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Abstract Background Cancer survivors face elevated risks of heart failure (HF) and death, with cardiac dysfunction being a significant concern. Current evaluations often emphasize systolic function while insufficiently addressing diastolic function. This study aims to investigate the prevalence of diastolic dysfunction and assess its prognostic implications in long-term cancer survivors. Methods We analyzed participants from the Atherosclerosis Risk in Communities (ARIC) Study with complete echocardiographic assessments and documented cancer histories. Diastolic function was classified by guideline criteria: normal (≤ 1 abnormal parameter), indeterminate (2 abnormal parameters), and dysfunction (≥ 3 abnormal parameters). The primary outcomes were incident HF and all-cause death. Diastolic dysfunction prevalence was compared between cancer survivors and non-cancer participants after propensity score matching. Cox regression, Kaplan–Meier, and restricted cubic spline (RCS) analyses were used to assess associated risks. Results A total of 5322 participants were included, with 18.4% (N = 979) being cancer survivors. The mean age of cancer survivors at echocardiography was 76.3 (5.10) years, with a median of 12.17 years since diagnosis. There were no significant differences in diastolic dysfunction prevalence (12.26% vs 10.73%, P = 0.29) after matching. Cox regression revealed a graded association between diastolic dysfunction and risks of HF and death. Fully adjusted hazard ratios were 2.59 (95% CI: 1.59–4.20, P

Abstract The aim of this research was to determine the residues of dioxins and dioxin-like polychlorinated biphenyls in cultured eel and find out the source of pollution and the distribution pattern of eels. One hundred samples of eel, 4 fodder samples, and 12 environmental samples (water, plants, and soil) were collected from 4 cities and counties in Jiangxi Province, China. The contents of 17 kinds of dioxins (PCDD/Fs) and 12 kinds of dioxin-like polychlorinated biphenyls (dl-PCBs) were determined by high-resolution gas chromatography-tandem mass spectrometry, and the exposure risk was evaluated by using risk index. The total toxicity equivalence quantity (TEQ) of dioxin and dioxin-like polychlorinated biphenyls in eel and fodder samples collected in the study area were 0.65 ± 0.31 pg/g and 0.10 ± 0.02 pg/g, respectively. Dl-PCBs were the main dioxin pollution in eel and fodder samples. 2,3',4,4',5-pentachlorodiphenyl and 2,3,3',4,4'-pentachlorobiphenyl were the main contributing monomers. The environmental samples were mainly polluted by polychlorinated dibenzo-p-dioxins (PCDDs), with the main contributing monomer being Octachlorodibenzodioxins (OCDD), while 3,3',4,4',5-pentachlorobiphenyl and 2,3,4,7,8-pentachlorodibenzofuran were the main toxic compounds in eel and fodder. The dioxin pollution of eels cultured in Jiangxi Province was mainly from fodder polluted via dl-PCBs. The meat segment VI (tail) exhibited a strong enrichment effect of polychlorinated benzofurans (PCDFs). It should be the key part for dioxins and dioxin-like polychlorinated biphenyls assessment. Further, the results were helpful to improve the edible safety of eel products and the efficiency of the risk assessment of dioxins and dioxin-like polychlorinated biphenyls in fish. Graphical Abstract

In this paper, we propose a novel approach to coordinate-based acoustic emission (AE) source localization to address the challenges of limited and imbalanced datasets from fiber-optic AE sensors used for structural health monitoring (SHM). We have developed a hybrid deep learning model combining four generative adversarial network (GAN) variants for data augmentation with an adapted inception neural network for regression-based prediction. The experimental setup features a single fiber-optic AE sensor based on a tightly coiled fiber-optic Fabry-Perot interferometer formed by two identical fiber Bragg gratings. AE signals were generated using the Hsu-Nielsen pencil lead break test on a grid-marked thin aluminum plate with 35 distinct locations, simulating real-world structural monitoring conditions in bounded isotropic plate-like structures. It is demonstrated that the single-sensor configuration can achieve precise localization, avoiding the need for a multiple sensor array. The GAN-based signal augmentation expanded the dataset from 900 to 4500 samples, with the Wasserstein distance between the original and synthetic datasets decreasing by 83% after 2000 training epochs, demonstrating the high fidelity of the synthetic data. Among the GAN variants, the standard GAN architecture proved the most effective, outperforming other variants in this specific application. The hybrid model exhibits superior performance compared to non-augmented deep learning approaches, with the median error distribution comparisons revealing a significant 50% reduction in prediction errors, accompanied by substantially improved consistency across various AE source locations. Overall, this developed hybrid approach offers a promising solution for enhancing AE-based SHM in complex infrastructures, improving damage detection accuracy and reliability for more efficient predictive maintenance strategies.

Abstract Aggregation‐induced emission (AIE) is a phenomenon where a molecule that is weakly or non‐luminescent in a diluted solution becomes highly emissive when aggregated. AIE luminogens (AIEgens) hold promise in diverse applications like bioimaging, chemical sensing, and optoelectronics. Investigation in AIE luminescence is also critical for understanding aggregation kinetics as the aggregation process is an essential component of AIE emission. Experimental investigation of AIEgen aggregation is challenging due to the fast timescale of the aggregation and the amorphous aggregate structures. Computer simulations such as molecular dynamics (MD) simulation provide a valuable approach to complement experiments with atomic‐level knowledge to study the fast dynamics of aggregation processes. However, individual simulations still struggle to systematically elucidate heterogeneous kinetics of the formation of amorphous AIEgen aggregates. Kinetic network models (KNMs), constructed from an ensemble of MD simulations, hold great potential in addressing this challenge. In these models, dynamic processes are modeled as a series of Markovian transitions occurring among metastable conformational states at discrete time intervals. In this perspective article, we first review previous studies to characterize the AIEgen aggregation kinetics and their limitations. We then introduce KNMs as a promising approach to elucidate the complex kinetics of aggregations to address these limitations. More importantly, we discuss our perspective on linking the output of KNMs to experimental observations of time‐resolved AIE luminescence. We expect that this approach can validate the computational predictions and provide great insights into the aggregation kinetics for AIEgen aggregates. These insights will facilitate the rational design of improved AIEgens in their applications in biology and materials sciences.

The spread of the FluA virus poses significant public health concerns worldwide. Fluorescent lateral flow immunoassay (LFIA) test strips have emerged as vital tools for the early detection and monitoring of influenza infections. However, existing quantitative virus-detection methods, particularly those utilizing smartphone-based sensing platforms, encounter accessibility challenges in resource-limited areas and among the elderly population. Despite their advantages in speed and portability, these platforms often lack user-friendliness for these demographics, impeding their widespread utilization. To address these challenges, this study proposes leveraging the optical pick-up unit (OPU) sourced from commercial optical drives as a readily available fluorescence excitation module for the quantitative detection of antibodies labeled with quantum-dot fluorescent microspheres. Additionally, we utilize miniaturized and high-performance optical components and 3D-printed parts, along with a customized control system, to develop an affordable point-of-care testing (POCT) device. Within the system, a stepping motor scans the test strip from the T-line to the C-line, enabling the calculation of the fluorescence-intensity ratio between the two lines. This simple yet effective design facilitates rapid and straightforward field or at-home testing for FluA. The proposed prototype platform demonstrates promising performance, achieving a limit of detection (LOD) of 2.91 ng/mL, a total detection time of no more than 15 min, and dimensions of 151 mm × 11.2 mm × 10.8 mm3. We believe that the proposed approach holds great potential for improving access to an accurate influenza diagnosis.

Egg products after thermal treatment possess a unique flavor and are favored by consumers. In this study, the key aroma-active compounds of egg yolk products and their formation mechanism during thermal treatment were investigated. The volatile aroma compounds in egg yolks were monitored using an electronic nose, gas chromatography-mass spectrometry (GC–MS) and gas chromatography–olfactometry–mass spectrometry (GC–O–MS), and the lipid molecular species were explored using ultra-high-performance liquid chromatography– mass spectrometry with a Q-Exactive HF-X Orbitrap (UPLC-Q-Exactive HF-X). A total of 68 volatile compounds were identified. Boiled eggs mainly derived their flavor from hexanal, 2-pentyl-furan, 2-butanone, 3-methyl-butanal and heptane. Meanwhile, fried eggs relied mainly on 14 compounds, the most important of which were 2-ethyl-3-methyl-pyrazine, 3-ethyl-2,5-dimethyl-pyrazine, 2-ethyl-3,5-dimethyl-pyrazine, nonanal and 2,3-diethyl-5-methyl-pyrazine, providing a baked and burnt sugar flavor. A total of 201 lipid molecules, belonging to 21 lipid subclasses, were identified in egg yolks, and 13 oxidized lipids were characterized using a molecular network. Phosphoethanolamines (PEs) containing polyunsaturated fatty acids were the primary flavor precursors contributing to the development of egg yolks’ flavor, participating in lipid oxidation reactions and the Maillard reaction and regulating the production of aldehydes and pyrazine compounds. This study provides reference and guidance for the development of egg yolk flavor products.

Objective • This study aimed to investigate the clinical impact of goal-oriented, evidence-based nursing in preventing perioperative stress injuries. Methods • A total of 380 patients undergoing surgery were allocated into either the control or study group. The study group received goal-oriented, evidence-based nursing, while the control group received routine nursing care. Various perioperative indicators, including operating time, position change time, intraoperative bleeding, and length of hospitalization, were assessed and compared between the two groups. Additionally, the Mini-Nutritional Assessment (MNA) score, Munro score, incidence of stress injuries, and nursing satisfaction rate were compared. Patients with perioperative pressure sores (PS) were further evaluated using the Pressure Ulcer Healing Score (PUSH), Braden Stress Injury Scale (Braden), visual analogue scale of pain (VAS), and wound healing time. Results • The study group exhibited higher MNA levels during and after the operation, while Munro levels were lower compared to the control group (P < .05). The study group demonstrated a shorter length of stay and quicker body position changes than the control group. Incidence of pressure sores (PS) was lower in the study group, accompanied by higher nursing satisfaction. PS patients in the study group had lower VAS and PUSH scores, higher Braden scores, and shorter wound healing times than those in the control group. Conclusion • This study highlights the efficacy of goal- oriented, evidence-based nursing in reducing perioperative stress injuries, advocating its adoption for improved care and patient outcomes. However, the single-center design limits generalizability, necessitating further validation. Ultimately, this approach signifies a step forward in nursing practice, promising better patient recovery and satisfaction. [ABSTRACT FROM AUTHOR]

Intrinsically disordered regions (IDR) and short linear motifs (SLiMs) play pivotal roles in the intricate signaling networks governed by phosphatases and kinases. B56δ (encoded by PPP2R5D) is a regulatory subunit of protein phosphatase 2A (PP2A) with long IDRs that harbor a substrate-mimicking SLiM and multiple phosphorylation sites. De novo missense mutations in PPP2R5D cause intellectual disabilities (ID), macrocephaly, Parkinsonism, and a broad range of neurological symptoms. Our single-particle cryo-EM structures of the PP2A-B56δ holoenzyme reveal that the long, disordered arms at the B56δ termini fold against each other and the holoenzyme core. This architecture suppresses both the phosphatase active site and the substrate-binding protein groove, thereby stabilizing the enzyme in a closed latent form with dual autoinhibition. The resulting interface spans over 190 Å and harbors unfavorable contacts, activation phosphorylation sites, and nearly all residues with ID-associated mutations. Our studies suggest that this dynamic interface is coupled to an allosteric network responsive to phosphorylation and altered globally by mutations. Furthermore, we found that ID mutations increase the holoenzyme activity and perturb the phosphorylation rates, and the severe variants significantly increase the mitotic duration and error rates compared to the normal variant. [ABSTRACT FROM AUTHOR]