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.

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.

Triple-negative breast cancer (TNBC) represents a distinctive subtype, characterized by the absence of estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2 (HER2). Due to its high inter-tumor and intra-tumor heterogeneity, TNBC poses significant chanllenges for personalized diagnosis and treatment. The advant of clustered regular interspaced short palindromic repeats (CRISPR) technology has profoundly enhanced our understanding of the structure and function of the TNBC genome, providing a powerful tool for investigating the occurrence and development of diseases. This review focuses on the application of CRISPR/Cas technology in the personalized diagnosis and treatment of TNBC. We begin by discussing the unique attributes of TNBC and the limitations of current diagnostic and treatment approaches: conventional diagnostic methods provide limited insights into TNBC, while traditional chemotherapy drugs are often associated with low efficacy and severe side effects. The CRISPR/Cas system, which activates Cas enzymes through complementary guide RNAs (gRNAs) to selectively degrade specific nucleic acids, has emerged as a robust tool for TNBC research. This technology enables precise gene editing, allowing for a deeper understanding of TNBC heterogeneity by marking and tracking diverse cell clones. Additionally, CRISPR facilitates high-throughput screening to promptly identify genes involved in TNBC growth, metastasis, and drug resistance, thus revealing new therapeutic targets and strategies. In TNBC diagnostics, CRISPR/Cas was applied to develop molecular diagnostic systems based on Cas9, Cas12, and Cas13, each employing distinct detection principles. These systems can sensitively and specifically detect a variety of TNBC biomarkers, including cell-specific DNA/RNA and circulating tumor DNA (ctDNA). In the realm of precision therapy, CRISPR/Cas has been utilized to identify key genes implicated in TNBC progression and treatment resistance. CRISPR-based screening has uncovered potential therapeutic targets, while its gene-editing capabilities have facilitated the development of combination therapies with traditional chemotherapy drugs, enhancing their efficacy. Despite its promise, the clinical translation of CRISPR/Cas technology remains in its early stages. Several clinical trials are underway to assess its safety and efficacy in the treatment of various genetic diseases and cancers. Challenges such as off-target effects, editing efficiency, and delivery methods remain to be addressed. The integration of CRISPR/Cas with other technologies, such as 3D cell culture systems, human induced pluripotent stem cells (hiPSCs), and artificial intelligence (AI), is expected to further advance precision medicine for TNBC. These technological convergences can offer deeper insights into disease mechanisms and facilitate the development of personalized treatment strategies. In conclusion, the CRISPR/Cas system holds immense potential in the precise diagnosis and treatment of TNBC. As the technology progresses and becomes more costs-effective, its clinical relevance will grow, and the translation of CRISPR/Cas system data into clinical applications will pave the way for optimal diagnosis and treatment strategies for TNBC patients. However, technical hurdles and ethical considerations require ongoing research and regulation to ensure safety and efficacy.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective:To investigate the nutritional risk status of children in PICU and analyze its influencing factors.Methods:From July 2021 to February 2023,all children aged 1 to 18 years admitted to PICU of Beijing Children's Hospital were investigated by using the pediatric Yorkhill Malnutrition Scoring tool(PYMS)and the clinical data questionnaire.Results:A total of 492 children in PICU were enrolled.The first nutritional risk screening results showed that there were 32 cases of no/low nutritional risk(6.5%),76 cases of medium risk(15.4%),and 384 cases of high risk(78.1%).The incidence of medium/high nutritional risk was as high as 93.5%.The PYMS score of nutritional risk in PICU was(2.61±1.42).The results of multiple linear regression analysis showed that weight,fever time before admission,white blood cells,body mass index,primary diagnosis,father's education,and diet before illness were the main influencing factors of nutritional risk of children in PICU(P<0.05).Conclusion:Children in PICU are in a state of high nutritional risk.It is suggested that children in PICU should carry out nutritional screening in a standardized manner,identify children with high nutritional risk and its influencing factors early.To actively conduct nutritional assessment and nutritional intervention could improve the clinical outcome of children in PICU.

Objective:To investigate whether intermittent fasting alleviates insulin resistance in a polycystic ovary syndrome(PCOS) mouse model through the regulation of autophagy.Methods:Fifty 3-week-old female C57BL/6J mice were randomly assigned into the following groups using a random number table: normal control(NC) group( n=10), maintained on a standard chow diet; high-fat diet(HFD) group( n=10) fed a diet with 60% of calories derived from fat; and PCOS model group( n=30), established by combining a HFD with dehydroepiandrosterone(DHEA) administration. Successful modeling was confirmed by disrupted estrous cycles, hyperandrogenism, and polycystic ovarian morphology. The PCOS model mice were further divided into three groups: PCOS group( n=9), PCOS with intermittent fasting group(PCOS+ IF, n=9), and PCOS with intermittent fasting plus the autophagy inhibitor 3-methyladenine(3-MA) group(PCOS+ IF+ 3-MA, n=9). Autophagy levels were assessed by detecting markers LC3 and p62 and observing autophagosomes via transmission electron microscopy. Glucose tolerance test(GTT) and insulin tolerance test(ITT) were performed, and the area under the curve(AUC) was calculated to evaluate insulin resistance. Western blotting was used to detect phosphorylation levels of phosphatidylinositol 3-kinase(PI3K), protein kinase B(Akt), mammalian target of rapamycin(mTOR), and p70S6 kiase(p70S6K). Results:Compared with the NC group, the PCOS model group showed absent estrous cycles, significantly elevated serum testosterone, sex hormone binding globulin, and luteinizing hormone(LH) levels( P<0.001), and polycystic ovarian changes on hematoxylin-eosin staining, confirming successful model establishment. Immunohistochemistry, transmission electron microscopy, and Western blotting demonstrated that autophagy levels were increased in the PCOS+ IF group compared with the PCOS group, while 3-MA administration reduced the intermittent fasting - induced autophagy. The AUC values for both GTT and ITT were significantly lower in the PCOS+ IF group than those in the PCOS group( P<0.001, P=0.003), but increased in the PCOS+ IF+ 3-MA group compared to the PCOS+ IF group( P<0.001, P=0.020). Western blotting analysis showed that phosphorylation levels of PI3K, Akt, mTOR, and p70S6K were significantly decreased in the PCOS+ IF group compared with the PCOS group( P=0.002, P=0.001, P=0.001, and P<0.001, respectively), and increased in the PCOS+ IF+ 3-MA group compared with the PCOS+ IF group( P=0.021, P=0.041, P=0.047, and P=0.024, respectively). Conclusions:Intermittent fasting alleviates insulin resistance in a PCOS mouse model through inhibitiing PI3K/Akt/mTOR signaling pathway and promoting autophagy.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

American military medical support equipment system digitalization were introduced in terms of connotation and development history,the development status of digitalization of four kinds of equipment was analyzed including the ambulance,hospital ship,medical helicopter and medical shelter,and the characteristics and implementation paths of American military medical support equipment system digitalization were described.The inspiration for the military medical support equipment system of the PLA were put forward from the aspects of top-level design,standard and specification,data and modeling,technology integration,construction of independent platform tools and personnel training.

Aim To investigate the mechanism of Guanxinning injection regulating cardiac immune mi-croenvironment to improve myocardial infarction in mice.Methods In this study,MI model was estab-lished by permanent ligation of left anterior descending coronary artery in mice.The mice were divided into five groups:sham operation group,model group,Guanxinning injection low dose group,Guanxinning in-jection high dose group and positive drug captopril group.Hearts were weighed,heart tissues were collect-ed,and Masson staining was used for pathological anal-ysis of heart tissues;immunofluorescence staining was used to detect apoptosis and CCL21 expression in the infarct border zone;flow cytometry was used to detect the proportion of immune cells in myocardial ischemia tissues and lymph nodes;PCR was used to detect CCL21 expression in heart and in vitro human lymphat-ic endothelial cells(HLEC).Results Compared with the model group,the low and high dose groups of Guanxinning injection significantly improved cardiac hypertrophy.Apoptosis in the border zone of myocardi-al infarction was reduced in the low and high dose groups of Guanxinning injection and captopril group.Compared with the model group,the proportion of leu-kocytes in the infarct border zone was dreduced and the proportion of CD4+T cells,Treg cells,and CD8+T cells in the mediastinal lymph nodes and infarct border zone of the heart was regulated in the low and high dose groups of Guanxinning injection;CCL21 secretion by the heart and lymphatic vessels increased.Conclu-sions Guanxinning injection can significantly improve cardiac hypertrophy and fibrosis in MI mice,reduce ap-optosis in the infarct border zone,and play a role in an-ti-myocardial ischemia injury by promoting CCL21 ex-pression in lymphatic vessels to regulate the proportion of mediastinal lymph nodes and cardiac T cells after myocardial infarction.

The emergence of CRISPR/Cas system has greatly promoted the progress in the field of gene editing,especially CRISPR/Cas9 system,which has become a core tool in biomedical research.Long noncoding RNAs(lncRNAs)play a key role in gene regulation,cell differentiation and the development of a variety of diseases.Especially in cancer research,lncRNAs have important application prospects as cancer biomarkers and therapeutic targets.However,lncRNAs are generally characterized by low abun-dance and poor conservation,which limits the study of their functions by traditional means.CRISPR/Cas9 technology provides an efficient,flexible and accurate tool for lncRNA research,which significantly accelerates the progress in this field.This paper first reviews the basic principles of CRISPR/Cas9 system and its wide applications in gene editing,including CRISPR knockout,knock-in,interference,activation and other functional systems.These technologies can not only screen key lncRNAs in specific biological processes,but also be used for gene function research to explore their roles in diseases.This article focu-ses on the analysis of CRISPR/Cas9 technology in the study of lncRNA functions,regulatory mecha-nisms,and its key applications in tumor research.In addition,the article also summarizes the methods of genome-wide screening by CRISPR/Cas9 to identify functional lncRNAs,and discusses the roles of these lncRNAs in cancer cell proliferation,migration,invasion and drug resistance.CRISPR/Cas9 knockout system can efficiently knock down lncRNA genes and reveal their specific functions in gene regulation.At the same time,CRISPR activation and interference technology provide a new idea for the research of non-coding genes,and further explore its clinical application in cancer and other diseases by regulating the expression level of lncRNAs.The article also discusses the potential of CRISPR technology in future ln-cRNA research,especially the progress in solving technical problems such as genome complexity,targe-ting efficiency and off-target effects.As mentioned in the review,CRISPR/Cas9 technology not only pro-vides a powerful tool for studying lncRNAs,but also provides new ideas and opportunities for developing new means of cancer diagnosis and treatment in the future.