Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

Stiff person syndrome (SPS) is a rare neuro-immune disorder characterized by exaggerated startle responses and muscle spasms in response to minor stimuli. SPS is often misdiagnosed as panic disorder or agoraphobia. This paper reported a case of a patient with SPS presenting symptoms similar to panic attack. The patient had been misdiagnosed as dystonia, anxiety disorder and panic attack. The patient was finally correctly diagnosed through multiple disciplinary team discussions. This study integrates a comprehensive understanding of symptomatology and patient-reported experiences with targeted neurological evaluations and supplementary diagnostic tools to improve the accuracy of etiological diagnoses. This study aims to enhance the ability of psychiatrists to recognize somatic diseases presenting with psychiatric symptoms and to improve clinical diagnostic and treatment levels.

Objective The aim of this study was to explore the predictive value of the systemic inflammatory immune nutri-tion score(SIINS)for the prognosis of immunotherapy for advanced gastric cancer.Methods A retrospective analysis was conducted on the clinical data of 202 patients with advanced gastric cancer who received treatment with programmed death-1(PD-1)inhibitors at the Harbin Medical University Cancer Hospital from October 2018 to July 2022.The LASSO regression analysis was used to screen prognostic indicators,construct SIINS indicator,determine the optimal cutoff value for predicting prognosis using subject operating characteristic curves,and divide patients into the high SIINS and low SIINS groups.Independent prognostic factors for overall survival(OS)were determined using univariate and multivariate Cox regression analyses.Results Four indicators,including lymphocyte count,lactate dehydrogenase,and neutrophil lymphocytes,were selected to construct the SIINS index.The prognosis of patients in the high SIINS group was significantly lower than that in the low SIINS group(P<0.05).The results of the multifactorial Cox regression a-nalysis showed that the Eastern Cooperative Oncology Group(ECOG)score,Geriatric Nutritional Risk Index(GNRI),SIINS,treatment regimen,and number of treatment lines(P<0.05)could serve as the independent predictive prognosis of immunotherapy for advanced gastric cancer.Conclusion SIINS can predict the prognosis of patients with advanced gastric cancer treated with PD-1 inhibitors.

Objective:To observe the effect of isokinetic sensorimotor training on the hand function of stroke survivors.Methods:Forty-two stroke survivors with hand dysfunction were randomly divided into an isokinetic group of 22 and a control group of 20. Both groups were given sensorimotor training in addition to routine drug treatment and rehabilitation therapy, but the isokinetic group was additionally provided with sensorimotor training based on isokinetic techniques for 45 minutes daily, 5 days a week for 4 consecutive weeks. Before and after the intervention, both groups were evaluated using the Semmes-Weinstein monofilament examination (SWME), their two-point discrimination (2-PD) was documented, proprioception of their wrist joints was quantified, and the Fugl-Meyer upper extremity assessment (FMA-UE) and the simplified upper limb function assessment (STEF) were applied.Results:In both groups after treatment, there was a significant improvement in the SWME scores and 2-PD distance of the index finger and the thenar, and there was a significant decrease in the angle of motion perception (at 30° of flexion). The average FMA-UE and STEF scores of both groups had improved. After the treatment, the SWME scores of the index finger and the thenar, as well as well as the average FMA-UE and STEF scores of the isokinetic group were significantly higher than the control group′s averages. Angle of motion perception was also significantly superior.Conclusions:Sensorimotor training based on isokinetic techniques can significantly improve touch, motion sense, gross motor function and the fine motor ability of stroke survivors.

Objective To provide reference for future basic research and clinical research,the research status and trend of podophyllotoxin were explored.Methods Based on Citespace and R software,the co-occurrence map,keyword clustering and burst analysis of the English literature on podophyllotoxin in the Scientific Core Collection(WoSCC)were carried out to explore the research hotspots and analyze the frontier progress.Results A total of 1220 papers on podophyllotoxin published by 531 institutions from 77 countries and regions were retrieved.The number of published papers showed an overall upward trend.The analysis of the author 's cooperation network map showed that there was cooperation and communication between the authors,but it was relatively scattered,and the cooperation was not close.This phenomenon also existed in the relationship between research institutions.The country with the largest number of papers was China,and the institution was Lanzhou University.869 authors participated in the research in this field,and 422 academic journals published papers on podophyllotoxin.Among them,podophyllotoxin,derivatives,analogues,biological evaluation and etoposide had a high frequency of occurrence,indicating that these fields had high attention and great research potential.Conclusion In recent years,the research on podophyllotoxin and its derivatives in the treatment of tumors has developed rapidly.In addition,the pharmacological effects and gene regulation of podophyllotoxin are also new research trends.The research hotspots show a trend of diversification,which provides strong evidence for further exploring the molecular mechanism of podophyllotoxin in the treatment of various diseases.However,the lack of relatively in-depth basic research has limited the development of clinical research.

Alzheimer's disease (AD) is a common neurodegenerative disorder among the elderly, and BuChE has emerged as a potential therapeutic target. In this study, we reported the development of compound 8e, a selective reversible BuChE inhibitor (eqBuChE IC₅₀ = 0.049 μmol/L, huBuChE IC₅₀ = 0.066 μmol/L), identified through extensive virtual screening and lead optimization. Compound 8e demonstrated favorable blood-brain barrier permeability, good drug-likeness property and pronounced neuroprotective efficacy. Additionally, 8e exhibited significant therapeutic effects in zebrafish AD models and scopolamine-induced cognitive impairments in mice. Further, 8e significantly improved cognitive function in APP/PS1 transgenic mice. Proteomics analysis demonstrated that 8e markedly elevated the expression levels of very low-density lipoprotein receptor (VLDLR), offering valuable insights into its potential modulation of the Reelin-mediated signaling pathway. Thus, compound 8e emerges as a novel and potent BuChE inhibitor for the treatment of AD, with significant implications for further exploration into its mechanisms of action and therapeutic applications.

The rapid screening of bioactive constituents within traditional Chinese medicine (TCM) presents a significant challenge to researchers. Prevailing strategies for the screening of active components in TCM often overlook trace components owing to their concealment by more abundant constituents. To address this limitation, a fishing strategy based on offline two-dimensional liquid chromatography (2D-LC) combined with surface plasmon resonance (SPR) was utilized to screen bioactive trace components targeting peroxiredoxin 3 (PRDX3), using Uncaria alkaloids (UAs) as a case study. Initially, an orthogonal preparative offline 2D-LC system combining a positively charged C₁₈ column and a conventional C₁₈ column under disparate mobile phase conditions was constructed. To fully reveal the trace alkaloids, 13 2D fractions of UAs were prepared, and their components were characterized using mass spectrometry (MS). Subsequently, employing PRDX3 as the targeting protein, a SPR-based screening approach was established and rigorously validated with geissoschizine methyl ether (GSM) serving as a positive control for binding. Employing this refined strategy, 29 candidate binding alkaloids were fished from the 13 2D fractions. Notably, combining offline 2D-LC with SPR increased the yield of candidate binding components from 10 to 29 when compared to SPR-based screening alone. Subsequent binding affinity assays confirmed that PRDX3 was a direct binding target for the 12 fished alkaloids, with isovallesiachotamine (IV), corynoxeine N-oxide (CO-N), and cadambine (CAD) demonstrating the highest affinity for PRDX3. Their interactions were further validated through molecular docking analysis. Subsequent intracellular H₂O₂ measurement assays and transfection experiments confirmed that these three trace alkaloids enhanced PRDX3-mediated H₂O₂ clearance. In conclusion, this study introduced an innovative strategy for the identification of active trace components in TCM. This approach holds promise for accelerating research on medicinal components within this field.

Objective To analyze the acupoint selection law of acupuncture and moxibustion for postherpetic neuralgia(PHN)with R language data mining technology.Methods The clinical research literature on acupuncture and moxibustion treatment of PHN included in CNKI,Wanfang Data,VIP and CBM from January 1,2010 to July 1,2023 was retrieved,and the database was established by Excel 2016.R language was used to statistically analyze the frequency of acupoint usage,meridians,locations,specific acupoints,etc.Through association rule analysis and clustering analysis,the characteristics and law of acupoint selection for acupuncture and moxibustion treatment of PHN were obtained.Results A total of 198 articles were included,including 83 acupoints,with a total frequency of 714 times.The high-frequency acupoints include Ashi acupoint,Jiaji acupoint and Yanglingquan.The commonly used meridians were gallbladder meridian,spleen meridian and large intestine meridiam.The acupoints were mostly in the upper and lower limbs,with the Wushu acupoints,Yuan acupoints and Xiahe acupoints being the most common.The core acupoint was Ashi acupoint,Jiaji acupoint,Hegu,Quchi,and 9 sets of association rules and 5 effective clusters were obtained.Conclusion The most commonly used acupoints for acupuncture and moxibustion treatment of PHN are Ashi acupoint,Jiaji acupoint,Hegu and Quchi,which mainly follow the principle of combining local acupoint selection with distal acupoint selection.

Objective:To develop a rapid assessment scale for healthy aging suitable for the Chinese population.Methods:Based on existing healthy aging assessment scales, national standards, and expert consensus, an initial Healthy Aging Rapid Assessment Scale was drafted through two rounds of expert consultation. A pre-survey was conducted with 3 220 subjects recruited from Guangzhou between July 2023 and July 2024. Items were screened through item analysis and exploratory factor analysis to form the final scale. Reliability and validity of the final scale were validated across five cities: Guangzhou, Dongguan, Shenzhen, Baoding, and Chuxiong.Results:The initial version comprised 36 items, while the finalized scale contained 18 items across three dimensions: metabolic health, mental health, and cognitive health. Test-retest reliability ranged from 0.71 to 0.81 across all study sites. The Spearman-Brown coefficient varied between 0.91-0.96, Cronbach′s α between 0.77-0.83, comparative fit index (CFI) between 0.90-0.98, goodness-of-fit index (GFI) between 0.90-0.99, and root-mean-square error of approximation (RMSEA) between 0.03-0.09. For the three dimensions, reliability and validity metrics demonstrated consistency: Spearman-Brown coefficients 0.87-0.99, Cronbach′s α 0.77-0.83, CFI 0.90-0.98, GFI 0.90-0.99, and RMSEA 0.03-0.09 across four regions.Conclusion:The developed Healthy Aging Rapid Assessment Scale for the Chinese population exhibits robust reliability and validity.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.