ObjectiveTo observe the effects of Jiangtang No. 3 prescription on inflammatory pathways and insulin resistance-related indicators in rats with type 2 diabetes mellitus （T2DM）， and to elucidate its molecular mechanism in combating diabetes. MethodsA T2DM rat model was established using a high-fat diet combined with intraperitoneal injection of streptozotocin （STZ）. Successfully modeled rats were randomly assigned to the model group， metformin group， and low-， medium-， and high-dose Jiangtang No. 3 prescription groups， and a normal group was also set. Daily gavage was administered for 8 weeks as follows： metformin at 0.1 g·kg^-1·d^-1， Jiangtang No. 3 prescription granules at 1.62， 3.24， 6.48 g·kg^-1·d^-1 for the respective dose groups， and sterile water for the normal and model groups. Rat body weight， fasting blood glucose （FBG）， oral glucose tolerance test （OGTT）， and insulin tolerance test （ITT） were measured. After drug intervention， enzyme-linked immunosorbent assay （ELISA） was used to determine serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL）， high-density lipoprotein cholesterol （HDL）， non-esterified fatty acids （NEFA）， interleukin （IL）-1β， IL-18， and insulin （INS）. Hematoxylin-eosin （HE） staining was used to observe morphological changes in adipose tissue. Real-time quantitative PCR was used to detect the mRNA expression of Toll-like receptor 4 （TLR4）， nuclear factor-κB （NF-κB）， NOD-like receptor protein 3 （NLRP3）， Caspase-1， IL-1β， IL-18， and gasdermin D （GSDMD） in adipose tissue. Western blot was used to measure the corresponding protein expression levels. ResultsCompared with the model group， Jiangtang No. 3 prescription groups exhibited significantly increased body weight （P<0.05， P<0.01）， significantly reduced FBG （P<0.05， P<0.01）， significant reductions in TC， TG， NEFA， and LDL （P<0.05， P<0.01）， and a significant increase in HDL （P<0.01）. Serum levels of inflammatory mediators IL-1β and IL-18 were significantly decreased （P<0.01）， the homeostatic model assessment of insulin resistance （HOMA-IR） index was significantly reduced （P<0.05， P<0.01）， and adipose tissue pathology was improved. The protein expression levels of TLR4， NF-κB， NLRP3， Caspase-1， IL-1β， IL-18， and GSDMD were markedly decreased （P<0.05， P<0.01）， and the mRNA expression levels of these indicators were also significantly downregulated （P<0.05， P<0.01）. Some effects were superior to those of the positive control drug metformin， and certain indicators exhibited dose-dependent improvements. ConclusionT2DM rats display significant inflammatory responses， disordered glucose and lipid metabolism， and insulin resistance. Jiangtang No. 3 prescription effectively suppresses inflammatory mediators， improves glucose and lipid metabolism and insulin resistance， and ameliorates pathological changes in adipose tissue. Its mechanism may be related to the regulation of the TLR4/NF-κB/NLRP3 signaling pathway in visceral adipose tissue， thereby influencing downstream inflammatory mediators.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba（TPAGH）， and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group， recombinant human epidermal growth factor（rhEGF） group（4 mg·kg^-1）， and low， medium， and high dose groups of TPAGH（3.5， 7， 14 mg·kg^-1）， with 24 mice in each group. A full-thickness skin excision model was constructed， and each administration group was coated with the drug at the wound site， and the model group was treated with an equal volume of normal saline， the treatment was continued for 30 days， during which 8 mice from each group were sacrificed on days 6， 12， and 30. The healing of the wounds in the mice was observed， and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin（HE）， Masson， and Sirius red staining， and enzyme-linked immunosorbent assay（ELISA） was used to dynamically measure the contents of interleukin-6（IL-6）， tumor necrosis factor-α（TNF-α）， vascular endothelial growth factor A（VEGFA）， matrix metalloproteinase（MMP）-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH， and molecular docking of key components and targets was performed. Gene Ontology（GO） biological process analysis and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis were carried out for the related targets， so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH， including 28 phenylpropanoids， 31 tannins， 23 triterpenes， 49 flavonoids， and 15 others， and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that， compared with the model group， the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate（P<0.05）， and the number of new capillaries， number of fibroblasts， number of new skin appendages， epidermal regeneration rate， collagen deposition ratio， and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved（P<0.05， 0.01）， the levels of IL-6， TNF-α， MMP-3 and MMP-9 in the skin tissues were reduced to different degrees， while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets， including tumor protein 53（TP53）， sarcoma receptor coactivator（SRC）， protein kinase B（Akt）1， signal transducer and activator of transcription 3（STAT3）， epidermal growth factor receptor（EGFR） and so on， participating in 75 signaling pathways such as advanced glycation end-products（AGE）-receptor for AGE（AGE/RAGE） signaling pathway， phosphatidylinositol 3-kinase（PI3K）/Akt signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway. Molecular docking confirmed that the key components genistein， geraniin， and casuariin had good binding ability to TP53， SRC， Akt1， STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction， thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology， the study explores how key components may bind to targets such as TP53， Akt1 and EGFR， exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.

ObjectiveTo investigate the mechanism of ferroptosis mediated by long-chain acyl-CoA synthetase 4 （ACSL4） signalling pathway in rats with coronary heart disease with blood stasis syndrome and the intervention effect of Xuefu Zhuyutang. MethodsSPF male SD rats were randomly divided into normal group， sham-operation group， model group， trimetazidine group （5.4 mg·kg^-1）， low-， medium-， and high-dose group （3.51， 7.02，14.04 g·kg^-1） of Xuefu Zhuyutang. The coronary artery left anterior descending ligation method was used to prepare a model of coronary heart disease with blood stasis syndrome， and continuous treatment for 7 d was conducted， while the sham-operation group was only threaded and not ligated. The general macroscopic symptoms of the rats were observed， and indicators such as electrocardiogram， echocardiography， and blood rheology were detected. The pathological morphology of myocardial tissue was observed by hematoxylin-eosin （HE） staining， and the changes in mitochondria in myocardial tissue were observed by transmission electron microscopy. The level of iron deposition in myocardial tissue was observed by Prussian blue staining. The levels of 12-hydroxyeicosatetraenoic acid （12-HETE） and 15-HETE were detected in serum by enzyme-linked immunosorbent assay. A biochemical colourimetric assay was used to detect the levels of Fe²⁺， lipid peroxidation （LPO）， glutathione （GSH）， and T-GSH/glutathione disulfide （GSSG） in myocardial tissue. DCFH-DA fluorescence quantitative assay was employed to detect the levels of reactive oxygen species （ROS）. Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was adopted to detect the protein and mRNA expressions of glutathione peroxidase 4 （GPX4）， ferritin heavy chain 1 （FTH1）， ACSL4， and ly-sophosphatidylcholine acyltransferase3 （LPCAT3） in myocardial tissue. ResultsCompared with those in the normal group， the rats in the model group were poor in general macroscopic symptoms. The electrocardiogram showed widened QRS wave amplitude and increased voltage， bow-back elevation of the ST segments， elevated T waves， J-point elevation， and accelerated heart rate. Echocardiography showed a significant reduction in left ventricular ejection fraction （LVEF） and left ventricular fraction shortening （LVFS） （P<0.01）. Blood rheology showed that the viscosity of the whole blood （low， medium， and high rate of shear） was significantly increased （P<0.01）. HE staining showed an abnormal structure of myocardial tissue. There was a large area of myocardial necrosis and inflammatory cell infiltration and a large number of connective tissue between myocardial fibers. Transmission electron microscopy showed that the mitochondria were severely atrophy or swelling. The cristae were reduced or even broken， and the matrix was flocculent or even vacuolated. Prussian blue staining showed that there were a large number of iron-containing particles， and the iron deposition was obvious. The content of 12-HETE and 15-HETE in the serum was significantly increased （P<0.01）. The content of Fe²⁺， LPO， and ROS in myocardial tissue was significantly increased （P<0.01）. The content of GSH was significantly decreased （P<0.01）， and T-GSH/GSSG was decreased （P<0.01）. The protein and mRNA expressions of GPX4 and FTH1 in myocardial tissue were both significantly decreased （P<0.05， P<0.01）， while those of ACSL4 and LPCAT3 increased significantly （P<0.01）. Compared with the model group， the general macroscopic symptoms and electrocardiogram results of rats in low-， medium- and high-dose groups of Xuefu Zhuyutang were alleviated， and the differences in LVEF/LVFS ratios were all significantly increased （P<0.05， P<0.01）. The differences in whole-blood viscosity （low， medium， and high rate of shear） were all significantly decreased （P<0.01）. The results of HE staining and transmission electron microscopy showed that the morphology， structure， and mitochondria of cardiomyocytes were improved. The content of 12-HETE and 15-HETE in serum was reduced to different degrees in low-， medium-， and high-dose groups of Xuefu Zhuyutang （P<0.05， P<0.01）. The content of Fe²⁺， LPO， and ROS was significantly reduced in the medium- and high-dose groups of Xuefu Zhuyutang （P<0.05， P<0.01）， and the content of GSH and T-GSH/GSSG was significantly increased （P<0.05， P<0.01）. The protein and mRNA expressions of GPX4 and FTH1 were significantly increased to varying degrees in the medium- and high-dose groups of Xuefu Zhuyutang （P<0.05， P<0.01）， and ACSL4 and LPCAT3 were decreased to different degrees in the low-， medium-， and high-dose groups of Xuefu Zhuyutang （P<0.05， P<0.01）. ConclusionXuefu Zhuyutang can regulate iron metabolism and anti-lipid oxidation reaction to mediate ferroptosis through the ACSL4 signalling pathway， thus exerting a protective effect on rats with coronary heart disease with blood stasis syndrome.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Primary female genital system lymphoma(PFGSL)is a rare subtype of extranodal lymphoma and patients commonly present in the department of gynecology.At present,there is a lack of uniform standards for the treatment of PFGSL.Although the classification of lymphoid neoplasmas was updated by the World Health Organization classification of haematolymphoid tumors in 2016,PFGSL was still not elaborated in sufficient detail.Most cases of PFGSL are non-Hodgkin lymphoma,involving the ovary and cervix.In some cases,involvement of uterine corpus,vagina,and vulva is reported.In this article,we report two cases of non-Hodgkin lymphoma in the female genital system,one from the uterus and the other from the ovary.By presenting the diagnosis and treatment of the two cases and reviewing the literature,we aim to provide a reference for clinicians in recognizing and treating rare cases.
Female ; Humans ; Genital Neoplasms, Female/diagnosis* ; Lymphoma, Non-Hodgkin/diagnosis* ; Ovarian Neoplasms

Urinary incontinence is a common complication following robot-assisted radical prostatectomy (RARP). Urethral length has been identified as a factor affecting postoperative continence recovery. In this meta-analysis, we examined the association between use of the maximal urethral length preservation (MULP) technique and postoperative urinary continence in patients undergoing RARP. We conducted a comprehensive search of PubMed, Web of Science, Embase, and the Cochrane Library up to December 31, 2023. The quality of the literature was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis was performed to synthesize data and calculate the odds ratio (OR) from eligible studies on continence and MULP. Six studies involving 1869 patients met the eligibility criteria. MULP was positively associated with both early continence (1 month after RARP; Z = 3.62, P = 0.003, OR = 3.10, 95% confidence interval [CI]: 1.68-5.73) and late continence (12 months after RARP; Z = 2.34, P = 0.019, OR = 2.10, 95% CI: 1.13-3.90). Oncological outcomes indicated that MULP did not increase the overall positive surgical margin rate or the positive surgical margin status at the prostate apex (both P > 0.05). In conclusion, the use of the MULP technique in RARP significantly improved both early and late postoperative continence outcomes without compromising oncological outcomes.
Humans ; Prostatectomy/adverse effects* ; Robotic Surgical Procedures/methods* ; Male ; Urethra/surgery* ; Urinary Incontinence/prevention & control* ; Postoperative Complications/etiology* ; Prostatic Neoplasms/surgery* ; Organ Sparing Treatments/methods*

Male factors contribute to 50% of infertility cases, with 20%-30% of cases being solely attributed to male infertility. Helicase for meiosis 1 ( HFM1 ) plays a crucial role in ensuring proper crossover formation and synapsis of homologous chromosomes during meiosis, an essential process in gametogenesis. HFM1 gene mutations are associated with male infertility, particularly in cases of non-obstructive azoospermia and severe oligozoospermia. However, the effects of intracytoplasmic sperm injection (ICSI) in HFM1 -related infertility cases remain inadequately explored. This study identified novel biallelic HFM1 variants through whole-exome sequencing (WES) in a Chinese patient with severe oligozoospermia, which was confirmed by Sanger sequencing. The pathogenicity of these variants was assessed using real-time quantitative polymerase chain reaction (RT-qPCR) and immunoblotting, which revealed a significant reduction in HFM1 mRNA and protein levels in spermatozoa compared to those in a healthy control. Transmission electron microscopy revealed morphological abnormalities in sperm cells, including defects in the head and flagellum. Despite these abnormalities, ICSI treatment resulted in a favorable fertility outcome for the patient, indicating that assisted reproductive techniques (ART) can be effective in managing HFM1 -related male infertility. These findings offer valuable insights into the management of such cases.
Humans ; Male ; Sperm Injections, Intracytoplasmic ; Oligospermia/therapy* ; Adult ; Spermatozoa/ultrastructure* ; Exome Sequencing ; Mutation