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PurposePatients with advanced prostate cancer (PCa) often develop castration-resistant PCa (CRPC) with poor prognosis. Prognostic information obtained from multiparametric magnetic resonance imaging (mpMRI) and histopathology specimens can be effectively utilized through artificial intelligence (AI) techniques. The objective of this study is to construct an AI-based CRPC progress prediction model by integrating multimodal data.Methods and materialsData from 399 patients diagnosed with PCa at three medical centers between January 2018 and January 2021 were collected retrospectively. We delineated regions of interest (ROIs) from 3 MRI sequences viz, T2WI, DWI, and ADC and utilized a cropping tool to extract the largest section of each ROI. We selected representative pathological hematoxylin and eosin (H&E) slides for deep-learning model training. A joint combined model nomogram was constructed. ROC curves and calibration curves were plotted to assess the predictive performance and goodness of fit of the model. We generated decision curve analysis (DCA) curves and Kaplan–Meier (KM) survival curves to evaluate the clinical net benefit of the model and its association with progression-free survival (PFS).ResultsThe AUC of the machine learning (ML) model was 0.755. The best deep learning (DL) model for radiomics and pathomics was the ResNet-50 model, with an AUC of 0.768 and 0.752, respectively. The nomogram graph showed that DL model contributed the most, and the AUC for the combined model was 0.86. The calibration curves and DCA indicate that the combined model had a good calibration ability and net clinical benefit. The KM curve indicated that the model integrating multimodal data can guide patient prognosis and management strategies.ConclusionThe integration of multimodal data effectively improves the prediction of risk for the progression of PCa to CRPC.

Abstract Background This study conducted a survey of men who have sex with men (MSM) in Maanshan City of Anhui Province to assess the risk behaviors related to human immunodeficiency virus (HIV) infection. Methods A cross-sectional survey was conducted from June 2016 to June 2019. The MSM were recruited by a peer-driven sampling method. A face-to-face interview with anonymous questionnaire was used for data collection. The information collected by the survey was summarized and epidemiology described the basic characteristics of MSM, and then the related factors were statistically analyzed. Results A total of 934 MSM were recruited with a average age was 30.5 (SD = 8.90) years old, including 816 (87.4%) HIV negative participants and 118 (12.6%) HIV positive ones. This study showed that freelancer (OR = 4.02, 95% CI: 1.96–8.23), scope of sexual partners distribution (OR = 1.78, 95% CI: 1.36–2.33), number of male sexual partners (OR = 2.11, 95% CI: 1.47–3.02), role of anal sex with men was receptive (OR = 2.54, 95% CI: 1.25–5.13) and versatile (OR = 2.34, 95% CI: 1.31–4.19) and non-steady sex partners (OR = 2.14, 95% CI: 1.56–2.93) were risk factors for HIV infection, while monthly income (OR = 0.68, 95% CI: 0.57–0.82), education level (OR = 0.79, 95% CI: 0.66–0.95), frequency of condom use (OR = 0.53, 95% CI: 0.35–0.81) and number of oral sex partners (OR = 0.35, 95% CI: 0.24–0.51) in the past 6 months were protective factors for HIV infection. Conclusion Risk behaviors were common in MSM, and urgent need for targeted and comprehensive interventions to reduce risky sexual behaviour and to prevent HIV infection in MSM.

Abstract Purpose Prostate cancer (PCa) with high Ki-67 expression and high Gleason Scores (GS) tends to have aggressive clinicopathological characteristics and a dismal prognosis. In order to predict the Ki-67 expression status and the GS in PCa, we sought to construct and verify MRI-based radiomics signatures. Methods and materials We collected T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images from 170 PCa patients at three institutions and extracted 321 original radiomic features from each image modality. We used support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) logistic regression to select the most informative radiomic features and built predictive models using up sampling and feature selection techniques. Using receiver operating characteristic (ROC) analysis, the discriminating power of this feature was determined. Subsequent decision curve analysis (DCA) assessed the clinical utility of the radiomic features. The Kaplan–Meier (KM) test revealed that the radiomics-predicted Ki-67 expression status and GS were prognostic factors for PCa survival. Result The hypothesized radiomics signature, which included 15 and 9 selected radiomics features, respectively, was significantly correlated with pathological Ki-67 and GS outcomes in both the training and validation datasets. Areas under the curve (AUC) for the developed model were 0.813 (95% CI 0.681,0.930) and 0.793 (95% CI 0.621, 0.929) for the training and validation datasets, respectively, demonstrating discrimination and calibration performance. The model's clinical usefulness was verified using DCA. In both the training and validation sets, high Ki-67 expression and high GS predicted by radiomics using SVM models were substantially linked with poor overall survival (OS). Conclusions Both Ki-67 expression status and high GS correlate with PCa patient survival outcomes; therefore, the ability of the SVM classifier-based model to estimate Ki-67 expression status and the Lasso classifier-based model to assess high GS may enhance clinical decision-making.

Objective To investigate the relationship between metabolomic profiles, genome-wide polygenic risk scores (PRSs) and risk of rheumatoid arthritis (RA).Methods 143 nuclear magnetic resonance-based plasma metabolic biomarkers were measured among 93 800 participants in the UK Biobank. The Cox regression model was used to assess the associations between these metabolic biomarkers and RA risk, and genetic correlation and Mendelian randomisation analyses were performed to reveal their causal relationships. Subsequently, a metabolic risk score (MRS) comprised of the weighted sum of 17 clinically validated metabolic markers was constructed. A PRS was derived by assigning weights to genetic variants that exhibited significant associations with RA at a genome-wide level.Results A total of 620 incident RA cases were recorded during a median follow-up time of 8.2 years. We determined that 30 metabolic biomarkers were potentially associated with RA, while no further significant causal associations were found. Individuals in the top decile of MRS had an increased risk of RA (HR 3.52, 95% CI: 2.80 to 4.43) compared with those below the median of MRS. Further, significant gradient associations between MRS and RA risk were observed across genetic risk strata. Specifically, compared with the low genetic risk and favourable MRS group, the risk of incident RA in the high genetic risk and unfavourable MRS group has almost elevated by fivefold (HR 6.10, 95% CI: 4.06 to 9.14).Conclusion Our findings suggested the metabolic profiles comprising multiple metabolic biomarkers contribute to capturing an elevated risk of RA, and the integration of genome-wide PRSs further improved risk stratification.

The commercialization of sodium-ion batteries (SIBs) as an effective alternative to lithium-ion batteries (LIBs) has garnered considerable attention. Among the various anodes for SIBs, hard carbon (HC) with expanded carbon layer spacing is the most promising candidate for commercialization. However, the intricate structure of HC can impact the initial coulombic efficiency (ICE) and cycling performance of the cell, potentially resulting in suboptimal capacity and rate capabilities. Here we find that the waste Camellia semiserrata shell (CSshell) can serve as a precursor for biomass-derived HC material, featuring unique edge-graphitized carbon layer structures formed through direct carbonization, distinct from conventional reported HC structures. Such an edge-graphitized HC material exhibits an exceptional initial reversible capacity of 320.06 mA h g−1 at a current density of 50 mA g−1 and a capacity retention of 93.7% after 1200 cycles at 500 mA g−1. The identification of the edge-graphited HC material, obtained from the waste CSshell, suggests a promising contender for low-cost and eco-friendly anode materials for SIBs. [ABSTRACT FROM AUTHOR]

Alkaline exchange membrane fuel cells (AEMFCs) hold great promise as highly efficient hydrogen energy conversion devices, largely due to the broad range of catalyst options available under alkaline conditions. However, the hydrogen oxidation reaction (HOR) at the anode exhibits significantly slower kinetics compared to proton exchange membrane fuel cells, which poses a challenge for achieving high performance. Iridium (Ir)-based catalysts present a compelling alternative to platinum (Pt)-based counterparts for the HOR in alkaline media due to their appropriate adsorption energy for both hydrogen and hydroxyl, alongside their superior CO tolerance. This review comprehensively summarizes recent advancements in the design strategies of advanced electrocatalysts for the alkaline HOR, including alloying effects, interface engineering, lattice strain, and phase engineering, focusing on their critical roles in modulating the electronic structure and coordination environments. Finally, the review discusses current challenges and offers perspectives on the future directions for improving the performance of Ir-based electrocatalysts. This review will guide future research in the development of high-performance Ir-based HOR electrocatalysts for AEMFCs. [ABSTRACT FROM AUTHOR]

AIM: To study the histological and ultrastructural changes of mouse retina after exposure to e-cigarette and the potential mechanism.METHODS: Totally 18 male c57BL mice aged 8-week-old were divided into control group(n=6), 0mg nicotine group(n=6)and 12mg nicotine group(n=6). The histological and ultrastructural changes of retina were evaluated by hematoxylin and eosin(HE)staining and transmission electron microscope(TEM), respectively. Additionally, the expression of Tuj1 and 8-OHdG was examined using immunofluorescent staining. RESULTS: In comparison with control group, the thickness of whole retina, nerve fiber layer(NFL)and inner plexiform layer(IPL)was significantly decreased in experimental groups(0mg and 12mg nicotine group)(P0.05). The dramatically reduced microvilli of RPE cells were also observed in experimental groups using TEM. Furthermore, residual microvilli were shortened. The expression of Tuj1 was decreased in ganglion cell layer(GCL), NFL and IPL, but no significant changes in the number of retinal ganglion cells were shown among three groups(P>0.05). In addition, the increased expression of 8-OHdG was observed in GCL and inner nuclear layer(INL)in experimental groups.CONCLUSION: E-cigarette can lead to the retinal damages in mice, which might be due to oxidative stress.

Background. Preoperative eye-covering training for 3 hours has been reported to effectively reduce the incidence of emergence delirium (ED) in preschool children. However, most children can only maintain the eye being covered for less than 60 min, and shortening eye-covering duration can also achieve similar clinical effects as long duration of eye-covering. This study was designed to compare the effects of 30-min and 60-min eye-covering pretreatment based on cartoon education only on preoperative anxiety, postoperative ED, and pain score after ophthalmic surgery with general anesthesia in preschool-aged children. Methods. Preschool-aged children (3–7 years) who were diagnosed with cataract, blepharoptosis, trichiasis, strabismus, eyelid tumor, and underwent ophthalmic surgery with general anesthesia from August 2021 to January 2022 were recruited. A total of 228 patients were randomly assigned at a 1 : 1:1 ratio to receive 30-min eye covering (30-min group), 60-min eye covering (60-min group) pretreatment, or programmed education only (C group). The preoperative anxiety, postoperative emergence delirium, and pain were compared between the groups. Results. The preoperative anxiety score, postoperative ED score, and incidence of ED in the 30-min group (n = 76) and 60-min group (n = 72) were significantly lower than those in the C group (n = 76), demonstrating a significant between-group difference (P0.05). Moreover, no significant difference was found in postoperative pain scores among the three groups (H = 0.274, P=0.872). Conclusion. Both 30-min and 60-min eye-covering pretreatments significantly reduce preoperative anxiety and postoperative ED after ophthalmic surgery with general anesthesia in preschool-aged children. The effects of the two groups show no intergroup difference, but the 30-min eye-covering pretreatment may be more convenient for practicing. Trial Registration. This study was registered with the No. NCT04973150.

A silylated melamine sponge (SMS) was prepared by two simple steps, namely, immersion and dehydration of a melamine sponge coated with methyltrichlorosilane. The silylated structure of SMS was characterized by FT-IR (Fourier-transform infrared) spectroscopy, SEM (Scanning electron microscopy) and in terms of water contact angles. Its oil-water absorption and separation capacities were measured by FT-IR and UV-visible spectrophotometry. The experimental results have shown that oligomeric silanol covalently bonds by Si-N onto the surface of melamine sponge skeletons. SMS has shown superhydrophobicity with a water contact angle exceeding 150° ± 1°, a better separation efficiency with regard to diesel oil (by 99.31% (wt/wt%) in oil-water mixture and even up to 99.99% (wt/wt%) for diesel oil in its saturated aqueous solution. Moreover, SMS inherited the intrinsic flame retardancy of the melamine sponge. In general, SMS has shown superhydrophobicity, high porosity, excellent selectivity, remarkable recyclability, and better absorption capacity for various oils and organic solvents, and a high separation efficiency for oil in saturated aqueous solutions. [ABSTRACT FROM AUTHOR]