OBJECTIVE To provide valuable insights for the adjustment of anti-infectious regimens， identification of adverse reactions， and individualized pharmaceutical care in patients with critically severe scrub typhus. METHODS Clinical pharmacists actively participated in the pharmaceutical care process for a patient with severe scrub typhus leading to mixed shock undergoing continuous renal replacement therapy and extracorporeal membrane oxygenation. Initially， the patient received meropenem （1 g， q12 h， ivdrip）， in combination with doxycycline （0.1 g， q12 h， po）， which was later switched to meropenem （1 g， q8 h， ivdrip） along with omacycline （100 mg， qd， ivdrip） due to impaired gastrointestinal function. However， as the patient’s condition progressively deteriorated and the infection became uncontrolled， the clinical pharmacists recommended that the clinicians adjust the anti-infective regimen to meropenem （2 g， q8 h， ivdrip） combined with tigecycline （100 mg for first dose； 50 mg， q12 h for maintenance； ivdrip）. The clinicians followed the advice of the clinical pharmacists. After treatment， the patient’s symptoms exhibited significant improvement， accompanied by a notable decrease in inflammatory markers， indicating that the infection had been successfully controlled. However， due to continuously increasing bilirubin levels， in order to reduce the risk of drug-induced liver injury， the clinicians changed tigecycline to azithromycin （0.5 g， qd， ivdrip） following the recommendation of the clinical pharmacists. RESULTS Ultimately， metagenomic next-generation sequencing of the bronchoalveolar lavage fluid and blood specimens indicated that Orientia tsutsugamushi had been completely eradicated in the patient. CONCLUSIONS Tigecycline may be a viable therapeutic choice for patients with severe scrub typhus. In the context of critically ill patients with scrub typhus， combining tigecycline with azithromycin might potentially enhance the efficacy in eliminating Orientia tsutsugamushi.

Objective:To investigate the risk factors associated with post-prematurity respiratory disease (PPRD) in very preterm infants.Methods:A prospective cohort study was conducted, enrolling 369 very preterm infants who were admitted to the neonatal intensive care unit of Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, within one week of birth from January 2019 to June 2023. Data on maternal and infant clinical characteristics, neonatal morbidities, and treatments during hospitalization were collected. The very preterm infants were divided into 2 groups based on whether they developed PPRD. Continuous variables were compared using Mann-Whitney U test, while categorical variables were compared using χ2 tests or continuity correction χ2 test. Multivariate Logistic regression analysis was used to identify the independent risk factors for PPRD in very preterm infants. Results:Among the 369 very preterm infants, 217 cases(58.8%) were male, with a gestational age of 30 (28, 31) weeks at birth and a birth weight of 1 320 (1 085, 1 590) g. Of these, 116 cases (31.4%) developed PPRD, while 253 cases (68.6%) did not. The very preterm infants in the PPRD group had a lower gestational age and lower birth weight (both, P<0.001). The PPRD group also had a higher proportion of males, lower Apgar scores at the 1 th minute after birth and the 5 th minutes after birth, a higher rate of born via cesarean delivery, and a higher incidence of bronchopulmonary dysplasia, more pulmonary surfactant treatment, longer durations of mechanical ventilation, longer total oxygen therapy, and lower Z-score for weight at discharge (all P<0.05). Multivariate Logistic regression analysis showed that gestational age ( OR=0.85, 95% CI 0.73-0.99, P=0.037), born via cesarean delivery ( OR=2.23, 95% CI 1.21-4.10, P=0.010), a duration of mechanical ventilation ≥7 days ( OR=2.51, 95% CI 1.43-4.39, P=0.001), and a Z-score for weight at discharge ( OR=0.82, 95% CI 0.67-0.99, P=0.040) were all independent risk factors for PPRD in very preterm infants. Conclusion:Very preterm infants with a small gestational age, born via cesarean section, mechanical ventilation ≥7 days, and a low Z-score for weight at discharge should be closely monitored for PPRD, and provided with standardized respiratory management after discharge.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

Objective To investigate the role of lncRNA SNHG1 in homocysteine-induced pyroptosis of podocyte.Methods Cbs+/-mice were randomly divided into two groups:a normal diet group(ND)and a high me-thionine diet group(HMD).Western blotting was used to detect the protein expression levels of Caspase-1,Cleaved Caspase-1,and NLRP3.Mouse renal glomerular podocytes were cultured in vitro,and then assigned into a control group(Control,0 μmol/L Hcy)and a homocysteine intervention group(Hcy,80 μmol/L Hcy).Western blotting was used to detect the protein expression levels of Caspase-1,Cleaved Caspase-1,and NLRP3.Mouse renal glomerular podocyion group(OE-NC + Hcy)and the lncSNHG1 overexpression + homocysteine intervention group(OE-SNHG1 + Hcy)were also established.After 48 hours of intervention,Real-time fluorescence quantita-tive PCR was used to detect the expression of lncSNHG1 in podocytes after Hcy intervention.Western blot was used to detect the expressions of Caspase-1,Cleaved Caspase-3 and NLRP3.Immunofluorescence was used to de-tect the expression levels of GSDMD and GSDMD-N.ELISA was used to detect the contents of IL-1β and IL-18.Results(1)In the animal experiments,the expression levels of pyroptosis-related proteins Caspase-1,Cleaved Caspase-1,NLRP3,GSDMD,and GSDMD-N were all increased in the HMD group compared with the ND group.(2)In the cellular experiments,the expression levels of Caspase-1,Cleaved Caspase-1,NLRP3,GSDMD,and GSDMD-N were all increased in the Hcy group compared with the Control group,and the contents of pyroptosis-mediated inflammatory factors IL-1β and IL-18 were increased as well.(3)In the cellular experiments,the expres-sion of lncSNHG1 was increased in the Hcy group compared with the control group.After transduction with lnc-SNHG1 lentivirus,the expression of lncSNHG1 was increased in the OE-SNHG1 group,compared with the control group and the OE-NC group.(4)In the cellular experiments,the expressions of pyroptosis-related proteins Cas-pase-1,Cleaved Caspase-1,NLRP3,GSDMD,and GSDMD-N were increased compared with the OE-NC+Hcy group,and the contents of pyroptosis-mediated inflammatory factors IL-1β and IL-18 were increased in the OE-SNHG1+Hcy group.Conclusion These results indicate that lncSNHG1 may play a role in promoting Hcy induced podocytepyroptosis.

Objective : To explore the effect of esketamine on anxiety-depressive-like behavior in mice and its rela- tionship with inflammation． Methods : SPF grade healthy adult male C57BL/6J mice，weighing 20 －24 g，were used in the exprement．The random number table method was used to divide into 5 groups (n = 8) : control group ( Con group) ，esketamine group (ESK group) ，model group ( LPS group) ，model + esketamine prevention group (LPS + ESK1 group) and model + esketamine treatment group ( LPS + ESK2 group) ．An inflammation-induced anxiety-depression model was prepared by intraperitoneal injection of LPS 0. 83 mg / kg．The ESK group was injec- ted with esketamine 10 mg / kg ; LPS group was injected with LPS 0. 83 mg / kg ; LPS + ESK1 group was injected with LPS 0. 83 mg / kg before 24 hours intraperitoneal injection of esketamine 10 mg / kg ; and the LPS + ESK2 group was injected with LPS 0. 83 mg / kg and 30 minutes later with esketamine 10 mg / kg．24 h after intraperitoneal injec- tion of LPS，the anxiety-depression-like behaviors of mice were measured using behavioral experiments．At the end of behavioral experiments，the spleen was taken immediately ; hippocampal tissues were taken and enzyme-linked immunosorbent assay (ELISA) was used to detect the contents of interleukin-1 β (IL-1 β) ，tumor necrosis factor al- pha (TNF-α) and interleukin 6 (IL-6) and neuronal pathological changes in hippocampal tissues were observed by HE staining. Results : Compared with the Con group，mice in the LPS group showed increased anxiety and depres- sion-like behavior (P＜0. 05) ，increased spleen weight / body weight (P ＜0. 05 ) ，increased hippocampal tissue concentrations of IL-1 β , TNF-α and IL-6 (P＜0. 05) ，and increased neuronal degeneration necrosis，there was no statistically significant difference in these indicators in the ESK group compared with the Con group．Compared with the LPS group，mice in the LPS + ESK1 and LPS + ESK2 groups showed reduced anxiety-depression-like behavior (P＜0. 05) ，decreased splenic weight / body weight (P ＜0. 05) ，hippocampal tissue IL-1 β , TNF-α , IL- 6 con- centrations were reduced (P＜0. 05) ，and neuronal degeneration necrosis was reduced．Compared with the LPS + ESK1 group，the LPS + ESK2 group showed an increase in the distance travelled in the central area of the open field experiment and the distance into the open arm of the elevated cross maze experiment (P＜0. 05) ，a decrease in IL-6 and TNF-α concentrations (P＜0. 05) ，and a reduction in the degree of neuronal damage． Conclusion Esketamine ameliorates LPS-induced anxiety-depression-like behavior and neuronal damage in mice by a mechanism that may be related to reduced inflammation.

Gorham-Stout disease(GSD)is a sporadic chronic disease characterized by progressive bone dissolution,absorption,and disappearance along with lymphatic vessel infiltration in bone-marrow cavities.Although the osteolytic mechanism of GSD has been widely studied,the cause of lymphatic hyperplasia in GSD is rarely investigated.In this study,by comparing the RNA expression profile of osteoclasts(OCs)with that of OC precursors(OCPs)by RNA sequencing,we identified a new factor,semaphorin 3A(Sema3A),which is an osteoprotective factor involved in the lymphatic expansion of GSD.Compared to OCPs,OCs enhanced the growth,migration,and tube formation of lymphatic endothelial cells(LECs),in which the expression of Sema3A is low compared to that in OCPs.In the presence of recombinant Sema3A,the growth,migration,and tube formation of LECs were inhibited,further confirming the inhibitory effect of Sema3A on LECs in vitro.Using an LEC-induced GSD mouse model,the effect of Sema3A was examined by injecting lentivirus-expressing Sema3A into the tibiae in vivo.We found that the overexpression of Sema3A in tibiae suppressed the expansion of LECs and alleviated bone loss,whereas the injection of lentivirus expressing Sema3A short hairpin RNA(shRNA)into the tibiae caused GSD-like phenotypes.Histological staining further demonstrated that OCs decreased and osteocalcin increased after Sema3A lentiviral treatment,compared with the control.Based on the above results,we propose that reduced Sema3A in OCs is one of the mechanisms contributing to the pathogeneses of GSD and that expressing Sema3A represents a new approach for the treatment of GSD.

OBJECTIVE: To investigate the expression and physiological significance of the ferroptosis marker 4-hydroxynonenal (4-HNE) in myofibroblasts induced by transforming growth factor-β1 (TGF-β1), providing theoretical evidence for its potential role in the diagnosis and treatment of fibrosis in systemic sclerosis (SSc). METHODS: Mouse embryonic fibroblasts (NIH3t3) were cultured and divided into two groups after 12 h of starvation: the control group (cultured in 1% serum-containing medium) and the TGF-β1 group (cultured in 10 μg/L TGF-β1 with 1% serum-containing medium). Cell morphology changes in both groups were observed under a microscope. To confirm successful establishment of the SSc cell model, fibrosis markers were analyzed using reverse transcription quantitative real-time PCR (RT-qPCR) and Western blot. Next, flow cytometry was employed to assess the intracellular levels of reactive oxygen species (ROS) in both groups. Finally, Western blot and immunofluorescence staining were used to measure the expression of 4-HNE in the TGF-β1-treated cells. RESULTS: Microscopic observations revealed that TGF-β1 treatment caused the NIH3t3 cells to transition from a typical spindle shape to a flat, polygonal shape with multiple protrusions, indicating fibroblast activation. The RT-qPCR and Western blot analyses showed that the expression of the fibrosis marker Vimentin was significantly upregulated in the TGF-β1 group compared with the control group (P < 0.01), confirming that TGF-β1 effectively promoted fibrosis-related gene and protein expression. Flow cytometry results indicated that TGF-β1 significantly elevated intracellular ROS levels, suggesting the induction of oxidative stress. Furthermore, both Western blot and immuno-fluorescence staining demonstrated a significant increase in 4-HNE expression in the TGF-β1-treated cells (immunofluorescence intensity P < 0.05). CONCLUSION TGF-β1 promotes fibroblast activation and fibrosis while inducing ROS production, leading to a marked increase in 4-HNE expression. Given the role of 4-HNE as a marker of lipid peroxidation and its elevated levels in the SSc cell model, this study suggests that 4-HNE could serve as a potential biomarker for fibrosis in SSc. The findings highlight the importance of investigating the mechanisms of 4-HNE in fibrosis and suggest that targeting this pathway could offer new therapeutic opportunities for treating SSc.
Animals ; Mice ; Scleroderma, Systemic/pathology* ; Aldehydes/pharmacology* ; Transforming Growth Factor beta1/metabolism* ; NIH 3T3 Cells ; Ferroptosis ; Reactive Oxygen Species/metabolism* ; Fibrosis ; Fibroblasts/metabolism* ; Biomarkers/metabolism* ; Myofibroblasts/metabolism*

OBJECTIVE To evaluate the safety and suitability of traditional Chinese medicine prescriptions generated by generative artificial intelligence （AIGC）， and to provide research ideas for empowering the traditional Chinese medicine industry with AIGC. METHODS Using the 2020 edition of Chinese Pharmacopoeia and the 5th edition of Traditional Chinese Medicine as corpus， GPT-4 and the real-time networking model developed based on GPT-4 （referred to as the “networking model”） were used for deep learning. The clinical cases included in the consensus of traditional Chinese medicine experts in recent years were extracted manually to regenerate prescriptions based on diagnosis using the GPT-4 model and networking model； traditional Chinese medicine experts conducted blind evaluation and scoring of GPT-4 generated prescriptions， networking model generated prescriptions， and expert consensus prescriptions. At the same time， Turing testing was used to evaluate whether the GPT-4 model and networking model had the same ability as human intelligence. RESULTS The average score of traditional Chinese medicine prescriptions generated by the GPT-4 model showed no statistically significant difference compared to manual prescriptions （P＞0.05）， while the average score of prescriptions generated by the networking model showed no statistically significant difference compared to traditional Chinese medicine prescriptions generated by the GPT-4 model （P＞0.05）. The proportion of model-generated prescriptions mistakenly judged as manual prescriptions in the Turing test was 51.11%. CONCLUSIONS The traditional Chinese medicine prescriptions generated by the GPT-4 model have reached a certain level of safety and suitability， and the GPT-4 model has passed the Turing test. The introduction of AIGC in the diagnosis and treatment process may provide technical support for the rational use of clinical traditional Chinese medicine.

Objective:To investigate the effects of 30% ethanol elution fraction of Artemisia absinthium extract with macroporous resin (AAEM-30%) on the dendritic cell (DC) and immunity of mice. Methods:AAEM-30% was obtained from the alcoholic extracts of A. absinthium by AB-8 macroporous resin, and its polysaccharide, flavonoid, and terpenoid contents were determined. The expressions of AAEM-30% on DC surface molecular cluster of differentiation (CD) 40, CD80 and CD86 were detected in vitro by flow cytometry, and the expressions of DC cytokines IL-6 and tumor necrosis factor-α (TNF-α) were detected by enzyme linked immunosorbent assay (ELISA). The effect of AAEM-30% on the immune function of ICR mice was measured in vivo with different doses (50 and 100 mg/kg) and different administration methods (subcutaneous injection, intraperitoneal injection, and gavage). Results:The contents of polysaccharides, flavonoids, and terpenoids in AAEM-30% were 24.30%, 22.50% and 28.19%, respectively. AAEM-30% significantly enhanced the expression of CD40, and CD86 and the secretion of IL-6 and TNF-α (all P<0.001). Compared with the control group, no statistically significant differences were found in the body mass of mice compared with the three administration methods (all P>0.05). The thymus index in the 50 and 100 mg/kg AAEM-30% intraperitoneal injection groups and the spleen index in the 50 mg/kg AAEM-30% gavage group were increased (all P<0.05). CD19 + cells increased in the 100 mg/kg AAEM-30% intraperitoneal injection group ( P<0.01) and in the 50 mg/kg AAEM-30% gavage group ( P<0.05). The CD11b + and CD11c + counts increased in the 100 mg/kg AAEM-30% gavage group ( P<0.05). The number of CD4 + and CD8 + T lymphocytes was increased by both gavage and intraperitoneal administration (all P<0.05). Conclusions:AAEM-30% can promote the maturation of DC and enhanced the immunity of mice without obvious side effects.