ObjectiveTo explore the effect of elbow-wrist functional orthosis on plantar pressure distribution and balance function in stroke patients with hemiplegia. MethodsFrom June, 2024 to April, 2025, 60 patients with post-stroke hemiplegia were recruited from Huashan Hospital, Fudan University, and Shanghai Hebin Rehabilitation Hospital. They were randomly divided into control group (n = 30) and intervention group (n = 30). The control group received routine neurological rehabilitation, while the intervention group received additional training with an elbow-wrist functional orthosis on the affected side, for eight weeks. Before and after intervention, the Modified Ashworth Scale (MAS) of the elbow joint, plantar pressure symmetry index (SI), plantar contact area and mean plantar pressure were recorded, and balance and mobility were assessed using the Berg Balance Scale (BBS), Timed Up & Go Test (TUGT) and 10-Meter Walk Test (10MWT). ResultsTwo cases dropped out in the control group. After treatment, MAS grades of the elbow joint, forefoot SI, affected side plantar pressure area, BBS scores, TUGT and 10MWT of both groups improved (|Z| > 3.969, |t| > 3.528, P < 0.01), while the hindfoot SI and average pressure of the affected foot improved in the intervention group (∣t∣ > 4.264, P < 0.001). Except for TUGT and 10MWT, the intervention group was superior to the control group (∣Z∣ > 2.030, ∣t∣ > 2.096, P < 0.05). ConclusionThe elbow-wrist functional orthosis can enhance balance function in stroke patients with hemiplegia by reducing upper-limb spasticity, optimizing center-of-gravity distribution, and improving postural control.

Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

[摘 要] 目的：探讨干扰素刺激基因家族成员黏病毒抵抗蛋白2（MX2）在调控肿瘤细胞对呼肠孤病毒（Reo）溶瘤敏感性中的作用及其机制。方法：选取4株具有不同耐药特征的人源肿瘤细胞，通过CCK-8法评估其对Reo的溶瘤敏感性；通过转录组测序筛选出差异表达基因MX2，qPCR法及WB法验证MX2在4株人源肿瘤细胞中的表达；使用siRNA敲低溶瘤低敏感的COC1/DDP细胞中的MX2基因。在细胞感染Reo病毒后，通过CCK-8法检测细胞存活率；qPCR法检测细胞中Reo病毒S1基因表达；免疫荧光法检测细胞内Reo病毒蛋白的积累；半数组织培养感染剂量（TCID50）法测定病毒滴度；流式细胞术分别检测细胞内Reo病毒dsRNA、活性氧（ROS）水平以及细胞凋亡率；透射电镜观察细胞内质网形态变化并采用WB法检测内质网应激相关蛋白（JNK、p-JNK、eIF2α、p-eIF2α、CHOP、PERK）的表达。结果：在4株肿瘤细胞中，SKOV3细胞对Reo溶瘤作用高度敏感，而COC1/DDP、HuH-7SRB及SNU-398细胞均为溶瘤低敏感性。转录组测序结果显示，MX2在溶瘤低敏感肿瘤细胞中的表达水平显著高于溶瘤高敏感细胞（P < 0.01）；在溶瘤低敏感性的COC1/DDP细胞中，敲低MX2显著促进Reo病毒复制、诱导细胞凋亡增加，并升高细胞内活性氧水平（均P < 0.001）。透射电镜观察显示，敲低MX2的COC1/DDP细胞感染Reo病毒后出现内质网肿胀、扩张及断裂等典型内质网应激超微结构改变。WB结果显示，内质网应激关键标志物eIF2α/p-eIF2α、PERK、CHOP及凋亡相关调节蛋白JNK/p-JNK的表达均显著上调（P < 0.05或P < 0.01）。结论：肿瘤细胞对Reo的溶瘤敏感性与其细胞内MX2表达水平密切相关。敲低MX2可显著增强Reo在细胞内的复制，进而促进ROS积累，触发内质网应激并促进凋亡。病毒复制增加与细胞凋亡激活的双重作用，最终协同增强Reo的溶瘤作用。

ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

ObjectiveTo describe the epidemiological characteristics and trend of pulmonary tuberculosis among the elderly in Shanghai from 2014 to 2023, to estimate the incidence between 2024‒2025, so as to provide references for optimizing the prevention and control strategies of pulmonary tuberculosis for elderly in Shanghai. MethodsData of pulmonary tuberculosis patients aged ≥60 years in Shanghai registered in the Tuberculosis Registration and Management System of Chinese Center for Disease Control and Prevention from 2014 to 2023 was derived to describe the demographic characteristics of the elderly patients with pulmonary tuberculosis, and to calculate the reported incidence rate and annual percentage change (APC) of pulmonary tuberculosis. The autoregressive integrated moving average (ARIMA) model was constructed using monthly reported incidence data from January 2014 to June 2023, and data from July to December in 2023 were used to validate the model and predict the reported incidence rate of pulmonary tuberculosis among elderly in 2024 and 2025. ResultsA total of 19 208 elderly pulmonary tuberculosis patients were registered and reported in Shanghai from 2014 to 2023, with an average annual reported incidence rate of 35.04/100 000. The reported incidence rate of pulmonary tuberculosis in elderly showed an overall decreasing trend, APC=-3.34% (t=-3.360,P=0.010). While, the proportion of elderly pulmonary tuberculosis patients showed a yearly increasing trend among the total registered and reported cases, APC=5.65% (t=10.820, P<0.001). The difference in the average annual reported incidence rate of pulmonary tuberculosis in elderly was statistically significant in different regions (χ²=31.762, P=0.007), with the central urban areas(33.23/100 000) being lower than that in suburban areas (36.46/100 000), and the annual decreasing rate was faster in central urban area, APC=-4.88% (t=-4.838, P<0.001) and -2.76% (t=-2.811, P=0.023), respectively. The incidence rate was significantly higher in males than that in females (χ²=514.395, P<0.001). Additionally, the difference in reported incidence rate was statistically significant among different age groups(χ²=119.751,P<0.001), among which patients aged ≥80 years had the highest average annual incidence rate (59.69/100 000), and those aged ≤60 years had the lowest average annual incidence rate (28.57/100 000). Compared with the non-residential permanent elderly population (47.68/100 000), the average annual incidence rate of pulmonary tuberculosis among the elderly with household registration in Shanghai was lower (33.82/100 000) (χ²=24.295, P<0.001). The ARIMA (0,0,1) (0,1,1) 12 model was used to predict the incidence rate of pulmonary tuberculosis among the elderly in Shanghai in 2024 and 2025, and which was predicted to be 37.41/100 000 and 35.92/100 000, respectively. ConclusionThe reported incidence rate of pulmonary tuberculosis among the elderly in Shanghai showed an overall yearly downward trend from 2014 to 2023, but its proportion in the total number of reported pulmonary tuberculosis cases increased year by year. Prevention and control efforts should still not be slackened and emphasis should be placed on male, suburban and non-residential permanent elderly populations.

With the continuous advancement of internet technology and the improvement of internet literacy among the general population, the concept of online-offline integration in internet hospitals has gradually gained acceptance and has been applied and developed both domestically and internationally. In thoracic surgery, the applicability of this model lies in enhancing efficiency and delivering comprehensive, diversified, and personalized medical services to address complex and severe conditions. However, challenges such as hardware limitations and diagnostic/treatment risks persist during the implementation of internet hospitals. Through future in-depth and localized research, the online-offline integration of internet hospitals is expected to undergo further development and refinement. This progress will facilitate its integration into clinical practice in thoracic surgery, ultimately providing patients with improved medical care services.

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent cause of chronic liver disease worldwide, and its intricate pathogenesis presents challenges in the development of new drugs. As a common way of post-translational modification, acetylation regulates protein stability, enzyme activity, and subcellular localization, occurring extensively in MASLD-associated processes such as lipid metabolism, inflammatory response, and oxidative stress. In this paper, we comprehensively review the mechanism of acetylation in MASLD, analyze the expression levels of acetylases in liver tissues of MASLD patients from the gene expression omnibus (GEO), discuss the changes in relevant enzyme expression and mechanisms in animal models, and further explore the feasibility of targeting acetylation for MASLD treatment, in the hope of offering a new perspective for advancing drug discovery in the field of MASLD.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.