Deciphering Closed-Pore Formation and Size-Dependent Sodium Cluster Filling Behavior for Nanopore-Confined Derived Hard Carbon Anodes.

The low-voltage plateau capacity (LVPC) of hard carbon (HC) anodes for sodium-ion batteries originates from sodium cluster filling within closed pores, and closed-pore engineering of activated carbon (AC) via nanopore-confined pyrolysis is a feasible strategy to produce HC anodes with high LVPC. However, the formation mechanism of closed pores and their size-dependent effects on sodium cluster filling behavior remain poorly understood. Herein, pitch-confined pyrolysis is utilized within the nanopores of AC to transform its open pores into closed pores, with pitch dose regulating closed-pore size.

Dual-Wavelength Synaptic Simulator ReS/TaNiSe for Multi-Timescale Learning in Neuromorphic Computing.

To address the limitations of silicon-based devices in neuromorphic computing, this study proposes a dual-wavelength photomodulated synaptic device based on the ReS₂/Ta₂NiSe₅ heterojunction. Through heterojunction band engineering, wavelength-selective synaptic plasticity is achieved, leveraging the photothermal effect at 1550 nm wavelength and the photoelectric effect at 520 nm wavelength. This enables a wavelength-selective synaptic weight update strategy, addressing the limitation of conventional single-wavelength devices that lack multi-timescale adaptability.

Wide Wavelength Band Responsive InSe/CIPS Heterojunction for Polarization Imaging Enhancement in Image Fusion.

Polarization photodetectors suffer from insufficient sensitivity, slow response speed, and limited spectral response range. Therefore, the development of new photodetectors with broad spectral response, high sensitivity, excellent polarization sensitivity, and low cost has become the focus of the current research field. Herein, we report an InSe/CIPS heterojunction-based approach for high-performance photodetection, polarization-sensitive photodetection, and polarization imaging in the visible to near-infrared region (400-808 nm).

Deep learning-based electrical impedance spectroscopy analysis for malignant and potentially malignant oral disorder detection.

Electrical impedance spectroscopy (EIS) is a powerful tool used to investigate the properties of materials and biological tissues. This study presents one of the first applications of EIS for the detection and classification of oral potentially malignant disorders (OPMDs) and oral cancer. We aimed to apply EIS in conjunction with deep learning to assist the clinical diagnosis of OPMD and oral cancer as a non-invasive diagnostic technology.

Knowledge and Awareness of Generative Artificial Intelligence Use in Medicine Among International Stakeholders: A Cross-Sectional Study.

Objective: To assess the knowledge, attitudes, and practices (KAP) of medical stakeholders regarding the use of generative artificial intelligence (GAI) tools.

Methods: A cross-sectional survey was conducted among stakeholders in medicine. Participants included researchers, clinicians, and medical journal editors with varying degrees of familiarity with GAI tools.

Brain-derived extracellular vesicles: A promising avenue for Parkinson's disease pathogenesis, diagnosis, and treatment.

The misfolding, aggregation, and deposition of alpha-synuclein into Lewy bodies are pivotal events that trigger pathological changes in Parkinson's disease. Extracellular vesicles are nanosized lipid-bilayer vesicles secreted by cells that play a crucial role in intercellular communication due to their diverse cargo. Among these, brain-derived extracellular vesicles, which are secreted by various brain cells such as neurons, glial cells, and Schwann cells, have garnered increasing attention.

Temporal Features-Fused Vision Retentive Network for Echocardiography Image Segmentation.

Echocardiography is a widely used cardiac imaging modality in clinical practice. Physicians utilize echocardiography images to measure left ventricular volumes at end-diastole (ED) and end-systole (ES) frames, which are pivotal for calculating the ejection fraction and thus quantitatively assessing cardiac function. However, most existing approaches focus on features from ES frames and ED frames, neglecting the inter-frame correlations in unlabeled frames.

TaPdS/MoS Heterojunction Phototransistor for High-Performance Photoelectric Synapses and Graphic Identification.

Artificial synapses and neurons with efficient, high-speed, and highly parallel information processing capabilities are considered to be a new direction for the next generation of learning, cognition, and data storage. In this work, we have integrated photodetectors and photoelectric synapse in TaPdS/MoS van der Waals heterostructures, which can be used in photodetection and optical artificial neural networks. We have systematically studied the photoelectric characteristics of the blue-violet to near-infrared (405 ∼ 1550 nm) band.

Development and External Validation of a Prediction Model for Early Postoperative Cerebral Infarction on Computed Tomography in Spontaneous Intracerebral Hemorrhage.

Background: Early postoperative cerebral infarction (ePCI) significantly worsens outcomes in patients with spontaneous intracerebral hemorrhage (ICH) undergoing surgery. This study aimed to develop and externally validate a nomogram to assess ePCI risk.

Methods: Adult patients with spontaneous supratentorial ICH who underwent surgery between May 2015 and September 2022 at a large tertiary referral center (development cohort) and another tertiary referral center (external validation cohort) were retrospectively included.

Efficacy of medications for the treatment of alcohol use disorder (AUD): A systematic review and meta-analysis considering baseline AUD severity.

Baseline severity of alcohol use disorder (AUD) is an influencing factor in the response to medications recommended for the treatment of AUD. The scarce efficacy of AUD medications partly justifies their limited uses. We were interested in evaluating the efficacy of approved and recommended AUD medications using generic inverse-variance, an analysis facilitating comparison between medications and placebo both at the end of the study and, concomitantly, to baseline values for the same participants.

Modernizing authorship criteria and transparency practices to facilitate open and equitable team science.

The rapid acceleration of authorship inflation-increasing numbers of authors per publication in collaborative research-has rendered the traditional "substantial contributions" criterion for authorship and the lack of transparency in author contributions increasingly problematic. To address these challenges, a revamped approach to authorship is proposed, replacing the rigid requirement of "substantial contributions" with a more flexible, project-specific criterion of "sufficient contributions," as determined and justified by the authors for each project. This change more accurately reflects and accommodates the proliferation of scientific collaboration ("team science" or "group science").

A novel mean shape based post-processing method for enhancing deep learning lower-limb muscle segmentation accuracy.

This study aims at improving the lower-limb muscle segmentation accuracy of deep learning approaches based on Magnetic Resonance Imaging (MRI) scans, crucial for the diagnostic and therapeutic processes in musculoskeletal diseases. In general, segmentation methods such as U-Net deep learning neural networks can achieve good Dice Similarity Coefficient (DSC) values, e.g.

Psychology needs more diversity at the level of Editor-in-Chief.

There are racial, gender, and geographical disparities for editors-in-chief in psychology. This is a problem, and many counter arguments are not persuasive. It is time for the field – and in the power of individuals - to implement suitable measures to make change happen.

A Shape-Consistent Deep-Learning Segmentation Architecture for Low-Quality and High-Interference Myocardial Contrast Echocardiography.

Objective: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, infarction, masses and other cardiac conditions. In the realm of MCE image analysis, accurate and consistent myocardial segmentation results are essential for enabling automated analysis of various heart diseases. However, current manual diagnostic methods in MCE suffer from poor repeatability and limited clinical applicability.

Treadmill exercise in combination with acousto-optic and olfactory stimulation improves cognitive function in APP/PS1 mice through the brain-derived neurotrophic factor- and Cygb-associated signaling pathways.

JOURNAL/nrgr/04.03/01300535-202509000-00031/figure1/v/2024-11-05T132919Z/r/image-tiff A reduction in adult neurogenesis is associated with behavioral abnormalities in patients with Alzheimer's disease. Consequently, enhancing adult neurogenesis represents a promising therapeutic approach for mitigating disease symptoms and progression.

Insomnia in Parkinson's Disease: Causes, Consequences, and Therapeutic Approaches.

Sleep disorders represent prevalent non-motor symptoms in Parkinson's disease (PD), affecting over 90% of the PD population. Insomnia, characterized by difficulties in initiating and maintaining sleep, emerges as the most frequently reported sleep disorder in PD, with prevalence rates reported from 27 to 80% across studies. Insomnia not only significantly impacts the quality of life of PD patients but is also associated with cognitive impairment, motor disabilities, and emotional deterioration.

Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation.

Individual muscle segmentation is the process of partitioning medical images into regions representing each muscle. It can be used to isolate spatially structured quantitative muscle characteristics, such as volume, geometry, and the level of fat infiltration. These features are pivotal to measuring the state of muscle functional health and in tracking the response of the body to musculoskeletal and neuromusculoskeletal disorders.