Assessment of chest CT abnormalities and pulmonary function at 6-month and 1-year after hospital discharge in Chinese patients of COVID-19 pneumonia at the turn of 2022-2023.

Objective: This study aimed to assess chest CT abnormalities and pulmonary function at 6-month and 1-year follow-ups in coronavirus disease 2019 (COVID-19) pneumonia patients of the China epidemic in the turn of 2022-2023.

Methods: A total of 156 hospitalized patients with COVID-19 pneumonia admitted between 29 November 2022 and 10 February 2023 were prospectively assessed at 6-month and 1-year follow-ups. Characteristics and CT scores of pulmonary abnormalities and pulmonary function were compared between different follow-up time points.

High-performance magnesium organic batteries using renewable biomolecule-based cathode.

Rechargeable magnesium batteries (RMBs) exhibit significant potential in large-scale energy storage due to their features of high volumetric capacity, resistance to dendrite formation, and abundant magnesium resources. However, the high polarity of divalent Mg2+ ions results in sluggish diffusion kinetics in conventional inorganic cathode materials, adversely affecting reversible capacity and rate performance. Organic materials such as pyrene-4,5,9,10-tetrone (PTO) and 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA), achieve rapid and reversible intercalation of magnesium ions through carbonyl enolization, but these materials are challenged by high cost, complex preparation, and poor environmental friendliness.

Prevalence of complementary therapy use in patients with inflammatory arthritis: a cross-sectional study in China.

This study aimed to evaluate the utilization of complementary and alternative medicine (CAM) among Chinese patients with inflammatory arthritis (IA), the types of CAM used, and the factors associated with its use. This cross-sectional study was conducted at the Department of Rheumatology and Immunology at the First Affiliated Hospital of Anhui Medical University. Data were collected from 503 IA patients using self-administered questionnaires and electronic medical records.

A Function-Oriented Binder with Exceptional Interface Ion Transport and Impurity Tolerance for Hard Carbon Anode.

Hard carbon is the sole anode material employed in commercial sodium-ion batteries. However, its intrinsic defects and impurities will lead to battery failure, diminishing further development of sodium batteries in energy storage. Here, an acrylonitrile copolymer and poly(ethylene oxide) (LA/PEO) composite binder is developed to address these challenges in biomass-derived hard carbon.

Prognostic risk modeling of endometrial cancer using programmed cell death-related genes: a comprehensive machine learning approach.

Background: Endometrial cancer represents a significant health challenge, with rising incidence and complex prognostic challenges. This study aimed to develop a robust predictive model integrating programmed cell death-related genes and advanced machine learning techniques.

Methods: Utilizing transcriptomic data from TCGA-UCEC and GSE119041 datasets, we employed a comprehensive approach involving 117 machine learning algorithms.

Novel Clean-Background Coffee Ring SERS Platform for Trace Toxin Analysis.

Biotoxins, known for their ubiquity and potent toxicity, pose significant threats to ecosystems and human health, highlighting the urgency the development of robust detection methods. Despite the significant potential of surface-enhanced Raman spectroscopy (SERS) in analytical science, challenges emerge when dealing with low Raman active molecules, such as biotoxins. Our study addresses this by introducing an innovative, ultrasensitive, clean-background coffee ring SERS (CC-SERS) platform, specifically designed for the detection of neo-saxitoxin (neo-STX), saxitoxin (STX), microcystin-LR (MC-LR), and microcystin-RR (MC-RR) using the AgNPs@AgO@AgCl coffee rings.

Leapfrogging : harnessing 1432 GPUs for 7× faster quantum random circuit sampling.

Random quantum circuit sampling serves as a benchmark to demonstrate quantum computational advantage. Recent progress in classical algorithms, especially those based on tensor network methods, has significantly reduced the classical simulation time and challenged the claim of first-generation quantum advantage experiments. However, in terms of generating uncorrelated samples, time to solution and energy consumption, previous classical simulation experiments still underperform the processor.

Tuning Li occupancy and local structures for advanced Co-free Ni-rich positive electrodes.

Structure evolution and surface reactivity have long been regarded as the most crucial points for studying Ni-rich positive electrodes for Li-ion batteries. Unfortunately, the influence of Li occupancy as a single factor on electro-chemomechanical stability has been overlooked and is missing, owing to the challenge of Li determination in the lattice. Here, a comprehensive analysis reveals different Li occupancies and related structural domains (Ni/Li exchange, LiXO, Li/Mn/X(Ni) ordering domains, X = Nb, W, and Mo) by using a combination of Li-sensitive characterization techniques.

Enhancing Motor Learning Performance by Incorporating Brain-to-brain Coupling with Affective Interaction.

The widespread clinical application of rehabilitation robots is an inevitable trend. Nonetheless, the absence of affective interactions in robot-based training could significantly limit rehabilitation robots' clinical effects. While a favorable patient-clinician relationship during rehabilitation training may promote positive affectivity and result in improved clinical outcomes, the mechanisms underlying this phenomenon remain unclear.

Precise CH Adsorption Affinity Modulation by Nitrogen Functionalization in Isostructural Coordination Networks.

Meticulous regulation of pore chemistry is essential for elucidating the intricate mechanism of the adsorption efficacy of porous materials. However, it is a great challenge to address the functionalization of pore chemistry while preserving pore size and geometry. In this study, the robust NPU-1 series network is selected as a platform to address this challenge.

MRI Motion Correction Through Disentangled CycleGAN Based on Multi-Mask K-Space Subsampling.

This work proposes a new retrospective motion correction method, termed DCGAN-MS, which employs disentangled CycleGAN based onmulti-mask k-space subsampling (DCGAN-MS) to address the image domain translation challenge. The multi-mask k-space subsampling operator is utilized to decrease the complexity of motion artifacts by randomly discarding motion-affected k-space lines. The network then disentangles the subsampled, motion-corrupted images into content and artifact features using specialized encoders, and generates motion-corrected images by decoding the content features.

Synthesis and characterization of anthocyanin-loaded bovine serum albumin nanoparticles: unveiling the encapsulation mechanisms with computational insights.

Background: Black rice anthocyanins (BRA) offer significant health benefits but are limited in application due to their low bioavailability. Bovine serum albumin (BSA) nanoparticles (NPs) have been shown to effectively enhance the stability of encapsulated BRA. However, the mechanism of BRA-BSA NP formation and their molecular interactions remain unclear.

Utilizing Nanoparticles to Overcome Anti-PD-1/PD-L1 Immunotherapy Resistance in Non-Small Cell Lung cancer: A Potential Strategy.

Lung cancer is the leading cause of cancer-related mortality globally, with non-small cell lung cancer (NSCLC) constituting 85% of cases. Immune checkpoint inhibitors (ICIs) represented by anti-programmed cell death protein 1 (PD-1)/ programmed cell death ligand 1 (PD-L1) have emerged as a promising frontier in cancer treatment, effectively extending the survival of patients with NSCLC. However, the efficacy of ICIs exhibits significant variability across diverse patient populations, with a substantial proportion showing poor responsiveness and acquired resistance in those initially responsive to ICIs treatments.

Inhibitory effects on smooth muscle cell adhesion and proliferation due to oscillating electric fields by nanogenerators.

A common complication of the removal of atherosclerotic plaques or thrombi deposits to restore blood flow is restenosis. It is known that the excessive adhesion and proliferation of smooth muscle cells (SMCs) is the primary reason for restenosis. In this work, we conducted an study to show that a weak oscillating electric field (EF) generated by a mechanically-driven nanogenerator could prohibit SMC adhesion and proliferation on a substrate surface.

Anion Adsorption at the Inner-Helmholtz Plane Directs Cathode Electrolyte Interphase Formation.

Constructing a stable cathode-electrolyte-interphase (CEI) on cathode surface constitutes the foundation of realizing high-voltage Li-ion batteries, yet its formation, a highly heterogeneous process involving irreversible reactions between electrolyte components and cathode materials, remains poorly understood. Herein, combining multiple in situ/operando interfacial characterization techniques, we establish the correlation between interfacial structure and interphasial chemistry, and reveal the key role played by adsorptive behavior of various electrolyte components in the inner-Helmholtz plane during CEI formation. Quartz crystal microbalance equipped with dissipation modification detects that difluorooxalatoborate (DFOB) anion preferentially adsorbed on LiCoO tends to expel carbonate solvents from the adsorption layer, thus suppressing their electrochemical decomposition at high voltages and leading to a more compact CEI derived from anions with limited contribution from organic ingredients.

Predicting Microvascular Invasion and Early Recurrence in Hepatocellular Carcinoma Using DeepLab V3+ Segmentation of Multiregional MR Habitat Images.

Rationale And Objectives: Accurate identification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is crucial for treatment and prognosis. Single-modality and feature fusion models using manual segmentation fail to provide insights into MVI. This study aims to develop a DeepLab V3+ model for automated segmentation of HCC magnetic resonance (MR) images and a decision fusion model to predict MVI and early recurrence (ER).

Associations of hippocampal volumes, brain hypometabolism, and plasma NfL with amyloid, tau, and cognitive decline.

Introduction: Various indicators of neurodegeneration (N) are used in the assessment of neuronal injury in Alzheimer's disease (AD). The heterogeneity of such indicators is less clear.

Methods: A total of 416 individuals with different cognitive statuses were recruited for this study.

An Integrated Virtual Screening Platform to Identify Potent Co-Assembled Nanodrugs for Cancer Treatment.

Co-assembled nanodrugs provide significant advantages in cancer treatment and drug delivery, yet effective screening methods to identify molecular combinations for co-assembly are lacking. This study presents a screening strategy integrating ligand-based virtual screening (LBVS) and density functional theory (DFT) calculations to explore new molecular combinations with co-assembly capabilities. The accuracy of this screening was validated by synthesizing various co-assembled nanodrugs under mild conditions.

Bacteria escape macrophage-mediated phagocytosis via targeting apurinic/apyrimidinic endonuclease 1 in sepsis.

Sepsis is a serious disease resulting from an imbalanced host response to bacterial infection, in which macrophages play a crucial role. However, the connection between bacterial infection and macrophage phagocytosis remains largely unknown. Here, we provide evidence supporting the role of apurinic/apyrimidinic endonuclease 1 (APE1) in regulating bacterial infection and macrophage immune function during sepsis.

Current status and influencing factors of pediatric clinical nurses' scientific research ability: a survey.

Background: Enhancing the research abilities of clinical nurses is a pivotal aspect of nursing management. The purpose of this survey is to assess the current state of research abilities among pediatric nurses and to identify the associated influencing factors, thereby providing empirical support for the improvement of research competencies in pediatric nurses.

Methods: Pediatric clinical nurses at a tertiary children's hospital in Nanjing, China from May 1st to 31st, 2024 were included for survey.

Superionic Ionic Conductor Discovery via Multiscale Topological Learning.

Lithium superionic conductors (LSICs) are crucial for next-generation solid-state batteries, offering exceptional ionic conductivity and enhanced safety for renewable energy and electric vehicles. However, their discovery is extremely challenging due to the vast chemical space, limited labeled data, and the understanding of complex structure-function relationships required for optimizing ion transport. This study introduces a multiscale topological learning (MTL) framework, integrating algebraic topology and unsupervised learning to tackle these challenges efficiently.

Enhancing Chest X-ray Diagnosis with a Multimodal Deep Learning Network by Integrating Clinical History to Refine Attention.

The rapid advancements of deep learning technology have revolutionized medical imaging diagnosis. However, training these models is often challenged by label imbalance and the scarcity of certain diseases. Most models fail to recognize multiple coexisting diseases, which are common in real-world clinical scenarios.

Real-World Effectiveness of 3 Types of Acellular Pertussis Vaccines Among Children Aged 3 Months-16 Years in Lu'an, China: A Matched Case-Control Study.

Background: The real-world vaccine effectiveness (VE) of the diphtheria, tetanus, and acellular pertussis (DTaP), DTaP- type b (Hib), and DTaP-inactivated polio (IPV)/Hib vaccines has not been thoroughly evaluated in China. Additionally, there are limited data on the VE of acellular pertussis-containing vaccines (aPVs) when used interchangeably.

Methods: We conducted a matched case-control study to estimate the VE of aPVs against polymerase chain reaction-confirmed pertussis infection in Lu'an in 2024.

Impacts of successive Chinese fir plantations on soil carbon and nitrogen dynamics: Conclusive insights from metagenomic analysis.

Chinese fir forests play a significant role both economically and ecologically, contributing to soil and water conservation while also serving as an efficient timber-producing species that brings economic benefits. However, the issue of soil degradation due to continuous Chinese fir planting cannot be overlooked. Continuous planting leads to a decrease in soil nutrients, a reduction in microbial diversity, and changes in microbial community composition, which in turn affect the abundance of carbon and nitrogen cycle functional genes in Chinese fir forest soils.