Clarifying the origin of molecular O in cathode oxides.

Anionic redox has reshaped the conventional way of exploring advanced cathode materials for Li-ion batteries. However, how anions participate in the redox process has been the subject of intensive debate, evolving from electron holes to O-O dimerization and currently to a focus on trapped molecular O based on high-resolution resonant X-ray inelastic scattering research. Here we show that the resonant X-ray inelastic scattering signal of molecular O is not exclusive to Li-rich oxide cathodes, but appears consistently in O-redox-inactive oxide materials even with a short beam exposure time as low as 1 min, indicating that molecular O species are not directly related to voltage hysteresis and voltage decay.

The effect of health insurance reimbursement rates on middle-aged and elderly people's hospital choices: evidence from China.

Background: Adjusting the health insurance reimbursement rate is essential to optimize the allocation of medical resources. This paper investigates the effect of health insurance reimbursement rates on middle-aged and elderly people's choice of hospitals in China.

Methods: This study is conducted using the China Health and Retirement Longitudinal Study (CHARLS) database.

Reinforcement learning-based generative artificial intelligence for novel pesticide design.

Introduction: Pesticides play a pivotal role in ensuring food security, and the development of green pesticides is an inevitable trend in global agricultural progress. Although deep learning-based generative models have revolutionized de novo drug design in pharmaceutical research, their application in pesticide research and development remains unexplored.

Objectives: This study aims to pioneer the application of generative artificial intelligence to pesticide design by proposing a reinforcement learning-based framework for obtaining pesticide-like molecules with high binding affinity.

Brilliant, stable, and electrically responsive photonic crystals based on dielectric particles and solvation repulsion.

Electrically responsive photonic crystals (ERPCs) capable of adjusting their structural colors in response to electric fields are promising next-generation smart optical materials. However, the poor color saturation and stability of conventional ERPCs significantly limit their practical applications. Here, a new kind of ZnS-silica/diethylene glycol ERPC was designed and fabricated by directly non-close-assembling ZnS-silica core-shell particles with high refractive indexes into a diethylene glycol with a low dielectric constant.

Powering up protein: How hydrogel-coated electrodes enhance biohybrid production.

Integrating water splitting with gas-fixing microorganisms offers a promising route for the sustainable production of chemicals, fuels, and food using renewable electricity. However, challenges such as insufficient gas utilization and undesirable side reactions hinder the scalability of these systems. To overcome these limitations, we proposed and investigated a universal hydrogel-coated electrode strategy to significantly enhance single-cell protein (SCP) production from CO and electricity.

Data-efficient generalization of AI transformers for noise reduction in ultra-fast lung PET scans.

Purpose: Respiratory motion during PET acquisition may produce lesion blurring. Ultra-fast 20-second breath-hold (U2BH) PET reduces respiratory motion artifacts, but the shortened scanning time increases statistical noise and may affect diagnostic quality. This study aims to denoise the U2BH PET images using a deep learning (DL)-based method.

Crack-Detection Algorithm Integrating Multi-Scale Information Gain with Global-Local Tight-Loose Coupling.

In this study, an improved target-detection model based on information theory is proposed to address the difficulties of crack-detection tasks, such as slender target shapes, blurred boundaries, and complex backgrounds. By introducing a multi-scale information gain mechanism and a global-local feature coupling strategy, the model has significantly improved feature extraction and expression capabilities. Experimental results show that, on a single-crack dataset, the model's mAP@50 and mAP@50-95 are 1.

Addressing challenges in pediatric thrombosis: a comprehensive guideline development.

Background: Pediatric thrombosis is a relatively rare but severe condition in the field of pediatrics, with far-reaching consequences. Recent studies have indicated a rising incidence of this disease in children over the years. Additionally, the pharmacological treatment of thrombotic diseases in children faces numerous challenges.

Robust and generalizable artificial intelligence for multi-organ segmentation in ultra-low-dose total-body PET imaging: a multi-center and cross-tracer study.

Purpose: Positron Emission Tomography (PET) is a powerful molecular imaging tool that visualizes radiotracer distribution to reveal physiological processes. Recent advances in total-body PET have enabled low-dose, CT-free imaging; however, accurate organ segmentation using PET-only data remains challenging. This study develops and validates a deep learning model for multi-organ PET segmentation across varied imaging conditions and tracers, addressing critical needs for fully PET-based quantitative analysis.

Macrophyte Restoration Promotes Lake Microbial Carbon Pump to Enhance Aquatic Carbon Sequestration.

Macrophyte-based lake restoration has successfully transitioned lakes from turbid conditions dominated by phytoplankton to a more natural, clear state; however, its impact on microbial carbon pump-mediated dissolved organic carbon (DOM) storage and greenhouse gas (GHG) emissions in the aquatic ecosystem remains largely unexplored. Through a year-long field study, we conducted a comparative analysis of two alternative habitats within the same lake-restored and unrestored areas. Results demonstrated that restoration not only substantially decreases nutrient levels and algal blooms-evidenced by over 50% reductions in nitrogen, phosphorus, and chlorophyll a-but also significantly increases the accumulation of recalcitrant DOM.

Ga-FAPI-04 PET/CT Imaging for Assessing Renal Tubulointerstitial Fibrosis in Lupus Nephritis.

The objective of this study was to evaluate the feasibility of using Ga-labeled fibroblast activation protein inhibitor-04 (Ga-FAPI-04) PET/CT imaging as a molecular tracer and noninvasive tool for assessing active renal tubulointerstitial fibrosis in patients with lupus nephritis (LN). The study included 29 LN patients who underwent Ga-FAPI-04 PET/CT scanning to quantify Ga-FAPI-04 uptake. Renal biopsies were performed within a week of scanning.

Robust and compact light-induced thermoelastic sensor for atmospheric methane detection based on a vacuum-sealed subminiature tuning fork.

A compact light-induced thermoelastic spectroscopy (LITES) instrument incorporating a subminiature quartz tuning fork (QTF) was developed for atmospheric methane (CH) sensing. The QTF features prong dimensions of 1700 µm in length and 120 µm in width, which enable substantial thermoelastic expansion at the microscale, significantly enhancing the piezoelectric signal. The subminiature QTF was vacuum sealed to achieve a high quality factor of 20,511 and a temperature coefficient of frequency of - 0.

Optimizing MR-based attenuation correction in hybrid PET/MR using deep learning: validation with a flatbed insert and consistent patient positioning.

Purpose: To address the challenges of verifying MR-based attenuation correction (MRAC) in PET/MR due to CT positional mismatches and alignment issues, this study utilized a flatbed insert and arms-down positioning during PET/CT scans to achieve precise MR-CT matching for accurate MRAC evaluation.

Methods: A validation dataset of 21 patients underwent whole-body [F]FDG PET/CT followed by [F]FDG PET/MR. A flatbed insert ensured consistent positioning, allowing direct comparison of four MRAC methods-four-tissue and five-tissue models with discrete and continuous μ-maps-against CT-based attenuation correction (CTAC).

The Mediating Effect of Depressive Symptoms between Frailty and Cognitive Impairment in the Northeast Chinese Older Adults.

Introduction: Cognitive impairment among older adults is a significant public health concern worldwide. This study aimed to investigate the prevalence of cognitive impairment, its correlates, and the mediating role of depressive symptoms between frailty and cognitive impairment among older adults in northeast region of China.

Methods: This was a cross-sectional study which used the intercept interview method to recruit participants.

Disrupted Cross-Scale Network Associated With Cognitive-Emotional Disorders in Sudden Sensorineural Hearing Loss.

Background: Sudden sensorineural hearing loss (SSNHL) is associated with abnormal changes in the brain's central nervous system. Previous studies on the brain networks of SSNHL have primarily focused on functional connectivity within the brain. However, in addition to functional connectivity, structural connectivity also plays a crucial role in brain networks.

Carotid Endarterectomy Ameliorates Cognitive Impairment in Clinical and Experimental Unilateral Carotid Artery Stenosis.

Background: Carotid endarterectomy (CEA) is widely used to treat carotid artery stenosis (CAS). However, the effects of CEA on unilateral CAS-induced cognitive impairment and the underlying mechanism remain poorly understood.

Methods And Results: Thirteen patients diagnosed with unilateral severe CAS underwent pre- and post-CEA assessments, including fluoro-2-deoxy-d-glucose positron emission tomography/magnetic resonance imaging, cognitive assessments, and routine blood tests before and after CEA.

Hovering hawkmoths exploit unsteady circulation to produce aerodynamic force.

This study employs an integrated approach, combining three-dimensional flow visualization and two-dimensional flow measurement to investigate the underlying unsteady aerodynamic mechanisms of hovering hawkmoths. Using a single vortex ring model, three aerodynamic force components, such as aerodynamic force induced by unsteady circulation, vortex loop size variation and added mass, are estimated within a dimensionless time (normalized by one wing beat cycle) range of 0.418 < < 0.

ppb-Level SO Photoacoustic Sensor for SF Decomposition Analysis Utilizing a High-Power UV Laser with a Power Normalization Method.

A highly sensitive sulfur dioxide (SO) photoacoustic gas sensor was developed for the sulfur hexafluoride (SF) decomposition detection in electric power systems by using a novel 266 nm low-cost high-power solid-state pulse laser and a high -factor differential photoacoustic cell. The ultraviolet (UV) pulse laser is based on a passive -switching technology with a high output power of 28 mW. The photoacoustic signal was normalized to the laser power to solve the fluctuation of the photoacoustic signal due to the power instability of the UV laser.

In situ labeling of pretargeted hyaluronan for PET/MR imaging of CD44+ tumors.

Background: Tumor-specific molecular probe-based imaging strategies have shown great potential for tumor diagnosis. However, the sensitivity and contrast of imaging may interfere with the complex labeling process and degradation of tumor-specific imaging probes. We sought to adapt a pretargeting strategy and an in vivo bioorthogonal reaction to improve hyaluronan (HA)-based tumor multimodal imaging diagnosis.

Oriented wide-bandgap perovskites for monolithic silicon-based tandems with over 1000 hours operational stability.

The instability of hybrid wide-bandgap (WBG) perovskite materials (with bandgap larger than 1.68 eV) still stands out as a major constraint for the commercialization of perovskite/silicon tandem photovoltaics, yet its correlation with the facet properties of WBG perovskites has not been revealed. Herein, we combine experiments and theoretical calculations to comprehensively understand the facet-dependent instability of WBG perovskites.

Microfluidic chip systems for characterizing glucose-responsive insulin-secreting cells equipped with FailSafe kill-switch.

Background: Pluripotent cell-derived islet replacement therapy offers promise for treating Type 1 diabetes (T1D), but concerns about uncontrolled cell proliferation and tumorigenicity present significant safety challenges. To address the safety concern, this study aims to establish a proof-of-concept for a glucose-responsive, insulin-secreting cell line integrated with a built-in FailSafe kill-switch.

Method: We generated β cell-induced progenitor-like cells (βiPLCs) from primary mouse pancreatic β cells through interrupted reprogramming.

A deep learning method for total-body dynamic PET imaging with dual-time-window protocols.

Purpose: Prolonged scanning durations are one of the primary barriers to the widespread clinical adoption of dynamic Positron Emission Tomography (PET). In this paper, we developed a deep learning algorithm that capable of predicting dynamic images from dual-time-window protocols, thereby shortening the scanning time.

Methods: This study includes 70 patients (mean age ± standard deviation, 53.

Enhanced creaminess of plant-based milk via enrichment of papain hydrolyzed oleosomes.

There is an increased consumer demand for plant-based milk in substituting dairy milk due to the ethical, health concerns and environmentally-friendly choice. However, perceived creaminess as dominant attributes present a big challenge in consumer acceptance for those milk alternatives. In this study, we developed a novel and easily scalable strategy to enhance the creaminess of soy milk via enrichment of oleosomes.