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Daily briefing: CRISPR gets an AI-designed upgrade
In vitro and in vivo evaluation of antioxidant activity, acute toxicity, and antihyperglycemic effect of individual and binary mixtures of crude methanolic extracts of Cucurbita moschata and Bidens pilosa
Background Bidens pilosa (BP) and Cucurbita moschata (CM) are used to treat diabetes traditionally. Little is known scientifically about the toxicity and efficacy of the individual or binary mixtures on blood-sugar-lowering effects. Hence, this study carried out toxicity studies and examined the antidiabetic effects of these plants to support traditional knowledge. We report the phytochemical composition, total phenolic (TPC), flavonoid content (TFC), and antioxidant activity of individual and mixed methanolic BP and CM leaf extracts. We also report acute toxicity of the individual extracts. This study is the first to investigate the antidiabetic effects of a combined BP and CM leaf extract in alloxan-induced diabetic mice. Aim The study aimed to determine toxicity and the blood-glucose-lowering effects of individual and combined mixtures of BP and CM on alloxan-induced diabetic mice. Materials and Methods Acute toxicity of the extracts was assessed through the LD 50 assay in rats after oral administration. TFC was measured using a modified aluminium chloride colourimetric method, while TPC was measured using the Folin-Ciocalteau’s method. The antioxidant activity was analysed using the Ferric Reducing Antioxidant Power (FRAP) method, 2,2-diphenyl-1-picrylhydrazyl (DPPH), and hydrogen peroxide radical scavenging assay. We investigated the antihyperglycemic effect of the extracts by measuring their blood-glucose-lowering effect in alloxan-induced diabetic mice. Results No mortality or significant behavioural changes were observed at doses up to 10,000 mg/kg, suggesting a high safety margin for the two plants under study. Oral administration of the combined leaf extract of BP and CM in the ratios of 1:1, 1:2, and 2:1 w/w % showed that the BP: CM (1:2) extract at the concentration of 500 mg/kg significantly reduced blood glucose levels from 17.2 ± 0.15 mmol/L to 3.9 ± 0.04 mmol/L. The positive control, glibenclamide (5 mg/kg), reduced blood glucose levels from 17.0 mmol/L to 4.1 mmol/L, respectively (p < 0.0001). Conclusion In vivo results of this study suggest that a combined leaf extract of B. pilosa and C. moschata may provide glucose-lowering effects as seen in mice though this is yet to be tested in humans. In addition, the extract may provide a nutritional source among Zambians. Acute toxicity results suggest that C. moschata and B. pilosa extracts are essentially safe, supporting their use as food and a potential source of nutraceuticals.
Found: a rocky exoplanet with an atmosphere — could it host life?
Computing the Skyline Query over a k2-tree compact data structure
This study aims to explore the feasibility of executing Skyline Queries—used to identify optimal data points based on multiple criteria—within compact data structures. While existing algorithms typically operate on plain or indexed datasets, this work investigates how such queries can be efficiently resolved using compact representations. We focus on implementing two Skyline Query variants, Constrained Skyline Query and Enumerating Skyline , within the k 2 -tree compact data structure. Our approach leverages the k 2 -tree’s inherent indexing capabilities to evaluate these queries directly on compressed data, avoiding the need for decompression. The results demonstrate that the k 2 -tree structure effectively supports both types of Skyline Queries. Our experimental evaluation shows improved resource utilization compared to non-indexed methods, confirming that compact data structures can process these queries efficiently without data inflation. This article presents a comprehensive study of implementing skyline queries directly over compact data structures—specifically the k 2 -tree, supported by extensive experimental evaluation and a complete theoretical analysis of the proposed algorithms.
Can giant space mirrors boost green energy on Earth? A start-up aims to find out
Blood urea nitrogen to albumin ratio and mortality in critically ill patients with cardiogenic shock
Purpose Given the high mortality associated with cardiogenic shock (CS), this study aimed to evaluate the association between the blood urea nitrogen-to-albumin ratio (BAR) and mortality in critically ill patients with CS. Patients and methods The data of this retrospective study were extracted from the Medical Information Mart for Intensive CARE-IV (MIMIC-IV v2.2) database. Patients who were diagnosed with CS were included as the study population. The primary outcome was one-year mortality, and secondary outcomes included in-hospital mortality and ICU mortality. Cox regression models were used to estimate the association between BAR and mortality.The prognostic value of BAR was assessed using the time-dependent area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results A total of 1,177 patients were enrolled in the study. After adjustment for covariates, BAR was associated with one-year mortality (HR: 1.02 [1.01–1.03], P < 0.001 per 1-unit increase). Compared with the low-BAR group, the medium- and high-BAR groups showed higher risks of one-year mortality (medium group: HR 1.30 [1.02–1.66], P = 0.034; high group: HR 1.75 [1.32–2.33], P < 0.001). Similar associations were observed for in-hospital mortality (per 1-unit increase: HR 1.02 [1.01–1.04], P < 0.001; high vs. low group: HR 1.51 [1.08–2.13], P = 0.017) and ICU mortality (per 1-unit increase: HR 1.02 [1.01–1.04], P < 0.001; high vs. low group: HR 1.67 [1.17–2.40], P = 0.005). E‑value analysis suggested robustness to unmeasured confounding. BAR demonstrated favorable discriminative ability, with a time‑dependent AUC of 0.612 and a Harrell’s C‑index of 0.607. When combined with existing prognostic indicators, BAR significantly improved prognostic accuracy. Conclusion In this study, higher BAR levels were associated with increased mortality in CS patients. BAR provided incremental prognostic value when combined with existing indicators.
What topological and geometric structure do biological foundation models learn? Evidence from 141 hypotheses
When biological foundation models like scGPT and Geneformer learn to process single-cell gene expression, what kind of geometric and topological structure forms in their internal representations? Is that structure biologically meaningful, or merely an artifact of training?. We address these questions through autonomous large-scale hypothesis screening: an AI-driven executor–brainstormer loop that proposed, tested, and refined 141 geometric and topological hypotheses across 52 iterations, covering persistent homology, manifold distances, cross-model alignment, community structure, directed topology, and more—all with explicit null controls and disjoint gene-pool splits. Three principal findings emerge. First, the models learn genuine geometric structure: gene embedding neighborhoods exhibit non-trivial topology (persistent homology significant in 11/12 transformer layers at p < 0.05 even in the weakest domain, and 12/12 in the other two), a multi-level distance hierarchy where manifold-aware metrics outperform Euclidean distance for identifying regulatory gene pairs, and graph-community partitions that track known transcription factor–target relationships. Second, this structure is shared across independently trained models: CCA alignment between scGPT and Geneformer yields canonical correlation of 0.80 and gene retrieval accuracy of 72%—yet no method among 19 tested could reliably recover gene-level correspondences, revealing that the models agree on the “shape” of gene space but not on precise gene placement. Third, the structure is more localized than it first appears: under the most stringent null controls (simultaneous auditing against all null families), robust signal concentrates in immune tissue, while lung and external-lung signals become fragile. These results—especially the carefully documented negatives among 141 hypotheses—calibrate what we can and cannot extract from biological model geometry, and demonstrate how autonomous screening can efficiently map the boundary between real structure and statistical artifact.
The epidemiology of the viral hepatitis in Brazil: A scoping review
Background Brazil has advanced toward eliminating viral hepatitis by 2030 through broad prevention, diagnosis, and treatment policies. Yet substantial gaps persist across the care continuum, especially in vulnerable populations and underserved regions. This scoping review synthesizes nationwide epidemiologic patterns and identifies knowledge gaps to inform policy. Methods We conducted a PRISMA‑guided scoping review on seven databases (2013–2024) for Portuguese/Spanish/English observational studies or systematic reviews with post‑2010 data, extracting epidemiological patterns by viral hepatitis type and population group. Results Across 200 included studies, the combined sample encompassed more than 14.5 million individuals. Hepatitis B was the most studied, followed by hepatitis C. Hepatitis A seroprevalence in general population ranged from 33.3–67.8%. In vulnerable populations, highest seroprevalence was among incarcerated populations (88.1%), followed by immigrants (87.4%) and transgender individuals (75.6%). Hepatitis B presented HBsAg prevalence ranging from 0–7.5% in the general population, with the highest rates in an endemic Amazon region. Hepatitis C seroprevalence varied from 0.04–2.2% in the general population, with higher rates among people who use drugs (36.9%). Hepatitis D was predominantly reported in the Amazon region, with prevalence ranging from 0–23.9%. For hepatitis E, prevalence in the general population ranged from 0.9–59.4%, with the highest value in the South region. Conclusions Viral hepatitis in Brazil shows heterogeneous epidemiologic patterns across regions and populations, alongside unequal research output. The predominance of small, cross‑sectional studies and their limited integration with social determinants of health highlight the need for future research employing methodologies that address the gaps identified in this review. The resulting evidence map can guide policies aligned with national elimination goals.
Automated CT dataset generation as a novel concept for verification of backshape-to-spine approach and Cobb Angle Estimation
Background Adolescent idiopathic scoliosis is a condition that affects up to 3% of adolescents. Although radiographic imaging is the gold standard for diagnosis and monitoring, repeated exposure to ionizing radiation poses significant health risks. Alternative methods, such as estimating spinal alignment and Cobb angle from back surface topography, have been proposed to mitigate these risks. However, validation of these methods is challenging because traditional datasets combine back surface scans and radiographs acquired at different times and in different postures. This introduces technique-dependent errors and makes it difficult to determine whether observed discrepancies stem from the method itself or from inconsistencies in the validation dataset. As a result, this uncertainty in methods accuracy arising from verification errors, limits these alternatives to complementary roles rather than establishing them as reliable diagnostic tools. Methods To address this limitation, we introduce a fully automated approach for generating verification datasets directly from computed tomography images. This approach enables precise and synchronized extraction of both external back surface and internal spinal structures, thereby eliminating posture-related discrepancies present in commonly used datasets. We assess the utility of our method through a two-step validation: first, by comparing automatically extracted parameters with manual measurements; and second, by comparing the results of an established surface topography method applied to our dataset with reported values from the literature. Results Our findings suggest that this automatically extracted CT dataset serves as a suitable reference standard for the verification and comparison of surface topography approaches. Conclusion This work provides a robust framework for future verification studies of different surface topography methods and may facilitate the development of non-radiographic techniques for scoliosis assessment, thereby reducing reliance on ionizing radiation in clinical practice.
Day-ahead active and reactive power scheduling of wind turbines and battery energy storage systems for power loss and CO2 emission reduction in AC microgrids
This paper proposes a day-ahead scheduling framework to analyze and optimize the impact of the coordinated active and reactive power management of wind turbines (WTs) and battery energy storage systems (BESSs) on the energy losses and CO 2 emissions of AC microgrids (MGs). Within this framework, the BESS plays a central role by absorbing surplus renewable generation, mitigating curtailment, supporting voltage regulation, and ensuring a stable and reliable dispatch over a 24-hour horizon. A population-based genetic algorithm (PGA) is proposed as the main solution methodology, while particle swarm optimization (PSO) and the multiverse optimizer (MVO) are employed as benchmark methods for comparison. To ensure a fair assessment, all optimization techniques are implemented under the same parallel processing scheme, using the same decision-variable encoding, feasibility correction procedure, and hourly sequential AC power-flow method. The objective is to minimize network energy losses and CO 2 emissions under both grid-connected and islanded operating modes. The proposed methodology is validated on 33-node and 69-node MGs, both evaluated under variable demand and wind-generation scenarios to capture the uncertainty and temporal variability associated with renewable production and load behavior. In addition, the BESS model includes charging/discharging efficiency, self-discharge effects, and battery lifetime assessment under the proposed operating scenarios, allowing a more realistic representation of storage performance. The optimization methods are evaluated over 100 independent runs using the best solution, average solution, standard deviation, and computational time as performance indicators. The results show that the proposed PGA provides the most robust and repeatable performance, while also highlighting the operational contribution of the BESS, reducing renewable curtailment, and guaranteeing compliance with all technical constraints, under deterministic baseline operation and under uncertain time-varying operating conditions in both test systems.
A robust cross-crop disease detection framework based on SIS-YOLOv11 with climate-adaptive mechanisms
Plant disease detection under complex climatic conditions and cross-crop scenarios remains a critical challenge. To address this, we propose a novel SimAM-Inception-StyleRandomization (SIS)-YOLOv11 algorithm based on YOLOv11n for early/late blight detection on potato and tomato leaves. Our core innovations are: 1) A C3k2-SSI module integrating Style Randomization, Inception architecture, and SimAM attention to enhance cross-crop generalization; 2) A Fusion-InceptionConv module for fine-grained feature extraction under rainfall/haze noise; 3) SPPF-Inception and C2PSA-IS modules to optimize multi-scale feature fusion; 4) DepGraph pruning to reduce 47.82% parameters while improving performance. Experiments show that the pruned SIS-YOLOv11 outperforms YOLOv11n by 3.7% in precision, 6.6% in recall, 5.4% in mAP50, and 7.9% in mAP50-95, and surpasses mainstream models (Faster R-CNN, SSD, etc.). This study provides a robust, lightweight solution for automated cross-crop disease detection in complex agricultural environments.
Altered stress and fear responses in the VPA rat model of autism: Behavioral dissociation across tactile, nociceptive, and social contexts
Altered sensitivity to environmental stimuli is a core feature of autism spectrum disorder (ASD) that may drive vulnerability to stress-related and anxiety disorders. To investigate this relationship, we evaluated autonomic and behavioral responses to tactile, nociceptive, and social stressors in juvenile Wistar rats prenatally exposed to valproic acid (VPA), a well-established model of ASD. VPA-exposed and saline-treated control (CTL) rats were subjected to a behavioral paradigm measuring defecation, freezing, and ultrasonic vocalizations (USVs) in response to handling, electro-tactile stimulation, classical fear conditioning, and an emotional contagion task. Compared to CTLs, VPA rats exhibited sustained hyperdefecation during handling and a higher prevalence of defecation during electro-tactile stimulation, independent of freezing changes. During fear conditioning, VPA rats demonstrated a delayed onset but subsequent enhancement of freezing responses, alongside disrupted temporal coordination between freezing and defecation behaviors. 22-kHz USVs positively correlated with freezing across both groups. In the emotional contagion task, observing a distressed conspecific increased freezing prevalence and suppressed vocalization rates in both cohorts; however, these effects were prolonged in VPA rats, which showed persistent freezing and an earlier reduction in vocalization rate. These findings indicate that VPA-treated rats display heightened stress reactivity, habituation deficit and suggest disrupted coordination of fear responses, supporting the VPA model as a relevant tool for investigating the neurobiological basis of stress vulnerability and social dysfunction in ASD.
Will making ‘replication studies’ easier to find help science self-correct?
Design and optimization of highly reliable cognitive non-orthogonal multiple access communication systems
Abstract In this paper, we consider a coexisting network of cellular transmission and device-to-device (D2D) communication, in which BS wants to communicate with far user, meanwhile, a D2D source desires to transmit information to a D2D destination. However, due to heavy shadowing or severe path loss, their direct links are not available. To cope with this problem, a relay is employed to assist the involved transmission. For such a relay-assisted spectrum sharing network, two transmission schemes are designed, i.e., multiple access broadcast NOMA (M-NOMA) scheme and time division broadcast NOMA (T-NOMA) scheme. For each scheme, we first perform power optimization to minimize the outage probability (OP) of D2D communication under the quality of service (QoS) constraint of cellular transmission. Based on the optimization results, we derive the OPs for both cellular and D2D signals. To gain more insights, the asymptotic OPs and the average throughput for both schemes are provided as well. On this basis, we further propose a more superior hybrid M/T-NOMA cognitive communication scheme, in which the system will adaptively select the one with higher system throughput between M-NOMA and T-NOMA as the final transmission scheme. Simulation results validate the accuracy of our analyses, and reveal the performance gain of our schemes over the benchmark schemes.
Daily briefing: Naked mole rat queens use a smell to stay on top
Study on electrochemical corrosion behavior of gray cast iron processed via laser cavitation peening
Laser cavitation peening (LCP) is a novel material surface treatment method. In this study, we investigated the electrochemical corrosion performance of LCP-treated HT250 gray cast iron, with and without a coverage layer, under various laser energies, defocusing amounts, and immersion times. In the LCP process, a 0.04 mm aluminum coverage layer was employed. The influence of the coverage layer on LCP processing was analyzed. The results show that the presence of a coverage layer during the LCP treatment improves the specimen’s anti-corrosion ability, with this alignment corresponding with an increase in laser energy. In comparison with laser energy, the effect of a coverage layer on corrosion resistance at various defocusing amounts is not very significant, and at a smaller defocusing amount, the treated specimen presents higher corrosion resistance. The corrosion resistance of gray cast iron in the case with a coverage layer first increases with the increase in laser energy and then decreases. The presence of a coverage layer helps to avoid laser ablation and cavitation erosion.
Automated detection of trigeminal neuralgia using multi-domain EEG feature analysis and CNN-attention architecture: a comparative machine learning study
Developmental gene expression patterns driving species-specific cortical features
Sex and the clock: Exploring sex differences in chronotype and circadian behavior among healthy older adults
This study aimed to compare subjective and objective circadian measures with a focus on sex differences and cognition in healthy older adults. A total of 126 participants (aged 65–90 years) completed the Horne & Ostberg Morning-Eveningness Questionnaire (MEQ) and the Circadian Type Inventory (CTI) to assess their morning-evening preference and four circadian traits: rigidity vs flexibility (CTI-FR) and languidity vs vigor (CTI-LV). These self-report measures were compared to actigraphy data from a sub-cohort of 63 individuals who wore wrist actigraphs for 24 hours a day over a 7-day period. Results showed that cognitively healthy older adults tend towards rigidity and vigor (on the CTI) and morningness (on the MEQ). Overall, the languid vs vigorous types and flexible vs rigid types displayed differences in MEQ scores. Sex moderated the association between the CTI-LV and MEQ with a steeper association in males than females (p = 0.012). Actigraphy data showed that males had less stable (interdaily stability, IS, p = 0.03) and more fragmented (interdaily variability, IV, p = 0.001) circadian rhythms than older females. Subjective MEQ scores were strongly predictive of acrophase time (p = 0.009) in males but not females. Using information processing speed (IPS) as a marker of cognitive function, we found that greater circadian rhythm fragmentation (IV) was linked to slower verbal IPS (p = 0.004) in males. Morning preference on the MEQ predicted faster spatial IPS in the overall sample (p < 0.001). These findings provide preliminary evidence of the relationship between subjective sleep preferences and objective circadian data in cognitively healthy older adults with notable sex differences in these relationships.