Imaging-guided bioresorbable acoustic hydrogel microrobots.

Micro- and nanorobots excel in navigating the intricate and often inaccessible areas of the human body, offering immense potential for applications such as disease diagnosis, precision drug delivery, detoxification, and minimally invasive surgery. Despite their promise, practical deployment faces hurdles, including achieving stable propulsion in complex in vivo biological environments, real-time imaging and localization through deep tissue, and precise remote control for targeted therapy and ensuring high therapeutic efficacy. To overcome these obstacles, we introduce a hydrogel-based, imaging-guided, bioresorbable acoustic microrobot (BAM) designed to navigate the human body with high stability.

Clinico-sero-pathological characteristics of anti-Ha antisynthetase syndrome.

To define the clinical, serological, and muscle histopathological characteristics, as well as treatment outcomes, of patients with anti-Ha antibody. We performed a retrospective analysis of clinical, serological, and pathological data and long-term treatment outcomes of anti-Ha patients between January 2005 and July 2023 at our center. Anti-Ha antibody was identified by immunoblot and reconfirmed by immunoprecipitation.

Association of glymphatic system dysfunction with cognitive impairment in temporal lobe epilepsy.

Objectives: To explore the relationship between glymphatic dysfunction and cognitive impairment in unilateral temporal lobe epilepsy (TLE).

Methods: This study retrospectively included 38 patients with unilateral TLE and 26 age- and gender-matched healthy controls (HCs). The diffusion tensor image analysis along the perivascular space (DTI-ALPS) index, choroid plexus volume (CPV), and cognitive assessment were obtained for each participant.

The influence of adult urine lead exposure on bone mineral densit: NHANES 2015-2018.

Introduction: Previous studies have indicated that exposure to heavy metals related to bone health is primarily limited to some common harmful metals, and the impact of lead has not been fully understood. This study aims to explore the relationship between urine lead exposure and bone density.

Methods: 1,310 adults were included from the NHANES database (2015-2018), and through generalized linear regression analysis and constrained cubic spline models, the association between lead levels and total bone density as well as lumbar spine bone density was explored.

Clinical outcome-guided deep temporal clustering for disease progression subtyping.

Objective: Complex diseases exhibit heterogeneous progression patterns, necessitating effective capture and clustering of longitudinal changes to identify disease subtypes for personalized treatments. However, existing studies often fail to design clustering-specific representations or neglect clinical outcomes, thereby limiting the interpretability and clinical utility.

Method: We design a unified framework for subtyping longitudinal progressive diseases.

Clinico-sero-pathological profiles and risk prediction model of idiopathic inflammatory myopathy (IIM) patients with different perifascicular changes.

Aims: To explore the clinico-sero-pathological characteristics and risk prediction model of idiopathic inflammatory myopathy (IIM) patients with different muscular perifascicular (PF) changes.

Methods: IIM patients in our center were enrolled and the clinico-sero-pathological data were retrospectively analyzed. A decision tree model was established through machine learning.

Bacterial outer membrane vesicle nanorobot.

Autonomous nanorobots represent an advanced tool for precision therapy to improve therapeutic efficacy. However, current nanorobotic designs primarily rely on inorganic materials with compromised biocompatibility and limited biological functions. Here, we introduce enzyme-powered bacterial outer membrane vesicle (OMV) nanorobots.

Strength-ductility materials by engineering a coherent interface at incoherent precipitates.

In the quest for excellent light-structural materials that can withstand mechanical extremes for advanced applications, design and control of microstructures beyond current material design strategies have become paramount. Herein, we design a coherent shell at incoherent precipitates in the 2195 aluminum alloy with multi-step metastable phase transitions. A high local strain rate a neoteric deformation-driven metallurgy method facilitated the diffusion of Li.

Extrinsic-Riveting Friction Stir Lap Welding of Al/Steel Dissimilar Materials.

To obtain high-quality joints of Al/steel dissimilar materials, a new extrinsic-riveting friction stir lap welding (ERFSLW) method was proposed combining the synthesis advantages of mechanical riveting and metallurgical bonding. SiC-reinforced Al matrix composite bars were placed in the prefabricated holes in Al sheets and steel sheets, arranged in a zigzag array. The bars were stirred and mixed with Al sheets under severe plastic deformation (SPD), forming composite rivets to strengthen the mechanical joining.

An innovative approach for assessing coronary artery lesions: Fusion of wrist pulse and photoplethysmography using a multi-sensor pulse diagnostic device.

Coronary heart disease (CHD) is a leading cause of mortality globally and poses a significant threat to public health. Coronary angiography (CAG) is a gold standard for the clinical diagnosis of CHD, but its invasiveness restricts its widespread application. In this study, we utilized a pulse diagnostic device equipped with pressure and photoelectric sensors to synchronously and non-invasively capture wrist pressure pulse waves and fingertip photoplethysmography (FPPG) of patients undergoing CAG.

Deep learning to predict rapid progression of Alzheimer's disease from pooled clinical trials: A retrospective study.

The rate of progression of Alzheimer's disease (AD) differs dramatically between patients. Identifying the most is critical because when their numbers differ between treated and control groups, it distorts the outcome, making it impossible to tell whether the treatment was beneficial. Much recent effort, then, has gone into identifying RPs.

Comprehensive carbon footprint analysis of wastewater treatment: A case study of modified cyclic activated sludge technology for low carbon source urban wastewater treatment.

To reduce pollution and carbon emissions, a quantitative evaluation of the carbon footprint of the wastewater treatment processes is crucial. However, micro carbon element flow analysis is rarely focused considering treatment efficiency of different technology. In this research, a comprehensive carbon footprint analysis is established under the micro carbon element flow analysis and macro carbon footprint analysis based on life cycle assessment (LCA).

High glucose levels accelerate atherosclerosis via NLRP3-IL/ MAPK/NF-κB-related inflammation pathways.

Background: As a chronic inflammatory disease, diabetes mellitus (DM) contributes to the development of atherosclerosis (AS). However, how the NLRP3 inflammasome participates in diabetes-related AS remains unclear. Therefore, this study aimed to elucidate the mechanism through which NLRP3 uses high glucose (HG) levels to promote AS.

Equity-based carbon neutral plan induces cross-regional coal leakage and industrial relocation.

China as a major coal-consuming economy faces the challenge of balancing economic development and carbon neutrality goal. This paper incorporates both efficiency-based and equity-based carbon neutrality policies into a numerical model to quantitatively assess how coal reduction under various carbon-neutral policies affects energy mix, economic growth, and industrial structures by 2060. Results show the nationwide coal intensity will ultimately plunge by over 95% from 2017 to 2060, mainly attributed to the coal-phasing-out in most industries.

Nanofluid Drop Impact on Heated Surfaces.

We experimentally elucidate the impact dynamics of ethylene glycol (EG) droplets laden with both hydrophilic and hydrophobic SiO nanoparticles (NPs) onto a flat heated surface in non-boiling, boiling, and Leidenfrost regimes. We use seven nanofluid concentrations (), ranging from 0.89 to 64.

Local Contrastive Learning for Medical Image Recognition.

The proliferation of Deep Learning (DL)-based methods for radiographic image analysis has created a great demand for expert-labeled radiology data. Recent self-supervised frameworks have alleviated the need for expert labeling by obtaining supervision from associated radiology reports. These frameworks, however, struggle to distinguish the subtle differences between different pathologies in medical images.

Unveiling the importance of VOCs from pesticides applicated in main crops for elevating ozone concentrations in China.

Volatile organic compounds (VOCs) are considered as important precursors of ozone in the air, while the contribution of VOCs from pesticide application (PVOCs) to ozone production is unknown. Utilizing data from the Ministry of Agriculture and Rural Affairs of the People's Republic of China and ChinaCropPhen1km, this paper developed PVOC emission inventories with a resolution of 1 km for the main crops (rice, maize, and wheat) from 2012 to 2019 in China. The results revealed that pesticide application is an important VOC emission source in China.

Learning-based intelligent trajectory planning for auto navigation of magnetic robots.

Electromagnetically controlled small-scale robots show great potential in precise diagnosis, targeted delivery, and minimally invasive surgery. The automatic navigation of such robots could reduce human intervention, as well as the risk and difficulty of surgery. However, it is challenging to build a precise kinematics model for automatic robotic control because the controlling process is affected by various delays and complex environments.

Knowledge-guided Deep Temporal Clustering for Alzheimer's Disease Subtypes in Completed Clinical Trials.

Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder with varied patient progression. We aim to test the hypothesis that AD patients can be categorized into subgroups based on differences in progression. We leveraged data from three randomized clinical trials (RCTs) to develop a knowledge-guided, deep temporal clustering (KG-DTC) framework for AD subtyping.

Mitochondrial myopathy without extraocular muscle involvement: a unique clinicopathologic profile.

Objective: Mitochondrial myopathy without extraocular muscles involvement (MiMy) represents a distinct form of mitochondrial disorder predominantly affecting proximal/distal or axial muscles, with its phenotypic, genotypic features, and long-term prognosis poorly understood.

Methods: A cross-sectional study conducted at a national diagnostic center for mitochondrial disease involved 47 MiMy patients, from a cohort of 643 mitochondrial disease cases followed up at Qilu Hospital from January 1, 2000, to January 1, 2021. We compared the clinical, pathological, and genetic features of MiMy to progressive external ophthalmoplegia (PEO) and mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) patients.

Construction of a synthetic microbial community based on multiomics linkage technology and analysis of the mechanism of lignocellulose degradation.

The efficient degradation of lignocellulose is a bottleneck for its integrated utilization. This research performed species analysis and made functional predictions in various ecosystems using multiomics coupling to construct a core synthetic microbial community with efficient lignocellulose degradation function. The synthetic microbial community was employed to degrade corn straw via solid-state fermentation.

Application of machine learning to predict hospital visits for respiratory diseases using meteorological and air pollution factors in Linyi, China.

Urbanization and industrial development have resulted in increased air pollution, which is concerning for public health. This study evaluates the effect of meteorological factors and air pollution on hospital visits for respiratory diseases (pneumonia, acute upper respiratory infections, and chronic lower respiratory diseases). The test dataset comprises meteorological parameters, air pollutant concentrations, and outpatient hospital visits for respiratory diseases in Linyi, China, from January 1, 2016 to August 20, 2022.