Efficacy and Safety of SHR8554 on Postoperative Pain in Subjects with Moderate to Severe Acute Pain Following Orthopedic Surgery: A Multicenter, Randomized, Double-blind, Dose-explored, Active-controlled, Phase II/III Clinical Trial.

Biased µ-opioid receptor (MOR) agonists enhance pain relief by selectively activating G protein-coupled receptor signaling and minimizing β-arrestin-2 activation, resulting in fewer side effects. This multicenter Phase II/III trial evaluated the optimal dosage, efficacy, and safety of SHR8554, a biased MOR agonist, for postoperative pain management following orthopedic surgery. In Phase II, 121 patients were divided into four groups to receive varying patient-controlled analgesia (PCA) doses of SHR8554 or morphine.

Efficacy and safety of PD-1 blockade-activated neoantigen specific cellular therapy for advanced relapsed non-small cell lung cancer.

Background: Due to its strong immunogenicity and tumor specificity, neoplastic antigen has emerged as an immunotherapy target with wide therapeutic prospect and clinical application value. Anti-programmed death-1 (PD-1) antibodies reinvigorate T cell-mediated antitumor immunity. So, we conducted single-arm trial to assess the safety and efficacy of PD-1 blockade(Camrelizumab)-activated neoantigen specific cellular therapy (aNASCT) on advanced relapsed non-small lung cancer(NSCLC)(ClinicalTrials.

Pathologic function and therapeutic potential of extracellular vesicle miRNA in sepsis.

Sepsis is a systemic inflammatory response initiated by an infection, which can lead to multi-organ dysfunction. The pathophysiology of sepsis is complex, and treatment options are limited. Traditional antibiotic therapies have shown limitations, such as promoting the emergence of antibiotic-resistant bacteria and disrupting the natural microbiota.

Natural products as Nrf2 modulators for ferroptosis inhibition in renal disease therapy: Recent progress and future prospects.

Background: The transcription factor Nrf2 (nuclear factor erythroid 2-related factor 2, NFE2L2) is a pivotal regulator of redox balance, metabolism, protein homeostasis and inflammation. Nrf2 is critically involved in both ferroptosis and renal diseases, and may serve as a significant target for many natural products in the treatment of renal diseases. However, a comprehensive overview on this topic is still lacking.

Integrated cell membrane encapsulated PQDs-TK quantum dot nanoclusters with ROS-responsive triggering for efficient and visualized DNA delivery.

With the unique photo-physical properties and strong bio-compatibility. Quantum dots (QDs) have sparked interest in biomedical fields such as imaging, biosensing and therapeutics. However, the low stability and insufficient tumor specificity have largely constrained their potential biomedical applications.

The potential mechanisms and material basis of Fuzheng Jiedu decoction broad-spectrum inhibiting coronaviruses.

Traditional Chinese medicine has unique advantages in preventing and treating COVID-19, and Fuzheng Jiedu decoction (FZJDD) was reported to be effective against COVID-19 in clinical trials. To investigate the potential mechanisms and material basis of FZJDD against SARS-CoV-2, we performed SARS-CoV-2 target protein inhibition analyses and a metabolite full spectrum analysis of FZJDD. Interestingly, FZJDD was found to block the binding of SARS-CoV-2 Spike protein with the receptor ACE2 and inhibit the activity of SARS-CoV-2 3CLpro.

Depression Severity Mediates the Relationships Between Parenting Styles, Peer-Victimization and Mobile Phone Dependence in Adolescents.

Purpose: Negative parenting styles, peer victimization, and mobile phone dependence (MPD) are prevalent public health problems among adolescents. Parenting styles and peer victimization were reported to affect MPD, but their interaction and the mechanism underlying this association still need to be explored. This study aimed to examine how these factors affect MPD in adolescents with depression.

Exploring the Microbial Landscape of Bone and Joint Infections: An Analysis Using 16S rRNA Metagenome Sequencing.

Background: Bone and joint infections (BJIs) are challenging to diagnose. This study evaluated the utility of 16S rRNA gene sequencing in diagnosing BJIs, comparing it with conventional bacterial culture to explore microbial diversity in orthopedic infections.

Methods: Thirty patients with BJIs were enrolled from January 2019 to September 2020 at a single orthopedic center.

Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation.

As maximum power point tracking (MPPT) algorithms have developed towards multi-task intelligent computing, processors in photovoltaic power generation control systems must be capable of achieving a higher performance. However, the challenges posed by the complex environment of photovoltaic fields with regard to processor reliability cannot be overlooked. To address these issues, we proposed a novel approach.

METTL3 improves the development of somatic cell nuclear transfer embryos through AURKB and H3S10ph in goats.

Developmental abnormalities are more common in somatic cell nuclear transfer (SCNT) embryos due to epigenetic barriers that occur during the maternal-to-zygotic transition (MZT). N6-methyladenosine (m6A) is an RNA epigenetic modification that plays a significant role in numerous biological processes. However, the relationship between m6A and SCNT embryonic development is largely unexplored.

Rapid Identification of Cell Types and Phenotypic States Using a One-Polymer Multichannel Nanosensor Fabricated via Flash Nanoprecipitation.

Cell state transitions are fundamental in biology, determining how cells respond to environmental stimuli and adapt to diseases and treatments. Cell surface-based sensing of geno/phenotypes is a versatile approach for distinguishing different cell types and states. Array-based biosensors can provide a highly sensitive platform for distinguishing cells based on the differential interactions of each sensing element with cell surface components.

Global research trends and hotspots in Parkinson's disease psychosis: a 25-year bibliometric and visual analysis.

Background: Parkinson's disease psychosis (PDP) is one of the most severe and disabling non-motor symptoms in the progression of Parkinson's disease (PD), significantly impacting the prognosis of PD patients. In recent years, there has been an increase in literature on PDP. However, bibliometrics has rarely been applied to PDP research.

Generalized Estimating Equations for Survival Data With Dependent Censoring.

Independent censoring is usually assumed in survival data analysis. However, dependent censoring, where the survival time is dependent on the censoring time, is often seen in real data applications. In this project, we model the vector of survival time and censoring time marginally through semiparametric heteroscedastic accelerated failure time models and model their association by the vector of errors in the model.

Structural analysis and intelligent classification of clinical trial eligibility criteria based on deep learning and medical text mining.

Objective: To enhance the efficiency, quality, and innovation capability of clinical trials, this paper introduces a novel model called CTEC-AC (Clinical Trial Eligibility Criteria Automatic Classification), aimed at structuring clinical trial eligibility criteria into computationally explainable classifications.

Methods: We obtained detailed information on the latest 2,500 clinical trials from ClinicalTrials.gov, generating over 20,000 eligibility criteria data entries.

Shared differential factors underlying individual spontaneous neural activity abnormalities in major depressive disorder.

Background: In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.

Methods: To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities.