ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective:To analyze the epidemiological characteristics of cases involving monkey injuries at medical institutions surrounding Qianlingshan Park in Guiyang City, and to provide a reference basis for preventive measures to reduce monkey injuries and standardized post-exposure treatment.Methods:A retrospective cross-sectional study was conducted, collecting 1 900 cases of monkey-induced injuries in Qianlingshan Park treated at the outpatient clinic of Guizhou Provincial Center for Disease Control and Prevention and the Department of Surgery at Qianling Hospital, Guiyang City, from 2021 to 2024. Statistical analysis was performed using Pearson′s chi-square test.Results:Total of 1 900 cases of monkey-related injuries in Qianlingshan Park were collected from 2021 to 2024. The exposure time distribution exhibited significant seasonality, with 48.58% of cases occurring during July and August, totaling 923 cases, indicating a peak in the summer. There were 774 male patients and 1 126 female patients, with a ratio of 1∶1.45.and significant differences were observed between different age groups and genders (χ2=195.00, P<0.001), with the highest number of cases occurring in the 0-9 and 20-29 age groups, accounting for 22.05%(419 cases) and 21.79%(414 cases), respectively. The upper limbs were the most common injury site, accounting for 50.84% of the total cases(966 cases in total), with significant differences between gender and injury location (χ2=22.00, P<0.001), Among females, the proportion of injuries to the upper and lower limbs (30.11% and 16.47%, respectively) was higher than that among males (20.74% and 8.63%, respectively). The majority of injuries were classified as Grade Ⅲ, making up 57.38% of cases(1 069 cases in total). Self-treatment after exposure was the most common approach(60.44%), with significant differences observed between wound severity and treatment method (χ2=6.90, P=0.032), Patients with Grade Ⅱ and Grade Ⅲ wounds were more likely to choose self-management (26.84% and 33.23%, respectively) than outpatient management (15.14% and 24.15%). Approximately 98.05% (1 863 cases) of monkey-injured patients had received rabies vaccinations. Conclusions:This study analyzes monkey-related injuries in Qianlingshan Park from 2021 to 2024, clarifying the temporal distribution of injuries, demographic characteristics, injury sites, and treatment methods. The findings provide references for optimizing human-monkey conflict management and the prevention and control of zoonotic diseases in urban ecological parks.

BACKGROUND:H uman pluripotent stem cell-derived cardiomyocytes offer an ideal cellular resource for studying heart diseases,conducting drug screening,developing in vitro heart models,and exploring potential cell therapies.However,human pluripotent stem cell-derived cardiomyocytes are characterized by immaturity with limited specific gene expression,low Ca2+processing levels,and underdeveloped structural,metabolic,and electrophysiological features.These limitations significantly impede the application of human pluripotent stem cell-derived cardiomyocytes.OBJECTIVE:To review the academic progress and clinical application of promoting the maturation of human pluripotent stem cell-derived cardiomyocytes by in vitro synthetic microenvironment.METHODS:CNKI,WanFang,VIP,PubMed,Web of Science,and Medline databases were searched,with"human pluripotent stem cells,human myocardial cells,hPSC-CMs,mature,OA,human pluripotent stem cell-derived cardiomyocytes,hPSC-CMs"as English search terms and"human pluripotent stem cells,cardiomyocytes,mature,OA,hPSC-CMs"as Chinese search terms.All relevant literature published from January 2002 to July 2024 was retrieved and 82 articles were included in the review.RESULTS AND CONCLUSION:(1)In recent years,in vitro synthetic microenvironments have attracted extensive attention due to their excellent intrinsic properties such as stiffness,plasticity,nanoscale morphology,and chemical functionality.(2)Human pluripotent stem cell-derived cardiomyocytes can be used as an effective platform for the treatment of cardiovascular diseases.(3)Mechanical stimulation,electrical stimulation,addition of biochemical molecules,and three-dimensional culture methods are effective methods to promote the maturation of human pluripotent stem cell-derived cardiomyocytes,which can further promote the clinical application of human pluripotent stem cell-derived cardiomyocytes.

Three evaluation methods were recommended for the key properties of the intravascular catheter lubricating coating such as stability,lubricity and integrity,including insoluble particle test method,friction test procedure and appearance detection method.Fifteen batches of microcatheters produced by different manufacturers were selected for testing to clarify the three methods in test principle,step,result,characteristic.References were provided for the design,production,evaluation and regulation of intravascular catheters with lubricant coatings.[Chinese Medical Equipment Journal,2025,46(1):66-72]

Soy is a vital source of plant carbohydrates.However,it poses significant allergenic risks,particularly to young children and animals.Among the various proteins in soy,β-conglycinin,which con-stitutes approximately 30％of total soy carbohydrates,is a primary allergen.Undigested β-conglycinin can lead to intestinal damage by inhibiting cell growth,disrupting the cytoskeleton,and inducing apopto-sis.It can also enter the lymphatic and circulatory systems,triggering allergic reactions.Conventional ELISA methods for detecting β-conglycinin rely on polyclonal or monoclonal antibodies,which are limited by their large molecular weight,difficulty in accessing the protein core,and sensitivity to acidic and bas-ic conditions.To address these limitations,this study aimed to develop nanobodies(Nbs)against β-con-glycinin.Nbs,derived from the variable regions of heavy-chain antibodies found in camelids,have a mo-lecular weight approximately one-tenth that of conventional antibodies.They offer advantages such as small size,stable structure,high specificity,and strong affinity.A female alpacas was immunized five times using β-conglycinin,which showed a heavy chain antibody potency of 1∶16 000 by ELISA.Pe-ripheral blood lymphocytes were subsequently isolated and total RNA was extracted.The variable region of the heavy-chain antibody was amplified via PCR,and recombinant plasmids were constructed and transformed into the E.coli competency strain ER2738.The resulting library contained about 3.5×108 CFU/mL,which increased to 1.15×1012 PFU/mL after phage rescue,with a 100％Nbs gene insertion rate,indicating high diversity.Its Nbs phage output was significantly enriched by four rounds of solid-phase elution with an enrichment rate of 155.9.Four rounds of solid-phase panning yielded 35 positive clones,all of which shared the same amino acid sequence upon sequencing.The selected Nb was ex-pressed in a prokaryotic system,and its binding ability to β-conglycinin was confirmed using Western blotting and ELISA.The results demonstrated excellent specificity and affinity.This research lays the groundwork for developing a rapid and efficient detection method for β-conglycinin using Nbs,potentially enhancing food safety and allergen management.

Aim To explore the effect of astragalosideⅣ(AS-Ⅳ)on lipopolysaccharide(LPS)-induced po-larization and migration of RAW 264.7 macrophages and the underlying mechanism.Methods 1 mg·L-1 LPS was used to construct cell migration model.Scratch assay was utilized to determine cell migration rate.Immunofluorescence staining was utilized to de-tect the expression and location of F4/80,iNOS and Arg-1.CCK-8 assay was used to determine the viabili-ty of RAW 264.7 cells.Griess assay was used to measure NO content.Molecular docking was used to analyze the interaction between AS-Ⅳ and the core tar-gets such as cGAS and STING protein.Western blot was employed to detect the expression of iNOS,Arg-1,cGAS,STING,NF-κB p65 and p-NF-κB p65 protein.Results AS-Ⅳ significantly inhibited the migration and M1 polarization of RAW 264.7 cells induced by LPS.Moreover,AS-Ⅳ could interact with cGAS and STING protein,especially cGAS.Further Western blot assay showed that AS-Ⅳ significantly downregulated the expression of iNOS,cGAS,STING and p-NF-κB p65 protein.Conclusions AS-Ⅳ could promote mac-rophage M1 to M2 polarization,thereby inhibited mac-rophage migration through restraining the cGAS/STING/NF-κB signaling pathway,which provides a new therapeutic target for AS-Ⅳ to improve the early inflammatory response of AS.

Accurate analysis of metal nanoparticles(MNPs)in sediments is a prerequisite for assessing the ecological risks of MNPs in aquatic environmental sediments.In this study,an analytical method for quantitative detection of concentration and particle size distribution of silver-containing nanoparticles(Ag-NPs),zinc-containing nanoparticles(Zn-NPs),cerium-containing nanoparticles(Ce-NPs),and titanium-containing nanoparticles(Ti-NPs)in sediments was established based on ultrasonic extraction-single particle inductively coupled plasma mass spectrometry(SP-ICP-MS).The effects of sample preparation conditions such as extraction solvent type,solid-liquid ratio,ultrasonic time,and settling time on the recovery of MNPs were investigated.The results showed that the extraction of MNPs from sediment by distilled water could effectively eliminate the high background signal interference introduced by the extractant under the conditions of solid-liquid ratio of 1∶400(g∶mL),ultrasonic extraction time of 1 h and settling time of 3 h.The detection limits for particle size of Ag-NPs,Zn-NPs,Ce-NPs and Ti-NPs in sediments were 31,35,26 and 85 nm,respectively,while the detection limits of particle concentrations were 1.21×104,1.90×104,5.26×107 and 1.48×107 particles/g,respectively.The spiking recoveries of Ag-NPs,Zn-NPs,Ce-NPs and Ti-NPs in sediments were 62.1％-108.7％,with relative standard deviations below 10％.This method could rapidly,accurately and simultaneously determine the concentration and particle size distribution of various MNPs in sediments,and was successfully applied to analysis of Ag-NPs,Zn-NPs,Ce-NPs,and Ti-NPs in authentic marine sediments.