BACKGROUND:Hydroxy safflower yellow A has anti-ischemia,anti-oxidation,anti-thrombotic and anti-inflammatory effects.Whether it affects neuronal pyroptosis after glucose-oxygen deprivation/reglucose-reoxygenation is still unclear. OBJECTIVE:To investigate the protective effect of hydroxy safflower yellow A on neuronal pyroptosis and its mechanism. METHODS:HT22 cells in logarithmic growth phase were randomly divided into five groups:normal group,model group,hydroxy safflower yellow A group,colivelin group,and colivelin+hydroxy safflower yellow A group.HT22 cells were treated with glucose-oxygen deprivation/reglucose-reoxygenation to establish neuronal pyroptosis model,and then treated with STAT3 agonist Colivelin and hydroxy safflower yellow A.JC-1 probe was employed to assess changes in mitochondrial membrane potential.Reactive oxygen species kit was used to determine the content of reactive oxygen species in cells.GSDMD/TUNEL staining was conducted to observe cell pyroptosis.Immunofluorescence analysis was performed to detect STAT3 and GSDMD protein expression.RT-PCR was utilized for assessing mRNA expression levels of STAT3,NLRP3,and Caspase-1.Western blot assay was utilized to measure the protein expression levels of p-STAT3,NLRP3,GSDMD,Cleaved-caspase-1,and interleukin-1β. RESULTS AND CONCLUSION:(1)Compared with the normal group,the number of pyroptotic cells increased in HT22 cells in the model group along with a significant increase in protein expression levels of p-STAT3,NLRP3,Cleaved-caspase-1,GSDMD,and interleukin-1β.Compared with the model group,the number of pyroptotic cells reduced,and the expression of pyroptosis-related proteins significantly decreased in the hydroxy safflower yellow A group.(2)In comparison with the model group,pyroptosis worsened in the colivelin group where mitochondrial membrane potential decreased along with elevated reactive oxygen species content and increased mRNA expression levels of STAT3,NLRP3,and Caspase-1,as well as increased protein expression levels of p-STAT3,NLRP3,GSDMD,Cleaved-caspase-1,and interleukin-1β.Compared with the Colivelin group,above indexes were improved in the colivelin+hydroxy safflower yellow A group.These results suggest that hydroxy safflower yellow A plays a neuroprotective role through STAT3 signaling pathway to inhibit HT22 pyroptosis after glucose-oxygen deprivation/reglucose-reoxygenation treatment.

ObjectiveTo establish the quality standards for Sennae Folium（Cassia angustifolia） dispensing granules based on standard decoctions. MethodsHigh performance liquid chromatography（HPLC） specific chromatograms were established for 15 batches of Sennae Folium（C. angustifolia） standard decoctions and 10 of Sennae Folium（C. angustifolia） dispensing granules from different manufacturers， and the similarity evaluation， hierarchical cluster analysis（HCA） and principal component analysis（PCA） were performed. Linear calibration with two reference substances（LCTRS） and quantitative analysis of multi-components by single-marker（QAMS） were established for the common peaks in the specific chromatograms to determine the contents of main components in the decoction pieces， standard decoctions and dispensing granules， and to calculate their transfer rates from decoction pieces to standard decoctions and dispensing granules. ResultsThe similarities of specific chromatograms of 15 batches of Sennae Folium（C. angustifolia） standard decoctions and 10 batches of Sennae Folium（C. angustifolia） dispensing granules were all greater than 0.95， and a total of 8 characteristic peaks were calibrated， and five of them were identified， including kaempferol-3，7-O-diglucoside， apigenin-6，8-di-C-glucoside， quercetin-3-O-gentianoside， sennoside B and sennoside A. HCA and PCA results showed that there were certain differences in the composition of different batches of standard decoctions， but no clustering was observed in the production area. As the standard decoctions， the extract rate of 15 batches of samples was 26.54%-45.38%， the contents of kaempferol-3，7-O-diglucoside， apigenin-6，8-di-C-glucoside， quercetin-3-O-gentianoside， sennoside B and sennoside A were 12.16-19.26， 2.57-4.94， 3.27-5.11， 6.75-11.39， 4.69-7.79 mg·g^-1， and their transfer rates from decoction pieces to standard decoctions were 45.41%-79.02%， 29.12%-55.07%， 40.52%-67.90%， 24.72%-49.12%， 27.54%-49.34%， respectively. The extract rates of Sennae Folium（C. angustifolia） dispensing granules（C8-C10） were 38.10%-39.50%， the transfer rates of the above five components from decoction pieces to dispensing granules were 72.85%-73.58%， 53.43%-53.94%， 40.19%-40.74%， 24.62%-25.00%， 28.65%-29.11%， respectively， which were generally consistent with the transfer rates from decoction pieces to standard decoctions. ConclusionCompared with the relative retention time method， LCTRS has higher prediction accuracy and is more suitable for chromatographic columns. The established quality control standard of Sennae Folium（C. angustifolia） dispensing granules based on standard decoction is reasonable and reliable， and all indicators of samples from different manufacturers are within the range specified based on the standard decoction， which can provide reference for the quality control and process research of this dispensing granules.

ObjectiveTo establish the specific chromatogram of Chuanxiong Rhizoma dispensing granules（CRdg）， and to evaluate its quality by chemometrics and two reference substances for determination of multiple components（TRSDMC）. MethodsHigh performance liquid chromatography（HPLC） specific chromatograms were established using 13 batches of CRdg from 7 manufacturers， and preliminary quality evaluation was performed by similarity evaluation and chemometrics analysis. Eight characteristic peaks in the specific chromatogram of CRdg were measured on 22 different types of C₁₈ columns， and the actual retention times were recorded. Taking chlorogenic acid（peak 1） and senkyunolide A（peak 8） as double standard compounds， the retention times of the eight characteristic peaks were predicted by linear calibration using two reference substances（LCTRS）， and the method was validated on three other columns of different brands. Taking chlorogenic acid as reference peak， the relative correction factor method（RCFM） was used to quantify cryptochlorogenic acid， caffeic acid， ferulic acid， senkyunolide I and senkyunolide A， and the results were compared with the external standard method（ESM）. ResultsThe similarities of specific chromatograms of 13 batches of CRdg were all >0.90， and a total of 8 characteristic peaks were calibrated， and six of them were identified， including chlorogenic acid（peak 1）， cryptochlorogenic acid（peak 2）， caffeic acid（peak 3）， ferulic acid（peak 5）， senkyunolide I（peak 6） and senkyunolide A（peak 8）. Through chemometric analysis， it was found that ferulic acid， chlorogenic acid， senkyunolide I and cryptochlorogenic acid were the main components causing quality difference in CRdg， and the accuracy of LCTRS in predicting the retention time of 8 characteristic peaks was superior to that of the relative retention time method（RRT）. Further comparison of the results obtained from RCFM and ESM showed that there was no statistically significant difference between the two methods. ConclusionA quality evaluation method for CRdg based on HPLC specific chromatogram and TRSDMC is established， its qualitative accuracy is better than that of RRT， the quantitative accuracy is similar to that of ESM， and 4 quality-differentiated components among different manufacturers are found. This method is stable and reliable， and has reference value for the quality evaluation of other dispensing granules.

ObjectiveTo establish the specific chromatogram of Chuanxiong Rhizoma dispensing granules（CRdg）， and to evaluate its quality by chemometrics and two reference substances for determination of multiple components（TRSDMC）. MethodsHigh performance liquid chromatography（HPLC） specific chromatograms were established using 13 batches of CRdg from 7 manufacturers， and preliminary quality evaluation was performed by similarity evaluation and chemometrics analysis. Eight characteristic peaks in the specific chromatogram of CRdg were measured on 22 different types of C₁₈ columns， and the actual retention times were recorded. Taking chlorogenic acid（peak 1） and senkyunolide A（peak 8） as double standard compounds， the retention times of the eight characteristic peaks were predicted by linear calibration using two reference substances（LCTRS）， and the method was validated on three other columns of different brands. Taking chlorogenic acid as reference peak， the relative correction factor method（RCFM） was used to quantify cryptochlorogenic acid， caffeic acid， ferulic acid， senkyunolide I and senkyunolide A， and the results were compared with the external standard method（ESM）. ResultsThe similarities of specific chromatograms of 13 batches of CRdg were all >0.90， and a total of 8 characteristic peaks were calibrated， and six of them were identified， including chlorogenic acid（peak 1）， cryptochlorogenic acid（peak 2）， caffeic acid（peak 3）， ferulic acid（peak 5）， senkyunolide I（peak 6） and senkyunolide A（peak 8）. Through chemometric analysis， it was found that ferulic acid， chlorogenic acid， senkyunolide I and cryptochlorogenic acid were the main components causing quality difference in CRdg， and the accuracy of LCTRS in predicting the retention time of 8 characteristic peaks was superior to that of the relative retention time method（RRT）. Further comparison of the results obtained from RCFM and ESM showed that there was no statistically significant difference between the two methods. ConclusionA quality evaluation method for CRdg based on HPLC specific chromatogram and TRSDMC is established， its qualitative accuracy is better than that of RRT， the quantitative accuracy is similar to that of ESM， and 4 quality-differentiated components among different manufacturers are found. This method is stable and reliable， and has reference value for the quality evaluation of other dispensing granules.

Kidney-Yang deficiency syndrome is a common geriatric disease that underlies chronic conditions such as diabetic nephropathy, chronic kidney disease, and osteoporosis. As age progresses, the kidney-Yang deficiency syndrome showcases increasingly pronounced manifestations, emerging as a key factor in the comorbidities experienced by elderly patients and affecting their quality of life and overall health status. Traditional Chinese medicine(TCM) has been extensively utilized in the treatment of kidney-Yang deficiency syndrome, with Epimedii Folium, Cinnamomi Cortex, and Lycii Fructus widely used in clinical settings. Despite the complexity of the molecular mechanisms involved in treating kidney-Yang deficiency syndrome, the potential therapeutic value of TCM remains compelling. Delving into the mechanisms of TCM treatment of kidney-Yang deficiency syndrome by regulating the neuro-endocrine-immune system can provide a scientific basis for targeted treatments of this syndrome and lay a foundation for the modernization of TCM. The pathophysiology of kidney-Yang deficiency syndrome involves multiple systems, including the interaction of the neuro-endocrine-immune system, the decline in renal function, the intensification of oxidative stress responses, and energy metabolism disorders. Understanding these mechanisms and their interrelationships can help untangle the etiology of kidney-Yang deficiency syndrome, aiding clinicians in making more precise diagnoses and treatments. Furthermore, the research on the specific applications of TCM in research on these pathological mechanisms can enhance the international recognition and status of TCM, enabling it to exert a greater global influence.
Humans ; Yang Deficiency/physiopathology* ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Kidney Diseases/physiopathology* ; Neurosecretory Systems/physiopathology* ; Animals ; Kidney/physiopathology* ; Endocrine System/physiopathology* ; Immune System/physiopathology*

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

This study primarily aimed to investigate the prevalence of human papillomavirus (HPV) and other common pathogens of sexually transmitted infections (STIs) in spermatozoa of infertile men and their effects on semen parameters. These pathogens included Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae, Pseudomonas aeruginosa , and Staphylococcus aureus . A total of 1951 men of infertile couples were recruited between 23 March 2023, and 17 May 2023, at the Department of Reproductive Medicine of The First People's Hospital of Yunnan Province (Kunming, China). Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping. Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs. The overall prevalence of HPV infection was 12.4%. The top five prevalent HPV subtypes were types 56, 52, 43, 16, and 53 among those tested positive for HPV. Other common infections with high prevalence rates were Ureaplasma urealyticum (28.3%), Ureaplasma parvum (20.4%), and Enterococcus faecalis (9.5%). The prevalence rates of HPV coinfection with Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae , and Staphylococcus aureus were 24.8%, 25.4%, 10.6%, 6.4%, 2.4%, 7.9%, 5.9%, 0.9%, and 1.3%, respectively. The semen volume and total sperm count were greatly decreased by HPV infection alone. Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability. Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters, emphasizing the necessity of semen screening for STIs.
Humans ; Male ; Infertility, Male/epidemiology* ; Coinfection/microbiology* ; Papillomavirus Infections/virology* ; Adult ; Sexually Transmitted Diseases/complications* ; China/epidemiology* ; Staphylococcus aureus/isolation & purification* ; Chlamydia trachomatis/isolation & purification* ; Prevalence ; Mycoplasma genitalium/isolation & purification* ; Ureaplasma urealyticum/isolation & purification* ; Neisseria gonorrhoeae/isolation & purification* ; Enterococcus faecalis/isolation & purification* ; Streptococcus agalactiae/isolation & purification* ; Herpesvirus 2, Human/genetics* ; Pseudomonas aeruginosa/isolation & purification* ; Semen/virology* ; Sperm Motility ; Spermatozoa/microbiology* ; Human Papillomavirus Viruses

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surgical intervention remains the primary treatment option for early-stage lung cancer, and video-assisted thoracoscopic surgery (VATS) has become a common approach due to its minimal invasiveness and rapid recovery. However, post-discharge recovery remains incomplete, underscoring the importance of postoperative care. Traditional follow-up methods, lack standardization, consume significant medical resources, and increase the burden of the patients. Artificial intelligence (AI)-driven disease management platforms offer a novel solution to optimize postoperative follow-up. This study followed 463 lung cancer surgery patients using an AI-based platform, aiming to identify common postoperative issues, propose solutions, improve quality of life, reduce recurrence-related costs, and promote AI integration in healthcare. METHODS: Using the AI disease management platform, this study integrated educational videos, collaboration between healthcare teams and AI assistants, daily health logs, health assessment forms, and personalized interventions to monitor postoperative recovery. The postoperative rehabilitation status of the patients was assessed by the Leicester Cough Questionnaire (LCQ-MC). Two independent t-test and one-way ANOVA were used to analyze the causes of postoperative cough in lung cancer. RESULTS: Most issues occurred within 7 d post-discharge, significantly declined on 14 d post-discharge. Factors such as gender, smoking history, and surgical approaches were found to influence cough recovery. The incidence of cough on 7 d post-discharge in females was higher than that in males (P<0.01), while the incidence of cough on 14 d post-discharge in elderly patients was lower than that in young patients (P=0.03). The AI-based platform effectively addressed cough, pain, and sleep disturbances through phased interventions. CONCLUSIONS The AI-based platform significantly enhanced postoperative management efficiency and the self-care capabilities of the patients, particularly in phased cough management. Future integration with wearable devices could enable more precise and personalized postoperative care, further advancing the application of AI technology across multidisciplinary healthcare domains.
Humans ; Lung Neoplasms/rehabilitation* ; Male ; Female ; Middle Aged ; Aged ; Patient Discharge ; Artificial Intelligence ; Adult ; Postoperative Care ; Postoperative Period ; Disease Management ; Quality of Life

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.