Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*

OBJECTIVE: Poxviruses are zoonotic pathogens that infect humans, mammals, vertebrates, and arthropods. However, the specific role of ticks in transmission and evolution of these viruses remains unclear. METHODS: Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses. Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences. RESULTS: Fifty-eight poxvirus species, representing two subfamilies and 20 genera, were identified, with 212 poxviral sequences assembled. A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes. These genomic sequences contained fragments originating from rodents, archaea, and arthropods. CONCLUSION Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses. These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer, gene recombination, and gene mutations, thereby promoting co-existence and co-evolution with their hosts. This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.
Animals ; Poxviridae/physiology* ; Ticks/virology* ; Phylogeny ; Transcriptome ; Evolution, Molecular ; Poxviridae Infections/virology* ; Genome, Viral

Regulated cell death (RCD) is a critical physiological process essential in maintaining skin homeostasis. Among the various forms of RCD, ferroptosis stands out due to its distinct features of iron accumulation, lipid peroxidation, and involvement of various inhibitory antioxidant systems. In recent years, an expanding body of research has solidly linked ferroptosis to the emergence of skin disorders. Therefore, understanding the mechanisms underlying ferroptosis in skin diseases is crucial for advancing therapy and prevention strategies. This review commences with a succinct elucidation of the mechanisms that underpin ferroptosis, embarks on a thorough exploration of ferroptosis’s role across a spectrum of skin conditions, encompassing melanoma, psoriasis, systemic lupus erythematosus (SLE), vitiligo, and dermatological ailments precipitated by ultraviolet (UV) exposure, and scrutinizes the potential therapeutic benefits of pharmacological interventions aimed at modulating ferroptosis for the amelioration of skin diseases.

Background::Although some well-established oncogenes are involved in cancer initiation and progression such as prostate cancer (PCa), the long tail of cancer genes remains to be defined. Goosecoid ( GSC) has been implicated in cancer development. However, the comprehensive biological role of GSC in pan-cancer, specifically in PCa, remains unexplored. The aim of this study was to investigate the role of GSC in PCa development. Methods::We performed a systematic bioinformatics exploration of GSC using datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, Gene Expression Omnibus, German Cancer Research Center, and our in-house cohorts. First, we evaluated the expression of GSC and its association with patient prognosis, and identified GSC-relevant genetic alterations in cancers. Further, we focused on the clinical characterization and prognostic analysis of GSC in PCa. To understand the transcriptional regulation of GSC by E2F transcription factor 1 ( E2F1), we performed chromatin immunoprecipitation quantitative polymerase chain reaction (qPCR). Functional experiments were conducted to validate the effect of GSC on the tumor cellular phenotype and sensitivity to trametinib. Results::GSC expression was elevated in various tumors and significantly correlated with patient prognosis. The alterations of GSC contribute to the progression of various tumors especially in PCa. Patients with PCa and high GSC expression exhibited worse progression-free survival and biochemical recurrence outcomes. Further, GSC upregulation in patients with PCa was mostly accompanied with higher Gleason score, advanced tumor stage, lymph node metastasis, and elevated prostate-specific antigen (PSA) levels. Mechanistically, the transcription factor, E2F1, stimulates GSC by binding to its promoter region. Detailed experiments further demonstrated that GSC acted as an oncogene and influenced the response of PCa cells to trametinib treatment. Conclusions::GSC was highly overexpressed and strongly correlated with patient prognosis in PCa. We found that GSC, regulated by E2F1, acted as an oncogene and impeded the therapeutic efficacy of trametinib in PCa.

Objective To observe and compare the changes of vertebral bone mineral density(BMD)in the early stages of spinal Mycobacterium tuberculosis infection.Methods Patients who underwent spinal surgery at Xiangya Hospital,Central South University from January 1 to December 31,2023 were continuously enrolled(spinal tuber-culosis group),based on gender matching,non-spinal tuberculosis surgical patients treated for spinal stenosis were selected as the control group.Dual-energy X-ray scans were performed on the enrolled patients,difference in verte-bral BMD between two groups of patients was compared.An animal model of spinal Mycobacterium tuberculosis in-fection(referred to as the animal model)was constructed,differences in microstructure of trabecular bone between spinal tuberculosis group and control group was compared,and the bone volume/tissue volume(BV/TV),the thickness of trabecular bone(Tb.Th),the number of trabecular bone(Tb.N),and sparse density of trabecular(Tb.Sp)were used as evaluation indexes to further analyze the bone quality differences between the diseased verte-brae and the neighboring vertebrae.Results 69 patients were included in the spinal tuberculosis group and the con-trol group,respectively.The BMD of patients in the spinal tuberculosis group(0.793[0.712,0.869]g/cm2)was lower than that of the control group(0.907[0.800,1.020]g/cm2),difference was statistically significant(P＜0.05).Microstructure of trabecular bone BV/TV([18.4±5.4]％),Tb.Th([0.124±0.010]mm)in the spinal tuberculosis group of animal model were significantly altered compared with BV/TV([22.6±3.2]％),Tb.Th([0.160±0.017]mm)in the control group(both P＜0.05).In the spinal tuberculosis group,microstructure of diseased vetebral trabecular bone BV/TV([25.5±6.7]％)and Tb.N([1.871±0.443]/mm)were significantly lower than BV/TV([26.6±6.8]％)and Tb.N([1.969±0.454]/mm)in the neighboring vertebrae,both with statistically difference(both P＜0.05).Conclusion In the early stages of spinal Mycobacterium tuberculosis infec-tion,microstructure of vertebral trabecular bone can be altered,leading to a decrease in BMD.

【Objective】 To investigate the effect of double plasma molecular adsorption system and sequential half-dose plasma exchange (DPMAS+HPE) on the short-term survival rate of patients with hepatitis B associated acute-on-chronic liver failure (HBV-ACLF). 【Methods】 Data on HBV-ACLF cases hospitalized in our hospital from January 1, 2015 to December 31, 2022 were retrospectively collected, and were divided into standard comprehensive medical treatment group and DPMAS+HPE group according to different treatment methods. Propensity score matching (PSM) was used to eliminate inter group confounding bias. The baseline data and improvement of laboratory indicators after treatment between two groups were compared. Death related risk factors in HBV-ACLF patients were screened by logistic regression analysis, and cumulative survival rates at 30 and 90 days between the two groups were compared by Kaplan-Meier survival analysis. 【Results】 A total of 373 cases of HBV-ACLF were included in this study. Among them, 136 cases in the treatment group received DPMAS+HPE once on the basis of comprehensive internal medicine treatment, and 237 cases only received comprehensive internal medicine treatment. After PSM, 136 patients were included as the control group. The decrease in alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total protein (TP) in the treatment group before and after treatment was significantly greater than that in the control group (446.5 vs 159.0, 317.0 vs 92.0,5.2 vs 0.3), with statistically significant difference (P<0.05). DPMAS+HPE treatment is an independent protective factor for mortality in HBV-ACLF patients at 30 and 90 days (30 days: OR=0.497, P<0.05; 90 days: OR= 0.436, P<0.05). The cumulative survival rates at 30 and 90 days in the treatment group were significantly higher than those in the control group (30 days: 50.71% vs 44.12%, P<0.05; 90 days: 30.15% vs 22.79%, P<0.05). 【Conclusion】 DPMAS+HPE improves the short-term prognosis of HBV-ACLF patients and can serve as an effective artificial liver model for the treatment of HBV-ACLF patients.

[Abstract] [Objective] To explore the risk factors of blood transfusion in patients with isolated traumatic brain injury (iTBI) based on multiple machine learning methods, so as to establish a predictive model to provide reasonable guidance for blood transfusion in patients with iTBI. [Methods] A total of 2 273 patients with iTBI from the First Affiliated Hospital of Nanchang University from January 1, 2015 to June 30, 2021 were included to compare and analyze the differences in variables such as vital signs, clinical indicators and laboratory testing indicators between transfusion and non transfusion patients. Furthermore, six machine learning models were established to compare the performance of different models through cross validation, accuracy, specificity, recall, f1 value and area under the ROC curve. The SHAP plot was used to explain the influencing factors of blood transfusion in iTBI patients. [Results] This study included 2 273 iTBI patients, with a total of 301 patients receiving blood transfusions. There were significant differences (P<0.05) in gender, age, HR, clinical diagnosis, skull fracture, treatment methods, hemorrhagic shock, GCS, K, Ca, PT, APTT, INR, RBC, Hct, Hb and Plt between transfusion and non transfusion patients; Moreover, the LOS, incidence of complications, mechanical ventilation rate, ICU admission rate, readmission rate within 90 days and in-hospital mortality rate of transfusion patients were all higher than those of the non transfusion group (P<0.05). Six machine learning algorithms were used for model construction, and the validation results on the test set showed that the CatBoost model performed the best with an AUC of 0.911. Furthermore, the SHAP framework was used to explain and visualize the optimal model CatBoost, showing that surgical treatment, lower GCS, higher INR, lower Hct, lower K, lower Ca, age ≥60 years, skull fractures and hemorrhagic shock increase the risk of blood transfusion in patients. [Conclusion] This study established a machine learning model for predicting blood transfusion in iTBI patients, and the CatBoost model performed the best. This model may be useful and beneficial for identifying transfusion risks in this population, making clinical transfusion decisions and monitoring progress.

AIM To compare the components difference between Lonicera fragrantissima Lindl.et Paxt.(LFL)and Lonicerae japonicae Flos(LJF),and to evaluate the medicinal value of LFL,so as to provide reference for the development and utilization of LFL and LJF.METHODS With 70%methanol as extraction solvent,the components were analyzed by UPLC-TOF-MS,and the contents of 20 components were determined by HPLC-QQQ-MS.The components difference was determined by multivariate statistical analysis.RESULTS A total of 52 components were identified in the buds of LFL and LJF.There were 4 different components in LJF,and the contents of 20 quantitative components were significantly different.The contents of isochlorogenic acid C,ferulic acid,luteolin and rutin in the buds of LFL were more than 2 times that of LJF,and the contents of marchanic acid and marchanin were 11.96 times and 37.23 times that of LJF respectively.Maganin,isochlorogenic acid A,maganic acid,rutin and dicomachanic acid are the key differentiating components of LFL and LJF.CONCLUSION The buds of LFL and LJF have similar species,but the content difference is obvious.The buds of LFL have important medicinal value,which need further development and utilization.

Intracellular neurofibrillary tangles resulting from abnormal hyperphosphorylation of Tau protein constitute one of the principal pathological markers of Alzheimer′s disease. Existing studies have indicated that BSc3094 is an efficacious inhibitor of Tau protein aggregation, capable of binding to Tau protein, inhibiting Tau protein phosphorylation, and enhancing cell viability concurrently, holding significant potential in treating Alzheimer′s disease. Nevertheless, due to the presence of the blood-brain barrier, it is challenging for drugs to penetrate the brain and exert their effects, and whether BSc3094 can treat Alzheimer′s disease by inhibiting Tau protein aggregation has not been profoundly investigated. Hence, in this study, small-sized (PLGA) nanoparticles were fabricated through the stirring method. BSc3094 was loaded into the nanoparticles (PLGA@BSc). To further enhance the brain entry efficiency of PLGA nanoparticles, a pathological BBB-targeting peptide was modified on the surface to obtain PLGA@BSc@K. In this study, the stability, cytotoxicity, and pathological targeting of the nanosystem were characterized. The particle size of the nanosystem was about 90 nm, which was negatively charged. The results demonstrated that the particle size of the nanoparticles did not fluctuate conspicuously within 168 h, and the stability was favorable. PLGA and BSc3094 had no notable impact on cell viability and displayed low cytotoxicity. At 1 and 4 h, it was observed that the uptake of targeted modified nanoparticles by cells in pathological states augmented, suggesting that PLGA@BSc@K had an excellent pathological blood-brain barrier targeting effect. This study provides a novel concept for the targeting of BSc3094 nanoparticles in the brain and the treatment of Alzheimer′s disease.