ObjectiveTo explore the training path of rehabilitation therapy professionals in local colleges and universities under the background of New Medicine. MethodsTaking Jining Medical University as an example, combining the interdisciplinary integration, intelligent driving and people-oriented New Medicine attributes of rehabilitation therapy, this study focused on the current practical problems in rehabilitation education, accurately aligned with the requirements of new medicine construction, reshaped the curriculum system with new concepts, empowered practical innovation with new technologies, and cultivated humanistic literacy with new connotations. By deeply integrating digital construction with educational practice, it carried out the construction and practice of the New Medicine talent training model in rehabilitation therapy, helping students form a stereoscopic knowledge structure, possess the ability to apply intelligent rehabilitation technology and solve complex rehabilitation problems, and become high-quality rehabilitation therapy talents with both morality and ability. ResultsThe overall construction of the rehabilitation therapy major established a model of Dual fusion foundation, Three element empowerment and Three dimensional soul casting, including reform and innovation in curriculum system, practical mode and moral education mechanism. It has formed a health oriented "vertical and horizontal integration-discipline fusion" dual-fusion stereoscopic curriculum system, an intelligent led "theory and practice-science and education-industry and education" three element integration practical mode, and a confucian medical culture "curriculum-practice-evaluation" three-dimensional integrated moral education mechanism. Through practical testing, this model achieved significant results and was widely recognized, including a significant improvement in the quality of talent cultivation, prominent achievements in resource construction, and prominent achievements in health services, providing strong support for the construction of regional rehabilitation medical systems. ConclusionThe reform of the rehabilitation treatment talent training model at Jining Medical University under the background of New Medicine provides a replicable and promotable practical paradigm for the training of rehabilitation talents in similar universities through reshaping the curriculum system, strengthening practical innovation, and cultivating humanistic literacy.

ObjectiveTo explore the training path of rehabilitation therapy professionals in local colleges and universities under the background of New Medicine. MethodsTaking Jining Medical University as an example, combining the interdisciplinary integration, intelligent driving and people-oriented New Medicine attributes of rehabilitation therapy, this study focused on the current practical problems in rehabilitation education, accurately aligned with the requirements of new medicine construction, reshaped the curriculum system with new concepts, empowered practical innovation with new technologies, and cultivated humanistic literacy with new connotations. By deeply integrating digital construction with educational practice, it carried out the construction and practice of the New Medicine talent training model in rehabilitation therapy, helping students form a stereoscopic knowledge structure, possess the ability to apply intelligent rehabilitation technology and solve complex rehabilitation problems, and become high-quality rehabilitation therapy talents with both morality and ability. ResultsThe overall construction of the rehabilitation therapy major established a model of Dual fusion foundation, Three element empowerment and Three dimensional soul casting, including reform and innovation in curriculum system, practical mode and moral education mechanism. It has formed a health oriented "vertical and horizontal integration-discipline fusion" dual-fusion stereoscopic curriculum system, an intelligent led "theory and practice-science and education-industry and education" three element integration practical mode, and a confucian medical culture "curriculum-practice-evaluation" three-dimensional integrated moral education mechanism. Through practical testing, this model achieved significant results and was widely recognized, including a significant improvement in the quality of talent cultivation, prominent achievements in resource construction, and prominent achievements in health services, providing strong support for the construction of regional rehabilitation medical systems. ConclusionThe reform of the rehabilitation treatment talent training model at Jining Medical University under the background of New Medicine provides a replicable and promotable practical paradigm for the training of rehabilitation talents in similar universities through reshaping the curriculum system, strengthening practical innovation, and cultivating humanistic literacy.

ObjectiveTo explore the training path of rehabilitation therapy professionals in local colleges and universities under the background of New Medicine. MethodsTaking Jining Medical University as an example, combining the interdisciplinary integration, intelligent driving and people-oriented New Medicine attributes of rehabilitation therapy, this study focused on the current practical problems in rehabilitation education, accurately aligned with the requirements of new medicine construction, reshaped the curriculum system with new concepts, empowered practical innovation with new technologies, and cultivated humanistic literacy with new connotations. By deeply integrating digital construction with educational practice, it carried out the construction and practice of the New Medicine talent training model in rehabilitation therapy, helping students form a stereoscopic knowledge structure, possess the ability to apply intelligent rehabilitation technology and solve complex rehabilitation problems, and become high-quality rehabilitation therapy talents with both morality and ability. ResultsThe overall construction of the rehabilitation therapy major established a model of Dual fusion foundation, Three element empowerment and Three dimensional soul casting, including reform and innovation in curriculum system, practical mode and moral education mechanism. It has formed a health oriented "vertical and horizontal integration-discipline fusion" dual-fusion stereoscopic curriculum system, an intelligent led "theory and practice-science and education-industry and education" three element integration practical mode, and a confucian medical culture "curriculum-practice-evaluation" three-dimensional integrated moral education mechanism. Through practical testing, this model achieved significant results and was widely recognized, including a significant improvement in the quality of talent cultivation, prominent achievements in resource construction, and prominent achievements in health services, providing strong support for the construction of regional rehabilitation medical systems. ConclusionThe reform of the rehabilitation treatment talent training model at Jining Medical University under the background of New Medicine provides a replicable and promotable practical paradigm for the training of rehabilitation talents in similar universities through reshaping the curriculum system, strengthening practical innovation, and cultivating humanistic literacy.

Tuberculosis (TB), a chronic infectious disease caused by Mycobacterium tuberculosis, is primarily airborne and remains a global health problem, especially in resource-limited countries and regions. The emergence of drug resistance in M. tuberculosis has rendered the existing means ineffective in the treatment of TB. Therefore, research in new therapeutic directions has become imperative. In this review, we outline functional peptides in terms of the mechanisms of action, anti-TB attempts, advantages and disadvantages, and latest advances, aiming to analyze the research progress in anti-TB peptides. Furthermore, we investigate the potential applications of bioactive compounds found in traditional Chinese Medicine within the context of peptides.

ObjectiveTo construct a machine learning model combining two-dimensional shear wave elastography （2D-SWE） and serological markers， and to investigate its clinical value in differentiating primary biliary cholangitis （PBC） from overlap syndrome （OS）. MethodsA total of 199 patients with pathologically confirmed PBC or OS in Nantong Third People’s Hospital from January 2021 to December 2025 were retrospectively enrolled， with 125 patients in the PBC group and 74 in the OS group. The patients were randomly divided into a training set with 139 patients and a test set with 60 patients at a ratio of 7∶3. Related data were collected， including serological markers， conventional two-dimensional ultrasound parameters， and 2D-SWE parameters （including velocity of shear wave ［VS］ and liver fibrosis index ［LFI］）. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. The univariate and multivariate Logistic regression analyses were used to identify independent predictive factors， which were then incorporated into six machine learning models， and 5-fold cross-validation was used for optimization of parameters. The indicators including the area under the receiver operating characteristic curve （AUC） were compared in the test set to determine the best model， and the SHapley additive exPlanations （SHAP） analysis was used for model interpretation. ResultsFemale patients accounted for 87.8% in the OS group and 79.2% in the PBC group. Compared with the PBC group， the OS group had significantly higher age， VS， LFI， splenic area， aspartate aminotransferase， total bilirubin， prothrombin time， immunoglobulin G （IgG）， and immunoglobulin M （Z=-2.883， -6.524， -4.000， -3.061， -2.194， -2.372， -4.079， -6.964， and -2.709， all P<0.05） and a significantly lower platelet count （Z=4.098， P<0.001）， and there were also significant differences between the two groups in the proportion of patients with positive anti-nuclear antibody， fibrosis stage， and inflammation grade （χ²=3.458， 63.198， and 101.038， all P<0.05）. Variables without multicollinearity were included in the regression analysis， and the multivariate Logistic regression analysis showed that VS （odds ratio ［OR］=4.503， 95% confidence interval ［CI］： 1.698 — 11.943， P=0.003）， LFI （OR=1.813， 95%CI： 1.050 — 3.132， P=0.033）， and IgG （OR=1.121， 95%CI： 1.026 — 1.226， P=0.012） were independent predictive factors for differentiating PBC from OS. Six machine learning models were constructed based on these variables， among which the logistic regression model showed the best predictive performance in the test set， with an AUC of 0.881 （95%CI： 0.788 — 0.974）， a sensitivity of 0.731， and a specificity of 0.794. The SHAP analysis showed that IgG contributed the most to model prediction. ConclusionThe noninvasive multimodal machine learning model combining 2D-SWE parameters （VS， LFI） and serum IgG can effectively differentiate PBC from OS， providing a reference for clinical decision-making regarding the need for liver biopsy.

To address issues such as loss of detailed information, blurred target boundaries, and unclear structural hierarchy in medical image fusion, this paper proposes an adaptive feature medical image fusion network based on a full-scale diffusion model. First, a region-level feature map is generated using a kernel-based saliency map to enhance local features and boundary details. Then, a full-scale diffusion feature extraction network is employed for global feature extraction, alongside a multi-scale denoising U-shaped network designed to fully capture cross-layer information. A multi-scale feature integration module is introduced to reinforce texture details and structural information extracted by the encoder. Finally, an adaptive fusion scheme is applied to progressively fuse region-level features, global features, and source images layer by layer, enhancing the preservation of detail information. To validate the effectiveness of the proposed method, this paper validates the proposed model on the publicly available Harvard dataset and an abdominal dataset. By comparing with nine other representative image fusion methods, the proposed approach achieved improvements across seven evaluation metrics. The results demonstrate that the proposed method effectively extracts both global and local features of medical images, enhances texture details and target boundary clarity, and generates fusion image with high contrast and rich information, providing more reliable support for subsequent clinical diagnosis.
Humans ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Diagnostic Imaging/methods* ; Image Interpretation, Computer-Assisted/methods*

G protein-coupled receptors (GPCRs) are significant drug targets, but their potential in cancer therapy remains underexplored. Conventional GPCR agonists or antagonists have shown limited effectiveness in cancer treatment, necessitating new GPCR-targeting strategies for more effective therapies. This study discovers that Yersinia pestis LcrV, a crucial linker protein for plague infection, acts as a biased agonist of a GPCR, the formyl peptide receptor 1 (FPR1). The LcrV protein induces unique conformational changes in FPR1, resulting in G proteins being activated in a distinctive state without subunit dissociation. This leads to a biased signaling profile characterized by cyclic adenosine monophosphate (cAMP) responses and β-arrestin2 recruitment, but not calcium mobilization. In FPR1-expressing triple-negative breast cancer (TNBC) cells, LcrV bi-directionally modulates intracellular signaling pathways, downregulating extracellular signal-regulated kinases (ERK1/2) and Akt pathways while upregulating Jun N-terminal kinase (JNK) and p38 pathways. This dual modulation results in cell cycle arrest and the inhibition of TNBC cell proliferation. In TNBC xenograft mouse models, long-term LcrV treatment inhibits tumor growth more effectively than a conventional FPR1 antagonist. Additionally, LcrV treatment reprograms tumor cells by reducing stemness-associated proteins OCT4 and c-MYC. Our findings highlight the potential of biased GPCR agonists as a novel GPCR-targeting strategy for cancer treatment.

Objective:To evaluate the diagnostic efficacy of B-type natriuretic peptide(BNP)combined with the Evaluation of Guidelines in Syncope Study(EGSYS)score for cardiogenic syncope(CS), and to provide evidence for rapid clinical identification of high-risk patients.Methods:We retrospectively analyzed 366 patients with syncope hospitalized in the department of cardiovascular medicine of Beijing Hospital from January 1, 2016, to December 31, 2022.Based on the international guideline diagnostic criteria, the patients were categorized into four groups: neutrally mediated reflex syncope(NMS)group, orthostatic hypotension(OH)group, cardiogenic syncope(CS)group, and syncope of unknown origin(US)group.BNP levels were measured at admission and EGSYS scores were calculated.Receiver operating characteristic(ROC)curve analysis was performed to assess the diagnostic efficacy of individual and combined indices for CS.Results:A total of 366 syncope patients were included, among which 70 patients(19.1%)were diagnosed with NMS, 25 patients(6.8%)with OH, 44 patients(12.0%)with CS, and 227 patients(62.0%)with US.Patients in the CS group had significantly higher BNP levels and EGSYS scores compared to those in the NMS, OH, and US groups(all P<0.001). The AUC of EGSYS score for diagnosing CS was 0.783(95% CI: 0.711-0.855), while the AUC of BNP level for diagnosing CS was 0.805(95% CI: 0.727-0.884). When BNP level was combined with EGSYS score, diagnostic performance was significantly improved, with the AUC increasing to 0.855(95% CI: 0.792-0.918). Conclusions:The combination of BNP and EGSYS score significantly can improve the diagnostic accuracy of cardiogenic syncope, providing a practical diagnostic strategy for the early identification of high-risk syncope patients in clinical practice.

The investigator-initiated trials （IIT）， as a widely existing form of clinical research both domestically and internationally， have attracted the attention of governments around the world due to the potential legal risks and issues they may cause， and the trend of legal supervision has gradually strengthened. The legal regulation of IIT in China is still in its early stages， with numerous legal issues that need to be clarified and sorted out. Based on the domestic and international legal reviews of IIT， this paper systematically sorted out the current situation of legal supervision of IIT in China and examined the existing issues， including weak legislative rules， incomplete regulatory systems， imperfect protection rules for research participants and informed consent systems， inadequate regulation of conflicts of interest management， and lax legal supervision of ethical review. Furthermore， this paper proposed suggestions for legal regulation of IIT from three perspectives， including strengthening legislation and emphasizing regulation， improving the mechanism for protecting research participants’ rights and interests， and balancing the legalization of IIT and the scientific development of clinical research， with a view to providing references for legal regulatory paths of IIT in China.