Differential selection of yield and quality traits has shaped genomic signatures of cowpea domestication and improvement.

Cowpeas (tropical legumes) are important in ensuring food and nutritional security in developing countries, especially in sub-Saharan Africa. Herein, we report two high-quality genome assemblies of grain and vegetable cowpeas and we re-sequenced 344 accessions to characterize the genomic variations landscape. We identified 39 loci for ten important agronomic traits and more than 541 potential loci that underwent selection during cowpea domestication and improvement. In particular, the synchronous selections of the pod-shattering loci and their neighboring stress-relevant loci probably led to the enhancement of pod-shattering resistance and the compromise of stress resistance during the domestication from grain to vegetable cowpeas. Moreover, differential selections on multiple loci associated with pod length, grain number per pod, seed weight, pod and seed soluble sugars, and seed crude proteins shaped the yield and quality diversity in cowpeas. Our findings provide genomic insights into cowpea domestication and improvement footprints, enabling further genome-informed cultivar improvement of cowpeas.

Ferroptosis: An important mechanism of disease mediated by the gut-liver-brain axis.

AIMS: As a unique iron-dependent non-apoptotic cell death, Ferroptosis is involved in the pathogenesis and development of many human diseases and has become a research hotspot in recent years. However, the regulatory role of ferroptosis in the gut-liver-brain axis has not been elucidated. This paper summarizes the regulatory role of ferroptosis and provides theoretical basis for related research. MATERIALS AND METHODS: We searched PubMed, CNKI and Wed of Science databases on ferroptosis mediated gut-liver-brain axis diseases, summarized the regulatory role of ferroptosis on organ axis, and explained the adverse effects of related regulatory effects on various diseases. KEY FINDINGS: According to our summary, the main way in which ferroptosis mediates the gut-liver-brain axis is oxidative stress, and the key cross-talk of ferroptosis affecting signaling pathway network is Nrf2/HO-1. However, there were no specific marker between different organ axes mediate by ferroptosis. SIGNIFICANCE: Our study illustrates the main ways and key cross-talk of ferroptosis mediating the gut-liver-brain axis, providing a basis for future research.

Genetic insights into repurposing statins for hyperthyroidism prevention: a drug-target Mendelian randomization study.

Background: Current therapeutic measures for thyroid dysfunction are limited and often accompanied by adverse effects. The use of lipid-lowering drugs like statins has recently been associated with lower thyroid eye diseases risk. Objective: To investigate the implications of genetically proxied lipid-lowering drugs on thyroid dysfunction. Methods: In this drug-target Mendelian randomization (MR) study, we utilized genetic variants within drug target genes associated with low-density lipoprotein (LDL) or triglyceride (TG), derived from a genome-wide association study (GWAS) meta-analysis (N ≤ 188,577), to simulate lifelong drug interventions. Genetic summary statistics for thyroid dysfunction outcomes were retrieved from GWAS datasets of Thyroid Omics Consortium (N ≤ 54,288) and UK Biobank (N = 484,598). Inverse-variance-weighted MR (IVW-MR) method was performed as primary analysis, followed by validation in colocalization analysis. A subsequent two-step MR analysis was conducted to identify biomarkers mediating the identified drug-outcome association. Results: In IVW-MR analysis, genetic mimicry of 3-hydroxy-3-methylglutarylcoenzyme reductase (HMGCR) inhibitors (e.g. statins) was significantly associated with lower risk of hyperthyroidism in two independent datasets (OR1, 0.417 per 1-mmol/L lower in LDL-C; 95% CI 0.262 to 0.664; P1 = 2.262 × 10-4; OR2 0.996; 95% CI 0.993-0.998; P2 = 0.002). Two-step MR analysis revealed eighteen biomarkers linked to genetic mimicry of HMGCR inhibition, and identified insulin-like growth factor 1 (IGF-1) levels mediating 2.108% of the negative causal relationship between HMGCR inhibition and hyperthyroidism. Conclusion: This study supports HMGCR inhibition as a promising therapeutic strategy for hyperthyroidism and suggests its underlying mechanisms may extend beyond lipid metabolism. Further investigations through laboratory studies and clinical trials are necessary to confirm and elucidate these findings.

Predicting Drug-Drug Interactions Involving Rifampicin Using a Semi-mechanistic Hepatic Compartmental Model.

AIMS: To develop a semi-mechanistic hepatic compartmental model to predict the effects of rifampicin, a known inducer of CYP3A4 enzyme, on the metabolism of five drugs, in the hope of informing dose adjustments to avoid potential drug-drug interactions. METHODS: A search was conducted for DDI studies on the interactions between rifampicin and CYP substrates that met specific criteria, including the availability of plasma concentration-time profiles, physical and absorption parameters, pharmacokinetic parameters, and the use of healthy subjects at therapeutic doses. The semi-mechanistic model utilized in this study was improved from its predecessors, incorporating additional parameters such as population data (specifically for Chinese and Caucasians), virtual individuals, gender distribution, age range, dosing time points, and coefficients of variation. RESULTS: Optimal parameters were identified for our semi-mechanistic model by validating it with clinical data, resulting in a maximum difference of approximately 2-fold between simulated and observed values. PK data of healthy subjects were used for most CYP3A4 substrates, except for gilteritinib, which showed no significant difference between patients and healthy subjects. Dose adjustment of gilteritinib co-administered with rifampicin required a 3-fold increase of the initial dose, while other substrates were further tuned to achieve the desired drug exposure. CONCLUSIONS: The pharmacokinetic parameters AUCR and CmaxR of drugs metabolized by CYP3A4, when influenced by Rifampicin, were predicted by the semi-mechanistic model to be approximately twice the empirically observed values, which suggests that the semi-mechanistic model was able to reasonably simulate the effect. The doses of four drugs adjusted via simulation to reduce rifampicin interaction.

CCDN-DETR: A Detection Transformer Based on Constrained Contrast Denoising for Multi-Class Synthetic Aperture Radar Object Detection.

The effectiveness of the SAR object detection technique based on Convolutional Neural Networks (CNNs) has been widely proven, and it is increasingly used in the recognition of ship targets. Recently, efforts have been made to integrate transformer structures into SAR detectors to achieve improved target localization. However, existing methods rarely design the transformer itself as a detector, failing to fully leverage the long-range modeling advantages of self-attention. Furthermore, there has been limited research into multi-class SAR target detection. To address these limitations, this study proposes a SAR detector named CCDN-DETR, which builds upon the framework of the detection transformer (DETR). To adapt to the multiscale characteristics of SAR data, cross-scale encoders were introduced to facilitate comprehensive information modeling and fusion across different scales. Simultaneously, we optimized the query selection scheme for the input decoder layers, employing IOU loss to assist in initializing object queries more effectively. Additionally, we introduced constrained contrastive denoising training at the decoder layers to enhance the model's convergence speed and improve the detection of different categories of SAR targets. In the benchmark evaluation on a joint dataset composed of SSDD, HRSID, and SAR-AIRcraft datasets, CCDN-DETR achieves a mean Average Precision (mAP) of 91.9%. Furthermore, it demonstrates significant competitiveness with 83.7% mAP on the multi-class MSAR dataset compared to CNN-based models.

Multipatterned Chondrocytes' Scaffolds by FL-MOPL with a BSA-GMA Hydrogel to Regulate Chondrocytes' Morphology.

Repairing articular cartilage damage is challenging due to its low regenerative capacity. In vitro, cartilage regeneration is a potential strategy for the functional reconstruction of cartilage defects. A hydrogel is an advanced material for mimicking the extracellular matrix (ECM) due to its hydrophilicity and biocompatibility, which is known as an ideal scaffold for cartilage regeneration. However, chondrocyte culture in vitro tends to dedifferentiate, leading to fibrosis and reduced mechanical properties of the newly formed cartilage tissue. Therefore, it is necessary to understand the mechanism of modulating the chondrocytes' morphology. In this study, we synthesize photo-cross-linkable bovine serum albumin-glycidyl methacrylate (BSA-GMA) with 65% methacrylation. The scaffolds are found to be suitable for chondrocyte growth, which are fabricated by homemade femtosecond laser maskless optical projection lithography (FL-MOPL). The large-area chondrocyte scaffolds have holes with interior angles of triangle (T), quadrilateral (Q), pentagon (P), hexagonal (H), and round (R). The FL-MOPL polymerization mechanism, swelling, degradation, and biocompatibility of the BSA-GMA hydrogel have been investigated. Furthermore, cytoskeleton and nucleus staining reveals that the R-scaffold with larger interior angle is more effective in maintaining chondrocyte morphology and preventing dedifferentiation. The scaffold's ability to maintain the chondrocytes' morphology improves as its shape matches that of the chondrocytes. These results suggest that the BSA-GMA scaffold is a suitable candidate for preventing chondrocyte differentiation and supporting cartilage tissue repair and regeneration. The proposed method for chondrocyte in vitro culture by developing biocompatible materials and flexible fabrication techniques would broaden the potential application of chondrocyte transplants as a viable treatment for cartilage-related diseases.

TRPV4 antagonist suppresses retinal ganglion cell apoptosis by regulating the activation of CaMKII and TNF-α expression in a chronic ocular hypertension rat model.

Glaucoma is characterized by a progressive loss of retinal ganglion cells (RGCs), leading to irreversible visual function impairment. Sustained increase in intraocular pressure represents a major risk factor for glaucoma, yet the underlying mechanisms of RGC apoptosis induced by intraocular pressure remains unclear. This study aims to investigate the role of TRPV4 in RGC apoptosis in a rat model of chronic ocular hypertension (COH) and the underlying molecular mechanism. In the COH rat models, we evaluated the visual function, retinal pathological changes and RGC apoptosis. TRPV4 expression and downstream signaling molecules were also detected. We found that RGC density decreased and RGC apoptosis was induced in COH eyes compared with control eyes. TRPV4 expression increased significantly in response to elevated IOP. TRPV4 inhibition by the TRPV4 antagonist HC-067047 (HC-067) suppressed RGC apoptosis and protected visual function. HC-067 treatment upregulated the phosphorylation of CaMKII in both control and COH eyes. Finally, HC-067 treatment suppressed the production of TNF-α induced by ocular hypertension. The TRPV4 antagonist HC-067 might suppress RGC apoptosis by regulating the activation of CaMKII and inhibiting the production of TNF-α in the COH model. This indicated that TRPV4 antagonists may be a potential and novel therapeutic strategy for glaucoma.

Cardiac Resolvin D2 ameliorates sepsis-induced cardiomyopathy via inhibiting Caspase-11/GSDMD dependent pyroptosis.

BACKGROUND: Sepsis-induced cardiomyopathy (SICM) is common complication in septic patients with a high mortality and is characterized by an abnormal inflammation response, which was precisely regulated by endogenous specialized pro-resolving mediators (SPMs). However, the metabolic changes of cardiac SPMs during SICM and the roles of SPMs subset in the development of SICM remain unknown. METHODS: In this work, the SPMs concentration was assessed using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) of SICM mice and SICM patients. The cardiac function was measured by echocardiography after the treatment of a SPMs subset, termed Resolvin D2 (RvD2). Caspase-11-/-, GSDMD-/- and double deficient (Caspase-11-/-GSDMD-/-) mice were used to clarify the mechanisms of RvD2 in SICM. RESULTS: We found that endogenous cardiac SPMs were disorders and RvD2 was decreased significantly and correlated with left ventricular ejection fraction (LVEF) and ß-BNP, cTnT in Lipopolysaccharide/Cecum ligation and puncture (CLP) induced SICM models. Treatment with RvD2 attenuated lethality, cardiac dysfunction and cardiomyocytes death during SICM. Mechanistically, RvD2 alleviated SICM via inhibiting Caspase-11/GSDMD-mediated cardiomyocytes pyroptosis. Finally, the plasma levels of RvD2 were also decreased and significantly correlated with IL-1ß, ß-BNP, cTnT and LVEF in patients with SICM. Of note, plasma RvD2 level is indicator of SICM patients from healthy controls or sepsis patients. CONCLUSION: These findings suggest that decreased cardiac RvD2 may involve in the pathogenesis of SICM. In addition, treatment with RvD2 represents a novel therapeutic strategy for SICM by inhibiting cardiomyocytes pyroptosis.

Unraveling the role of low-density lipoprotein-related genes in lung adenocarcinoma: Insights into tumor microenvironment and clinical prognosis.

BACKGROUND: The hypothesized link between low-density lipoprotein (LDL) and oncogenesis has garnered significant interest, yet its explicit impact on lung adenocarcinoma (LUAD) remains to be elucidated. This investigation aims to demystify the function of LDL-related genes (LRGs) within LUAD, endeavoring to shed light on the complex interplay between LDL and carcinogenesis. METHODS: Leveraging single-cell transcriptomics, we examined the role of LRGs within the tumor microenvironment (TME). The expression patterns of LRGs across diverse cellular phenotypes were delineated using an array of computational methodologies, including AUCell, UCell, singscore, ssGSEA, and AddModuleScore. CellChat facilitated the exploration of distinct cellular interactions within LDL_low and LDL_high groups. The findmarker utility, coupled with Pearson correlation analysis, facilitated the identification of pivotal genes correlated with LDL indices. An integrative approach to transcriptomic data analysis was adopted, utilizing a machine learning framework to devise an LDL-associated signature (LAS). This enabled the delineation of genomic disparities, pathway enrichments, immune cell dynamics, and pharmacological sensitivities between LAS stratifications. RESULTS: Enhanced cellular crosstalk was observed in the LDL_high group, with the CoxBoost+Ridge algorithm achieving the apex c-index for LAS formulation. Benchmarking against 144 extant LUAD models underscored the superior prognostic acuity of LAS. Elevated LAS indices were synonymous with adverse outcomes, diminished immune surveillance, and an upsurge in pathways conducive to neoplastic proliferation. Notably, a pronounced susceptibility to paclitaxel and gemcitabine was discerned within the high-LAS cohort, delineating prospective therapeutic corridors. CONCLUSION: This study elucidates the significance of LRGs within the TME and introduces an LAS for prognostication in LUAD patients. Our findings accentuate putative therapeutic targets and elucidate the clinical ramifications of LAS deployment.

Whole Genome Duplication Events Likely Contributed to the Aquatic Adaptive Evolution of Parkerioideae.

As the only aquatic lineage of Pteridaceae, Parkerioideae is distinct from many xeric-adapted species of the family and consists of the freshwater Ceratopteris species and the only mangrove ferns from the genus Acrostichum. Previous studies have shown that whole genome duplication (WGD) has occurred in Parkerioideae at least once and may have played a role in their adaptive evolution; however, more in-depth research regarding this is still required. In this study, comparative and evolutionary transcriptomics analyses were carried out to identify WGDs and explore their roles in the environmental adaptation of Parkerioideae. Three putative WGD events were identified within Parkerioideae, two of which were specific to Ceratopteris and Acrostichum, respectively. The functional enrichment analysis indicated that the lineage-specific WGD events have played a role in the adaptation of Parkerioideae to the low oxygen concentrations of aquatic habitats, as well as different aquatic environments of Ceratopteris and Acrostichum, such as the adaptation of Ceratopteris to reduced light levels and the adaptation of Acrostichum to high salinity. Positive selection analysis further provided evidence that the putative WGD events may have facilitated the adaptation of Parkerioideae to changes in habitat. Moreover, the gene family analysis indicated that the plasma membrane H+-ATPase (AHA), vacuolar H+-ATPase (VHA), and suppressor of K+ transport growth defect 1 (SKD1) may have been involved in the high salinity adaptation of Acrostichum. Our study provides new insights into the evolution and adaptations of Parkerioideae in different aquatic environments.

Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling.

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model links the concentration-time profile of a drug with its therapeutic effects based on the underlying biological or physiological processes. Clinical endpoints play a pivotal role in drug development. Despite the substantial time and effort invested in screening drugs for favourable pharmacokinetic (PK) properties, they may not consistently yield optimal clinical outcomes. Furthermore, in the virtual compound screening phase, researchers cannot observe clinical outcomes in humans directly. These uncertainties prolong the process of drug development. As incorporation of Artificial Intelligence (AI) into the physiologically based pharmacokinetic/pharmacodynamic (PBPK) model can assist in forecasting pharmacodynamic (PD) effects within the human body, we introduce a methodology for utilizing the AI-PBPK platform to predict the PK and PD outcomes of target compounds in the early drug discovery stage. In this integrated platform, machine learning is used to predict the parameters for the model, and the mechanism-based PD model is used to predict the PD outcome through the PK results. This platform enables researchers to align the PK profile of a drug with desired PD effects at the early drug discovery stage. Case studies are presented to assess and compare five potassium-competitive acid blocker (P-CAB) compounds, after calibration and verification using vonoprazan and revaprazan.

Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design.

Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and limited data availability, pose additional challenges to the design process compared to proteins. This review explores the dynamic field of peptide therapeutics, leveraging deep learning to enhance structure prediction and design. Our exploration encompasses various facets of peptide research, ranging from dataset curation handling to model development. As deep learning technologies become more refined, we channel our efforts into peptide structure prediction and design, aligning with the fundamental principles of structure-activity relationships in drug development. To guide researchers in harnessing the potential of deep learning to advance peptide drug development, our insights comprehensively explore current challenges and future directions of peptide therapeutics.

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides.

Cyclic peptides are gaining attention for their strong binding affinity, low toxicity, and ability to target "undruggable" proteins; however, their therapeutic potential against intracellular targets is constrained by their limited membrane permeability, and researchers need much time and money to test this property in the laboratory. Herein, we propose an innovative multimodal model called Multi_CycGT, which combines a graph convolutional network (GCN) and a transformer to extract one- and two-dimensional features for predicting cyclic peptide permeability. The extensive benchmarking experiments show that our Multi_CycGT model can attain state-of-the-art performance, with an average accuracy of 0.8206 and an area under the curve of 0.8650, and demonstrates satisfactory generalization ability on several external data sets. To the best of our knowledge, it is the first deep learning-based attempt to predict the membrane permeability of cyclic peptides, which is beneficial in accelerating the design of cyclic peptide active drugs in medicinal chemistry and chemical biology applications.

Targeting NEDD8 suppresses surgical stress-facilitated metastasis of colon cancer via restraining regulatory T cells.

Regulatory T cells (Tregs) are a key determinant for the immunosuppressive and premetastatic niche for cancer progression after surgery resection. However, the precise mechanisms regulating Tregs function during surgical stress-facilitated cancer metastasis remain unknown. This study aims to unravel the mechanisms and explore potential strategies for preventing surgical stress-induced metastasis by targeting NEDD8. Using a surgical stress mouse model, we found that surgical stress results in the increased expression of NEDD8 in Tregs. NEDD8 depletion abrogates postoperative lung metastasis of colon cancer cells by inhibiting Treg immunosuppression and thereby partially recovering CD8+T cell and NK cell-mediated anti-tumor immunity. Furthermore, Treg mitophagy and mitochondrial respiration exacerbated in surgically stressed mice were attenuated by NEDD8 depletion. Our observations suggest that cancer progression may result from surgery-induced enhancement of NEDD8 expression and the subsequent immunosuppressive function of Tregs. More importantly, depleting or inhibiting NEDD8 can be an efficient strategy to reduce cancer metastasis after surgery resection by regulating the function of Tregs.

Efficient pulmonary lymphatic drainage is necessary for inflammation resolution in ARDS.

The lymphatic vasculature is the natural pathway for the resolution of inflammation, yet the role of pulmonary lymphatic drainage function in sepsis-induced acute respiratory distress syndrome (ARDS) remains poorly characterized. In this study, indocyanine green-near infrared lymphatic living imaging was performed to examine pulmonary lymphatic drainage function in septic mouse models. We found that the pulmonary lymphatic drainage was impaired owing to the damaged lymphatic structure in sepsis-induced ARDS. Moreover, prior lymphatic defects by blocking vascular endothelial growth factor receptor-3 (VEGFR-3) worsened sepsis-induced lymphatic dysfunction and inflammation. Posttreatment with vascular endothelial growth factor-C (Cys156Ser) (VEGF-C156S), a ligand of VEGFR-3, ameliorated lymphatic drainage by rejuvenating lymphatics to reduce the pulmonary edema and promote draining of pulmonary macrophages and neutrophils to pretracheal lymph nodes. Meanwhile, VEGF-C156S posttreatment reversed sepsis-inhibited CC chemokine ligand 21 (CCL21), which colocalizes with pulmonary lymphatic vessels. Furthermore, the advantages of VEGF-C156S on the drainage of inflammatory cells and edema fluid were abolished by blocking VEGFR-3 or CCL21. These results suggest that efficient pulmonary lymphatic drainage is necessary for inflammation resolution in ARDS. Our findings offer a therapeutic approach to sepsis-induced ARDS by promoting lymphatic drainage function.

Polyolefin-derived substrate-grown carbon nanotubes as binder-free electrode for hydrogen evolution in alkaline media.

Switching from a linear mode of waste management to a circular loop by transforming plastic waste into carbon nanotubes (CNTs) is a promising approach to current plastic waste treatment. One of the many applications of CNTs is its use for electrocatalytic water splitting for hydrogen evolution. Existing methods of CNTs-based hydrogen evolution reaction (HER) electrode fabrication involve additives like polymeric binders and additional steps to improve CNT dispersion, which are detrimental to the CNT structure and properties. The in-situ fabrication approach can potentially be a one-pot solution to HER electrode synthesis. In this study, polyolefins pyrolysis gas and a Co:Ni:Mg catalyst were used to fabricate binder-free CNTs-based electrodes on different substrates for HER. The study assessed CNT quality on conductive carbon paper, semiconductive silicon, and dielectric glass substrates, evaluating their HER performance in 1 M KOH. A mixture of hollow-core, bamboo-like, and cup-stacked arrangement nanotubes were synthesized on the substrates, with CNTs on glass and carbon paper substrates possessing better graphitization than CNTs grown on silicon. This is in agreement with HER performance, whereby the as-prepared electrodes required overpotentials of 267 mV, 241 mV, and 216 mV for silicon, glass, and carbon paper, respectively, to achieve 10 mA/cm2. Despite being poorly conductive, the glass substrate electrode achieved a lower overpotential than the silicon electrode. Additionally, the as-prepared silicon electrode faced a delamination issue likely attributed to the lower surface energy of the silicon substrate surface, demonstrating the weaker adhesion between the CNTs and silicon surface. The proposed approach thus showed that the in-situ fabricated electrodes performed better than separately synthesized CNTs prepared into electrodes by 27.4% and 14.2% for carbon paper and glass substrates, respectively. The improved performance of the as-prepared, binder-free electrodes can be linked to the lower charge-transfer resistance and reduced contact resistance between the CNTs and substrate.

CXCL16 exacerbates Pseudomonas aeruginosa keratitis by promoting neutrophil activation.

Pseudomonas aeruginosa (PA) keratitis is a major cause of blindness characterized by corneal inflammation. In a murine model of PA keratitis, we assessed the detrimental effects of CXC chemokine ligand 16 (CXCL16). Quantitative PCR (qPCR), western blotting (WB) and immunofluorescence were used to measure the expression and localization of CXCL16 and its receptor, CXC chemokine receptor 6 (CXCR6). Clinical scores, plate counting, and hematoxylin-eosin staining were used to assess infection severity and its exacerbation by CXCL16. Immunofluorescence, myeloperoxidase assays, and flow cytometry were used to detect neutrophil activity and colocalization with CXCR6. WB and immunofluorescence were used to measure levels of reactive oxygen species (ROS) and matrix metalloproteinases (MMPs). These methods also were used to measure the activation of downstream NF-κB signaling and its positive feedback on CXCL16 expression. ELISA, flow cytometry, and qPCR were used to measure the expression of CXCL2 and T helper 17 (Th17) cell-related genes. CXCL16 and CXCR6 expression was increased in infected corneas. Topical application of CXCL16 exacerbated keratitis by increasing corneal bacterial load and promoting neutrophil infiltration, whereas neutralizing antibody against CXCL16 had the opposite effect. CXCL16 also increased ROS and MMP levels. This neutrophil activation may be caused by its positive feedback with the NF-κB pathway and the upregulation of CXCL2 and Th17 cell related-genes. These data suggest that CXCL16 is an attractive therapeutic target for PA keratitis.

Efficient Computational Framework for Target-Specific Active Peptide Discovery: A Case Study on IL-17C Targeting Cyclic Peptides.

The development of potentially active peptides for specific targets is critical for the modern pharmaceutical industry's growth. In this study, we present an efficient computational framework for the discovery of active peptides targeting a specific pharmacological target, which combines a conditional variational autoencoder (CVAE) and a classifier named TCPP based on the Transformer and convolutional neural network. In our example scenario, we constructed an active cyclic peptide library targeting interleukin-17C (IL-17C) through a library-based in vitro selection strategy. The CVAE model is trained on the preprocessed peptide data sets to generate potentially active peptides and the TCPP further screens the generated peptides. Ultimately, six candidate peptides predicted by the model were synthesized and assayed for their activity, and four of them exhibited promising binding affinity to IL-17C. Our study provides a one-stop-shop for target-specific active peptide discovery, which is expected to boost up the process of peptide drug development.

Manipulation of Spin-Orbit Torque in Tungsten Oxide/Manganite Heterostructure by Ionic Liquid Gating and Orbit Engineering.

Spin-orbit coupling (SOC) is the interaction between electron's spin and orbital motion, which could realize a charge-to-spin current conversion and enable an innovative method to switch the magnetization by spin-orbit torque (SOT). Varied techniques have been developed to manipulate and improve the SOT, but the role of the orbit degree of freedom, which should have a crucial bearing on the SOC and SOT, is still confusing. Here, we find that the charge-to-spin current conversion and SOT in W3O8-δ/(La, Sr)MnO3 could be produced or eliminated by ionic liquid gating. Through tuning the preferential occupancy of Mn/W-d electrons from the in-plane (dx2-y2) to out-of-plane (d3z2-r2) orbit, the SOT damping-like field efficiency is nearly doubled due to the enhanced spin Hall effect and interfacial Rashba-Edelstein effect. These findings not only offer intriguing opportunities to control the SOT for high-efficient spintronic devices but also could be a fundamental step toward spin-orbitronics in the future.

Homozygous missense variant in MEIOSIN causes premature ovarian insufficiency.

STUDY QUESTION: Are variants of genes involved in meiosis initiation responsible for premature ovarian insufficiency (POI)? SUMMARY ANSWER: A MEIOSIN variant participates in the pathogenesis of human POI by impairing meiosis due to insufficient transcriptional activation of essential meiotic genes. WHAT IS KNOWN ALREADY: Meiosis is the key event for the establishment of the ovarian reserve, and several gene defects impairing meiotic homologous recombination have been found to contribute to the pathogenesis of POI. Although STRA8 and MEIOISN variants have been found to associate with POI in a recent study, the condition of other meiosis initiation genes is unknown and direct evidence of variants participating in the pathogenesis of POI is still lacking. STUDY DESIGN, SIZE, DURATION: This was a retrospective genetic study. An in-house whole exome sequencing (WES) database of 1030 idiopathic POI patients was screened for variations of meiosis initiation genes. PARTICIPANTS/MATERIALS, SETTING, METHODS: Homozygous or compound heterozygous variations of genes involved in meiosis initiation were screened in the in-house WES database. The pathogenicity of the variation was verified by in vitro experiments, including protein structure prediction and dual-luciferase reporter assay. The effect of the variant on ovarian function and meiosis was demonstrated through histological analyses in a point mutation mouse model. MAIN RESULTS AND THE ROLE OF CHANCE: One homozygous variant in MEIOSIN (c.1735C>T, p.R579W) and one in STRA8 (c.258 + 1G>A), which initiates meiosis via the retinoic acid-dependent pathway, were identified in a patient with idiopathic POI respectively. The STRA8 variation has been reported in the recently published work. For the MEIOSIN variation, the dual-luciferase reporter assay revealed that the variant adversely affected the transcriptional function of MEIOSIN in upregulating meiotic genes. Furthermore, knock-in mice with the homologous mutation confirmed that the variation impacted the meiotic prophase I program and accelerated oocyte depletion. Moreover, the variant p.R579W localizing in the high-mobility group (HMG) box domain disrupted the nuclear localization of the MEIOSIN protein but was dispensable for the cell-cycle switch of oocytes, suggesting a unique role of the MEIOSIN HMG box domain in meiosis initiation. LIMITATIONS, REASONS FOR CAUTION: Further studies are needed to explore the role of other meiosis initiation genes in the pathogenesis of POI. WIDER IMPLICATIONS OF THE FINDINGS: The MEIOSIN variant was verified to cause POI by impaired transcriptional regulation of meiotic genes and was inherited by a recessive mode. The function of HMG box domain in MEIOSIN protein was also expanded by this study. Although causative variations in meiotic initiation genes are rare in POI, our study confirmed the pathogenicity of a MEIOSIN variant and elucidated another mechanism of human infertility. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Key Research & Developmental Program of China (2022YFC2703800, 2022YFC2703000), National Natural Science Foundation for Distinguished Young Scholars (82125014), National Natural Science Foundation of China (32070847, 32170867, 82071609), Basic Science Center Program of NSFC (31988101), Natural Science Foundation of Shandong Province for Grand Basic Projects (ZR2021ZD33), Natural Science Foundation of Shandong Province for Excellent Young Scholars (ZR2022YQ69), Taishan Scholars Program for Young Experts of Shandong Province (tsqn202211371), and Qilu Young Scholars Program of Shandong University. The authors declare no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.