First-in-Human Study to Assess the Safety, Pharmacokinetics, and Pharmacodynamics of BMS-986308: A Renal Outer Medullary Potassium Channel Inhibitor.

In patients with heart failure (HF) who respond inadequately to loop diuretic therapy, BMS-986308, an oral, selective, reversible renal outer medullary potassium channel (ROMK) inhibitor may represent an effective diuretic with a novel mechanism of action. We present data from the first-in-human study aimed to assess the safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) following single ascending doses of BMS-986308 in healthy adult participants. Forty healthy participants, aged from 20 to 55 years, and body mass index (BMI) from 19.8 to 31.6 kg/m2 were assigned to 1 of 5 dose cohorts (1, 3, 10, 30, and 100 mg) and randomized (6:2) to receive BMS-986308 oral solution or matching placebo. Following administration, BMS-986308 was rapidly absorbed with a median time to maximum concentration (Tmax) of 1.00 to 1.75 h and exhibiting a mean terminal half-life (t1/2) of approximately 13 h. Dose proportionality was evident in BMS-986308 area under the concentration-time curve (AUC), while maximum concentration (Cmax) was slightly greater than dose-proportional. We observed that urine output (or diuresis; mL) and urinary sodium excretion (or natriuresis; mmol) increased in a dose-dependent manner, starting at a minimum pharmacologically active dose of 30 mg. The largest mean changes from baseline in diuresis and natriuresis occurred in both the 6- and -24 h post-dose period following administration of 100 mg (1683.0 mL and 2055.3 mL, and 231.7 mmol and 213.7 mmol, respectively; ***P < 0.001). Overall, single-dose BMS-986308 was found to be safe, well-tolerated, with an excellent PK profile, and substantial diuretic and natriuretic activity.

Association between abdominal obesity indices and falls among older community-dwellers in Guangzhou, China: a prospective cohort study.

BACKGROUND: Central obesity was considered as a risk factor for falls among the older population. Waist circumference (WC), lipid accumulation product (LAP), visceral adiposity index (VAI), and the Chinese visceral adiposity index (CVAI) are considered as surrogate markers for abdominal fat deposition in increasing studies. Nevertheless, the longitudinal relationship between these indices and falls among the older population remains indistinct. This study aimed to explore the association between abdominal obesity indices and falls among older community-dwellers. METHODS: Our study included 3501 individuals aged ≥ 65 years from the Guangzhou Falls and Health Status Tracking Cohort at baseline in 2021 and then prospectively followed up in 2022. The outcome of interest was the occurrence of falls. The Kaplan-Meier curves and multivariable Cox regression analysis were used to explore the associations between abdominal obesity indices and falls. Moreover, the restricted cubic spline analysis (RCS) was conducted to test the non-linear relationships between abdominal obesity indices and hazards of falls incident. RESULTS: After a median follow-up period of 551 days, a total of 1022 participants experienced falls. The cumulative incidence rate of falls was observed to be higher among individuals with central obesity and those falling within the fourth quartile (Q4) of LAP, VAI, and CVAI. Participants with central obesity and those in Q4 of LAP, VAI, and CVAI were associated with higher risk of falls, with hazard ratios (HRs) of 1.422 (HR 95%CI: 1.255-1.611), 1.346 (1.176-1.541), 1.270 (1.108-1.457), 1.322 (1.154-1.514), respectively. Each 1-SD increment in WC, LAP, VAI, and CVAI was a significant increased risk of falls among participants. Subgroup analysis further revealed these results were basically stable and appeared to be significantly stronger among those females, aged 65-69 years, and with body mass index (BMI) ≥ 28 kg/m2. Additionally, RCS curves showed an overall upward trend in the risk of falls as the abdominal indices increased. CONCLUSIONS: Abdominal obesity indices, as WC, LAP, VAI, and CVAI were significantly associated with falls among older community-dwellers. Reduction of abdominal obesity indices might be suggested as the strategy of falls prevention.

Irinotecan plus raltitrexed as second-line treatment in locally advanced or metastatic colorectal cancer patients: a prospective open-label, single-arm, multi-center, phase II study.

BACKGROUND: Colorectal cancer is the third most common cancer and the second leading cause of cancer death. There are limited therapeutic options for the treatment of locally advanced or metastatic colorectal cancers which fail first-line chemotherapy. Phase I/II studies showed that the combined application of the raltitrexed and irinotecan has significant synergistic effect and acceptable toxicity. However, most of these previous studies have relatively small sample size. METHODS: This is a prospective open-label, single-arm, multi-center, Phase II trial. Brief inclusion criteria: patients were aged 18 to 75 years with locally advanced or metastatic colorectal cancer after failure of 5-FU and oxaliplatin therapy. Enrolled patients received raltitrexed (3 mg/m2, d1) and irinotecan (180 mg/m2, d1) each 21-day cycle until disease progression or unacceptable toxicity. The primary endpoint was progression-free survival, and the secondary endpoints were disease control rate, objective response rate, overall survival and safety. RESULTS: A total of 108 patients were enrolled between September 2016 and May 2020. The median age was 61 years, ECOG 1 score accounts for 67.6%, the rest were ECOG 0. A total of 502 cycles were completed, with an average of 4.6 cycles and a median of 4 cycles. 108 patients were evaluated, with an objective response rate of 17.6%, and disease control rate of 76.9%. The median follow-up time was 27 months (range:3.1-61.0 m) at data cut-off on March 2023. Median progression-free survival was 4.9 months (95% CI 4.1-5.7) and median overall survival was 13.1 months (95% CI 12.2-15.5). The most common adverse events that were elevated are alanine aminotransferase increased, aspartate aminotransferase increased, fatigue, diarrhoea, neutrocytopenia, thrombocytopenia, hypohemoglobin, and leukocytopenia. Most of the adverse events were Grade I/II, which were relieved after symptomatic treatment, and there were no treatment-related cardiotoxicities and deaths. CONCLUSIONS: The combination of raltitrexed and irinotecan as second-line treatment for mCRC could be a reliable option after failure of standard 5-Fu-first-line chemotherapy in locally advanced or metastatic colorectal cancers, especially for patients with 5-FU intolerance (cardiac events or DPD deficiency patients). TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03053167, registration date was 14/2/2017.

Knowledge-reinforced explainable next basket recommendation.

The next basket recommendation task aims to predict the items in the user's next basket by modeling the user's basket sequence. Existing next basket recommendations focus on improving recommendation performance, and most of these methods are black-box models, ignoring the importance of providing explanations to improve user satisfaction. Furthermore, most next basket recommendation methods are designed for consumer users, and few methods are proposed for business user characteristics. To address the above problems, we propose a Knowledge Reinforced Explainable Next Basket Recommendation (KRE-NBR). Specifically, we construct a basket-based knowledge graph and obtain pretrained embeddings of entities that contain rich information of the knowledge graph. To obtain high-quality user predictive vectors, we fuse user pretrained embeddings, user basket sequence level embeddings, and user repurchase embeddings. One highlight of the user repurchase embeddings is that they are able to model business user repurchase behavior. To make the results of next basket recommendations explainable, we use reinforcement learning for path reasoning to find the items recommended in the next basket and generate recommendation explanations at the same time. To the best of our knowledge, this is the first work to provide recommendation explanations for next basket recommendations. Extensive experiments on real datasets show that the recommendation performance of our proposed approach outperforms several state-of-the-art baselines.

Distinguishing Quantum Phases through Cusps in Full Counting Statistics.

Measuring physical observables requires averaging experimental outcomes over numerous identical measurements. The complete distribution function of possible outcomes or its Fourier transform, known as the full counting statistics, provides a more detailed description. This method captures the fundamental quantum fluctuations in many-body systems and has gained significant attention in quantum transport research. In this Letter, we propose that cusp singularities in the full counting statistics are a novel tool for distinguishing between ordered and disordered phases. As a specific example, we focus on the superfluid-to-Mott transition in the Bose-Hubbard model. Through both analytical analysis and numerical simulations, we demonstrate that the full counting statistics exhibit a cusp singularity as a function of the phase angle in the superfluid phase when the subsystem size is sufficiently large, while it remains smooth in the Mott phase. This discontinuity can be interpreted as a first-order transition between different semiclassical configurations of vortices. We anticipate that our discoveries can be readily tested using state-of-the-art ultracold atom and superconducting qubit platforms.

Benzo-Extended Heli(aminoborane)s: Inner Rim BN-Doped Helical Molecular Carbons with Remarkable Chiroptical Properties.

Atomically precise synthesis of three-dimensional boron-nitrogen (BN)-based helical structures constitutes an undeveloped field with challenges in synthetic chemistry. Herein, we synthesized and comprehensively characterized a new class of helical molecular carbons, named benzo-extended [n]heli(aminoborane)s ([n]HABs), in which the helical structures consisted of n = 8 and n = 10 ortho-condensed conjugated rings with alternating BN atoms at the inner rims. X-ray crystallographic analysis, photophysical studies, and density functional theory calculations revealed the unique characteristics of this novel [n]HAB system. Owing to the high enantiomerization energy barriers, the optical resolution of [8]HAB and [10]HAB was achieved with chiral high-performance liquid chromatography. The isolated enantiomers of [10]HAB exhibited record absorption and luminescence dissymmetry factors (|gabs|=0.061; |glum|=0.048), and boosted CPL brightness up to 292 M-1 cm-1, surpassing most helicene derivatives, demonstrating that the introduction of BN atoms into the inner positions of helicenes can increase both the |gabs| and |glum| values.

Prediction of Surface Subsidence in Mining Areas Based on Ascending-Descending Orbits Small Baseline Subset InSAR and Neural Network Optimization Models.

Surface subsidence hazards in mining areas are common geological disasters involving issues such as vegetation degradation and ground collapse during the mining process, which also raise safety concerns. To address the accuracy issues of traditional prediction models and study methods for predicting subsidence in open-pit mining areas, this study first employed 91 scenes of Sentinel-1A ascending and descending orbits images to monitor long-term deformations of a phosphate mine in Anning City, Yunnan Province, southwestern China. It obtained annual average subsidence rates and cumulative surface deformation values for the study area. Subsequently, a two-dimensional deformation decomposition was conducted using a time-series registration interpolation method to determine the distribution of vertical and east-west deformations. Finally, three prediction models were employed: Back Propagation Neural Network (BPNN), BPNN optimized by Genetic Algorithm (GA-BP), and BPNN optimized by Artificial Bee Colony Algorithm (ABC-BP). These models were used to forecast six selected time series points. The results indicate that the BPNN model had Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE) within 7.6 mm, while the GA-BP model errors were within 3.5 mm, and the ABC-BP model errors were within 3.7 mm. Both optimized models demonstrated significantly improved accuracy and good predictive capabilities.

High-Performance Organic Aerogels Tailored for Versatile Recycling Approaches: Recycling-Reforming-Upcycling.

Organic aerogels are emerging as promising materials due to their versatile properties, rendering them excellent candidates for a variety of applications in the fields of thermal insulation, energy storage, pharmaceuticals, chemical adsorption, and catalysis. However, current aerogel designs rely on cross-linked polymer networks, which lack efficient end-of-use solutions, thereby hindering their overall sustainability. In this study, a facile synthesis of organic aerogels with a unique combination of imine and cyanurate moieties is presented, resulting in high-performance, lightweight insulating materials. The aerogels' structure, ensures mechanical robustness, thermal resistance, and hydrophobicity without additional treatments, crucial for long-term performance. Additionally, in response to the currently unsustainable use of cross-linked polymer materials, the molecular design offers diverse avenues of chemical recycling. These include full depolymerization back into the original monomers, partial network fragmentation producing soluble oligomers that can be promptly employed to fabricate new aerogels, and upcycling of aerogel waste into useful building blocks. This work pioneers a novel approach to material design, emphasizing recyclability as a core feature while maintaining high-performance excellence.

Photoluminescence Tuning of Stable CaYGaO4: Bi/Eu via Compositional Modulation and Crystallographic Site Engineering for nUV wLEDs.

The olivine-based gallate CaYGaO4 (CYG) with unique cationic ordering, rich lattice sites, and self-photoluminescence (PL) is suitable for application as a host of phosphor. However, research in this area is still in its early stages, especially in high-quality full-spectrum white lighting. Herein, novel CYG: Bi3+/Eu3+ with a controllable PL property is designed based on energy transfer and superposition of emissions from blue self-PL, blue PL of Bi3+, and red-PL of Eu3+. Intriguingly, PL intensity and quantum efficiency could be enhanced via codoping Li+/Zn2+ separately/simultaneously because of their two intentional functions as both charge balancer and flux. Unlike self- and Eu3+ PL, Bi3+ PL is quite sensitive to the lattice environment owing to its exposed 6s2 electronic configuration and is tuned via codoping Sr2+ to regulate the nephelauxetic effect and crystal field splitting concurrently around Bi3+. Meanwhile, for further regulating the PL of Bi3+ and obtaining "warm" white light, La3+ is codoped into the phosphor via crystallographic site engineering to control the substitution trends of Bi3+ at distinct lattice sites. Finally, as a proof-of-concept, a full-spectrum phosphor-converted white-light-emitting diode device under nUV pumping with remarkable color rendering index (Ra), high luminous efficiency, and chemical/thermal stability is achieved by utilizing the individual CYG:Bi/Eu/Li/Zn/Sr/La phosphor via a remote "capping" packaging method.

Improving the removal rate of bisphenol A and Cu2+ from water using P/N coexisting ß-cyclodextrin-based adsorbents by enhancing adsorbents-pollutants interactions.

Bisphenol A (BPA), a prominent endocrine-disrupting compound, has garnered considerable attention due to its urgent need for rapid removal from water. Herein, we first used a novel reactive phosphine oxide containing tertiary amines as crosslinker to prepare water-insoluble crosslinked ß-cyclodextrin (ß-CD) adsorbent via radical-mediated thiol-ene polymerization. Owing to the synergistic hydrogen-bond (H-bond) interactions of functional groups (tertiary amine and PO groups) toward BPA, the resulted adsorbents showed fast adsorption kinetics to BPA with an adsorption equilibrium time of 5 min. After six adsorption-desorption cycles, the removal efficiency of BPA was 92.5 %, indicating its excellent reusability. Due to the presence of the CS bonds, the ß-CD -derived bio-adsorbents offered binding sites for Cu2+ ions, resulting in a maximum adsorption capacity of 113.89 mg g-1.

MIGP: Metapath Integrated Graph Prompt Neural Network.

Graph neural networks (GNNs) leveraging metapaths have garnered extensive utilization. Nevertheless, the escalating parameters and data corpus within graph pre-training models incur mounting training costs. Consequently, GNN models encounter hurdles including diminished generalization capacity and compromised performance amidst small sample datasets. Drawing inspiration from the efficacy demonstrated by self-supervised learning methodologies in natural language processing, we embark on an exploration. We endeavor to imbue graph data with augmentable, learnable prompt vectors targeting node representation enhancement to foster superior adaptability to downstream tasks. This paper proposes a novel approach, the Metapath Integrated Graph Prompt Neural Network (MIGP), which leverages learnable prompt vectors to enhance node representations within a pretrained model framework. By leveraging learnable prompt vectors, MIGP aims to address the limitations posed by mall sample datasets and improve GNNs' model generalization. In the pretraining stage, we split symmetric metapaths in heterogeneous graphs into short metapaths and explicitly propagate information along the metapaths to update node representations. In the prompt-tuning stage, the parameters of the pretrained model are fixed, a set of independent basis vectors is introduced, and an attention mechanism is employed to generate task-specific learnable prompt vectors for each node. Another notable contribution of our work is the introduction of three patent datasets, which is a pioneering application in related fields. We will make these three patent datasets publicly available to facilitate further research on large-scale patent data analysis. Through comprehensive experiments conducted on three patent datasets and three other public datasets, i.e., ACM, IMDB, and DBLP, we demonstrate the superior performance of the MIGP model in enhancing model applicability and performance across a variety of downstream datasets. The source code and datasets are available in the website.1.

Revealing the optimal traditional processing methods and its protective effects against febrile seizures of Arisaema cum bile.

Arisaema cum bile (known as Dan Nanxing in Chinese, DNX) is a herbal medicine used for treating febrile seizure (FS), which commonly prepared by using Arisaematis Rhizoma and animal bile. This study was designed to explore the optimal processing time of DNX and its potential mechanism on the anti-FS effect. A total of 17 volatile organic compounds (VOCs) were the characteristic ones to distinguish different fermentation stages of DNX by using gas chromatography-ion mobility spectrometry (GC-IMS), such as 2-heptanone monomer, and heptanal monomer. DNX with fermentation for 3 months had an obvious pattern of VOCs with others, which could be regarded as the optimal fermentation time. The Enterococcus and Staphylococcus might be the core bacteria on the production of VOCs. Additionally, DNX (2.8 g/kg, p.o.) reversed hot water bath-induced FSs of rats, as indicated by increased seizure latency and decreased seizure duration time. It also prevented hippocampal neuronal loss, increased GABAAR, and decreased GRIA1 expression. At the genus level, relative abundance of Enterococcus and Akkermansia were enriched after DNX treatment. These findings suggested that fermentation for 3 months might be the optimal process time for DNX, and DNX possess an anti-FS effect through regulating neurotransmitter disorder and gut microbiota.

Enhancing Defect-Induced Dipole Polarization Strategy of SiC@MoO3 Nanocomposite Towards Electromagnetic Wave Absorption.

Defect engineering in transition metal oxides semiconductors (TMOs) is attracting considerable interest due to its potential to enhance conductivity by intentionally introducing defects that modulate the electronic structures of the materials. However, achieving a comprehensive understanding of the relationship between micro-structures and electromagnetic wave absorption capabilities remains elusive, posing a substantial challenge to the advancement of TMOs absorbers. The current research describes a process for the deposition of a MoO3 layer onto SiC nanowires, achieved via electro-deposition followed by high-temperature calcination. Subsequently, intentional creation of oxygen vacancies within the MoO3 layer was carried out, facilitating the precise adjustment of electromagnetic properties to enhance the microwave absorption performance of the material. Remarkably, the SiC@MO-t4 sample exhibited an excellent minimum reflection loss of - 50.49 dB at a matching thickness of 1.27 mm. Furthermore, the SiC@MO-t6 sample exhibited an effective absorption bandwidth of 8.72 GHz with a thickness of 2.81 mm, comprehensively covering the entire Ku band. These results not only highlight the pivotal role of defect engineering in the nuanced adjustment of electromagnetic properties but also provide valuable insight for the application of defect engineering methods in broadening the spectrum of electromagnetic wave absor ption effectiveness. SiC@MO-t samples with varying concentrations of oxygen vacancies were prepared through in-situ etching of the SiC@MoO3 nanocomposite. The presence of oxygen vacancies plays a crucial role in adjusting the band gap and local electron distribution, which in turn enhances conductivity loss and induced polarization loss capacity. This finding reveals a novel strategy for improving the absorption properties of electromagnetic waves through defect engineering.

Identification of Key Toxic Substances Considering Metabolic Activation: A Combination of Transcriptome and Nontarget Analysis.

There have been numerous studies using effect-directed analysis (EDA) to identify key toxic substances present in source and drinking water, but none of these studies have considered the effects of metabolic activation. This study developed a comprehensive method including a pretreatment process based on an in vitro metabolic activation system, a comprehensive biological effect evaluation based on concentration-dependent transcriptome (CDT), and a chemical feature identification based on nontarget chemical analysis (NTA), to evaluate the changes in the toxic effects and differences in the chemical composition after metabolism. Models for matching metabolites and precursors as well as data-driven identification methods were further constructed to identify toxic metabolites and key toxic precursor substances in drinking water samples from the Yangtze River. After metabolism, the metabolic samples showed a general trend of reduced toxicity in terms of overall biological potency (mean: 3.2-fold). However, metabolic activation led to an increase in some types of toxic effects, including pathways such as excision repair, mismatch repair, protein processing in endoplasmic reticulum, nucleotide excision repair, and DNA replication. Meanwhile, metabolic samples showed a decrease (17.8%) in the number of peaks and average peak area after metabolism, while overall polarity, hydrophilicity, and average molecular weight increased slightly (10.3%). Based on the models for matching of metabolites and precursors and the data-driven identification methods, 32 chemicals were efficiently identified as key toxic substances as main contributors to explain the different transcriptome biological effects such as cellular component, development, and DNA damage related, including 15 industrial compounds, 7 PPCPs, 6 pesticides, and 4 natural products. This study avoids the process of structure elucidation of toxic metabolites and can trace them directly to the precursors based on MS spectra, providing a new idea for the identification of key toxic pollutants of metabolites.

Pre-treatment plasma retinol binding protein 4 level and its change after treatments predict systemic treatment response in psoriasis patients.

BACKGROUND: Retinol binding protein 4 (RBP4) is a mediator of inflammation and related to skin lesion formation, which suggests its engagement in psoriasis pathology and progression. This study intended to explore the change in RBP4 after systemic treatments, and its ability to predict treatment response in psoriasis patients. METHODS: This prospective study enrolled 85 psoriasis patients and 20 healthy subjects. Plasma RBP4 was detected by enzyme-linked immunosorbent assay at baseline and 12th week (W12) after systemic treatments in psoriasis patients, as well as after enrollment in healthy subjects. Psoriasis Area and Severity Index (PASI) 75 and PASI 90 were evaluated at W12 in psoriasis patients. RESULTS: RBP4 at baseline was higher in psoriasis patients than in healthy subjects [median (interquartile range): 13.39 (9.71-22.92) versus 9.59 (6.57-13.72) µg/mL] (P = 0.003). In psoriasis patients, 50 (58.8%) patients achieved PASI 75 at W12, and 25 (29.4%) patients achieved PASI 90 at W12. RBP4 was decreased at W12 compared to its level at baseline (P < 0.001). Lower RBP4 at baseline predicted achieving PASI 75 at W12 (P = 0.038). Greater RBP4 change (baseline-W12) precited achieving PASI 75 (P = 0.036) and PASI 90 (P = 0.045) at W12. Receiver operating characteristic curves suggested that after adjustment for all clinical features, RBP4 at baseline and RBP4 change (baseline-W12) had an acceptable ability to predict PASI 75 and PASI 90 at W12 with all area under curve values > 0.7. CONCLUSION: Plasma RBP4 is decreased after systemic treatments, and its low baseline level and greater decline after treatments predict good treatment response in psoriasis patients.

Exploring Aqueous Solution-Processed Pseudohalide Rare-Earth Double Perovskite Ferroelectrics toward X-ray Detection with High Sensitivity.

Three-dimensional (3D) pseudohalide rare-earth double perovskites (PREDPs) have garnered significant attention for their versatile physical properties, including ferroelectricity, ferroelasticity, large piezoelectric responses, and circularly polarized luminescence. However, their potential for X-ray detection remains unexplored, and the low Curie temperature (TC) limits the performance window for PREDP ferroelectrics. Here, by applying the chemical regulation strategies involving halogen substitution on the organic cation and Rb/Cs substitution to the PREDP [(R)-M3HQ]2RbEu(NO3)6 [(R)-M3HQ = (R)-N-methyl-3-hydroxylquinuclidinium] with a low TC of 285 K, a novel 3D PREDP ferroelectric [(R)-CM3HQ]2CsEu(NO3)6 [(R)-CM3HQ = (R)-N-chloromethyl-3-hydroxylquinuclidinium] are successfully synthesized, for which the TC reaches 344 K. More importantly, such a strategy endowed [(R)-CM3HQ]2CsEu(NO3)6 with notable X-ray detection capabilities. Centimeter-sized [(R)-CM3HQ]2CsEu(NO3)6 single crystals fabricated from aqueous solutions demonstrated a sensitivity of 1307 µC Gyair-1 cm-2 and a low detectable dose rate of 152 nGyair s-1, the highest sensitivity reported for hybrid double perovskite ferroelectric detectors. This work positions PREDPs as promising candidates for the next generation of eco-friendly optoelectronic materials and also offers substantial insights into the interaction between structure, composition, and functionality in ferroelectric materials.

Associations between type 2 diabetes mellitus and risk of falls among community-dwelling elderly people in Guangzhou, China: a prospective cohort study.

BACKGROUND: Several studies have demonstrated that older adults with type 2 diabetes mellitus (T2DM) have a higher risk of falls compared to those without T2DM, which may lead to disability and a lower quality of life. While, limited prospective studies have quantified the associations in southern China. We conducted a longitudinal cohort study to quantify the associations between T2DM and falls and investigate the risk factors of falls among community-dwelling elderly people in Guangzhou, China. METHODS: The population-based study included 8800 residents aged 65 and over in 11 counties of Guangzhou at baseline in 2020 and then prospectively followed up through 2022. Of 6169 participants had complete follow-up and were included in the present study. A fall event was identified by self-reported. The Cox regression was applied to quantify the associations between T2DM and falls, and hazard ratios (HRs) were calculated to the factors associated with falls among participants. RESULTS: The median follow-up time for participants was 2.42 years. During the follow-up period, the incidence of falls among all participants was 21.96%. After adjusting for covariates in Cox regression models, T2DM remained a significant risk factor for falls, with HR of 1.781 (95% CI: 1.600-1.983) in the unadjusted covariates model and 1.757 (1.577-1.957) in the adjusted covariates model. Female (1.286, 1.136-1.457), older age (≥ 80: 1.448, 1.214-1.729), single marital status (1.239, 1.039-1.477), lower education level (primary school and below: 1.619, 1.004-1.361), hypertension (1.149, 1.026-1.286) and stroke (1.619, 1.176-2.228) were associated with a higher risk of falls, whereas everyday physical exercise (0.793, 0.686-0.918) was associated with a lower risk of falls. CONCLUSION: Falls are common, with risks between T2DM and falls quantified and several factors investigated in the longitudinal cohort study among community-dwelling elderly people in Guangzhou, China. Targeted action on the risk factors may reduce the burden of falls in elderly people with T2DM in the future.

Synthetic Nicotinamide Cofactors as Alternatives to NADPH in Imine Reductase-Catalyzed Reactions.

This study demonstrates the effectiveness of synthetic nicotinamide cofactors as cost-effective alternatives to NADPH in imine reductase (IRED) catalysis. The synthetic cofactors maintained catalytic activity and stereoselectivity, achieving high conversion rates. Molecular docking studies revealed key structural interactions influencing performance. Combining a glucose dehydrogenase (GDH) recycling system further enhanced the stability and efficiency. These findings highlight the potential of synthetic cofactors to reduce costs and improve the feasibility of IRED-catalyzed processes for industrial applications.

Applying urinary ultrasound to predict the risk of spontaneous ureteral stone passage: a retrospective cohort study.

BACKGROUND: To assess the value of urological ultrasound in predicting the risk of spontaneous passage of ureteral stones. METHODS: Clinical and ultrasound data were collected consecutively from patients receiving conservative treatment for ureteral stones, and the outcome of spontaneous passage was followed up for 1 month. Ultrasound variables independently associated with the risk of spontaneous stone passage were screened. A logistic regression prediction model was constructed based on the independent risk factors, and the discriminative efficacy and clinical utility of the prediction model in inferring the risk of spontaneous passing were assessed by the receiver operating characteristic (ROC) curve, calibration curve and clinical decision curve. RESULTS: A total of 163 patients undergoing conservative treatment for ureteral stones were included in the study, with a mean age of 45.95 ± 13.01 years. Among them, 47 cases (28.83%) experienced failure of spontaneous stone passage. Multivariable analysis revealed that stone length (OR: 2.622, P = 0.027), distal stone location (OR: 0.219, P = 0.003), and ureteral jetting frequency (OR: 6.541, P < 0.001) were independent risk factors for spontaneous stone passage. A prediction model incorporating stone length, stone location, and affected ureteral jetting frequency was developed to assess the risk of spontaneous stone passage. The area under the ROC curve was 0.814 (95% CI: 0.747-0.882), indicating good discriminatory power. The prediction model also demonstrated favorable net clinical benefit. CONCLUSION: A prediction model based on ultrasound-derived stone length, location, and ureteral jetting frequency can accurately evaluate the risk of spontaneous stone passage in patients with ureteral stones, providing a basis for optimizing the clinical decision-making on ureteral stones, and has reliable clinical application value.

Analysis of the beneficial effects of prior soybean cultivation to the field on corn yield and soil nitrogen content.

Corn-soybean rotation is a cropping pattern to optimize crop structure and improve resource use efficiency, and nitrogen (N) fertilizer application is an indispensable tool to increase corn yields. However, the effects of N fertilizer application levels on corn yield and soil N storage under corn-soybean rotation have not been systematically studied. The experimental located in the central part of the Songnen Plain, a split-zone experimental design was used with two planting patterns of continuous corn (CC) and corn-soybean rotations (RC) in the main zone and three N application rates of 0, 180, and 360 kg hm-2 of urea in the secondary zone. The research has shown that RC treatments can enhance plant growth and increase corn yield by 4.76% to 79.92% compared to CC treatments. The amount of N fertilizer applied has a negative correlation with yield increase range, and N application above 180 kg hm-2 has a significantly lower effect on corn yield increase. Therefore, a reduction in N fertilizer application may be appropriate. RC increased soil N storage by improving soil N-transforming enzyme activity, improving soil N content and the proportion of soil organic N fractions. Additionally, it can improve plant N use efficiency by 1.4%-5.6%. Soybeans grown in corn-soybean rotations systems have the potential to replace more than 180 kg hm-2 of urea application. Corn-soybean rotation with low N inputs is an efficient and sustainable agricultural strategy.