To address the constrains imposed by insufficient hydrogen peroxide (H2O2) and high glutathione (GSH) expression in tumor cells on the efficacy of chemodynamic therapy (CDT), zeolitic imidazolate framework-8 (ZIF-8) loaded with disulfiram (DSF) and 3-amino-1,2,4-triazole (3-AT) was synthesized via a one-pot approach. Subsequently, hyaluronic acid (HA)-modified cupric peroxide (CuO2) was in-situ grown on its surface through biomineralization to construct a multifunctional copper-based nanozyme ADZCH (3-AT/DSF@ZIF-8@CuO2-HA). This nanoplatform disrupts the intratumoral H2O2 homeostasis, depletes GSH, and synchronously delivers DSF and Cu2+ via cascade catalysis, thereby enhancing CDT and sensitizing tumors to DSF-based chemotherapy. The results of physicochemical characterization indicated that ADZCH presented a uniform core-shell structure with favorable dispersibility. Its particle size and Zeta potential were 196.5 nm and −19.5 mV, respectively. It possessed a microporous structure with a specific surface area of 81.8600 m2/g, and demonstrated efficient loading capacity for DSF and 3-AT, achieving drug loading efficiencies of 5.91% and 45.07%, respectively. Moreover, ADZCH can continuously and slowly release drugs in an acidic environment and maintain good stability under diverse physiological conditions. In vitro functional assays verified that ADZCH catalytically generated H2O2 and hydroxyl radicals while concurrently depleting GSH in a concentration- and incubation time-dependent manner. Cellular uptake experiments showed that HA modification significantly improved the uptake of nanoparticles by 4T1 cells. Cytotoxicity tests showed that 80 μg/mL ADZCH had a significant cytotoxic effect on 4T1 cells but no significant toxicity on L929 cells. DCFH-DA probe detection indicated that ADZCH could significantly induce intracellular reactive oxygen species (ROS) generation, thereby enhancing CDT efficacy. Live/dead staining experiments showed that ADZCH efficiently induced apoptosis, with the proportion of dead cells reaching 94.74%, demonstrating its promising potential for anti-tumor applications.This study provides new research ideas and experimental basis for overcoming the tumor microenvironment barrier and enhancing the anti-tumor effect of CDT combined with chemotherapy.

Yttrium-90 microsphere selective internal radiation therapy (SIRT), also known as transarterial radioembolization, has become one of the pivotal treatments for liver cancer, particularly for selected advantageous patient groups. This review summarizes the characteristics of different patients with liver cancer that could obtain maximum benefit from SIRT and discusses key factors affecting efficacy and safety, including tumor characteristics, liver function, patient performance status, and treatment intent. In evaluating appropriate candidates, mapping serves as a crucial simulation procedure to assess tumor vascular anatomy, predict lung shunting, and guide catheter positioning and dose planning. This procedure substantially enhances therapeutic precision while minimizing the risk of nontarget radiation-related adverse events, such as radiation-induced pneumonitis and gastrointestinal toxicity. Several studies have suggested that SIRT is not only suitable for patients with early or limited hepatocellular carcinoma but can also be used as a bridging therapy for liver transplantation and conversion therapy for unresectable liver cancers. In combination with systemic treatments, SIRT has demonstrated survival benefits in patients with unresectable liver cancer. This review also highlights the importance of further optimizing patient screening through personalized dosimetry and mapping to ensure the precision and safety of treatment. A thorough review of relevant literature and clinical practice offers clinicians comprehensive suggestions on patient screening and clarifies the promise of SIRT in the liver cancer population.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective:To investigate the anemia conditions and characteristics of iron metabolism during different stages of pregnancy in women with different genotypes of thalassemia.Methods:This cohort study selected 3 303 singleton pregnant women who underwent regular prenatal examinations and genetic tests of thalassemia and were delivered at Maternal & Child Health Hospital of Guangxi Zhuang Autonomous Region from January 2019 to December 2023. According to the results of thalassemia gene testing, the women were divided into groups: those without thalassemia genes served as the control group (1 539 cases), and those with thalassemia genes (1 764 cases) were further divided based on genotype into the -α/αα group (326 cases), --/αα or -α/-α group (649 cases), point mutation α-thalassemia group (201 cases), β 0-thalassemia group (368 cases), β +-thalassemia group (91 cases), and α combined with β-thalassemia group (129 cases). Hemoglobin (Hb) and serum ferritin (SF) levels were measured in the first, second, and third trimester of pregnancy. Differences in anemia and iron reserves among the groups at different pregnancy stages were compared using repeated measures analysis of variance, LSD test, Kruskal-Wallis rank-sum test, and Bonferroni correction. Results:Compared to the first trimester, Hb levels decreased in the second and third trimester across all groups (LSD test, all P<0.05), and the severity of anemia increased (Bonferroni correction, all P<0.017). The severity of anemia varied among the groups at the same pregnancy stage ( Hfirst trimester=918.20, Hsecond trimester=1 224.50, Hthird trimester=980.19; all P<0.001), and Hb levels also differed ( Ffirst trimester=282.54, Fsecond trimester=352.31, Fthird trimester=239.02; all P<0.001). The β 0-thalassemia group had higher rates of moderate anemia in the first, second, and third trimester of pregnancy [38.6% (142/368), 85.3% (314/368), and 73.6% (271/368)] compared to other groups (Bonferroni correction, all P<0.002), and lower Hb levels [(102.1±8.9), (92.0±7.3), and (94.6±7.7) g/L] than other groups (LSD test, all P<0.05). As pregnancy progresses, SF levels in each group of pregnant women gradually decreased (LSD test, all P<0.05), and the degree of iron deficiency worsened (Bonferroni correction, all P<0.05). The iron deficiency rate in thalassemia pregnant women during the third trimester ranges from 21.5% (79/368) to 46.0% (150/326). The degree of iron deficiency varies among groups within the same gestational period ( Hfirst trimester=79.13, Hsecond trimester=203.98, Hthird trimester=130.55; all P<0.001), and SF levels also differ ( Ffirst trimester=17.28, Fsecond trimester=44.60, Fthird trimester=31.87; all P<0.001). Among them, the β 0-thalassemia group had the lowest iron deficiency rates in the second, and third trimesters [9.8% (36/368), and 21.5% (79/368)] (Bonferroni correction, all P<0.002). SF levels in the β 0-thalassemia and β +-thalassemia groups were higher than those in other groups during each gestational period (LSD test, all P<0.05). Conclusions:Pregnant women with thalassemia may experience varying degrees of iron deficiency during pregnancy, with the severity of iron deficiency and anemia increasing with gestational age. The degree of iron deficiency and anemia during pregnancy varies among pregnant women with different genotypes of thalassemia. Clinically, individualized management should be provided for pregnant women with thalassemia based on their genotypes, with dynamic monitoring of anemia and iron metabolism changes.

Objective:To evaluate the association between heatwaves and fall-related mortality.Methods:A total of 61 421 fall-related mortality from 2013 to 2022 in 7 provinces of China were included in a time-stratified case-crossover design, with daily meteorological data derived from the fifth generation European Reanalysis dataset produced by the European Centre for Medium-Range Weather Forecasts. Conditional logistic regression chimeric distributed lag nonlinear model was used to analyze the association between heatwaves and fall-related mortality and stratified analysis was conducted according to gender and age.Results:Heatwaves were associated with an increased risk of fall-related morality. The risk of fall-related mortality during heatwaves was higher than during non-heatwave periods ( OR=1.11, 95% CI: 1.05-1.18). The attributable fraction of fall-related motality due to heatwaves was 10.25% (95% CI: 4.49%-15.36%). For each 1 ℃ increase above the heatwave threshold, the risk of fall-related mortality increased by 34% ( OR=1.34, 95% CI: 1.02-1.76). The effect of heatwave duration on fall-related mortality was not statistically significant. Stratified analyses indicated that women experienced a higher risk of fall-related mortality during heatwaves ( OR=1.13, 95% CI: 1.04-1.22) compared to man ( OR=1.10, 95% CI: 1.04-1.17). Conclusions:Heatwave increases the risk of fall-related mortality, and the intensity of heatwaves modify this risk. Women are vulnerable populations.

Objective:To analyze the clinical efficacy of pasteurization-inactivated tumor bone replantation combined with intramedullary vascularized fibula for reconstructing bone defects after surgery for malignant bone tumors in children and adolescents.Methods:A retrospective analysis was performed on the data of 54 patients who underwent pasteurization-inactivated tumor bone replantation combined with intramedullary vascularized fibula reconstruction for bone defects after surgery for malignant bone tumors at the Bone and Soft Tissue Tumor Treatment Center of Peking University People's Hospital from September 2015 to September 2023. There were 39 males and 15 females, with an age of 12.4±5.6 years (range, 4 to 23 years). The tumor types included 33 cases of osteosarcoma, 19 cases of Ewing sarcoma, and 2 cases of soft tissue sarcoma. All cases were at Enneking stage IIB. The tumor locations were 30 cases in the femur, 19 cases in the tibia, 4 cases in the ilium, and 1 case in the humerus. The survival rate, bone healing time, tumor recurrence, and metastasis were observed. The limb function was evaluated using the Musculoskeletal Tumor Society (MSTS)-93 score.Results:All patients successfully completed the surgery and were followed up, with a follow-up time of 44.6±27.1 months (range, 12 to 96 months). The operation time was 527±132 min (range, 150 to 730 min), and the blood loss was 730±591 ml (range, 300 to 2,800 ml). The length of inactivated tumor bone was 16.5±4.5 cm (range, 9.1 to 24.0 cm), the defect length accounted for 43.4%±12.2% of the total length of the affected bone (range, 23.8% to 75.5%), the proximal osteotomy of the long bones in the extremities was 14.1±8.3 cm from the articular surface (range, 1.9 to 31.1 cm), the distal osteotomy was 9.4±6.2 cm from the articular surface (range, 1.7 to 22.9 cm), and the length of the harvested vascularized fibula was 18.0±4.0 cm (range, 11.0 to 26.4 cm). At the last follow-up, 51 patients were alive, including 47 with no evidence of tumor and 4 with tumor; 3 patients died of tumor progression. Local recurrence occurred in 5 patients, including 4 with soft tissue recurrence in the surgical area (3 underwent surgical resection and 1 received radiotherapy) and 1 with recurrence at the site of inactivated bone. Distant metastasis occurred in 11 patients, including 5 with lung metastasis only, 2 with bone metastasis only, and 4 with combined lung and bone metastasis. Among the 5 patients with lung metastasis only, lung metastases were resected, with 3 surviving with tumor, 2 surviving without tumor; the 2 patients with bone metastasis only underwent surgical resection of bone metastases, both surviving without tumor. Among the 4 patients with combined lung and bone metastasis, 3 died of tumor progression and 1 survived with tumor. The Kaplan-Meier curve showed a 5-year survival rate of 90.8%±6.2% and a 5-year recurrence-free and metastasis-free survival rate of 68.7%±7.9%. The osteotomy healing time at the diaphysis was 8.4±2.3 months (range, 4 to 13 months), the osteotomy healing time at the metaphysis was 5.9±1.7 months (range, 3 to 10 months), and the healing time between inactivated tumor bone and fibula was 6.4±2.0 months (range, 4 to 11 months). No nonunion occurred. The MSTS-93 score at the last follow-up was 94.4%±4.8% (range, 80% to 100%).Conclusion:Pasteurization-inactivated tumor bone replantation combined with intramedullary vascularized fibula reconstruction for bone defects after surgery for malignant bone tumors in children and adolescents has satisfactory clinical efficacy, high bone healing rate, and low rates of local recurrence and distant metastasis.

Objective:To construct a questionnaire to measure parents′ behavioral and social drivers (BeSD) in administering rotavirus vaccine to their children, and to test the reliability and validity of the questionnaire.Methods:A questionnaire was constructed to investigate the BeSD of rotavirus vaccination among parents based on the WHO BeSD questionnaire. A survey was conducted among parents of children aged 0-3 years old in vaccination clinics from 15 community health service centers in Nanjing City of Jiangsu Province, Yuhuan and Kaihua Counties of Zhejiang Province, Anqing City of Anhui Province, and Yangpu District of Shanghai City from April to May in 2024. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to analyze the reliability (internal consistency reliability, combination reliability and split half reliability) and validity (structural validity, convergence validity and discriminative validity) of the questionnaire.Results:A total of 850 questionnaires were collected, of which 614 were valid, with an effective response rate of 72.20%. The EFA resulted in the refinement of the rotavirus vaccine BeSD questionnaire from 37 to 35 items (including 24 core items), and suggested a five-factor structure including the perceptions of vaccine, confidence in vaccine, social process of vaccination, motivation for vaccination, and practical problems of vaccination. The cumulative variance contribution rate reached 56.27%. The CFA confirmed an ideal five-factor model fit (GFI=0.82,CFI=0.86,PNFI=0.67,RMSEA=0.07). The AVE of each dimension was greater than 0.50. The AVE square root of each dimension of the questionnaire was greater than its correlation coefficient. The Cronbach′s α coefficient of the total questionnaire was 0.79.Conclusion:The developed BeSD questionnaire of rotavirus vaccine has good reliability and validity, and can be used to measure parents′ behavioral and social factors in administering rotavirus vaccine to their children.

Objective To screen for key genes and important pathways common for different etiologies of acute kidney injury(AKI)by pathway-associated deep neural network and multiple machine learning algorithms.Methods AKI microarray datasets GSE30718,GSE37838,GSE53769,GSE108113,GSE125779,GSE99325,and GSE174020 downloaded from the Gene Expression Omnibus(GEO)database were merged,including 60 kidney samples from AKI patients and 79 kidney samples from healthy controls.They were divided(8∶2)into training sets and test sets,and were used to train and evaluate pathway-associated deep neural network and 4 machine learning algorithms,including least absolute shrinkage and selection operator(LASSO),random forest(RF),support vector machine-recursive feature elimination(SVM-RFE),and extreme gradient boosting(XgBoost),to screen for common key genes and pathways of different etiologies of AKI.The downloaded datasets GSE99340 and GSE1563 were merged,including 43 kidney samples from AKI patients and 36 kidney samples from healthy controls,which were used as external validation sets for LASSO model and nomogram performance test based on the final screened genes.The pathway-associated deep neural network and machine learning algorithms were evaluated using receiver operating characteristic curves,precision,recall,accuracy,and F1-score.The immune cell infiltration characteristics were explored in AKI via cell-type identification by estimating relative subsets of RNA transcripts(CIBERSORT),and Pearson correlation coefficients were used to evaluate the correlation between the final screened common key genes and immune cell infiltration levels.Results The pathway-associated deep neural network trained by 5-fold cross validation produced an area under curve(AUC)of 0.914 5±0.007 0,a precision of 0.750 0±0.044 0,a recall of 0.923 1±0.048 0,an accuracy of 0.838 7±0.016 0,and an F1-score of 0.827 6±0.020 0 in the test set,yielding a robust and highly accurate classification performance for AKI,and identified key pathways and a subset of candidate genes.The 4 machine learning algorithms all achieved high discriminative performance for AKI in the test set with AUC≥0.860,precision≥0.750,recall≥0.800,and F1-score≥0.774,and screened 7 common key genes for AKI with different etiologies,including CD86,C-X-C motif chemokine ligand 10(CXCL10),dynamin 2(DNM2),proto-oncogene FOS,transcription factor 12(TCF12),VGF nerve growth factor inducible(VGF),and A kinase anchoring protein 5(AKAP5).Based on the final screened common key genes,the LASSO model had an AUC of 0.940 4 for the test set and an AUC of 0.944 4 for the external validation,and the model showed a very high discriminatory ability for the AKI,which demonstrated the overall regulatory performance of the genes.The nomogram constructed based on the screened 7 genes demonstrated the highest classification performance with an AUC of 0.928 9,validating the outstanding contribution and overall action performance of the screened individual genes.Immune cell infiltration analysis showed that there were significant differences in B cells na?ve,mast cells activated,monocytes,macrophages M1,B cells memory,and dendritic cells activated between AKI samples and healthy control samples(all P＜0.05).Macrophages M1 and monocytes were positively correlated with CD86 and CXCL10,mast cells activated were positively correlated with FOS,and B cells na?ve were negatively correlated with CD86 and CXCL10(all P＜0.01).Mast cells activated were positively correlated with VGF and negatively correlated with CD86 and TCF12,while memory B cells were positively correlated with CD86(all P＜0.05).Conclusion Strategy combining pathway-associated deep neural network and multiple machine learning classifiers can mine high-value key genes from high-dimensional,complex and heterogeneous transcriptomic data as potential targets for therapeutic interventions in AKI.