Hydrogen isotope exchange (HIE) plays a pivotal role in the synthesis of isotopically labeled compounds, which are widely used in the pharmaceutical industry for drug pharmacokinetic and pharmacodynamic studies. While electrochemical HIE has emerged as a powerful strategy for site-selective labeling of C-H bonds, extending its application to alkyl amine-containing drugs has been hindered by the instability of α-amino radicals and their susceptibility to overoxidation. Here, we report the first electrochemical HIE protocol that enables efficient deuterium (D) labeling of both cyclic and acyclic alkyl amine substrates. The key innovation lies in using 1,3-propanedithiol as the hydrogen atom transfer (HAT) catalyst, which could in situ generate a potent HAT agent─a mercaptothiyl radical─via alternating current electrolysis. This radical benefits from a significantly weakened effective S-H bond dissociation energy of 34 kcal/mol compared to conventional monothiol HAT catalysts (∼80 kcal/mol), driven by exothermic disulfide ring formation. Mechanistic studies and computational analyses reveal a strong structure-activity relationship among dithiols, identifying 1,3-propanedithiol as the optimal catalyst, which is uniquely suited to balance fast HAT kinetics with efficient regeneration of the dithiol. The application of this method to over 30 pharmaceutically relevant compounds achieved up to 3.7 D per molecule. This work addresses a long-standing challenge in electrochemical HIE and introduces a new HAT platform with broad potential in synthetic and biological chemistry.
Dupuytren's contracture (DC) is a fibroproliferative disorder of the palmar fascia with substantial variation in prevalence across populations. However, epidemiological data from Asian countries remain limited, and little is known about upper-limb-specific quality of life or dietary correlates associated with DC. This cross-sectional study investigated the prevalence of DC in a community-dwelling Japanese population, assessed its impact on upper-limb function, and examined demographic, medical, lifestyle, and dietary correlates. DC diagnosis and severity were evaluated by hand surgeons using the original 5-grade clinical staging system proposed by Meyerding in 1936, a historical but practical method for epidemiological surveys that categorizes disease severity based on the number of affected digits and degree of flexion deformity. Demographic and lifestyle data were collected using standardized questionnaires, biochemical parameters were measured from fasting blood samples, upper-limb disability was assessed using the Quick Disabilities of the Arm, Shoulder and Hand (qDASH), and nutrient intake during the preceding month was estimated using the validated Brief Diet History Questionnaire (BDHQ). Among 1,304 participants, DC was identified in 100 (7.7%), with most cases classified as grade 0 (palpable nodules without digital flexion contracture). In univariate analyses, older age, male sex, smoking, diabetes mellitus, manual labor, and several nutrient intakes-including alcohol, protein, carbohydrate, sodium, and omega-3 fatty acids-were associated with DC. Multivariate analyses showed that older age, male sex, and alcohol intake were positively associated with DC. An inverse association between total energy intake and DC was also observed. No measurable difference in qDASH scores was observed according to the presence or severity of DC in this screening cohort. These findings provide additional epidemiological data on DC in a community-dwelling Japanese population, in which most detected cases were mild and identified at an early stage. The BDHQ-based dietary analyses were secondary and exploratory. Although alcohol intake was positively associated with DC, the dietary findings, including the inverse association with total energy intake, should be regarded as hypothesis-generating and require confirmation in longitudinal studies.
Maize ear rot severely restricts maize yield and quality, making the breeding of disease-resistant varieties the core strategy for disease prevention and control. Due to the highly uneven spatial distribution of lesions on maize ears, precise full-surface detection is essential for objectively quantifying disease severity. However, traditional manual disease grading is highly subjective, and conventional RGB-based detection methods struggle to precisely identify lesion regions associated with maize ear rot. These limitations hinder the precise identification and quantitative analysis of maize ear rot infection regions, thereby limiting the reliability of phenotypic data used for resistance evaluation and subsequent genome-wide association studies (GWAS). To address these challenges, this study developed an integrated full-surface hyperspectral imaging system featuring line-scan imaging and synchronous rotation control. Non-redundant full-surface ear images were then generated using the oriented FAST and rotated BRIEF (ORB) algorithm combined with random sample consensus (RANSAC), hereafter referred to as ORB-RANSAC. Furthermore, after Savitzky-Golay (SG) preprocessing and feature selection using a genetic algorithm (GA), three machine learning models and three deep learning models were established, and their classification performance was compared. The results showed that the convolutional neural network-bidirectional long short-term memory network (CNN-Bi-LSTM) model achieved the best average performance, with an average overall accuracy (OA) of 95.61 ± 0.36%. It also achieved higher overall accuracy than traditional machine learning models such as random forest (RF), indicating that CNN-Bi-LSTM can achieve high-precision pixel-level detection of lesion regions showing Fusarium-associated maize ear rot symptoms. Additionally, this model was deployed in locally developed automatic analysis software, enabling an integrated analysis workflow from raw hyperspectral data input to the quantification of disease-related phenotypic parameters. This study not only fills the technical gap in the non-destructive full-surface detection of maize ear rot but also provides an efficient and reliable automated tool for high-throughput phenomics research, which holds great significance for accelerating the discovery of maize resistance genes and ensuring food security.
Camizestrant is a next-generation selective estrogen receptor degrader and complete estrogen receptor antagonist and is being evaluated for the treatment of patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. This phase 1, single-center, single-period, nonrandomized, open-label study sought to determine the mass balance recovery of camizestrant and conduct metabolite profiling and structural identification. Routes of elimination, safety, and tolerability were secondary objectives. Six healthy women postmenopausal participants (median age, 60.5 years, range, 59-69) were administered a single dose of 75 mg oral [14C]camizestrant (solution) following an overnight fast. Blood, urine, and fecal samples were collected at protocol-defined intervals until mass balance criteria were met. By the end of the sampling period (432 hours postdose), 82% of the administered total radioactivity was recovered in excreta (urine, 16.8%; feces, 65.2%). The amount of radioactivity excreted in the feces in the first 24 hours was minimal, providing evidence that camizestrant absorption was high; most of the administered total radioactivity in feces was recovered between 24 and 192 hours postdose, suggesting biliary elimination. Unchanged camizestrant represented 13.6% of the total drug-related material in plasma. Of the 11 identified metabolites in plasma, an N-glucuronide conjugate of camizestrant (M4) and an N-glucuronide of an acid metabolite (M14) were the most abundant (20.1% and 11.2%, respectively). Thirteen metabolites were identified in urine (M4 most abundant; 2.3% of total radioactive dose). Eight metabolites were identified in feces (oxidative defluorinated alcohol metabolite [M1] was most abundant; 14.5% of total radioactive dose); unchanged camizestrant represented 14.5% of the total radioactive dose in feces, with in vitro data supporting unchanged camizestrant being likely due, in part, to hydrolyzed M4. SIGNIFICANCE STATEMENT: This study characterizes the absorption, metabolism, and excretion of camizestrant, a next-generation selective estrogen receptor degrader and complete estrogen receptor antagonist, in healthy humans. The majority was recovered in feces between 24 and 192 hours postdose, suggesting biliary elimination of absorbed camizestrant.
With growing demand for safe and sustainable energy-storage systems, aqueous zinc-ion batteries (AZIBs) are emerging as promising candidates due to their non-flammable electrolytes and environmental benignity. However, their practical deployment is hindered by sluggish Zn2+ transport and electrode instability. In this work, we examine the influence of composition on Zn2+ storage in Prussian Blue Analogue (PBA) positive electrodes- Na2CuFe(CN)6·yH2O (Cu-PBA), Na2CoFe(CN)6·yH2O (Co-PBA) and the mixed-metal Na2Co0.5Cu0.5Fe(CN)6·yH2O (CoCu-PBA). Guided by theoretical calculations, CoCu-PBA exhibits the most favorable Zn2+ intercalation behavior, delivering 58 mAh g-1 at 100 mA g-1. For the negative electrode, Zn-vanadate (ZnxV2O5·yH2O, ZnVO) with its expanded ion-diffusion channels and lower band gap compared to V2O5, provides enhanced diffusion pathways and achieves 80 mAh g-1 at 100 mA g-1. A full AZIB cell assembled using CoCu-PBA and ZnVO with a ZnSO4-silica gel electrolyte delivers a specific capacity of 49 mAh g-1 (@100 mA g-1), an energy density of 61 Wh kg-1 (@125 W kg-1), a power density of 612 W kg-1 (@18 Wh kg-1) and excellent cycling stability (92% retention over 500 cycles at 300 mA g-1). These findings highlight an optimized electrode-electrolyte design for advancing high-performance AZIBs.
Modified Cardiometabolic Index (MCMI) is a novel metabolic assessment metric integrating waist-to-height ratio (WHtR), lipid, and fasting plasma glucose (FPG). Rheumatoid arthritis (RA), as an autoimmune disease, is closely linked to metabolic status, yet the relation of MCMI to RA remains unclear. Phenotypic age acceleration (PAA), reflecting biological aging, possibly mediates the relation of MCMI to RA. Our study aimed to elucidate the relation of MCMI to RA and assess the mediating effect of PAA. 1999-2010 and 2015-2020 National Health and Nutrition Examination Survey (NHANES) data on 10,564 adults were analyzed. RA status was determined via questionnaire. MCMI was calculated based on WHtR, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and FPG. PAA was derived as the residual of phenotypic age (PA) regressed on chronological age. The association of MCMI with RA was examined via weighted logistic regression (WLR), restricted cubic splines (RCS) assessed potential nonlinearity, and mediation analysis examined the effect of PAA. In multivariable-adjusted models, every one-unit rise in MCMI was related to a 45.1% higher RA prevalence (OR = 1.451, 95% CI: 1.250-1.685). MCMI was split into tertiles. The highest tertile (T3) displayed a significantly higher RA prevalence than the lowest tertile (T1) (OR = 1.879, 95% CI: 1.379-2.559). RCS analysis indicated a linear relation of MCMI to RA (P for nonlinear = 0.331). PAA accounted for 17.446% of the relation of MCMI to RA in mediation analysis (P < 0.001). MCMI is positively associated with RA risk, with PAA partially mediating this relationship. These findings suggest that metabolic dysregulation may influence RA development through accelerated biological aging, providing a novel perspective for early prevention and metabolic interventions in RA. Key Points • These findings suggest that poorer metabolic health may be associated with RA, partly through accelerated biological aging. • In practice, metabolic assessment may help identify people at higher risk of RA and support earlier lifestyle or clinical interventions. • The results also highlight biological aging as a possible pathway linking metabolism and RA.
Anti-lock braking control for in-wheel motor-driven electric vehicles is challenging because electro-hydraulic composite braking combines fast and accurately controllable motor regenerative braking with slower hydraulic pressure regulation. Existing ABS strategies often disable regenerative braking during ABS intervention, which limits both braking performance and energy recovery. This paper proposes a delay-aware action-space-grouped Soft Actor-Critic controller, termed SAC-DA-ASG, for coordinated ABS control of the motor regenerative braking system and the hydraulic braking system. The proposed controller addresses two implementation issues. First, an action-space grouping scheme maps coordinated solenoid-valve operations into a single hydraulic mode, reducing invalid actuator combinations and the policy search space. Second, a delay-aware augmented state incorporates recent system states to compensate for heterogeneous actuator response delays and improve the Markov representation. The controller is trained under randomized road-adhesion and actuator conditions and is evaluated against baseline SAC variants and a Bosch-type ABS strategy. Simulation results show that SAC-DA-ASG keeps the wheel slip ratio closer to the target value of 0.15, reduces slip fluctuation and peak slip, and shortens braking distance under uniform and split- μ road conditions. Sensitivity tests under solenoid-valve delay and vehicle-mass perturbations further indicate robust closed-loop behavior. Real-time hardware-in-the-loop tests on a Speedgoat platform show close agreement with simulation in braking time, stopping distance, and slip-ratio regulation. These results demonstrate the feasibility of DRL-based coordinated electro-hydraulic ABS control for in-wheel motor-driven electric vehicles.
Growing evidence suggests that metabolic disturbances underlie pregnancy losses, imposing a substantial public health burden among young women of reproductive age. Glycolipid metabolism 7 factors (GLM7) is a composite glycolipid metabolism index derived from routinely measured metabolic indicators; however, its relevance to pregnancy loss in young women remains unexamined. The present study analyzed publicly available data from the 2009-2018 National Health and Nutrition Examination Survey (NHANES) cycles. Participants were categorized as having no pregnancy loss, single pregnancy loss, or recurrent pregnancy loss (≥ 2 losses). GLM7 was calculated as the logarithm of the product of age, body mass index, fasting blood glucose, fasting insulin, triglycerides, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol levels. The association between GLM7 and pregnancy loss categories was evaluated, potential dose-response patterns were explored, and effect modification by selected sociodemographic and behavioral factors was assessed. Of the 736 women included in the analysis, 300 (37%) reported a history of pregnancy loss. In binary analyses, higher GLM7 was initially associated with pregnancy loss (OR = 1.21, 95% CI: 1.03-1.44); however, the association was attenuated after adjustment for the number of pregnancies (OR = 1.19, 95% CI: 0.99-1.44). In multinomial analyses, higher GLM7 levels were not significantly associated with single pregnancy loss. In contrast, higher GLM7 remained independently associated with recurrent pregnancy loss after adjustment for all covariates (OR = 1.17, 95% CI: 1.02-1.42; P = 0.046). Women in the second to fourth quartiles had significantly higher odds of recurrent pregnancy loss than those in the lowest quartile. No significant nonlinearity was observed in the association between GLM7 and recurrent pregnancy loss (P for nonlinearity = 0.265). No statistically significant interaction was observed across the subgroups. In this nationally representative sample of U.S. women aged 18-35 years, higher GLM7 levels were more robustly associated with recurrent rather than isolated pregnancy loss. The findings suggested that cumulative glycolipid metabolic burden may be particularly relevant to repeated reproductive failures and serve as indicators to improved strategies for early reproductive risk identification and preventive healthcare for women.
The development of solid-state electrolytes (SSEs) for chloride-ion batteries (CIBs) has lagged significantly behind that of electrode materials, primarily due to the difficulty in simultaneously achieving high structural stability, electronic insulation, and fast Cl- diffusion kinetics at room temperature. Drawing inspiration from the structural analogy between electrode materials and SSEs in cationic battery systems, this study adopts a materials design strategy that transforms layered CIB electrode materials into SSE candidates by substituting transition metals (TM) with equivalent non-transition main group metals (M). Through comprehensive first-principles high-throughput screening based on thermal, kinetic, and thermodynamic stability, we identify O-GaOCl (Pmmn space group) and Ca2GaO3Cl as the most promising SSE materials. Our analysis of electronic structures reveals that replacing TM3+ with M3+ eliminates partially filled d-orbitals near the Fermi level, resulting in wide bandgaps of 3.78 eV for O-GaOCl and 3.34 eV for Ca2GaO3Cl, satisfying the stringent insulation requirements for electrolytes. Evaluation of Cl- diffusion kinetics demonstrates that O-GaOCl exhibits an exceptionally low migration barrier of 0.25 eV, attributed to a concerted migration mechanism where two Cl- ions move simultaneously, reducing electrostatic repulsion. Ca2GaO3Cl shows a moderate barrier of 0.44 eV. Electrochemical window calculations indicate that O-GaOCl and Ca2GaO3Cl possess stable windows of 1.60 V and 3.28 V, respectively. These findings establish a viable pathway for designing CIB SSEs and position O-GaOCl and Ca2GaO3Cl as compelling candidates for enabling all-solid-state CIB technology.
Cardiovascular and neoplastic disease are common morbidities in managed care chimpanzees (Pan troglodytes). Despite the potential for these states to induce hemostatic derangements, coagulation assessments remain poorly explored in this species. A portable, point-of-care device, such as VCM Vet (VCM), may be advantageous for evaluating coagulation kinetics in zoological and field settings opposed to laboratory thromboelastography (TEG) or conventional coagulation parameter (CCP) assays. Using whole blood opportunistically collected from anesthetized chimpanzees (n = 26), this study investigated proof of concept for VCM, established reference values for VCM clot formation and clot strength parameters, compared VCM profiles across sex, age, and sample collection characteristics, and compared clinical interpretations of VCM to plasma-based TEG and CCP. Samples from 25 chimpanzees were analyzed with the VCM, all of which produced interpretable kinetic tracings without error. Reference values were established based on results from 21 healthy chimpanzees from this sample population. Relative to established reference values in domestic dogs, cats, and horses, chimpanzees formed strong clots at a fast rate. Female chimpanzees formed significantly stronger clots than males, and older chimpanzees (>30 yr old) formed clots significantly faster than younger chimpanzees (≤30 yr old) (p < 0.05). Additionally, baseline values derived from descriptive statistics were reported for plasma-based TEG and CCP based on results from 19 healthy chimpanzees from the sample population. Comparisons made visually between VCM and TEG tracings, and between clinical interpretations for VCM, TEG, and CCP, support that these diagnostics may provide similar clinical information, although complete corroboration was limited due to evaluation in predominately healthy chimpanzees. This foundational dataset provides key reference values to encourage use of coagulation assessments and improve standard of care for chimpanzees in managed settings.
Osteoarthritis (OA) is a chronic and degenerative joint disorder that is prevalent in middle-aged and older populations. While several long non-coding RNAs (lncRNAs) have been implicated in OA progression, the role of lncRNA Mirt2 and its regulatory mechanisms remain unclear. The expression of lncRNA Mirt2, miR-429, and TANK-binding kinase 1 (TBK1) was detected using qRT-PCR in normal and OA cartilage tissues. The interleukin (IL)-1β-stimulated chondrocyte was used as an in vitro OA cell. EdU, TUNEL assay, western blot, and ELISA assays were used for our experiments. Luciferase reporter assays, RNA immunoprecipitation (RIP), and RNA pulldown were used to investigate the interactions between lncRNA Mirt2, miR-429, and TBK1. An in vivo OA model was established, and cartilage damage was evaluated using H/E and Safranin O/Fast Green staining. LncRNA Mirt2 expression was significantly downregulated in OA cartilage tissues and IL-1β-stimulated chondrocytes (p < 0.05). Transfection of the lncRNA Mirt2 overexpression vector led to a remarkable increase in cell proliferation, a significant reduction in cell apoptosis and inflammation, and a marked elevation in autophagy in IL-1β-induced chondrocytes (p < 0.05). Functional investigation revealed that lncRNA Mirt2 acts as a competing endogenous RNA (ceRNA) by sponging miR-429 in IL-1β-induced chondrocytes. Additionally, miR-429 directly targets TBK1. Rescue experiments showed that overexpression of miR-429 or inhibition of TBK1 effectively counteracted the functional consequences of lncRNA Mirt2 upregulation in IL-1β-stimulated chondrocytes, reversing its promotive effects on cell proliferation and autophagy, as well as its inhibitory effect on apoptosis. The in vivo experiments indicated overexpression of lncRNA Mirt2 down-regulated miR-429, up-regulated TBK1, substantially attenuated cartilage damage, and accelerated autophagy in OA mice (p < 0.05). LncRNA Mirt2 promoted chondrocyte proliferation and alleviated chondrocyte apoptosis, inflammation, and cartilage degeneration by activating miR-429/TBK1-mediated autophagy. Consequently, lncRNA Mirt2 could be a potential target for OA diagnosis and treatment.
Diamond and graphene are emerging as promising successors to silicon-based materials for semiconductor applications, particularly when integrated into graphene/diamond heterostructures. However, fabricating high-quality graphene (0002) atomic layers on diamond (111) with intimate contact-mostly desired for device integration-remains a great challenge. Here, we report a strategy to realize a covalently bonded, graphene (0002)/diamond (111) heterojunction using thermal electron irradiation. Combining structural characterization with theoretical calculations, the formation mechanism and energy band characteristics of this junction structure were clarified, and the microscopic mechanism of hexagonal diamond (lonsdaleite) acting as an intermediate state before its transformation into graphene layers was proposed. The heterostructure exhibits a high piezoresistive response under the present testing configuration, with a gauge factor of -1149. This performance is attributed to two key factors: first, the heterojunction-induced formation of an electron-rich layer on the diamond surface; and second, a significant stress-induced increase in the density of states of carbon C 2p orbitals within the diamond layer. Leveraging diamond's intrinsic properties, piezoresistive chips based on this structure may offer opportunities for high-temperature, radiation-tolerant, wide-range, and fast-response sensing applications after further device-level optimization and validation. These results provide a useful basis for developing diamond-based semiconductor and sensing devices.
Spiking Neural Networks (SNNs) offer a promising pathway toward energy-efficient neuromorphic computing due to their event-driven computation and sparse spike-based communication. However, most existing SNN architectures are derived from dense Artificial Neural Networks (ANNs) and do not explicitly exploit the role of network topology in learning dynamics. In this work, we propose a community-aware sparse topology design framework for graph-based SNNs. Using seven distinct community detection algorithms (KMeans, Spectral Clustering, Fast Greedy, Louvain, Leiden, Infomap, and Small-World), we systematically compare how different modular organizations influence convergence speed, classification accuracy, and energy consumption under strictly controlled conditions (64 neurons, 92% sparsity, ≈ 10 communities, T = 4 time steps). Experimental results on MNIST and CIFAR-10 reveal a dataset-dependent trade-off. On simple, low-noise MNIST, fine-grained methods like Infomap achieve the highest accuracy (99.67%). On the more complex CIFAR-10, coarse and noise-robust methods (Louvain, KMeans, Small-World) perform best (≈ 92.96% accuracy), slightly outperforming fine-grained algorithms (≈ 90.8%). Notably, all community-driven topologies converge dramatically faster than conventional SNNs (27-44 epochs vs. 100-300 epochs). Despite using twice as many neurons as the baseline TANet-Tiny, our sparse modular architectures maintain the same inference energy (≈ 1.2 mJ per sample) thanks to higher sparsity (92% vs. ≈80%) and structured connectivity, halving the energy per neuron. These findings challenge the prevailing assumption that network size or sparsity alone is sufficient, demonstrating that how sparse connections are organized - the graph topology - critically influences learning efficiency, accuracy, and energy consumption. Our framework provides practical guidelines for dataset-aware community detection in neuromorphic system design.
Childhood obesity interventions have shown modest and often unsustainable effects, with frequent weight regain driven by physiological and behavioral compensatory mechanisms. While nutritional adaptations have been relatively well described, energetic adaptations remain insufficiently explored in pediatric populations. This study aimed to investigate the temporal dynamics of resting energy expenditure (REE), substrate oxidation, thyroid hormones, leptin concentrations, and adaptive thermogenesis (AT) throughout a 10-month weight loss intervention in adolescents with obesity. Forty adolescents with obesity (13.9 ± 1.4 years; 20 boys) were recruited from a pediatric rehabilitation center and participated in a 10-month multidisciplinary intervention combining physical activity, nutritional education, and psychological support. Participants completed up to nine assessment visits at 4-5-week intervals. At each visit, anthropometry (weight, height, BMI z-score), fasting REE, substrate oxidation (indirect calorimetry), and blood sampling (TSH, triiodothyronine, thyroxine, leptin) were performed. Body composition was assessed by DXA at baseline, mid- and post-intervention. Among the 38 adolescents analyzed, the intervention induced significant changes in body composition, with a reduction in fat mass and BMI z-score over time (all p<0.001) and a transient increase in fat-free mass (FFM) (p<0.001), while body weight initially decreased (p<0.040) before partially increasing at later stages (p≤0.001). REE remained unchanged throughout the intervention, and no statistically significant difference between REEm and REEp (AT) was not observed, while respiratory quotient increased significantly (p<0.001) over time. This longitudinal study reveals that, despite moderate weight loss, REE remained stable and AT was not clearly apparent, while the shift toward greater carbohydrate oxidation indicates ongoing and dynamic metabolic remodeling. Overall, these exploratory findings may suggest that metabolic adaptations to weight loss may be more variable than previously assumed, although confirmation in larger cohorts is still required.
Phonocardiogram (PCG) is a graphical representation of heart sounds and murmurs, playing a vital role in the early screening and prevention of cardiovascular diseases (CVDs). In this study, we propose a first camera-stethoscope that is capable of recording PCG contactlessly, enabled by the principle of defocused speckle imaging (DSI). By illuminating the chest surface adjacent to the heart with a laser beam and employing a defocused camera to capture the reflected laser speckle interference, the subtle cardiac vibrations involved in heart sound generation are magnified and measured. By adjusting the defocused level, we can achieve different amplification effects of heart sounds. Additionally, we propose an algorithm to extract PCG signals from the video, including the fast detection of S1 and S2 events. In laboratory experiments, we evaluated the robustness of laser positioning and revealed a nonlinear amplification relationship between defocused level and PCG signals. The reliability of camera-stethoscope has been validated on 21 healthy adult subjects against the reference of contact electronic stethoscope. Moreover, we conducted clinical validation in the Department of Ultrasound. The proposed camera-stethoscope achieved F1-scores of 0.94 for both S1 and S2 detection on 45 patients, demonstrating its reliability and clinical potential. This work established the fundamental optical sensing model and algorithms for novel PCG monitoring.
Superfluorescence in self-assembled CsPbBr3 superlattices of colloidal quantum dots (QDs) has garnered extensive attention due to its ultra-fast, intense burst emission. Among the available fabrication methods for superlattices, saturated solvent evaporation remains widely utilized for its operational simplicity and cost-effectiveness. However, this conventional method exhibits poor controllability and process randomness owing to the absence of a stable preparation platform, thereby hindering controlled self-assembly. Here, a high-temperature (30-70 °C) saturated solvent evaporation method was developed for size-tunable and efficient preparation of high-quality CsPbBr3 superlattices. In this approach, the coffee-ring effect governs assembly by driving solute transport, inducing a distinct spatial gradient where superlattice size decreases from the substrate edge to center. Systematic modulation of assembly temperature and QD concentration enables adjustability of superlattice dimensions. Specifically, higher temperatures attenuate solute migration, thereby reducing superlattice size, while increased QD concentration strengthens inter-dot interactions to promote the formation of larger superlattices. A near-100-fold radiative acceleration of the prepared superlattices compared to conventional QD films demonstrates the ultrafast superfluorescence emission capability. Combined with their potential for scalable production, a material foundation was provided for ultrafast photonic applications. And it also opens up a reliable pathway for superlattice fabrication, laying a foundation for future size-dependent superlattice research and the development of high-performance optoelectronic devices.
Rapid diagnosis, timely treatment, and continuous monitoring are essential for improving outcomes in neurovascular diseases (time=brain). Such point-of-care applications, however, require imaging to be conducted in dynamic and often confined spaces. While magnetic particle imaging (MPI) shows preclinical promise for fast (neuro)vascular imaging, it relies on complex and restricted imaging gantries. Here, we present a unique gantry-free robot-assisted MPI strategy (Robotic MPI) that is 'portable'. Using permanent magnets, Hall sensors and correction coils, we developed a single-sided detector with a detection threshold of ~ 5 µg iron-containing contrast agent at the detector surface. Robot-assisted positioning and pose tracking, combined with a dedicated maximum likelihood expectation-maximization-based reconstruction algorithm, translates detector signals into tomographic images with a spatial resolvability of 7 mm (visually evaluated at an imaging depth of ~ 5 mm). Surface imaging (SI) provided anatomical reference, delivering hybrid MPI/SI scans. Robotic-MPI's ability to visualize 3D (neuro)vasculature in a phantom model, highlights the system's potential for next-generation, portable vascular imaging solutions.
Dry electrospun nanofibrous facial masks (D-ENFMs) have emerged as a promising platform in nano/biomaterials research, attributed to their eco-friendly nature and convenient use. However, their practical application is significantly hindered by three critical barriers: low active ingredient loading capacity, slow dissolution kinetics, and undesirable solid residues after use. Inspired by the unique "dry-state preservation and wet-state release" survival strategy of Anastatica hierochuntica, a bioinspired core-sheath beaded-structured nanofibrous membrane (B-NFM) is developed via one-step emulsion electrospinning. This architecture enables long-term stable encapsulation of squalane emulsion droplets in the dry state and triggers ultra-fast dissolution upon contact with moisture, followed by efficient moisturization through the synergistic "water locking-hydration replenishment-barrier repair" mechanism of squalane. The surfactant coconut diethanolamide plays a dual critical role: stabilizing the oil-in-water emulsion for efficient squalane encapsulation, and modulating molecular reorganization to impart superhydrophilicity, enabling instantaneous dissolution and complete residue elimination. Notably, this one-step strategy is successfully scaled to a 256-needle roll-to-roll electrospinning system, achieving a daily output of 155.52 m2. This bioinspired design paradigm will pave the way for a new generation of sustainable, high-performance nanomaterials for advanced skincare applications.
We aimed to describe the sociodemographic and clinical characteristics of subtypes of metabolic dysfunction-associated fatty liver disease (MAFLD) in Malaysia. Adults with MAFLD were identified from a 2023 nationwide community-based cross-sectional study. Three mutually exclusive MAFLD subtypes were classified first by diabetes status (diabetic MAFLD), then by ≥ 2 metabolic dysfunctions (metabolic dysfunction MAFLD), and finally by overweight/obesity with < 2 metabolic dysfunctions (overweight MAFLD). Among 309 respondents with MAFLD, the mean age was 46.8 ± 14.8 years, with a balanced sex distribution, and most were Malay (63.8%) and married or living with a partner (71.8%). The diabetic MAFLD subtype was characterised by older age, Indian ethnicity, and a higher proportion of divorced or widowed individuals, whereas younger adults were predominantly represented in the metabolic dysfunction subtype. Metabolic syndrome, hypertension, and raised total cholesterol were more common in the metabolic dysfunction subtype. The diabetic subtype had the highest waist circumference, blood pressure, triglycerides, glycosylated haemoglobin A1c, and fasting blood glucose. A higher proportion (22.7%) of the diabetic subtype had moderate or high risks of advanced liver fibrosis, compared to metabolic dysfunction (8.8%) and overweight (0.0%) subtypes, P = 0.002. Around 57.6% of the diabetic MAFLD subtype had a high 10-year cardiovascular risk compared to 25.8% and 10.0% in the metabolic dysfunction and overweight subtypes, respectively, P < 0.001. Individuals with diabetes, metabolic dysfunction, and overweight MAFLD subtypes in Malaysia had different sociodemographic characteristics and clinical profiles. MAFLD subtypes may be used for risk stratification, and individualised treatment may be considered for different subtypes.
Soft ionic gels are promising materials for flexible optoelectronic sensors owing to their softness, transparency, and light responsiveness. However, achieving controllable regulation of device sensitivity and response speed through modulation of gel composition or molecular structure remains challenging. Here, we demonstrate that specific ion effects induce reconfiguration of the hydration-polymer network in gelatin hydrogels, thereby enabling tunable optoelectronic properties. Kosmotropic anions reinforce interfacial polarization by promoting structural ordering within the polymer-water network, resulting in highly sensitive (0.288 µW mm-2) and fast-response (0.077 s) self-powered photodetection. In contrast, chaotropic anions disrupt network organization, enhance water disorder, and amplify photothermal-driven ion migration, leading to weak (1.44 µW mm-2) yet slow-response (2.08 s) persistent photoconductivity. These results reveal an ion-specific hydration mechanism that governs the transition between polarization-dominated and ion migration-dominated optoelectronic behaviors. As a proof of concept, optical encryption communication and image recognition/learning are demonstrated using photodetection-mode and photosynaptic-mode devices, respectively.