Background In 2021, chronic obstructive pulmonary disease (COPD) emerged as the forth leading cause of death in the world. However, the impact of air pollutants on COPD is still inconsistent across current studies. Objective To analyze the relationship between ambient sulfur dioxide (SO₂) exposure and hospital admissions for COPD in Lanzhou, and to examine the modified effects of SO₂ across different genders, age groups, and seasons. Methods A total of 20718 hospital admission records for COPD were collected from Lanzhou between 2016 and 2020, alongside synchronized data on SO₂ concentration and meteorological variables. A generalized additive model integrated with a distributed lag nonlinear model was used to assess the relationship and the lag effects between SO₂ exposure and COPD admissions. Potential confounders, including meteorological factors, day-of-the-week effect, and holidays, were controlled for, with a maximum lag period set at 7 d. Two-pollutant models and sensitivity analyses were conducted to ensure robustness. Results are expressed as relative risks (RR) with 95% confidence intervals (95%CI). Results During the study period, the average daily number of COPD admissions was 11.34±7.03. The average mass concentration of SO₂ was (23.72±12.35) μg·m⁻³. SO₂ exposure was positively correlated with COPD admissions; specifically, each 10 μg·m⁻³ increase in SO₂ concentration was associated with an RR of 1.440 (95%CI: 1.317, 1.573). Stratified analyses found that at a cumulative lag of 7 d, the RRs were higher among females, individuals aged ≥65 years, and during the cold season. Conversely, no significant increase in COPD admission risk related to SO₂ was observed during the warm season. For every 10 μg·m⁻³ increase in SO₂ concentration, the RR was 1.483 (95%CI: 1.311, 1.678) for females, 1.441 (95%CI: 1.311, 1.583) for those aged > 65 years， and 1.595 (95%CI: 1.313, 1.937) during the cold season. Conclusion Short-term exposure to ambient SO₂ exposure in Lanzhou is associated with an increased risk of COPD admission. The association is more pronounced among females, the elderly (aged> 65 years) and during the cold season.

Diarrhea-predominant irritable bowel syndrome （IBS-D） exhibits typical characteristics of psychosomatic comorbidity. Its core pathogenesis is considered to involve simultaneous disorders of both the body and the spirit， for which the former is attributed to liver constraint and spleen deficiency， and dysfunction of large intestine conduction， whereas the latter is induced by spirit restlessness of zang （脏） organs， and gate insecurity of the corporeal soul. Based on this understanding， the therapeutic principle of "simultaneous regulation of body and spirit" is established. For regulating the body， the methods include soothing the liver， fortifying the spleen， consolidating the intestines， and stopping diarrhea， with emphasis on the front-mu （募） points of the related zang-fu （脏腑） organs and acupoints of the foot yangming （阳明） stomach channel and foot taiyin （太阴） spleen channel. For regulating the spirit， the methods include calming the brain spirit， tranquilizing the zang organs spirit， and securing the corporeal soul gate， mainly selecting acupoints of Governer Vessel （督脉） and the back-shu （背俞） points of the corresponding zang-fu organs. Needle manipulation techniques for supplementation and drainage are flexibly applied according to the deficiency or excess nature of the syndrome. In addition， comprehensive application of moxibustion， electroacupuncture， and auricular therapy is emphasized， with the aim of providing clinical insights for diagnosis and treatment.

Processed electroencephalogram (EEG) indices, such as the Bispectral Index, have markedly influenced anesthesia practice as they translate brain activity into simple numerical indices. Nevertheless, as the manufacturing algorithms are not disclosed, the underlying neurophysiology remains obscured. Additionally, these indices are often affected by electromyographic contamination, pharmacological variability, and patient-specific EEG heterogeneity. In contrast, an EEG spectrogram, or density spectral array, preserves the frequency- and time-resolved structures of cortical oscillations. This information is presented in a form that is both physiologically meaningful and clinically interpretable. In this review, we trace the evolution of anesthesia from an index-based to a spectrogram-guided approach, and summarize the clinical rationale for adopting the latter. Key applications of this approach include the use of frontal alpha power as a biomarker of cortical stability and postoperative brain health, the identification of nociceptive arousal through alpha dropout and beta or delta arousal patterns, and individualized titration of multimodal or age-specific anesthetic management. Although current devices lack standardized quantitative alpha metrics and have limited sensitivity for low-frequency brain wave components, structured EEG education programs have proven to be effective in terms of fostering spectrogram literacy among anesthesiologists. By combining neurophysiological precision with bedside practicality, the EEG spectrogram represents a pivotal advance toward individualized, mechanism-based, and brain-protective anesthesia, transforming anesthetic monitoring from mere algorithmic abstraction to cortical insight.

Background Diarrhea disease is a common intestinal infectious disease, and its incidence is affected by meteorological conditions. A better understanding of its epidemiological patterns and influencing factors, together with the construction of reliable prediction models, is of great significance for precise public health prevention and control. Objective To clarify the epidemic characteristics of adult diarrhea disease in Shanghai, analyze the associations of meteorological factors and a web search index with adult diarrhea disease, and develop and compare forecasting models to support precise regional prevention and control. Methods Weekly surveillance data of adult diarrhea disease cases from the Shanghai Comprehensive Surveillance Information System for Diarrhea Diseases, together with concurrent meteorological observation data and web search index (Baidu index) data from 2014 to 2019, were collected. A distributed lag non-linear model (DLNM) was adopted to analyze the associations of multiple meteorological factors and the web search index with the number of diarrhea disease cases. By integrating meteorological factors and web search index data, three types of forecasting models were developed, including autoregressive integrated moving average (ARIMA), Random Forest, and extreme gradient boosting (Xgboost), and their predictive performances were evaluated. Results Adult diarrhea disease in Shanghai exhibited seasonal variation, with an major incidence peak in summer and winter peaks in some years. The number of cases declined annually after 2015. Mean temperature was significantly associated with the risk of diarrhea disease, and both low and high temperature exposures were associated with increased risks. The highest risk was observed at 32.8°C (RR=2.04, 95%CI: 1.62, 2.55), while the strongest effect of low temperature was observed at 0.9 °C (RR=1.53, 95%CI: 1.25, 1.88). When relative humidity exceeded 69%, the risk of diarrhea disease increased with relative humidity, reaching a peak at 81% (RR=1.20, 95%CI: 1.07, 1.35). When weekly cumulative precipitation exceeded 16 mm, the risk also increased with increasing precipitation, reaching a maximum at 105 mm (RR=1.23, 95%CI: 1.07, 1.42). The web search index was positively associated with the risk of diarrhea disease. Model prediction indicated that both the Random Forest model and the Xgboost model adequately captured the overall trend in diarrhea disease cases, with R² values generally exceeding 0.7. Notably, the Xgboost model demonstrated greater accuracy in capturing peak intensities. Conclusion Meteorological factors are associated with adult diarrhea disease in Shanghai. The web search index may serve as an auxiliary indicator for diarrhea forecasting. Machine learning models, with advantages in integrating multisource data, may provide effective predictive tools for the prevention and control of diarrhea disease.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective To observe the functional connectivity and glucose metabolism of insular subregions in behavior variant of frontotemporal dementia(bvFTD)patients,also their correlations with cognitive function.Methods Thirty-eight bvFTD patients(bvFTD group)and 44 healthy individuals(control group)were retrospectively enrolled.The average time series signals of insular subregions were extracted as seed points based on functional MRI(fMRI)and 18F-FDG PET,then whole brain functional connectivity map was obtained.Meanwhile,the pons was selected as the reference brain region,and the standard uptake value ratio(SUVR)of insular subregions were calculated.The above parameters were compared between groups,and the correlations of SUVR of insular subregions with clinical cognitive function scale scores in bvFTD group were analyzed.Results Compared with control group,the functional connections between all insular subregions and bilateral frontal lobe,temporal lobe,anterior cingulate gyrus,anterior cingulate gyrus and middle cingulate gyrus,as well as between some subregions and bilateral parietal and occipital lobes were weakened in bvFTD group(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05).SUVR of all insular subregions significantly decreased(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05),which in right ventral agranular insula(vIa),dorsal agranular insula(dIa),dorsal dysgranular insula(dId)and left dorsal agranular insula(dIa)were negatively correlated with frontal behavioral inventory(FBI)score in bvFTD group(r=-0.452--0.330,all P＜0.05).Conclusion In bvFTD patients,the functional connectivity and glucose metabolism of insular subregions changed,and SUVR of right vIa,dIa,dId and left dIa were negatively correlated with FBI score.

Eimeria labbeana is a major pathogen of pigeon coccidiosis,causing damage to the intes-tinal epithelial cells of pigeons,which leads to gut injury,diarrhea,decreased production perform-ance,and even death.There have been no research on the pathogen characteristics of isolated strains in China.In this study,1 008 fecal samples were collected from nine cities in Zhejiang Prov-ince,including Hangzhou,Ningbo,Wenzhou,Shaoxing,Huzhou,Jinhua,Quzhou,Taizhou and Lishui.The samples were examined using the McMaster counting method to quantify oocysts per gram of feces,and coccidia species in positive samples were identified through microscopy.Patho-gens were isolated and purified with methods of single oocyst pickout under the microscopy and passage in coccidia-free pigeon,followed by a detailed study of their characteristics.Our findings demonstrated an overall infection rate of 55.8％(562/1 008)for pigeon coccidia in the surveyed ar-eas,with E.labbeana present across all farms.A strain of E.labbeana isolated from Zhejiang was successfully obtained and designated E.labbeana-ZJ.PCR identification and sequence alignment showed that this Zhejiang isolate shared a 99.67％similarity in the 18S rRNA gene sequence with the Australian strain(KT305927.1)and clustered into a small subgroup.Pathogenicity and oocyst shedding patterns were assessed through animal infection experiments,revealing a 4 days latent period,with peak infection occurring on the 8th day.Following infection,notable clinical symptoms emerged,with significant intestinal damage,and changes in body weight,indicating moderate path-ogenicity.The results enriched the epidemiological survey data of pigeon coccidiosis in China,and provide a new basis for further research and effective control measures against pigeon coccidiosis.

Four cases of typical faults of Siemens MOBILETT XP Digital bedside DR were introduced.The causes for the problems were analyzed,and some countermeasures were put forward accordingly.References were provided for medical engineers to treat similar faults.[Chinese Medical Equipment Journal,2025,46(3):118-120]

Objective:To observe the efficacy of plasma beam combined with intense pulsed light on facial burn scars and its impact on scar score and pain level.Method:This study was a prospective study,and a random number table method was used to divided 92 patients with facial burn scars who were admitted to Maoming People's Hospital from March 2024 to August 2024 into control group(received intense pulsed light treatment,46 cases)and study group(received plasma beam treatment in addition to the control group,46 cases).The efficacy,related scale scores,scar recovery and incidence of adverse reaction rates between two groups were compaerd.Result:Compared with control group after treatment,the clinical total effective rate and the chinese version of the simplified burn health scale(BSHS-B)score of the study group were higher,while vancouver scar scale(VSS),visual analogue scale(VAS)scores,scar thickness,and scar blood flow perfusion were lower(P＜0.05).There was no significant difference in the incidence of adverse reaction rates between the two groups(P＞0.05).Conclusion:Plasma beam combined with intense pulsed light on facial burn scars,can improve clinical efficacy,improve scar thickness and blood flow perfusion,alleviate scar itching and pain,and has good safety in treating facial burn scar patients.

Objective To observe the functional connectivity and glucose metabolism of insular subregions in behavior variant of frontotemporal dementia(bvFTD)patients,also their correlations with cognitive function.Methods Thirty-eight bvFTD patients(bvFTD group)and 44 healthy individuals(control group)were retrospectively enrolled.The average time series signals of insular subregions were extracted as seed points based on functional MRI(fMRI)and 18F-FDG PET,then whole brain functional connectivity map was obtained.Meanwhile,the pons was selected as the reference brain region,and the standard uptake value ratio(SUVR)of insular subregions were calculated.The above parameters were compared between groups,and the correlations of SUVR of insular subregions with clinical cognitive function scale scores in bvFTD group were analyzed.Results Compared with control group,the functional connections between all insular subregions and bilateral frontal lobe,temporal lobe,anterior cingulate gyrus,anterior cingulate gyrus and middle cingulate gyrus,as well as between some subregions and bilateral parietal and occipital lobes were weakened in bvFTD group(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05).SUVR of all insular subregions significantly decreased(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05),which in right ventral agranular insula(vIa),dorsal agranular insula(dIa),dorsal dysgranular insula(dId)and left dorsal agranular insula(dIa)were negatively correlated with frontal behavioral inventory(FBI)score in bvFTD group(r=-0.452--0.330,all P＜0.05).Conclusion In bvFTD patients,the functional connectivity and glucose metabolism of insular subregions changed,and SUVR of right vIa,dIa,dId and left dIa were negatively correlated with FBI score.