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 Magnetoreception, the remarkable ability of diverse animals to sense and utilize the geomagnetic field for orientation and navigation, remains a molecularly unresolved mystery in sensory biology. The putative magnetoreceptor (MagR, previously known as IscA1) is a highly conserved iron-sulfur protein implicated in both magnetoreception and iron metabolism; however, the functional diversity among its cross-species homologs remains poorly understood. Cellular morphology is a key genetically determined trait that can be altered through genetic or environmental modifications—a process known as cell morphology engineering. Constructing engineered cells with specific morphological features and magnetic sensitivity to achieve remote, non-invasive magnetic modulation represents a crucial goal in this field with significant application potential. Therefore, this study aims to systematically investigate the effects of MagR heterologous expression on bacterial morphology and magnetic sensing capabilities, screen for MagR-based magnetically sensitive morphology engineering pathways, and reveal the underlying molecular mechanisms. Methods We systematically screened 28 MagR homologous genes from diverse prokaryotic and animal taxa to evaluate their expression and corresponding phenotypic effects in Escherichia coli (E. coli). To compare the differential magnetic responses among bacteria expressing various recombinant MagR proteins, we utilized high-throughput automated bright-field microscopic imaging and scanning electron microscopy (SEM). Furthermore, comprehensive biochemical and biophysical characterizations of iron and iron-sulfur cluster binding were performed using Ferrozine colorimetric assays, electron paramagnetic resonance (EPR) spectroscopy, ultraviolet-visible (UV-Vis) absorption, and circular dichroism (CD) spectroscopy. Additionally, 100 mT static magnetic field (SMF) exposure experiments were conducted to assess magnetically tunable phenotypes, while the intrinsic magnetic properties of purified MagR proteins were directly measured using a superconducting quantum interference device (SQUID) magnetometer. Results Our results demonstrated that the heterologous expression of MagR homologs induced varying degrees of bacterial filamentation. From this comprehensive screen, two distinct morphological patterns were identified: hydra (Hydra vulgaris) MagR (hyMagR) promoted uniform cell elongation and filamentation, exhibiting robust magnetic sensitivity manifested as significantly enhanced filamentation under the 100 mT SMF. In contrast, pigeon (Columba livia) MagR (clMagR) induced only low-frequency, extreme filamentation (sporadically exceeding 80 μm) with a relatively weaker magnetic morphological response. Mechanistically, our data unambiguously proved that these phenotypic differences are primarily driven by distinct iron redox preferences rather than total cellular iron accumulation. Specifically, hyMagR preferentially binds ferrous iron (Fe²⁺), whereas clMagR favors ferric iron (Fe³⁺) and forms more stable iron-sulfur clusters. Intriguingly, although SQUID magnetometry showed that purified clMagR exhibited approximately five-fold higher mass magnetic susceptibility than hyMagR, its cellular magnetic response was weaker. We hypothesize that the Fe²⁺-preferred intracellular environment associated with hyMagR overexpression primes the cell for enhanced generation of reactive oxygen species (ROS) via the Fenton reaction. Exposure to an SMF synergizes with this primed redox state, triggering the bacterial SOS response and upregulating cell division inhibitors to efficiently induce uniform filamentation. Conclusion Our findings identify the Fe²⁺/Fe³⁺ redox state as a critical determinant of MagR-mediated morphological remodeling and magnetic responsiveness. This discovery suggests a potential strategy for engineering magnetically responsive cellular systems for synthetic biology applications, and provides a plausible framework, which potentially combines intrinsic protein magnetism with redox-state modulation, for further investigating the evolutionary mechanisms of MagR-mediated magnetoreception.

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 Magnetoreception, the remarkable ability of diverse animals to sense and utilize the geomagnetic field for orientation and navigation, remains a molecularly unresolved mystery in sensory biology. The putative magnetoreceptor (MagR, previously known as IscA1) is a highly conserved iron-sulfur protein implicated in both magnetoreception and iron metabolism; however, the functional diversity among its cross-species homologs remains poorly understood. Cellular morphology is a key genetically determined trait that can be altered through genetic or environmental modifications—a process known as cell morphology engineering. Constructing engineered cells with specific morphological features and magnetic sensitivity to achieve remote, non-invasive magnetic modulation represents a crucial goal in this field with significant application potential. Therefore, this study aims to systematically investigate the effects of MagR heterologous expression on bacterial morphology and magnetic sensing capabilities, screen for MagR-based magnetically sensitive morphology engineering pathways, and reveal the underlying molecular mechanisms. Methods We systematically screened 28 MagR homologous genes from diverse prokaryotic and animal taxa to evaluate their expression and corresponding phenotypic effects in Escherichia coli (E. coli). To compare the differential magnetic responses among bacteria expressing various recombinant MagR proteins, we utilized high-throughput automated bright-field microscopic imaging and scanning electron microscopy (SEM). Furthermore, comprehensive biochemical and biophysical characterizations of iron and iron-sulfur cluster binding were performed using Ferrozine colorimetric assays, electron paramagnetic resonance (EPR) spectroscopy, ultraviolet-visible (UV-Vis) absorption, and circular dichroism (CD) spectroscopy. Additionally, 100 mT static magnetic field (SMF) exposure experiments were conducted to assess magnetically tunable phenotypes, while the intrinsic magnetic properties of purified MagR proteins were directly measured using a superconducting quantum interference device (SQUID) magnetometer. Results Our results demonstrated that the heterologous expression of MagR homologs induced varying degrees of bacterial filamentation. From this comprehensive screen, two distinct morphological patterns were identified: hydra (Hydra vulgaris) MagR (hyMagR) promoted uniform cell elongation and filamentation, exhibiting robust magnetic sensitivity manifested as significantly enhanced filamentation under the 100 mT SMF. In contrast, pigeon (Columba livia) MagR (clMagR) induced only low-frequency, extreme filamentation (sporadically exceeding 80 μm) with a relatively weaker magnetic morphological response. Mechanistically, our data unambiguously proved that these phenotypic differences are primarily driven by distinct iron redox preferences rather than total cellular iron accumulation. Specifically, hyMagR preferentially binds ferrous iron (Fe²⁺), whereas clMagR favors ferric iron (Fe³⁺) and forms more stable iron-sulfur clusters. Intriguingly, although SQUID magnetometry showed that purified clMagR exhibited approximately five-fold higher mass magnetic susceptibility than hyMagR, its cellular magnetic response was weaker. We hypothesize that the Fe²⁺-preferred intracellular environment associated with hyMagR overexpression primes the cell for enhanced generation of reactive oxygen species (ROS) via the Fenton reaction. Exposure to an SMF synergizes with this primed redox state, triggering the bacterial SOS response and upregulating cell division inhibitors to efficiently induce uniform filamentation. Conclusion Our findings identify the Fe²⁺/Fe³⁺ redox state as a critical determinant of MagR-mediated morphological remodeling and magnetic responsiveness. This discovery suggests a potential strategy for engineering magnetically responsive cellular systems for synthetic biology applications, and provides a plausible framework, which potentially combines intrinsic protein magnetism with redox-state modulation, for further investigating the evolutionary mechanisms of MagR-mediated magnetoreception.

Objectives:To investigate the predictive value of Murray's law-based quantitative flow ratio(μQFR)in side branches for long-term clinical prognosis in patients with non-left main bifurcation lesions who underwent simple main branch stenting,and to provide a potential functional assessment standard for intervention decision-making on coronary bifurcation lesions.Methods:A retrospective analysis was conducted in 408 patients with non-left main bifurcation lesions who underwent simple main branch stenting at Lianyungang First People's Hospital and Nanjing First Hospital between July 2018 and January 2021.The study utilized third-generation QFR software to analyze pre-and post-procedure anatomical and functional parameters of the target lesion's main branch and key branches.The primary endpoint was target vessel failure(TVF)events during the 3-year follow-up.Patients were stratified into TVF and non-TVF groups.Baseline characteristics,procedural data,and pre-/post-procedural parameters of target vessels were compared between groups.Multivariable Cox regression was performed to identify predictors of TVF.Diagnostic efficacy of predictors was evaluated using area under the receiver operating characteristic(ROC)curve(AUC)with DeLong's method for comparison.Patients were dichotomized based on the optimal cutoffof post-procedural side branch μQFR,with TVF incidence rates compared via Cox regression and Kaplan-Meier analysis.Results:During 3-year follow-up,54 patients(13.2%)experienced TVF(TVF group),data were compared with 354 patients(86.76%)without TVF(non-TVF group).The TVF group showed higher post-procedural side branch diameter stenosis([32.93±17.80]%vs.[22.62±11.96]%,P<0.001)and lower μQFR(0.80±0.10 vs.0.89±0.07,P<0.001).Multivariate Cox regression identified higher post-procedural side branch μQFR as an independent protective factor against 3-year TVF(per 0.01 increase:HR=0.903,95%CI:0.850-0.959,P<0.001).ROC curves indicated that post-procedural side branch μQFR had moderate diagnostic efficacy for predicting 3-year TVF(AUC=0.769,95%CI:0.678-0.861,P<0.001),with a significantly higher AUC value than post-operative side branch area stenosis and minimal lumen diameter(both P<0.001),the optimal cutoffvalue was 0.84.Multivariate Cox regression and Kaplan-Meier survival analysis revealed markedly higher 3-year TVF rates in patients with μQFR≤0.84 compared to patients with μQFR>0.84(HR=4.007,95%CI:2.342-6.855,P<0.001;28.3%vs.7.9%,log-rank P<0.001).Conclusions:For patients with bifurcation lesions not involving the left main,the immediate post-procedural side branch μQFR could better predict 3-year TVF than anatomical indices.Maintaining post-stenting side branch μQFR>0.84 may optimize clinical outcomes when using a single-stent strategy.

Background::The increasing incidence of inflammatory bowel disease (IBD) presents significant medical and societal challenges. A well-designed IBD database is crucial for both epidemiological studies and clinical management. However, inconsistencies between regional databases hinder cross-institutional and international research, especially between Eastern and Western societies.Methods::We developed a new IBD database, the 301 IBD database, integrating the IBD clinical characteristics from the Penn IBD database (USA) and the latest IBD guidelines and consensus and clinical practices of the Chinese PLA General Hospital (PLAGH). We applied this database to analyze clinical data of IBD inpatients at PLAGH from 2008 to 2023.Results::The 301 IBD database contains 490 items in 6 sections including demographic characteristics, personal history, clinical phenotype, disease activity, laboratory tests and examinations, and treatment. Features of the 301 IBD database include inpatient focus, biochemical indicators and opportunistic infection focus, and more about ulcerative colitis (UC)-associated complications. Single-center analysis revealed an increasing hospitalization trend, from 2.35% in 2008 to 3.94% in 2023. We found that the clinical characteristics of our UC inpatients are predominantly male (62.5%), extensive lesions (55.1%), low usage of biologics (4.1%), and a high incidence of UC-CRC (3.0%). The clinical characteristics of CD inpatients included male predominance (68.39%), early onset age (35.43 ± 14.75-year-old), and high rate of surgery (25.81%).Conclusion::The 301 IBD database, integrating Eastern and Western clinical data, provides a valuable tool for IBD clinical research. Future international, multicenter collaborations are expected to further enhance its utility.

Objective:This study aimed to integrate RNA-seq data to identify key genes associated with macrophage-ferroptosis and develop a prognostic model for hepatocellular carcinoma(HCC).Methods:We retrieved a dataset from the GEO database containing transcriptome data and clinical information for 163 samples.Macrophage-related genes were identified using WGCNA and immune infiltration analyses.Ferroptosis-related genes from the FerrDbV2 database were intersected with differentially expressed genes to obtain significant macrophage-ferroptosis-related genes.Hub genes were screened via protein interaction network construction,and key genes were identified using four machine learning algorithms.These genes exhibited significant expression differences between cancer and normal tissues and were closely linked to patient prognosis.ROC curve and KM survival analyses were performed,and expression levels were validated at the transcriptome and proteome levels.Results:Four key genes RRM2,KIF20A,PCK2,and PDK4 were identified and evaluated.RRM2 and KIF20A demonstrated high importance in classification prediction models and reliable performance in ROC and KM analyses(AUC＞0.9,P＜0.05).These genes regulate cancer cell proliferation/survival and macrophage polarization/function,influencing the tumor microenvironment and HCC progression.Conclusion:RRM2 and KIF20A regulate cancer cell proliferation and survival,modulate macrophage polarization and function,and influence the immune response in the tumor microenvironment.They can serve as prognostic biomarkers and potential immunotherapy targets for hepatocellular carcinoma.

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 observe the changes of invariant natural killer T(iNK T)cells in visceral adipose tissue and blood lipids of high-fat diet-fed mice,and to analyze the correlation between iNK T cells and lipid metabolism.Methods Fifty-two C57BL/6 mice were selected as the high-fat diet group,and 51 C57BL/6 mice as the normal control group.The high-fat diet intervention lasted for 12 weeks.At weeks 1,4,8,and 12,the epididymal and perirenal fats of mice in both groups were collected and weighed to record the visceral fat mass(VFM),and the changes in body fat content(BFC)were calculated.Flow cytometry and laser scanning confocal microscopy were used to detect the changes of invariant natural killer T(iNK T)cells in visceral adipose tissue.An automatic biochemical analyzer was used to measure the lipid levels in mice,and the correlations of iNKT cells in visceral adipose tissue with VFM,BFC,and serum lipid levels were analyzed.Results At 12 weeks after high-fat diet feeding,the body weight,VFM,BFC,serum total cholesterol(TC),triglyceride(TG)and high-density lipoprotein cholesterol(HDL-C)increased significantly,while the content of invariant natural killer T(iNK T)cells in visceral adipose tissue decreased obviously in the high-fat diet group,as compared with the control group(P＜0.01).The iNKT cell number in visceral adipose tissue of mice was negatively correlated with VFM,BFC,serum HDL-C and serum TG(r=-0.293,-0.289,-0.337,-0.199,P＜0.05),and was not correlated with serum TC and LDL-C(r=-0.122,-0.082,P＞0.05).Conclution VFM is increased and iNK T cell number is decreased in in adipose tissue of high-fat diet-fed mice.The number of iNK T cells is negatively correlated with VFM,BFC,serum HDL-C and TG.