Mosquito-borne viruses (MBVs) remain a significant public health concern in Northern Queensland, Australia, with dengue virus (DENV), Ross River virus (RRV), and Barmah Forest virus (BFV) representing the most common pathogens. Wolbachia-based biological control programs have made notable contributions to reducing dengue transmission by suppressing Aedes aegypti vector competence. Recent surveillance data indicates increased MBV activity, with national case numbers nearly doubling between 2023 and 2024 and early 2025 data suggesting sustained transmission during seasonal peak. Traditional surveillance approaches, while highly valuable for disease monitoring, have limitations in detecting novel or divergent viral strains in real time. Over the past decades, more than 919 unclassified flaviviruses have been reported nationwide, including 117 in Queensland. The advent of metagenomic and metatranscriptomic approaches now enable enhanced, field-based detection of both known and emerging arboviruses. Strengthening mosquito control programs through continued Wolbachia releases, alongside integrated genomic surveillance, predictive modelling, and community engagement will enhance early detection, guide targeted interventions, and reduce the MBV burden in Northern Queensland. This integrated framework provides a strategic pathway to sustains and expand vector control effectiveness while safeguarding public health in high-risk regions.

Interferon-γ-responsive theranostic nanoplatform for adaptive antibacterial therapy.

This article reports on the item construction of a new screening scale to measure coping and communication among adolescents with a parent enrolled in hospice. The aim of this study was to use cognitive interviewing methodology to determine the validity and reliability of the Adolescent Coping and Communication Scale (ACCS). The young adults in this study identified the need for a consistent point person on the hospice care team to discuss their concerns and provide information and support. The ACCS is a concise 15-question tool using a 5-point Likert scale to monitor the adolescent's coping and communication needs in real time. It can easily be formatted electronically or in paper format and completed in less than 10 minutes. It can be used as a clinical screening tool by health professionals who seek to help adolescents navigate this critical time when their parent is near the end of life. These results can also be used to inform the development of interventions that assist families with strategies tailored to an adolescent's specific needs. Additional research is needed to assess the psychometric properties of scale items. Future research should investigate the use of this tool in other age groups and populations.

Optimization of drug diffusion in drug-eluting stents for coronary artery based on deep reinforcement learning.

Major Depressive Disorder (MDD) is one of the most prevalent psychological disorders and frequently co-occurs with alcohol use disorders, increasing the risk of functional impairment. Monitoring alcohol use during depression treatment is therefore critical for early intervention. Passively collected data via devices like smartphones and smartwatches, offers a low-burden method for monitoring behavior in real time. This study investigated whether deep learning models trained on passively collected data (i.e., accelerometer, heart rate, respiratory rate, screen usage, and GPS data) could detect and predict alcohol use in individuals with MDD. Data were collected from 300 clinically depressed individuals who were enrolled in the Tracking Depression Study, a 90-day longitudinal study. Participants self-reported their alcohol use every week by completing the Timeline FollowBack. We trained models to predict same-day and next-day alcohol use. To validate these models, we split the data by participant, so that predictions were made on individuals who were not included in the training set. The models achieved moderate performance (mean AUC = 0.67 for both prediction tasks) when capturing both interindividual (between-person) and intraindividual (within-person) variability. Similar performances were observed when evaluating the model exclusively on predicting intraindividual variability (AUCs=0.69 same-day, 0.68 next-day). However, model performance remained comparable to a baseline using only the day of week as predictor. These findings suggest that much of the predictive signal derives from temporal patterns. This indicates that interventions aligned with such temporal cues may already be effective, and that the added value of our model appears limited.

AI-driven detection of metal contaminants in construction and demolition wood waste for enhanced valorisation.

FRET/SAXS integration reveals the digestion-absorption trade-off driven by dynamic self-assembly of human milk triacylglycerols.

The ability to continuously monitor key biomarkers is crucial for advancing personalized medicine and enabling early disease intervention. Potassium ions (K+) play a vital role in neural signaling, cardiac function, and sensory processing, particularly in the cochlea, where potassium imbalances are linked to disorders such as Ménière's disease. However, existing diagnostic methods cannot monitor K+ in the inner ear in real time, limiting insight into the ionic mechanisms that underlie auditory function and related disorders. This study presents a miniaturized potassium-selective biosensor, incorporating a stable reference electrode, for continuous and real-time monitoring of K+ dynamics in the inner ear. The sensor underwent extensive benchtop validation, demonstrating high sensitivity (⁓52.8 mV/dec), a broad linear range (10-5-10-1mol/L), a limit of detection of 10-5·16mol/L, strong selectivity coefficients (-2.62 for Na+, -4.10 for Mg2+, and -3.85 for Ca2+), and excellent stability over two months. In-vivo experiments in a guinea pig model confirmed the biosensor's capability to track dynamic potassium fluctuations under physiological conditions, such as responses to controlled potassium administration. These findings establish the feasibility of real-time K+ monitoring in the cochlea, providing a valuable tool for studying auditory physiology, understanding potassium regulation in the inner ear, and advancing targeted diagnostics and treatments for inner ear disorders.

Real time PCR-based evaluation of live attenuated lumpy skin disease virus vaccines for immunogenicity and efficacy.

Systematic evaluation and hepatic targeting of a dual-fluorescence icaritin microemulsion: elucidating the protein corona-mediated delivery mechanism.

Current trend on preparation, properties, and wound healing applications of polysaccharide-based hydrogel patches: A review.

Design, validation and evaluation of a triplex real time qualitative PCR assay targeting zoonotic Capnocytophaga species in EDTA whole blood and plasma simulated clinical specimens.

Multi-Node real time control for pressure regulation and energy recovery in water distribution networks using Pump-as-Turbines

On site operation of a real time measurement system for monitoring transient currents through line surge arresters

Current diagnostic workup for infectious uveitis relies on the use of various immunoassays and polymerase chain reaction (PCR) tests on ocular fluids that are time consuming and not comprehensive, requiring large sample volumes to probe for all causes. To streamline the diagnostic process, improve turnaround time, and target inclusivity, we developed a highly multiplexed pan-ocular-pathogen panel (OcuPan) that can be used for broad-range pathogen detection in only 1 assay, with PCR-level sensitivity and in a timely fashion (12 hours). Here, we assessed the clinical usefulness and performance of this innovative assay as a novel tool for rapid and accurate laboratory diagnosis of infectious uveitis. Laboratory evaluation of a novel diagnostic test and technology PARTICIPANTS AND CONTROLS: A total of 109 patients from 2 centers were included, including 78 infectious uveitis cases and 31 controls. Intraocular samples (n = 108 from patients and 43 from controls) were processed by PCR and the OcuPan diagnostic assay that detects 46 ocular pathogens plus 2 resistance/virulence markers. Clinical sensitivity and specificity, quantification capabilities, and agreement between PCR and the OcuPan assay. The clinical sensitivity and specificity of the OcuPan assay were 50.9% (95% CI, 41.3-60.5) and 100% (95% CI 89.7%-100%), respectively. Sensitivity varied according to the sample matrix tested, with undiluted vitreous having the highest positivity rates (72.4%, 95% CI 55.1-89.7), followed by dilute vitreous (53.3%, 95% CI 34.4-72.3) and aqueous (36.7%, 95% CI 22.7-50.7). There was excellent overall agreement (93.5%) between the OcuPan assay and PCR (kappa of 0.870 ± 0.047; P < .001) with positive (PPA) and negative (NPA) percentage agreements >92% for all targets. PPA was 100% for herpesviruses and Treponema pallidum, whereas the NPA values ranged from 96.6% to 100% for these pathogens. For Toxoplasma gondii, the PPA was 75% and NPA 100%. We also found significant correlation (Spearman ρ = -0.7506, P < .0001) between the quantitative metric for the OcuPan assay and the real-time PCR cycle threshold values. The OcuPan assay offers an all-in-one highly multiplexed detection system for rapid, comprehensive, quantitative, and accurate diagnosis of infectious uveitis.

Machine vision defect segmentation and geometric measurement for real time quality monitoring in friction stir welding

Ketogenic diet attenuates high fat diet induced obesity in rats: insights into hepatic and intestinal tissues.

Patagonian shellfish and hidden threats: unveiling the viral landscape and the first quantitative microbial risk assessment of Argentine bivalve mollusks.

Fluorescence-guided surgery (FgS) is increasingly used across oncologic specialties to enhance intraoperative visualisation of tumour tissue and lymphatic drainage; however, its clinical impact remains limited by heterogeneous tracer uptake, variable signal intensity, and reliance on subjective visual interpretation, leading to inter-operator variability, uncertainty at tumour margins, residual disease, and inconsistent nodal assessment. This narrative review examines the role of artificial intelligence (AI) in addressing these limitations, synthesising evidence published between January 2000 and December 2025 across neuro-oncology, gynaecological oncology, and thoracic oncology. In neuro-oncology, early clinical and preclinical studies have directly evaluated real-time AI-enhanced interpretation of intraoperative fluorescence, including quantitative analysis of 5-aminolevulinic acid (5-ALA) and hyperspectral imaging, providing proof-of-concept evidence that AI can augment margin detection beyond subjective visual assessment. In contrast, gynaecological and thoracic oncology currently lack validated studies in which AI directly interprets intraoperative fluorescence signals, despite fluorescence imaging being clinically established in both fields; instead, AI development in these specialties has progressed primarily in adjacent domains such as radiomics, digital pathology, risk stratification, surgical planning, and intraoperative computer vision, demonstrating technical maturity but limited integration into fluorescence-guided decision-making. Overall, the available evidence supports proof-of-concept feasibility for real-time AI-enhanced fluorescence interpretation in neuro-oncology, while identifying a clear translational gap in gynaecological and thoracic oncology that warrants targeted research to integrate existing AI capabilities into intraoperative fluorescence-guided surgery.

Background: Spontaneous bacterial peritonitis (SBP) is a severe and possibly life-threatening consequence in patients with liver cirrhosis and ascites. Standard diagnostic tools such as ascitic fluid culture often suffer from low sensitivity with delayed results. Real-time polymerase chain reaction (RT-PCR) as a more rapid and sensitive molecular diagnostic technique has been developed to identify bacterial DNA in ascitic fluid. Objective: To evaluate the role of real-time PCR in the diagnosis of spontaneous bacterial peritonitis, compared to ascitic fluid vial culture. Methodology: This research was designed as a diagnostic cross-sectional study. Spontaneous bacterial peritonitis was identified using both blood culture bottles and real-time PCR techniques. The study population included 68 male and 32 female patients aged between 45 and 60 years, all in different stages of hepatic cirrhosis with ascites (mild, moderate, and severe), and exhibiting acceptable hematological and biochemical parameters. Results: Real-time PCR targeting 16s rRNA demonstrated much higher sensitivity, detecting bacterial DNA in 85% of patients, including many who had negative culture results. There was a statistically significant difference between PCR positive and negative patients regarding WBC count, AST, CRP, ascitic fluid albumin, and SAAG levels, while a significant difference was also observed between culture positive and negative patients regarding ascitic fluid total leukocytic count and neutrophil count (P-value <0.05). Conclusion: PCR testing of ascitic fluid using 16s rRNA is a more sensitive and accurate diagnostic tool compared to conventional culture. While culture detected bacterial growth in just over half of the patients, PCR was able to identify bacterial DNA in the majority of cases, including those with negative culture results.