Browse Articles
Discover research articles across all indexed journals
Multimodal super-resolution: discovering hidden physics and its application to fusion plasmas
The consequences of traditional cervical cauterization on cervical integrity and pregnancy: a cross-sectional study
CD137L promotes immune surveillance in melanoma via HLTF regulation
Multiomics Mendelian randomization integrating pQTL, eQTL and mQTL data revealed BTN3A2 as a potential drug target for nephrolithiasis
Decoding structural transitions from CdSe nanoclusters to quantum dots through dynamic nuclear polarization NMR
Energy additivity as a requirement for universal quantum thermodynamical frameworks
Noise-induced quantum synchronization with entangled oscillations
Abstract Random fluctuations can lead to cooperative effects in complex systems. We here report the observation of noise-induced quantum synchronization in a chain of superconducting transmon qubits with nearest-neighbor interactions. The application of Gaussian white noise to a single site leads to synchronous oscillations in the entire chain. We show that the two synchronized end qubits are entangled, with nonzero concurrence, and that they belong to a class of generalized Bell states known as maximally entangled mixed states, whose entanglement cannot be increased by any global unitary. We further demonstrate the stability against frequency detuning of both synchronization and entanglement by determining the corresponding generalized Arnold tongue diagrams. Our results highlight the constructive influence of noise in a quantum many-body system, and initiate the exploration of collective synchronization effects with stronger than classical correlations.
A computational dive into tuning nitrosourea adsorption on T-graphene nanosheets
Spurious precision in meta-analysis of observational research
Abstract Meta-analysis assigns more weight to studies with smaller standard errors to maximize the precision of the overall estimate. In observational settings, however, standard errors are shaped by methodological decisions. These decisions can interact with publication bias and p-hacking, potentially leading to spuriously precise results reported by primary studies. Here we show that such spurious precision undermines standard meta-analytic techniques, including inverse-variance weighting and bias corrections based on the funnel plot. Through simulations and large-scale empirical applications, we find that selection models do not resolve the issue. In some cases, a simple unweighted mean of reported estimates outperforms widely used correction methods. We introduce MAIVE (Meta-Analysis Instrumental Variable Estimator), an approach that reduces bias by using sample size as an instrument for reported precision. MAIVE offers a simple and robust solution for improving the reliability of meta-analyses in the presence of spurious precision.
Automated differentiation of acute encephalopathy with biphasic seizures and late reduced diffusion and prolonged febrile seizures in acute phase
RAPDOR: Using Jensen-Shannon Distance for the computational analysis of complex proteomics datasets
Abstract The computational analysis of large proteomics datasets from gradient profiling or spatially resolved proteomics is often as crucial as experimental design. We present RAPDOR, a tool for intuitive analyzing and visualizing such datasets, based on the Jensen-Shannon distance and analysis of similarities between replicates, applied to the identification of RNA-binding proteins (RBPs) and spatial proteomics. First, we examine the in-gradient distribution profiles of protein complexes with or without RNase treatment (GradR) to identify RBPs in the cyanobacterium Synechocystis 6803. RBPs play pivotal regulatory and structural roles. Although numerous RBPs are well characterized, the complete set of RBPs remains unknown for any species. RAPDOR identifies 165 potential RBPs, including ribosomal proteins, RNA-modifying enzymes, and proteins not previously associated with RNA binding. High-ranking putative RBPs, such as ribosome hibernation factor LrtA/RaiA, phosphoglucomutase Sll0726, antitoxin Ssl2245, and preQ(1) synthase QueF predicted by RAPDOR but not the TriPepSVM algorithm, are experimentally validated, indicating the existence of uncharacterized RBP domains. These data are available online, providing a resource for RNase-sensitive protein complexes in cyanobacteria. We then show by reanalyzing existing datasets that RAPDOR effectively examines the intracellular redistribution of proteins upon growth factor stimulation. RAPDOR is a generic, non-parametric tool for analyzing highly complex datasets.
Antioxidant and anticancer properties of citrus-mediated nanoformulations revealed by meta-analysis
Abstract This study aims to explore and analyse the potential antioxidant and anticancer potential of various citrus-mediated nanoformulations (CMNs), focusing on their effectiveness in scavenging free radicals and inducing cytotoxicity in cancer cells. This research employs a meta-analysis approach to assess data from multiple studies on CMNs. This study is the first meta-analysis to evaluate the antioxidant and anticancer properties of CMNs concurrently. This study offers a novel perspective by examining citrus species, plant parts utilised, nanoparticle types, particle sizes, and coating materials. The analysis employs the Population, Intervention, Comparison, and Outcome (PICO) framework and complies with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The analysis utilizes Hedges’ effect size and includes validation through fail-safe N. The IC50 evaluation (µg/mL) revealed a significant effect of CMNs on antioxidant activity (d++ = 3.49; P < 0.05). The IC50 value of 3.49 in the CMN indicates that a lower concentration is sufficient to inhibit 50% of the free radical activity, reflecting a stronger antioxidant potential than that of the control group. However, the overall antioxidant assay results (d++ = 0.2; P = 0.309) and radical inhibition (%) for CMNs (d++ = 0.1; P = 0.602) did not significantly differ. Subgroup analysis provided further insights, showing that both citrus peel and polyvinyl alcohol significantly reduced IC50 values (d++ >1; P < 0.05). In addition, radical inhibition significantly increased in CMNs derived from Citrus paradisi (d++ = 3.05; P = 0.015), followed by those derived from Citrus limon (d++ = 2.25; P < 0.01) and Citrus reticulata (d++ = 1.03; P = 0.025). Various types of nanoformulations, such as Ag chitosan-NP (silver nanoparticle with chitosan), Ag-NP (silver nanoparticles), cerium dioxide nanoparticle (CeO₂-NPs), hydrogel-based nanocomposite (Hydrogel-NPCs), pectin-based nanoemulsion (Pectin-NPEs), titanium dioxide nanoparticle (TiO₂-NP), and whey-based nanoemulsion (Whey-NPEs), also significantly enhanced free radical scavenging activity (d++ >1; P < 0.01). In terms of anticancer activity, CMN has a strong effect size (|d++| >1; P < 0.05), with species such as Citrus macroptera and plant parts such as juice showing highly positive effects (d++ = 2.25; P < 0.001). Additionally, nanoparticles with sizes between 101 and 500 nm exhibited significant effectiveness (d++ = 2.26; P < 0.001). These findings indicate that citrus-derived compounds have potential as anticancer agents by actively enhancing the antioxidant capacity of healthy cells. The significant antiproliferative activity observed across multiple cancer cell lines, supported by robust statistical analyses, demonstrates the potential of CMNs as a natural therapeutic approach for cancer prevention and treatment.
MXene-configured graphite towards long-life lithium-ion batteries under extreme conditions
Detection of PEG-specific antibodies in SARS-CoV-2 positive and negative sera with implications for autoimmune reactivity
Impacts of urban and cropland expansions on natural habitats in Southeast Asia
Mass fabrication of PDMS microfluidic devices by injection molding and applications in sensitive 3D spheroid and explant culture
Advances in biomonitoring technologies for women’s health
Abstract In global healthcare systems, sex and gender biases have favored cisgender males, which has led women and transgender individuals to be understudied and underrepresented in medical literature. Thus, these populations are largely overlooked in health policy making. Persistent gender inequalities, socioeconomic divides, and racial-ethnic discrimination, particularly in low-resource communities, have exacerbated women’s health concerns, delaying advancements in care and accessibility. However, recent years have seen the emergence of tracking technologies and wearable devices that enable long-term biomonitoring of key health biomarkers which promise to facilitate early disease diagnosis for women from all walks of life. These innovations value education and accessibility, which can break down barriers to health care access and management that has affected generations of women around the world. This review discusses emerging biomonitoring technologies for diagnosing and managing critical women’s health conditions as defined by the World Health Organization, including breast and gynecological cancers, vaginal infections, fertility, pregnancy and post-menopausal osteoporosis. Additionally, we examine the current commercial landscape of women’s health technologies, highlighting barriers to adoption, such as medical insurance access and socioeconomic status, as well as discuss opportunities for future innovation.