Clinical biomarker-based biological aging and risk of benign prostatic hyperplasia: A large prospective cohort study.

Objective: Chronological age (CAge), biological age (BAge), and accelerated age (AAge) are all important for aging-related diseases. CAge is a known risk factor for benign prostatic hyperplasia (BPH); However, the evidence of association of BAge and AAge with BPH is limited. This study aimed to evaluate the association of CAge, Bage, and AAge with BPH in a large prospective cohort. Method: A total of 135,933 males without BPH at enrolment were extracted from the UK biobank. We calculated three BAge measures (Klemera-Doubal method, KDM; PhenoAge; homeostatic dysregulation, HD) based on 16 biomarkers. Additionally, we calculated KDM-BAge and PhenoAge-BAge measures based on the Levine method. The KDM-AAge and PhenoAge-AAge were assessed by the difference between CAge and BAge and were standardized (mean = 0 and standard deviation [SD] = 1). Cox proportional hazard models were applied to assess the associations of CAge, Bage, and AAge with incident BPH risk. Results: During a median follow-up of 13.150 years, 11,811 (8.690%) incident BPH were identified. Advanced CAge and BAge measures were associated with an increased risk of BPH, showing threshold effects at a later age (all P for nonlinearity <0.001). Nonlinear relationships between AAge measures and risk of BPH were also found for KDM-AAge (P = 0.041) and PhenoAge-AAge (P = 0.020). Compared to the balance comparison group (-1 SD < AAge < 1 SD), the accelerated aging group (AAge > 2 SD) had a significantly elevated BPH risk with hazard ratio (HR) of 1.115 (95% CI, 1.000-1.223) for KDM-AAge and 1.180 (95% CI, 1.068-1.303) for PhenoAge-AAge, respectively. For PhenoAge-AAge, subgroup analysis of the accelerated aging group showed an increased HR of 1.904 (95% CI, 1.374-2.639) in males with CAge <50 years and 1.233 (95% CI, 1.088-1.397) in those having testosterone levels <12 nmol/L. Moreover, AAge-associated risk of BPH was independent of and additive to genetic risk. Conclusions: Biological aging is an independent and modifiable risk factor for BPH. We suggest performing active health interventions to slow biological aging, which will help mitigate the progression of prostate aging and further reduce the burden of BPH.

Near Ultraviolet-Excitable Cyan-Emissive Hybrid Copper(I) Halides Nonlinear Optical Crystals with Near-Unity Photoluminescence Quantum Yield and High-Efficiency X-ray Scintillation.

Designing and synthesizing multifunctional hybrid copper halides with near ultraviolet (NUV) light-excited high-energy emission (< 500 nm) remains challenging. Here, a pair of broadband-excited high-energy emitting isomers, namely, α-/ß-(MePh3P)2CuI3 (MePh3P = methyltriphenylphosphonium), were synthesized. α-(MePh3P)2CuI3 with blue emission peaking at 475 nm is firstly discovered wherein its structure contains regular [CuI3]2‒ triangles and crystallizes in centrosymmetric space group P21/c. While ß-(MePh3P)2CuI3 featuring distorted [CuI3]2‒ planar triangles shows inversion symmetry breaking and crystallizes in the noncentrosymmetric space group P21, which exhibits cyan emission peaking at 495 nm with prominent near-unity photoluminescence quantum yield and the excitation band ranging from 200 to 450 nm. Intriguingly, ß-(MePh3P)2CuI3 exhibits phase-matchable second-harmonic generation response of 0.54 × KDP and a suitable birefringence of 0.06@1064 nm. Furthermore, ß-(MePh3P)2CuI3 also can be excited by X-ray radioluminescence with a high scintillation light yield of 16193 photon/MeV and an ultra-low detection limit of 47.97 nGy/s, which is only 0.87% of the standard medical diagnosis (5.5 µGy/s). This work not only promotes the development of solid-state lighting, laser frequency conversion and X-ray imaging, but also provides a reference for constructing multifunctional hybrid metal halides.

PGD: Shared gene linking polycystic ovary syndrome and endometrial cancer, influencing proliferation and migration through glycometabolism.

The relationship among polycystic ovary syndrome (PCOS), endometrial cancer (EC), and glycometabolism remains unclear. We explored shared genes between PCOS and EC, using bioinformatics to unveil their pathogenic connection and influence on EC prognosis. Gene Expression Omnibus datasets GSE226146 (PCOS) and GSE196033 (EC) were used. A protein-protein interaction (PPI) network was constructed to identify the central genes. Candidate markers were screened using dataset GSE54250. Differences in marker expression were confirmed in mouse PCOS and human EC tissues using RT-PCR and immunohistochemistry. The effect of PGD on EC proliferation and migration was explored using Ki-67 and Transwell assays. PGD's impact on the glycometabolic pathway within carbon metabolism was assessed by quantifying glucose content and lactic acid production. R software identified 31 common genes in GSE226146 and GSE196033. Gene Ontology functional classification revealed enrichment in the "purine nucleoside triphosphate metabolism process," with key Kyoto Encyclopedia of Genes and Genomes pathways related to "carbon metabolism." The PPI network identified 15 hub genes. HK2, NDUFS8, PHGDH, PGD, and SMAD3 were confirmed as candidate markers. The RT-PCR analysis validated distinct HK2 and PGD expression patterns in mouse PCOS ovarian tissue and human EC tissue, as well as in normal and EC cells. Transfection experiments with Ishikawa cells further confirmed PGD's influence on cell proliferation and migration. Suppression of PGD expression impeded glycometabolism within the carbon metabolism of EC cells, suggesting PGD as a significant PCOS risk factor impacting EC proliferation and migration through modulation of single carbon metabolism. These findings highlight PGD's pivotal role in EC onset and prognosis.

Validity of stem cell-loaded scaffolds to facilitate endometrial regeneration and restore fertility: a systematic review and meta-analysis.

Objective: Various stem cell-loaded scaffolds have demonstrated promising endometrial regeneration and fertility restoration. This study aimed to evaluate the efficacy of stem cell-loaded scaffolds in treating uterine injury in animal models. Methods: The PubMed, Embase, Scopus, and Web of Science databases were systematically searched. Data were extracted and analyzed using Review Manager version 5.4. Improvements in endometrial thickness, endometrial glands, fibrotic area, and number of gestational sacs/implanted embryos were compared after transplantation in the stem cell-loaded scaffolds and scaffold-only group. The standardized mean difference (SMD) and confidence interval (CI) were calculated using forest plots. Results: Thirteen studies qualified for meta-analysis. Overall, compared to the scaffold groups, stem cell-loaded scaffolds significantly increased endometrial thickness (SMD = 1.99, 95% CI: 1.54 to 2.44, P < 0.00001; I² = 16%) and the number of endometrial glands (SMD = 1.93, 95% CI: 1.45 to 2.41, P < 0.00001; I² = 0). Moreover, stem cell-loaded scaffolds present a prominent effect on improving fibrosis area (SMD = -2.50, 95% CI: -3.07 to -1.93, P < 0.00001; I² = 36%) and fertility (SMD = 3.34, 95% CI: 1.58 to 5.09, P = 0.0002; I² = 83%). Significant heterogeneity among studies was observed, and further subgroup and sensitivity analyses identified the source of heterogeneity. Moreover, stem cell-loaded scaffolds exhibited lower inflammation levels and higher angiogenesis, and cell proliferation after transplantation. Conclusion: The evidence indicates that stem cell-loaded scaffolds were more effective in promoting endometrial repair and restoring fertility than the scaffold-only groups. The limitations of the small sample sizes should be considered when interpreting the results. Thus, larger animal studies and clinical trials are needed for further investigation. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42024493132.

Mechanisms of gastrointestinal toxicity in neuromyelitis optica spectrum disorder patients treated with mycophenolate mofetil: insights from a mouse model and human study.

Mycophenolate mofetil (MMF) is commonly utilized for the treatment of neuromyelitis optica spectrum disorders (NMOSD). However, a subset of patients experience significant gastrointestinal (GI) adverse effects following MMF administration. The present study aims to elucidate the underlying mechanisms of MMF-induced GI toxicity in NMOSD. Utilizing a vancomycin-treated mouse model, we compiled a comprehensive data set to investigate the microbiome and metabolome in the GI tract to elucidate the mechanisms of MMF GI toxicity. Furthermore, we enrolled 17 female NMOSD patients receiving MMF, who were stratified into non-diarrhea NMOSD and diarrhea NMOSD (DNM) groups, in addition to 12 healthy controls. The gut microbiota of stool samples was analyzed using 16S rRNA gene sequencing. Vancomycin administration prevented weight loss and tissue injury caused by MMF, affecting colon metabolomes and microbiomes. Bacterial ß-glucuronidase from Bacteroidetes and Firmicutes was linked to intestinal tissue damage. The DNM group showed higher alpha diversity and increased levels of Firmicutes and Proteobacteria. The ß-glucuronidase produced by Firmicutes may be important in causing gastrointestinal side effects from MMF in NMOSD treatment, providing useful information for future research on MMF. IMPORTANCE: Neuromyelitis optica spectrum disorder (NMOSD) patients frequently endure severe consequences like paralysis and blindness. Mycophenolate mofetil (MMF) effectively addresses these issues, but its usage is hindered by gastrointestinal (GI) complications. Through uncovering the intricate interplay among MMF, gut microbiota, and metabolic pathways, this study identifies specific gut bacteria responsible for metabolizing MMF into a potentially harmful form, thus contributing to GI side effects. These findings not only deepen our comprehension of MMF toxicity but also propose potential strategies, such as inhibiting these bacteria, to mitigate these adverse effects. This insight holds broader implications for minimizing complications in NMOSD patients undergoing MMF therapy.

The optimization method of wing plasma ice shape regulation based on quantitative assessment of flight risk.

Plasma ice shape regulation is a technology which uses plasma actuator to regulate the continuous ice into safer intermittent ice by its significant thermal effect with limited energy. Whether plasma ice shape regulation could reduce flight risk is a new problem under the wing with continuous ice. The 3D printed ice shapes were arranged on the leading edge of the wing based on NACA0012 airfoil, aiming to simulate the configuration after ice shape regulation. And the aerodynamic parameters were obtained by wind tunnel experiments. The experimental results showed that the ratio of signal regulation ice width d to chord length of the wing b A determined the aerodynamic characteristics, and the aerodynamic characteristics changed better compared with configuration of the continuous ice. However, the flight risk of the wing under given regulation ratio is unknown. Based on the straight and swept wing after regulating, the flight safety boundaries were simulated by the reachable set method. Further, a method of quantitative assessment of flight risk is proposed. Quantitative values of risk were calculated. The results show that the flight risk all decreases from level 2 to level 4 compared with configuration of the continuous ice when d / b A equals 0.15 under conditions of swept and straight wing.

GateView: A Multi-Omics Platform for Gene Feature Analysis of Virus Receptors within Human Normal Tissues and Tumors.

Viruses are obligate intracellular parasites that rely on cell surface receptor molecules to complete the first step of invading host cells. The experimental method for virus receptor screening is time-consuming, and receptor molecules have been identified for less than half of known viruses. This study collected known human viruses and their receptor molecules. Through bioinformatics analysis, common characteristics of virus receptor molecules (including sequence, expression, mutation, etc.) were obtained to study why these membrane proteins are more likely to become virus receptors. An in-depth analysis of the cataloged virus receptors revealed several noteworthy findings. Compared to other membrane proteins, human virus receptors generally exhibited higher expression levels and lower sequence conservation. These receptors were found in multiple tissues, with certain tissues and cell types displaying significantly higher expression levels. While most receptor molecules showed noticeable age-related variations in expression across different tissues, only a limited number of them exhibited gender-related differences in specific tissues. Interestingly, in contrast to normal tissues, virus receptors showed significant dysregulation in various types of tumors, particularly those associated with dsRNA and retrovirus receptors. Finally, GateView, a multi-omics platform, was established to analyze the gene features of virus receptors in human normal tissues and tumors. Serving as a valuable resource, it enables the exploration of common patterns among virus receptors and the investigation of virus tropism across different tissues, population preferences, virus pathogenicity, and oncolytic virus mechanisms.

Effectiveness of simulation-based clinical research curriculum for undergraduate medical students - a pre-post intervention study with external control.

BACKGROUND: Simulation is widely utilized in medical education. Exploring the effectiveness of high-fidelity simulation of clinical research within medical education may inform its integration into clinical research training curricula, finally cultivating physician-scientist development. METHODS: Standard teaching scripts for both clinical trial and cross-sectional study simulation were designed. We recruited undergraduates majoring in clinical medicine at 3th grade into a pre-post intervention study. Additionally, a cross-sectional survey randomly selected medical undergraduates at 4th or 5th grade, medical students in master and doctor degree as external controls. Self-assessment scores of knowledge and practice were collected using a 5-point Likert scale. Changes in scores were tested by Wilcoxon signed-rank test and group comparisons were conducted by Dunn's tests with multiple corrections. Multivariable quantile regressions were used to explore factors influencing the changes from baseline. RESULTS: Seventy-eight undergraduates involved the clinical trial simulation and reported improvement of 1.60 (95% CI, 1.48, 1.80, P < 0.001) in knowledge and 1.82 (95% CI, 1.64, 2.00, P < 0.001) in practice score. 83 undergraduates involved in the observational study simulation and reported improvement of 0.96 (95% CI, 0.79, 1.18, P < 0.001) in knowledge and 1.00 (95% CI, 0.79, 1.21, P < 0.001) in practice. All post-intervention scores were significantly higher than those of the three external control groups, P < 0.001. Higher agreement on the importance of clinical research were correlated with greater improvements in scores. Undergraduates in pre-post study showed high confidence in doing a future clinical research. CONCLUSION: Our study provides evidence supporting the integration of simulation into clinical research curriculum for medical students. The importance of clinical research can be emphasized during training to enhance learning effect.

Recent Progress of Ion-Modified TiO2 for Enhanced Photocatalytic Hydrogen Production.

Harnessing solar energy to produce hydrogen through semiconductor-mediated photocatalytic water splitting is a promising avenue to address the challenges of energy scarcity and environmental degradation. Ever since Fujishima and Honda's groundbreaking work in photocatalytic water splitting, titanium dioxide (TiO2) has garnered significant interest as a semiconductor photocatalyst, prized for its non-toxicity, affordability, superior photocatalytic activity, and robust chemical stability. Nonetheless, the efficacy of solar energy conversion is hampered by TiO2's wide bandgap and the swift recombination of photogenerated carriers. In pursuit of enhancing TiO2's photocatalytic prowess, a panoply of modification techniques has been explored over recent years. This work provides an extensive review of the strategies employed to augment TiO2's performance in photocatalytic hydrogen production, with a special emphasis on foreign dopant incorporation. Firstly, we delve into metal doping as a key tactic to boost TiO2's capacity for efficient hydrogen generation via water splitting. We elaborate on the premise that metal doping introduces discrete energy states within TiO2's bandgap, thereby elevating its visible light photocatalytic activity. Following that, we evaluate the role of metal nanoparticles in modifying TiO2, hailed as one of the most effective strategies. Metal nanoparticles, serving as both photosensitizers and co-catalysts, display a pronounced affinity for visible light absorption and enhance the segregation and conveyance of photogenerated charge carriers, leading to remarkable photocatalytic outcomes. Furthermore, we consolidate perspectives on the nonmetal doping of TiO2, which tailors the material to harness visible light more efficiently and bolsters the separation and transfer of photogenerated carriers. The incorporation of various anions is summarized for their potential to propel TiO2's photocatalytic capabilities. This review aspires to compile contemporary insights on ion-doped TiO2, propelling the efficacy of photocatalytic hydrogen evolution and anticipating forthcoming advancements. Our work aims to furnish an informative scaffold for crafting advanced TiO2-based photocatalysts tailored for water-splitting applications.

The Effect of Antihyperglycemic Medications on COVID-19: A Meta-analysis and Systematic Review from Observational Studies.

BACKGROUND: Diabetes, a chronic disease worldwide, may be associated with a poorer prognosis in patients with coronavirus disease 2019 (COVID-19). While some antihyperglycemic medications may be beneficial, others may increase the risk of adverse clinical outcomes of COVID-19. We aimed to analyze the effect of antihyperglycemic medications on COVID-19. METHODS: We searched the Web of Science, Cochrane Library, EMBASE, PubMed, and Scopus databases from December 2019 to June 2022 to identify literature related to patients with COVID-19 and type 2 diabetes mellitus (T2DM) treated with antihyperglycemic medications. RESULTS: 56 studies were included in the analysis. Metformin (OR 0.66; 95% CI 0.58-0.74; p < 0.05), Glucagon-like peptide-1 receptor agonist (GLP-1ra) (OR 0.73; 95% CI 0.59-0.91; p < 0.05), and sodium-dependent glucose transporters 2 inhibitor (SGLT 2i) (OR 0.77; 95% CI 0.69-0.87; p < 0.05) were associated with lower mortality risk, while insulin was associated with increased mortality risk (OR 1.40; 95% CI 1.26-1.55; p < 0.05). Meanwhile, metformin (OR 0.65; 95% CI 0.50-0.85; p < 0.05) and GLP-1ra (OR 0.84; 95% CI 0.76-0.94; p < 0.05) were significantly associated with decreased severe manifestation risk. What's more, metformin (OR 0.77; 95% CI 0.62-0.96; p < 0.05), GLP-1ra (OR 0.86; 95% CI 0.81-0.92; p < 0.05), and SGLT 2i (OR 0.87; 95% CI 0.79-0.97; p < 0.05) were also associated with a decreased risk of hospitalization, but insulin were associated with an increased risk of hospitalization (OR 1.31; 95% CI 1.12-1.52; p < 0.05). Nevertheless, the results of the subgroup analyses showed that the effects of different glucose-lowering agents on COVID-19 may be related to in-hospital use or out-hospital use, elderly or non-elderly patients use, and different geography. CONCLUSION: Metformin, GLP-1ra, and SGLT 2i have shown a positive effect on clinical outcomes in COVID-19, particularly in non-elderly individuals. However, insulin use may pose a higher risk, especially in elderly patients, so need with caution. Meanwhile, DPP-4i, TZD, α-GLUi, and sulfonylureas appeared to have a neutral effect. These results need to be validated in future clinical studies.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma.

BACKGROUND: The study on predicting the differentiation grade of colorectal cancer (CRC) based on magnetic resonance imaging (MRI) has not been reported yet. Developing a non-invasive model to predict the differentiation grade of CRC is of great value. AIM: To develop and validate machine learning-based models for predicting the differentiation grade of CRC based on T2-weighted images (T2WI). METHODS: We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023. Patients were randomly assigned to a training cohort (n = 220) or a validation cohort (n = 95) at a 7:3 ratio. Lesions were delineated layer by layer on high-resolution T2WI. Least absolute shrinkage and selection operator regression was applied to screen for radiomic features. Radiomics and clinical models were constructed using the multilayer perceptron (MLP) algorithm. These radiomic features and clinically relevant variables (selected based on a significance level of P < 0.05 in the training set) were used to construct radiomics-clinical models. The performance of the three models (clinical, radiomic, and radiomic-clinical model) were evaluated using the area under the curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: After feature selection, eight radiomic features were retained from the initial 1781 features to construct the radiomic model. Eight different classifiers, including logistic regression, support vector machine, k-nearest neighbours, random forest, extreme trees, extreme gradient boosting, light gradient boosting machine, and MLP, were used to construct the model, with MLP demonstrating the best diagnostic performance. The AUC of the radiomic-clinical model was 0.862 (95%CI: 0.796-0.927) in the training cohort and 0.761 (95%CI: 0.635-0.887) in the validation cohort. The AUC for the radiomic model was 0.796 (95%CI: 0.723-0.869) in the training cohort and 0.735 (95%CI: 0.604-0.866) in the validation cohort. The clinical model achieved an AUC of 0.751 (95%CI: 0.661-0.842) in the training cohort and 0.676 (95%CI: 0.525-0.827) in the validation cohort. All three models demonstrated good accuracy. In the training cohort, the AUC of the radiomic-clinical model was significantly greater than that of the clinical model (P = 0.005) and the radiomic model (P = 0.016). DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process. CONCLUSION: In this study, we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC. This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Changes in disease burden and global inequalities in bladder, kidney and prostate cancers from 1990 to 2019: a comparative analysis based on the global burden of disease study 2019.

BACKGROUND: Bladder, kidney and prostate cancers make significant contributors to cancer burdens. Exploring their cross-country inequalities may inform equitable strategies to meet the 17 sustainable development goals before 2030. METHODS: We analyzed age-standardized disability-adjusted life-years (ASDALY) rates for the three cancers based on Global Burden of Diseases Study 2019. We quantified the inequalities using slope index of inequality (SII, absolute measure) and concentration index (relative measure) associated with national sociodemographic index. RESULTS: Varied ASDALY rates were observed in the three cancers across 204 regions. The SII decreased from 35.15 (95% confidence interval, CI: 29.34 to 39.17) in 1990 to 15.81 (95% CI: 7.99 to 21.79) in 2019 for bladder cancers, from 78.94 (95% CI: 75.97 to 81.31) in 1990 to 59.79 (95% CI: 55.32 to 63.83) in 2019 for kidney cancer, and from 192.27 (95% CI: 137.00 to 241.05) in 1990 to - 103.99 (95% CI: - 183.82 to 51.75) in 2019 for prostate cancer. Moreover, the concentration index changed from 12.44 (95% CI, 11.86 to 12.74) in 1990 to 15.72 (95% CI, 15.14 to 16.01) in 2019 for bladder cancer, from 33.88 (95% CI: 33.35 to 34.17) in 1990 to 31.13 (95% CI: 30.36 to 31.43) in 2019 for kidney cancer, and from 14.61 (95% CI: 13.89 to 14.84) in 1990 to 5.89 (95% CI: 5.16 to 6.26) in 2019 for prostate cancer. Notably, the males presented higher inequality than females in both bladder and kidney cancer from 1990 to 2019. CONCLUSIONS: Different patterns of inequality were observed in the three cancers, necessitating tailored national cancer control strategies to mitigate disparities. Priority interventions for bladder and kidney cancer should target higher socioeconomic regions, whereas interventions for prostate cancer should prioritize the lowest socioeconomic regions. Additionally, addressing higher inequality in males requires more intensive interventions among males from higher socioeconomic regions.

Dual treatment with kynurenine pathway inhibitors and NAD+ precursors synergistically extends life span in Drosophila.

Tryptophan catabolism is highly conserved and generates important bioactive metabolites, including kynurenines, and in some animals, NAD+. Aging and inflammation are associated with increased levels of kynurenine pathway (KP) metabolites and depleted NAD+, factors which are implicated as contributors to frailty and morbidity. Contrastingly, KP suppression and NAD+ supplementation are associated with increased life span in some animals. Here, we used DGRP_229 Drosophila to elucidate the effects of KP elevation, KP suppression, and NAD+ supplementation on physical performance and survivorship. Flies were chronically fed kynurenines, KP inhibitors, NAD+ precursors, or a combination of KP inhibitors with NAD+ precursors. Flies with elevated kynurenines had reduced climbing speed, endurance, and life span. Treatment with a combination of KP inhibitors and NAD+ precursors preserved physical function and synergistically increased maximum life span. We conclude that KP flux can regulate health span and life span in Drosophila and that targeting KP and NAD+ metabolism can synergistically increase life span.

Efficacy and safety of drug-coated balloon for de novo lesions of large coronary arteries: Systematic review and meta-analysis of randomized controlled trials.

Background: Drug-coated balloon (DCB) is a novel approach to avoiding stent-related complications and has proven effective for the treatment of in-stent restenosis (ISR) and small vessels. However, its role in the treatment of de novo lesions in large vessels is less settled. Aims: To estimate the efficacy and safety of drug-coated balloon versus stent in the treatment of de novo lesions in large coronary arteries. Methods: We searched the literature until April 2023. We judged the safety of DCB based on major adverse cardiovascular events (MACEs), cardiac death, all-cause mortality, non-fatal myocardial infarction, target lesion revascularization (TLR), and bleeding event; and efficacy according to late lumen loss (LLL), minimum lumen diameter (MLD). We conducted subgroup analyses according to stent type and whether urgent PCI was required. Results: A total of 10 RCTs were included. Overall, LLL (mean difference (MD) = -0.19, 95 % confidence interval (CI): -0.32 to -0.06, P = 0.003) was lower in the DCB group than in the Stent arm. This effect was consistent in subgroup analysis regardless of stent type and disease type. In terms of safety indicators, there were no significant differences between DCB and stent. The subgroup analyses found that safety indicators showed no significant differences between DCB and drug-eluting stent (DES), but TLR was lower in the DCB than in the bare metal stent (BMS). Moreover, in ST-elevation myocardial infarction (STEMI), safety indicators and LLL showed no significant differences between DCB and DES, but MLD in the DCB was smaller. While in patients with excluded STEMI, MACE and TLR was lower in the DCB compared with the overall stent. Conclusions: DCB could be a promising alternative for treating de novo lesions in large coronary arteries with satisfactory efficacy and low risk, superior to BMS and not inferior to DES, with a trend toward lower late lumen loss.

Sustained Release-Driven Interface Engineering Enables Fast Charging Lithium Metal Batteries.

LiNO3 has attracted intensive attention as a promising electrolyte additive to regulate Li deposition behavior as it can form favorable Li3N, LiNxOy species to improve the interfacial stability. However, the inferior solubility in carbonate-based electrolyte restricts its application in high-voltage Li metal batteries. Herein, an artificial composite layer (referred to as PML) composed of LiNO3 and PMMA is rationally designed on Li surface. The PML layer serves as a reservoir for LiNO3 release gradually to the electrolyte during cycling, guaranteeing the stability of SEI layer for uniform Li deposition. The PMMA matrix not only links the nitrogen-containing species for uniform ionic conductivity but also can be coordinated with Li for rapid Li ions migration, resulting in homogenous Li-ion flux and dendrite-free morphology. As a result, stable and dendrite-free plating/stripping behaviors of Li metal anodes are achieved even at an ultrahigh current density of 20 mA cm-2 (>570 h) and large areal capacity of 10 mAh cm-2 (>1200 h). Moreover, the Li||LiFePO4 full cell using PML-Li anode undergoes stable cycling for 2000 cycles with high-capacity retention of 94.8%. This facile strategy will widen the potential application of LiNO3 in carbonate-based electrolyte for practical LMBs.

Lithium-Ion Charged Polymer Channels Flattening Lithium Metal Anode.

The concentration difference in the near-surface region of lithium metal is the main cause of lithium dendrite growth. Resolving this issue will be key to achieving high-performance lithium metal batteries (LMBs). Herein, we construct a lithium nitrate (LiNO3)-implanted electroactive ß phase polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) crystalline polymorph layer (PHL). The electronegatively charged polymer chains attain lithium ions on the surface to form lithium-ion charged channels. These channels act as reservoirs to sustainably release Li ions to recompense the ionic flux of electrolytes, decreasing the growth of lithium dendrites. The stretched molecular channels can also accelerate the transport of Li ions. The combined effects enable a high Coulombic efficiency of 97.0% for 250 cycles in lithium (Li)||copper (Cu) cell and a stable symmetric plating/stripping behavior over 2000 h at 3 mA cm-2 with ultrahigh Li utilization of 50%. Furthermore, the full cell coupled with PHL-Cu@Li anode and LiFePO4 cathode exhibits long-term cycle stability with high-capacity retention of 95.9% after 900 cycles. Impressively, the full cell paired with LiNi0.87Co0.1Mn0.03O2 maintains a discharge capacity of 170.0 mAh g-1 with a capacity retention of 84.3% after 100 cycles even under harsh condition of ultralow N/P ratio of 0.83. This facile strategy will widen the potential application of LiNO3 in ester-based electrolyte for practical high-voltage LMBs.

Synergistic binding mechanisms of co-contaminants in soil profiles: Influence of iron-bearing minerals and microbial communities.

In contaminated soil sites, the coexistence of inorganic and organic contaminants poses a significant threat to both the surrounding ecosystem and public health. However, the migration characteristics of these co-contaminants within the soil and their interactions with key components, including Fe-bearing minerals, organic matter, and microorganisms, remain unclear. This study involved the collection of a 4.3-m-depth co-contaminated soil profile to investigate the vertical distribution patterns of co-contaminants (namely, arsenic, cadmium, and polychlorinated biphenyls (PCBs)) and their binding mechanisms with environmental factors. The results indicated a notable downward accumulation of inorganic contaminants with increasing soil depth, whereas PCBs were predominantly concentrated in the uppermost layer. Chemical extraction and synchrotron radiation analysis highlighted a positive correlation between the abundance of reactive iron (FeCBD) and both co-contaminants and microbial communities in the contaminated site. Furthermore, Mantel tests and structural equation modeling (SEM) demonstrated the direct impacts of FeCBD and microbial communities on co-contaminants within the soil profile. Overall, these results provided valuable insights into the migration and transformation characteristics of co-contaminants and their binding mechanisms mediated by minerals, organic matter, and microorganisms.

Network pharmacology combined with experimental verification to explore the potential mechanism of naringenin in the treatment of cervical cancer.

Cervical cancer is the second leading cause of morbidity and mortality in women worldwide. Traditional treatment methods have become limited. Naringenin, a flavonoid abundant in various fruits and herbal medicines, has demonstrated anti-tumor properties among other effects. This research undertook to elucidate the mechanism of naringenin in the context of cervical cancer treatment by leveraging network pharmacology and performing experimental validation. Initial steps involved predicting potential naringenin targets and subsequently screening for overlaps between these targets and those related to cervical cancer, followed by analysis of their interrelationships. Molecular docking was subsequently utilized to verify the binding effect of the central target. Within the framework of network pharmacology, it was discovered that naringenin might possess anti-cancer properties specific to cervical cancer. Following this, the anti-tumor effects of naringenin on Hela cell viability, migration, and invasion were assessed employing CCK-8, transwell, wound healing assays, and western blotting. Experimental data indicated that naringenin attenuates the migration and invasion of Hela cells via downregulation EGFR/PI3K/AKT signaling pathway. Thus, our findings suggest that naringenin has therapeutic impacts on cervical cancer via multiple mechanisms, primarily by inhibiting the migration and invasion through the EGFR/PI3K/AKT/mTOR pathway. This study offers fresh insights for future clinical studies.

Boosting the Cycle Performance of Iron Trifluoride Based Solid State Batteries at Elevated Temperatures by Engineering the Cathode Solid Electrolyte Interface.

Iron trifluoride (FeF3) is attracting tremendous interest due to its lower cost and the possibility to enable higher energy density in lithium-ion batteries. However, its cycle performance deteriorates rapidly in less than 50 cycles at elevated temperatures due to cracking of the unstable cathode solid electrolyte interface (CEI) followed by active materials dissolution in liquid electrolyte. Herein, by engineering the salt composition, the Fe3O4-type CEI with the doping of boron (B) atoms in a polymer electrolyte at 60 °C is successfully stabilized. The cycle life of the well-designed FeF3-based composite cathode exceeds an unprecedented 1000 cycles and utilizes up to 70% of its theoretical capacities. Advanced electron microscopy combined with density functional theory (DFT) calculations reveal that the B in lithium salt migrates into the cathode and promotes the formation of an elastic and mechanic robust boron-contained CEI (BOR-CEI) during cycling, by which the durability of the CEI to frequent cyclic large volume changes is significantly enhanced. To this end, the notorious active materials dissolution is largely prohibited, resulting in a superior cycle life. The results suggest that engineering the CEI such as tuning its composition is a viable approach to achieving FeF3 cathode-based batteries with enhanced performance.

Development and validation of a clinical model to predict preconception risk of gestational diabetes mellitus in nulliparous women: A retrospective cohort study.

OBJECTIVE: To develop and validate a model to predict the preconception risk of gestational diabetes mellitus (GDM) in nulliparous women. METHODS: This was a retrospective cohort study. A total of 1565 women in early pregnancy who underwent preconception health examinations in the Women and Children's Hospital of Chongqing Medical University between January 2020 and June 2021 were invited to participate in a questionnaire survey. Logistic regression analysis was performed to determine the preconception risk factors for GDM. These factors were used to construct a model to predict GDM risk in nulliparous women. Then, the model was used to assess the preconception risk of GDM in 1060 nulliparous women. RESULTS: Independent preconception risk factors for GDM included the following: age 35 years or greater, diastolic blood pressure 80 mm Hg or greater, fasting plasma glucose 5.1 mmol/L or greater, body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters) 24 or greater, weight gain 10 kg or greater in the year before pregnancy, age of menarche 15 years or greater, three or more previous pregnancies, daily staple food intake 300 g or greater, fondness for sweets, and family history of diabetes. BMI less than 18.5, daily physical activity duration 1 h or greater, and high-intensity physical activity were protective factors. These factors were used to construct a model to predict GDM risk in nulliparous women, and the incidence of GDM significantly increased as the risk score increased. The area under the curve of the prediction model was 0.82 (95% confidence interval 0.80-0.85). CONCLUSION: The preconception GDM risk prediction model demonstrated good predictive efficacy and can be used to identify populations at high risk of GDM before pregnancy, which provides the possibility for preconception intervention.