Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.

Sophorae Flavescentis Radix is one of the commonly used traditional Chinese medicine in China, and a large amount of pharmaceutical residue generated during its processing and production is discarded as waste, which not only wastes resources but also pollutes the environment. Therefore, elucidating the chemical composition of the residue of Sophorae Flavescentis Radix and the differences between the residue and Sophorae Flavescentis Radix itself is of great significance for the comprehensive utilization of the residue. This study, based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) technology combined with multivariate statistical methods, provides a thorough characterization, identification, and differential analysis of the overall components of Sophorae Flavescentis Radix and its residue. Firstly, 61 compounds in Sophorae Flavescentis Radix were rapidly identified based on their precise molecular weight, fragment ions, and compound abundance, using a self-constructed compound database. Among them, 41 compounds were found in the residue, mainly alkaloids and flavonoids. Secondly, through principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA), 15 key compounds differentiating Sophorae Flavescentis Radix from its residue were identified. These included highly polar alkaloids, such as oxymatrine and oxysophocarpine, which showed significantly reduced content in the residue, and less polar flavonoids, such as kurarinone and kuraridin, which were more abundant in the residue. In summary, this paper clarifies the overall composition, structure, and content differences between Sophorae Flavescentis Radix and its residue, suggesting that the residue of Sophorae Flavescentis Radix can be used as a raw material for the extraction of its high-activity components, with promising potential for development and application in cosmetics and daily care. This research provides a scientific basis for the future comprehensive utilization of Sophorae Flavescentis Radix and its residue.
Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Mass Spectrometry/methods* ; Sophora/chemistry* ; Flavonoids/chemistry* ; Alkaloids/chemistry*

OBJECTIVE: To explore the therapeutic effects and underlying mechanisms of Dendrobium officinale (Tiepi Shihu) extract (DOE) on insomnia. METHODS: Forty-two male Sprague-Dawley rats were randomly divided into 6 groups (n=7 per group): normal control, model control, melatonin (MT, 40 mg/kg), and 3-dose DOE (0.25, 0.50, and 1.00 g/kg) groups. Rats were raised in a strong-light (10,000 LUX) and -noise (>80 db) environment (12 h/d) for 16 weeks to induce insomnia, and from week 10 to week 16, MT and DOE were correspondingly administered to rats. The behavior tests including sodium pentobarbital-induced sleep experiment, sucrose preference test, and autonomous activity test were used to evaluate changes in sleep and emotions of rats. The metabolic-related indicators such as blood pressure, blood viscosity, blood glucose, and uric acid in rats were measured. The pathological changes in the cornu ammonis 1 (CA1) region of rat brain were evaluated using hematoxylin and eosin staining and Nissl staining. Additionally, the sleep-related factors gamma-aminobutyric acid (GABA), glutamate (GA), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) were measured using enzyme linked immunosorbent assay. Finally, we screened potential sleep-improving receptors of DOE using polymerase chain reaction (PCR) array and validated the results with quantitative PCR and immunohistochemistry. RESULTS: DOE significantly improved rats' sleep and mood, increased the sodium pentobarbital-induced sleep time and sucrose preference index, and reduced autonomic activity times (P<0.05 or P<0.01). DOE also had a good effect on metabolic abnormalities, significantly reducing triglyceride, blood glucose, blood pressure, and blood viscosity indicators (P<0.05 or P<0.01). DOE significantly increased the GABA content in hippocampus and reduced the GA/GABA ratio and IL-6 level (P<0.05 or P<0.01). In addition, DOE improved the pathological changes such as the disorder of cell arrangement in the hippocampus and the decrease of Nissel bodies. Seven differential genes were screened by PCR array, and the GABA_A receptors (Gabra5, Gabra6, Gabrq) were selected for verification. The results showed that DOE could up-regulate their expressions (P<0.05 or P<0.01). CONCLUSION DOE demonstrated remarkable potential for improving insomnia, which may be through regulating GABA_A receptors expressions and GA/GABA ratio.
Animals ; Dendrobium/chemistry* ; Rats, Sprague-Dawley ; Male ; Sleep Initiation and Maintenance Disorders/blood* ; Plant Extracts/therapeutic use* ; Receptors, GABA-A/metabolism* ; Noise/adverse effects* ; Light/adverse effects* ; gamma-Aminobutyric Acid/metabolism* ; Sleep/drug effects* ; Rats ; Receptors, GABA/metabolism*

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

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*

Objective To explore the characteristics of vaginal microecology and vaginitis distribution of female patients in Xi'an,so as to provide reliable reference for clinical treatment.Methods A total of 102 124 women in Shaanxi Provincial People's Hospital from January 2018 to August 2023 were selected as the research objects.Vaginal secretions were collected from patients,and the vaginal microecology was detected and analyzed.Results Among 102 124 female patients,99.87%had vaginal microecological imbalance.The main disease types were vulvovaginal candidiasis(VVC),accounting for 16.03%,bacterial vaginitis(BV),accounting for 9.61%and trichomonal vaginitis(TV),accounting for 1.34%.Statistical analysis showed that the age of VVC,BV and TV patients was mainly 21～30 years old.The prevalence of VVC and BV in summer and autumn was higher than that in other seasons,while the prevalence of TV was relatively high in summer.In addition,there were 27 552 cases of simple vaginitis(26.98%)and 1 443 cases of mixed vaginitis(1.41%)in 101 995 female patients with vaginal microecology imbalance.In patients with mixed vaginitis,the BV+VVC combination accounted for the vast majority(79.00%),and the age group was mainly between 21 and 40 years old.Among the 28 995 patients with vaginitis,4 308 patients(14.86%)had recurrence,and the recurrence rate of simple vaginitis(11.44%,3 152/27 552)was much lower than that of mixed vaginitis(80.11%,1 156/1 443).Conclusion The main type of female simple vaginitis in Xi'an is VVC,which has a high prevalence in summer and autumn.The main type of mixed vaginitis is BV+VVC,Compared with simple vaginitis,patients with mixed infection are more likely to relapse.

Cells are the fundamental structural and functional units of biological organisms,with inherent differences in composition and interactions with exogenous substances,known as cellular heterogeneity.Single cell inductively coupled plasma-mass spectrometry(SC-ICP-MS)allows for the high-throughput introduction of individual cells,enabling the highly sensitive detection and quantification of elements within a single cell,thus effectively providing information on cellular heterogeneity.This review outlined the SC-ICP-MS sample preparation process for different types of cells(single-cell systems,aggregation-prone and adherent cell systems,animal tissues,and plant tissues),including steps such as separation,washing,and fixation,as well as the advantages and existing issues of the current sample introduction systems and quantification methods.The recent applications of SC-ICP-MS in detecting endogenous substances(endogenous elements and proteins),exogenous substances(heavy metals,metal-based drugs and nanoparticles),and the simultaneous detection of both endogenous and exogenous substances were summarized.Finally,the perspectives on the future development of SC-ICP-MS in analytical methods and application fields were presented,including the optimization of single-cell sample preparation,transport efficiency,evaluation standards of ionization efficiency,and the establishment of multiparametric cell analysis platforms.

Silver nanoparticles(AgNPs)is widely used in biomedicine,daily chemicals,food industry and other fields,and the possible negative health effects of its exposure have attracted widespread attention.Accurate analysis of AgNPs in biological matrices is the basis for biosafety studies of AgNPs.Among the existing analytical techniques,single particle-inductively coupled plasma-mass spectrometry(sp-ICP-MS)has significant advantages such as high sensitivity and simultaneous detection of different forms of silver.However,AgNPs in biological matrices is uniquely highly dynamic and low in content,and the matrix interference is severe,which increases the complexity of the analysis.Although some scholars have reviewed the application of this method for detection of metal nanoparticles in different scenarios,there is a lack of a summary of the quality control and optimization of the whole process from the perspective of AgNPs detection.There is still a lack of reference standards for the sp-ICP-MS analysis of AgNPs in biological matrices,and the existing methods need to be summarized and further optimized to achieve accurate quantification.Therefore,this paper reviewed the recent studies on the analysis of silver-containing nanoparticles in biological matrices based on sp-ICP-MS,mainly included the principles of the technique,the extraction methods of the particles,and the process of data processing,which focused on elaborating and comparing different pre-treatment methods,and explored issues of the current application of sp-ICP-MS for detection of AgNPs in biological tissues and the development of future optimization trends.The current problems of sp-ICP-MS for detection of AgNPs in biological tissues and the future development trend were also discussed.

Objective To investigate the clinical features and prognosis of acute pancreatitis(AP)complicated with metabolic syndrome(MS).Methods 139 AP patients were retrospectively selected and divided into MS group(76 cases)and non-MS group(63 cases),general data of the two groups were collected and analyzed;conservative treatment was given to 2 groups of patients,and the general conditions,laboratory indicators,comorbidities,and related indicators of disease severity of the two groups were compared and analyzed,and the influencing factors of poor prognosis in patients(AP combined with MS)were analyzed.Results Compared with non-MS group,HDL,Ca2+in MS group decreased significantly,Body weight、Body Mass Index(BMI)、diabetes mellitus、hypertension(systolic/diastolic blood pressure)、hyperlipidemia、white blood cell count、CRP、PCT、IL-6、FPG、UA、TC、TG、TyG、TYG-BMI and non-traditional lipid parameters TC/HDL-C、TG/HDL-C、LDL-C/HDL-C and non-HDL-C were significantly increased.There were no significant differences in age、sex、length of stay、BUN、CREA、LDL-C、ALT and AST between the two groups(P＞0.05);BMI,white blood cell count,CRP,IL-6,FPG,UA,TC,TG,TyG,TYG-BMI,TC/HDL-C,TG/HDL-C,LDL-C/HDL-C,and non-HDL-C were independent risk factors for poor prognosis in AP patients with MS,and HDL-C was a potential protective factor for prognosis in AP patients with MS,the difference was statistically significant(P＜0.05).Conclusion With the change of modern lifestyle,there are more and more MS patients,and the incidence of MS patients with AP is gradually increasing.TyG,TYG-BMI and non-traditional lipid parameters are novel,convenient and practical markers for clinical evaluation,which have a high diagnostic and predictive value for AP with MS metabolic abnormalities,and provides clinical basis for management and intervention.