The oral-gut microbiome axis in inflammatory bowel disease: from inside to insight.

Inflammatory bowel disease (IBD) is an idiopathic and persistent inflammatory illness of the bowels, leading to a substantial burden on both society and patients due to its high incidence and recurrence. The pathogenesis of IBD is multifaceted, partly attributed to the imbalance of immune responses toward the gut microbiota. There is a correlation between the severity of the disease and the imbalance in the oral microbiota, which has been discovered in recent research highlighting the role of oral microbes in the development of IBD. In addition, various oral conditions, such as angular cheilitis and periodontitis, are common extraintestinal manifestations (EIMs) of IBD and are associated with the severity of colonic inflammation. However, it is still unclear exactly how the oral microbiota contributes to the pathogenesis of IBD. This review sheds light on the probable causal involvement of oral microbiota in intestinal inflammation by providing an overview of the evidence, developments, and future directions regarding the relationship between oral microbiota and IBD. Changes in the oral microbiota can serve as markers for IBD, aiding in early diagnosis and predicting disease progression. Promising advances in probiotic-mediated oral microbiome modification and antibiotic-targeted eradication of specific oral pathogens hold potential to prevent IBD recurrence.

Changes in Gut Microbiota in Patients with Multiple Sclerosis Based on 16s rRNA Gene Sequencing Technology: A Review and Meta-Analysis.

BACKGROUND: This meta-analysis explores alterations in the gut microbiota of patients with Multiple Sclerosis (MS) using 16S ribosomal RNA (rRNA) gene sequencing. METHODS: Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, our comprehensive review spanned major databases, including PubMed, Web of Science, Embase, Cochrane, and Ovid, targeting observational studies that implemented 16S rRNA gene sequencing on fecal specimens. The quality of these studies was meticulously evaluated using the Newcastle-Ottawa scale. RESULTS: Our search yielded 26 relevant studies conducted between 2015-2022, encompassing 2885 participants. No significant differences were observed in alpha diversity indices (Shannon, Chao1, Operational Taxonomic Units (OTU), and Simpson) between MS patients and controls in general. Nonetheless, subgroup analyses according to disease activity using the Shannon index highlighted a significant decrease in microbial diversity during MS's active phase. Similarly, an evaluation focusing on MS phenotype revealed diminished diversity in individuals with relapsing-remitting MS (RRMS). Microbial composition analysis revealed no consistent increase in pro-inflammatory Bacteroidetes or decrease in anti-inflammatory Firmicutes within the MS cohort. CONCLUSION: The gut microbiome's role in MS presents a complex panorama, where alterations in microbial composition might hold greater significance to disease mechanisms than diversity changes. The impact of clinical factors such as disease activity and phenotype are moderately significant, underscoring the need for further research to elucidate these relationships. Prospective research should employ longitudinal methodologies to elucidate the chronological interplay among gut microbiota, disease evolution, and therapeutic strategies.

Photo-Fenton Degradation of Tetracycline and Photoelectrochemical Properties of ZnFe2O4@ZnWO4 Heterostructure Composite Coupling.

Problems such as bacterial resistance caused by tetracycline antibiotics pose a serious threat to human production and life and ecosystems. We prepared ZnFe2O4@ZnWO4 heterojunction nanocomposites using hydrothermal and coprecipitation methods. The micromorphology, structure, and photoelectrochemical properties were analyzed. In combination with the presence of H2O2, the photo-Fenton activity of the antibiotic tetracycline at high concentration was tested under visible light irradiation, and its catalytic mechanism was investigated. The results showed that the composition of the composite heterojunction improved the catalytic activity of the catalyst. At a pollutant concentration of 50 mg L-1 and pH 5, 30% ZnWO4/ZnFe2O4 degraded 92.1% of tetracycline in 60 min with a degradation rate of 0.0295 min-1, which was 6.7 times higher than that of pure ZnFe2O4. The results of free radical trapping experiments and electron spin resonance techniques indicated that hydroxyl radical (•OH) and superoxide radical (O2-) played important roles in the photo-Fenton degradation of tetracycline. Notably, the catalyst maintained a high degradation rate (80%) after five cycles. ZnFe2O4 introduced in this article may provide a promising strategy for achieving strong light absorption and is authoritative in meeting future environmental requirements.

Acid-resistant chitosan/graphene oxide adsorbent for Cu2+ removal: The role of mixed cross-linking and amino-functionalized.

Copper ions in wastewater pose a significant threat to human and ecological safety. Therefore, preparing macroscopic adsorbents with reusable and high adsorption performance is paramount. This paper used graphene oxide as the adsorbent and chitosan as the thickener. Additionally, a silane coupling agent was employed to enhance the acid resistance of chitosan, and amino-modification of graphene oxide was performed. Macroscopic adsorbents with high adsorption capacity were fabricated using 3D printing technology. The results show that all five proportions of inks exhibit good printability. Dissolution experiments revealed that all materials maintained structural integrity after 180 days across pH values. Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Photoelectron Spectroscopy (XPS) confirmed the successful preparation of the materials. Adsorption experiments showed that the best performing material ratio was 8 wt% graphene oxide and 7 wt% chitosan. Adsorption kinetics and isothermal adsorption experiments demonstrated that the adsorption process occurred via monolayer chemisorption. The adsorption process was attributed to strong electrostatic forces, van der Waals forces, and nitrogen/oxygen-containing functional group coordination. Cycling experiments showed that the material retained good adsorption performance after 6 cycles, suggesting its potential for practical heavy metal treatment applications.

Photocatalytic removal of ammonia nitrogen from water: investigations and challenges for enhanced activity.

Ammonia nitrogen (NH3-N/NH4+-N) serves as a crucial chemical in biochemistry and fertilizer synthesis. However, it is also a toxic compound, posing risks from eutrophication to direct threats to human health. Ammonia nitrogen pollution pervades water sources, presenting a significant challenge. While several water treatment technologies exist, biological treatment, though widely used, has its limitations. Hence, green and efficient photocatalytic technology emerges as a promising solution. However, current monolithic semiconductor photocatalysts prove inadequate in controlling ammonia nitrogen pollution. Therefore, this review focuses on enhancing semiconductor photocatalysts' efficiency through modification, discussing four mechanisms: (1) mono-ionic modification; (2) metallic and non-metallic modification; (3) construct heterojunctions; and (4) enhancement of synergistic effects of multiple technologies. The influencing factors of photocatalytic ammonia nitrogen removal efficiency are also explored. Moreover, the review outlines the limitations of current photocatalytic pollution treatment and discusses future development trends and research challenges. Currently, the main products of ammonia nitrogen removal include NO3-, NO2-, and N2. To mitigate secondary pollution, the green process of converting ammonia nitrogen to N2 using photocatalysis emerges as a fundamental approach for future treatment. Overall, this review aims to deepen understanding of photocatalysis in ammonia nitrogen treatment and guide researchers toward widespread implementation of this endeavor.

Analysis of the 1-year efficacy of four different surgical methods for treating Chinese super obese (BMI ≥ 50 kg/m2) patients.

This study aimed to retrospectively analyze the perioperative and postoperative follow-up data of patients with super obesity who had undergone RYGB, SG, BPD/DS, and SADI-S. A retrospective observational study was conducted to analyze the perioperative and postoperative follow-up data of 60 patients with super obesity who had undergone bariatric surgery. A total of 34 men and 26 women were included in this study. The participants had an average preoperative BMI of 53.81 ± 3.25 kg/m2. The body weight and BMI of all four patient groups decreased significantly at 3, 6, and 12 months postoperatively compared with the preoperative values. Additionally, the TWL (%) and EWL (%) of all four groups increased gradually over the same period. Compared with the preoperative values, the systolic and diastolic blood pressure, glycosylated hemoglobin, uric acid, triglycerides, and total cholesterol decreased to varying degrees in the four groups 1 year postoperatively. RYGB, SG, BPD/DS, and SADI-S are all safe and effective in treating super obese patients and improving their metabolic diseases to a certain extent.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.