Research on the toxicological prognostic significance of age-related genes in endometrial cancer unveiling key factors in patient prognosis.

This study investigates the influence of aging-related genes on endometrial cancer, a prominent gynecological malignancy with rising incidence and mortality. By analyzing gene expression differences between cancerous and normal endometrial tissues, 42 aging-related genes were identified as differentially expressed. Utilizing the TCGA-UCEC sample, consensus clustering divided the samples into two molecular subgroups, Aging low and Aging high, based on their expression profiles. These subgroups showed distinct prognoses and survival rates, with the Aging high group associated with DNA repair and cell cycle pathways, and the Aging low group showing suppressed metabolic pathways and increased immune cell infiltration, suggesting a potential for better immunotherapy outcomes. Mutation analysis did not find significant differences in mutation frequencies between the groups, but a high Tumor Mutation Burden (TMB) correlated with better prognosis. A risk score model was also developed, showcasing significant prognostic power. Further analysis of the SIX1 gene revealed its overexpression in cancer cells. Drug sensitivity tests indicated that the low-risk group might respond better to chemotherapy. This research underscores the significance of aging-related genes in endometrial cancer, offering insights into their prognostic value and therapeutic potential, which could lead to personalized treatment approaches and enhanced patient management.

CollaPPI: A Collaborative Learning Framework for Predicting Protein-Protein Interactions.

Exploring protein-protein interaction (PPI) is of paramount importance for elucidating the intrinsic mechanism of various biological processes. Nevertheless, experimental determination of PPI can be both time-consuming and expensive, motivating the exploration of data-driven deep learning technologies as a viable, efficient, and accurate alternative. Nonetheless, most current deep learning-based methods regarded a pair of proteins to be predicted for possible interaction as two separate entities when extracting PPI features, thus neglecting the knowledge sharing among the collaborative protein and the target protein. Aiming at the above issue, a collaborative learning framework CollaPPI was proposed in this study, where two kinds of collaboration, i.e., protein-level collaboration and task-level collaboration, were incorporated to achieve not only the knowledge-sharing between a pair of proteins, but also the complementation of such shared knowledge between biological domains closely related to PPI (i.e., protein function, and subcellular location). Evaluation results demonstrated that CollaPPI obtained superior performance compared to state-of-the-art methods on two PPI benchmarks. Besides, evaluation results of CollaPPI on the additional PPI type prediction task further proved its excellent generalization ability.

Evaluation study of single-anastomosis duodenal-ileal bypass with sleeve gastrectomy in the treatment of Chinese obese patients based on efficacy and nutrition.

To evaluate the efficacy and nutrition of single-anastomosis duodenal-ileal bypass with sleeve gastrectomy (SADI-S) in Chinese obese patients in the first postoperative year. Clinical data of 66 obese patients who underwent SADI-S surgery at China-Japan Union Hospital of Jilin University from November 2018 to May 2022 were retrospectively collected. The weight, body mass index (BMI), percentage of excess weight loss (%EWL), and percentage of total weight loss (%TWL) were recorded at 3, 6, and 12 months after surgery. Moreover, metabolic disease remission and nutrient deficiencies were assessed at 1 year postoperatively. Overall, 66 patients (38 males and 28 females) were recruited, with a mean age of 35 (18-61) years and an average preoperative BMI of 42.94 kg/m2. Before surgery, 38 patients had type 2 diabetes mellitus (T2DM), 46 patients had hyperuricemia (HUA), 45 patients had hypertension (HTN), 35 patients had hyperlipidemia, 12 patients had hypercholesterolemia, 12 patients had hyper-low-density lipoproteinemia, and 14 patients had gastroesophageal reflux disease symptoms (GERD). All patients had undergone a DaVinci robotic or laparoscopic SADI-S surgery, and none converted to laparotomy or died. Four patients developed postoperative complications and were cured and discharged after conservative treatment or surgical treatment. At 3, 6 and 12 months, the average %EWL was 62.07 ± 26.56, 85.93 ± 27.92, and 106.65 ± 29.65%, %TWL was 22.67 ± 4.94, 32.10 ± 5.18, and 40.56 ± 7.89%, respectively. Fasting blood glucose (FBG), glycated hemoglobin (HbA1c), uric acid (UA), triglycerides (TG), blood pressure (BP), and other indexes were significantly lower after one year post-surgery compared with the preoperative period (P < 0.05). The remission rates of T2DM, HUA, HTN, hypertriglyceridemia, hypercholesterolemia, and hyper-low-density lipoproteinemia 1 year after surgery were 100, 65.2, 62.2, 94.3, 100, and100%, respectively. One year after surgery, the remission rate of GERD was 71.4% (10/14), the rate of new occurrence of GERD was 12.1% (8/66), and the overall incidence rate was 18.2% (12/66). Except for vitamin B12(vit B12), the other nutrient indexes were significantly decreased after 1 year of surgery relative to levels before surgery (P < 0.05). The deficiency rates for vitamin A (vit A), vitamin E (vit E), zinc ion (Zn), and folic acid (FA) were higher (45.5, 25.8, 24.2, and 16.7%, respectively); however, there were no related clinical symptoms. SADI-S had significant effects on weight loss and metabolic disease remission. The main nutrient deficiencies after SADI-S were vit A, vit E, Zn, and FA deficiencies. The long-term efficacy and safety of SADI-S warrant further follow-up.

Large-Scale Molecular Dynamics Simulation Based on Heterogeneous Many-Core Architecture.

As the application of molecular dynamics (MD) simulations continues to evolve, the demand for accelerating large-scale simulation systems and handling of enormous simulation tasks is steadily increasing. We propose a parallel acceleration method for large-scale MD simulations based on Sunway heterogeneous many-core processors. This method integrates task scheduling, simulation calculations, and data storage, effectively tackling issues related to large-scale simulations and numerous simulation tasks. The task scheduling strategy flexibly handles tasks on various scales and enables parallel execution of multiple tasks. During the simulation calculations, we ported GROMACS to the Sunway architecture and accelerated the calculation of short-range forces through a heterogeneous processor. Our method achieves approximately 10-fold acceleration and 90% scalability when executing a single simulation task. When handling numerous simulation tasks, our method achieves parallel execution of all of the tasks with 90% scalability. By employing our method, we carried out 50 ns simulations on over 3000 distinct conotoxin structures individually within just 5 h. Additionally, we evaluated more than 200 protein-ligand complexes, and the simulation efficiency significantly exceeded that of midsized to small GPU clusters.

5-FU promotes HBV replication through oxidative stress-induced autophagy dysfunction.

BACKGROUND & AIMS: Hepatitis B virus (HBV) reactivation is a major problem that must be overcome during chemotherapy for HBV-related hepatocellular carcinoma (HCC). However, the mechanism underlying chemotherapy-associated HBV reactivation is still not fully understood, hindering the development of improved HBV-related HCC treatments. METHODS: A meta-analysis was performed to assess the HBV reactivation risk during transcatheter arterial chemoembolization (TACE). To investigate the regulatory effects and mechanisms of 5-FU on HBV replication, an HBV mouse model was established by pAAV-HBV1.2 hydrodynamic injection followed by intraperitoneal 5-FU injection, and different in vitro models (HepG2.2.15 or Huh7 cells) were established. Realtime RT‒qPCR, western blotting, luciferase assays, and immunofluorescence were used to determine viral parameters. We also explored the underlying mechanisms by RNA-seq, oxidative stress evaluation and autophagy assessment. RESULTS: The pooled estimated rate of HBV reactivation in patients receiving TACE was 30.3 % (95 % CI, 23.1%-37.4 %). 5-FU, which is a chemotherapeutic agent commonly used in TACE, promoted HBV replication in vitro and in vivo. Mechanistically, 5-FU treatment obviously increased autophagosome formation, as shown by increased LC3-II levels. Additionally, 5-FU impaired autophagic degradation, as shown by marked p62 and mCherry-GFP-LC3 upregulation, ultimately promoting HBV replication and secretion. Autophagy inhibition by 3-methyladenine or chloroquine significantly altered 5-FU-induced HBV replication. Furthermore, 5-FU-induced autophagy and HBV replication were markedly attenuated with a reactive oxygen species (ROS) scavenger. CONCLUSIONS: Together, our results indicate that ROS-induced autophagosome formation and autophagic degradation play a critical role in 5-FU-induced HBV reactivation.

Molecular mechanism of sex pheromone perception in male Mythimna loreyi revealed by in vitro system.

BACKGROUND: Mythimna loreyi is an important agricultural pest with a sensitive sex pheromone communication system. To clarify the pheromone binding proteins (PBPs) and pheromone receptors (PRs) involved in sex pheromone perception is important for both understanding the molecular olfactory mechanism and developing a new pest control strategy in M. loreyi. RESULTS: First, the electroantennogram (EAG) assay showed that male M. loreyi displayed the highest response to the major sex pheromone component Z9-14:Ac, and higher responses to two minor components, Z7-12:Ac and Z11-16:Ac. Second, the fluorescence competition binding assay showed that PBP1 bound all three pheromones and other tested compounds with high or moderate affinity, while PBP2 and PBP3 each bound only one pheromone component and few other compounds. Third, functional study using the Xenopus oocyte system demonstrated that, of the six candidate PRs, PR2 was weakly sensitive to the major pheromone Z9-14:Ac, but was strongly sensitive to pheromone analog Z9-14:OH; PR3 was strongly and specifically sensitive to a minor component Z7-12:Ac; PR4 and OR33 were both weakly sensitive to another minor component, Z11-16:Ac. Finally, phylogenetic relationship and ligand profiles of PRs were compared among six species from two closely related genera Mythimna and Spodoptera, suggesting functional shifts of M. loreyi PRs toward Spodoptera PRs. CONCLUSION: Functional differentiations were revealed among three PBPs and six PRs in sex pheromone perception, laying an important basis for understanding the molecular mechanism of sex pheromone perception and for developing new control strategies in M. loreyi. © 2023 Society of Chemical Industry.

Ionotropic Receptor IR75q.2 Mediates Avoidance Reaction to Nonanoic Acid in the Fall Armyworm Spodoptera frugiperda (Lepidoptera, Noctuidae).

Ionotropic receptors (IRs) play an important role in olfaction, but little is known in nondrosophila insects. Here, we report in vitro and in vivo functional characterization of IR75q.2 in the invasive moth pest Spodoptera frugiperda. First, 13 IRs (including four coreceptor IRs) were found specifically or highly expressed in adult antennae. Second, these IRs were tested for responding profiles to 59 odorants using the Xenopus oocyte expression system, showing that only SfruIR75q.2 responded to 8-10C fatty acids and their corresponding aldehydes, with SfruIR8a as the only coreceptor. Third, the three acids (especially nonanoic acid) showed repellent effects on moth's behavior and oviposition, but the repellence significantly reduced to the insects with IR75q.2 knockout by CRISPR/Cas9. Taken together, our study reveals the function of SfruIR75q.2 in perception of acid and aldehyde odorants and provides the first in vivo evidence for olfactory function of an odor-specific IR in Lepidoptera.

GraphGPT: A Graph Enhanced Generative Pretrained Transformer for Conditioned Molecular Generation.

Condition-based molecular generation can generate a large number of molecules with particular properties, expanding the virtual drug screening library, and accelerating the process of drug discovery. In this study, we combined a molecular graph structure and sequential representations using a generative pretrained transformer (GPT) architecture for generating molecules conditionally. The incorporation of graph structure information facilitated a better comprehension of molecular topological features, and the augmentation of a sequential contextual understanding of GPT architecture facilitated molecular generation. The experiments indicate that our model efficiently produces molecules with the desired properties, with valid and unique metrics that are close to 100%. Faced with the typical task of generating molecules based on a scaffold in drug discovery, our model is able to preserve scaffold information and generate molecules with low similarity and specified properties.

Binding Properties of Odorant-Binding Protein 7 to Host Volatiles in Larvae of Spodoptera frugiperda.

The chemosensory system is crucial during the growth and development of the moths. Spodoptera frugiperda (Lepidoptera: Noctuidae) is one of the most destructive insect pests. However, there is little functional research on odorant-binding proteins (OBPs) in the larval stage of S. frugiperda. Here, we obtained SfruOBP7 from transcriptomics and conducted the sequence analysis. We used quantitative real-time PCR to explore the expression profiles of SfruOBP7. The function identification showed that SfruOBP7 has a binding ability to 18 plant volatiles. Further molecular docking and site-directed mutant assay revealed that Lys45 and Phe110 were the key binding sites for SfruOBP7 interacting with linalool. In the behavior assays, linalool could attract the larvae, and dsOBP7-treated larvae lost their attraction to linalool. Our results help to reveal the essential molecular mechanism of the olfactory perception in the larvae and design an attractant based on the host volatiles.

Molecular generation strategy and optimization based on A2C reinforcement learning in de novo drug design.

MOTIVATION: In the field of pharmacochemistry, it is a time-consuming and expensive process for the new drug development. The existing drug design methods face a significant challenge in terms of generation efficiency and quality. RESULTS: In this paper, we proposed a novel molecular generation strategy and optimization based on A2C reinforcement learning. In molecular generation strategy, we adopted transformer-DNN to retain the scaffolds advantages, while accounting for the generated molecules' similarity and internal diversity by dynamic parameter adjustment, further improving the overall quality of molecule generation. In molecular optimization, we introduced heterogeneous parallel supercomputing for large-scale molecular docking based on message passing interface communication technology to rapidly obtain bioactive information, thereby enhancing the efficiency of drug design. Experiments show that our model can generate high-quality molecules with multi-objective properties at a high generation efficiency, with effectiveness and novelty close to 100%. Moreover, we used our method to assist shandong university school of pharmacy to find several candidate drugs molecules of anti-PEDV. AVAILABILITY AND IMPLEMENTATION: The datasets involved in this method and the source code are freely available to academic users at https://github.com/wq-sunshine/MomdTDSRL.git.

HiSIF-DTA: A Hierarchical Semantic Information Fusion Framework for Drug-Target Affinity Prediction.

Accurately identifying drug-target affinity (DTA) plays a significant role in promoting drug discovery and has attracted increasing attention in recent years. Exploring appropriate protein representation methods and increasing the abundance of protein information is critical in enhancing the accuracy of DTA prediction. Recently, numerous deep learning-based models have been proposed to utilize the sequential or structural features of target proteins. However, these models capture only the low-order semantics that exist in a single protein, while the high-order semantics abundant in biological networks are largely ignored. In this article, we propose HiSIF-DTA'a hierarchical semantic information fusion framework for DTA prediction. In this framework, a hierarchical protein graph is constructed that includes not only contact maps as low-order structural semantics but also protein-rotein interaction (PPI) networks as high-order functional semantics. Particularly, two distinct hierarchical fusion strategies (i.e., Top-down and Bottom-Up) are designed to integrate the different protein semantics, therefore contributing to a richer protein representation. Comprehensive experimental results demonstrate that HiSIF-DTA outperforms current state-of-the-art methods for prediction on the benchmark datasets of the DTA task. Further validation on binary tasks and visualization analysis demonstrates the generalization and interpretation abilities of the proposed method.

An odorant receptor tuned to an attractive plant volatile vanillin in Spodoptera litura.

The insect olfaction plays crucial roles in many important behaviors, in which ORs are key determinants for signal transduction and the olfactory specificity. Spodoptera litura is a typical polyphagous pest, possessing a large repertoire of ORs tuning to broad range of plant odorants. However, the specific functions of those ORs remain mostly unknown. In this study, we functionally characterized one S. litura OR (OR51) that was highly expressed in the adult antennae. First, by using Xenopus oocyte expression and two-electrode voltage clamp recording system (XOE-TEVC), OR51 was found to be strongly and specifically responsive to vanillin (a volatile of S. litura host plants) among 77 tested odorants. Second, electroantennogram (EAG) and Y-tube behavioral experiment showed that vanillin elicited significant EAG response and attraction behavior especially of female adults. This female attraction was further confirmed by the oviposition experiment, in which the soybean plants treated with vanillin were significantly preferred by females for egg-laying. Third, 3D structural modelling and molecular docking were conducted to explore the interaction between OR51 and vanillin, which showed a high affinity (-4.46 kcal/mol) and three residues (Gln163, Phe164 and Ala305) forming hydrogen bonds with vanillin, supporting the specific binding of OR51 to vanillin. In addition, OR51 and its homologs from other seven noctuid species shared high amino acid identities (78-97%) and the same three hydrogen bond forming residues, suggesting a conserved function of the OR in these insects. Taken together, our study provides some new insights into the olfactory mechanisms of host plant finding and suggests potential applications of vanillin in S. litura control.

Merge Loss Calculation Method for Highly Imbalanced Data Multiclass Classification.

In real classification scenarios, the number distribution of modeling samples is usually out of proportion. Most of the existing classification methods still face challenges in comprehensive model performance for imbalanced data. In this article, a novel theoretical framework is proposed that establishes a proportion coefficient independent of the number distribution of modeling samples and a general merge loss calculation method independent of class distribution. The loss calculation method of the imbalanced problem focuses on both the global and batch sample levels. Specifically, the loss function calculation introduces the true-positive rate (TPR) and the false-positive rate (FPR) to ensure the independence and balance of loss calculation for each class. Based on this, global and local loss weight coefficients are generated from the entire dataset and batch dataset for the multiclass classification problem, and a merge weight loss function is calculated after unifying the weight coefficient scale. Furthermore, the designed loss function is applied to different neural network models and datasets. The method shows better performance on imbalanced datasets than state-of-the-art methods.

Conserved Odorant Receptors Involved in Nonanal-Induced Female Attractive Behavior in Two Spodoptera Species.

Moths rely on plant volatiles to locate appropriate plants for feeding and laying eggs. While extensive research has been conducted on the global agricultural pests, Spodoptera frugiperda and Spodoptera litura, their molecular mechanisms for detecting plant volatiles remain mostly unknown. Here, we have demonstrated that nonanal, a common plant volatile, is attractive for both virgin and gravid females of the two species. Second, we have identified a conserved odorant receptor clade (SfruOR47 clade) that is primarily tuned to nonanal. Finally, by three-dimensional (3D) structure prediction, molecular docking, and site-directed mutagenesis, we have revealed that the His57 and Glu61 residues, also shared by other six orthologous ORs, are essential for nonanal binding in SfruOR47 and SlituOR9, indicating the conserved structure and function of ORs in the SfruOR47 clade. These findings offer novel insights into the molecular mechanisms and evolutionary aspects of moth behavior in response to plant volatiles.

Factors related to dietary quality among older stroke high-risk population in Tianjin community, China: a multicenter study.

BACKGROUND: Stroke is a common and frequently-occurring disease in older people. It has the characteristics of high morbidity, high mortality, high recurrence rate and high disability rate. Most stroke risk studies are based on pathophysiology, however psychosocial factors such as diet quality are often understudied. The aim of this study was to assess stroke risk in urban community residents in Tianjin and investigate the factors that affect the dietary quality of older stroke high-risk populations. METHODS: Using a cross-sectional, multicenter study, recruit people aged 60 to 80 in Tianjin. Dietary intake data were obtained through a validated food frequency questionnaire, which were used to calculate Alternate Healthy Eating Index-2010 (AHEI-2010) and to analyze its association with sociodemographic characteristics, stroke risk factors and health marker variables. RESULTS: A total of 1068 participants from 4 community health service centers in Tianjin were recruited, including 300 low-risk individuals and 768 high-risk individuals. Compared with the low-risk group (62.75 ± 3.59), the AHEI-2010 mean score of the high-risk group (56.83 ± 6.54) was significantly lower. The top three most common risk factors among participants were dyslipidemia (80.3%), hypertension (60.6%), and physical inactivity (58.2%). Multiple logistic regression showed that diet quality was independently and significantly associated with stroke risk (OR = 0.765; 95%CI: 0.690-0.848, p < 0.001). CONCLUSION: The diet quality of high-risk stroke population in Tianjin is far from ideal. At the same time, public health knowledge needs to be disseminated and educated, especially among those at high risk of cerebrovascular disease, with a focus on improving psychosocial factors such as diet quality.

Copper-Catalyzed Enantioselective Difluoromethylation-Alkynylation of Olefins by Solving the Dilemma between Acidities and Reduction Potentials of Difluoromethylating Agents.

Molecules containing a difluoromethyl group or a propargylic stereocenter are widely used in pharmaceuticals and agrochemicals, and 1,2-functionalization of olefins is an important method for introducing the two groups into molecules simultaneously. The construction of the propargylic stereocenter with terminal alkynes usually requires bases. However, difluoromethylating agents with high reduction potentials often decompose in the presence of bases because of their acidities, and those with low reduction potentials are stable but difficult to undergo the desired single electron transfer (SET) reduction. Using the linear relationship between reduction potential differences (ΔE) and Hammett substituent constants (σ) of difluoromethyl aryl sulfones, we solved the dilemma between acidities and reduction potentials of difluoromethylating agents. Herein, we report the first enantioselective difluoromethylation-alkynylation of olefins with difluoromethyl 4-chlorophenyl sulfone with high enantioselectivity (>90 % ee). We also extended this asymmetric fluoroalkylation-alkynylation reaction with other fluoroalkyl sulfones, which enabled efficient installation of trifluoromethyl, difluoroalkyl, difluorobenzyl, (benzenesulfonyl)-difluoromethyl and monofluoromethyl groups into products.

The prevalence and risk factors of anxiety in multiple sclerosis: A systematic review and meta-analysis.

Background: Patients with multiple sclerosis (MS) suffer from repetitive neurological deterioration, while anxiety may play a significant role in the disease's progression. Objective: To explore the prevalence of anxiety in MS and to investigate the risk factors related to anxiety in MS patients. Methods: An analysis of four databases, PubMed, Web of Science, EMBASE, and Cochrane Library, has been conducted to determine the prevalence or risk factors for anxiety in MS published before May 2021. Results: In total, 32 studies were found to be eligible. Anxiety prevalence was estimated to be 36% based on the pooled estimates [the 95% confidence interval (CI) = [0.30-0.42], I 2 = 98.4%]. Significant risk factors for developing of anxiety were as follows: age at survey [the weighted mean difference (WMD) = 0.96, 95% CI = [0.86-1.06], I 2 = 43.8%], female [the odd ratio (OR) = 1.78, 95% CI = [1.38-2.30], I 2 = 0%], living together (OR 2.83, 95% CI = [1.74-4.59], I 2 = 0%), past psychiatric history (OR 2.42, 95% CI = [1.56-3.75], I 2 = 0%), depression (OR 7.89, 95% CI = [3.71-16.81], I 2 = 0%), not taking MS medication (OR 2.33, 95% CI = [1.29-4.21], I 2 = 77.8%), relapsing-remitting MS (RRMS) (OR 1.50, 95% CI = [0.94-2.37], I 2 = 53.5%), and baseline Expanded Disability Status Scale (EDSS) (OR 0.84, 95% CI = [0.48-1.21], I 2 = 62.2%). Conclusion: An estimated 36% of people with MS suffer from anxiety. And anxiety rates in MS patients are significantly associated with age, gender, living together, prior psychiatric history, depression, drug compliance, RRMS, and baseline EDSS. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=287069, identifier CRD42021287069.

Efficient Large-Scale Virtual Screening Based on Heterogeneous Many-Core Supercomputing System.

With the rapid growth of virtual drug data- bases, the need for efficient molecular docking tools for large-scale screening is also growing. We have developed Vina@QNLM 2.0, a novel molecular docking system that leverages the logical processing units and computational processing arrays of heterogeneous multicore architecture processors. Compared to Vina@QNLM, the new version optimizes the docking speed without sacrificing accuracy. This greatly improves the scoring capability for large molecules (molecular weight > 500). Simultaneously, the new system provides enhanced support for applications such as reverse target finding through an improved parallel strategy. Vina@QNLM 2.0 achieves a speedup 20 times higher than that, using logical processing units only during a single docking process. Additionally, we successfully scaled the reverse target finding a task to 122,401 kernel groups with a robust scalability of 80.01%. In practice, we completed a reverse target-seeking for nine glycan molecules with 10,094 proteins within 1 hour.