[Objective] To establish a new scoring system to predict the perioperative outcomes (operation time, intraoperative blood loss, and trifecta achievement) in patients undergoing robot-assisted partial nephrectomy (RAPN) by integrating the RENAL and Mayo adhesive probability (MAP) scores. [Methods] Clinical data of 178 patients with renal cell carcinoma who underwent RAPN performed by the same surgeon in our hospital during Jan.2015 and Jan.2022 were retrospectively analyzed.The RENAL and MAP scores of all patients were calculated.Linear regression and logistic regression were used to evaluate the associations between the components of the RENAL and MAP scores (a total of 6 variables) and perioperative outcomes.The factors with significant associations were then included into logistic regression analysis to identify independent predictors for constructing an assessment system for perioperative outcomes, and the receiver operating characteristic (ROC) curve was plotted to calculate the area under the curve (AUC) to predict its efficacy. [Results] Multivariate linear regression analysis showed that tumor size (β=6.14, 95%CI: 1.93—10.34, P=0.004), exophytic rate (β=10.60, 95%CI: 3.44—17.76, P=0.004), and perinephric fat thickness (β=16.48, 95%CI: 8.52—24.45, P<0.001) were significantly associated with operation time.Tumor size (β=10.55 95%CI: 5.60—15.49, P<0.001) was associated with both intraoperative blood loss and trifecta achievement (OR=1.73, 95%CI: 1.26—2.36, P=0.001). Multivariate logistic regression analysis of these 3 factors identified tumor size (OR=9.07, 95% CI: 1.18—69.45, P=0.03) and perinephric fat thickness (OR=2.28, 95%CI: 1.86—6.04, P=0.01) as independent predictors of perioperative outcomes.Based on these findings, the tumor size and perinephric fat thickness (RP) scoring was constructed, which demonstrated better predictive ability than RENAL score or MAP score alone (RP vs.RENAL vs.MAP: 0.766 vs.0.548 vs.0.684). [Conclusion] The RP score includes fewer variables than the RENAL and MAP scores but outperforms them.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Background::Breast cancer is ranked among the most prevalent malignancies in the Chinese female population. However, comprehensive reports detailing the latest epidemiological data and attributable disease burden have not been extensively documented.Methods::In 2018, high-quality cancer surveillance data were recorded in 700 population-based cancer registries in China. We extracted data on female breast cancers (International Classification of Diseases, Tenth Revision [ICD-10]: C50) and estimated the incidence and mortality in 2022 according to the baseline data and corresponding trends from 2010 to 2018. Pathological types were classified according to the ICD for Oncology, 3rd Edition codes. Disability-adjusted life years (DALYs) were calculated as the sum of the years of life lost (YLLs) and years lived with disability (YLDs).Results::In 2022, approximately 357,200 new female breast cancer cases and 75,000 deaths occurred in China, accounting for 15.59% and 7.94% of total new cancer cases and deaths, respectively. The age-standardized incidence rate (ASIR) was 33.04 per 100,000. When analyzed by pathological type, the ASIRs for papillary neoplasms, invasive breast carcinoma, rare and salivary gland-type tumors, and other types were 1.13, 29.79, 0.24, and 1.88 per 100,000, respectively. The age-standardized mortality rate (ASMR) was 6.10 per 100,000. A total of 2,628,000 DALYs were found to be attributable to female breast cancer in China, comprising 2,278,300 YLLs and 349,700 YLDs. The ASIR, ASMR, and age-standardized rate (ASR) for DALYs in urban areas were consistently higher than those in rural areas. We observed a four-fold increase in the ASIR and ASR for DALYs and an eight-fold increase in the ASMR among females over 55 years compared with those aged under 55 years.Conclusion::These data provide invaluable insights into the latest epidemiology of female breast cancer in China and highlight the urgency for disease prevention and control strategy formulation.

Despite significant advancements in treatments for heart failure,the overall prognosis for patients remains poor.Hemodynamic abnormalities in heart failure manifest as elevated left atrial pressure and pulmonary congestion.Previous studies have shown that reducing left atrial pressure can improve symptoms and prognosis for heart failure patients,suggesting that left-sided heart overload may be a potential target for heart failure treatment.Atrial shunting procedures aim to create a stable and controlled left-to-right intracardiac shunt,restoring the decompensated left heart volume and pressure load in heart failure patients to a compensatory state,thereby improving heart failure symptoms and prognosis.Currently,this treatment is still in the clinical research stage globally.Existing data indicate that atrial shunting procedures can lower left atrial pressure at rest or during exercise in heart failure patients,improve pulmonary congestion,enhance patients'exercise tolerance,and clinical cardiac function.However,no studies have yet confirmed that it can improve clinical endpoints such as rehospitalization and mortality due to heart failure.Future research will focus on identifying heart failure patients who may benefit from atrial shunting,with assessments of heart failure etiology,right heart function,and reversibility of pulmonary vascular resistance,as well as heart failure classification based on ejection fraction,serving as potential key factors for patient selection.

This study investigated the epidemiological and genotypic characteristics of group A rotavirus(RVA)in children under 5 years of age with diarrhea at a viral diarrhea surveillance sentinel hospital in Guangdong Province from 2021 to 2022,to provide a basis for RVA prevention and control.A total of 1 858 fecal samples from children under 5 years of age with diarrhea in 2021-2022 were collected.Rotavirus antigen was detected with ELISA,and positive samples were further sequenced and categorized.Among the 1 858 samples,156 were RVA positive.The positivity rates in boys and girls were 8.76％and 7.87％,respectively.Significant differences were observed in the detection rates of RVA infection among age groups.The rate of RVA infection increased gradually from December to April of the following year.In 2021,the main endemic strains of RVA in the Guangdong region were of the G9P[8]subtype,and the rare G8P[8]subtype increased in China.In 2022,the G8P[8]subtype surpassed the G9P[8]subtype for the first time.In cases of diarrhea in infants younger than 5 years in Guangdong Province from 2021 to 2022,the RVA genotypes were diverse,the G9P[8]genotype significantly decreased,and the G8P[8]subtype became a dominant genotype.Continuous RVA genotype monitoring remains necessary to assess the risk of RVA-related disea-ses.

Objective:To study the epidemiological and genetic characteristics of coxsackievirus B3 (CVB3) circulating in Guangdong Province from 2008 to 2021.Methods:This study collected the specimens of hand, foot, and mouth disease (HFMD) cases from 2008 to 2021 that were positive for other enteroviruses except for enterovirus 71 (EV71), coxsackievirus A16 (CVA16), and CVA6, as well as the specimens of herpangina and neonatal infection cases from 2020 to 2021. Enteroviruses in these specimens were detected and their types were identified. CVB3 strains were isolated and the entire VP1 sequences of CVB3 strains were amplified and sequenced. The genetic features of CVB3 strains were analyzed using DNAStar 7.1 and MEGA 6.06 software packages.Results:Among 3 484 HFMD cases positive for other enteroviruses from 2008 to 2021, CVB3-positive cases accounted for 1.6% (57/3 484); among 560 cases of herpangina from 2020 to 2021, CVB3-positive cases accounted for 2.1% (12/560); one neonatal infection case in 2021 was positive for CVB3. CVB3-positive cases accounted for 67.1% (47/70) in 2021 and 18.6% (13/70) in 2020, while there were less than five cases in other years. Forty-eight CVB3 strains were isolated and the entire VP1 sequences of 26 CVB3 strains were obtained. Phylogenetic analysis indicated that the CVB3 strains could be divided into eight genotypes (A-H) and the strains of genotypes A, D and E were prevalent in the Chinese mainland. The 26 CVB3 strains isolated in Guangdong Province shared 80.2%-100.0% nucleotide homology, and belonged to two genotypes of D and E, with genotype D prevalent from 2008 to 2017 and genotype E prevalent from 2020 to 2021.Conclusions:CVB3 is prevalent sporadically in Guangdong Province from 2008 to 2017, but the epidemic intensity increased during 2020 and 2021. CVB3 strains of genotypes D and E are prevalent in Guangdong Province during 2008 to 2021, with genotype E being the prevalent genotype during 2020 and 2021.

Objective:To retrospectively analyze the treatment status of tyrosine kinase inhibitors (TKI) in newly diagnosed patients with chronic myeloid leukemia (CML) in China.Methods:Data of chronic phase (CP) and accelerated phase (AP) CML patients diagnosed from January 2006 to December 2022 from 77 centers, ≥18 years old, and receiving initial imatinib, nilotinib, dasatinib or flumatinib-therapy within 6 months after diagnosis in China with complete data were retrospectively interrogated. The choice of initial TKI, current TKI medications, treatment switch and reasons, treatment responses and outcomes as well as the variables associated with them were analyzed.Results:6 893 patients in CP ( n=6 453, 93.6%) or AP ( n=440, 6.4%) receiving initial imatinib ( n=4 906, 71.2%), nilotinib ( n=1 157, 16.8%), dasatinib ( n=298, 4.3%) or flumatinib ( n=532, 7.2%) -therapy. With the median follow-up of 43 ( IQR 22-75) months, 1 581 (22.9%) patients switched TKI due to resistance ( n=1 055, 15.3%), intolerance ( n=248, 3.6%), pursuit of better efficacy ( n=168, 2.4%), economic or other reasons ( n=110, 1.6%). The frequency of switching TKI in AP patients was significantly-higher than that in CP patients (44.1% vs 21.5%, P<0.001), and more AP patients switched TKI due to resistance than CP patients (75.3% vs 66.1%, P=0.011). Multi-variable analyses showed that male, lower HGB concentration and ELTS intermediate/high-risk cohort were associated with lower cytogenetic and molecular responses rate and poor outcomes in CP patients; higher WBC count and initial the second-generation TKI treatment, the higher response rates; Ph + ACA at diagnosis, poor PFS. However, Sokal intermediate/high-risk cohort was only significantly-associated with lower CCyR and MMR rates and the poor PFS. Lower HGB concentration and larger spleen size were significantly-associated with the lower cytogenetic and molecular response rates in AP patients; initial the second-generation TKI treatment, the higher treatment response rates; lower PLT count, higher blasts and Ph + ACA, poorer TFS; Ph + ACA, poorer OS. Conclusion:At present, the vast majority of newly-diagnosed CML-CP or AP patients could benefit from TKI treatment in the long term with the good treatment responses and survival outcomes.

Objective:To investigate the post-traumatic stress response in women with unintended pregnancy termination and analyze its related factors.Methods:Totally 388 women with unintended pregnancy termination from two public hospitals in Fujian were selected as the research subjects.They were assessed with the Impact of E-vent Scale-Revised(IES-R),Hospital Anxiety and Depression Scale(HADS),Connor-Davidson Resilience Scale(CD-RISC)and Perinatal Grief Scale(PGS).The total score of IES-R ≥35 was positive for post-traumatic stress disorder screening.Results:The total score of IES-R was(20.6±12.4),and the positive rate of post-traumatic stress disorder screening was 16.5％.Multiple linear regression analysis showed that the IES-R total scores were higher in those who thought pregnancy timing was appropriate than those who thought pregnancy timing was wrong(β=0.13),and lower in women with moderate pain during termination than in those with severe pain(β=-0.09).The IES-R total scores were positively correlated with gestational weeks,depression scores of the HADS and grief scores of the PGS(β=0.18,0.27,0.16),and negatively correlated with optimism scores of the CD-RISC(β=-0.12).Conclusion:The post-traumatic stress response of unintended termination of pregnancy is at a moder-ate level.Post-traumatic stress symptoms are more likely to occur in women who thought pregnancy timing is ap-propriate,and those with severe pain during pregnancy termination,large gestational weeks,high level of depression during pregnancy,and high level of grief after pregnancy termination.

DNA origami is a powerful technique for generating nanostructures with dynamic properties and intelligent controllability. The precise geometric shapes, high programmability, and excellent biocompatibility make DNA origami nanostructures an emerging drug delivery vehicle. The shape, size of the carrier material, as well as the loading and release of drugs are important factors affecting the bioavailability of drugs. This paper focuses on the controllable design of DNA origami nanostructures, efficient drug loading, and intelligent drug release. It summarizes the cutting-edge applications of DNA origami technology in biomedicine, and discusses areas where researchers can contribute to further advancing the clinical application of DNA origami carriers.

Four furan α-butenolactones were isolated from 50% acetone extract of tuber of Alisma orientale by silica gel column, chromatography gel column and high performance liquid chromatography techniques. Their structures were identified by modern wave spectroscopy techniques and electronic circular dichroism (ECD) and assigned as (5R)-5-hydroxy-3,4-dimethylfuran-2(5H)-one (1), 5-hydroxy-3,5-dimethylfuran-2(5H)-one (2), 5-hydroxy-4-(1-methylethyl)-2(5H)-furanone (3) and alismanoid A (4). Compound 1 was new compound and compounds 2–4 were first isolated from Alisma orientale. Compound 1-4 had potential antifibrotic activities.