Objective: To develop QingNangTCM, a specialized large language model (LLM) tailored for expert-level traditional Chinese medicine (TCM) question-answering and clinical reasoning, addressing the scarcity of domain-specific corpora and specialized alignment. Methods: We constructed QnTCM_Dataset, a corpus of 100 000 entries, by integrating data from ShenNong_TCM_Dataset and SymMap v2.0, and synthesizing additional samples via retrieval-augmented generation (RAG) and persona-driven generation. The dataset comprehensively covers diagnostic inquiries, prescriptions, and herbal knowledge. Utilizing P-Tuning v2, we fine-tuned the GLM-4-9B-Chat backbone to develop QingNangTCM. A multi-dimensional evaluation framework, assessing accuracy, coverage, consistency, safety, professionalism, and fluency, was established using metrics such as bilingual evaluation understudy (BLEU), recall-oriented understudy for gisting evaluation (ROUGE), metric for evaluation of translation with explicit ordering (METEOR), and LLM-as-a-Judge with expert review. Qualitative analysis was conducted across four simulated clinical scenarios: symptom analysis, disease treatment, herb inquiry, and failure cases. Baseline models included GLM-4-9B-Chat, DeepSeek-V2, HuatuoGPT-II (7B), and GLM-4-9B-Chat (freeze-tuning). Results: QingNangTCM achieved the highest scores in BLEU-1/2/3/4 (0.425/0.298/0.137/0.064), ROUGE-1/2 (0.368/0.157), and METEOR (0.218), demonstrating a balanced and superior normalized performance profile of 0.900 across the dimensions of accuracy, coverage, and consistency. Although its ROUGE-L score (0.299) was lower than that of HuatuoGPT-II (7B) (0.351), it significantly outperformed domain-specific models in expert-validated win rates for professionalism (86%) and safety (73%). Qualitative analysis confirmed that the model strictly adheres to the “symptom-syndrome-pathogenesis-treatment” reasoning chain, though occasional misclassifications and hallucinations persisted when dealing with rare medicinal materials and uncommon syndromes. Conclusion Combining domain-specific corpus construction with parameter-efficient prompt tuning enhances the reasoning behavior and domain adaptation of LLMs for TCM-related tasks. This work provides a technical framework for the digital organization and intelligent utilization of TCM knowledge, with potential value for supporting diagnostic reasoning and medical education.

Objective To investigate the drug resistance phenotype/genotype and virulence gene carrying status, serotype, and sequence typing (ST) of Campylobacter jejuni in Fengtai District in 2024. Methods The drug resistance phenotype was detected by agar dilution method, and serotyping was performed by real-time fluorescence quantitative polymerase chain reaction (PCR). The whole genome sequencing was used to analyze drug resistance genes, virulence genes, and other characteristics. Results Among the 35 Campylobacter jejuni strains analyzed, the antibiotics with the highest resistance rates were nalidixic acid and ciprofloxacin (both 82.86%), followed by tetracycline (74.89%). All strains exhibited a 100.00% sensitivity rate to erythromycin. The multiple drug resistance rate was 77.14%. The predominant drug resistance genes were gyrA-T86I (94.29%) and tetO (74.29%). The most common serotype was HS:2, accounting for 25 strains. A total of 132 virulence genes were detected. There were 12 clonal complexes (CC) and 24 ST types. Conclusion The drug resistance situation of Campylobacter jejuni in Fengtai District is relatively severe, and the drug resistance phenotype is related to specific genetic mutations to some extent. The serotypes are diverse, the virulence genes are complex, and the pathogenic potential is significant, posing a notable risk for inducing Guillain-Barré syndrome (GBS). The high number of ST types indicates substantial genetic diversity.

The aging microenvironment, as a key driver of tumorigenesis and progression, plays a critical role in tumor immune regulation through one of its core features-the senescence-associated secretory phenotype (SASP). SASP consists of a variety of interleukins, chemokines, proteases, and growth factors. It initially induces surrounding cells to enter a state of senescence through paracrine mechanisms, thereby creating a sustained inflammatory stimulus and signal amplification effect within the tissue microenvironment. Furthermore, these secreted factors activate key signaling pathways such as NF-κB, cGAS-STING, and mTOR, which regulate the expression of immune-related molecules (such as PD-L1) and promote the recruitment of immunosuppressive cells, including regulatory T cells and myeloid-derived suppressor cells. This process ultimately contributes to the formation of an immunosuppressive tumor microenvironment. Furthermore, the article explores potential anti-tumor immunotherapy strategies targeting SASP and its associated molecular mechanisms, including approaches to inhibit SASP secretion or eliminate senescent cells. Although these strategies have shown promise in certain tumor models, the high heterogeneity among tumor types may result in varied responses to SASP-targeted therapies. This highlights the need for further research into adaptive stratification and personalized treatment approaches. Targeting immune regulatory mechanisms in the aging microenvironment-particularly SASP-holds great potential for advancing future anti-tumor therapies.

Dysfunction of the interoceptive system is recognized as an important component of clinical symptoms, including anxiety, depression, psychosis, and other mental disorders. Non-invasive neuromodulation is an emerging clinical intervention approach, and over the past decade, research on non-invasive neuromodulation aimed at regulating interoception has rapidly developed. This review first outlines the pathways of interoceptive signals and assessment methods, then summarizes the interoceptive abnormalities in psychiatric disorders and current studies for non-invasive neuromodulation targeting interoception, including intervention modes, target sites, interoceptive measures, and potential neurobiological mechanisms. Finally, we discuss significant research challenges and future directions.
Humans ; Interoception/physiology* ; Mental Disorders/therapy*

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In general, bioassay-guided fractionation and isolation of bioactive constituents from botanical materials frequently ended up with the reward of a single compound. However, botanical materials typically exert their therapeutic actions through multi-pathway effects due to the intrinsic complex nature of chemical constituents. In addition, the content of bioactive compounds in botanical materials is largely dependent on humidity, temperature, soil, especially geographical origins, from which rapid and accurate identification of plant materials is pressingly needed. These long-standing obstacles collectively impede the deep exploitation and application of these versatile natural sources. To address the challenges, a new paradigm integrating biogravimetric analyses and machine learning-driven origin classification (BAMLOC) was developed. The biogravimetric analyses are based on absolute qHNMR quantification and in vivo zebrafish model-assisted activity index calculation, by which bioactive substance groups jointly responsible for the bioactivities in all fractions are pinpointed before any isolation effort. To differentiate origin-different botanical materials varying in the content of bioactive substance groups, principal component analysis, linear discriminant analysis, and hierarchical cluster analysis in conjunction with supervised support vector machine are employed to classify and predict production areas based on the detection of volatile organic compounds by E-nose and GC-MS. Expanding BAMLOC to Codonopsis Radix enables the identification of polyacetylenes and pyrrolidine alkaloids as the bioactive substance group for immune restoration effect and accurately determines the origins of plants. This study advances the toolbox for the discovery of bioactive compounds from complex mixtures and lays a more definitive foundation for the in-depth utilization of botanical materials.

Objective: To construct microRNA(miR)-22 gene knockout(miR-22-/-) mice using CRISPR/Cas 9 technology, to breed miR-22-/- mice and to identify their genotypes. Methods : In this experiment, CRISPR/Cas 9 technology was used to construct miR-22-/- genetically engineered mice. After gene identification, the F0 generation miR-22-/- mice were mated with wild-type mice in the same litter to obtain F1 generation miR-22-/- mice. The miR-22 knockout efficiency was analyzed at the RNA level by real-time fluorescence quantitative polymerase chain reaction(qPCR). Western blot was used to detect the interaction between miR-22 and target genes. Results : miR-22-/- mice were successfully constructed using CRISPR/Cas 9 technology, gene identification was performed on the bred mice, and three stable genotypes of miR-22+/+,miR-22+/-, and miR-22-/- were identified. The real-time fluorescence quantitative PCR detection results confirmed that miR-22-/- mice showed almost no expression of miR-22 in the heart, liver, lung, kidney, spleen, and thymus tissues compared to wild-type mice in the same litter. Western blot analysis showed that the relative expression level of NLRP3 protein in miR-22-/- mouse tissues was lower than that in wild-type mice. Conclusion A miR-22-/- mouse model is successfully constructed, and stable genetic homozygous miR-22-/- mice is obtained. This indicates that miR-22 has an inhibitory effect on the downstream target gene NLRP3.

Objective: To explore the breeding and genotyping of CCR2 knockout mice, and to verify the applicability of the polymerase chain reaction(PCR) method for genotype detection of CCR2 knockout mice. Methods: The introduced CCR2 pure male mice and wild-type female mice were mated and bred to produce the offspring generation, the obtained F1 generation heterozygous mice were continued to be mated. DNA was extracted by clipping the tail tissues of the mice at the age of 2 weeks, the target gene fragment was amplified by PCR, and the genotypic results were determined by agarose gel electrophoresis. The proportion of purebred progeny carrying the CCR2 knockout gene was increased by genetic crosses, the effect of CCR2 knockout in the progeny mice was verified by using Western blot against major immune cells and key organs, and flow cytometry was used to detect whether the knockout of the CCR2 gene had any effect on the function of the immune system by targeting the major immune cells. Results: CCR2 knockout mice were successfully bred and characterized, and three genotypes of F2 generation mice were obtained: CCR2+/+, CCR2+/-, and CCR2-/-. The offspring genotypes were identified by PCR, and Western blot showed extremely low CCR2 protein expression in CCR2 knockout mice. Flow analysis showed that CCR2 knockdown reduced the expression of CD4+T and Th1 cells in mouse spleen-derived T cells, but did not affect macrophage function. Conclusion Correct breeding and identification are important ways to get the pure CCR2 knockout mice, and PCR method for identifying mouse genotypes is simple, fast and reliable.

Objective To explore the role of the brief visuospatial memory test-revised(BVMT-R)in predicting the clinical conversion to psychosis in subjects with clinical high-risk for psychosis(CHR-P).Methods A total of 217 CHR subjects were recruited and assessed using BVMT-R at baseline.Participants were followed up for three years to determine whether they converted to psychosis.The relationship between BVMT-R total score and CHR-P conversion probability was analyzed using generalized additive model,and the cutoff values of BVMT-R total score for predicting CHR-P conversion were calculated by maximally selected rank statistics.Then,the total BVMT-R score was stratified into different intervals based on the cutoff values obtained as previously described.Finally,the positive likelihood ratios and the conversion rates at different time points were calculated for each interval.Results A total of 168 subjects with CHR-P completed the 3-year follow-up assessment.According to the results of the generalized additive model,the relationship between the BVMT-R total score and CHR-P conversion probability exhibited the characteristics of a piecewise function model.The cutoff values identified using the maximally selected rank statistics method were 18 and 29,which divided the BVMT-R total scores into three intervals:0-18,19-29,and 30-36.The positive likelihood ratios of the three intervals for predicting CHR-P psychosis conversion were significantly different(all P<0.01).All three intervals had significantly different rates of psychosis conversion at different follow-up time points(all P<0.01).Conclusion The total BVMT-R score can be divided into three intervals,each associated with a distinct positive likelihood ratio for predicting psychosis conversion in CHR-P individuals.Accordingly,the BVMT-R total score may serve as a preliminary indicator for estimating the probability of psychosis conversion in the CHR-P population.

Objective: To examine the causal association and potential mechanisms between bone mineral density in different age groups and primary malignant bone tumor based on two sample Mendelian randomization (MR), so as to provide a reference for the prevention and treatment of primary malignant bone tumor. Methods: The genome-wide association study (GWAS) of bone mineral density was obtained from the GEFOS database,which included 66 628 subjects divided into five age groups (0-15, 15-30, 30-45, 45-60, and >60 years) based on the phases of human bone development. The GWAS of primary malignant bone tumor was sourced from the FinnGen database, including 648 cases and 378 749 controls. Using bone mineral density of five age groups as the exposure and primary malignant bone tumor as the outcome, an MR analysis was performed with the inverse-variance weighted (IVW) method. Sensitivity analysis were conducted using Cochran's Q test, MR-Egger regression, MR-PRESSO test and MR Steiger test. The potential mechanisms underlying the causal association between bone density and primary malignant bone tumors were explored using Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Results: The MR analysis results showed that there was a negative causal association between bone density and primary malignant bone tumors in the 30-45 age group (OR=0.301, 95%CI: 0.126-0.721). No statistically significant associations between bone density and primary malignant bone tumors were found in the 0-15, 15-30, 45-60, and >60 age groups (all P>0.05). Sensitivity analysis did not detect heterogeneity, pleiotropy (all P>0.05) and reverse causality. KEGG enrichment analysis revealed that genes highly associated with bone density and primary malignant bone tumors were enriched in the mTOR signaling pathway and the Wnt signaling pathway, among which Low Density lipoprotein Receptor Related protein 5 and Wnt Family Member 16 are key regulatory genes. Conclusion The decrease in bone mineral density among individuals aged 30-45 may increase the risk of primary malignant bone tumors through the mTOR signaling pathway and the Wnt signaling pathway.