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NiFe layered double hydroxide (NiFe-LDH) nanosheets and metal-nitrogen-carbon materials (M-N-C, M = Ni, Fe, Co, etc.) are supreme catalysts in the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) process, respectively. Nevertheless, the monotonic performance and insufficient stability severely hamper their practical application in rechargeable batteries. Herein, we simultaneously combine ultrathin NiFe-LDH nanowalls with renewable soybean-derived Fe-N-C matrix to obtain a hybrid materials (NiFe-LDH/FeSoy-CNSs-A), which exhibits robust catalytic activities for OER ( E j=10 = 1.53 V vs. RHE) and ORR ( E 1/2 = 0.91 V vs. RHE), with a top-notch battery parameters and stability in assembled rechargeable Zn-air batteries. Intensive investigations indicate that the vertically dispersed NiFe-LDH nanosheets, Fe-N-C matrix derived from soybean and the strong synergy between them are responsible for the unprecedented OER and ORR performances. The key role of intrinsic N defects involved in the hybrid materials is firstly specified by ultrasoundassisted extraction of soy protein from soybean. The exquisite design can facilitate the utilization of sustainable biomass-derived catalysts, and the mechanism investigations of N defects and oxygenic groups on the structure-activity relationship can stimulate the progress of other functional hybrid electrocatalysts.

Destruction of cellular redox homeostasis to induce cancer cell apoptosis is an emerging tumor therapeutic strategy. To achieve this goal, elevating exogenous oxidative stress or impairing the antioxidant defense system of cancer cells is an effective method. Herein, we firstly report a biocompatible and versatile nanoplatform based on mesoporous polydopamine (MpDA) nanoparticles and a phase‐change material (PCM) for delivering calcium ascorbate (Vc‐Ca), simultaneously enabling combination therapy of hyperthermia, reactive oxygen species (ROS) generation, and suppression of tumor antioxidant capability. In this design, Vc‐Ca encapsulated in MpDA using PCM is controllably released due to the melting of PCM matrix in response to photothermal heating upon near‐infrared irradiation. Vc‐Ca is proved to be a pro‐oxidant that can promote the production of ROS (H2O2) in the tumor site. Remarkably, MpDA can not only act as a photothermal agent but also can break the redox balance of cancer cells through depleting the primary antioxidant glutathione, thus amplifying Vc‐Ca‐mediated oxidative therapy. Both in vitro and in vivo results demonstrate the significantly enhanced antitumor activity of boosted ROS combined with local hyperthermia. This study highlights the potential applications of Vc‐Ca in cancer treatment, and the prepared multifunctional nanoplatform provides a novel paradigm for high‐efficiency oxidation‐photothermal therapy. An original nanoplatform based on mesoporous polydopamine nanoparticles (MpDA) and a phase‐change material for delivering calcium ascorbate (Vc‐Ca) were successfully fabricated. Vc‐Ca locked in MpDA can be triggered by hyperthermia to selectively produce H2O2 in the tumor sites. MpDA can amplify Vc‐Ca‐mediated reactive oxygen species (ROS) therapy by destructing the redox homeostasis. This multifunctional nanoplatform exhibits enhanced ROS and photothermal synergistic therapy efficiency.

Background Non-cystic fibrosis bronchiectasis is a chronic respiratory disease characterized by bronchial dilation. However, the significance of elevated eosinophil counts in acute exacerbations of bronchiectasis remains unclear. Methods This retrospective case-control study included 169 hospitalized patients with acute exacerbations of non-cystic fibrosis bronchiectasis. Based on blood eosinophil levels, patients were categorized into eosinophilic and non-eosinophilic bronchiectasis groups. Various clinical variables, including lung function, comorbidities and clinical features were collected for analysis. The study aimed to examine the differences between these groups and their clinical phenotypes. Results Eosinophilic bronchiectasis (EB) was present in approximately 22% of all hospitalized patients with bronchiectasis, and it was more prevalent among male smokers ( P <  0.01). EB exhibited greater severity of bronchiectasis, including worse airway obstruction, higher scores in the E-FACED (FACED combined with exacerbations) and bronchiectasis severity index (BSI), a high glucocorticoids medication possession ratio, and increased hospitalization cost ( P  < 0.05 or P  < 0.01). Furthermore, we observed a significant positive correlation between blood eosinophil count and both sputum eosinophils (r = 0.49, P  < 0.01) and serum total immunoglobulin E levels (r = 0.21, P  < 0.05). Additional analysis revealed that patients with EB had a higher frequency of shortness of breath ( P <  0.05), were more likely to have comorbid sinusitis ( P <  0.01), and exhibited a greater number of lung segments affected by bronchiectasis ( P  < 0.01). Conclusions These findings suggest that EB presents a distinct pattern of bronchiectasis features, confirming the notion that it is a specific phenotype.

Background Ovarian cancer (OC) is often associated with an unfavorable prognosis. Given the crucial involvement of lysosomes in tumor advancement, lysosome-related genes (LRGs) hold promise as potential therapeutic targets. Methods To identify differentially expressed lysosome-related genes (DE-LRGs), we performed a matching analysis between differentially expressed genes (DEGs) in OC and the pool of LRGs. Genes with prognostic significance were analyzed using multiple regression analyses to construct a prognostic risk signature. The model's efficacy was validated through survival analysis in various cohorts. We further explored the model's correlation with clinical attributes, tumor microenvironment (TME), mutational patterns, and drug sensitivity. The quantitative real-time polymerase chain reaction (qRT-PCR) validated gene expression in OC cells. Results A 10-gene prognostic risk signature was established. Survival analysis confirmed its predictive accuracy across cohorts. The signature served as an independent prognostic element for OC. The high-risk and low-risk groups demonstrated notable disparities in terms of immune infiltration patterns, mutational characteristics, and sensitivity to therapeutic agents. The qRT-PCR results corroborated and validated the findings obtained from the bioinformatic analyses. Conclusions We devised a 10-LRG prognostic model linked to TME, offering insights for tailored OC treatments.

Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However, its widespread application has been limited by the heavy resource burden of CMR interpretation. Here, to address this challenge, we developed and validated computerized CMR interpretation for screening and diagnosis of 11 types of CVD in 9,719 patients. We propose a two-stage paradigm consisting of noninvasive cine-based CVD screening followed by cine and late gadolinium enhancement-based diagnosis. The screening and diagnostic models achieved high performance (area under the curve of 0.988 ± 0.3% and 0.991 ± 0.0%, respectively) in both internal and external datasets. Furthermore, the diagnostic model outperformed cardiologists in diagnosing pulmonary arterial hypertension, demonstrating the ability of artificial intelligence-enabled CMR to detect previously unidentified CMR features. This proof-of-concept study holds the potential to substantially advance the efficiency and scalability of CMR interpretation, thereby improving CVD screening and diagnosis. A two-step, video-based deep learning model is developed to first screen for cardiac anomalies using noncontrast magnetic resonance imaging, followed by diagnosis of 11 types of cardiovascular disease using gadolinium enhancement-based imaging.

BackgroundThe elimination of HBV covalently closed circular DNA (cccDNA) remains a critical hurdle for chronic hepatitis B (CHB) management.ObjectiveIn this investigation, we examined the efficacy of glycine administration and its potential enhancement in interferon-α (IFN-α) antiviral efficacy to stimulate hepatocyte proliferation to mitigate cccDNA levels.DesignThe study cohort comprised 89 healthy individuals and 496 HBV-infected patients, with subgroups of 30 and 42 participants receiving randomised nucleos(t)ide analogue (NA) and PegIFN-α treatments, respectively. Glycine concentrations were quantified via liquid chromatography‒tandem mass spectrometry, and its diagnostic potential was assessed via receiver operating characteristic curve analysis. The therapeutic impact of glycine was evaluated in various HBV-infected cell lines and murine models via various methodologies including transcriptomic sequencing, metabolomics sequencing, flow cytometry, immunofluorescence and in situ hybridisation.ResultsElevated serum glycine levels with a robust positive correlation with serum alanine aminotransferase levels (R=0.7650) were observed in HBV-infected patients relative to healthy controls. The area under the curve for differentiating patients with HBeAg-expressing CHB from healthy controls was 0.9701. Glycine supplementation diminished HBV cccDNA levels by approximately 50% by promoting hepatocyte proliferation. Glycine is metabolised into a one-carbon unit, activating mTORC1 signalling via glycine transporter-1. Furthermore, glycine ameliorates hepatic inflammation by inhibiting the nuclear factor-kappa B signalling pathway through glycine receptors. Combination therapy with IFN-α effectively suppressed HBV replication, achieving a 60% reduction in HBsAg levels and sustained viral suppression in mice.ConclusionGlycine has the potential to reduce HBV cccDNA levels by stimulating hepatocyte proliferation. The phased administration of glycine and IFN-α significantly enhances its therapeutic efficacy. These findings suggest a novel and promising strategy for the treatment of CHB.

Introduction: The absence of predictive models for early latent tuberculosis infection (LTBI) progression persists. This study aimed to create a screening model to identify high-risk LTBI patients prome to active tuberculosis (ATB) reactivation. Methodology: Patients with confirmed ATB were enrolled alongside LTBI individuals as a reference, with relevant clinical data gathered. LASSO regression cross-validation reduced data dimensionality. A nomogram was developed using multiple logistic regression, internally validated with Bootstrap resampling. Evaluation included C-index, receiver operating characteristic (ROC) curve, and calibration curves, with clinical utility assessed through decision curve analysis. Results: The final nomogram incorporated serum albumin (OR = 1.337, p = 0.046), CD4+ (OR = 1.010, p = 0.004), and CD64 index (OR = 0.009, p = 0.020). The model achieved a C-index of 0.964, an area under the ROC curve of 0.962 (95% CI: 0.926–0.997), sensitivity of 0.971, and specificity of 0.910. Internal validation showed a mean absolute error of 0.013 and 86.4% identification accuracy. The decision curve indicated substantial net benefit at a risk threshold exceeding 10% (1: 9). Conclusions: This study established a biologically-rooted nomogram for high-risk LTBI patients prone to ATB reactivation, offering strong predictability, concordance, and clinical value. It serves as a personalized risk assessment tool, accurately identifying patients necessitating priority prophylactic treatment, complementing existing host risk factors effectively.

Considerable efforts that isolate and characterize degrading bacteria for polycyclic aromatic hydrocarbons (PAHs) have focused on contaminated environments so far. Here we isolated three distinctive pyrene (PYR)-degrading bacteria from a paddy soil that was not contaminated with PAHs. These included a novel Bacillus sp. PyB-9 and efficient degraders, Shigella sp. PyB-6 and Agromyces sp. PyB-10. All three strains could utilize naphthalene, phenanthrene, anthracene, fluoranthene and PYR as sole carbon sources, and degraded PYR in a range of temperatures (27–37 °C) and pH (5–8). Strains PyB-6 and PyB-10 almost completely degraded 50 mg L−1 PYR within 15 days, and 75.5% and 98.9% of 100 mg L−1 PYR in 27 days, respectively. The kinetics of PYR biodegradation was well represented by the Gompertz model. Ten and twelve PYR metabolites were identified in PYR degradation process by strains PyB-6 and PyB-10, respectively. Chemical analyses demonstrated that the degradation mechanisms of PYR were the same for strains PyB-6 and PyB-10 with initial dioxygenation mainly on C-4,5 positions of PYR. The degradation of 4,5-phenanthrenedicarboxylic acid was branched to 4-phenanthrenecarboxylic acid pathway and 5-hydroxy-4-phenanthrenecarboxylic acid pathway, both of which played important roles in PYR degradation by strains PyB-6 and PyB-10. To our knowledge, Shigella sp. and Agromyces sp. were found for the first time to possess the capability for PAHs degradation. These findings contributed to upgrading the bank of microbial resource and knowledge on PAH biodegradation.

Background The objective is to explore the value of preoperative geriatric nutritional risk index (GNRI) in evaluating long-term prognosis in elderly locally advanced rectal cancer (LARC) patients who accepted neoadjuvant chemoradiotherapy (NCRT) and to compare GNRI with established nutritional markers, including prognostic nutritional index (PNI) and controlling nutritional status (CONUT) score. Methods Preoperative GNRI was retrospectively assessed in 172 LARC patients aged ≥ 60 years who underwent radical resection after NCRT at two centers. Optimal cutoff value of GNRI was determined by X-tile program. The association of GNRI with clinicopathological parameters and nutritional markers was analyzed. The survival ability of markers was evaluated using time-dependent receiver-operating characteristic (ROC) curve analysis. Finally, survival analysis was performed using Kaplan–Meier and Cox regression analysis. Results GNRI was highly correlated with nutritional markers. An optimal cutoff value for the GNRI was 96. In the time-dependent ROC curve, GNRI demonstrated a stable predictive ability for both disease-free survival (DFS) and overall survival (OS). Multivariate analysis showed that GNRI was the only nutritional marker that independently predicted DFS (HR 2.457, 95% CI 1.066–5.665, P  = 0.035) and OS (HR 9.002, 95% CI 3.100–26.146, P  < 0.001). As an additional benefit, GNRI was able to stratify survival in subgroups of ypTNM and tumor response. Conclusion Preoperative GNRI is a promising predictor of long-term survival for elderly LARC patients undergoing NCRT, superior to the established nutritional markers.

Background This study aimed to evaluate the clinical feasibility and performance of CT-based auto-segmentation models integrated into an All-in-One radiotherapy workflow for rectal cancer. Methods This study included 312 rectal cancer patients, with 272 used to train three nnU-Net models for CTV45, CTV50, and GTV segmentation, and 40 for evaluation across one internal ( n  = 10), one clinical AIO ( n  = 10), and two external cohorts ( n  = 10 each). Segmentation accuracy (DSC, HD, HD95, ASSD, ASD) and time efficiency were assessed. Results In the internal testing set, mean DSC of CTV45, CTV50, and GTV were 0.90, 0.86, and 0.71; HD were 17.08, 25.48, and 79.59 mm; HD 95 were 4.89, 7.33, and 56.49 mm; ASSD were 1.23, 1.90, and 6.69 mm; and ASD were 1.24, 1.58, and 11.61 mm. Auto-segmentation reduced manual delineation time by 63.3–88.3% ( p  < 0.0001). In clinical practice, average DSC of CTV45, CTV50 and GTV were 0.93, 0.88, and 0.78; HD were 13.56, 23.84, and 35.38 mm; HD 95 were 3.33, 6.46, and 21.34 mm; ASSD were 0.78, 1.49, and 3.30 mm; and ASD were 0.74, 1.18, and 2.13 mm. The results from the multi-center testing also showed applicability of these models, since the average DSC of CTV45 and GTV were 0.84 and 0.80 respectively. Conclusions The models demonstrated high accuracy and clinical utility, effectively streamlining target volume delineation and reducing manual workload in routine practice. Trial registration The study protocol was approved by the Institutional Review Board of Peking University Third Hospital (Approval No. (2024) Medical Ethics Review No. 182-01).