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The research on the hot corrosion resistance of nickel-based superalloys is critical to determining and enhancing their service life. Therefore, this study investigates the cyclic hot corrosion behavior of GH4738 alloy coated with a mixed salt (75 wt% Na2SO4+25 wt% NaCl) at 750 °C and 800 °C. X-ray diffractometer (XRD), scanning electron microscope (SEM), energy dispersive spectrometer (EDS), and transmission electron microscope (TEM) are used to analyze the phase compositions and film structures of the corrosion products, as well as to explore the corrosion mechanism. The results show that a thicker oxide layer is formed at higher temperatures, indicating poorer hot corrosion resistance at elevated temperatures. The corrosion products form at both temperatures to show a distinct layered structure, the outer layer is mainly composed of Cr2O3 and a small amount of TiO2, while the inner layer consists of Al2O3, CrS, and TiS. In addition, it is found that the corrosion mechanism of O, S, and Cl elements in the corrosion process is synergistic and accompanied by alkaline melting.

Abstract Background Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project. Methods The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain. Conclusion Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.

Background: Aberrant functional connectivity is a hallmark of schizophrenia. The precise nature and mechanism of dysconnectivity in schizophrenia remains unclear, but evidence suggests that dysconnectivity is different in wake versus sleep. Microstate analysis uses electroencephalography (EEG) to investigate large-scale patterns of coordinated brain activity by clustering EEG data into a small set of recurring spatial patterns, or microstates. We hypothesized that this technique would allow us to probe connectivity between brain networks at a fine temporal resolution and uncover previously unknown sleep-specific dysconnectivity. Methods: We studied microstates during sleep in patients with schizophrenia by analyzing high-density EEG sleep data from 114 patients with schizophrenia and 79 control participants. We used a polarity-insensitive k-means analysis to extract a set of 6 microstate topographies. Results: These 6 states included 4 widely reported canonical microstates. In patients and control participants, falling asleep was characterized by a shift from microstates A, B, and C to microstates D, E, and F. Microstate F was decreased in patients during wake, and microstate E was decreased in patients during sleep. The complexity of microstate transitions was greater in patients than control participants during wake, but this reversed during sleep. Conclusions: Our findings reveal behavioral state–dependent patterns of cortical dysconnectivity in schizophrenia. Furthermore, these findings are largely unrelated to previous sleep-related EEG markers of schizophrenia such as decreased sleep spindles. Therefore, these findings are driven by previously undescribed sleep-related pathology in schizophrenia.

Isothermal heat treatment experiments were used to studied the dissolution behavior and kinetics of the γ′ precipitates within the hot-extruded novel powder metallurgy Ni-based superalloy A1. The characteristics of the γ′ precipitates were accurately and rapidly extracted by deep learning methods. The JMAK models were established to predict the change of the area fraction of γ′ precipitates during heat treatment. The determination coefficient R2 of model is 0.99. The results indicate that the dissolution sequence, morphological evolution, and dissolution mechanisms of the three types of γ′ precipitates are different. The small-sized tertiary γ′ precipitates (γ′t) dissolve first, while the larger-sized primary γ′ precipitates (γ′p) dissolve last. After 15 min at 1120 °C, there were only a small amount of γ′ precipitates with 0.19 ± 0.03 % area fraction. And there was not significant changed over time. After 1 min at 1150 °C, the γ′ precipitates completely dissolved. During the process of low temperature subsolvus heat treatment (1060 °C, 1090 °C), the large-sized γ′s grown at the expense of consuming the small-sized γ′ precipitates, and the γ′s tend towards directional arrangement due to elastic interaction energy. During the subsolvus heat treatment process, the γ′p spilt due to elastic strain energy and the uneven diffusion of alloying elements, while neck-connected coalescence coarsening occurs due to the overlapping diffusion fields.

Summary: Background: Response to antipsychotic drugs (APD) varies greatly among individuals and is affected by genetic factors. This study aims to demonstrate genome-wide associations between copy number variants (CNVs) and response to APD in patients with schizophrenia. Methods: A total of 3030 patients of Han Chinese ethnicity randomly received APD (aripiprazole, olanzapine, quetiapine, risperidone, ziprasidone, haloperidol and perphenazine) treatment for six weeks. This study is a secondary data analysis. Percentage change on the Positive and Negative Syndrome Scale (PANSS) reduction was used to assess APD efficacy, and more than 50% change was considered as APD response. Associations between CNV burden, gene set, CNV loci and CNV break-point and APD efficacy were analysed. Findings: Higher CNV losses burden decreased the odds of 6-week APD response (OR = 0.66 [0.44, 0.98]). CNV losses in synaptic pathway involved in neurotransmitters were associated with 2-week PANSS reduction rate. CNV involved in sialylation (1p31.1 losses) and cellular metabolism (19q13.32 gains) associated with 6-week PANSS reduction rate at genome-wide significant level. Additional 36 CNVs associated with PANSS factors improvement. The OR of protective CNVs for 6-week APD response was 3.10 (95% CI: 1.33–7.19) and risk CNVs was 8.47 (95% CI: 1.92–37.43). CNV interacted with genetic risk score on APD efficacy (Beta = −1.53, SE = 0.66, P = 0.021). The area under curve to differ 6-week APD response attained 80.45% (95% CI: 78.07%–82.82%). Interpretation: Copy number variants contributed to poor APD efficacy and synaptic pathway involved in neurotransmitter was highlighted. Funding: National Natural Science Foundation of China, National Key R&D Program of China, China Postdoctoral Science Foundation.

Abstract Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

Abstract Objective To perform an evidence-based evaluation of the clinical efficacy of Taijiquan, Baduanjin, Yijinjing and Wuqinxi in interventions for type 2 diabetes. Design A systematic review and network meta-analysis. Methods The comprehensive search included Chinese and other language databases such as the MEDLINE (PubMed), Web of Science, Excerpta Medica Database (Embase), The Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, China Scientific Journal Database, VIP and China Biomedical Literature Database (CBM). Clinical randomized controlled trials of four traditional Chinese exercise therapies in the treatment of type 2 diabetes, including Taijiquan, Baduanjin, Yijinjing and Wuqinxi, were retrieved. The search time was conducted from the establishment of the database to 30 October 2022. Two researchers screened the documents that met the inclusion criteria, extracted data according to the preset table and evaluated the methodological quality of the included studies according to the quality evaluation tools recommended by the Cochrane System Reviewer Manual V.5.1. The R language, Stata and ADDIS statistical software programs were used to conduct statistics and analysis of intervention measures. Results A total of 33 randomized controlled trials with 2609 patients were identified. All patients were from China. The results of the network meta-analysis showed that Taijiquan ranked the best for improving HbA1c, 2-h postprandial blood glucose (2hPG), low-density lipoprotein cholesterol (LDL-C) and insulin sensitivity index indicator levels; Yijinjing reduced fasting plasma glucose (FPG) and total cholesterol (TC) indicator levels for the best probability ranking; Baduanjin improved the triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) probability ranking the most. When the training period was less than 12 weeks, Baduanjin had better effects in improving 2hPG, TC, TG, HDL-C and LDL-C indicator levels. Taijiquan had better effects in reducing FPG levels. When the training period was 12 weeks, the effect of Yijinjing in improving FPG, HbAlc, TC and HDL-C levels was better than that in other traditional Chinese exercise, and Taijiquan had better effects in improving 2hPG, TG and LDL-C indicator levels. When the training period was longer than 12 weeks, Taijiquan had better effects in improving FPG, HbAlc, 2hPG and LDL-C indicator levels, and Baduanjin had better effects in improving TC, TG and HDL-C indicator levels. Conclusion The four traditional Chinese exercise therapies can improve blood glucose levels, blood lipid levels and insulin-related indicators of type 2 diabetes to varying degrees. Studies have shown that Taijiquan has a better targeted treatment effect on type 2 diabetes. Systematic review registration CRD42020214786. Protocol published We published the protocol article “Network meta-analysis of four kinds of traditional Chinese exercise therapy in the treatment of type 2 diabetes: Protocol for a systematic review” in the BMJ Open magazine 2021, Issue 11, Volume 7.

Tweek atmospherics are extremely low frequency and very low frequency pulse signals with frequency dispersion characteristics that originate from lightning discharges and that propagate in the Earth–ionosphere waveguide over long distances. In this study, we developed an automatic method to recognize tweek atmospherics and diagnose the lower ionosphere based on the machine learning method. The differences (automatic − manual) in each ionosphere parameter between the automatic method and the manual method were −0.07 ± 2.73 km, 0.03 ± 0.92 cm−3, and 91 ± 1,068 km for the ionospheric reflection height (h), equivalent electron densities at reflection heights (Ne), and propagation distance (d), respectively. Moreover, the automatic method is capable of recognizing higher harmonic tweek sferics. The evaluation results of the model suggest that the automatic method is a powerful tool for investigating the long-term variations in the lower ionosphere.

In this work, the thermoplasticity of hot extruded (HEXed) FGH4096 superalloy was greatly enhanced by sub-solvus temperature holding followed by extremely slow cooling (S-ESC). After S-ESC processing, the dispersed fine γ′ precipitates inside the grains and grain boundaries obviously grow up. Under most deformation conditions, the S-ESCed samples exhibit smaller flow stress and larger strain rate sensitive index (m) values than the HEXed samples, especially the peak value of m is 0.75 vs. 0.32. This is because fine γ′ precipitates limit deformation by pinning dislocation, and coarse γ′ precipitates promote dynamic recrystallization (DRX). Under the high strain rate of 1 s−1, the DRX degree of the HEXed sample is greatly affected by temperature, while the S-ESCed samples maintain a high DRX degree at different temperature. At the high temperature of 1100 °C, the S-ESCed samples exhibit smaller grain sizes and higher DRX degrees than the HEXed sample under low strain rates. More importantly, because the γ′ precipitates promote DRX, the S-ESCed sample achieves superplasticity at 1090 °C and 10−3 s−1.

Summary: Polygenic risk scores (PRSs) developed from multi-ancestry genome-wide association studies (GWASs), PRSmulti, hold promise for improving PRS accuracy and generalizability across populations. To establish best practices for leveraging the increasing diversity of genomic studies, we investigated how various factors affect the performance of PRSmulti compared with PRSs constructed from single-ancestry GWASs (PRSsingle). Through extensive simulations and empirical analyses, we showed that PRSmulti overall outperformed PRSsingle in understudied populations, except when the understudied population represented a small proportion of the multi-ancestry GWAS. Furthermore, integrating PRSs based on local ancestry-informed GWASs and large-scale, European-based PRSs improved predictive performance in understudied African populations, especially for less polygenic traits with large-effect ancestry-enriched variants. Our work highlights the importance of diversifying genomic studies to achieve equitable PRS performance across ancestral populations and provides guidance for developing PRSs from multiple studies.

Summary: Crohn's disease (CD) and ulcerative colitis (UC) are two etiologically related yet distinctive subtypes of the inflammatory bowel diseases (IBD). Differentiating CD from UC can be challenging using conventional clinical approaches in a subset of patients. We designed and evaluated a novel molecular-based prediction model aggregating genetics, serum biomarkers, and tobacco smoking information to assist the diagnosis of CD and UC in over 30,000 samples. A joint model combining genetics, serum biomarkers and smoking explains 46% (42–50%, 95% CI) of phenotypic variation. Despite modest overlaps with serum biomarkers, genetics makes unique contributions to distinguishing IBD subtypes. Smoking status only explains 1% (0–6%, 95% CI) of the phenotypic variance suggesting it may not be an effective biomarker. This study reveals that molecular-based models combining genetics, serum biomarkers, and smoking information could complement current diagnostic strategies and help classify patients based on biologic state rather than imperfect clinical parameters.

Cognitive impairments are a key feature of psychopathology. Here, authors exploit the genetic overlap between cognitive dimensions and psychopathology to parse the biology of psychiatric illness and identify “meta-loci” genome segments characterized by specific patterns of overlap.

Monocyte chemotactic protein-1-induced protein-1 (MCPIP-1) is highly expressed in activated immune cells and negatively regulates immune responses, while the mechanisms underlying the immunoregulation of neutrophils in acute bacterial infection and liver injury remain elusive. Here, we examined the role of MCPIP-1 in regulating neutrophil functions during acute bacterial peritonitis and liver injury. Mice with myeloid cell-specific overexpression (McpipMye-tg) or knockout (McpipΔMye) of MCPIP-1 were generated. We found that reactive oxygen species and myeloperoxidase production, formation of neutrophil extracellular traps, and migratory capacity were deficient in McpipMye-tg neutrophils but enhanced in McpipΔMye neutrophils. The recruitment of neutrophils and pathogen clearance were markedly suppressed in McpipMye-tg mice following intraperitoneal infection with Salmonella typhimurium while intensified in McpipΔMye mice. Severe acute S. typhimurium-infected peritonitis and liver injury occurred in McpipMye-tg mice but were alleviated in McpipΔMye mice. RNA sequencing, RNA-binding protein immunoprecipitation and qPCR analysis revealed that MCPIP-1 downregulated the protective functions of neutrophils via degrading the mRNA of cold inducible RNA-binding protein. Consistently, MCPIP-1 was highly expressed in neutrophils of patients with acute infectious diseases, especially in those with liver injury. Collectively, we uncover that MCPIP-1 negatively regulates the antibacterial capacities of neutrophils, leading to exacerbating severe acute bacterial peritonitis and liver injury. It may serve as a candidate target for maintaining neutrophil homeostasis to control acute infectious diseases.

Background: Metformin, which has been shown to be highly effective in treating type 2 diabetes (T2D), is also believed to be valuable for Alzheimer’s disease (AD). Computer simulation techniques have emerged as an innovative approach to explore mechanisms. Objective: To study the potential mechanism of metformin action in AD and T2D. Methods: The chemical structure of metformin was obtained from PubChem. The targets of metformin were obtained from PubChem, Pharm Mapper, Batman, SwissTargetPrediction, DrugBank, and PubMed. The pathogenic genes of AD and T2D were retrieved from the GeneCards, OMIM, TTD, Drugbank, PharmGKB, and DisGeNET. The intersection of metformin with the targets of AD and T2D is represented by a Venn diagram. The protein-protein interaction (PPI) and core targets networks of intersected targets were constructed by Cytoscape 3.7.1. The enrichment information of GO and Kyoto Encyclopedia of Gene and Genomics (KEGG) pathways obtained by the Metascape was made into a bar chart and a bubble diagram. AutoDockTools, Pymol, and Chem3D were used for the molecular docking. Gromacs software was used to perform molecular dynamics (MD) simulation of the best binding target protein. Results: A total of 115 key targets of metformin for AD and T2D were obtained. GO analysis showed that biological process mainly involved response to hormones and the regulation of ion transport. Cellular component was enriched in the cell body and axon. Molecular function mainly involved kinase binding and signal receptor regulator activity. The KEGG pathway was mainly enriched in pathways of cancer, neurodegeneration, and endocrine resistance. Core targets mainly included TP53, TNF, VEGFA, HIF1A, IL1B, IGF1, ESR1, SIRT1, CAT, and CXCL8. The molecular docking results showed best binding of metformin to CAT. MD simulation further indicated that the CAT-metformin complex could bind well and converge relatively stable at 30 ns. Conclusion: Metformin exerts its effects on regulating oxidative stress, gluconeogenesis and inflammation, which may be the mechanism of action of metformin to improve the common pathological features of T2D and AD.

Abstract Background Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. Methods We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. Results The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5–4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. Conclusions By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Summary: Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.

A study on actinic keratosis identifies multiple loci showing genome-wide significant association with implicated genes within biological pathways for pigmentation, immune regulation, and extracellular matrix homeostasis.

Summary: Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.

Loss of function of tuberous sclerosis complex 1 or 2 (TSC1 or TSC2) leads to the activation of mammalian target of rapamycin complex 1 (mTORC1). Hyperactivated mTORC1 plays a critical role in tumor growth, but the underlying mechanism is still not completely elucidated. Here, by analyzing Tsc1- or Tsc2-null mouse embryonic fibroblasts, rat Tsc2-null ELT3 cells, and human cancer cells, we present evidence for the involvement of epidermal growth factor receptor (EGFR) as a downstream target of mTORC1 in tumor growth. We show that mTORC1 leads to increased EGFR expression through upregulation of runt-related transcriptional factor 1 (RUNX1). Knockdown of EGFR impairs proliferation and tumoral growth of Tsc-deficient cells, while overexpression of EGFR promotes the proliferation of the control cells. Moreover, the mTOR signaling pathway has been shown to be positively correlated with EGFR in human cancers. In addition, we demonstrated that EGFR enhances cell growth through activation of signal transducer and activator of transcription 3 (STAT3). We conclude that activation of the RUNX1/EGFR/STAT3 signaling pathway contributes to tumorigenesis caused by hyperactivated mTORC1 and should be targeted for the treatment of mTORC1-related tumors, particularly TSC.

Abstract Quercetin has demonstrated antioxidant, anti-inflammatory, hypoglycemic, and hypolipidemic activities, suggesting therapeutic potential against type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD). In this study, potential molecular targets of quercetin were first identified using the Swiss Target Prediction platform and pathogenic targets of T2DM and AD were identified using online Mendelian inheritance in man (OMIM), DisGeNET, TTD, DrugBank, and GeneCards databases. The 95 targets shared among quercetin, T2DM, and AD were used to establish a protein–protein interaction (PPI) network, top 25 core genes, and protein functional modules using MCODE. Metascape was then used for gene ontology and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. A protein functional module with best score was obtained from the PPI network using CytoHubba, and 6 high-probability quercetin targets (AKT1, JUN, MAPK, TNF, VEGFA, and EGFR) were confirmed by docking simulations. Molecular dynamics simulation was carried out according to the molecular docking results. KEGG pathway enrichment analysis suggested that the major shared mechanisms for T2DM and AD include “AGE-RAGE signaling pathway in diabetic complications,” “pathways in cancer,” and “MAPK signaling pathway” (the key pathway). We speculate that quercetin may have therapeutic applications in T2DM and AD by targeting MAPK signaling, providing a theoretical foundation for future clinical research.

Background: Immunogenic cell death (ICD) remodels the tumor immune microenvironment, plays an inherent role in tumor cell apoptosis, and promotes durable protective antitumor immunity. Currently, appropriate biomarker-based ICD immunotherapy for breast cancer (BC) is under active exploration.Methods: To determine the potential link between ICD genes and the clinical risk of BC, TCGA-BC was used as the training set and GSE58812 was used as the validation set. Gene expression, consistent clustering, enrichment analysis, and mutation omics analyses were performed to analyze the potential biological pathways of ICD genes involved in BC. Furthermore, a risk and prognosis model of ICD was constructed to evaluate the correlation between risk grade and immune infiltration, clinical stage, and survival prognosis.Results: We identified two ICD-related subtypes by consistent clustering and found that the C2 subtype was associated with good survival prognosis, abundant immune cell infiltration, and high activity of immune biological processes. Based on this, we constructed and validated an ICD risk and prognosis model of BC, including ATG5, HSP90AA1, PIK3CA, EIF2AK3, MYD88, IL1R1, and CD8A. This model can effectively predict the survival rate of patients with BC and is negatively correlated with the immune microenvironment and clinical stage.Conclusion: This study provides new insights into the role of ICD in BC. The novel classification risk model based on ICD in BC established in this study can aid in estimating the potential prognosis of patients with BC and the clinical outcomes of immunotherapy and postulates targets that are more useful in comprehensive treatment strategies.

Objective: The aim of this study was to explore the therapeutic target and mechanism of Hydroxy Safflower Yellow A pigment (HSYA)—the main water-soluble component of Safflower—in the treatment of Poststroke Cognitive Impairment (PSCI) by network pharmacology and molecular docking methods. Method: GeneCards, PharmMapper, and Swiss Target Prediction databases were used to screen HSYA targets. Protein-Protein Interaction analysis, Gene Ontology, and KEGG enrichment analysis were performed through STRING and Metascape databases, respectively. Cytoscape 3.6.0 was used to draw the network diagram of the “HSYA-target-PSCI pathway.” AutoDockVina was used for molecular docking. Results: A total of 310 targets of HSYA and 2455 potential targets of PSCI were screened, and the shared target was 159. After GO and KEGG enrichment analysis, HSYA was found to exhibit a therapeutic effect on PSCI by regulating various cancer pathways, endocrine regulation, cell proliferation, and apoptosis pathways. The molecular docking results suggest that HSYA has the best docking activity with the core target HRAS. Molecular dynamics simulation results showed that HSYA was the best binding agent to MAPK1, followed by HRAS. Conclusion: HSYA may regulate cell autophagy and apoptosis by regulating various pathways like PI3K-AKT and MAPK signaling pathways. It inhibits the secretion of inflammatory and angiogenic factors, inhibits endothelial angiogenesis, and plays a role in treating PSCI.

Trans-ethnic genetic correlation is significantly less than 1 for many diseases. Here, the authors stratify this correlation by genomic annotations, finding that loci whose causal disease effect sizes differ between ethnicities are likely impacted by selection, particularly positive selection.

Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key non-rapid eye movement (NREM) sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 72 schizophrenia (SCZ) patients and 58 controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, statistically predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.

Objective The objective of this study was to clarify the potential mechanism of quercetin against knee osteoarthritis (KOA) based on network pharmacology and molecular docking.

Abstract Background The network pharmacology method was used to predict the active components of Banxia Xiexin decoction, its targets and the key signalling pathways that are activated in the treatment of depression and ulcerative colitis to explore the common mechanism. Methods The active components and targets of Banxia Xiexin decoction were obtained by searching the ETCM,TCMSP and TCMIP database. The disease targets of depression and ulcerative colitis were obtained by combining the following the DisGeNET, OMIM,Drugbank,CTD and PharmGKB disease databases. The drug and disease target genes were obtained from the intersection of the herbal medicine targets and the disease targets and were imported into the STRING platform for the analysis of PPI network. The network modules were constructed using Cytoscape software. An analysis of the functional annotations of GO terms and KEGG signalling pathways was performed for each network module. Then, the tissue distribution, sub-cellular distribution and protein attributes of the key targets in the pathway were analysed by the BioGPS, Genecards and DisGeNET databases. Results The mechanism of Banxia Xiexin Decoction in the treatment of depression and ulcerative colitis is related to drug reaction, steroid metabolism, lipid metabolism, inflammatory response, oxidative stress response, cell response to lipopolysaccharide, insulin secretion regulation, estradiol response and other biological functions, mainly through the regulation of 5-hydroxytryptamine synaptic, arachidonic acid metabolism, HIF-1 signaling pathway and NF-kappa B signaling pathway can achieve the effect of same treatment for different diseases. Conclusions The mechanism of Banxia Xiexin Decoction in treating different diseases involves direct or indirect correlation of multiple signal pathways, mainly involved in drug metabolism and lipid metabolism, but also through comprehensive intervention of the body’s nervous system, immune system, digestive system and other systems. The effective components of Banxia Xiexin Decoction are mainly act on eight key target proteins (such as ALB, IL6, VEGFA, TNF, PTGS2, MAPK1, STAT3, EGFR) to carry out multi-target effect mechanism, biological mechanism of treating different diseases with the same treatment, and related mechanism of overall treatment, which provide theoretical reference for further research on the material basis and mechanism of Banxiaxiexin decoction on antidepressant and prevention and treatment of ulcerative colitis.

BackgroundIn recent years, Chinese and international studies have reported that traditional Chinese exercises (TCEs) have good therapeutic effects on pulmonary function, endurance capacity, and quality of life in patients with chronic obstructive pulmonary disease (COPD). However, only a few studies have reported the differences in the efficacy of different TCEs in the treatment of COPD.ObjectiveThe objective of this study is to compare the effects of five TCEs on patients with COPD, including Taijiquan (TJQ), Baduanjin (BDJ), Liuzijue (LZJ), Wuqinxi (WQX), and Yijinjing (YJJ).MethodsAll randomized controlled trials (RCTs) of TCEs for patients with COPD were searched in PubMed, Web of Science, Cochrane Library, Excerpt Medica Database (EMBASE), China National Knowledge Infrastructure (CNKI), China Biology Medicine database (CBM), China Scientific Journal Database (VIP), and Wanfang database. The search period was from the establishment of each database to August 16, 2021. The quality of the included studies was assessed according to the Cochrane handbook of systematic review, and the network meta-analysis was conducted with R 4.0.2 (Ross Ihaka, Auckland, New Zealand) and ADDIS 1.16.8 (Gert vsn Valkenhoef, Groningen, Netherlands). The effect size was evaluated using the mean difference (MD) and 95% confidence interval (CI).ResultsA total of 53 RCTs involving 3,924 patients were included. The network meta-analysis results showed that WQX was the most effective in improving FEV1/FVC% score and 6-MWT score. The difference was statistically significant (MD = 8.62, 95% CI 4.46 to 13.04, P < 0.05), (MD = 74.29, 95% CI 47.67 to 102.24, P < 0.05). However, YJJ was the most effective in reducing the CAT score, and the difference was statistically significant (MD = −8.38, 95% CI −13.24 to −3.28, P < 0.05).ConclusionThe existing evidence shows that WQX has advantages over other TCEs in improving pulmonary function and endurance capacity in patients with COPD, while YJJ has advantages in improving the quality of life. Although TCEs show no significant adverse effects, more large-scale, double-blind, and high-quality RCTs are needed in the future to verify the findings of this study.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021293640.

ObjectiveThis study aims to systematically evaluate the effect of non-invasive brain stimulation (NIBS) on neuropathic pain (NP) after spinal cord injury and compare the effects of two different NIBS.MethodsRandomized controlled trials (RCTs) about the effect of NIBS on NP after spinal cord injury (SCI) were retrieved from the databases of PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang Data, VIP, and CBM from inception to September 2021. The quality of the trials was assessed, and the data were extracted according to the Cochrane handbook of systematic review. Statistical analysis was conducted with Stata (version 16) and R software (version 4.0.2).ResultsA total of 17 studies involving 507 patients were included. The meta-analysis showed that NIBS could reduce the pain score (SMD = −0.84, 95% CI −1.27 −0.40, P = 0.00) and the pain score during follow-up (SMD = −0.32, 95%CI −0.57 −0.07, P = 0.02), and the depression score of the NIBS group was not statistically significant than that of the control group (SMD = −0.43, 95%CI −0.89–0.02, P = 0.06). The network meta-analysis showed that the best probabilistic ranking of the effects of two different NIBS on the pain score was repetitive transcranial magnetic stimulation (rTMS) (P = 0.62) > transcranial direct current stimulation (tDCS) (P = 0.38).ConclusionNIBS can relieve NP after SCI. The effect of rTMS on NP is superior to that of tDCS. We suggest that the rTMS parameters are 80–120% resting motion threshold and 5–20 Hz, while the tDCS parameters are 2 mA and 20 min. However, it is necessary to carry out more large-scale, multicenter, double-blind, high-quality RCT to explore the efficacy and mechanism of NIBS for NP after SCI.

T cell polyfunctionality is a hallmark of protective immunity against pathogens and cancer, yet the molecular mechanism governing it remains mostly elusive. We found that canonical Wnt agonists inhibited human memory CD8+ T cell differentiation while simultaneously promoting the generation of highly polyfunctional cells. Downstream effects of Wnt activation persisted after removal of the drug, and T cells remained polyfunctional following subsequent cell division, indicating the effect is epigenetically regulated. Wnt activation induced a gene expression pattern that is enriched with stem cell–specific gene signatures and upregulation of protein arginine methyltransferase 1 (PRMT1), a known epigenetic regulator. PRMT1+CD8+ T cells are associated with enhanced polyfunctionality, especially the ability to produce IL-2. In contrast, inhibition of PRMT1 ameliorated the effects of Wnt on polyfunctionality. Chromatin immunoprecipitation revealed that H4R3me2a, a permissive transcription marker mediated by PRMT1, increased at the IL-2 promoter loci following Wnt activation. In vivo, Wnt-treated T cells exhibited superior polyfunctionality and persistence. When applied to cytomegalovirus (CMV) donor–seropositive, recipient-seronegative patients (D+/R–) lung transplant patient samples, Wnt activation enhanced CMV-specific T cell polyfunctionality, which is important in controlling CMV diseases. These findings reveal a molecular mechanism governing T cell polyfunctionality and identify PRMT1 as a potential target for T cell immunotherapy.

At present, various contradictions in most coal-energy cities have become increasingly prominent, which has become a disharmonious factor restricting the optimization and upgrading of coal-energy cities. Since the turn of the century, taking effective improvement and protection measures and promoting the economic transformation of cities reliant on coal as an energy source has been the primary job of departments at all levels in order to secure the sustainable growth of cities. In this paper, the economic transformation and sustainable growth of coal-energy cities are included in the enhanced TOPSIS economic transformation evaluation model based on the proposed entropy weight. This study examines the industrialization of cities that rely on coal energy resources, assesses the industrial efficacy of coal energy using the DEA technique, and proposes a plan for the industrialization of cities that rely on coal energy resources. This paper summarizes the industrial transformation process of coal-energy cities and designs an evaluation method for the industrial economic transformation of coal-energy cities. This paper determines a set of evaluation index systems suitable for the economic transformation of coal-based energy cities; constructs an evaluation model for the economic transformation of improved TOPSIS coal-based energy cities based on entropy weight; and, finally, calculates and analyzes the industrial economic statistics of a city over the years. It is found that, at the economic structure level, the transformation score of driving forces increases from 0.606 to 0.871; at the level of social economic structures, the transition score of the pressure system increases from 0.476 to 0.779, and the transition score of the state system increases from 0.401 to 0.699; at the level of urban construction structures, the transformation score of the pressure system increases from 0.467 to 0.568; and at the level of comprehensive transformation structures, the transformation score affecting the system increases from 0.611 to 0.716. This shows that, in the process of transformation, the driving force of industrial and economic development in coal-energy-based cities is sufficient, while the pressure of social and economic transformation is great. In the process of transformation, we should strengthen infrastructure construction and protect the urban environment.

Abstract. Schizophrenia is a life-long, complex mental illness that still lacks satisfactory treatments. In recent years, increasing numbers of candidate biomarkers of schizophrenia occurrences and drug responses to schizophrenia therapies have been successfully identified by many omics studies. This review discusses the latest discoveries regarding effective drug targets and relevant drug classifications in schizophrenia. It also assesses our understanding of biomarkers for drug efficacy and adverse drug reactions in current schizophrenia treatments using omics technologies. Future applications in clinical practice have been proposed based on these new findings, and are now considered highly promising strategies to better treat schizophrenia. Finally, we explore several novel approaches that aim to reveal additional genetic signatures of schizophrenia using multi-omics data, which are hoped to improve the diagnosis and treatment of this illness in the future.

Background: Schizophrenia (SCZ) is a severe psychiatric disorder that affects approximately 0.75% of the global population. Both genetic and environmental factors contribute to development of SCZ. SCZ tends to run in family while both genetic and environmental factor contribute to its etiology. Much evidence suggested that alterations in DNA methylations occurred in SCZ patients. Methods: To investigate potential inheritable pattern of DNA methylation in SCZ family, we performed a genome-wide analysis of DNA methylation of peripheral blood samples from 106 Chinese SCZ family trios. Genome-wide DNA methylations were quantified by Agilent 1 × 244 k Human Methylation Microarray. Findings: In this study, we proposed a loci inheritance frequency model that allows characterization of differential methylated regions as SCZ biomarkers. Based on this model, 112 hypermethylated and 125 hypomethylated regions were identified. Additionally, 121 hypermethylated and 139 hypomethylated genes were annotated. The results of functional enrichment analysis indicated that multiple differentially methylated genes (DMGs) involved in Notch/HH/Wnt signaling, MAPK signaling, GPCR signaling, immune response signaling. Notably, a number of hypomethylated genes were significantly enriched in cerebral cortex and functionally enriched in nervous system development. Interpretation: Our findings not only validated previously discovered risk genes of SCZ but also identified novel candidate DMGs in SCZ. These results may further the understanding of altered DNA methylations in SCZ. Funding: None.

Introduction Traditional Chinese exercise therapy, as one of the commonly used exercise interventions for the treatment of type 2 diabetes patients in China, has been proven effective by many clinical practices, but there is still a lack of evidence-based research. This study aims to integrate clinical randomised controlled correlations via network meta-analysis evidence.Methods and analysis The comprehensive search included Chinese and other language databases such as the MEDLINE (PubMed), Web of Science, Excerpt Medica Database (EMBASE), The Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, China Scientific Journal Database (VIP), China Biomedical Literature Database (CBM). Clinical randomised controlled trials of four traditional Chinese exercise therapies in the treatment of type 2 diabetes, including Tai Chi, Ba Duan Jin, Yi Jin Jing and Wu Qin Xi were retrieved. The search time was conducted from the establishment of the database to 30 October 2020. Two researchers screened the documents that met the inclusion criteria, extracted data according to the preset table, and evaluated the methodological quality of the included studies according to the quality evaluation tools recommended by the Cochrane System Reviewer Manual V.5.1. The R language and ADDIS statistical software were used to conduct statistics and analysis of intervention measures.PROSPERO registration number CRD42020214786

Abstract Background Cyclosporine A (CsA) is routinely used to treat patients with steroid‐refractory acute severe ulcerative colitis (ASUC). Here, we studied the underlying mechanisms of CsA‐mediated alleviation in ASUC patients. Methods Neutrophil functions including expression of cytokines, apoptosis, and migration were measured by qRT‐PCR, flow cytometry, and Transwell assay. Dynamic changes of glycolysis and tricarboxylic acid (TCA) cycle were measured by a Seahorse extracellular flux analyzer. Gene differences were determined and verified by RNA sequencing, qRT‐PCR, and Western blotting. Small interfering RNA and inhibitors were used to knock down Sirtuin 6 (SIRT6) in HL‐60 cells and block expression of SIRT6, hypoxia‐inducible factor‐1α (HIF‐1α), and pyruvate dehydrogenase lipoamide kinase isozyme 4 (PDK4) in neutrophils. Results We found that HIF‐1α expression and glycolysis significantly increased, while the release of IL‐8, myeloperoxidase (MPO) and reactive oxygen species (ROS), the apoptosis, and ability of migration markedly decreased in neutrophils of ASUC patients who responded to CsA (Response group) compared with those who did not respond to CsA (Nonresponse group). We also observed that CsA‐induced functional alternation of neutrophils was initiated through suppressing SIRT6 expression, which is responsible for expression of the downstream signaling molecules (e.g., HIF‐1α, PFKFB3) and PDK4 ubiquitination, leading to fueling neutrophil glycolysis and TCA cycle. Furthermore, blockage of SIRT6 signaling demonstrated to be the same functional changes as CsA to decrease the migration of neutrophils. Conclusions The data reveal a novel mechanism of CsA in alleviating ASUC by promoting neutrophil HIF‐1α expression and restricting excessive neutrophil activation in a SIRT6−HIF‐1α−glycolysis axis, suggesting SIRT6 as a candidate target for maintaining mucosal homeostasis and treating intestinal inflammation.

Background. Dysphagia is a common sequelae after stroke. Noninvasive brain stimulation (NIBS) is a tool that has been used in the rehabilitation process to modify cortical excitability and improve dysphagia. Objective. To systematically evaluate the effect of NIBS on dysphagia after stroke and compare the effects of two different NIBS. Methods. Randomized controlled trials about the effect of NIBS on dysphagia after stroke were retrieved from databases of PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang Data, VIP, and CBM, from inception to June 2021. The quality of the trials was assessed, and the data were extracted according to the Cochrane Handbook for Systematic Reviews of Interventions. A statistical analysis was carried out using RevMan 5.3 and ADDIS 1.16.8. The effect size was evaluated by using the standardized mean difference (SMD) and a 95% confidence interval (CI). Results. Ultimately, 18 studies involving 738 patients were included. Meta-analysis showed that NIBS could improve the dysphagia outcome and severity scale (DOSS) score (standard mean difference SMD=1.44, 95% CI 0.80 to 2.08, PtDCS P=0.48, the best probabilistic ranking of the SSA score is rTMS P=0.72>tDCS P=0.28, and the best probabilistic ranking of the PAS score is rTMS P=0.68>tDCS P=0.32. Conclusion. Existing evidence showed that NIBS could improve swallowing dysfunction and reduce the occurrence of aspiration after stroke, and that rTMS is better than tDCS. Limited by the number of included studies, more large-sample, multicenter, double-blind, high-quality clinical randomized controlled trials are still needed in the future to further confirm the results of this research.

Individuals at ultra-high risk (UHR) of psychosis are characterised by the emergence of attenuated psychotic symptoms and deterioration in functioning. In view of the high non-psychotic comorbidity and low rates of transition to psychosis, the specificity of the UHR status has been called into question. This study aims to (i) investigate if the UHR construct is associated with the genetic liability of schizophrenia or other psychiatric conditions; (ii) examine the ability of polygenic risk scores (PRS) to discriminate healthy controls from UHR, remission and conversion status. PRS was calculated for 210 youths (nUHR = 102, nControl = 108) recruited as part of the Longitudinal Youth at Risk Study (LYRIKS) using nine psychiatric traits derived from twelve large-scale psychiatric genome-wide association studies as discovery datasets. PRS was also examined to discriminate UHR-Healthy control status, and healthy controls from UHR remission and conversion status. Result indicated that schizophrenia PRS appears to best index the genetic liability of UHR, while trend level associations were observed for depression and cross-disorder PRS. Schizophrenia PRS discriminated healthy controls from UHR (R2 = 7.9%, p = 2.59 x 10-3, OR = 1.82), healthy controls from non-remitters (R2 = 8.1%, p = 4.90 x 10-4, OR = 1.90), and converters (R2 = 7.6%, p = 1.61 x 10-3, OR = 1.82), with modest predictive ability. A trend gradient increase in schizophrenia PRS was observed across categories. The association between schizophrenia PRS and UHR status supports the hypothesis that the schizophrenia polygenic liability indexes the risk for developing psychosis.

Abstract Ordered nanopatterns of triblock copolymer polystyrene-block-poly(2-vinylpyridine)-block- poly (ethylene oxide)(PS-b-P2VP-b-PEO) have been achieved by the addition of lithium chloride (LiCl). The morphological and structural evolution of PS-b-P2VP-b-PEO/LiCl thin films were systematically investigated by varying different experimental parameters, including the treatment for polymer solution after the addition of LiCl, the time scale of ultrasonic treatment and the molar ratio of Li+ ions to the total number of oxygen atoms (O) in PEO block and the nitrogen atoms (N) in P2VP block. When toluene was used as the solvent for LiCl, ordered nanopattern with cylinders or nanostripes could be obtained after spin-coating. The mechanism of nanopattern transformation was related to the loading of LiCl in different microdomains.

[This corrects the article DOI: 10.1371/journal.pgen.1007329.].

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p

Mesalamine is commonly used to treat ulcerative colitis (UC). Although mesalamine acts topically, in vitro data suggest that intracellular transport is required for its beneficial effect. Genetic variants in mucosal transport proteins may affect this uptake, but the clinical relevance of these variants has not been studied. The aim of this study was to determine whether variants in genes involved in cellular transport affect the response to mesalamine in UC.Subjects with UC from a 6-week clinical trial using multiple doses of mesalamine were genotyped using a genome-wide array that included common exome variants. Analysis focused on cellular transport gene variants with a minor allele frequency >5%. Mesalamine response was defined as improvement in Week 6 Physician's Global Assessment (PGA) and non-response as a lack of improvement in Week 6 PGA. Quality control thresholds included an individual genotyping rate of >90%, SNP genotyping rate of >98%, and exclusion for subjects with cryptic relatedness. All included variants met Hardy-Weinberg equilibrium (p>0.001).457 adults with UC were included with 280 responders and 177 non-responders. There were no common variants in transporter genes that were associated with response to mesalamine. The genetic risk score of responders was similar to that of non-responders (p = 0.18). Genome-wide variants demonstrating a trend towards mesalamine response included ST8SIA5 (p = 1x10-5).Common transporter gene variants did not affect response to mesalamine in adult UC. The response to mesalamine may be due to rare genetic events or environmental factors such as the intestinal microbiome.

UnlabelledGene-based tests of association can increase the power of a genome-wide association study by aggregating multiple independent effects across a gene or locus into a single stronger signal. Recent gene-based tests have distinct approaches to selecting which variants to aggregate within a locus, modeling the effects of linkage disequilibrium, representing fractional allele counts from imputation, and managing permutation tests for p-values. Implementing these tests in a single, efficient framework has great practical value. Fast ASsociation Tests (Fast) addresses this need by implementing leading gene-based association tests together with conventional SNP-based univariate tests and providing a consolidated, easily interpreted report. Fast scales readily to genome-wide SNP data with millions of SNPs and tens of thousands of individuals, provides implementations that are orders of magnitude faster than original literature reports, and provides a unified framework for performing several gene based association tests concurrently and efficiently on the same data.Availabilityhttps://bitbucket.org/baderlab/fast/downloads/FAST.tar.gz, with documentation at https://bitbucket.org/baderlab/fast/wiki/Home.

Inhibition of telomerase by inducing/stabilizing G-quadruplex formation is a promising strategy to design new anticancer drugs. We synthesized and characterized a new dinuclear complex [(dmb)2Ru(obip)Ru(dmb)2](4+) (dmb = 4,4'-dimethyl-2,2'-bipyridine, obip = (2-(2-pyridyl)imidazo[4,5-f][1,10]phenanthroline) with high affinity for both antiparallel and mixed parallel / antiparallel G-quadruplex DNA. This complex can promote the formation and stabilize G-quadruplex DNA. Dialysis and TRAP experiments indicated that [(dmb)2Ru(obip)Ru(dmb)2](4+) acted as an excellent telomerase inhibitor due to its obvious selectivity for G-quadruplex DNA rather than double stranded DNA. In vitro co-culture experiments implied that [(dmb)2Ru(obip)Ru(dmb)2](4+) inhibited telomerase activity and hindered cancer cell proliferation without side effects to normal fibroblast cells. TUNEL assay indicated that inhibition of telomerase activity induced DNA cleavage further apoptosis in cancer cells. Therefore, Ru(II) complex represents an exciting opportunity for anticancer drug design by specifically targeting cancer cell G-quadruplexes DNA.

Genome-wide association studies (GWAS) are now used routinely to identify SNPs associated with complex human phenotypes. In several cases, multiple variants within a gene contribute independently to disease risk. Here we introduce a novel Gene-Wide Significance (GWiS) test that uses greedy Bayesian model selection to identify the independent effects within a gene, which are combined to generate a stronger statistical signal. Permutation tests provide p-values that correct for the number of independent tests genome-wide and within each genetic locus. When applied to a dataset comprising 2.5 million SNPs in up to 8,000 individuals measured for various electrocardiography (ECG) parameters, this method identifies more validated associations than conventional GWAS approaches. The method also provides, for the first time, systematic assessments of the number of independent effects within a gene and the fraction of disease-associated genes housing multiple independent effects, observed at 35%-50% of loci in our study. This method can be generalized to other study designs, retains power for low-frequency alleles, and provides gene-based p-values that are directly compatible for pathway-based meta-analysis.

Yeast two-hybrid screens are an important method for mapping pairwise physical interactions between proteins. The fraction of interactions detected in independent screens can be very small, and an outstanding challenge is to determine the reason for the low overlap. Low overlap can arise from either a high false-discovery rate (interaction sets have low overlap because each set is contaminated by a large number of stochastic false-positive interactions) or a high false-negative rate (interaction sets have low overlap because each misses many true interactions). We extend capture-recapture theory to provide the first unified model for false-positive and false-negative rates for two-hybrid screens. Analysis of yeast, worm, and fly data indicates that 25% to 45% of the reported interactions are likely false positives. Membrane proteins have higher false-discovery rates on average, and signal transduction proteins have lower rates. The overall false-negative rate ranges from 75% for worm to 90% for fly, which arises from a roughly 50% false-negative rate due to statistical undersampling and a 55% to 85% false-negative rate due to proteins that appear to be systematically lost from the assays. Finally, statistical model selection conclusively rejects the Erdös-Rényi network model in favor of the power law model for yeast and the truncated power law for worm and fly degree distributions. Much as genome sequencing coverage estimates were essential for planning the human genome sequencing project, the coverage estimates developed here will be valuable for guiding future proteomic screens. All software and datasets are available in and , -, and -, and are also available from our Web site, http://www.baderzone.org.