleated sheets along with 97.4468% overall quality factor of the predicted structure. Interestingly, it was observed that only 4.5% residues were present in outlier region and the observed errors were fixed. Moreover, 91.1% residues of the selected structure were present in favored region and 8.9% in allowed region having -6.0 Z-score. High throughput virtual screening and comparative molecular docking studies was performed. Four novel compounds have been reported that showed minimum binding energy (-8.1 Kcal/mol) and maximum binding affinity against MDM-2. Molecular docking analyses revealed that Ser154, Arg155, Pro156, Ser157, Lys185, Ser186, Ser188, Ser190, Ile189, Val247, Glu257, Asp173, Glu174, Glu178, Arg161, Ard181, Lys182, Arg183 and His184 residues are significant residues for therapeutic drug targets. The reported compounds showed effective energy scores. In addition, the site-directed mutagenesis may be helpful for further analyses. The reported compounds may act like potent drug compounds against MDM-2.

Unsupervised Learning of Monocular Depth and Ego-Motion with Optical Flow Features and Multiple Constraints.

This paper proposes a novel unsupervised learning framework for depth recovery and camera ego-motion estimation from monocular video. The framework exploits the optical flow (OF) property to jointly train the depth and the ego-motion models. Unlike the existing unsupervised methods, our method extracts the features from the optical flow rather than from the raw RGB images, thereby enhancing unsupervised learning. In addition, we exploit the forward-backward consistency check of the optical flow to generate a mask of the invalid region in the image, and accordingly, eliminate the outlier regions such as occlusion regions and moving objects for the learning. Furthermore, in addition to using view synthesis as a supervised signal, we impose additional loss functions, including optical flow consistency loss and depth consistency loss, as additional supervision signals on the valid image region to further enhance the training of the models. Substantial experiments on multiple benchmark datasets demonstrate that our method outperforms other unsupervised methods.

Pleiotropy facilitates parallel adaptation in sticklebacks.

Highly pleiotropic genes are predicted to be used less often during adaptation, as mutations in these loci are more likely to have negative fitness consequences. Following this logic, we tested whether pleiotropy impacts the probability that a locus will be used repeatedly in adaptation. We used two proxies to estimate pleiotropy: number of phenotypic traits affected by a given genomic region and gene connectivity. We first surveyed 16 independent stream‐lake and three independent benthic‐limnetic ecotype pairs of threespine stickleback to estimate genome‐wide patterns in parallel genomic differentiation. Our analysis revealed parallel divergence across the genome; 30%–37% of outlier regions were shared between at least two independent pairs in either the stream‐lake or benthic‐limnetic comparisons. We then tested whether parallel genomic regions are less pleiotropic than nonparallel regions. Counter to our a priori prediction, parallel genomic regions contained genes with significantly more pleiotropy; that is, influencing a greater number of traits and more highly connected. The increased pleiotropy of parallel regions could not be explained by other genomic factors, as there was no significant difference in mean gene count, mutation or recombination rates between parallel and nonparallel regions. Interestingly, although nonparallel regions contained genes that were less connected and influenced fewer mapped traits on average than parallel regions, they also tended to contain the genes that were predicted to be the most pleiotropic. Taken together, our findings are consistent with the idea that pleiotropy only becomes constraining at high levels and that low or intermediate levels of pleiotropy may be beneficial for adaptation.

Ironsmith: An automated pipeline for QSM-based data analyses

Quantitative susceptibility mapping (QSM) is an MRI-based, computational method for anatomically localizing and measuring concentrations of specific biomarkers in tissue such as iron. Growing research suggests QSM is a viable method for evaluating the impact of iron overload in neurological disorders and on cognitive performance in aging. Several software toolboxes are currently available to reconstruct QSM maps from 3D GRE MR Images. However, few if any software packages currently exist that offer fully automated pipelines for QSM-based data analyses: from DICOM images to region-of-interest (ROI) based QSM values. Even less QSM-based software exist that offer quality control measures for evaluating the QSM output. Here, we address these gaps in the field by introducing and demonstrating the reliability and external validity of Ironsmith; an open-source, fully automated pipeline for creating and processing QSM maps, extracting QSM values from subcortical and cortical brain regions (89 ROIs) and evaluating the quality of QSM data using SNR measures and assessment of outlier regions on phase images. Ironsmith also features automatic filtering of QSM outlier values and precise CSF-only QSM reference masks that minimize partial volume effects. Testing of Ironsmith revealed excellent intra- and inter-rater reliability. Finally, external validity of Ironsmith was demonstrated via an anatomically selective relationship between motor performance and Ironsmith-derived QSM values in motor cortex. In sum, Ironsmith provides a freely-available, reliable, turn-key pipeline for QSM-based data analyses to support research on the impact of brain iron in aging and neurodegenerative disease.

Design of classification model on high-dimensional imbalance data of motor bearing fault

According to the characteristics of high-dimensional imbalance distribution of motor bearing fault data, a design scheme of classification model is proposed for the high-dimensional data reduction problem in the classification algorithm. For details: Combining standard particle swarm optimization algorithm and random forest algorithm, a new high-dimensional data reduction algorithm is proposed. Aiming at the imbalance problem of data categories in the classification algorithm, we proposes to use machine learning under the sum of squares of dynamic deviations criterion to divide the minority sample data set into mixed regions, high-purity minority sample regions and outlier regions, and then use smote algorithm to complete the data equalization processing, so as to make the sample data equalization processing more reasonable, Focusing on the task of motor bearing fault classification, a design scheme of using standard particle swarm optimization algorithm to improve the least squares support vector machine model is proposed.

Genomic signatures of parallel alpine adaptation in recently evolved flightless insects

Natural selection along elevational gradients has potential to drive predictable adaptations across distinct lineages, but the extent of such repeated evolution remains poorly studied for many widespread alpine taxa. We present parallel genomic analyses of two recently evolved flightless alpine insect lineages to test for molecular signatures of repeated alpine adaptation. Specifically, we compare low-elevation vs. alpine stonefly ecotypes from parallel stream populations in which flightless upland ecotypes have been independently derived. We map 67,922 polymorphic genetic markers, generated across 176 Zelandoperla fenestrata specimens from two independent alpine stream populations in New Zealand's Rock and Pillar Range, to a newly developed plecopteran reference genome. Genome-wide scans revealed 31 regions with outlier single nucleotide polymorphisms (SNPs) differentiating lowland vs. alpine ecotypes in Lug Creek, and 37 regions with outliers differentiating ecotypes in Six Mile Creek. Of these regions, 13% (8/60) yielded outlier SNPs across both within-stream ecotype comparisons, implying comparable genomic shifts contribute to this repeated alpine adaptation. Candidate genes closely linked to repeated outlier regions include several with documented roles in insect wing-development (e.g., dishevelled), suggesting that they may contribute to repeated alpine wing reduction. Additional candidate genes have been shown to influence insect fecundity (e.g., ovo) and lifespan (e.g., Mrp4), implying that they might contribute to life history differentiation between upland and lowland ecotypes. Additional outlier genes have potential roles in the evolution of reproductive isolation among ecotypes (hedgehog and Desaturase 1). These results demonstrate how replicated outlier tests across independent lineages can potentially contribute to the discovery of genes underpinning repeated adaptation.

Growth genes are implicated in the evolutionary divergence of sympatric piscivorous and insectivorous rainbow trout (Oncorhynchus mykiss)

BackgroundIdentifying ecologically significant phenotypic traits and the genomic mechanisms that underly them are crucial steps in understanding traits associated with population divergence. We used genome-wide data to identify genomic regions associated with key traits that distinguish two ecomorphs of rainbow trout (Oncorhynchus mykiss)—insectivores and piscivores—that coexist for the non-breeding portion of the year in Kootenay Lake, southeastern British Columbia. “Gerrards” are large-bodied, rapidly growing piscivores with high metabolic rates that spawn north of Kootenay Lake in the Lardeau River, in contrast to the insectivorous populations that are on average smaller in body size, with lower growth and metabolic rates, mainly forage on aquatic insects, and spawn in tributaries immediately surrounding Kootenay Lake. We used pool-seq data representing ~ 60% of the genome and 80 fish per population to assess the level of genomic divergence between ecomorphs and to identify and interrogate loci that may play functional or selective roles in their divergence.ResultsGenomic divergence was high between sympatric insectivores and piscivores (F_{text{ST}} = 0.188), and in fact higher than between insectivorous populations from Kootenay Lake and the Blackwater River (F_{text{ST}} = 0.159) that are > 500 km apart. A window-based F_{text{ST}} analysis did not reveal “islands” of genomic differentiation; however, the window with highest F_{text{ST}} estimate did include a gene associated with insulin secretion. Although we explored the use of the “Local score” approach to identify genomic outlier regions, this method was ultimately not used because simulations revealed a high false discovery rate (~ 20%). Gene ontology (GO) analysis identified several growth processes as enriched in genes occurring in the ~ 200 most divergent genomic windows, indicating many loci of small effect involved in growth and growth-related metabolic processes are associated with the divergence of these ecomorphs.ConclusionOur results reveal a high degree of genomic differentiation between piscivorous and insectivorous populations and indicate that the large body piscivorous phenotype is likely not due to one or a few loci of large effect. Rather, the piscivore phenotype may be controlled by several loci of small effect, thus highlighting the power of whole-genome resequencing in identifying genomic regions underlying population-level phenotypic divergences.

Structural characterization and functional annotation of microbial proteases mined from solid tannery waste metagenome

We report structural characterization of proteases mined in silico from solid tannery waste (STW) metagenome. The physico-chemical analysis revealed the molecular weight of selected query proteases in the range of 34–43 kDa except 52.46 kDa for Cp-6. Secondary structure analysis suggested the dominance of α-helices (26–51 %) followed by β-sheets (13–34 %). Conserved regions in the selected proteases were identified using multiple sequence alignment. Diversity analysis of the proteases was performed by aligning with their best hits and already characterized proteases of similar families. The 3D structures of 19 selected amino acid sequences were deduced using homology modeling and evaluated following Ramachandran plots (R-plots), stability of the 3D conformation, and overall quality factor (G factor). The R-plots of all structures had 96.4–98.9 % residues in the favoured region, whereas 0-0.8 % lied in the outlier region. Fifteen modeled protein structures passed the quality assessment criteria and were subsequently used for molecular docking. All models showed two domains except Cp-6, which had an extra domain. Ligand binding sites and active sites were identified using sequence and structural homologs of the respective protease molecules. Serine, lysine, and serine of different conserved motifs were specified as the active site residues in carboxypeptidases, whereas serine, aspartate, and histidine were specific to aminopeptidases Ap-1, Ap-2, and Ap-4. Further, Ap-8 and Ap-9 required Mn2+ for enzyme activity along with histidine and glutamate in their active sites. These 3D structures were used for molecular docking with their specific peptide ligands to obtain stable docked conformations. Successfully docked complexes indicated the catalytic activity of these enzymes in hydrolyzing the peptide ligand. The structural and functional insights gained from our study may help in the identification of novel industrially important proteases after validation through experimental studies.

The population genomics of repeated freshwater colonizations by Gulf pipefish.

How organisms adapt to the novel challenges imposed by the colonization of a new habitat has long been a central question in evolutionary biology. When multiple populations of the same species independently adapt to similar environmental challenges, the question becomes whether the populations have arrived at their adaptations through the same genetic mechanisms. In recent years, genetic techniques have been used to tackle these questions by investigating the genome-level changes underlying local adaptation. Here, we present a genomic analysis of colonization of freshwater habitats by a primarily marine fish, the Gulf pipefish (Syngnathus scovelli). We sample pipefish from four geographically distinct freshwater locations and use double-digest restriction site associated DNA sequencing to compare them to 12 previously studied saltwater populations. The two most geographically distant and isolated freshwater populations are the most genetically distinct, although demographic analysis suggests that these populations are experiencing ongoing migration with their saltwater neighbours. Additionally, outlier regions were found genome-wide, showing parallelism across ecotype pairs. We conclude that these multiple freshwater colonizations involve similar genomic regions, despite the large geographical distances and different underlying mechanisms. These similar patterns are probably facilitated by the interacting effects of intrinsic barriers, gene flow among populations and ecological selection in the Gulf pipefish.

Detecting genetic signals of selection in heavily bottlenecked reindeer populations by comparing parallel founder events.

Founder populations are of special interest to both evolutionary and conservation biologists, but the detection of genetic signals of selection in these populations is challenging due to their demographic history. Geographically separated founder populations likely to have been subjected to similar selection pressures provide an ideal but rare opportunity to overcome these challenges. Here we take advantage of such a situation generated when small, isolated founder populations of reindeer were established on the island of South Georgia, and using this system we look for empirical evidence of selection overcoming strong genetic drift. We generated a 70k ddRADseq single nucleotide polymorphism database for the two parallel reindeer founder populations and screened for signatures of soft sweeps. We find evidence for a genomic region under selection shared among the two populations, and support our findings with Wright-Fisher model simulations to assess the power and specificity of interpopulation selection scans-namely Bayescan, OutFLANK, PCadapt and a newly developed scan called Genome Wide Differentiation Scan (GWDS)-in the context of pairwise source-founder comparisons. Our simulations indicate that loci under selection in small founder populations are most probably detected by GWDS, and strengthen the hypothesis that the outlier region represents a true locus under selection. We explore possible, relevant functional roles for genes in linkage with the detected outlier loci.

Bioinformatics features and immunogenic epitopes of Echinococcus granulosus Myophilin as a promising target for vaccination against cystic echinococcosis.

Cystic echinococcosis (CE) is a neglected zoonosis especially in underdeveloped countries around the world. Hence, immunization strategies are beneficial to avert the infection. The present investigation was aimed to predict the primary biochemical characteristics of the EgMyophilin and its potential B-cell and human leukocyte antigen (HLA)-binding epitopes as a promising vaccine candidate. Different web servers were used to predict physico-chemical, antigenic and allergenic profiles, transmembrane domain, subcellular localization, post-translational modification (PTM) sites, secondary and 3D structure, tertiary model refinement and validations. B-cell and HLA-binding epitopes were predicted and screened in terms antigenicity, allergenicity, solubility (B-cell) or hydrophobicity (T-cell). The 89.82 KDa protein was non-allergenic, hydrophilic, stable, with improved thermotolerance and 94 post-translational modification sites. The secondary structure included 42.94% alpha helix, 42.82% random coil and 41.23% extended strand. Based on Ramachandran plot output for refined model, 96.2%, 99.5%, and 0.45% of amino acid residues were incorporated in the favored, allowed, and outlier regions of the refined model, respectively. After epitope screening, four B-cell and five HLA-binding epitopes possessed the highest antigenic index in the protein sequence. This paper is a premise for further researches, and provides insights for the development of a suitable vaccine against CE. More empirical studies are required using the EgMyophilin alone or in combination with other antigens/epitopes in the future.

Immunoinformatic analysis of immunogenic B- and T-cell epitopes of MIC4 protein to designing a vaccine candidate against Toxoplasma gondii through an in-silico approach.

PurposeToxoplasmosis, transmitted by Toxoplasma gondii, is a worldwide parasitic disease that affects approximately one-third of the world's inhabitants. Today, there are no appropriate drugs to deter tissue cysts from developing in infected hosts. So, developing an effective vaccine would be valuable to avoid from toxoplasmosis. Considering the role of microneme antigens such as microneme protein 4 (MIC4) in T. gondii pathogenesis, it can be used as potential candidates for vaccine against T. gondii.Materials and MethodsIn this study several bioinformatics methods were used to assess the different aspects of MIC4 protein such as secondary and tertiary structure, physicochemical characteristics, the transmembrane domains, subcellular localization, B-cell, helper-T lymphocyte, cytotoxic-T lymphocyte epitopes, and other notable characteristic of this protein design a suitable vaccine against T. gondii.ResultsThe studies revealed that MIC4 protein includes 59 potential post-translational modification sites without any transmembrane domains. Moreover, several probable epitopes of B- and T-cells were detected for MIC4. The secondary structure comprised 55.69% random coil, 5.86% beta-turn, 19.31% extended strand, and 19.14% alpha helix. According to the Ramachandran plot results, 87.42% of the amino acid residues were located in the favored, 9.44% in allowed, and 3.14% in outlier regions. The protein allergenicity and antigenicity revealed that it was non-allergenic and antigenic.ConclusionThis study gives vital basic on MIC4 protein for further research and also established an effective vaccine with different techniques against acute and chronic toxoplasmosis.

A Computational Approach to Modeling an Antagonistic Angiogenic VEGFR1-IL2 Fusion Protein for Cancer Therapy.

In cancer treatment, immunotherapy has great potential for improving the prognosis of patients with hematologic and solid malignancies. In this study, various bioinformatics tools and servers were used to design an antiangiogenic fusion protein. After comprehensive evaluation, an antiangiogenic fusion protein was designed using a soluble extracellular domain of human vascular endothelial growth factor receptor 1 (sVEGFR-1) and human interleukin-2 (IL-2) joined by a flexible linker. The final construct was composed of 875 amino acids. The secondary structure of the fusion protein, obtained by CFSSP, PSIPRED, and SOPMA tools, consisted of 14.17% helices, 29.71% extended strands, 4.69% beta turns and 51.43% random coils. Tertiary structure prediction by Raptor X showed that the fusion protein comprises 3 domains with 875 modeled amino acids, out of which 26 positions (2%) were considered disordered. The Ramachandran plot revealed 89.3%, 7.1%, and 3.6% amino acid residues in favored, allowed, and outlier regions, respectively. Physical features of the Molecular Dynamic (MD) simulated system such as root mean square deviation, root mean square fluctuation, solvent-on hand surface region, and radius of gyration identified the fusion construct as a stable and compact protein with few fluctuations in its overall structure. Docking of the fusion protein showed that interaction between sVEGFR-1/VEGFA and IL-2/IL-2R still exists. In silico analysis revealed that the fusion protein comprising IL-2 and sVEGFR-1 has stable structure and the selected linker can efficiently separate the two domains. These observations may be helpful in determining protein stability prior to protein expression.

Distinguishing type II focal cortical dysplasias from normal cortex: A novel normative modeling approach

ObjectiveFocal cortical dysplasias (FCDs) are a common cause of apparently non-lesional drug-resistant focal epilepsy. Visual detection of subtle FCDs on MRI is clinically important and often challenging. In this study, we implement a set of 3D local image filters adapted from computer vision applications to characterize the appearance of normal cortex surrounding the gray-white junction. We create a normative model to serve as the basis for a novel multivariate constrained outlier approach to automated FCD detection. MethodsStandardized MPRAGE, T2 and FLAIR MR images were obtained in 15 patients with radiologically or histologically diagnosed FCDs and 30 healthy volunteers. Multiscale 3D local image filters were computed for each MR contrast then sampled onto the gray-white junction surface. Using an iterative Gaussianization procedure, we created a normative model of cortical variability in healthy volunteers, allowing for identification of outlier regions and estimates of similarity in normal cortex and FCD lesions. We used a constrained outlier approach following local normalization to automatically detect FCD lesions based on projection onto the mean FCD feature vector. ResultsFCDs as well as some normal cortical regions such as primary sensorimotor and paralimbic regions appear as outliers. Regions such as the paralimbic regions and the anterior insula have similar features to FCDs. Our constrained outlier approach allows for automated FCD detection with 80% sensitivity and 70% specificity. SignificanceA normative model using multiscale local image filters can be used to describe the normal cortical variability. Although FCDs appear similar to some cortical regions such as the anterior insula and paralimbic cortices, they can be identified using a constrained outlier detection approach. Our method for detecting outliers and estimating similarity is generic and could be extended to identification of other types of lesions or atypical cortical areas.

Toxoplasma gondii ROP38 protein: Bioinformatics analysis for vaccine design improvement against toxoplasmosis

Rhoptry proteins (ROPs) play a significant role in various stages of Toxoplasma gondii (T. gondii) life cycle, being critical for both invasion and intracellular survival. ROP38 is a key manipulator of host gene expression and has a function in tachyzoite to bradyzoite conversion. In this study, we've employed various bioinformatics online tools for immunogenicity prediction of ROP38 protein, comprising physico-chemical, antigenic and allergenic profiles, transmembrane domain, subcellular localization, post-translational modification (PTM) sites, secondary and 3D structure, B-cell, MHC-binding and cytotoxic T-lymphocyte (CTL) epitopes. The findings showed 54 PTM sites without a transmembrane domain. Also, ROP38 was proved a non-allergenic and antigenic protein. The protein had Sec signal peptide (Sec/SPI) with 0.8762 likelihood. The secondary structure included 52.68% random coil, 29.57% alpha helix and 17.74% extended strand. Based on Ramachandran plot output for refined model, 95.3%, 3.4%, and 1.4% of amino acid residues were incorporated in the favored, allowed, and outlier regions, respectively. B-cell epitopes TFPGDDIQTSS (67–72) and KAKNKWGRTRYTLQG (207–221) as well as T-cell epitope LSPVGFFTAL (6–15) possessed the highest antigenic index in the protein sequence. This paper is a premise for further researches, and provides insights for the development of a suitable vaccine against toxoplasmosis. More empirical studies are required using the ROP38 alone or in combination with other antigens/epitopes in the future.

X-Linked Signature of Reproductive Isolation in Humans is Mirrored in a Howler Monkey Hybrid Zone.

Reproductive isolation is a fundamental step in speciation. While sex chromosomes have been linked to reproductive isolation in many model systems, including hominids, genetic studies of the contribution of sex chromosome loci to speciation for natural populations are relatively sparse. Natural hybrid zones can help identify genomic regions contributing to reproductive isolation, like hybrid incompatibility loci, since these regions exhibit reduced introgression between parental species. Here, we use a primate hybrid zone (Alouatta palliata × Alouatta pigra) to test for reduced introgression of X-linked SNPs compared to autosomal SNPs. To identify X-linked sequence in A. palliata, we used a sex-biased mapping approach with whole-genome re-sequencing data. We then used genomic cline analysis with reduced-representation sequence data for parental A. palliata and A. pigra individuals and hybrids (n = 88) to identify regions with non-neutral introgression. We identified ~26 Mb of non-repetitive, putatively X-linked genomic sequence in A. palliata, most of which mapped collinearly to the marmoset and human X chromosomes. We found that X-linked SNPs had reduced introgression and an excess of ancestry from A. palliata as compared to autosomal SNPs. One outlier region with reduced introgression overlaps a previously described “desert” of archaic hominin ancestry on the human X chromosome. These results are consistent with a large role for the X chromosome in speciation across animal taxa and further, suggest shared features in the genomic basis of the evolution of reproductive isolation in primates.

Feasibility of Quality Measures for the Diagnosis and Treatment of Carpal Tunnel Syndrome

The American Academy of Orthopaedic Surgeons and the American Society for Surgery of the Hand developed candidate quality measures for potential inclusion in the Merit-Based Incentive Program and National Quality Forum in the hope that hand surgeons could report specialty-specific data. The following measures regarding the management of carpal tunnel syndrome (CTS) were developed using a Delphi consensus process: (1) use of magnetic resonance imaging (MRI) for diagnosis of CTS, (2) use of adjunctive surgical procedures during carpal tunnel release (CTR), and (3) use of formal occupational and/or physical therapy after CTR. This study simulated attempts to identify outlier regions in an insurance claims database, which is an important step in establishing feasibility of these measures. Using the Truven Health MarketScan, we identified 643,357 patients who were given a diagnosis of CTS between 2012 and 2014. We reported the percentage of metropolitan statistical areas (MSA) with one or more claims for MRI within 90 days of CTS diagnosis, one or more adjunctive surgical procedures, and one or more formal referrals for physical and/or occupational therapy within 6 weeks of CTR, and we calculated the rate of use for each of these diagnostic or treatment modalities. In addition, we report the precision ratio (signal to noise), SD, and 95% confidence interval. A high percentage of patients given a diagnosis of CTS did not have MRI (99%), and the precision ratio was considered high (0.99). Over 30% of all observed MSAs had at least one claim for MRI as a diagnostic modality in CTS. Most patients (98%) did not have adjunctive surgical procedures. For the observed years, over 28% of MSAs had at least one insurance claim for an adjunctive procedure. A total of 86% of patients did not receive formal occupational or physical therapy after CTR. In addition, 92% of MSAs had at least one claim for therapy. The precision ratio was considered high (approximately 0.85). There is regional variation in the utilization rate of diagnostic MRI for CTS, adjunctive surgical procedures, and formal referral for physical and occupational therapy. For the proposed quality measures, outlier regions can be detected in insurance claims data. Use of MRI in diagnosis, adjunctive surgical procedures, and formal therapy after surgery are feasible quality measures for the Merit-Based Incentive Program and National Quality Forum.

Population Genomics Reveals Demographic History and Genomic Differentiation of Populus davidiana and Populus tremula.

Forest trees can increase our understanding of how evolutionary processes drive the genomic landscape and understand speciation due to the majority of forest trees being distributed widely and able to adapt to different climates and environments. Populus davidiana and Populus tremula are among the most geographically widespread and ecologically important tree species in Northern Hemisphere. Whole-genome resequencing data of 41 individuals of P. davidiana and P. tremula throughout Eurasia was conducted, finding that genetic differentiation was evident between the two species, the FST values between P. davidiana and P. tremula was 0.3625. The ancestors of the two aspen diverged into P. davidiana and P. tremula species approximately 3.60 million years ago (Mya), which was in accordance with the rapid uplift of Qinghai–Tibet Plateau (QTP) around the Miocene/Pliocene boundary. The two species experienced a considerable long-term bottleneck after divergence, with population expansion beginning approximately 20,000 years ago after the end of the last glacial maximum. Although the majority of regions of genomic differentiation between the two species can be explained by neutral evolutionary processes, some outlier regions have also been tested that are significantly influenced by natural selection. We found that the highly differentiated regions of the two species exhibited significant positive selection characteristics, and also identified long-term balancing selection in the poorly differentiated regions in both species. Our results provide strong support for a role of linked selection in generating the heterogeneous genomic landscape of differentiation between P. davidiana and P. tremula. These results provide the detailed and comprehensive genomic insights into genetic diversity, demography, genetic burden, and adaptation in P. davidiana and P. tremula.