By reviewing the physical biological research on the activation of acupoint effects by acupuncture， this paper explains the activation mechanism from the perspective of the generation and transmission of mechanical signals caused by acupuncture， and reveals the physical-chemical coupling processes in the acupoint microenvironment. Future research should focus on locally mechanosensitive cells， further exploring how acupuncture mechanical signals trigger dynamic changes in cells and molecules in the acupoints， and the physical-chemical information transduction mechanism， which will provide scientific evidence for the acupoint activation during acupuncture. Related studies will contribute to a deeper understanding of the scientific principles behind acupuncture and promote its clinical application and development.

Dermatofibrosarcoma protuberans (DFSP) is a rare, low-grade malignant cutaneous tumor characterized by a high propensity for local recurrence, yet low rates of metastasis and mortality. The pathogenesis of DFSP is primarily associated with a chromosomal translocation t(17; 22)(q22; q13), which leads to the fusion of the platelet-derived growth factor subunit B gene with the collagen type I alpha 1 chain gene in the majority of cases. Diagnosis relies on histopathological examination, supported by imaging studies for comprehensive assessment. Surgical resection remains the cornerstone of treatment; however, it is frequently complicated by a high risk of local recurrence. Recent advances in radiotherapy and targeted therapeutic strategies offer promising avenues for reducing recurrence rates and improving patient survival. Nevertheless, the pathological heterogeneity and diverse clinical manifestations of DFSP pose considerable challenges to the development and implementation of individualized treatment approaches. Thus, further fundamental research and refinement of clinical management are imperative to advance the diagnosis and therapy of DFSP.

Objective:To construct and evaluate a radiomics model for predicting perineural invasion in patients with intrahepatic cholangiocarcinoma (ICC).Methods:Clinical data of 144 patients with ICC undergoing surgery in the People’s Hospital of Zhengzhou University ( n=113) and the Affiliated Cancer Hospital of Zhengzhou University ( n=31) from January 2018 to June 2023 were retrospectively analyzed, including 80 males and 64 females, aged (58.8±10.1) years. The patients were randomly divided into a training set ( n=100) and a test set ( n=44) at a ratio of 7: 3. The former set was used to build the model for predicting perineural invasion, and the latter was used to evaluate the model. Enhanced CT images and clinical data of the patients were collected, and features related to perineural invasion were screened. A light gradient boosting machine was used to construct an imaging genomics model. The model was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results:Univariate and multivariate logistic regression analysis showed that none of the clinical features were associated with neural invasion in ICC patients (all P>0.05). Six, 25, 32, and 37 radiomics features were obtained by screening the intratumoral, 2 mm peritumoral, 5 mm peritumoral, and 8 mm peritumoral regions, respectively. The area under the ROC curve for predicting perineural invasion in ICC patients was 0.849 (95% CI: 0.774-0.923) in the training set and 0.745 (95% CI: 0.597-0.894) in the test set for the intratumoral model, 0.966 (95% CI: 0.938-0.995) and 0.750 (95% CI: 0.604-0.896) for the 5mm peritumoral model, 0.936 (95% CI: 0.892-0.980) and 0.792 (95% CI: 0.644-0.939) for the 2mm peritumoral model, and 0.961 (95% CI: 0.929-0.992) and 0.689 (95% CI: 0.526-0.853) for the 8mm peritumoral model. The area under the ROC curve, accuracy, sensitivity, and specificity of the combined intratumoral and 5mm peritumoral model for predicting perineural invasion were 0.927 (95% CI: 0.878-0.976), 88.0%, 84.5%, and 89.8% in the training set, and 0.849 (95% CI: 0.737-0.960), 77.3%, 85.2%, and 72.0% in the test set, respectively. The calibration curve showed a deviation between the calibration curve of the combined intratumoral and 5mm peritumoral model and the ideal line, but it could achieve basic consistency. DCA showed that when the threshold was between 0.18 and 0.70, the combined intratumoral and 5mm peritumoral model could bring clinical net benefit to patients when predicting neural invasion. Conclusion:The intratumoral and 5mm peritumoral imaging genomics model based on enhanced CT features can effectively predict neural invasion and offer clinical benefits in patients with ICC.

Recently,diffusion models have emerged as a promising paradigm for molecular design and optimization.However,most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geom-etries,with limited research on molecular sequence diffusion models.The International Union of Pure and Applied Chemistry(IUPAC)names are more akin to chemical natural language than the simplified molecular input line entry system(SMILES)for organic compounds.In this work,we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language(SMILES)and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language.We propose DiffIUPAC,a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings.Evaluation results demonstrate that our model out-performs existing methods and successfully captures the semantic rules of both chemical languages.Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints.Additionally,to illustrate the model's applicability in drug design,we conducted case studies in functional group editing,analogue design and linker design.

Dermatofibrosarcoma protuberans (DFSP) is a rare, low-grade malignant cutaneous tumor characterized by a high propensity for local recurrence, yet low rates of metastasis and mortality. The pathogenesis of DFSP is primarily associated with a chromosomal translocation t(17; 22)(q22; q13), which leads to the fusion of the platelet-derived growth factor subunit B gene with the collagen type I alpha 1 chain gene in the majority of cases. Diagnosis relies on histopathological examination, supported by imaging studies for comprehensive assessment. Surgical resection remains the cornerstone of treatment; however, it is frequently complicated by a high risk of local recurrence. Recent advances in radiotherapy and targeted therapeutic strategies offer promising avenues for reducing recurrence rates and improving patient survival. Nevertheless, the pathological heterogeneity and diverse clinical manifestations of DFSP pose considerable challenges to the development and implementation of individualized treatment approaches. Thus, further fundamental research and refinement of clinical management are imperative to advance the diagnosis and therapy of DFSP.

Objective:To construct and evaluate a radiomics model for predicting perineural invasion in patients with intrahepatic cholangiocarcinoma (ICC).Methods:Clinical data of 144 patients with ICC undergoing surgery in the People’s Hospital of Zhengzhou University ( n=113) and the Affiliated Cancer Hospital of Zhengzhou University ( n=31) from January 2018 to June 2023 were retrospectively analyzed, including 80 males and 64 females, aged (58.8±10.1) years. The patients were randomly divided into a training set ( n=100) and a test set ( n=44) at a ratio of 7: 3. The former set was used to build the model for predicting perineural invasion, and the latter was used to evaluate the model. Enhanced CT images and clinical data of the patients were collected, and features related to perineural invasion were screened. A light gradient boosting machine was used to construct an imaging genomics model. The model was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results:Univariate and multivariate logistic regression analysis showed that none of the clinical features were associated with neural invasion in ICC patients (all P>0.05). Six, 25, 32, and 37 radiomics features were obtained by screening the intratumoral, 2 mm peritumoral, 5 mm peritumoral, and 8 mm peritumoral regions, respectively. The area under the ROC curve for predicting perineural invasion in ICC patients was 0.849 (95% CI: 0.774-0.923) in the training set and 0.745 (95% CI: 0.597-0.894) in the test set for the intratumoral model, 0.966 (95% CI: 0.938-0.995) and 0.750 (95% CI: 0.604-0.896) for the 5mm peritumoral model, 0.936 (95% CI: 0.892-0.980) and 0.792 (95% CI: 0.644-0.939) for the 2mm peritumoral model, and 0.961 (95% CI: 0.929-0.992) and 0.689 (95% CI: 0.526-0.853) for the 8mm peritumoral model. The area under the ROC curve, accuracy, sensitivity, and specificity of the combined intratumoral and 5mm peritumoral model for predicting perineural invasion were 0.927 (95% CI: 0.878-0.976), 88.0%, 84.5%, and 89.8% in the training set, and 0.849 (95% CI: 0.737-0.960), 77.3%, 85.2%, and 72.0% in the test set, respectively. The calibration curve showed a deviation between the calibration curve of the combined intratumoral and 5mm peritumoral model and the ideal line, but it could achieve basic consistency. DCA showed that when the threshold was between 0.18 and 0.70, the combined intratumoral and 5mm peritumoral model could bring clinical net benefit to patients when predicting neural invasion. Conclusion:The intratumoral and 5mm peritumoral imaging genomics model based on enhanced CT features can effectively predict neural invasion and offer clinical benefits in patients with ICC.

Objective To systematically analyze the risk prediction instruments for central line associated bloodstream infection in ICU patients,with a view to provide references for clinical practice.Methods The PubMed,Embase,Web of Science,Cochrane Library,CIN AHL,CNKI,WanFang,VIP and CBM Database were searched from inception to May 2024.There were 2 researchers who independently screened the literature,extracted the information,and assessed the risk of bias and applicability of the included literature.Results 11 studies were involved in the final review,involving 9 risk prediction models and 2 risk assessment tables,9 of which validated the predictive efficacy or reliability and validity of the instruments.Conclusion The risk prediction instruments for central line associated bloodstream infection in ICU patients had good predictive efficacy and applicability,but the overall risk of bias was high.It is recommended that further examination,verification the existing instruments should be conducted,or to build a prediction instrument with low risk of bias and high applicability.

Objective To investigate the relationship between sleep disorders and coronary heart disease through big data combined with Mendelian randomization analysis.Methods Data from 2005 to 2018 National Health and Nutrition Examination Survey in the United States were utilized.Logistic regression analysis was employed to evaluate the association between sleep disorders and coronary heart disease,while analyzing relevant influencing factors.A two-sample Mendelian randomization approach was implemented using Genome-Wide Association Studies to establish causal relationships.Results Logistic regression analysis demonstrated a significant association between sleep disorders and coronary heart disease(P＜0.001),with the neutrophil-to-lymphocyte ratio serving as a mediating factor in this relationship(P＜0.001).Mendelian randomization analysis revealed a positive correlation between sleep disorders and coronary heart disease(OR=1.030,95％CI:1.01-1.04).Conclusion Sleep disorders can increase the risk of coronary heart disease by activating inflammatory factors.

In 2025,the International Association of Pancreatology(IAP),in collaboration with the American Pancreatic Association,European Pancreatic Club,Indian Pancreas Club,and Japan Pancreas Society,released the International Association of Pancreatology revised guidelines on acute pancreatitis 2025.This edition represents a comprehensive revision of the 2013 guidelines,based on high-quality evidence accumulated over the past decade,particularly randomized controlled trials.The guidelines encompass 18 key areas-including pain management,fluid therapy,nutritional support,management of infected necrosis,complication control,discharge and follow-up,and recurrence prevention-offering a total of 96 recommendations that emphasize individualized treatment.These updates provide important guidance for standardizing clinical practice and improving outcomes in acute pancreatitis,while also indicating future research directions such as the development of targeted therapies.However,some recommendations remain limited by lower evidence quality,uncertain applicability in specific clinical settings,and insufficient consideration of economic burden and cost-effectiveness.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.