ObjectiveTo investigate the mechanism by which Notoginsenoside R1 （NGR1） ameliorates hypoxia/reoxygenation （H/R）-induced injury in AC16 human cardiomyocyte cell lines through the regulation of mitophagy. MethodsCommon genes linked to hypoxia/reoxygenation injury and mitophagy were identified by intersecting data from GeneCards and MitoCarta databases. AC16 cell viability was assessed via CCK-8 assay under varying NGR1 concentrations （0， 6.25， 12.5， 25， 50， 100， 200， 300， 400， 500 μmol/L）. AC16 cells were divided into the following groups： control group （Control）， model group （H/R）， and treatment groups （H/R + NGR1 at 100， 200 and 300 μmol/L）. Mitochondrial membrane potential （ΔΨm） was measured using 5，5'，6，6'-tetrachloro-1，1'，3，3'-tetraethylbenzimidazolylcarbocyanine iodide （JC-1） staining. Transcriptional levels of mitophagy-related genes （Parkin， Pink1， P62） were quantified by reverse transcription-quantitative PCR （RT-qPCR）. Protein expression of mitophagy-related markers （Parkin， Pink1， P62， and LC3BⅡ） was evaluated via Western blot analysis. Mitochondrial ultrastructure was visualized by transmission electron microscopy （TEM）. ResultsCompared to the control group， cell viability in the H/R group significantly decreased （P<0.01）. Treatment with NGR1 at concentrations above 100 μmol/L significantly enhanced the cell viability of AC16 cells compared to the H/R group （P<0.01）. H/R induced a significant decrease in mitochondrial membrane potential （P<0.01）， which was restored by NGR1 treatment （P<0.01）. The mRNA levels of Parkin， Pink1， and P62 in the H/R group were upregulated compared to the control group （P<0.05）， while NGR1 intervention downregulated their expression （P<0.05）. Protein expression levels of Parkin， Pink1， and LC3BⅡ in the H/R group significantly increased， while P62 expression decreased compared to the control group （P<0.01）. In contrast， different doses of NGR1 treatment significantly reduced the expression of Parkin， Pink1， and LC3BⅡ while increasing P62 expression （P<0.05）. TEM revealed that the mitochondrial structure in the H/R group was severely disrupted， with fragmented and disorganized cristae， which was alleviated by NGR1. ConclusionNGR1 ameliorates H/R-induced AC16 cell injury， and its mechanism may be associated with modulating the Pink1/Parkin pathway to suppress excessive mitophagy.

Objective To elucidate the changes in the gut microbiota and molecular mechanism of huaier in enhancing the efficacy of oxaliplatin (OXA) chemotherapy in gastric cancer (GC). Methods The effects of huaier on the gut microbiota structure and intestinal barrier function in MKN45-bearing mice were analyzed by using 16S rRNA sequencing, RT-qPCR, and IHC. UPLC-MS and network pharmacology, as well as in vivo experimental approaches, were employed to investigate the key bioactive constituents of huaier systematically and elucidate the underlying mechanisms by which huaier exerts therapeutic effects against GC. The expression of the PI3K/AKT/SREBP pathway was detected in cancer cells and tissues via Western blot analysis. The safety profile of huaier combined with OXA was verified through serum biochemistry and HE-stained tissue section analyses. Results Huaier inhibited the PI3K/AKT/SREBP pathway by increasing the abundance of Akkermansia muciniphila, reduced lipid droplet deposition, and ultimately enhanced the sensitivity to OXA in the treatment of GC. Conclusion This study demonstrates the value of huaier in gastric cancer treatment by enhancing chemosensitivity and provides novel insights into its systemic therapeutic effects through molecular mechanisms and gut microbiota modulation.

Objective To construct an intelligent segmentation and T-stage diagnostic model for esophageal cancer based on the DAEUnet and ConvNeXt networks using transfer learning.Methods Dicom raw data from 126 patients diagnosed with esophageal cancer between January 2018 and April 2022 were collected,including 100 cases from Department of Thoracic Surgery at the First Affiliated Hospital of Army Medical University and 26 cases from the Department of Thoracic Surgery at Shanxi Cancer Hospital.After data augmentation,a total of 60 275 images were obtained.The DAEUnet esophageal cancer intelligent segmentation network was built,and on this basis,3 classification networks,ConvNeXt,Swin Transformer,and ResNet were constructed for T-stage diagnosis of esophageal cancer.Results The Dice similarity coefficient(DSC)for esophageal cancer intelligent segmentation using the DAEUnet network was 0.82,and the DSC value of the esophagus,aorta,normal esophagus,mediastinal lymph nodes,and heart was 72.4％,87.5％,79.3％,60.5％ and 96.8％,respectively.Among the 3 T-stage diagnosis models for esophageal cancer,the ConvNeXt model performed the best,with a precision value for T1～T4 stages of 0.65,0.727,0.889 and 0.92,respectively,and an AUC value of 0.892,which were superior to the ResNet and Swin Transformer networks.Conclusion The proposed DAEUnet and ConvNeXt-based intelligent segmentation and T-stage diagnosis model for esophageal cancer improves T-stage accuracy and treatment efficiency.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

Objective To analyze the influencing factors of delirium after endovascular aortic repair, and to provide a basis for clinical nursing and prevention of this condition. Methods Patients who underwent endovascular aortic repair at Fuwai Hospital, Chinese Academy of Medical Sciences from 2018 to 2019 were selected. The Chinese version of the Nursing Delirium Screening Scale (Nu-DESC) was used to assess whether postoperative delirium occurred. Patients with a Nu-DESC score≥ 3 were assigned to the delirium group. Non-delirium patients who had the same surgeon and adjacent surgical order were selected at a 1 : 4 ratio to form the non-delirium group. Univariate analysis was performed on the clinical data of the two groups. Factors with P<0.1 in the univariate analysis and those considered clinically significant were included in a multivariate logistic regression analysis to identify the influencing factors of postoperative delirium. Stratified analysis was conducted based on thoracic endovascular aortic repair (TEVAR) and endovascular abdominal aortic repair (EVAR). Results A total of 213 patients were included, comprising 46 in the delirium group and 167 in the non-delirium group. The overall mean age was (60.3±12.0) years, and 183 (85.9%) were male. Univariate analysis showed that emergency admission, preoperative neutrophil percentage, aortic dissection, surgical duration, intubation time, and ICU stay may be associated with postoperative delirium. Multivariate analysis revealed that longer operative and intubation times were associated with a higher likelihood of delirium. In the stratified analysis, the results for the TEVAR group were consistent with the overall findings, whereas no significant differences were observed in the EVAR group. Conclusion Longer surgical and intubation times are associated with an increased risk of delirium in patients undergoing TEVAR. No significant factors influencing delirium are identified in patients undergoing EVAR.

Objective To investigate the clinical efficacy of Jianpi Qushi Method(a spleen-invigorating and dampness-removing approach)combined with Chinese herbal fumigation therapy in treating seborrheic alopecia of spleen deficiency with dampness-accumulation type and to observe its influence on hormone levels.Methods The observation was carried out in 104 patients with spleen deficiency with dampness-accumulation type of seborrheic alopecia,who admitted to the Department of Dermatology at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from January 2023 to February 2024.The patients were equally randomized into a trial group and a control group,with 52 cases in each group.The control group received oral administration of Finasteride Tablets,while the trial group was additionally treated with Jianpi Qushi Method combined with Chinese herbal fumigation therapy for 3 months.Serum hormone levels,hair loss scores,clinical symptom scores(including greasy hair,pruritus,scaling,and growth of new hair),and trichoscopic parameters of the hair in the two groups were assessed before and after treatment.After treatment,the clinical efficacy and adverse reactions in the two groups were also evaluated.Results(1)After 3 months of treatment,the total effective rate in the trial group was 94.23％(49/52)and that in the control group was 73.08％(38/52).The trial group demonstrated significantly superior efficacy compared to the control group(tested by chi-square test,P<0.01).(2)After treatment,both groups exhibited a significant decrease in serum testosterone level(P<0.05)and a significant increase in serum estradiol level(P<0.05)compared to those before treatment.Notably,the trial group showed a more pronounced reduction in testosterone and a greater elevation in estradiol than the control group(P<0.01).(3)Both groups displayed a significant reduction in hair loss scores after treatment(P<0.05),and the trial group achieved a markedly greater decrease than the control group(P<0.01).(4)After treatment,the clinical symptom scores for greasy hair,pruritus,scaling,and growth of new hair significantly decreased in both groups compared to those before treatment(P<0.05).And the trial group exhibited significantly greater improvements in the scores of all symptoms than the control group(P<0.01).(5)After treatment,both groups showed a significant increase in hair density(hairs/cm2)and count of upright regrowing hair(P<0.05),along with a significant decrease in vellus hair count,hair count in the single hair follicle,and count of perifollicular keratosis(P<0.05).The trial group demonstrated significantly superior improvements in all trichoscopic parameters compared to the control group(P<0.01).(6)No significant adverse reactions were observed in either group during the treatment period,indicating a favorable safety profile for both therapeutic approaches.Conclusion Jianpi Qushi Method combined with Chinese herbal fumigation therapy exerts significant efficacy in treating seborrheic alopecia of spleen deficiency with dampness-accumulation type.The combined therapy is effective on regulating hormone levels,promoting hair regeneration,and alleviating symptoms such as greasy hair and pruritus,and demonstrates favorable safety.

Based on the interleukin-17(IL-17) signaling pathway, this study explores the effect and mechanism of Bufei Decoction on Klebsiella pneumoniae pneumonia in rats. SD rats were randomly divided into the control group, model group, Bufei Decoction low-dose group(6.68 g·kg~(-1)·d~(-1)), Bufei Decoction high-dose group(13.36 g·kg~(-1)·d~(-1)), and dexamethasone group(1.04 mg·kg~(-1)·d~(-1)), with 10 rats in each group. A pneumonia model was established by tracheal drip injection of K. pneumoniae. After successful model establishment, the improvement in lung tissue damage was observed following drug administration. Core targets and signaling pathways were screened using transcriptomics techniques. Real-time fluorescence quantitative polymerase chain reaction was used to detect the mRNA expression of core targets interleukin-6(IL-6), interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and chemokine CXC ligand 6(CXCL6). Western blot was used to assess key proteins in the IL-17 signaling pathway, including interleukin-17A(IL-17A), nuclear transcription factor-κB activator 1(Act1), tumor necrosis factor receptor-associated factor 6(TRAF6), and downstream phosphorylated p38 mitogen-activated protein kinase(p-p38 MAPK), and phosphorylated nuclear factor-κB p65(p-NF-κB p65). Apoptosis of lung tissue cells was detected by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling(TUNEL). The results showed that, compared with the control group, the model group exhibited significant pathological damage in lung tissue. The mRNA expression of IL-6, IL-1β, TNF-α, and CXCL6, as well as the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly increased, and the number of apoptotic cells was notably higher, indicating successful model establishment. Compared with the model group, both low-and high-dose groups of Bufei Decoction showed reduced pathological damage in lung tissue. The mRNA expression levels of IL-6, IL-1β, TNF-α, and CXCL6, and the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly decreased, with a significant reduction in apoptotic cells in the high-dose group. In conclusion, Bufei Decoction can effectively improve lung tissue damage and reduce inflammation in rats with K. pneumoniae. The mechanism may involve the regulation of the IL-17 signaling pathway and the reduction of apoptosis.
Animals ; Interleukin-17/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Rats ; Male ; Klebsiella pneumoniae/physiology* ; Klebsiella Infections/immunology* ; Humans ; Lung/drug effects*

Osteoporosis(OP) is a metabolic bone disorder characterized by reduced bone mass and degenerative bone tissue. Osteoporotic pain(OPP) is its most common clinical symptom, significantly affecting the quality of life of patients. With the limitations of modern medical treatments and the intensification of aging, it is imperative to explore more cost-effective interventions for OPP. This paper, based on databases such as China National Knowledge Infrastructure(CNKI), VIP, Wanfang, BioMed, and Web of Science, uncovered the connection between the pathogenesis of OPP in traditional Chinese medicine(TCM) and modern medical mechanisms and retrospectively summarized the basic and clinical research methods and evidence of TCM prescriptions in the treatment of OP and related pain diseases. Studies have shown that TCM prescriptions, focusing on treatments such as nourishing the kidney, strengthening the spleen, and activating blood circulation to remove blood stasis, can significantly improve pain symptoms, increase bone mineral density(BMD), and adjust bone metabolic indicators such as C-terminal telopeptide of type Ⅰ collagen(CTX), serum bone Gla-protein(S-BGP), and alkaline phosphatase(ALP). The mechanisms of action of TCM prescriptions in treating OP and improving OPP symptoms were related to signaling pathways such as Wnt/β-catenin, nuclear factor kappa-B(NF-κB), mitogen-activated protein kinase(MAPK), phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt), and the osteoprotegerin(OPG)/receptor activator of NF-κB(RANK)/receptor activator of NF-κB ligand(RANKL) axis. Further strengthening the accumulation and analysis of clinical data, rigorously designing and conducting randomized controlled trials of TCM treatments for OPP with large sample sizes, standardizing outcome measures in basic and clinical research by using methods such as the core outcome set(COS), and incorporating mass spectrometry and omics approaches to uncover more potential active components and mechanisms may contribute to a deeper exploration of the advantages and essence of TCM prescriptions in the treatment of OPP.
Humans ; Osteoporosis/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Retrospective Studies ; Bone Density/drug effects* ; Medicine, Chinese Traditional ; Pain/metabolism* ; Animals

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To analyze the characteristics of HIV-1 pretreatment drug resistance(PDR)and molecular transmission networks in Yubei District,Chongqing,providing evidence for targeted interventions.Methods Using a cross-sectional design,plasma samples were collected from HIV/AIDS patients receiving antiretroviral therapy(ART)in Yubei District from January 2022 to December 2023.Pol gene fragments were extracted and amplified for HIV-1 genotyping and drug resistance analysis.Molecular transmission networks were constructed based on genetic distance calculations.Results Among 478 HIV-1 pol sequences,eight geno-types were identified:with CRF07_BC(60.4%,289/478),CRF08_BC(15.5%,74/478),CRF01_AE(11.7%,56/478),and CRF85_BC(5.9%,28/478).The overall PDR rate was 6.3%(30/478),with resistance to nucleoside reverse transcriptase inhibitors(NRTIs)and non-nucleoside reverse transcriptase inhibitors(NNRTIs)at 1.7%(8/478)and 5.2%(25/478),respectively.No protease inhibitor(PI)resistance was de-tected.The molecular network included 177 cases(37.0%network entry rate),forming 53 clusters with 198 connections.Cluster sizes ranged from 2 to 17 nodes,and 75.3%(149/198)of connections were associated with five subdistricts/towns:Shuanglonghu Street,Huixing Street,Luoqi Town,Gulu Town,and Baoshenghu Street.Conclusion HIV-1 genotypes in Yubei District exhibit diversity and complexity,with moderate PDR prevalence.Regional clustering of transmission networks suggests the need for enhanced molecular surveil-lance and targeted interventions based on analytical findings.