In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.

Intravitreal injection of anti-vascular endothelial growth factor(VEGF)agents has become the primary treatment for macular edema associated with retinal vascular disease such as diabetic retinopathy and retinal vein occlusion, but there are limitations such as variable treatment efficacy and insufficient durability of therapeutic effects. As the first bispecific antibody applied in ophthalmic treatment, Faricimab achieves favorable outcomes by simultaneously targeting both VEGF-A and angiopoietin-2(Ang-2)pathways. Based on evidence from recent clinical trials and real-world studies, this article reviews the research progress on Faricimab for the treatment of diabetic macular edema(DME), retinal vein occlusion-associated macular edema(RVO-ME)and refractory macular edema compared to the therapeutic effects of other agents. Additionally, based on Faricimab's safety characteristics and future potential, its therapeutic prospects for macular edema associated with retinal vascular diseases are discussed. This review aims to provide evidence-based references for optimizing clinical treatment strategies, thereby contributing to mitigating the risk of vision loss due to macular edema.

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 investigate the relationship between the lipid metabolism-related gene sterol carrier protein 2(SCP2) and prostate cancer (PCa) from a multi-omics perspective using single-cell transcriptomes combined with Mendelian randomization. Methods： Single-cell transcriptome data of benign and malignant prostate tissues were obtained from GSE120716, GSE157703 and GSE141445 datasets, respectively. Integration, quality control and annotation were performed on the data to categorize the epithelial cells into high and low SCP2 expression groups, followed by further differential and trajectory analyses. Single nucleotide polymorphism (SNP) data for SCP2 expression quantitative trait loci (eQTL) were subsequently downloaded from Genotype-Tissue Expression (GTEx) and investigated from the PCa Society Cancer-Related Genomic Alteration Panel for the Investigation of Cancer-Related Alterations (PRACTICAL) to obtain PCa outcome data for Mendelian randomization analysis to validate the causal relationship between SCP2 and PCa. Results： High SCP2-expressing epithelial cells had higher energy metabolism and proliferation capacity with low immunotherapy response and metastatic tendency. Trajectory analysis showed that epithelial cells with high SCP2 expression may have a higher degree of malignancy, and SCP2 may be a key marker gene for differentiation of malignant epithelial cells in the prostate. Further Mendelian randomization results showed a significant causal relationship between SCP2 and PCa development (OR=1.045, 95% CI: 1.010 －1.083, P=0.011). Conclusion： By combining single-cell transcriptome and Mendelian randomization, the role of the lipid metabolism-related gene SCP2 in PCa development has been confirmed, and new targets and therapeutic directions for PCa treatment have been provided.
Humans ; Prostatic Neoplasms/genetics* ; Male ; Mendelian Randomization Analysis ; Polymorphism, Single Nucleotide ; Quantitative Trait Loci ; Single-Cell Analysis ; Sequence Analysis, RNA ; Carrier Proteins/genetics* ; Transcriptome ; Lipid Metabolism

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Cervical spondylotic radiculopathy(CSR)is a condition caused by the degeneration of cervical intervertebral discs and facet joints,primarily manifesting as the pain,sensory abnormalities,and motor dysfunction in the cervical nerve innervation area of neck,shoulder,and upper limb.For the treatment of CSR,tendon-bone syndrome differentiation in traditional Chinese medicine often faces the issues of conceptual confusion and non-standard syndrome differentiation.Based on the traditional tendon-bone syndrome differentiation and by integrating modern anatomical insights,Professor LIN Ding-Kun,an esteemed scholar of Traditional Chinese Medicine,proposed a classification system for the cervical spine that includes the categories of tendons,joints,bones and marrow.This paper explored the thoughts of Professor LIN for the tendon-bone syndrome differentiation of CSR,summarized the targets of manual therapy,and proposed the four kinds of pathological changes such as tendon overstrain,joint dislocation,bone lesion,and marrow injury,as well as the four techniques of traditional Chinese medicine manipulations,i.e.relaxation of tendons,reduction of joints,protection of marrow,and treatment of bones.The aim is to improve the syndrome-differentiation and treatment for CSR with orthopedic and traumatologic manipulations,and to provide reference for clinical practice.

AIM To investigate the effects and mechanism of Shenxiao Jiedu Tongluo Recipe on renal AIM 2-mediated pyroptosis of a golden hamster model of diabetic nephropathy(DN).METHODS Fifty male golden hamsters of SPF grade were randomly divided into the control group and the model group.The golden hamsters of the model group successfully developed into DN models by feeding of high glucose and high fat diet and intraperitoneal injection of STZ were further randomly assigned into the model group,the enagliflozin group(10 mg/kg),and the low-dose and the high-dose Shenxiao Jiedu Tongluo Recipe groups(12.8,25.6 g/kg)for 8 weeks gavage of the corresponding administration.The golden hamsters had their levels of fasting blood glucose,24 h-UTP,serum TC,LDL-C,Scr,and Sur detected by automatic biochemical analyzer;their serum SOD activity and MDA level detected by biochemical method;their serum levels of IL-1β,IL-18,and TNF-α detected by ELISA method;their pathomorphological changes of kidney tissue observed by HE and PAS staining;their protein expressions of ROS and γH2AX detected by immunofluorescence or immunohistochemistry;and their renal protein expressions of AIM 2,caspase-1 and GSDMD detected by Western blot and immunohistochemistry.RESULTS Compared with the control group,the model group showed atrophic glomeruli;enlarged glomerular capsule cavity;mesangial expansion;edema and necrosis in the dilated renal tubules;increased levels of fasting blood glucose,24 h-UTP,serum TC,LDL-C,Scr,Sur,IL-1β,IL-18,TNF-α,MDA and renal protein expressions of ROS,γH2AX,AIM2,caspase-1,GSDMD(P＜0.01);and decreased serum SOD activity(P＜0.01).Compared with the model group,the high-dose Shenxiao Jiedu Tongluo Recipe group and the enagliflozin group displayed improved renal histopathology,decreased levels of 24 h-UTP,serum TC,LDL-C,Scr,Sur,IL-1β,IL-18,TNF-α,MDA and renal protein expressions of ROS,γH2AX,AIM2,caspase-1,GSDMD(P＜0.05,P＜0.01);and increased serum SOD activity(P＜0.01).CONCLUSION Shenxiao Jiedu Tongluo Recipe can inhibit AIM 2-mediated cell death and alleviate renal inflammatory damage in golden hamsters by inhibiting their expression of ROS-dsDNA-AIM 2 signal pathway to attain reduction of their renal ROS level,DNA damage of renal intrinsic cells,and synthesis of AIM 2 inflammatory corpuscles as well.

Objective:To understand the current status of pubertal sexual characteristics development of girls aged 6-18 years in Tongzhou District of Beijing and to compare the differences in sexual characteristics development among girls characterized as thin, normal, overweight, and obese.Methods:A cross-sectional survey was conducted among 2 844 girls aged 6-18 years in Tongzhou District of Beijing from September 2022 to July 2023. The developmental stages of breast and pubic hair were assessed on site, and menarche status was inquired. Weight and height were measured. The girls were subsequently characterized into thin, normal, overweight and obese groups. Basic information (including family and personal history) was obtained through questionnaires. Probit probability unit regression was applied to calculate the age of each Tanner stage of sexual characteristics development and the age of menarche. The χ 2 test was applied to compare the counting data between two or multiple groups. Results:A total of 2 844 girls were surveyed and 2 704 girls met the inclusion criteria, resulting in a valid response rate of 95.1%. Among these girls, 1 105 (40.9%) were aged 6-9 years, 1 053 (38.9%) were aged 10-13 years, and 546 (20.2%) were aged 14-18 years. The of height-for-age Z-score (HAZ), weight-for-age Z-score (WAZ), and body mass index-for-age Z-score (BAZ) were 0.46(-0.23,1.16), 0.69(-0.16,1.67), and 0.67(-0.27,1.73) respectively. The prevalences of thin, overweight, and obesity were respectively 1.7% (45/2 704), 17.3% (467/2 704), and 19.9% (538/2 704), respectively. There were 45 girls in the thin group, 1 654 girls in the normal weight group, 1 005 girls in the overweight and obesity group. The age of Tanner stage breast 2 (B2), Tanner stage pubic hair 2 (P2), and menarche was 9.0 (95% CI 8.9-9.1), 10.5 (95% CI 10.4-10.6), and 11.4 (95% CI 11.3-1.5) years, respectively. The current status of breast and pubic hair maturity in girls with pubertal development shows that 64.6% (1 211/1 874) of these girls had breast development preceding pubic hair development, 32.4% (607/1 874) had concurrent breast and pubic hair development, and 3.0% (56/1 874) had pubic hairs development preceding breast development. The interval age between B2 and B5 was 4.7 (95% CI 4.6-4.8) years, between P2 and P5 was 4.5 (95% CI 4.4-4.6) years, and between B2 and menarche was 2.4 (95% CI 2.3-2.5) years. The ages of sexual characteristics development in overweight and obese groups were earlier than that in normal and thin groups. The ages of B2 in thin, normal, overweight, and obese groups were 10.0 (95% CI 9.5-10.6), 9.3 (95% CI 9.2-9.4), and 8.6 (95% CI 8.4-8.7) years, respectively. The age of menarche in thin, normal, overweight, and obese groups were 13.1 (95% CI 12.4-13.7), 11.6 (95% CI 11.4-11.7), and 11.1 (95% CI 11.0-11.2) years, respectively. The interval ages between B2 and B5 and between P2 and P5 was 4.5 and 4.1 years, respectively in the overweight and obese groups, and those in normal group and thin group was 4.7 and 4.5 years, 4.6 and 4.7 years, respectively. Conclusions:The ages of sexual characteristics development and menarche tend in Tongzhou District of Beijing to be earlier than that being reported of Beijing's survey 20 years ago. Girls characterized as overweight and obese not only start puberty at an earlier age than girls of normal weight, but also have a shorter developmental process.