Publications by authors named "WeiZhi Liu"

Perovskite quantum dots (PQDs) show promise in light-emitting diodes (LEDs). However, near-infrared (NIR) LEDs employing PQDs exhibit inferior external quantum efficiency related to the PQD emitting in the visible range. One fundamental issue arises from the PQDs dynamic surface: the ligand loss and ions migration to the interfacial sites serve as quenching centers, resulting in trap-assisted recombination and carrier loss.

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  • This study explores how resting-state EEG can reveal neurophysiological markers linked to impulsivity in individuals addicted to gambling or methamphetamine, compared to healthy controls.
  • Participants from three groups (gamblers, methamphetamine users, and healthy controls) underwent EEG recordings and impulsivity assessments, revealing significant differences in impulsivity traits and behaviors among the groups.
  • Findings indicated that gambling addicts showed the highest overall impulsivity, methamphetamine users had greater attentional impulsivity, and specific EEG connectivity patterns distinguished addicts from healthy individuals, highlighting the importance of these neural mechanisms in understanding addiction-related impulsivity.
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To discover new potential drug for acute kidney injury (AKI), a series of novel alginate oligosaccharide derivatives were synthesized and characterized by the spectroscopic analysis. By using the controlled experimental method, the target compounds were evaluated preliminarily for therapeutic activity in AKI. The results demonstrated that compounds 2a, 2b, 2c and 3b exhibited notable inhibitory activity against the expression of related proteins at 250 μg/ml in vitro.

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  • The study investigates the effectiveness of a computer vision system in aiding exercise management for patients with knee osteoarthritis by comparing tele-rehabilitation and outpatient intervention programs.
  • The trial involves 60 patients with knee OA, randomly assigned to either an exercise therapy group or a control group, with assessments using various outcome measures at multiple intervals.
  • The research is ethically approved and registered, with a focus on evaluating improvements in functional ability, quality of life, and physical fitness over a 12-week intervention period.
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  • ZnSeTe quantum dots are promising for creating heavy-metal-free LEDs that meet blue light standards.
  • Advances in core-shell engineering have greatly improved the external quantum efficiency of these QD-LEDs.
  • This study investigates how ligand density and composition affect the stability of the materials and devices, finding that replacing organic ligands with inorganic ones enhances their overall stability.
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Objective: To reveal the chain mediating roles of insomnia and anxiety between social support and PTSD in nursing staff under the stage of COVID-19 regular pandemic prevention and control in China.

Methods: A total of 784 nurses were recruited using the convenience sampling method in Jiangsu Province, China. Demographic questionnaire, Perceived Social Support Scale, Impact of Event Scale-Revised, Generalized Anxiety Disorder-7 and Insomnia Severity Index were applied to collect data.

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Background: Repetitive transcranial magnetic stimulation (rTMS) showed potentially beneficial effects for the treatment of post-traumatic stress disorder (PTSD). Low-frequency (LF) rTMS decreases neuronal excitability and may have better safety compared to high-frequency (HF) rTMS. However, there lacks meta-analysis specifically focusing on LF rTMS.

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The solution-derived non-stoichiometric nickel oxide (NiO) is a promising hole-injecting material for stable quantum dot light-emitting diodes (QLEDs). However, the carrier imbalance due to the misalignment of energy levels between the NiO and polymeric hole-transporting layers (HTLs) curtails the device efficiency. In this study, the modification of the NiO surface is investigated using either 3-cyanobenzoic acid (3-CN-BA) or 4-cyanobenzoic acid (4-CN-BA) in the QLED fabrication.

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Objective: The study aims to explore the relationship between modifiable lifestyle factors (physical activity, sedentary time, body composition, muscle strength) and mental health, and predict future changes in mental health.

Methods: A cross-sectional survey was conducted on 133 men (age: 29.03 ± 6.

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Near-infrared light-emitting diodes (NIR LEDs) based on perovskite quantum dots (QDs) have produced external quantum efficiency (EQE) of ~15 %. However, these high-performance NIR-QLEDs suffer from immediate carrier quenching because of the accumulation of migratable ions at the surface of the QDs. These uncoordinated ions and carriers-if not bound to the nanocrystal surface-serve as centers for exciton quenching and device degradation.

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Bacterial cellulose (BC) has recently attracted a lot of attention as a high-performance, low-cost separator substrate for a variety of lithium-ion (LIBs) and lithium‑sulfur batteries (LISs). BC-base can be used in the design and manufacture of separators, mainly because of its unique properties compared to traditional polyethylene/polypropylene separator materials, such as high mechanical properties, high safety, good ionic conductivity, and suitability for a variety of design and manufacturing needs. In this review, we briefly introduce the sources, production methods, and modification strategies of BC, and further describe the preparation methods and properties of BC battery separators for various LIBs and LISs.

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The growing demand for wearable and attachable displays has sparked significant interest in flexible quantum-dot light-emitting diodes (QLEDs). However, the challenges of fabricating and operating QLEDs on flexible substrates persist due to the lack of stable and low-temperature processable charge-injection/-transporting layers with aligned energy levels. In this study, we utilized NiO nanoparticles that are compatible with flexible substrates as a hole-injection layer (HIL).

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Gouty arthritis causes severe pain and inflammation. Alginate oligosaccharides (AOSs) are natural products derived from alginate and have anti-inflammatory properties. We explored the potential effects of AOSs with different degrees of polymerization (Dp) on gouty arthritis and associated mechanisms.

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Background: The efficacy of large language models (LLMs) in domain-specific medicine, particularly for managing complex diseases such as osteoarthritis (OA), remains largely unexplored.

Objective: This study focused on evaluating and enhancing the clinical capabilities and explainability of LLMs in specific domains, using OA management as a case study.

Methods: A domain-specific benchmark framework was developed to evaluate LLMs across a spectrum from domain-specific knowledge to clinical applications in real-world clinical scenarios.

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The management of diabetic wound healing remains a severe clinical challenge due to the complicated wound microenvironments, including abnormal immune regulation, excessive reactive oxygen species (ROS), and repeated bacterial infections. Herein, we report an extracellular matrix (ECM)-mimetic coating derived from scallop byssal protein (Sbp9), which can be assembled within 30 min under the trigger of Ca driven by strong coordination interaction. The biocompatible Sbp9 coating and genetically programmable LL37-fused coating exhibit outstanding antioxidant, antibacterial, and immune regulatory properties .

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Background: Sex-based differences are known to be a significant feature of chronic stress; however, the morphological mechanisms of the brain underlying these differences remain unclear. The present study aimed to use magnetic resonance imaging (MRI) and voxel-based morphometry (VBM) to investigate the effects of sex on gray matter volume (GMV) changes under conditions of chronic stress.

Methods: A total of 32 subjects were included for analysis in the present study: 16 participants experiencing chronic stress and 16 healthy controls.

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  • PTSD is a serious mental health problem, and new studies are looking at how big data and machine learning can help understand it better.
  • Researchers found 873 studies, and after looking closely at 31 of them, they discovered that machine learning can identify PTSD with an accuracy of 89%.
  • Using different types of data together makes it even more accurate, scoring 96%, which is better than just using one type of data.
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  • Many healthcare workers faced mental health issues during the COVID-19 pandemic.
  • A study found that around 10% reported post-traumatic stress symptoms (PTSS), 13% had symptoms of depression, and 8% experienced anxiety.
  • Certain factors like job type and work hours affected their mental health, and treatment could focus on sleep problems and feelings of worry.
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Although bioactive peptides enhancing bone healing have demonstrated effectiveness in treating bone defects, in vivo instability poses a challenge to their clinical application. Currently reported peptide delivery systems do not meet the demands of bone tissue repair regarding stability and peptide release efficacy. Herein, the self-assembling recombinant chimeric protein (Sbp5-2) is developed by genetic engineering with cell adhesion peptide RGD as the targeted peptide and a newly discovered scallop byssal-derived protein Sbp5-2 that can assemble into wet stable films as the structural domain.

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  • Cognitive models say that how we think can affect PTSD, especially not paying attention to good things and focusing too much on scary stuff.
  • The study checked if a way to change how we pay attention (called ABM) really helps people with PTSD by comparing it to another method (called ACT).
  • The results showed that ACT was better at improving PTSD symptoms overall, but both methods helped with attention issues, and more research is needed to understand ACT’s full benefits.
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Introduction: Recent years have witnessed a persistent threat to public mental health, especially during and after the COVID-19 pandemic. Posttraumatic stress disorder (PTSD) has emerged as a pivotal concern amidst this backdrop. Concurrently, machine learning (ML) techniques have progressively applied in the realm of mental health.

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  • The study looked at how fear during the COVID-19 pandemic affected people's mental health, especially posttraumatic stress symptoms (PTSS).
  • Researchers collected data from 150 people at two different times, finding that people experienced less fear over time but those with more fear had worse PTSS.
  • The results suggest that reducing fear can help people cope better with trauma, and future programs could focus on lowering fear during tough times like pandemics.
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The use of large language models (LLMs) in clinical medicine is currently thriving. Effectively transferring LLMs' pertinent theoretical knowledge from computer science to their application in clinical medicine is crucial. Prompt engineering has shown potential as an effective method in this regard.

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