Application of Deep Learning for Studying NMDA Receptors.

Artificial intelligence underwent remarkable advancement in the past decade, revolutionizing our way of thinking and unlocking unprecedented opportunities across various fields, including drug development. The emergence of large pretrained models, such as ChatGPT, has even begun to demonstrate human-level performance in certain tasks.However, the difficulties of deploying and utilizing AI and pretrained model for nonexpert limited its practical use. To overcome this challenge, here we presented three highly accessible online tools based on a large pretrained model for chemistry, the Uni-Mol, for drug development against CNS diseases, including those targeting NMDA receptor: the blood-brain barrier (BBB) permeability prediction, the quantitative structure-activity relationship (QSAR) analysis system, and a versatile interface of the AI-based molecule generation model named VD-gen. We believe that these resources will effectively bridge the gap between cutting-edge AI technology and NMDAR experts, facilitating rapid and rational drug development.

CD4+CD25+ regulatory T cells decreased future liver remnant after associating liver partition and portal vein ligation for staged hepatectomy.

BACKGROUND: Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) is an innovative surgical approach for the treatment of massive hepatocellular carcinoma (HCC), the key to successful planned stage 2 ALPPS is future liver remnant (FLR) volume growth, but the exact mechanism has not been elucidated. The correlation between regulatory T cells (Tregs) and postoperative FLR regeneration has not been reported. AIM: To investigate the effect of CD4+CD25+ Tregs on FLR regeneration after ALPPS. METHODS: Clinical data and specimens were collected from 37 patients who developed massive HCC treated with ALPPS. Flow cytometry was performed to detect changes in the proportion of CD4+CD25+ Tregs to CD4+ T cells in peripheral blood before and after ALPPS. To analyze the relationship between peripheral blood CD4+CD25+ Treg proportion and clinicopathological information and liver volume. RESULTS: The postoperative CD4+CD25+ Treg proportion in stage 1 ALPPS was negatively correlated with the amount of proliferation volume, proliferation rate, and kinetic growth rate (KGR) of the FLR after stage 1 ALPPS. Patients with low Treg proportion had significantly higher KGR than those with high Treg proportion (P = 0.006); patients with high Treg proportion had more severe postoperative pathological liver fibrosis than those with low Treg proportion (P = 0.043). The area under the receiver operating characteristic curve between the percentage of Tregs and proliferation volume, proliferation rate, and KGR were all greater than 0.70. CONCLUSION: CD4+CD25+ Tregs in the peripheral blood of patients with massive HCC at stage 1 ALPPS were negatively correlated with indicators of FLR regeneration after stage 1 ALPPS and may influence the degree of fibrosis in patients' livers. Treg percentage was highly accurate in predicting the FLR regeneration after stage 1 ALPPS.

Pulmonary nocardiosis with bloodstream infection diagnosed by metagenomic next-generation sequencing in a kidney transplant recipient: A case report.

BACKGROUND: Pulmonary nocardiosis is difficult to diagnose by culture and other conventional testing, and is often associated with lethal disseminated infections. This difficulty poses a great challenge to the timeliness and accuracy of clinical detection, especially in susceptible immunosuppressed individuals. Metagenomic next-generation sequencing (mNGS) has transformed the conventional diagnosis pattern by providing a rapid and precise method to assess all microorganisms in a sample. CASE SUMMARY: A 45-year-old male was hospitalized for cough, chest tightness and fatigue for 3 consecutive days. He had received a kidney transplant 42 d prior to admission. No pathogens were detected at admission. Chest computed tomography showed nodules, streak shadows and fiber lesions in both lung lobes as well as right pleural effusion. Pulmonary tuberculosis with pleural effusion was highly suspected based on the symptoms, imaging and residence in a high tuberculosis-burden area. However, anti-tuberculosis treatment was ineffective, showing no improvement in computed tomography imaging. Pleural effusion and blood samples were subsequently sent for mNGS. The results indicated Nocardia farcinica as the major pathogen. After switching to sulphamethoxazole combined with minocycline for anti-nocardiosis treatment, the patient gradually improved and was finally discharged. CONCLUSION: A case of pulmonary nocardiosis with an accompanying bloodstream infection was diagnosed and promptly treated before the dissemination of the infection. This report emphasizes the value of mNGS in the diagnosis of nocardiosis. mNGS may be an effective method for facilitating early diagnosis and prompt treatment in infectious diseases, which overcomes the shortcomings of conventional testing.

A retrospective cohort study of geographic differences in the semen of 1,012 sperm donors in China.

Background: Male reproductive health has become a serious public health concern, and semen quality is essential to male reproduction. We aimed to investigate geographical differences in the semen quality of sperm donors from northern and southern China by enrolling donors across the country. Methods: A total of 1,012 sperm donors were enrolled in this study between 2015 and 2019. Donors were first divided into two parts based on their birthplace according to the "Qinling-Huaihe" line, and secondly, by their residential latitude. Finally, donors were re-classified into two groups (typically north and south) which contained 667 samples. Results: Statistically significant differences in sperm concentration were observed among men from different latitudes in China (P=0.04). The sperm concentrations of males from 18° to 27° north latitude were significantly lower than those from 36° to 45° and 45° to 54° [median 131, 134, and 146, respectively, P=0.021 (18° to 27° vs. 36° to 45°) and P=0.01 (18° to 27° vs. 45° to 54°)]. Conclusion: We hypothesize environmental pollution and mental stress due to the increased population size may be the main factors underlying differences in the sperm quality of men in northern and southern China.

Targeted next-generation sequencing for pulmonary infection diagnosis in patients unsuitable for bronchoalveolar lavage.

Background: Targeted next-generation sequencing (tNGS) has emerged as a rapid diagnostic technology for identifying a wide spectrum of pathogens responsible for pulmonary infections. Methods: Sputum samples were collected from patients unable or unwilling to undergo bronchoalveolar lavage. These samples underwent tNGS analysis to diagnose pulmonary infections. Retrospective analysis was performed on clinical data, and the clinical efficacy of tNGS was compared to conventional microbiological tests (CMTs). Results: This study included 209 pediatric and adult patients with confirmed pulmonary infections. tNGS detected 45 potential pathogens, whereas CMTs identified 23 pathogens. The overall microbial detection rate significantly differed between tNGS and CMTs (96.7% vs. 36.8%, p < 0.001). Among the 76 patients with concordant positive results from tNGS and CMTs, 86.8% (66/76) exhibited full or partial agreement. For highly pathogenic and rare/noncolonized microorganisms, tNGS, combined with comprehensive clinical review, directly guided pathogenic diagnosis and antibiotic treatment in 21 patients. This included infections caused by Mycobacterium tuberculosis complex, certain atypical pathogens, Aspergillus, and nontuberculous Mycobacteria. Among the enrolled population, 38.8% (81/209) of patients adjusted their treatment based on tNGS results. Furthermore, tNGS findings unveiled age-specific heterogeneity in pathogen distribution between children and adults. Conclusion: CMTs often fall short in meeting the diagnostic needs of pulmonary infections. This study highlights how tNGS of sputum samples from patients who cannot or will not undergo bronchoalveolar lavage yield valuable insights into potential pathogens, thereby enhancing the diagnosis of pulmonary infections in specific cases.

Metagenomic next-generation sequencing contributes to the diagnosis of mixed pulmonary infection: a case report.

BACKGROUND: Pulmonary cryptococcosis (PC) and mixed pulmonary infection are difficult to be diagnosed due to the non-specificity and their overlapping clinical manifestations. In terms of the clinical diagnosis of PC and mixed pulmonary infection, conventional tests have limitations such as a long detection period, a limited range of pathogens, and low sensitivity. Metagenomics next-generation sequencing (mNGS) is a nascent and powerful method that can detect pathogens without culture, to diagnose known and unexplained infections in reduced time. CASE PRESENTATION: A 43-year-old female was admitted to the hospital after suffering from a cough for one month. At the time of admission, a contrast-enhanced chest CT revealed multiple nodules and plaques in her right lung, as well as the formation of cavities. The blood routine assays showed evidently increased white blood cell count (mainly neutrophils), CRP, and ESR, which suggested she was in the infection phase. The serum CrAg-LFA test showed a positive result. Initially, she was diagnosed with an unexplained pulmonary infection. Bronchoalveolar lavage fluid (BALF) samples were collected for microbial culture, immunological tests and the mNGS. Microbial culture and immunological tests were all negative, while mNGS detected Corynebacterium striatum, Pseudomonas aeruginosa, Streptococcus pneumoniae, and Cryptococcus neoformans. The diagnosis was revised to PC and bacterial pneumonia. Lung infection lesions were healed after she received targeted anti-infection therapy with mezlocillin and fluconazole. In a follow-up after 2 months, the patient's symptoms vanished. CONCLUSIONS: Here, we demonstrated that mNGS was capable of accurately distinguishing Cryptococcus from M. tuberculosis in pulmonary infection, and notably mNGS was capable of swiftly and precisely detecting pathogens in mixed bacterial and fungal pulmonary infection. Furthermore, the results of mNGS also have the potential to adjust anti-infective therapies.

Construction of a 3-mRNA hypoxia prognostic model to evaluate immune microenvironment in hepatocellular carcinoma.

BACKGROUND: Hypoxia is a key factor in the development of hepatocellular carcinoma (HCC), which is the most common primary liver cancer with poor prognosis. The current study aimed to identify the potential prognostic biomarkers of the hypoxia-associated gene signature in patients with HCC, and to further explore the relationship between hypoxia and immune infiltration. METHODS: After the determination of differentially expressed genes (DEGs) using the HCC transcriptome data of The Cancer Genome Atlas database and hypoxia-related gene set, the prognosis-associated genes were identified using univariate Cox regression analysis. Then, the hypoxia prognosis model was established via multivariate Cox regression analysis, with functional annotation conducted using Gene Set Enrichment Analysis. CIBERSORT was utilized to analyze the degree of tumor immune invasion, and an International Cancer Genome Consortium cohort to verify the reliability of the prognosis model. Expression levels of hypoxia-associated genes were detected by real-time quantitative polymerase chain reaction in HCC samples. RESULTS: 3 genes (ENO1, SAP30, and STC2) constructed the hypoxia prognosis model. The patients were subdivided into 2 groups based on median risk score, with a high hypoxic score indicating poor prognosis of HCC. The hypoxia signature could be employed as an independent prognostic factor in HCC. In addition, the proportion of macrophages was higher in the high-risk group. CONCLUSION: The hypoxia-associated signature could be a potential prognostic marker of HCC and provides a different perspective for immunotherapy of HCC.

Change of tumor-infiltrating lymphocyte of associating liver partition and portal vein ligation for staged hepatectomy for hepatocellular carcinoma.

BACKGROUND: The role of tumor-infiltrating lymphocytes (TILs) in the growth and progression of hepatocellular carcinoma (HCC) has attracted widespread attention. AIM: To evaluate the feasibility of associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) for massive HCC by exploring the role of TIL in the tumor microenvironment. METHODS: Fifteen massive HCC patients who underwent ALPPS treatment and 46 who underwent hemi-hepatectomy were selected for this study. Propensity score matching was utilized to match patients in ALPPS and hemi-hepatectomy groups (1:1). Quantitative analysis of TILs in tumor and adjacent tissues between the two groups was performed by immunofluorescence staining and further analyses with oncological characteristics. In the meantime, trends of TILs in peripheral blood were compared between the two groups during the perioperative period. RESULTS: Continuous measurement of tumor volume and necrosis volume showed that the proportion of tumor necrosis volume on the seventh day after stage-I ALPPS was significantly higher than the pre-operative value (P = 0.024). In the preoperative period of stage-I ALPPS, the proportion of tumor necrosis volume in the high CD8+ T cell infiltration group was significantly higher than that in the low group (P = 0.048). CONCLUSION: TIL infiltration level maintained a dynamic balance during the preoperative period of ALPPS. Compared with right hemi-hepatectomy, the ALPPS procedure does not cause severe immunosuppression with the decrease in TIL infiltration and pathological changes in immune components of peripheral blood. Our results suggested that ALPPS is safe and feasible for treating massive HCC from the perspective of immunology. In addition, high CD8+ T cell infiltration is associated with increasing tumor necrosis in the perioperative period of ALPPS.

Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design.

Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.

Bioinformatics analysis and experimental verification of five metabolism-related lncRNAs as prognostic models for hepatocellular carcinoma.

BACKGROUND: The number of patients with hepatocellular carcinoma (HCC) is showing a growing trend all over the world. The metabolic microenvironment has been shown to play a key role in the pathogenesis of HCC in recent studies. The expression of metabolites and metabolic processes in tumor cells can be regulated by gene regulation mediated by long non-coding RNAs (lncRNAs), the abnormal expression of which is closely related to tumor occurrence and metastasis. However, the fundamental mechanism of applying metabolism-related lncRNAs to predicting HCC is still unclear. METHODS: With the complete RNA sequence data and clinical data obtained from The Cancer Genome Atlas database and metabolism-related genes downloaded from the Kyoto Encyclopedia of Genes and Genomes database, with false discovery rate < 0.001, log fold change > 1.5 selected as the screening criteria for lncRNA, the relationship between the expression level of metabolism-related LncRNAs (MRLs) and the overall survival rate was determined by the Univariate Cox regression analyses with the establishment of the metabolic prognosis model by the application of Multivariate Cox regression analyses, revealing the different biological processes and signaling pathways in both high-risk groups and low-risk groups by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and gene set enrichment analysis, leading the expression of lncRNA to be assessed by the reverse transcription-polymerase chain reaction results. RESULTS: The overall survival rate of HCC patients is significantly correlated with signature of 5-MRLs. The prognosis characteristics of lncRNA reveal the relatively high death rate of patients in the high-risk groups, with the predicted signals by functional and pathway enrichment analysis related to biosynthesis, metabolic process, and metabolic pathway, with the prognostic characteristics of 5-MRLs by the combined analysis showing that it is an independent factor of HCC superior to the traditional clinical indicators in predicting the prognosis. A trend of high-expression was shown in MRLs in tumors by reverse transcription-polymerase chain reaction. CONCLUSION: The new 5-MRLs as potential biomarkers provide more powerful prognostic information for HCC patients. In the future clinical treatment of HCC, it will provide doctors with more methods.

Efficacy of the association liver partition and portal vein ligation for staged hepatectomy for the treatment of solitary huge hepatocellular carcinoma: a retrospective single-center study.

BACKGROUND: The feasibility of association liver partition and portal vein ligation for staged hepatectomy (ALPPS) for solitary huge hepatocellular carcinoma (HCC, maximal diameter ≥ 10 cm) remains uncertain. This study aims to evaluate the safety and the efficacy of ALPPS for patients with solitary huge HCC. METHODS: Twenty patients with solitary huge HCC who received ALPPS during January 2017 and December 2019 were retrospectively analyzed. The oncological characteristics of contemporaneous patients who underwent one-stage resection and transcatheter arterial chemoembolization (TACE) were compared using propensity score matching (PSM). RESULTS: All patients underwent complete two-staged ALPPS. The median future liver remnant from the ALPPS-I stage to the ALPPS-II stage increased by 64.5% (range = 22.3-221.9%) with a median interval of 18 days (range = 10-54 days). The 90-day mortality rate after the ALPPS-II stage was 5%. The 1- and 3-year overall survival (OS) rates were 70.0% and 57.4%, respectively, whereas the 1- and 3-year progression-free survival (PFS) rates were 60.0% and 43.0%, respectively. In the one-to-one PSM analysis, the long-term survival of patients who received ALPPS was significantly better than those who received TACE (OS, P = 0.007; PFS, P = 0.011) but comparable with those who underwent one-stage resection (OS, P = 0.463; PFS, P = 0.786). CONCLUSION: The surgical outcomes of ALPPS were superior to those of TACE and similar to those of one-stage resection. ALPPS is a safe and effective treatment strategy for patients with unresectable solitary huge HCC.

Identification of Prognostic Immune-Related Genes in Pancreatic Adenocarcinoma and Establishment of a Prognostic Nomogram: A Bioinformatic Study.

BACKGROUND: The prognosis of pancreatic adenocarcinoma (PAAD) is extremely poor and has not been improved. Thus, an effective method to assess the prognosis of patients must be established to improve their survival rate. METHOD: This study investigated immune-related genes that could be used as potential therapeutic targets for PAAD. Level 3 gene expression data from the PAAD cohort and the relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. For validation, other PAAD datasets (DSE62452) were downloaded from the Gene Expression Omnibus (GEO) database. The PAAD datasets from TCGA and GEO were used to screen immune-related genes through the Molecular Signatures Database using gene set enrichment analysis. Then, the overlapping immune-related genes of the two datasets were identified. Coexpression networks of the immune-related genes were constructed. RESULTS: A signature of three immune-related genes (CKLF, ERAP2, and EREG) was identified in patients with PAAD. The signature could be used to divide the patients with PAAD into high- and low-risk groups based on their median risk score. Multivariate Cox regression analysis was performed to determine the independent prognostic factors of PAAD. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to assess the prediction accuracy of the prognostic signature. Last, a nomogram was established to assess the individualized prognosis prediction model based on the clinical characteristics and risk score of the TCGA PAAD dataset. The accuracy of the prognostic signature was further evaluated through functional evaluation and principal component analysis. CONCLUSIONS: The results indicated that the signature of three immune-related genes had excellent predictive value for PAAD. These findings might help improve personalized treatment and medical decisions.

Mining TCGA Database for Tumor Microenvironment-Related Genes of Prognostic Value in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The "Estimation of STromal and Immune cells in MAlignant Tumors using Expression data" algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain FABP3, GALNT5, GPR84, ITGB6, MYEOV, PLEKHS1, and STRA6 and may be candidate biomarkers for HCC prognosis.