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Molecular Interactions of Fluoroquinolone Antibiotics with Lipid Membranes
Full text linkLevofloxacin is a broad-spectrum fluoroquinolone antibiotic in clinical use that targets DNA gyrase in the cytosol. It is used in systemic applications via oral or intravenous route, and its pharmacokinetics and access to its molecular targets are strongly influenced by interactions with cellular membranes. We used NMR and MD simulations to investigate the physical state of levofloxacin in solution and its interactions with lipid membranes, assessing the role of membrane charge and antibiotic concentration. Using zwitterionic DOPC and negatively charged DOPC/DOPG lipid membranes, we observe concentration-dependent self-association of levofloxacin in solution below its solubility limits and association with lipid membranes with a preference for negatively charged bilayers. Below the solubility limit, levofloxacin solutions that appear clear contain self-associated molecular assemblies in fast exchange equilibrium with a monomeric soluble population. In the presence of lipid membranes, this equilibrium is shifted in favor of a membrane-associated population with preference for negative lipids. MD simulations show levofloxacin condensation in solution and fractional membrane insertion, which suggest the presence of a molecular population embedded in the lipid bilayer, coexisting with self-associated levofloxacin molecular "droplets" in exchange with a solvated population
A partially pooled network scale-up method model: detailed estimation of child sexual exploitation material trafficking prevalence in Philippine municipalities
Full text linkEffective policy and intervention strategies to combat human trafficking for child sexual exploitation material (CSEM) production require accurate prevalence estimates. Traditional network scale-up method (NSUM) models often necessitate standalone surveys for each geographic region, escalating costs, and complexity. This study introduces a partially pooled NSUM model, using a hierarchical Bayesian framework that efficiently aggregates and utilizes data across multiple regions without increasing sample sizes. We developed this model for a novel national survey dataset from the Philippines and we demonstrate its ability to produce detailed municipal-level prevalence estimates of trafficking for CSEM production. Our results not only underscore the model’s precision in estimating hidden populations but also highlight its potential for broader application in other areas of social science and public health research, offering significant implications for resource allocation and intervention planning
The effects of prophylactic use of paracetamol on body temperature and blood pressure in elderly patients with acute stroke: Data from the PRECIOUS trial
Full text linkBackground and aims Prophylactic administration of paracetamol (acetaminophen) has been reported to reduce body temperature in the first day after stroke and to reduce blood pressure on the first day. We aimed to validate these findings in the randomised PRECIOUS trial and to assess the effect of paracetamol on body temperature in the first seven days after stroke. Patients and methods PRECIOUS was an international, 3*2 factorial, randomised, controlled, clinical trial assessing preventive treatment with paracetamol, metoclopramide, and ceftriaxone in patients aged 66 years or older with acute stroke and a score on the National Institutes of Health Stroke Scale (NIHSS) ≥ 6. Paracetamol was given in a dose of 4g daily for four days. Vital signs were recorded at 12 hours intervals up to seven days. The primary outcomes of this study were body temperature and systolic and diastolic blood pressure at 24 hours after randomisation, analysed with linear regression. The presence of a subfebrile temperature or fever at 24 hours was a secondary outcome. Results We used data from 1419 of 1493 patients included in PRECIOUS. Paracetamol reduced mean body temperature by 0.1°C (95% CI, 0.0–0.2) at 24 hours after randomisation but did not lower systolic or diastolic blood pressure. Paracetamol reduced the occurrence of subfebrile temperatures or fever at 24 hours from 15.8% to 8.3% (p<0.001). The effects of paracetamol on body temperature were consistent over the four days of treatment. Conclusion Prophylactic use of paracetamol resulted in a modest reduction in mean body temperature and almost halved the rate of subfebrile temperatures or fever at 24 hours after stroke, but had no effect on blood pressure
Human Decision-Making in Crowds in a Virtual Flood Scenario
Full text linkFlood evacuation outcomes are critically shaped by human behaviour, yet empirical data on individual decision-making remain scarce due to the dangers and logistical challenges of collecting data during real natural hazards. To address this gap, this study used Virtual Reality (VR) to examine how social cues, specifically crowd behaviour, interact with factors such as crowd size, clarity of the safe destination, and floodwater level to influence evacuation choices and delays. Four within-subjects VR experiments were conducted with 84 participants, systematically testing these variables in an immersive flood scenario. Results showed that crowd behaviour strongly determined both route choice and evacuation latency, often outweighing other factors. Participants tended to follow crowds into floodwater, demonstrating the influence of social information. However, this influence weakened when water levels were very high, indicating a threshold overrides social cues. Larger crowds and unclear destination information further increased reliance on social information and pre-movement times. These findings highlight the powerful role of social dynamics in emergency decision-making and underscore the need to integrate realistic human behaviour, particularly social influence, into flood risk models, public warnings, and evacuation planning to improve community resilience and safety
Dual Direct Matrix Converter-Based Drives With Enhanced Input Power Factor Control and Common-Mode Voltage Elimination
Full text linkThe demand for high-efficiency, compact, and power-dense ac–ac conversion is driving renewed interest in matrix converters for industrial and renewable energy applications. This article introduces a novel input power factor (IPF) control strategy for a dual direct matrix converter (DMC)-based drive, enabling independent control of IPF while mitigating common-mode voltage (CMV) without additional hardware. Unlike conventional approaches that inherently constrain the reactive power control range, the proposed method extends IPF control to absolute maximum ratings, unlocking unprecedented flexibility in grid-interfacing applications. A fully decoupled approach to output voltage synthesis and IPF control is demonstrated by leveraging a generalized complex-domain model, ensuring optimal control across varying load conditions. Experimental validation is conducted on a dual DMC prototype, verifying the superior performance of the proposed method. The results highlight an expanded IPF control range and elimination of high-frequency CMV, positioning this methodology as a disruptive advancement in matrix converter technology
Evidence of cancer: a systematic review of metabolomics in extracellular vesicles for cancer biomarker detection
Full text linkBackground: The early detection of cancer remains a critical challenge in clinical oncology, with significant implications for patient survival rates and treatment outcomes. Research focus has shifted to developing minimally invasive diagnostic approaches for cancer detection and prognosis, such as metabolomic analysis of biological fluids and tumour-derived components, including extracellular vesicles (EVs). EVs carry molecular cargo, including metabolites, that reflect the pathophysiological state of their cell of origin. Analysis and characterisation of these metabolites may offer novel insights into cancer biology and facilitate the identification of potential biomarkers. Aim of review: This review systematically examines existing literature on the metabolomic analysis of EVs in the context of cancer to obtain a deeper understanding of potential metabolite biomarkers associated with cancer. Key scientific concepts of review: A comprehensive search of PubMed, Scopus, and Web of Science was conducted using a defined strategy to identify studies analysing EV-derived metabolites in cancer. Twelve eligible studies were included, collectively reporting 1,602 identified metabolites across various cancer types, sample sources, EV isolation methods, and metabolomic techniques. Of these, 333 metabolites were reported to be differentially regulated in EVs derived from patients with cancer, or conditioned medium from cancerous cell lines and their respective healthy controls. The review highlights the potential of EV metabolomics to detect cancer biomarkers but also underscores methodological variability as a major limitation. Differences in isolation and analytical techniques likely contribute to inconsistent findings, emphasising the need for standardised protocols in future research
Effectiveness of mandated approaches to increasing board independence in achieving intended governance outcomes: Professional investors' perspective
No full textDrawing on interviews with 27 professional investors and proceeding from a resource dependence theoretical lens, this study investigates how professional investors perceive the effectiveness of mandated approaches to increasing board independence in achieving intended governance goals in the Nigerian banking sector. We inductively identify three distinct effectiveness categories for board independence approaches: quixotic, symbolic, and practical. We further unpack seven contextual factors that influence these perceptions, namely person-specific utility; board cronyism; loss of independence over time; disconnection with business realities despite their technical competence; non-executive directors’ (NEDs’) concern for business survival; NEDs’ subservience to the major shareholder; and NEDs’ reputational standing. We provide insights that demonstrate that the mandated approaches to increasing board independence are not universally effective in achieving intended governance goals and must instead be evaluated within their institutional and contextual realities
Investigation of hybrid desiccant microencapsulated phase change material (HYB-D-MPCM) for dehumidification and cooling
Full text linkIn desiccant cooling systems, the dehumidification component plays a vital role, as its performance directly affects the overall coefficient of performance (COP). However, the moisture adsorption process is inherently exothermic, releasing heat that increases the sensible load and reduces the cooling efficiency, particularly in hot and humid climates. Conventional desiccant cooling systems often face this limitation because the heat released during moisture removal raises the air temperature, adding to the sensible cooling demand and lowering the effectiveness of the system. This study investigates a novel composite material, a hybrid solid desiccant with microencapsulated phase change material (HYB-D-MPCM) which is designed to enhance moisture removal while mitigating heat build-up through latent heat absorption. The composite was prepared via wet physical mixing with varying MPCM content and evaluated through preliminary screening of the adsorption–desorption performance, supported by statistical analysis, followed by the investigation of two air filter configurations, namely the HYB-D-MPCM block and the HYB-D-MPCM granules. The best configuration was then selected and TRNSYS simulations were performed to assess performance in an office building under hot and humid climate conditions. From preliminary investigation, the results showed that the HYB-D-MPCM granules achieved superior dehumidification, with an absolute humidity reduction of 2.86 g/m3 and the lowest total enthalpy of 0.187 kW, outperforming both the block form and the traditional silica gel due to increased heat and mass transfer. TRNSYS simulations further demonstrated that the HYB-D-MPCM granules can reduce latent loads by up to 40% without the typical sensible heat penalty associated with conventional desiccant cooling systems. Although this study focusses on dehumidification performance, future work should explore regeneration and discharge behaviour under real operating conditions. These findings provide a strong foundation for the continued development of efficient desiccant-PCM materials tailored for hot and humid climates
Extracellular-Matrix-Based Materials from Decellularized Tissue: Opportunities, Challenges, and Future Directions in Regenerative Medicine
Full text linkExtracellular matrix (ECM) biomaterials have been used as inductive scaffolds to promote tissue regeneration in a variety of clinical applications. ECM biomaterials derived from decellularized tissue (dECM) can retain essential bioactive components of the native ECM that can guide cellular processes; however, the composition and bioactivity of the dECM is highly dependent on the decellularization and postprocessing methods. This intrinsic regenerative potential underpins the clinical success of dECM biomaterials in applications including soft tissue repair, cardiac reconstruction, and urological interventions. Here, clinical use of current dECM biomaterials, advances in the fabrication of dECM biomaterials, and hurdles to clinical translation of dECM products are discussed. Clinical use to date has mostly been limited to native dECM sheets or milling to generate powder dECM. Recent advances in fabrication methods from electrospinning to 3D printing have expanded the potential clinical applications of dECM biomaterials by increasing the structural and compositional complexity available to researchers. Despite significant progress, challenges remain in standardizing decellularization processes, optimizing dECM bioactivity retention, and ensuring mechanical compatibility with native tissues. Future research should focus on refining fabrication techniques and establishing standardized criteria for dECM characterization and translational pathways
pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits
Full text linkBackgroundRoot hairs play a key role in plant nutrient and water uptake. Historically, root hair traits have largely been quantified manually. As such, this process has been laborious and low-throughput. However, given their importance for plant health and development, high-throughput quantification of root hair morphology could help underpin rapid advances in the genetic understanding of these traits. With recent increases in the accessibility and availability of artificial intelligence (AI) and machine learning techniques, the development of tools to automate plant phenotyping processes has been greatly accelerated.ResultsWe present pyRootHair, a high-throughput, AI-powered software application to automate root hair trait extraction from microscope images of plant roots grown on agar plates. pyRootHair is capable of batch processing over 600 images per hour without manual input from the end user. In this study, we deploy pyRootHair on a panel of 24 diverse wheat (Triticum aestivum and Triticum turgidum ssp. durum) cultivars and uncover a large, previously unresolved amount of variation in many root hair traits. We show that the overall root hair profile falls under 2 distinct shape categories and that different root hair traits often correlate with each other. We also demonstrate that pyRootHair can be deployed on a range of plant species, including oat (Avena sativa), rice (Oryza sativa), teff (Eragrostis tef), and tomato (Solanum lycopersicum).ConclusionsThe application of pyRootHair enables users to rapidly screen a large number of plant germplasm resources for variation in root hair morphology, supporting high-resolution measurements and high-throughput data analysis. This facilitates downstream investigation of the impacts of root hair genetic control and morphological variation on plant performance. pyRootHair is installable via PyPI (https://pypi.org/project/pyRootHair/) and can be accessed on GitHub at https://github.com/iantsang779/pyRootHair
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