Objectives: . This study aimed to investigate the regulatory functions of gamma-aminobutyric acid (GABA)ergic neural circuits from the inferior colliculus (IC) to the medial geniculate body (MGB) in salicylate-induced tinnitus. Methods: . Mice were treated with salicylate to induce tinnitus, and tinnitus-like behaviors were evaluated via gap prepulse inhibition of acoustic startle. Using combined viral tracing methodologies, we identified and mapped the pathways and connections from the IC to the MGB. Furthermore, we employed Gq-coupled human M3 designer receptors exclusively activated by designer drugs (DREADDs) and Gi-coupled human M4 DREADDs to achieve targeted excitation or suppression of GABAergic neurons in the IC and MGB. Following the administration of clozapine N-oxide, which binds to these receptors, we modulated these neural circuits to assess their impact on tinnitus severity in a mouse model. Results: . Our findings demonstrated that mice exposed to salicylate exhibited tinnitus-like behaviors. GABAergic neurons projecting retrogradely from the MGB to the IC were primarily concentrated in the external nucleus of the IC. After clozapine N-oxide administration, chemogenetic activation of IC-MGB GABAergic neurons aggravated salicylate-induced tinnitus. Additionally, activation of GABAergic neurons between the IC and MGB induced the perception of tinnitus even without salicylate. However, chemogenetic inhibition of the IC-MGB GABAergic circuit did not reverse salicylate-induced tinnitus. Conclusion . These findings suggest that activation of the IC-MGB GABAergic neural circuit may contribute to tinnitus generation through a mechanism distinct from that of salicylate-induced tinnitus. This study provides novel insights into the mechanisms underlying tinnitus.

ObjectiveThis study aims to investigate the molecular mechanism by which Guizhi Fulingwan （GFW） inhibits ferroptosis in endometriosis （EMT） through the regulation of the hypoxia inducible factor-1α/heme oxygenase 1 （HIF-1α/HO-1） signaling pathway. MethodsMachine learning was employed to identify ferroptosis-related biomarkers associated with EMT. Network pharmacology was utilized to identify the active components of GFW and its potential therapeutic targets against EMT， including core targets. Functional enrichment analysis was conducted to explore the biological processes， molecular functions， cellular components， and signaling pathways associated with the potential targets. An EMT rat model was established via autologous transplantation. Thirty female Sprague-Dawley （SD） rats were randomly divided into five groups： sham-operated， model， positive control （dienogest at 0.2 mg·kg^-1）， low-dose GFW （2.5 g·kg^-1）， and high-dose GFW （5 g·kg^-1）. After modeling， the rats received their respective treatment by oral gavage for 28 consecutive days， while the sham and model groups received equal volumes of distilled water. Serum and ectopic endometrial tissues were collected. Hematoxylin and eosin （HE） staining was employed to evaluate morphological alterations in ectopic lesions. Quantitative real-time polymerase chain reaction （Real-time PCR） and Western blot were conducted to assess mRNA and protein expression of HIF-1α， HO-1， glutathione peroxidase 4 （GPX4）， spermidine/spermine N1-acetyltransferase （SAT1）， and prostaglandin-endoperoxide synthase 2 （PTGS2）. Tissue levels of malondialdehyde （MDA）， glutathione （GSH）， and ferrous iron （Fe²⁺） were quantified using commercial assay kits. Serum levels of interleukin-6 （IL-6） and transforming growth factor-β₁ （TGF-β₁） were measured via enzyme-linked immunosorbent assay （ELISA）. ResultsFive ferroptosis-related biomarkers in EMT were identified： ALOX12， CHAC1， SAT1， AST1， and HO-1. Network pharmacology analysis revealed 42 active components of GFW and 192 potential therapeutic target genes related to EMT treatment， with FOS， JUN， HO-1 identified as core targets. Functional enrichment analysis indicated that the potential targets were primarily involved in oxidative stress response and reactive oxygen species metabolism and were enriched in the HIF-1 signaling pathway. Compared to the sham-operated group， the model group exhibited significant increases in both mRNA and protein expression of HIF-1α， HO-1， and PTGS2， as well as elevated tissue levels of Fe²⁺ and MDA. Conversely， GSH levels and the expression of GPX4 and SAT1 were markedly reduced， and serum levels of IL-6 and TGF-β₁ levels were significantly higher （P<0.01）. Compared with the model group， all GFW-treated groups showed significant downregulation of HIF-1α and HO-1， reduced Fe²⁺ levels， and downregulated expression of MDA， PTGS2， IL-6， and TGF-β₁. Meanwhile， GSH， GPX4， and SAT1 expression levels were significantly increased （P<0.05， P<0.01）， effectively ameliorating iron overload and oxidative stress， thereby demonstrating therapeutic efficacy in EMT， with the high-dose GFW demonstrating the most pronounced therapeutic effects. ConclusionGFW exerts therapeutic effects on endometriosis by regulating the HIF-1α/HO-1 signaling pathway to rectify iron metabolism disorders and attenuate free iron-induced oxidative damage. It upregulates the antioxidative defense system to inhibit lipid peroxidation cascades and modulates inflammatory cytokine networks. These effects collectively disrupt the pathological interaction between ferroptosis and chronic inflammation， providing a novel theoretical foundation for the clinical application of GFW in EMT treatment.

Negative logarithm of the acid dissociation constant (pK _a) significantly influences the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of molecules and is a crucial indicator in drug research. Given the rapid and accurate characteristics of computational methods, their role in predicting drug properties is increasingly important. Although many pK _a prediction models currently exist, they often focus on enhancing model precision while neglecting interpretability. In this study, we present GraFpK _a, a pK _a prediction model using graph neural networks (GNNs) and molecular fingerprints. The results show that our acidic and basic models achieved mean absolute errors (MAEs) of 0.621 and 0.402, respectively, on the test set, demonstrating good predictive performance. Notably, to improve interpretability, GraFpK _a also incorporates Integrated Gradients (IGs), providing a clearer visual description of the atoms significantly affecting the pK _a values. The high reliability and interpretability of GraFpK _a ensure accurate pK _a predictions while also facilitating a deeper understanding of the relationship between molecular structure and pK _a values, making it a valuable tool in the field of pK _a prediction.

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 To analyze the application effects of artificial intelligence (AI) software and Mimics software in preoperative three-dimensional (3D) reconstruction for thoracoscopic anatomical pulmonary segmentectomy. Methods A retrospective analysis was conducted on patients who underwent thoracoscopic pulmonary segmentectomy at the Second People's Hospital of Huai'an from October 2019 to March 2024. Patients who underwent AI 3D reconstruction were included in the AI group, those who underwent Mimics 3D reconstruction were included in the Mimics group, and those who did not undergo 3D reconstruction were included in the control group. Perioperative related indicators of each group were compared. Results A total of 168 patients were included, including 73 males and 95 females, aged 25-81 (61.61±10.55) years. There were 79 patients in the AI group, 53 patients in the Mimics group, and 36 patients in the control group. There were no statistical differences in gender, age, smoking history, nodule size, number of lymph node dissection groups, postoperative pathological results, or postoperative complications among the three groups (P>0.05). There were statistical differences in operation time (P<0.001), extubation time (P<0.001), drainage volume (P<0.001), bleeding volume (P<0.001), and postoperative hospital stay (P=0.001) among the three groups. There were no statistical differences in operation time, extubation time, bleeding volume, or postoperative hospital stay between the AI group and the Mimics group (P>0.05). There was no statistical difference in drainage volume between the AI group and the control group (P=0.494), while there were statistical differences in operation time, drainage tube retention time, bleeding volume, and postoperative hospital stay (P<0.05). Conclusion For patients requiring thoracoscopic anatomical pulmonary segmentectomy, preoperative 3D reconstruction and preoperative planning based on 3D images can shorten the operation time, postoperative extubation time and hospital stay, and reduce intraoperative bleeding and postoperative drainage volume compared with reading CT images only. The use of AI software for 3D reconstruction is not inferior to Mimics manual 3D reconstruction in terms of surgical guidance and postoperative recovery, which can reduce the workload of clinicians and is worth promoting.

Objective To investigate the mechanism of Kuijie Ankang Decoction in regulating immune,autophagy and intestinal flora in the treatment of ulcerative colitis(UC).Methods UC mouse model was established by free drinking with sodium dextran sulfate.The mice were randomly divided into blank control group,model group,Kuijie Ankang Decoction group,salazine sulfopyridine(SASP)group and 3-methyladenine(3-MA)group,with 12 mice in each group.Each drug group was given corresponding drugs for gavage,the blank control group and model group were given the same volume of distilled water for gavage for 7 days.The general condition of mice was observed and the disease activity index(DAI)was scored,the morphology of colon tissue was observed by HE staining,the contents of TNF-α,IL-1β,IL-6,IL-8 and IL-10 in colon tissue were detected by ELISA,the mRNA and protein expressions of LC3,Beclin-1 and p62 in colon tissue were detected by RT-qPCR and Western blot,respectively.16S rDNA sequencing was used to analyze the structure of intestinal flora.Results Compared with the blank control group,the mice in the model group showed a decrease in body mass,an increase in DAI score,a decrease in colon length,serious mucosal injury and inflammatory cell infiltration,the contents of TNF-α,IL-1β,IL-6 and IL-8 in colon tissue significantly increased(P<0.05,P<0.01),the content of IL-10 decreased(P<0.01),the mRNA expressions of LC3 and Beclin-1 in colon tissue decreased(P<0.05,P<0.01),the mRNA and protein expression of p62 increased(P<0.01),while the expressions of LC3Ⅱ/LC3Ⅰ and Beclin-1 proteins decreased(P<0.05,P<0.01).Compared with the model group,the body mass of mice in Kuijie Ankang Decoction group and SASP group increased(P<0.05),DAI score decreased(P<0.05),the colon length increased(P<0.05),the pathological damage of colon mucosa was alleviated,the contents of TNF-α,IL-1β,IL-6 and IL-8 in colon tissue decreased(P<0.05,P<0.01),the content of IL-10 increased(P<0.01),the expressions of LC3 and Beclin-1 mRNA in colon tissue increased(P<0.05,P<0.01),the expression of p62 mRNA and protein decreased(P<0.05,P<0.01),the expressions of LC3Ⅱ/LC3Ⅰand Beclin-1 protein increased(P<0.05,P<0.01).16S rDNA sequencing results showed that the diversity and evenness of the intestinal flora in the model group mice decreased,with a decrease in the relative abundance of Firmicutes,Actinobacteria and Patescibacteria(P<0.05),and an increase in the relative abundance of Bacteroidota,Verrucomicrobiota and Proteobacteria(P<0.05);the relative abundance of Bacilli and Coriobacteriia decreased(P<0.05),the relative abundance of Bacteroidia,Clostridia and Verrucomicrobiae increased(P<0.05);the relative abundance of Ligilactobacillus and Dubosiella decreased(P<0.05),the relative abundance of unclassified Muribaculaceae,Lachnospiraceae NK4A136_group,Akkermansia and unclassified Lachnospiraceae increased(P<0.05).Compared with the model group,the diversity and evenness of intestinal flora increased in Kuijie Ankang Decoction group and SASP group,with an increase in the relative abundance of Firmicutes(P<0.05),a decrease in the relative abundance of Bacteroidota and Verrucomicrobiota(P<0.05),the relative abundance of Bacteroidia and Bacilli increased(P<0.05),the relative abundance of Verrucomicrobiae decreased(P<0.05);the relative abundance of unclassified Muribaculaceae and Ligilactobacillus increased(P<0.05),while the relative abundance of Lachnospiraceae NK4A136_group and Akkermansia decreased(P<0.05).Conclusion Kuijie Ankang Decoction can significantly improve the intestinal mucosal injury of UC mice,and the mechanism may be related to the regulation of colon autophagy level and intestinal flora disorder.

Objective To translate the Urinary Incontinence Awareness and Attitude Scale(URINAS)and test its reliability and validity.Methods The Chinese version of the URINAS was developed by Brislin's translation model for translation,back translation,cultural adaptation,and pilot investigation.A convenience sampling method was used to select 384 urinary incontinence patients who visited a tertiary hospital in Nanchang,Jiangxi Province from June 2024 to October 2024 for investigation,in order to evaluate the reliability and validity of the scale.Results The Chinese version of the URINAS consisted of 5 dimensions with 26 entries.The Cronbach's alpha coefficient of this scale was 0.843;the folded half reliability was 0.917;the retest reliability was 0.852.The content validity of the scale at the level of the entries ranged from 0.846 to 1.000,and that at the level of the scale was 0.979.A total of 5 metrics were extracted by exploratory factor analysis,and the cumulative variance contribution rate of 74.286％.The results of the validation factor analysis showed a chi-square/degree of freedom of 2.268,a root mean square error of approximation of 0.064,a standardized fit index of 0.916,a Tucker-Lewis index of 0.923,a comparative fit index of 0.906,and a goodness-of-fit index of 0.922.Conclusion The URINAS has good reliability and validity,and can better reflect the level of patients' cognition and attitude towards urinary incontinence,thus providing theoretical basis for the development of corresponding intervention programs for such patients.

Objectives:To explore whether short-course radiotherapy (SCRT)-based total neoadjuvant therapy (TNT) combined with PD-1 inhibitors could further promote tumor regression and improve the prognosis.Methods:This is a prospective, multicenter, two-arm randomized controlled, seamless phase Ⅱ/Ⅲ trial for proficient mismatch repair or microsatellite stable (pMMR/MSS) locally advanced rectal cancer (LARC). Eligible patients were randomly assigned to the iTNT (TNT+PD-1) group or the TNT group. Patients in the TNT group received SCRT (5 Gy×5) followed by 4 cycles of CAPOX or 6 cycles of mFOLFOX chemotherapy, with the iTNT group receiving SCRT followed by the same regime in combination with 4 cycles of Sintilimab. Total mesorectal excision (TME) surgery or watch and wait (W&W) was performed after neoadjuvant therapy and then 2 cycles of same regimen as before were recommended. The primary endpoints are the complete response (CR) rate for phase Ⅱ trial and 3-year disease-free survival (DFS) for phase Ⅲ trial. A total of 588 patients will be enrolled for the phase Ⅱ/Ⅲ trial. Short-term efficacy and safety data from the initial 100 treated patients were analyzed as planned.Results:From 2022-8-31 to 2023-5-24 the initial 100 patients were enrolled from 10 hospitals in China, 76.0%(76/100) patients were male, and the median age was 61 years (21-74 years). More patients had tumors located in the lower rectum (78.0%, 78/100), staged T3-4 (97.0%, 97/100) and N1-2 (93.0%, 93/100), and about half of the tumors invaded the mesorectal fascia (52.0%, 52/100) and with extramural vascular invasion (51.0%, 51/100). Analyses were performed according to the per-protocal (PP) set. All patients in the iTNT group ( n=52) and the TNT group ( n=48) completed SCRT; The 4-cycle chemotherapy±Sintilimab completion rates were 86.5% and 100.0% in the iTNT and TNT groups, respectively. In the iTNT group, 82.7% (43/52), 11.5% (6/52), and 5.8% (3/52) of the patients received 4, 3, and 2 cycles of PD-1 inhibitor. After TNT, 68 patients underwent radical surgery and 15 patients achieved cCR and adopted W&W. The pathological complete response (pCR) rates were 48.5% (16/33) and 17.1% (6/35) in the iTNT and TNT groups, with CR rates of 50.0% (25/50) and 26.1% (12/46), respectively. The incidence of treatment-related grade 3-4 adverse events was 26.9% (14/52, iTNT group) and 18.8% (9/48, TNT group), with thrombocytopenia and leukopenia being the most common. Among patients receiving immunotherapy, grade 3 immunotherapy-related adverse events occurred in 2 (3.8%, 2/52) patients: one case was pancreatitis, another case was hepatitis combined with myositis and myocarditis. Conclusion:The preliminary results show that SCRT-based TNT combined with PD-1 inhibitors could further improve the CR rate for LARC without unexpected serious adverse events.

Aim To investigate the effect of Senecio scandens Buch.-Ham on inflammatory pain mediated by mast cell P2X7 receptor.Methods Using the ATP-induced foot inflammatory pain,immunofluores-cence and toluidine blue staining techniques were used to investigate whether Senecio scandens has inhibitory effect on P2X7 receptor on mast cells.Using the calci-um ion imaging experimental technology,to explore whether Senecio scandens inhibit the intracellular cal-cium ion enrichment caused by activation of P2X7 re-ceptor on mouse peritoneal mast cell.The whole-cell patch clamp technique was used to investigate whether senecio scandens could inhibit the inward current in-duced by activation of P2X7 receptor on mouse perito-neal mast cell.Results In vivo,Senecio scandens alle-viate ATP induced inflammatory pain(3.9 g·kg-1:P＜0.05),and significantly inhibited the infiltration of P2X7 receptor-positive mast cells(3.9 g·kg-1:P＜0.05).Knockout of mast cell can reduce the analgesic effect of Senecio scandens(3.9 g·kg-1:P=0.645).In vitro.The experiment results show that senecio scandens can significantly inhibit the calcium influx(300 mg·L-1:P＜0.05;1 g·L-1:P＜0.01;3 g·L-1:P＜0.01)and the inward current mediated by P2X7 receptor in mast cell(1 g·L-1:P＜0.01).Conclusion Senecio scandens alleviate inflammatory pain by inhibiting mast cell P2X7 receptor.

Negative logarithm of the acid dissociation constant(pKa)significantly influences the absorption,dis-tribution,metabolism,excretion,and toxicity(ADMET)properties of molecules and is a crucial indicator in drug research.Given the rapid and accurate characteristics of computational methods,their role in predicting drug properties is increasingly important.Although many pKa prediction models currently exist,they often focus on enhancing model precision while neglecting interpretability.In this study,we present GraFpKa,a pKa prediction model using graph neural networks(GNNs)and molecular finger-prints.The results show that our acidic and basic models achieved mean absolute errors(MAEs)of 0.621 and 0.402,respectively,on the test set,demonstrating good predictive performance.Notably,to improve interpretability,GraFpKa also incorporates Integrated Gradients(IGs),providing a clearer visual description of the atoms significantly affecting the pKa values.The high reliability and interpretability of GraFpKa ensure accurate pKa predictions while also facilitating a deeper understanding of the relation-ship between molecular structure and pKa values,making it a valuable tool in the field of pKa prediction.