Browse Articles

Effectiveness of tuberculosis preventive treatment on disease incidence among people living with HIV/AIDS: A systematic review and meta-analysis

Background Clinical trials have shown the protective efficacy of tuberculosis preventive treatment (TPT) for averting disease and death from tuberculosis among people living with HIV/AIDS (PLHIV). TPT has been recommended for PLHIV since the 1980s. However, tuberculosis is still the first cause of death in PLHIV. Objective We aimed to summarize the evidence related to the real-world effectiveness of TPT on tuberculosis incidence among PLHIV. Method This is a systematic review and meta-analysis of observational cohort studies. The search was carried out in PubMed (via MEDLINE), Embase, LILACS, Scopus and Web of Science databases. Free and controlled vocabulary was used for the searches, with no restrictions on language or publication period. Studies reporting hazard ratios (HR) for tuberculosis incidence among PLHIV who received TPT were pooled using random-effects meta-analysis models. Meta-regression was performed to assess whether study-level characteristics accounted for heterogeneity, as evaluated by Cochran’s I² statistic. Study quality was appraised using the Newcastle-Ottawa Scale. This study was registered with PROSPERO (CRD42024586273). Results Among 8,330 screened studies, 34 were included, with nine contributing to the meta-analysis. TPT was associated with a 63% reduction in tuberculosis incidence risk (HR = 0.37, 95% CI: 0.28–0.48; I² = 43%). Children exhibited consistent stronger protection (82% risk reduction, HR = 0.18, 0.09–0.37; I² = 0%) than adults (56% reduction, HR = 0.44, 0.37–0.53; I² = 21%). Conclusion In real world conditions, TPT significantly and substantially reduces tuberculosis incidence in PLHIV, with consistent evidence of stronger protective effects in children. Despite some heterogeneity among adult studies, the pooled evidence confirms the protective effectiveness previously observed in clinical trials. These findings reinforce the global recommendation for broad implementation of TPT among PLHIV.

Ultrafast decoupling of polarization and strain in ferroelectric BaTiO3

Abstract A fundamental understanding of the interplay between lattice structure, polarization and electrons is pivotal to the optical control of ferroelectrics. The interaction between light and matter enables the remote and wireless control of the ferroelectric polarization on the picosecond timescale, while inducing strain, i.e., lattice deformation. At equilibrium, the ferroelectric polarization is proportional to the strain, and is typically assumed to be so also out of equilibrium. Decoupling the polarization from the strain would remove the constraint of sample design and provide an effective knob to manipulate the polarization by light. Here, upon above-bandgap laser excitation of the prototypical ferroelectric BaTiO 3 , we induce and measure an ultrafast decoupling between polarization and strain that begins within 350 fs, by softening Ti-O bonds via charge transfer, and lasts for several tens of picoseconds. We show that the ferroelectric polarization out of equilibrium is mainly determined by photoexcited electrons, instead of the strain.

Novel thiazole derivatives as effective anti-cancer agents against human osteosarcoma cell line (SaOS-2): Microwave-assisted one-pot three-component synthesis, in vitro anti-cancer studies, and in silico investigations

The current research involves the preparation of novel thiazole derivatives, which was carried out via one-pot three-component reaction utilizing conventional and microwave irradiation (MW) methods. The MW method reduced the reaction time and allowed the reactions to be carried out with higher yields. 1H NMR, 13C NMR, EI-MS and FT-IR techniques were employed for the characterization of synthesized compounds. All compounds exhibited anti-cancer activity ranging from 0.190 to 0.273 µg/mL against SaOS-2 cell line and the best activity was shown by compound 4i which exhibited IC50 value = 0.190 ± 0.045 µg/mL. It is evident that the concentration of these compounds is a critical factor in determining their biological efficacy. This dose-dependent relationship highlights the importance of optimizing compound concentrations to achieve maximal therapeutic benefits while minimizing potential side effects. Moreover, these findings demonstrated the potential of thiazole derivatives as promising candidates for anti-cancer drug development and warrant further investigation into their mechanisms of action and therapeutic applications. Molecular modelling was utilized to predict potential interactions of the synthesized compounds that exhibited inhibitory effects. The analyses revealed that compound 4i exhibited strong inhibitory effects against EGFR (docking score: −6.434, MM-GBSA energy: −53.40 kcal/mol) in in silico studies.

An integrated transcriptomic and proteomic map of the mouse hippocampus at synaptic resolution

Abstract Understanding the brain’s molecular diversity requires spatially resolved maps of transcripts and proteins across regions and compartments. Here, we performed deep spatial molecular profiling of the mouse hippocampus, combining microdissection of 3 subregions and 4 strata with fluorescence-activated synaptosome sorting, transcriptomics, and proteomics. This approach revealed thousands of locally enriched molecules spanning diverse receptor, channel, metabolic, and adhesion families. Integration of transcriptome and proteome data highlighted proteins tightly linked to or decoupled from mRNA availability, in part due to protein half-life differences. Incorporation of translatome data identified roles for protein trafficking versus local translation in establishing compartmental organization of pyramidal neurons, with distal dendrites showing increased reliance on local protein synthesis. Classification of CA1 synapses revealed contributions from kinases, cytoskeletal elements, and adhesion molecules in defining synaptic specificity. Together, this study provides a molecular atlas of the hippocampus and its synapses ( syndive.org ), and offers insights into spatial transcript-protein relationships.

Editorial Note: Parental non-involvement strategy for handling sibling conflict on social avoidance in migrant children: Chain mediation of sibling conflict and parent-child conflict

Daily briefing: Repeated heatwaves make your biological clock run fast

Multi-state catch bond formed in the Izumo1:Juno complex that initiates human fertilization

Abstract Izumo1:Juno-mediated adhesion between sperm and egg cells is essential for mammalian sexual reproduction. However, conventional biophysical and structural approaches have provided only limited functional insights. Using atomic force microscopy-based single-molecule force spectroscopy and all-atom steered molecular dynamic simulations, we explore the role of mechanical forces in regulating the human Izumo1:Juno complex. Our findings reveal a multi-state catch bond capable of withstanding forces up to 600 pN– mechanostability rarely observed among eukaryotic protein complexes. We find that this enhanced mechanostability is impaired in the infertility-associated mutant, JunoH177Q. Detailed steered molecular dynamics simulations show how force-dependent structural reorganization of the Izumo1:Juno complex engages previously undiscovered binding conformations to achieve this state of high mechanostability. Overall, this study significantly enhances our understanding of the mechanical underpinnings that regulate human fertilization.

Identification of core genes in the extracellular matrix and the regulatory mechanisms of the immune microenvironment in idiopathic pulmonary fibrosis using WGCNA and machine learning methods

Objective This research aims to detect genes associated with the extracellular matrix (ECM) in idiopathic pulmonary fibrosis (IPF) using bioinformatics techniques and investigate their relationships with immune infiltration, with the goal of identifying new diagnostic and therapeutic targets for IPF. Methods The study employed a combination of differential expression analysis, weighted gene co-expression network analysis (WGCNA), and various machine learning algorithms to screen for characteristic genes. Gene set enrichment analysis (GSEA), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to evaluate relevant biological functions and pathways. Additionally, the analysis of immune cell infiltration was conducted to assess the disease’s immune status and the correlations between genes and immunity. Results IPF is strongly linked to pathways such as ECM organization and immune response, with differentially expressed genes primarily involving signal pathways related to collagen deposition in the extracellular matrix. A total of 1,193 ECM-related genes associated with IPF were identified, and 94 differentially expressed ECM-related genes were further screened compared to the normal control group. Through machine learning approaches, three key genes—BAAT, COMP, and CXCL13—were pinpointed. These genes are closely tied to the onset, progression, and immune processes of IPF, and clustering analysis based on them can reveal distinct disease states and changes in immune cell infiltration patterns. Conclusion BAAT, COMP, and CXCL13 may serve as potential therapeutic targets for slowing the progression and preventing the exacerbation of IPF. Moreover, monocytes demonstrate consistent infiltration patterns across the disease group, control group, and various subgroups, indicating their potential significance in the development of IPF.

Crotonylation of IDH1 alleviates MASLD progression by enhancing the TCA cycle

Critical node detection in temporal social networks, based on global and semi-local centrality measures

Nodes that play strategic roles in networks are called critical or influential nodes. For example, in an epidemic, we can control the infection spread by isolating critical nodes; in marketing, we can use certain nodes as the initial spreaders aiming to reach the largest part of the network, or they can be selected for removal in targeted attacks to maximise the fragmentation of the network. In this study, we focus on critical node detection in temporal networks. We propose three new measures to identify the critical nodes in temporal networks: the temporal supracycle ratio, temporal semi-local integration, and temporal semi-local centrality. We analyse the performance of these measures based on their effect on the SIR epidemic model in three scenarios: isolating the influential nodes when an epidemic happens, using the influential nodes as seeds of the epidemic, or removing them to analyse the robustness of the network. We compare the results with existing centrality measures, particularly temporal betweenness, temporal centrality, and temporal degree deviation. The results show that the introduced measures help identify influential nodes more accurately. The proposed methods can be used to detect nodes that need to be isolated to reduce the spread of an epidemic or as initial nodes to speedup dissemination of information.

Multiplex bead assays enable integrated serological surveillance and reveal cross-pathogen vulnerabilities in Zambezia Province, Mozambique

Abstract Multiplex serological assays simultaneously measure antibodies to multiple antigens, furnishing insights into exposure and susceptibility to several pathogens and cross-pathogen vulnerabilities. Our serosurvey tests dried blood spots from 1292 individuals for IgG antibodies to 35 antigens from 18 pathogens using a multiplex bead assay for vaccine preventable diseases, malaria, SARS-CoV-2, neglected tropical diseases, and enteric pathogens in Mozambique. We produce pathogen-specific seroprevalence estimates and age-seroprevalence curves and identify spatial differences in seroprevalence. Rural clusters have higher odds of seropositivity to most NTDs neglected tropical diseases, Plasmodium falciparum malaria, and enteric pathogens, but lower odds of seropositivity to SARS-CoV-2 and vaccine preventable diseases compared to urban clusters. This co-occurrence identifies clusters with high vulnerability to multiple pathogens. We identify a candidate group of antigens that are correlated with high overall vulnerability. Our results demonstrate a role for multiplex serology in integrated disease surveillance to guide control strategies for individual and co-endemic pathogens.

Immunophenotyping identifies key immune biomarkers for coronary artery disease through machine learning

Introduction The differences among immune subtypes in coronary artery disease (CAD), their interrelationships, and the associated immune biomarkers remain incompletely understood. Methods The samples were collected from the GSE20686 and GSE42148 datasets for analysis. Principal component analysis (PCA) and Gene Set Variation Analysis (GSVA) were performed on the subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine functional and pathways in CAD. Machine learning models were constructed for CAD prediction. Model validation was performed using GSE56885 and GSE71226 datasets. The expression and function of the identified genes were evaluated using immunohistochemistry, CCK-8 assays, wound healing assays, and Transwell invasion assays. Results Multiple immune cells showed correlations with CAD samples. Two immune cell subtypes were identified, with significant differences in programmed cell death-ligand (PD-L1) expression, immune scores, and stromal scores between subtypes (P < 0.05). Three CAD hub genes were identified by WGCNA. GO analysis revealed enrichment in Biological Process (BP) and Molecular Function (MF). Among the several machine learning models, the RF model was selected based on combining parameters. The model mainly included two CAD immune marker genes, AKT1 and PTK2B. Differential expression of AKT1 and PTK2B was observed in cardiac myocytes. Inhibition of PTK2B suppressed cell proliferation and invasion, and induced apoptosis in HUVEC cells. Conclusion Immunophenotyping revealed an association between CAD and PD-L1. AKT1 and PTK2B were identified as key disease signature genes, which may hold clinical significance for the diagnosis, prognostic assessment and treatment of CAD.

Trait anxiety is associated with reduced reward-related replay at rest

Multidisciplinary early activity team collaboration practice in ICUs: A qualitative study

Purpose To understand the collaborative practice experience of ICU patients’ multidisciplinary early activity team members to provide a reference for formulating a scientific multidisciplinary team collaboration model. Methods Based on the phenomenological research methodology of qualitative research, in-depth interviews were conducted with 22 multidisciplinary early mobilization teams of ICU patients in nine general tertiary hospitals in China, using a purposive sampling method, Themes were then distilled. Results Three themes and six subthemes emerged from the analysis. (1) Inadequate collaboration concepts: ① manager's philosophy, ② multidisciplinary membership concept; (2) Poor team building: ① poor team structure, ② member training needs to be strengthened; (3) Imperfect team management mechanism: ① no continuous improvement measures, ② unclear incentives. Conclusion Good teamwork, which promotes early mobilization of ICU patients, is a scientifically feasible model of collaboration that should be constructed to guide the team in their work.

Subsecond optically controlled domain switching in freestanding ferroelectric BaTiO3 membrane

Decompression with interbody fusion versus decompression alone for degenerative lumbar diseases: A meta-analysis

Objective To appraise the clinical effectiveness and complications of two surgical approaches, namely decompression alone (DA) versus decompression with interbody fusion (DF), in managing degenerative lumbar diseases (DLD). Methods As of July 1, 2024, an exhaustive search identified all randomized controlled studies and cohort studies comparing DA and DF in DLD management. Relevant data were extracted using strict criteria, and study quality was assessed via the Newcastle-Ottawa Scale and Cochrane Collaboration’s tool. The extracted outcomes encompassed a range of measures, including operative duration, intraoperative hemorrhage, hospitalization length, time to ambulation, short form 12 physical component score (SF12-PCS), low back pain visual analog scale (VAS) score, leg pain VAS score, Oswestry disability index (ODI), Japanese orthopedic association (JOA) score, EuroQol five dimensions (EQ-5D), incidence of complications, reoperation rate, and Odom’s criteria. Results A total of 35 articles were included in this study, involving 12,030 patients. Of these, 7,442 patients were in the DA group, while 4,588 were in the DF group. Operative duration was shorter (MD = −89.09, 95%CI −92.71, −85.47, P < 0.00001), intraoperative hemorrhage was less (MD = −242.26, 95%CI −252.16, −232.36, P < 0.00001), hospitalization length was shorter (MD = −2.36, 95%CI −2.59, −2.14, P < 0.00001), and time to ambulation was reduced (MD = −10.49, 95%CI −12.52, −8.46, P < 0.00001) in the DA group than in the DF group. At the final follow-up for ODI, the DF group demonstrated statistically superior outcomes compared to the DA group (MD = 1.28, 95%CI 0.35, 2.21, P = 0.007). Data revealed no significant differences in SF12-PCS, JOA score, back pain VAS score, leg pain VAS score, final follow-up EQ-5D, reoperation rates, complication rates, and Odom’s criteria (P > 0.05). Conclusion When treating DLD, DA offers more favorable outcomes in terms of operative duration, intraoperative hemorrhage, hospitalization length, and time to ambulation. These findings suggest that DA should be considered the preferred surgical approach for most DLD patients, unless specific indications for fusion exist. Clinicians should tailor decisions to each surgery’s specifics to optimize patient outcomes. Trial registration PROSPERO registration number: CRD42024580975.

A salt-free medium facilitating electrode prelithiation towards fast-charging and high-energy lithium-ion batteries

Abstract The substantial consumption of lithium ions and sluggish reaction kinetics at the anode detrimentally impact the deliverable energy and fast-charging capability of lithium-ion batteries with silicon-based anodes. The prevailing contact prelithiation method using an electrolyte medium can replenish the active lithium, but it may cause materials/electrode instability and bring barrier for lithium-ion transport. Here we explore a contact prelithiation methodology employing cyclic carbonate mediums that can enable spatially and temporally uniform prelithiation reaction. These mediums enable a delicate equilibrium between a lithium-ion diffusion and the intrinsic prelithiation reaction rate throughout the electrode depth. Not only does this prelithiation method serve the fundamental purpose of tackling lithium loss issue, but it also fosters the creation of a solid electrolyte interphase with favorable lithium-ion transport properties. By utilizing fluoroethylene carbonate as the medium for anode contact prelithiation, an Ah-level laminated Si/C||LiCoO2 pouch cell shows a significant enhancement in cell-level energy density by 42.7%. Moreover, a Si/C||LiCoO2 pouch cell achieves an 80.9% capacity utilization at a fast-charging rate of 10 C (6 min) and exhibits a low capacity decay rate of 0.047% per cycle. Such a prelithiation method demonstrates versatility across various cyclic carbonate mediums, electrodes, and scalability for industrial applications.

A Systematic Review and Meta-analysis Protocol on Depressive Symptoms Among Medical Students in South Asia Using Patient-reported Validated Assessment Tools: Prevalence and Associated Factors

Depression among medical students in South Asia is notably higher than the global average, with prevalence rates ranging from approximately 30% to 60%. Untreated depression not only affects individual student’s well-being, but also impacts academic performance and future clinical competence. This study protocol aims to synthesize evidence on the prevalence and associated factors of depressive symptoms among medical students in South Asia. The study will systematically navigate Medline (PubMed), Scopus, CINHAL, EMBASE, and APA PsycInfo for studies available before 1st May, 2025, following PRISMA guidelines for reporting and adhering to PRISMA-P standards for protocol development. The search will search for grey literature and adopt citation chain technique, using keyword truncation and string search along with standard indexing terms. Observational longitudinal studies, including cross-sectional, cohort studies, and case-control using validated patient-reported depressive symptoms measuring tools comprising South Asian medical students. Review articles, intervention studies, case reports, case series, commentaries, pre-prints, conference abstracts, protocols, unpublished research, and correspondences will not be considered. No language limitation will be applied. Two independent reviewers will screen studies, with disagreements resolved by a third reviewer. The study aims to extract information on prevalence and associated factors of depressive symptoms, conducting a narrative synthesis and meta-analysis using random effect models. Forest and funnel plots will be used to visualize findings, while heterogeneity will be assessed using the I2 statistic, with subgroup and sensitivity analysis performed to ascertain the robustness. Risk of bias (RoB) will be measured adopting the modified Newcastle-Ottawa Scale (mNOS). Statistical analysis will be conducted using R studio v.4.3.2 and GraphPad Prism v.9.0. Understanding the prevalence and risk factors is essential to guide targeted interventions and evidence-based policy reforms that support the mental well-being of future healthcare professionals. By systematically synthesizing data from observational studies, this review will provide a comprehensive synthesis of depressive symptoms, prevalence and its correlates among medical students in South Asian region, laying the groundwork for preventive strategies and improved mental health care practices.

A multifaceted strategy for intra- and extracellular nucleic acid regulation to alleviate intervertebral disc degeneration

Basketball detection based on YOLOv8

Accurate and timely detection of basketballs is crucial for ensuring fairness in games, enhancing the precision of data analysis, optimizing tactical planning for coaches, and improving the spectator experience. However, current basketball detection technologies face challenges such as variations in target scale, scene complexity, and changing camera angles, which limit automated systems’ accuracy and real-time performance. To address these issues, this study introduces a novel real-time basketball detection model, BGS-YOLO, incorporating several key innovations. First, the model integrates a BiFPN (Bidirectional Feature Pyramid Network) that enhances detection accuracy by efficiently merging feature maps across different resolutions, allowing for more effective feature extraction from basketball targets. Second, the Global Attention Mechanism (GAM) dynamically adjusts the model’s focus, optimizing feature attention in complex or partially occluded scenes, boosting recall in occluded scenarios by 3.2%, thereby improving localization precision. Finally, SimAM-C2f increases the model’s robustness in high-interference environments by calculating similarity features between the target and the background, reducing false positives by 15%, ensuring more reliable detection. Experimental results show that BGS-YOLO surpasses existing models across key metrics such as precision, recall, F1 score, and mean average precision (mAP), achieving a mAP of 93.2%. All improvements were statistically significant (p < 0.001). These advancements significantly enhance the accuracy and robustness of basketball detection, offering valuable technical support for intelligent sports analytics.