This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

A previous study showed that the length of the foreskin plays a role in the risk of sexually transmitted infections and chronic prostatitis, which can lead to poor quality of sexual life. Here, the association between foreskin length and sexual dysfunction was evaluated. A total of 5700 participants were recruited from the andrology clinic at The First Affiliated Hospital of University of Science and Technology of China (Hefei, China). Clinical characteristics, including foreskin length, were collected, and sexual function was assessed by the International Index of Erectile Function-5 (IIEF-5) and Premature Ejaculation Diagnostic Tool (PEDT) questionnaires. Men with sexual dysfunction were more likely to have redundant foreskin than men without sexual dysfunction. Among the 2721 erectile dysfunction (ED) patients and 1064 premature ejaculation (PE) patients, 301 (11.1%) ED patients and 135 (12.7%) PE patients had redundant foreskin, respectively. Men in the PE group were more likely to have redundant foreskin than men in the non-PE group ( P = 0.004). Logistic regression analyses revealed that the presence of redundant foreskin was associated with increased odds of moderate/severe ED (adjusted odds ratio [aOR] = 1.31, adjusted P = 0.04), moderate PE (aOR = 1.38, adjusted P = 0.02), and probable PE (aOR = 1.37, adjusted P = 0.03) after adjusting for confounding variables. Our study revealed a positive correlation between the presence of redundant foreskin and the risk of sexual dysfunction, especially in PE patients. Assessment of the length of the foreskin during routine clinical diagnosis may provide information for patients with sexual dysfunction.
Humans ; Male ; Foreskin ; Cross-Sectional Studies ; Adult ; Erectile Dysfunction/epidemiology* ; Premature Ejaculation/epidemiology* ; Middle Aged ; China/epidemiology* ; Surveys and Questionnaires ; Sexual Dysfunction, Physiological/epidemiology* ; Young Adult

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

Objective:To construct an evaluation indicator system for accessories of patient monitor,so as to provide a basis for clinical management,equipment procurement,and technical improvement for accessories of medical monitor.Methods:The initial selection indicators of corresponding accessories of three types of monitoring of medical monitors,including electrocardiogram(ECG),blood oxygen saturation(SpO2)and non-invasive blood pressure(NIBP),were determined through literature research,expert consultation,and actual investigation.The Delphi method was adopted to conduct two rounds of questionnaire consultation for experts from clinical medicine,biomedical engineering and other fields in medical institutions included Sichuan Provincial People's Hospital,The Affiliated Hospital of Southwest Medical University and Medical Institute of Chengdu Institute of Metrology Verification and Testing.The evaluation indicators were screened and optimized,and the Analytic Hierarchy Process(AHP)was used to calculate the weights of each indicator.The consistency test was conducted to verify the rationality of the evaluation indicator system.Results:The evaluation indicator system for accessories of medical monitor included three first-level indicators:clinical value,cost value,and management value.The number of second-level indicators about ECG,SpO2 and NIBP of evaluation indicator system were respectively 10,9 and 8,and the number of third-level indicators of that were respectively 20,19,and 14.In the first-level indicators,the clinical value had the highest weight,with 72.49%for ECG,70.88%for SpO2 and 70.32%for NIBP.In the second-level indicators,the accuracy(28.70%for ECG,38.13%for SpO2 and 43.03%for NIBP)and safety(27.47%for ECG,26.48%for SpO2 and 23.06%for NIBP)were the core indicators.The weights of cost value and management value were between 14.62%and 17.41%,and between 12.27%and 12.89%,respectively.Conclusion:The evaluation indicator system for accessories of medical monitor integrates multi-dimensional expert opinions and quantitative analysis,highlights the priority principle for clinical performance.It can provide theoretical support for optimizing selection about accessory for medical institutions,and improving quality of monitoring,and promoting standardized management in the industry.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To evaluate the consumption of opioid and postoperative analgesia of intercostal nerve block(ICNB)and paravertebral block(PVB)for autologuous rib cartilage graft for auricular reconstruction in children with microtia.Methods A total of 120 patients scheduled for autologuous rib cartilage graft for auricular reconstruction were enrolled.According to randomized blocks,patients were allocated into three groups(n=40 in each group):general anesthesia group(GA group),ultrasound-guided intercostal nerve block group(ICNB group)and ultrasound-guided PVB group(PVB group).GA group only received general anesthesia,while ICNB group and PVB group received single-shot nerve block with lidocaine after induction of general anesthesia.All groups were received patient-controlled intravenous analgesia(PCIA)for 48 hours postoperatively.Intraoperative opioid requirement was recorded.Heart rate(HR)and mean arterial pressure(MAP)were recorded at different time points during surgery.Time of the first visual analogue scale(VAS)obtained and duration of postanesthesia care unit(PACU)stay were evaluated.The VAS scores of chest and ear during deep breath and at rest were recorded during 48 hours postoperatively.Opioid consumption and postoperative analgesia-related adverse events were compared among the three groups during 48 hours after surgery.Results Compared with those in GA group,intraoperative fentanyl consumption(P=0.02,P<0.01),time of the first VAS obtained(P<0.01,P=0.02),duration of PACU stay(P<0.01,P<0.01)and HR when harvesting the first rib cartilage(P=0.04,P<0.01)were statistically lower in ICNB group and PVB group than those in GA group,but no statistical difference was found between these two groups.There were no statistical differences in VAS scores,opioid consumption and analgesia-related adverse events among the three groups.Conclusion Ultrasound-guided single-shot ICNB and PVB with lidocaine provide similar efficacy of reducing intraoperative opioid consumption,maintaining intraoperative hemodynamic stability and faster awakening,but fail to alleviate postoperative pain.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To evaluate the consumption of opioid and postoperative analgesia of intercostal nerve block(ICNB)and paravertebral block(PVB)for autologuous rib cartilage graft for auricular reconstruction in children with microtia.Methods A total of 120 patients scheduled for autologuous rib cartilage graft for auricular reconstruction were enrolled.According to randomized blocks,patients were allocated into three groups(n=40 in each group):general anesthesia group(GA group),ultrasound-guided intercostal nerve block group(ICNB group)and ultrasound-guided PVB group(PVB group).GA group only received general anesthesia,while ICNB group and PVB group received single-shot nerve block with lidocaine after induction of general anesthesia.All groups were received patient-controlled intravenous analgesia(PCIA)for 48 hours postoperatively.Intraoperative opioid requirement was recorded.Heart rate(HR)and mean arterial pressure(MAP)were recorded at different time points during surgery.Time of the first visual analogue scale(VAS)obtained and duration of postanesthesia care unit(PACU)stay were evaluated.The VAS scores of chest and ear during deep breath and at rest were recorded during 48 hours postoperatively.Opioid consumption and postoperative analgesia-related adverse events were compared among the three groups during 48 hours after surgery.Results Compared with those in GA group,intraoperative fentanyl consumption(P=0.02,P<0.01),time of the first VAS obtained(P<0.01,P=0.02),duration of PACU stay(P<0.01,P<0.01)and HR when harvesting the first rib cartilage(P=0.04,P<0.01)were statistically lower in ICNB group and PVB group than those in GA group,but no statistical difference was found between these two groups.There were no statistical differences in VAS scores,opioid consumption and analgesia-related adverse events among the three groups.Conclusion Ultrasound-guided single-shot ICNB and PVB with lidocaine provide similar efficacy of reducing intraoperative opioid consumption,maintaining intraoperative hemodynamic stability and faster awakening,but fail to alleviate postoperative pain.

Objective:To construct an evaluation indicator system for accessories of patient monitor,so as to provide a basis for clinical management,equipment procurement,and technical improvement for accessories of medical monitor.Methods:The initial selection indicators of corresponding accessories of three types of monitoring of medical monitors,including electrocardiogram(ECG),blood oxygen saturation(SpO2)and non-invasive blood pressure(NIBP),were determined through literature research,expert consultation,and actual investigation.The Delphi method was adopted to conduct two rounds of questionnaire consultation for experts from clinical medicine,biomedical engineering and other fields in medical institutions included Sichuan Provincial People's Hospital,The Affiliated Hospital of Southwest Medical University and Medical Institute of Chengdu Institute of Metrology Verification and Testing.The evaluation indicators were screened and optimized,and the Analytic Hierarchy Process(AHP)was used to calculate the weights of each indicator.The consistency test was conducted to verify the rationality of the evaluation indicator system.Results:The evaluation indicator system for accessories of medical monitor included three first-level indicators:clinical value,cost value,and management value.The number of second-level indicators about ECG,SpO2 and NIBP of evaluation indicator system were respectively 10,9 and 8,and the number of third-level indicators of that were respectively 20,19,and 14.In the first-level indicators,the clinical value had the highest weight,with 72.49%for ECG,70.88%for SpO2 and 70.32%for NIBP.In the second-level indicators,the accuracy(28.70%for ECG,38.13%for SpO2 and 43.03%for NIBP)and safety(27.47%for ECG,26.48%for SpO2 and 23.06%for NIBP)were the core indicators.The weights of cost value and management value were between 14.62%and 17.41%,and between 12.27%and 12.89%,respectively.Conclusion:The evaluation indicator system for accessories of medical monitor integrates multi-dimensional expert opinions and quantitative analysis,highlights the priority principle for clinical performance.It can provide theoretical support for optimizing selection about accessory for medical institutions,and improving quality of monitoring,and promoting standardized management in the industry.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.