OBJECTIVE To investigate the risk factors for sodium valproate （VPA）-induced hyperammonemia in neurocritical patients， and to construct a risk prediction model. METHODS Clinical data were retrospectively collected from 172 neurocritical patients who received VPA treatment in the Department of Critical Care Medicine， the Fourth Affiliated Hospital of Soochow University from January 2022 to June 2025. Patients were divided into the hyperammonemia group （73 cases） and the normal group （99 cases） based on their blood ammonia levels. Univariate analysis and LASSO regression analysis were used to screen for predictive variables. Independent factors were identified through multivariate Logistic regression analysis， and a nomogram was constructed accordingly. The performance of the model was evaluated using receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis （DCA）. RESULTS Combination of univariate analysis and LASSO regression analysis screened out seven predictive variables： body mass index （BMI）≥24.0 kg/m 2 ， concomitant use of benzodiazepines， VPA blood concentration， hemoglobin， serum urea， average daily VPA dose， and albumin. Multivariate Logistic regression analysis showed that concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， VPA blood concentration， albumin and serum urea level （with odds ratios of 1.615， 1.538， 1.623， 1.942 and 0.637， respectively； 95% confidence intervals of 1.128-2.359， 1.059-2.251， 1.112-2.431， 1.106-3.598 and 0.402-0.980， respectively） were all significantly associated with VPA-induced hyperammonemia in neurocritical patients （ P ＜0.05）. The nomogram prediction model constructed based on these variables was evaluated， showing that the area under the ROC curve was 0.810 for the test set and 0.844 for the validation set. The calibration curves closely approximated t he actual curves， and the application of this model could improve the clinical net benefit. CONCLUSIONS Concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， high VPA blood concentration and high albumin level are independent risk factors for VPA-induced hyperammonemia in neurocritical patients， while high serum urea level is an independent protective factor. The risk prediction model constructed based on these factors exhibits good discrimination， consistency， and clinical applicability， making it applicable for predicting the risk of VPA-induced hyperammonemia in neurocritical patients.

Postoperative cognitive dysfunction (POCD) is a clinically significant complication in elderly patients, largely driven by surgery-induced neuroinflammation. The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway, a crucial regulator of innate immunity, has been implicated in neuroinflammatory activation. This study investigated whether electroacupuncture (EA) improves POCD by modulating this pathway in aged rats. Aged male Sprague-Dawley rats were subjected to sevoflurane anesthesia and splenectomy to establish a POCD model. Animals were divided into sham, POCD, POCD+EA, and POCD+EA+cGAS inhibitor groups. The EA groups received stimulation at Baihui (Governor Vessel 20 (GV20)), Neiguan (Pericardium 6 (PC6)), and Zusanli (Stomach 36 (ST36)) acupoints. Cognitive function was evaluated using the Morris water maze, while hippocampal expression of cGAS-STING pathway components and downstream effectors—interferon regulatory factor 3 (IRF3), nuclear factor kappa B (NF-κB), and interleukin-1 beta (IL-1β)—was assessed by Western blot. Cellular localization was determined by immunofluorescence staining. Compared with the Sham group, rats in the POCD group showed significant impairments in spatial memory, accompanied by upregulated protein expression of cGAS, STING, NF-κB, IRF3, and IL-1β in the hippocampus. Upon pathway activation, cGAS and STING proteins were predominantly co-localized with neurons, and their fluorescence intensity in the hippocampus was markedly increased. These behavioral deficits and molecular alterations were partially reversed in both the POCD+EA and POCD+EA+inhibitor groups. Electroacupuncture alleviates POCD in aged rats by inhibiting hippocampal cGAS-STING pathway activation and reducing neuroinflammation, suggesting a promising non-pharmacological strategy for POCD management.

Objective To analyze the relationship between umbilical cord blood chemokines regulated upon activation normal T cell expressed and secreted(RANTES),C-X-C motif chemokine ligand 12(CXCL12),C-X-C motif chemokine receptor 4(CXCR4)and neonatal septicemia inflammatory response and outcome.Meth-ods A total of 242 children with neonatal septicemia admitted to a hospital from January 2020 to January 2024 were selected as the study subjects,and were divided into non-critical group(101 cases),critical group(79 cases)and extremely critical group(62 cases)according to neonatal critical case score.According to the prognosis,the subjects were divided into good prognosis group and bad prognosis group.The levels of RAN-TES,CXCL12,CXCR4 and inflammatory factors[C-reactive protein(CRP),interleukin-6,IL-1β]in umbilical cord blood of each group were detected.The correlation between RANTES,CXCL12,CXCR4 and inflammato-ry factors in umbilical cord blood of neonatal septicemia was analyzed by Pearson correlation,and the influen-cing factors of poor prognosis of neonatal septicemia were analyzed by multivariate Logistic regression.Re-ceiver operating characteristic(ROC)curve was drawn to analyze the value of umbilical cord blood RANTES,CXCL12 and CXCR4 in predicting the poor prognosis of neonatal septicemia.Results The levels of RAN-TES,CXCL12,CXCR4,CRP,IL-6 and IL-1β in umbilical cord blood of extremely critical group were higher than those of critical group and non-critical group,and the differences were statistically significant(P＜0.05).The levels of RANTES,CXCL12 and CXCR4 in umbilical cord blood of neonatal septicemia were posi-tively correlated with CRP,IL-6 and IL-1β(P＜0.05).Multivariate Logistic regression analysis showed that extremely severe,early-onset septicemia,high RANTES,high CXCL12 and high CXCR4 were risk factors for poor prognosis of neonatal septicemia(P＜0.05).ROC curve analysis results showed that the area under the curve(AUC)of umbilical cord blood RANTES,CXCL12 and CXCR4 in predicting poor prognosis of neonatal septicemia were 0.810,0.814 and 0.763,respectively,and the AUC of three indicators combined prediction was 0.914,which was higher than that of single prediction.Conclusion The increased levels of RANTES,CX-CL12 and CXCR4 in umbilical cord blood of neonatal septicemia are associated with inflammation,aggravation and poor prognosis,and the combination of RANTES,CXCL12 and CXCR4 can predict the risk of poor prog-nosis of neonatal septicemia.

Sigma-1 receptor (σ ₁R) has become a focus point of drug discovery for central nervous system (CNS) diseases. A series of novel 1-phenylethan-1-one O-(2-aminoethyl) oxime derivatives were synthesized. In vitro biological evaluation led to the identification of 1a, 14a, 15d and 16d as the most high-affinity (K _i < 4 nmol/L) and selective σ ₁R agonists. Among these, 15d, the most metabolically stable derivative exhibited high selectivity for σ ₁R in relation to σ ₂R and 52 other human targets. In addition to low CYP450 inhibition and induction, 15d also exhibited high brain permeability and excellent oral bioavailability. Importantly, 15d demonstrated effective antipsychotic potency, particularly for alleviating negative symptoms and improving cognitive impairment in experimental animal models, both of which are major challenges for schizophrenia treatment. Moreover, 15d produced no significant extrapyramidal symptoms, exhibiting superior pharmacological profiles in relation to current antipsychotic drugs. Mechanistically, 15d inhibited GSK3β and enhanced prefrontal BDNF expression and excitatory synaptic transmission in pyramidal neurons. Collectively, these in vivo proof-of-concept findings provide substantial experimental evidence to demonstrate that modulating σ ₁R represents a potential new therapeutic approach for schizophrenia. The novel chemical entity along with its favorable drug-like and pharmacological profile of 15d renders it a promising candidate for treating schizophrenia.

Image 1.

Objective:To analyze the effect of influenza vaccination on influenza cluster epidemic in primary and secondary schools in Beijing during the 2023-2024 surveillance season and provide evidence for the improvement of influenza vaccination strategies.Methods:The incidence data of influenza cluster epidemic and influenza vaccination coverage in the schools in Beijing during 2023-2024 were collected. Descriptive epidemiological methods were used to analyze cluster epidemic characteristics, and χ2 test was used to compare incidence differences between groups, and OR value and vaccine effectiveness [VE=(1- OR)×100%] were calculated. A negative binomial regression model was used to evaluate the association between school vaccination rates and cluster epidemic risk. Joinpoint regression was used to analyze trends in relative risk ( RR) with increasing vaccination coverage and to determine the optimal vaccination threshold. Results:A total of 126 influenza cluster epidemic were reported in 115 primary and secondary schools in Beijing during 2023-2024 with the median size of 15 case, the average attack rate was 36.26% (2 033/5 607). The epidemics mainly occurred in urban area (70, 55.56%). Primary schools were the main setting (78, 61.90%), and influenza A(H3N2) was the predominant subtype (108, 85.71%). The overall influenza vaccination coverage in the primary and secondary students was 54.26%, while the average vaccination in classes affected by the epidemics was 58.57%. The overall protection rate was 47.62%, the protection rate was higher in primary schools (49.65%) than in secondary schools (46.60%). The protection rates against influenza A(H1N1)pdm09 (80.93%) and influenza B (Victoria lineage) (81.65%) were significantly higher than that against influenza A(H3N2) (44.19%). When school vaccination coverage reached ≥76.00%, the epidemic risk decreased by 52.82%.Conclusions:Even the match between influenza vaccine strains and circulating strains is suboptimal, increasing influenza vaccination coverage in schools can effectively reduce the risk for influenza cluster epidemic. In the future, measures such as policy guidance and public health education should be taken to further improve vaccination coverage, thereby establishing herd immunity and reducing the transmission risk of influenza in schools.

Objective:To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing.Methods:The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing.Results:The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure ( r=0.482, P<0.001) and weekly average wind speed ( r=0.003, P=0.034), and negatively correlated with the weekly average temperature ( r=-0.541, P<0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error ( RMSE) of 0.115 3 and mean absolute error ( MAE) of 0.076 7 (the RMSE and MAE values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. Conclusions:Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.

ObjectiveTo explore the mechanism by which Buyang Huanwutang regulates the glutathione peroxidase 4 （GPX4）-acyl-CoA synthetase long-chain family member 4 （ACSL4） axis to inhibit ferroptosis and promote neurological functional recovery after spinal cord injury （SCI）. MethodsNinety rats were randomly divided into five groups： sham operation group， model group， low-dose Buyang Huanwutang group （12.5 g·kg^-1）， high-dose Buyang Huanwutang group （25 g·kg^-1）， and Buyang Huanwutang + inhibitor group （25 g·kg^-1 + 5 g·kg^-1 RSL3）. The SCI model was established by using the allen method. Tissue was collected on the 7th and 28th days after operation. Motor function was assessed by using the Basso-Beattie-Bresnahan （BBB） scale. Hematoxylin-eosin （HE）， Nissl， and Luxol fast blue （LFB） staining were performed to observe spinal cord histopathology. Transmission electron microscopy was used to examine mitochondrial ultrastructure. Immunofluorescence staining was used to detect the number of NeuN-positive cells and the fluorescence intensity of myelin basic protein （MBP）， GPX4， and ACSL4. Real-time fluorescent quantitative polymerase chain reaction （Real-time PCR） was used to analyze the mRNA expression of GPX4 and ACSL4. Enzyme linked immunosorbent assay （ELISA） was performed to measure the levels of reactive oxygen species （ROS）， malondialdehyde （MDA）， glutathione （GSH）， and superoxide dismutase （SOD）. Colorimetric assays were used to determine the iron content in spinal cord tissue. ResultsCompared to the sham operation group， the model group exhibited significantly reduced BBB scores （P<0.01）， severe pathological damage in spinal cord tissue， and marked mitochondrial ultrastructural disruption. In addition， the model group showed a decrease in the number of NeuN-positive cells （P<0.01）， reduced fluorescence intensity of MBP and GPX4 （P<0.01）， lower levels of GSH and SOD （P<0.01）， and downregulated mRNA expression of GPX4 （P<0.01）. Moreover， compared to the sham operation group， the model group had elevated levels of ROS， MDA， and tissue iron content （P<0.01）， along with increased fluorescence intensity and mRNA expression of ACSL4 （P<0.01）. Compared with the model group and Buyang Huanwutang + inhibitor group， the Buyang Huanwutang group showed significantly improved BBB scores （P<0.05， P<0.01） and exhibited less severe spinal cord tissue damage， reduced edema and inflammatory cell infiltration， increased neuronal survival， and more intact myelin structures. Additionally， mitochondrial ultrastructure was significantly improved in the Buyang Huanwutang group. Compared to the model group and Buyang Huanwutang + inhibitor group， the Buyang Huanwutang group significantly increased the number of NeuN-positive cells and the fluorescence intensity of MBP （P<0.05， P<0.01）. Furthermore， Buyang Huanwutang significantly increased the fluorescence intensity and mRNA expression of GPX4 （P<0.01） and decreased the fluorescence intensity and mRNA expression of ACSL4 （P<0.01） compared to the model group and Buyang Huanwutang + inhibitor group. Finally， the Buyang Huanwutang group significantly decreased ROS， MDA， and tissue iron content （P<0.01） and significantly increased GSH and SOD levels （P<0.01） compared to the model group and Buyang Huanwutang + inhibitor group. ConclusionBuyang Huanwutang inhibits ferroptosis through the GPX4/ACSL4 axis， reduces secondary neuronal and myelin injury and oxidative stress， and ultimately promotes the recovery of neurological function.

Objective:To analyze the effect of influenza vaccination on influenza cluster epidemic in primary and secondary schools in Beijing during the 2023-2024 surveillance season and provide evidence for the improvement of influenza vaccination strategies.Methods:The incidence data of influenza cluster epidemic and influenza vaccination coverage in the schools in Beijing during 2023-2024 were collected. Descriptive epidemiological methods were used to analyze cluster epidemic characteristics, and χ2 test was used to compare incidence differences between groups, and OR value and vaccine effectiveness [VE=(1- OR)×100%] were calculated. A negative binomial regression model was used to evaluate the association between school vaccination rates and cluster epidemic risk. Joinpoint regression was used to analyze trends in relative risk ( RR) with increasing vaccination coverage and to determine the optimal vaccination threshold. Results:A total of 126 influenza cluster epidemic were reported in 115 primary and secondary schools in Beijing during 2023-2024 with the median size of 15 case, the average attack rate was 36.26% (2 033/5 607). The epidemics mainly occurred in urban area (70, 55.56%). Primary schools were the main setting (78, 61.90%), and influenza A(H3N2) was the predominant subtype (108, 85.71%). The overall influenza vaccination coverage in the primary and secondary students was 54.26%, while the average vaccination in classes affected by the epidemics was 58.57%. The overall protection rate was 47.62%, the protection rate was higher in primary schools (49.65%) than in secondary schools (46.60%). The protection rates against influenza A(H1N1)pdm09 (80.93%) and influenza B (Victoria lineage) (81.65%) were significantly higher than that against influenza A(H3N2) (44.19%). When school vaccination coverage reached ≥76.00%, the epidemic risk decreased by 52.82%.Conclusions:Even the match between influenza vaccine strains and circulating strains is suboptimal, increasing influenza vaccination coverage in schools can effectively reduce the risk for influenza cluster epidemic. In the future, measures such as policy guidance and public health education should be taken to further improve vaccination coverage, thereby establishing herd immunity and reducing the transmission risk of influenza in schools.

Objective:To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing.Methods:The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing.Results:The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure ( r=0.482, P<0.001) and weekly average wind speed ( r=0.003, P=0.034), and negatively correlated with the weekly average temperature ( r=-0.541, P<0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error ( RMSE) of 0.115 3 and mean absolute error ( MAE) of 0.076 7 (the RMSE and MAE values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. Conclusions:Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.