Objective: To investigate the distribution frequency and molecular mechanism of the rare blood type Lu(a-b-) in Shenzhen, and to compare the polymorphisms of the Lutheran blood group system encoding gene LU and the In (Lu) phenotype-related gene KLF1 among Han Chinese, Indian, and Uyghur populations in Xinjiang. Methods: Serological methods were used to screen the Lu(a-b-) phenotype of blood donors in Shenzhen. Third-generation sequencing was employed to sequence the full-length of the LU and KLF1 genes in Lu (a-b-) phenotype samples as well as the samples from the Han Chinese, Indians, and Uyghur population, followed by analysis of gene haplotypes frequencies. Results: Ten individuals with the Lu(a-b-) phenotype were screened out of 14 367 blood donors in Shenzhen, yielding a frequency of approximately 0.07%. Only 2 cases showed mutations in the coding region of the LU gene, while all individuals showed heterozygous mutations in the coding region of the KLF1 gene. The highest mutation frequencies of the LU and KLF1 genes were observed in the Uyghur population in Xinjiang and the Han Chinese in Shenzhen, respectively. Conclusion: All Lu(a-b-) phenotypes are of the In (Lu) type, and their formation mechanism is mainly related to KLF1 gene mutations. Both the LU and KLF1 genes exhibit significant polymorphism in the Han Chinese, Indians, and Uyghur populations.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

Background: and Purpose Therapeutic target selection in noninvasive brain stimulation for poststroke motor recovery typically relies on the interhemispheric inhibition model, which is effective for mildly affected patients but offers limited benefits for severely affected individuals. The mechanisms governing recovery from moderate-to-severe stroke remain poorly understood, which hinders the development of targeted interventions. Methods: We analyzed resting-state functional magnetic resonance imaging data from patients with unilateral subcortical stroke and moderate-to-severe upper limb deficits, both pre- and postintervention, along with data from healthy controls. We developed a novel dynamic lag analysis method for identifying recovery-related homotopic sensorimotor regions with altered interhemispheric interactions. To further uncover the global reorganization pathway, we developed dynamic lateralization approaches to detect large-scale functional connectivity (FC) alterations associated with the identified regions in transient lateralization states. Results: Dynamic time-lag analysis revealed significantly reduced synchronized states in the homotopic dorsal premotor cortex (PMd) post-intervention compared with pre-intervention, which correlated with motor recovery. Further dynamic lateralization analysis revealed a prolonged segregation state in patients, characterized by weakened interhemispheric and strengthened intrahemispheric interactions. In this state, patients showed decreased FC in the ipsilesional PMd and increased FC in the contralesional PMd with bilateral subcortical networks. These recoveryrelated alterations were absent in the traditional static analysis. Conclusions Dynamic analyses targeting interhemispheric interactions are valuable for understanding neural reorganization after stroke. The diminished interactions between the homotopic PMd indicate a compensatory mechanism. Importantly, a state-dependent compensatory pathway was identified, wherein the contralesional PMd assumes the functions of the ipsilesional PMd through enhanced interactions with subcortical structures, potentially guiding more effective interventions.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Based on the data from the 5^th National Physical Fitness Surveillance in China, this study aimed to explore the relationship between abnormal body weight and physical fitness levels in older adults.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the incremental vaccine effectiveness (VE) of two dose of the mumps containing vaccine (MuCV) in chidren, so as to provide a basis for optimizing mumps immunization strategies. Methods: A 1∶2 frequency matched case-control study was conducted by using reported mumps cases in childcare centers or schools from Lu an, Hefei, Ma anshan and Huainan cities of Anhui Province from September 1, 2023 to June 30, 2024, as a case group(383 cases). And healthy children in the same classroom were selected as a control group(766 cases). The MuCV immunization histories of participants were collected to estimate the incremental VE of the second dose of MuCV against mumps. Group comparisons were performed using the Chi square test or t-test. For matched case-control pairs, the Cox regression model was employed to calculate the odds ratio (OR) with 95% confidence interval (CI) for two dose MuCV vaccination and to estimate the incremental vaccine effectiveness (VE). Results: There were no statistically significant differences between the case and control groups regarding gender, age, dosage of MuCV vaccination and the time interval since the last dose vaccination( χ 2/t=0.05, 0.20, 0.94, -0.02, P >0.05). The proportions of the case and control groups vaccinated with two doses of MuCV were 26.63% and 29.37%, respectively, and the overall incremental VE of the second dose of MuCV was 40.73% (95% CI=3.03%-63.77%, P <0.05). Subgroup analyses revealed that the incremental VE for children with a period of ≥1 year between the two doses of MuCV was 54.13% (95% CI=1.90%-78.56%, P <0.05), while for children with a period of <1 year, it was 30.63% (95% CI=-28.59%-62.58%, P >0.05). The incremental VE of the second dose of MuCV was 30.36% (95% CI=-25.95%-61.50%, P >0.05) in kindergarten children and 66.73% (95% CI=14.92%-86.99%, P <0.05) in elementary and secondary school students. The incremental VE was 28.78% (95% CI=-27.46%-60.21%, P >0.05) within five years of the last dose of MuCV vaccination and 66.07% (95% CI=-41.56%-91.87%, P >0.05) for vaccinations administered beyond five years. Conclusions The second dose of MuCV may offer additional protection for children; however, extending the interval between two dose of MuCV (<1 year) has shown limited incremental protective effects. Therefore, it is crucial to consider optimizing current immunization strategies for mumps.

Objective To explore the characteristics of latent profiles of ego depletion in patients with heart failure,and analyze the impacts of these profiles on patients' self-management behavior.Methods 280 heart failure patients who were hospitalized in a tertiary grade A hospital were conveniently selected in Nanjing from April to October 2024 as study subjects.The investigation utilized a general information questionnaire,the Ego-Depletion Scale for Heart Failure Patients,the Self-Management Scale of Heart Failure Patients,and the Chronic Disease Self-Efficacy Scale.The latent profile categories of ego depletion was explored in heart failure patients.Univariate analysis and multiple Logistic regression analysis were used to investigate the influencing factors of different latent profile categories and the impact of each category on patients' self-management levels.Results The ego depletion of 255 heart failure patients could be classified into 3 latent profiles:self-adaptive low depletion group(35.29％),symptom distressed moderate depletion group(43.53％),and social life change high depletion group(21.18％).Multiple Logistic regression analysis showed that residence,primary caregiver,education level,New York Heart Association cardiac function grade,and self-efficacy score were factors influencing the potential profile of ego depletion in heart failure patients(P＜0.05).The comparison of self-management scores among patients in different latent profiles of ego depletion showed statistically significant differences(P＜0.05).Conclusion The level of ego depletion in patients with heart failure is high with significant heterogeneity.Medical staff should pay attention to the heterogeneity and influencing factors of ego depletion in patients with heart failure in time,and develop personalized comprehensive intervention strategies to alleviate ego depletion and improve their self-management levels.

Objective To observe the effects of Ditan Yizhi Decoction on mitochondrial dynamics-mediated glucose metabolism in vascular dementia(VaD)rats based on the ROS/Drp1 axis;To explore its mechanism in treating VaD.Methods Ten male SD rats were randomly selected from 70 as the sham-operation group,and VaD models were prepared using the modified bilateral common carotid artery permanent ligation method for the remaining rats.The successfully modeled rats were randomly divided into model group,positive drug group(donepezil hydrochloride),inhibitor group(Mdivi-1)and Ditan Yizhi Decoction low-,medium-and high-dosage groups(12.86,25.725,51.45 g/kg),and intervened with corresponding method for 4 consecutive weeks.Morris water maze experiment was used to assess the learning memory ability of rats,HE and Nissl staining were used to observe the morphology of hippocampal tissue,transmission electron microscopy was used to observe the mitochondrial ultrastructure of hippocampal neurons,DHE fluorescent probe was used to detect the content of ROS in hippocampal neurons,Western blot was used to detect the expressions of Drp1,p-Drp1,Mfn2,Opa1,HK1,PKM2,GLUT1 and LDHA,the contents of serum IL-1β,IL-6 and TNF-α were detected by ELISA.Results Compared with the sham-operation group,rats in the model group had a prolonged escape latency(P<0.01)and a reduced number of crossing platforms(P<0.01);neuronal gaps in the CA1 region of the hippocampus were enlarged,with irregular cell morphology and blurred borders,neuronal consolidation,lysis and fragmentation of Nissl bodies and reduced number of Nissl bodies,swelling and deformation of mitochondria,disorganization of the cristae,and disruption of the bilayer membrane structure;the content of ROS in CA1 region of the hippocampus was elevated,the protein expressions of Mfn2 and Opa1 significantly decreased(P<0.01),the expressions of p-Drp1,HK1,PKM2,GLUT1,LDHA proteins significantly increased(P<0.01),and serum contents of IL-1β,IL-6 and TNF-α significantly increased(P<0.01).Compared with the model group,the escape latency was significantly shortened in Ditan Yizhi Decoction groups,positive drug group and inhibitor group(P<0.01),and the number of crossing platforms increased(P<0.05,P<0.01);the number of neurons in the hippocampal CA1 region increased,with normal morphology,orderly arrangement,abundant Nissl bodies,recovered mitochondrial morphology,and decreased rupture;the ROS content in hippocampal CA1 region decreased(P<0.01),while the expressions of Mfn2 and Opa1 proteins increased(P<0.01),the expressions of p-Drp1,HK1,PKM2,GLUT1 and LDHA proteins decreased(P<0.01),and the serum contents of IL-1β,IL-6 and TNF-α decreased(P<0.05).Conclusion Ditan Yizhi Decoction can improve cognitive impairment and neuronal morphology in VaD rats,and the mechanism maybe related to regulation of mitochondrial dynamics through the ROS/Drp1 axis,attenuating glycometabolic disorders,and reducing inflammatory response.