Objective To systematically evaluate the short-term efficacy and safety of McKeown and Sweet methods in the treatment of esophageal cancer. Methods PubMed, EMbase, The Cochrane Library, Web of Science, Wanfang, VIP, CNKI and Chinese Biomedical Literature database were searched for literature on the short-term efficacy and safety of McKeown and Sweet methods in the treatment of esophageal cancer published from the establishment to May 2023. Newcastle-Ottawa Scale was used to evaluate the quality of researches, and meta-analysis was performed using RevMan5.4. Results A total of 9 articles were included, involving 3687 patients including 1019 in the McKeown group and 2668 in the Sweet group. NOS score was 8-9 points. There were no statistical differences in the age, sex or American Joint Committee on Cancer stage between the two groups (P>0.05). Patients in the McKeown group had longer operative time and hospital stay, more intraoperative blood loss, and higher Eastern Cooperative Oncology Group scores than those in the Sweet group (P<0.05). However, the McKeown operation could remove more lymph nodes (P=0.001). In terms of safety, the incidences of pulmonary complications [OR=2.20, 95%CI (1.40, 3.46), P=0.001] and postoperative anastomotic leakage [OR=2.06, 95%CI (1.45, 2.92), P=0.001] were higher in the McKeown group than those in the Sweet group. In addition, there were no statistical differences between the two groups in the Karnofsky score, cardiac complications, vocal cord injury or paralysis, chylous leakage, or gastric emptying (P>0.05). Conclusion Compared with McKeown, Sweet method has advantages in operation time, intraoperative blood loss and hospital stay, and has lower incidence of postoperative pulmonary complications and anastomotic leakage. However, McKeown has more lymph node dissection.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Objective: To construct an index system of public health risk assessment for air pollution emergency, so as to provide a tool of evaluating the public health risks of air pollution emergency. Methods: Index system of public health risk assessment for air pollution emergency was established through literature review and group discussions. The index system was determined through two rounds of Delphi expert consultations involving specialists in environmental health, toxicology, epidemiology, health emergency response, and atmospheric monitoring. The effectiveness of the consultation was evaluated by positive coefficient, authority coefficient and coordination coefficient. The weights of index were determined using a combination weighting method of the expert scoring method and the entropy weight method. Results: Fifteen experts participated in the consultation, including 11 males and 4 females. There were 8 experts with a doctor degree, 6 experts with a master degree, 1 experts with a bachelor degree. A total of 11 experts with senior professional titles, and 4 experts with associate senior professional titles. The average work experience was (23.73±10.48) years. The expert positive coefficients for the two rounds of consultations were 83.33% and 100%, respectively. The expert authority coefficients were 0.794 and 0.811, respectively. The coefficients of variation for the importance, feasibility, and sensitivity scores of each index in the two rounds of comsultations were 0.097 to 0.352, 0.078 to 0.478, 0.115 to 0.388, and 0.049 to 0.133, 0.052 to 0.153, 0.049 to 0.178, respectively. The Kendall's coefficients of concordance were 0.237 and 0.440 (both with P<0.05) for the two rounds of consultations. The constructed assessment index system included "likelihood" "hazard" "vulnerability" "controllability" with comprehensive weights of 0.206 7, 0.059 6, 0.378 1, and 0.355 5, respectively. Among the 13 second indicators, "monitoring capability" had the highest comprehensive weight of 0.192 6. Among the 40 tertiary indicators, "real-time monitoring of atmospheric pollutants" "retrospective evaluation of early forecasting results" "types, quantities, and combined effects of atmospheric pollutants" "exposure modes of the population to atmospheric pollutants" had relatively high comprehensive weights of 0.089 5, 0.043 1, 0.041 1 and 0.040 3, respectively. Conclusion The constructed index system of public health risk assessment for air pollution emergency can be applied to the public health risk assessment for air pollution emergencies.

Plants of the Isodon genus are an important source of terpenoids， with their constituents exhibiting rich structural diversity and remarkable biological activities （such as anticancer， antimicrobial， and anti-inflammatory properties）， demonstrating significant potential in the field of immunomodulation. This review summarizes recent advances in the immunomodulatory mechanisms， development and application of terpenoid compounds from the Isodon genus. It has been found that these compounds can modulate key inflammatory signaling pathways， such as nuclear factor-kappa B （NF-κB） and mitogen-activated protein kinases （MAPKs）， thereby blocking the cascade amplification of inflammatory factors， alleviating chronic inflammatory responses， and correcting immune dysregulation. Additionally， they can influence the polarization direction of macrophages and dynamically regulate the balance among different functional subsets of T cells， restoring immune homeostasis. Their clinical translation faces multiple challenges， including poor druggability， a lack of systematic safety data， the absence of precise pharmacodynamic biomarkers， complexities in clinical trial design， and unclear industrialization pathways.

The plants of the genus Caragana Fabr. are desert plants of the Leguminosae family, which are widely used in traditional ethnomedicine, with the effects of nourishing Yin and nourishing blood, dispelling wind and removing dampness, clearing heat and detoxifying toxins. The anti-inflammatory effect of Caragana Fabr. has attracted much attention, the research on the related mechanism has made some progress, but it lacks systematic collation. By summarising the anti-inflammatory effects of the active ingredients of Caragana Fabr., the authors found that they have good anti-inflammatory activities on different inflammatory cell models in vitro, and have good improvement effects on rheumatoid arthritis, colitis, complex nephritis, and acute lung injury and other disease models. The anti-inflammatory effects of the active components of this genus mainly include the reduction of the levels of a variety of pro-inflammatory factors, and the signalling pathways involved mainly include TLR4/NF-κB, TLR4/MAPK, TLR4/NF-κB/IRF3, JAK/STAT-1, ERK/STAT-1 and so on. Therefore, the paper mainly reviews the research progress on the anti-inflammatory effects and mechanisms of the Caragana Fabr. plants and their active components according to disease types, with a view to providing reference for the in-depth study of their anti-inflammatory activities and the development of new products with related functions.

Traditional Chinese medicine (TCM) is a well-accepted therapy for atopic dermatitis (AD). However, there are currently no evidence-based guidelines integrating TCM and Western medicine for the treatment of AD, limiting the clinical application of such combined approaches. Therefore, the China Association of Chinese Medicine initiated the development of the current guideline, focusing on key issues related to the use of TCM in the treatment of AD. This guideline was developed in accordance with the principles of the guideline formulation manual published by the World Health Organization. A comprehensive review of the literature on the combined use of TCM and Western medicine to treat AD was conducted. The findings were extensively discussed by experts in dermatology and pharmacy with expertise in both TCM and Western medicine. This guideline comprises 23 recommendations across seven major areas, including TCM syndrome differentiation and classification of AD, principles and application scenarios of TCM combined with Western medicine for treating AD, outcome indicators for evaluating clinical efficacy of AD treatment, integration of TCM pattern classification and Western medicine across disease stages, daily management of AD, the use of internal TCM therapies and proprietary Chinese medicines, and TCM external treatments. Please cite this article as: Du XR, Wu MY, Tao MC, Lin Y, Gu CY, Wu MF, Cao Y, Chen DC, Li W, Wang HW, Wang Y, Wang Y, Lu HZ, Liu X, Su XF, Li FL. Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine. J Integr Med. 2025; 23(6):641-653.
Dermatitis, Atopic/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Integrative Medicine ; Drugs, Chinese Herbal/therapeutic use* ; Practice Guidelines as Topic

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning