Prostate cancer is one of the most common male urological malignancies,in which bone metastasis of desmo-plasia-resistant prostate cancer is an important stage in the progression of the disease,which seriously affects the quality of life and survival of patients.With the development of nuclide therapy technology in recent years,223-Ra,as a new type of alpha-targeted therapy,has shown good efficacy in the treatment of desmoplasia-resistant prostate cancer bone metastasis.The purpose of this pa-per is to review the characteristics,mechanism of action,treatment,and the main research results of its treatment of desmoplasia-resistant prostate cancer bone metastasis,and provide a comprehensive review of the clinical application of 223-Ra in the treatment of desmoplasia-resistant prostate cancer bone metastasis for the clinical application of 223-Ra in prostate cancer bone metastasis.

Objective:To observe and analyze the correlations between aqueous humor cytokine concentrations and disorganization of retinal inner layers (DRIL), as well as postoperative visual acuity, in patients with idiopathic epiretinal membrane (iERM).Methods:A prospective clinical study. From November 2022 to October 2024, 40 eyes of 40 patients diagnosed with iERM at Ophthalmology Center of Zhejiang Provincial People's Hospital (Affiliated People's Hospital) underwent cataract surgery alone or combined with pars plana vitrectomy (iERM group) were enrolled; 19 eyes of 19 patients undergoing cataract surgery alone during the same period served as the control group. All eyes underwent best-corrected visual acuity (BCVA) testing and swept-source optical coherence tomography (SS-OCT). BCVA was assessed using a logarithmic visual acuity chart and converted to the logarithm of the minimum angle of resolution (logMAR) for statistical analysis. Central macular thickness (CMT) was measured using SS-OCT. The iERM group was further subdivided into DRIL-positive and DRIL-negative subgroups (21 eyes and 19 eyes, respectively), based on the presence or absence of DRIL. Aqueous humor samples were collected preoperatively from eyes in both the iERM and control groups. Concentrations of transforming growth factor (TGF)-β1, TGF-β2, TGF-β3, platelet-derived growth factor (PDGF)-AB, hepatocyte growth factor, fibroblast growth factor, vascular endothelial growth factor-A (VEGF-A), placental growth factor (PLGF), glial cell line-derived neurotrophic factor (GDNF), intercellular adhesion molecule-1 (ICAM-1), angiopoietin (Ang)-1, Ang-2, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) were measured. Follow-up examinations using the same equipment and methods were performed at 1 month postoperatively. Aqueous cytokine levels were compared between the iERM group, control group, DRIL-positive subgroup, and DRIL-negative subgroup. Correlations between aqueous cytokine levels in the iERM group and BCVA or CMT were also analyzed. Intergroup comparisons utilized the Mann-Whitney U test; correlations between variables were assessed using Spearman's rank correlation analysis. Results:Compared to the control group, the iERM group exhibited significantly higher aqueous concentrations of TGF-β1, TGF-β3, PDGF-AB, PLGF, GDNF, ICAM-1, Ang-1, and TNF-α ( P<0.05). Compared to the DRIL-negative subgroup, the DRIL-positive subgroup showed significantly elevated aqueous concentrations of TGF-β3, PDGF-AB, PLGF, GDNF, ICAM-1, Ang-1, Ang-2, TNF-α, and IL-6 ( P<0.05). Significant differences were observed in logMAR BCVA ( P=0.028) and CMT ( P<0.001) within the iERM group between preoperative and 1-month postoperative measurements. LogMAR BCVA differed significantly between the DRIL-positive and DRIL-negative subgroups ( P=0.048). Correlation analysis revealed that baseline aqueous levels of VEGF-A and IL-6 in eyes with DRIL were positively correlated with postoperative BCVA ( r=0.324, 0.452; P=0.042, 0.003). No significant correlation was found between CMT and any cytokine ( P>0.05). Conclusions:Aqueous humor cytokines are closely associated with DRIL in iERM patients. IL-6 and VEGF-A may serve as potential predictive biomarkers for early postoperative visual recovery.

Objective:To analyze the clinical characteristics, treatment response, and prognosis of patients newly diagnosed with immunoglobulin A multiple myeloma (IgA MM), and to ascertain whether the IgA isotype remains a poor prognostic factor in the bortezomib era.Methods:This study retrospectively enrolled 155 patients newly diagnosed with IgA MM and 420 with non-IgA MM admitted to the Department of Hematology, the First Affiliated Hospital of Nanchang University from March 2014 to December 2021. We compared the two groups in terms of their clinical characteristics, prognoses, and progression-free survival (PFS) and overall survival (OS) following different treatment regimens.Results:Compared with the non-IgA group, the IgA group presented with more aggressive clinical features, including a higher proportion of patients with hemoglobin<85 g/L (61.3% vs 51.4%, P=0.035), extramedullary manifestations (20.0% vs 11.4%, P=0.008), and gain/amp (1q21) (48.6% vs 36.7%, P=0.032). Efficacy analysis revealed a lower overall response rate (ORR) in the IgA group than in the non-IgA group (83.2% vs 92.4%, P=0.001). Among patients treated with bortezomib-based regimens, the ORR was 91.2% in the IgA group and 94.8% in the non-IgA group, but the difference was nonsignificant ( P=0.146). Survival analysis showed that the median PFS and OS were significantly shorter in the IgA group compared with the non-IgA group[23.5 (95% CI: 17.4-29.5) months and 48.8 (95% CI: 30.1-67.5) months vs 40.7 (95% CI: 33.8 - 47.6) months and not reached, respectively; P<0.001 and P=0.002]. In the subgroup of patients who received bortezomib-based therapy without subsequent autologous hematopoietic stem cell transplantation (auto-HSCT), the PFS and OS were significantly shorter in the IgA group compared with the non-IgA group[25.4 (95% CI: 18.7-32.1) months and 53.5 (95% CI: 35.4-71.6) months vs 41.0 (95% CI: 33.7-48.3) months and not reached; P=0.001 and P=0.011]. In patients who underwent bortezomib-based induction therapy followed by auto-HSCT, the 1-, 3-, and 5-year OS rates for the IgA group were 96%, 81%, and 81%, respectively, compared with 93%, 89%, and 79% for the non-IgA group, but the difference was nonsignificant ( P=0.758) . Conclusion:In the bortezomib era, IgA MM is still associated with a poorer overall prognosis than non-IgA MM, likely due to its inherent high-risk biological characteristics. Although bortezomib-based regimens effectively improve the treatment response, they fail to completely bridge the survival gap between the two disease isotypes. Therefore, bortezomib-based therapy followed by auto-HSCT may be a key strategy to overcome the poor prognosis of IgA MM, potentially enabling these patients to achieve long-term survival comparable to that of their non-IgA counterparts.

High-performance phototheranostics with combined photothermal therapy and photoacoustic imaging have been considered promising approaches for efficient cancer diagnosis and treatment. However, developing phototheranostic materials with efficient photothermal conversion efficiency (PCE), especially over the second near-infrared window (NIR-II, 1000-1700 nm), remains challenging. Herein, we report an ultraefficient NIR-II-activated nanomedicine with phototheranostic and vaccination capability for highly efficient in vivo tumor elimination and metastasis inhibition. The NIR-II nanomedicine of a semiconducting biradical oligomer with a motor-flexible design was demonstrated with a record-breaking PCE of 87% upon NIR-II excitation. This nanomedicine inherently features extraordinary photothermal stability, good biocompatibility, and excellent photoacoustic performance, contributing to high-contrast photoacoustic imaging in living mice and high-performance photothermal elimination of tumors. Moreover, a whole-cell vaccine based on a NIR-II nanomedicine with NIR-II-activated performance was further designed to remotely activate the antitumor immunologic memory and effectively inhibit tumor occurrence and metastasis in vivo, with good biosafety. Thus, this work paves a new avenue for designing NIR-II active semiconducting biradical materials as a promising theranostics platform and further promotes the development of NIR-II nanomedicine for personalized cancer treatment.

Histone deacetylase 3 (HDAC3) is an epigenetic modification enzyme that plays a crucial role in the development and progression of diabetes and its complications. Studies have reported that increased HDAC3 activity is associated with pancreatic β-cell dysfunction in type 1 diabetes, while in type 2 diabetes, HDAC3 affects insulin resistance and signaling by regulating the metabolism of the liver, adipose tissue, and muscle. Additionally, HDAC3 plays a key role in diabetic complications such as cardiomyopathy, retinopathy, and nephropathy. Selective inhibition of HDAC3 has the potential to improve insulin sensitivity, reduce chronic inflammation, and enhance pancreatic cell function, offering a promising new therapeutic strategy for diabetes and its complications.

BACKGROUND:The combination of traditional Chinese medicine syndrome and semen quality-related parameters can jointly predict the occurrence of abnormal increase in sperm DNA fragmentation index (DFI) and draw a column chart,which can significantly improve clinical practicality and application efficiency,provide a basis for comprehensive evaluation of semen quality in clinical practice,take active intervention measures to improve clinical outcomes,and formulate personalized medical plans.OBJECTIVE:To explore the prediction model and verification of sperm DNA fragments based on traditional Chinese medicine syndrome and semen quality-related parameters.METHODS:Retrospective analysis was made on 420 infertile patients who received traditional Chinese medicine syndrome diagnosis and sperm DNA fragment rate examination in the Department of Traditional Chinese Medicine Andrology,Nanxishan Hospital of Guangxi Zhuang Autonomous Region from July 2019 to July 2021.According to the Manual of Human Semen Examination and Treatment Laboratories (6th Edition),137 patients with sperm DFI>30％ were included in the group of abnormally high sperm DFI,and 283 patients with sperm DFI ≤ 30％ were taken as the control group.First,univariate analysis was used to screen the influencing factors of the abnormal increase of sperm DFI.Then,the best matching factor was selected by using the collinearity problem of LASSO correction factors.Then,it was included in the multifactor forward stepwise logistic regression to find out its independent influencing factors and draw a nomogram.Finally,the receiver operating characteristic curve,calibration curve,decision curve analysis and clinical impact curve were used to verify the differentiation and accuracy of the prediction model and its clinical application effectiveness.RESULTS AND CONCLUSION:(1) The results of the univariate analysis showed that age,body mass index,forward motion rate,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney sperm deficiency syndrome were the influencing factors for the abnormal increase of sperm DFI (P<0.05).(2) The best matching factors further screened by LASSO regression were age,body mass index,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney essence deficiency syndrome (P<0.05).(3) Multifactor forward stepwise Logistic regression showed that age,body mass index,sperm concentration,total sperm motility,damp heat downpour syndrome,and kidney yang deficiency syndrome were six independent factors that caused the abnormal increase in sperm DFI.(4) Receiver operating characteristic curve showed that the area under the curve of the model group was 0.760(0.713,0.806),and the area under the curve of the validation group was 0.745(0.714,0.776).It showed that the prediction model had good discrimination.(5) The average absolute error of the calibration curve was 0.040,and the Hosmer Lemeshow test (P>0.05),suggesting that there was no significant statistical difference between the probability of the abnormal increase in DFI of spermatozoa predicted by the model and the probability of the abnormal increase in DFI of spermatozoa actually occurred,which confirmed that the model had good accuracy.(6) Decision curve analysis and clinical impact curve showed that the model group and validation group had the maximum clinical net benefit when the threshold probability values were (0.08-0.84) and (0.09-0.78) respectively,and had good clinical application efficiency within the threshold probability range.(7) These findings conclude that age,body mass index,sperm concentration,total sperm viability,damp heat downpour syndrome and kidney yang deficiency syndrome are independent factors that cause the abnormal increase in sperm DFI.The nomogram of the clinical prediction model constructed by them has good clinical prediction value and clinical application efficiency,and can provide the basis for comprehensive clinical evaluation of semen quality and individualized medical service.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.