ObjectiveTo explore the clinical efficacy and mechanism of Bupi Qingfei prescription （BPQF） in treating stable bronchiectasis in the patients with syndromes of lung-spleen Qi deficiency and phlegm-heat accumulation in the lungs. MethodsA randomized， double-blind， placebo-controlled trial was conducted. Patients were randomized into BPQF and placebo control （PC） groups. On the basis of conventional Western medicine treatment， the BPQF granules and placebo were respectively administered at 10 g each time， twice a day， for a course of 24 weeks. The TCM symptom scores， Quality of Life Questionnaire for Bronchiectasis （QOL-B） scores， lung function indicators， T lymphocyte subsets， level of inflammatory factors in the sputum， level of neutrophil elastase （NE） in the sputum， and occurrence of adverse reactions were observed before and after treatment in the two groups. ResultsA total of 64 patients completed the study， encompassing 32 in the BPQF group and 32 in the PC group. After treatment， the BPQF group showed decreased TCM symptom scores （P<0.01）， increased QOL-B scores （P<0.01）， and declined levels of tumor necrosis factor （TNF）-α and NE （P<0.05， P<0.01）. The PC group showed decreased TCM symptom （except spleen deficiency） scores （P<0.01）， increased the QOL-B health cognition and respiratory symptom domain scores （P<0.05， P<0.01）， and a declined TNF-α level （P<0.01）. Moreover， the BPQF group had lower TCM symptom （except chest tightness） scores （P<0.05， P<0.01）， higher QOL-B （except treatment burden） scores （P<0.05， P<0.01）， and lower levels of interleukin-6 and TNF-α （P<0.05） than the PC group. Neither group showed serious adverse reactions during the treatment process. ConclusionBPQF can ameliorate the clinical symptoms of stable bronchiectasis patients who have lung-spleen Qi deficiency or phlegm-heat accumulation in the lungs by regulating the immune balance and inhibiting airway inflammatory responses.

The sixth edition of the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) was published in 2025. This review compared KMAP-DD 2025 with four major international clinical practice guidelines: Canadian Network for Mood and Anxiety Treatments Clinical Guidelines for the Management of Major Depressive Disorders, National Institute for Health and Care Excellence Depression Guideline, Royal Australian and New Zealand College of Psychiatrists Clinical Practice Guidelines for Mood Disorders, and British Association for Psychopharmacology Guideline. While KMAP-DD is based on expert consensus, and others on evidence-based methods, overall treatment strategies for depressive episodes were fairly consistent. Especially, KMAP-DD 2025 offers more structured recommendations in areas lacking strong evidence, such as premenstrual dysphoric disorder, perinatal depression, and depression with medical comorbidities. KMAP-DD 2025 also reflected Korean clinical practice patterns emphasizing rapid symptom relief and early use of combination strategies. Despite limitations as a consensus-based guideline, KMAP-DD 2025 complements evidence-based approaches and provides practical, situation-specific guidance for real-world clinical decision-making in Korea.

Objective To explore the effect of mangiferin(MF)on pyroptosis in an amyotrophic lateral sclerosis(ALS)cell model by regulating the nuclear factor erythroid 2-related factor 2/heme oxygenase-1(Nrf2/HO-1)signaling pathway.Methods(1)Mouse NSC-34 cell lines transfected with hSOD1WT and hSOD1G93A plasmids were randomly divided into blank group,model group,MF(100 μmol/L)group,MF(200 μmol/L)group.MF was added into the culture plate for 24 hours.Cell viability was assessed using CCK-8 kit.Lactate dehydrogenase(LDH)release was measured using LDH cytotoxicity detection kit.Levels of inflammatory factors interleukin(IL)-1β and IL-18 in cell supernatant were determined by enzyme-linked immunosorbent assay(ELISA).The expression of Nrf2,HO-1,NADPH quinone oxidoreductase-1(NQO-1),NOD-like receptor protein 3(NLRP3),gasdermin D(GSDMD)-N and caspase-1 was detected by Western blotting.(2)Mouse hSOD1G93A NSC-34 cells were randomly divided into model group,MF(200 μmol/L)group,Nrf2-siRNA group and Nrf2-siRNA+MF(200 μmol/L)group.The cells were transiently transfected with Nrf2-siRNA using LipofectamineTM 3000.Western blotting was used to detect the protein expression levels of Nrf2,HO-1,NQO-1,NLRP3,caspase-1 and GSDMD-N.Results(1)The results of the CCK-8 assay showed that after the hSOD1G93A NSC-34 cells were treated with MF at concentrations of 300 μmol/L and below for 24 hours,the changes in cell viability were not significant(P>0.05).Compared with blank group,the release of LDH,the contents of IL-1β and IL-18 in the cell culture supernatant of model group were increased(P<0.001);the protein expression levels of Nrf2,HO-1,and NQO-1 were decreased(P<0.05 or P<0.01);the protein expression levels of NLRP3,caspase-1,and GSDMD-N were increased(P<0.05 or P<0.01 or P<0.001).Compared with model group,the release of LDH,the contents of IL-18 and IL-1β in the culture supernatant in MF(100 μmol/L)and MF(200 μmol/L)groups were decreased(P<0.001);the protein expression levels of NLRP3,caspase-1 and GSDMD-N were decreased(P<0.05 or P<0.001),and the expression levels of Nrf2,HO-1 and NQO-1 were increased(P<0.05 or P<0.01).(2)Compared with model group,the protein expession levels of Nrf2,NO-1 and NQO-1 were increased(P<0.05 or P<0.001)in MF(200 μmol/L)group,while the protein expression levels of NLRP3,caspase-1 and GSDMD-N were decreased(P<0.001);the protein expression levels of Nrf2 and HO-1 were decreased in Nrf2-siRNA group(P<0.01 or P<0.001),while the protein expression levels of NLRP3,caspase-1 and GSDMD-N were increased(P<0.001).Compared with Nrf2-siRNA group,the protein expression levels of Nrf2,HO-1 and NQO-1 in Nrf2-siRNA+MF(200 μmol/L)group were increased(P<0.01 or P<0.001),and the protein expression levels of NLRP3,caspase-1 and GSDMD-N were decreased(P<0.001).Conclusion MF can inhibit pyroptosis in the ALS cell model through Nrf2/HO-1 signaling pathway,playing a protective role.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Microplastics are widely present in various environments such as water bodies,land,and atmosphere,which pose threats to the ecological environment and human health through transmission and accumulation in the food chain.The existing detection techniques for microplastics face challenges such as complex preparation procedure of samples,low efficiency in processing large batches of samples,and difficulties in handling complex samples.Therefore,there is an urgent need for rapid and efficient detection techniques suitable for complex microplastics samples in the field of environmental monitoring.Raman spectroscopy,known for its advantages such as rapidity,accuracy,high sensitivity,non-destructiveness,and non-contact,demonstrates great application potential in detection of microplastics.Deep learning,an artificial intelligence method known for its large-scale data processing,nonlinear modeling and automatic feature extraction capabilities,is receiving increasing attention in the analysis of Raman spectroscopy signals.The application of deep learning-based Raman spectroscopy has significantly improved performance indicators such as detection efficiency and accuracy.This article introduced the existing Raman enhancement techniques,summarized the deep learning methods applied in Raman spectroscopy signal analysis,reviewed the recent research and application progress of deep learning-based Raman spectroscopy in detection of microplastics,and finally discussed the challenges and future prospects of deep learning-based Raman spectroscopy in detection of microplastics.

The single photon counting imaging detector based on microchannel plate(MCP)has the characteristics of high sensitivity and low dark count rate,and has been applied to the optical remote sensing detection of weak ultraviolet spectral signals in space.In this work,by using planar array single photon counting imaging detector as the detector,flat-field concave grating as the splitter,and electrodeless discharge lamp(EDL)as the excitation light source,a dispersion detection system suitable for hydride generation-atomic fluorescence spectrometry(HG-AFS)was developed.The wavelength calibration of the system was carried out,and the negative high pressure and EDL stability time of the planar array single photon counting imaging detector were analyzed and optimized.The characteristic emission spectral lines of As and Bi elements excited in the wavelength range of 180-320 nm were analyzed,and the scattering interference in the wavelength range of 257.3-306.7 nm was discussed.The results showed that the AFS dispersion detection system based on the planar array single photon counting imaging detector could detect and analyze the HG-AFS fluorescence signal initially,and the influence of scattering interference on the detection results was effectively avoided.The system had the advantages including simple structure,no refrigeration and temperature control,no moving parts and simultaneous measurement of multi-band.

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

PURPOSE: To analyze risk factors for severe trauma and establish a nomogram for early risk prediction, to improve the early identification of severe trauma. METHODS: This study was conducted on the patients treated in 81 trauma treatment institutions in Gansu province from 2020 to 2022. Patients were grouped by year, with 5364 patients from 2020 to 2021 as the training set and 1094 newly admitted patients in 2020 as the external validation set. Based on the injury severity score (ISS), patients in the training set were classified into 2 subgroups of the severe trauma group (n = 478, ISS scores ≥25) and the non-severe trauma group (n = 4886, ISS scores <25). Univariate and binary logistic regression analyses were employed to identify independent risk factors for severe trauma. Subsequently, a predictive model was developed using the R software environment. Furthermore, the model was subjected to internal and external validation via the Hosmer-Lemeshow test and receiver operating characteristic curve analysis. RESULTS: In total, 6458 trauma patients were included in this study. Initially, this study identified several independent risk factors for severe trauma, including multiple traumatic injuries (polytrauma), external hemorrhage, elevated shock index, elevated respiratory rate, decreased peripheral oxygen saturation, and decreased Glasgow coma scale score (all p < 0.05). For internal validation, the area under the receiver operating characteristic curve was 0.914, with the sensitivity and specificity of 88.4% and 87.6%, respectively; while for external validation, the area under the receiver operating characteristic curve was 0.936, with the sensitivity and specificity of 84.6% and 93.7%, respectively. In addition, a good model fitting was observed through the Hosmer-Lemeshow test and calibration curve analysis (p > 0.05). CONCLUSION This study establishes a nomogram for early risk prediction of severe trauma, which is suitable for primary healthcare institutions in underdeveloped western China. It facilitates early triage and quantitative assessment of trauma severity by clinicians prior to clinical interventions.
Humans ; Nomograms ; Male ; Female ; Wounds and Injuries/diagnosis* ; Risk Factors ; Middle Aged ; Adult ; Injury Severity Score ; Risk Assessment ; ROC Curve ; Aged ; Logistic Models ; China ; Glasgow Coma Scale