Chaihu Guizhi Ganjiangtang was first recorded in the Treatise on Cold Damage （Shang Han Lun）. This prescription is composed of Bupleuri Radix， Scutellariae Radix， Cinnamomi Ramulus， Zingiberis Rhizoma， Trichosanthis Radix， Ostreae Concha， and Glycyrrhizae Radix et Rhizoma. It has the effects of soothing Lesser Yang， warming the spleen， and stimulating the generation of body fluid. It is mainly used to treat digestive tract diseases such as chronic cholecystitis （CC）， irritable bowel syndrome， and non-alcoholic fatty liver disease. Dyspepsia caused by CC presents a variety of gastrointestinal symptoms such as abdominal pain， poor appetite， postprandial fullness， aversion to greasy food， soft stool， and bitter mouth， being a type of biliary dyspepsia. In modern medicine， dyspepsia caused by CC is mainly managed by medical treatment and surgical treatment. Internal medicine mainly focuses on reducing inflammation， promoting the function of gallbladder， resolving stones， alleviating spasms， and relieving the pain for CC， demonstrating definite short-term efficacy but suffering from single effects， high recurrence rate， and poor compliance. Although surgical treatment can cure cholecystitis， it is accompanied by the increased incidence of adverse events such as abdominal pain， diarrhea， and dyspepsia. Modern clinical studies have confirmed that Chaihu Guizhi Ganjiangtang can significantly alleviate the symptoms such as abdominal pain and dyspepsia of CC patients. Pharmacological studies have found that Chaihu Guizhi Ganjiangtang mainly contains active ingredients such as Bupleuri Radix saponins， baicalin， cinnamaldehyde， gingerol， Trichosanthis Radix polysaccharide， Ostreae Concha polysaccharide， and Glycyrrhizae Radix et Rhizoma total flavonoids. Chaihu Guizhi Ganjiangtang can ameliorate the symptoms of dyspepsia caused by CC by inhibiting inflammatory responses， improving gallbladder contraction and gastrointestinal motility， regulating the bile acid-intestinal flora axis and the brain-gut axis， and modulating blood lipids through multiple targets. By reviewing the previous literature， this article summarizes the research progress in the treatment of dyspepsia caused by CC with Chaihu Guizhi Ganjiangtang and its main active ingredients as well as the pathogenesis of this disease and puts forward the shortcomings and improvement strategies for the current research. The review aims to provide a reference for the further research on Chaihu Guizhi Ganjiangtang in the treatment of dyspepsia caused by CC.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveTo analyze the research hotspots and development trends in the field of spinal cord stimulation (SCS) for spinal cord injury (SCI). MethodsLiterature about SCS for SCI was retrieve from the Web of Science (WOS) Core Collection database, with a time range from January, 1999 to July, 2025. VOSviewer 1.6.20 and CiteSpace 6.4.R2 were used to analyze the annual publication volume, countries, authors, institutions, journals and keywords. ResultsA total of 636 literatures were included. From 1999 to 2025, the overall publication trend in this field showed an upward trajectory, with recent years fluctuating but tending to stabilize. The country with the most publications was the United States (429 papers), followed by Russia (98 papers) and China (70 papers). The institution with the highest number of publications was the University of California, Los Angeles (76 papers), the author with the most publications was V. Reggie Edgerton (70 papers), and the journal with the most publications was Journal of Clinical Medicine (31 papers). The most frequently cited study focused on exploring the combination of epidural spinal cord stimulation with task-specific training to restore motor function in patients with complete SCI. Keyword analysis showed that the research hotspots in this field were mainly focused on neuroregulation mechanisms, recovery of motor and autonomic nervous dysfunction, artificial intelligence, closed-loop stimulation and brain-computer interface technology innovations. In recent years, the research focus gradually shifted from basic mechanisms to personalized and precise multifunctional rehabilitation strategies. ConclusionThe field of SCS for SCI has undergone phases of basic mechanism exploration and clinical application expansion. Current research hotspots and future trends focus primarily on the development of new stimulation paradigms and combined innovative technologies.

ObjectiveTo develop a community-family management model for older adults with mild cognitive impairment (MCI) and to formulate detailed application specifications, and to fully leverage the initiative of communities and families under limited resource conditions, for achieving community-based early detection and early intervention for older adults with MCI. MethodsA systematic literature review was conducted to identify pertinent publications. Corpus-based research methodologies were employed to extract, refine, integrate and synthesize management elements, thereby establishing the specific content and service processes for each stage of the management model. Utilizing the 5W2H analytical framework, essential elements such as management stakeholders, target populations, content and methods for each stage were delineated. The model and its application guidelines were finalized through expert consultation and demonstration. ResultsAn expert evaluation of the management model yielded mean scores of 4.84, 4.32 and 4.84 for acceptability, feasibility and systematicity, respectively. By integrating the identified core elements with expert ratings and feedback, the final iteration of the community-family management model for older adults with MCI was formulated. This model comprised of five stages: screening and identification, comprehensive assessment, intervention planning, monitoring and referral pathways to ensure implementation, and enhanced support for communities, family members and caregivers. Additionally, it included 18 specific application guidelines. ConclusionThe proposed management model may theoretically help delay cognitive decline, improve cognitive function and potentially promote reversal from MCI to normal cognition. It may also enhance the awareness and coping capacity of older adults and their families, strengthen community healthcare professionals' ability to early identify and manage MCI.

arcopenia is a systemic skeletal muscle disorder characterized by a decrease in skeletal muscle mass and progressive decline in function， with multiple signaling pathways involved in its occurrence and development. Among them， the AMP-activated protein kinase （AMPK） signaling pathway， as a key pathway regulating cellular energy homeostasis， plays an important role in the regulation of skeletal muscle metabolism and functional maintenance by improving abnormalities in glucose and lipid metabolism， balancing skeletal muscle protein synthesis and degradation， improving mitochondrial function， promoting autophagy， and inhibiting inflammatory responses and oxidative stress. This article reviews the research progress on how various traditional Chinese medicine （TCM） monomers， including polyphenols， flavonoids， and terpenoids； various traditional Chinese medicine extracts， such as those from Lycium barbarum ， Asini Corii Colla， and Panax quinquefolium ， and TCM compounds， such as Guiqi zhuangjin decoction， Jianpi qiangji granules， and Qigu capsules， intervene in sarcopenia by regulating the AMPK signaling pathway to promote muscle protein synthesis， inhibit protein degradation， improve mitochondrial function， and alleviate inflammation and oxidative stress. Additionally， their molecular mechanisms are explored. The aim is to deeply elucidate the basis of TCM in the prevention and treatment of sarcopenia and to provide theoretical support for the development of related innovative drugs.

ObjectiveTo observe the effect of functional pelvic floor muscle training on pelvic floor muscle function, incontinence symptoms and quality of life in female patients with stress urinary incontinence (SUI). MethodsFrom February, 2024 to July, 2025, 40 female patients with SUI were recruited from Beijing Bo'ai Hospital and advertisements. They were randomly divided into control group (n = 20) and experimental group (n = 20). The control group received conventional pelvic floor muscle contraction and relaxation training, and the experimental group received functional pelvic floor muscle contraction and relaxation training, for eight weeks. The data of pelvic floor muscle strength, pelvic floor muscle surface electromyography (sEMG), 1-hour urine pad test and Incontinence Quality of Life questionnaire (I-QOL) were collected before and after training. The compliance rate was counted after training. ResultsOne case dropped down in the control group and three cases dropped down in the experimental group. After treatment, the pelvic floor muscle strength increased in both groups (|Z| > 3.317, P < 0.01), the pre-resting average value, sustained contraction average value and durable contraction average value of sEMG improved in the control group (|t| > 2.731, P < 0.05), the mass of 1-hour urine pad significantly reduced (t > 9.215, P < 0.001) and the I-QOL score significantly increased (|t| > 13.229, P < 0.001) in both groups; compared with the control group, the pelvic floor muscle strength significantly increased (Z = -2.281, P = 0.023), the mass of 1-hour urine pad significantly reduced (t = 4.215, P < 0.001), the I-QOL score significantly increased (t = -4.501, P < 0.001), and the compliance rate significantly increased (Z = -2.798, P < 0.01) in the experimental group . ConclusionFunctional pelvic floor muscle training can significantly improve pelvic floor muscle strength, incontinence symptoms and quality of life in female patients with SUI.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

ObjectiveTo analyze the temporal trend of knockdown resistance (kdr) gene mutations highly correlated with pyrethroid resistance in field populations of Aedes aegypti in Jinghong City of Yunnan Province, and to provide a scientific basis for formulating rational insecticide use strategies. MethodsAdult mosquito samples of Aedes aegypti from 2016 to 2023 and larvae mosquito samples from July 2022 to June 2023 were collected in Jinghong City of Yunnan Province. Allele specific PCR (AS-PCR) was used to measure kdr mutations at amino acid positions 989, 1016 and 1534 of the voltage-gated sodium ion channel (VGSC) gene. Data such as mutation rate and mutation allele frequency were calculated, SPSS software was used to perform trend chi square tests on mutation rate and mutation allele frequency with year and month, as well as comparison of mutation allele frequencies and genotype distributions between the dry and rainy seasons, thereby delineating the temporal trend of kdr gene mutations. ResultsAmong the 173 samples collected from 2016 to 2023, the mutation rates of S989P and V1016G were 100.00% for each year, while the mutation rate of F1534C ranged from 62.50% to 100.00%. The mutation rate and mutation allele frequency of F1534C were increased over the years (χ²=22.079, P<0.001; χ²=42.971, P<0.001). Concurrently, the proportion of the PPGGCC genotype was increased annually (χ²=60.790, P<0.001). Among the 288 samples collected from July 2022 to June 2023, the monthly mutation rates for S989P, V1016G, and F1534C were consistently 100.00%. There was only one type of mutation present, namely S989P+V1016G+F1534C. In the combinations of the three genotypes, the SPGGCC genotype accounted for 1.39% (4/288), the PPGGFC accounted for 2.78% (8/288), and the PPGGCC had the highest proportion at 95.83% (276/288). After tesiting the samples collected in August 2023, the mutation rates of 989, 1016 and 1534 sites of VGSC in females, males, and larvae of the same generation were all 100.00%. ConclusionSince 2016, the gene mutations at S989P and V1016G loci in the VGSC gene of wild Aedes aegypti in Jinghong City have remained consistently at 100.00%, while the mutation rate and mutant allele frequency of F1534C have increased year by year during the testing period. By 2023, the mutation rates at three loci in the VGSC gene of Aedes aegypti in Jinghong City had all reached 100.00%, and neither changes in insect developmental stage nor gender differences during transmission exerted a detectable impact on the mutation rates. In the control of Aedes aegypti in Jinghong City, the use of pyrethroid insecticides should be stopped or reduced, and regular monitoring of kdr genes should be carried out to promptly detect new mutations.

CD20 is a surface marker protein of B-cell lymphoma, and its extracellular region is the target of specific antibodies and drugs. To obtain a cheap and easily modified specific preparation targeting CD20, we optimized the gene of CD20 extracellular region according to codon degeneracy to facilitate its expression in Escherichia coli. The optimized gene was cloned into pGEX-4T-1 vector, and the recombinant vector was transformed into E. coli BL21(DE3) for expression. The purified protein was identified by SDS-PAGE and Western blotting. Systematic evolution of ligands by exponential enrichment (SELEX) was employed to screen the ssDNA aptamer that specifically binds to the fusion protein, and the affinity of the aptamer to CD20 was detected by flow cytometry. Then, the cytotoxicity test was carried out to examine the inhibitory effect of the aptamer on B lymphoma cells. In this study, we established the prokaryotic expression method of CD20 and obtained the aptamer specifically binding to the extracellular region of CD20, which laid a foundation for the development of therapeutic drugs targeting CD20.
Humans ; Escherichia coli/metabolism* ; SELEX Aptamer Technique/methods* ; Aptamers, Nucleotide/genetics* ; Antigens, CD20/metabolism* ; Ligands