A deep catalogue of protein-coding variation in 983,578 individuals.

Rare coding variants that substantially affect function provide insights into the biology of a gene1-3. However, ascertaining the frequency of such variants requires large sample sizes4-8. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser.

Identification of POU4F1 as a novel prognostic biomarker and therapeutic target in esophageal squamous cell carcinoma.

BACKGROUND: Esophageal cancer is a significant global health concern, ranking seventh in incidence and sixth in mortality. It encompasses two pathological types: esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma, with ESCC being more prevalent globally and associated with higher mortality rates. The POU (Pit-Oct-Unc) domain family transcription factors, comprising 15 members, play important roles in embryonic development and organ formation. Aberrant expression of POUs has been observed in several human cancers, influencing cell proliferation, tumor invasion, and drug resistance. However, their specific role in ESCC remains unknown. METHODS: We analyzed TCGA and GEO databases to assess POUs expression in ESCC tissues. Kaplan-Meier and ROC analyses were used to evaluate the prognostic value of POUs. Gene Set Enrichment Analysis and Protein-Protein interaction network were used to explore the potential pathway. Functional assays (Cell Counting Kit-8, EdU Staining assay, and cloning formation assay) and mechanism analyses (RNA-seq, flow cytometry, and Western blot) were conducted to determine the effects of POU4F1 knockdown on ESCC cell phenotypes and signaling pathways. RESULTS: POU4F1 and POU6F2 were upregulated in various cancer tissues, including ESCC, compared to normal tissues. POU4F1 expression was significantly correlated with patient survival and superior to previous models (AUC = 0.776). Knockdown of POU4F1 inhibited ESCC cell proliferation and affected cell cycle, autophagy, and DNA damage pathways in ESCC cells. CONCLUSION: POU4F1 is a novel and promising prognostic and therapeutic target for ESCC patients, providing insights into potential treatment strategies.

Does environmental regulation promote enterprise environmental protection investments? A quasi-natural experiment from river chief system in the Yangtze river delta of China.

The investment decisions of enterprises are affected by environmental regulations designed to protect the environment, so environmental regulations may change companies' investment behavior in environmental protection. This study focuses on the River Chief System (RCS)1, an innovative environmental regulation related to river governance which officially launched in China in 2014. Based on data collected from heavy-polluting companies in the Yangtze River Delta, we use the difference-in-differences model (DID Model)2 and focus on RCS's impacts on micro-environmental protection investments. Our findings reveal that the RCS is conducive to expanding the scale of enterprises' environmental protection investments. Industrial structural upgrades appear to have a masking effect wherein the one-sided pursuit of industrial structural upgrades may slow economic growth and cause enterprises to reduce the scale of environmental investments. We recommend that the allocation of environmental investment should be based on the characteristics of local markets and public participation, and maintain a balance between secondary and tertiary industries, government and business incentives.

Correlation Between Life Satisfaction and Symptoms of ADHD in Dental Students: The Mediation of Resilience.

OBJECTIVE: This study explores the correlation between life satisfaction and ADHD symptoms. It also discusses whether resilience mediates the correlation between ADHD symptoms and life satisfaction. METHOD: We surveyed 297 dental students. A total of 291 completed a self-report scale consisting of the Adult ADHD Self-Report Scale, Wender Utah Rating Scale, Life Satisfaction Scale, and Conner-Davidson Resilience Scale. The study used hierarchical linear regression analysis, resampling, and asymptotic strategies for data processing. RESULTS: The ADHD screening results of the self-report scale were positive for 6.87% of the students. This positive rate differed among participants of diverse ages and varying paternal education levels. ADHD symptoms were negatively correlated with life satisfaction and resilience. Life satisfaction was observably positively associated with resilience. Resilience serves as a mediating role between life satisfaction and the two symptoms of ADHD. CONCLUSION: Resilience intervention programs can enhance the life satisfaction of dental students, especially those with positive ADHD symptoms screening.

PTPN22 through the regulation of Th17/Treg balance acts as a potential target for the treatment of Graves' disease.

Graves' disease (GD) is an autoimmune disease and the most common cause of hyperthyroidism. While the phosphotyrosine phosphatase non-receptor type 22 (PTPN22) variant is associated with GD susceptibility, its precise role and mechanism in GD remain unclear. To investigate this, we induced GD in mice using Ad-TSHR289 and isolated CD4+ T cells from spleen tissues. We conducted a series of experiments, including hematoxylin-eosin staining, enzyme-linked immunosorbent assay (ELISA), immunohistochemistry, flow cytometry, immunofluorescence (IF), reverse transcription quantitative PCR (RT-qPCR), and western blotting. PTPN22 expression was found to be downregulated in GD mice. Overexpression of PTPN22 ameliorated pathological damage and increased serum levels of T4 and thyroid stimulating hormone receptor antibody (TRAb), as well as the ratio of thyroid weight to body weight in GD mice. Furthermore, GD mice exhibited elevated levels of CD4+ and IL-17+ T cells, an increased Th17/Treg ratio, and upregulation of IL-17A mRNA expression. Conversely, there was a decrease in Foxp3+ T cells and transcriptional levels of Foxp3, which were reversed by PTPN22 overexpression. In vitro experiments showed that PTPN22 overexpression in CD4+ T cells from spleen tissues of GD mice enhanced Foxp3 expression while reducing IL-17A expression. Mechanistically, PTPN22 overexpression led to decreased levels of phosphorylated Lck (p-Lck), Lck, phosphorylated Fyn (p-Fyn), Fyn, phosphorylated Zap70 (p-Zap70), and Zap70 in both in vivo and in vitro GD models. In summary, PTPN22 can alleviate thyroid dysfunction in GD by modulating Th17/Treg balance through the downregulation of the Lck/Zap70 signaling axis.

Piezoelectric Biomaterials Inspired by Nature for Applications in Biomedicine and Nanotechnology.

Bioelectricity provides electrostimulation to regulate cell/tissue behaviors and functions. In the human body, bioelectricity can be generated in electromechanically responsive tissues and organs, as well as biomolecular building blocks that exhibit piezoelectricity, with a phenomenon known as the piezoelectric effect. Inspired by natural bio-piezoelectric phenomenon, efforts have been devoted to exploiting high-performance synthetic piezoelectric biomaterials, including molecular materials, polymeric materials, ceramic materials, and composite materials. Notably, piezoelectric biomaterials polarize under mechanical strain and generate electrical potentials, which can be used to fabricate electronic devices. Herein, a review article is proposed to summarize the design and research progress of piezoelectric biomaterials and devices toward bionanotechnology. First, the functions of bioelectricity in regulating human electrophysiological activity from cellular to tissue level are introduced. Next, recent advances as well as structure-property relationship of various natural and synthetic piezoelectric biomaterials are provided in detail. In the following part, the applications of piezoelectric biomaterials in tissue engineering, drug delivery, biosensing, energy harvesting, and catalysis are systematically classified and discussed. Finally, the challenges and future prospects of piezoelectric biomaterials are presented. It is believed that this review will provide inspiration for the design and development of innovative piezoelectric biomaterials in the fields of biomedicine and nanotechnology.

An endophytic fungus interacts with the defensin-like protein OsCAL1 to regulate cadmium allocation in rice.

Defensin-like proteins are conserved in multicellular organisms and contribute to innate immune responses against fungal pathogens. In rice, defensins play a novel role in regulating cadmium (Cd) efflux from the cytosol. However, whether the antifungal activity of defensins correlates with Cd-efflux function remains unknown. In this study, we isolated an endophytic Fusarium, designed Fo10, by a comparative microbiome analysis of rice plants grown in a paddy contaminated with Cd. Fo10 is tolerant to high levels of Cd, but is sensitive to the defensin-like protein OsCAL1, which mediates Cd efflux to the apoplast. We found that Fo10 symbiosis in rice is regulated by OsCAL1 dynamics, and Fo10 coordinates multiple plant processes, including Cd uptake, vacuolar sequestration, efflux to the environment, and formation of Fe plaques in the rhizosphere. These processes are dependent on the salicylic acid signaling pathway to keep Cd levels low in the cytosol of rice cells and to decrease Cd levels in rice grains without any yield penalty. Fo10 also plays a role in Cd tolerance in the poaceous crop maize and wheat, but has no observed effects in the eudicot plants Arabidopsis and tomato. Taken together, these findings provide insights into the mechanistic basis underlying how a fungal endophyte and host plant interact to control Cd accumulation in host plants by adapting defense responses to promote the establishment of a symbiosis that permits adaptation to high-Cd environments.

Data on microRNA expression, predicted gene targets and pathway analysis in response to different concentrations of a cranberry proanthocyanidin-rich extract and its metabolite 3-(4-hydroxyphenyl)-propionic acid in intestinal Caco-2BBe1 cells.

Cranberry-derived proanthocyanidin (PAC) is processed by the gut microbiota to produce 3-(4-hydroxyphenyl)-propionic acid (HPPA), among other metabolites. These data are in support of the article entitled, "Cranberry proanthocyanidin and its microbial metabolite 3,4-dihydroxyphenylacetic acid, but not 3-(4-hydroxyphenyl)-propionic acid, partially reverse pro-inflammatory microRNA responses in human intestinal epithelial cells," published in Molecular Nutrition and Food Research [1]. Here we describe data generated by nCounterⓇ Human v3 miRNA Expression Panel of RNA obtained from Caco-2BBe1 cells exposed to two different concentrations of cranberry extract rich in PAC (50 µg/ml or 100 µg/ml) or 3-(4-hydroxyphenyl)-propionic acid (5 µg/ml or 10 µg/ml) for 24 h, then stimulated with 1 ng/ml of IL-1ß or not (mock) for three hours. The raw data are publicly available at the NCBI GEO database GSE237078. This work also includes descriptive methodological procedures, treatment-responsive microRNA (miRNA) expression profiles in Caco-2BBe1 cells, and in silico mRNA gene target and pathway enrichment analyses of significantly differentially expressed miRNAs (q < 0.001). Cranberry and its components have recognized health benefits, particularly in relation to combatting inflammation and pathogenic bacterial adhesion. These data will be valuable as a reference to study the response of intestinal cells to other polyphenol-rich food sources, analyze gut microbial responses to cranberry and its metabolites in different cell lines and mammalian hosts to elucidate individualized effects, and to delineate the role of the gut microbiota in facilitating the benefits of cranberry. Moreover, these data will aid in expanding our knowledge on the mechanisms underlying the benefits of cranberry and its components.

Early identification of Parkinson's disease with anxiety based on combined clinical and MRI features.

Objective: To identify cortical and subcortical volume, thickness and cortical area features and the networks they constituted related to anxiety in Parkinson's disease (PD) using structural magnetic resonance imaging (sMRI), and to integrate multimodal features based on machine learning to identify PD-related anxiety. Methods: A total of 219 patients with PD were retrospectively enrolled in the study. 291 sMRI features including cortical volume, subcortical volume, cortical thickness, and cortical area, as well as 17 clinical features, were extracted. Graph theory analysis was used to explore structural networks. A support vector machine (SVM) combination model, which used both sMRI and clinical features to identify participants with PD-related anxiety, was developed and evaluated. The performance of SVM models were evaluated. The mean impact value (MIV) of the feature importance evaluation algorithm was used to rank the relative importance of sMRI features and clinical features within the model. Results: 17 significant sMRI variables associated with PD-related anxiety was used to build a brain structural network. And seven sMRI and 5 clinical features with statistically significant differences were incorporated into the SVM model. The comprehensive model achieved higher performance than clinical features or sMRI features did alone, with an accuracy of 0.88, a precision of 0.86, a sensitivity of 0.81, an F1-Score of 0.83, a macro-average of 0.85, a weighted-average of 0.92, an AUC of 0.88, and a result of 10-fold cross-validation of 0.91 in test set. The sMRI feature right medialorbitofrontal thickness had the highest impact on the prediction model. Conclusion: We identified the brain structural features and networks related to anxiety in PD, and developed and internally validated a comprehensive model with multimodal features in identifying.

Impact of hydrogen sulfide on anammox and nitrate/nitrite-dependent anaerobic methane oxidation coupled technologies.

The coupling between anammox and nitrate/nitrite-dependent anaerobic methane oxidation (n-DAMO) has been considered a sustainable technology for nitrogen removal from sidestream wastewater and can be implemented in both membrane biofilm reactor (MBfR) and granular bioreactor. However, the potential influence of the accompanying hydrogen sulfide (H2S) in the anaerobic digestion (AD)-related methane-containing mixture on anammox/n-DAMO remains unknown. To fill this gap, this work first constructed a model incorporating the C/N/S-related bioprocesses and evaluated/calibrated/validated the model using experimental data. The model was then used to explore the impact of H2S on the MBfR and granular bioreactor designed to perform anammox/n-DAMO at practical levels (i.e., 0∼5% (v/v) and 0∼40 g/S m3, respectively). The simulation results indicated that H2S in inflow gas did not significantly affect the total nitrogen (TN) removal of the MBfR under all operational conditions studied in this work, thus lifting the concern about applying AD-produced biogas to power up anammox/n-DAMO in the MBfR. However, the presence of H2S in the influent would either compromise the treatment performance of the granular bioreactor at a relatively high influent NH4+-N/NO2--N ratio (e.g., >1.0) or lead to increased energy demand associated with TN removal at a relatively low influent NH4+-N/NO2--N ratio (e.g., <0.7). Such a negative effect of the influent H2S could not be attenuated by regulating the hydraulic residence time and should therefore be avoided when applying the granular bioreactor to perform anammox/n-DAMO in practice.

UC-stack: a deep learning computer automatic detection system for diabetic retinopathy classification.

Object. The existing diagnostic paradigm for diabetic retinopathy (DR) greatly relies on subjective assessments by medical practitioners utilizing optical imaging, introducing susceptibility to individual interpretation. This work presents a novel system for the early detection and grading of DR, providing an automated alternative to the manual examination.Approach. First, we use advanced image preprocessing techniques, specifically contrast-limited adaptive histogram equalization and Gaussian filtering, with the goal of enhancing image quality and module learning capabilities. Second, a deep learning-based automatic detection system is developed. The system consists of a feature segmentation module, a deep learning feature extraction module, and an ensemble classification module. The feature segmentation module accomplishes vascular segmentation, the deep learning feature extraction module realizes the global feature and local feature extraction of retinopathy images, and the ensemble module performs the diagnosis and classification of DR for the extracted features. Lastly, nine performance evaluation metrics are applied to assess the quality of the model's performance.Main results. Extensive experiments are conducted on four retinal image databases (APTOS 2019, Messidor, DDR, and EyePACS). The proposed method demonstrates promising performance in the binary and multi-classification tasks for DR, evaluated through nine indicators, including AUC and quadratic weighted Kappa score. The system shows the best performance in the comparison of three segmentation methods, two convolutional neural network architecture models, four Swin Transformer structures, and the latest literature methods.Significance. In contrast to existing methods, our system demonstrates superior performance across multiple indicators, enabling accurate screening of DR and providing valuable support to clinicians in the diagnostic process. Our automated approach minimizes the reliance on subjective assessments, contributing to more consistent and reliable DR evaluations.

TFPI from erythroblasts drives heme production in central macrophages promoting erythropoiesis in polycythemia.

Bleeding and thrombosis are known as common complications of polycythemia for a long time. However, the role of coagulation system in erythropoiesis is unclear. Here, we discover that an anticoagulant protein tissue factor pathway inhibitor (TFPI) plays an essential role in erythropoiesis via the control of heme biosynthesis in central macrophages. TFPI levels are elevated in erythroblasts of human erythroblastic islands with JAK2V617F mutation and hypoxia condition. Erythroid lineage-specific knockout TFPI results in impaired erythropoiesis through decreasing ferrochelatase expression and heme biosynthesis in central macrophages. Mechanistically, the TFPI interacts with thrombomodulin to promote the downstream ERK1/2-GATA1 signaling pathway to induce heme biosynthesis in central macrophages. Furthermore, TFPI blockade impairs human erythropoiesis in vitro, and normalizes the erythroid compartment in mice with polycythemia. These results show that erythroblast-derived TFPI plays an important role in the regulation of erythropoiesis and reveal an interplay between erythroblasts and central macrophages.