Browse Articles

CiCLoDS: Joint cell clustering and gene selection for single-cell spatial transcriptomics

Fast learning-free organoid quantification and tracking with OrganoSeg2

MM-GradCAM: an improved multimodal GradCAM method with 1D and 2D ECG data for detection of cardiac arrhythmia

Abstract As cardiac arrhythmia remains one of the leading causes of death worldwide, early and accurate diagnosis of cardiac arrhythmia is critical to improving patient outcomes. Electrocardiogram (ECG) analysis plays a critical role in the diagnosis of these diseases, and recent advances in deep learning have led to significant advances in automated ECG interpretation. However, the “black box” nature of these models limits clinical confidence and highlights the need for explainable artificial intelligence methods. This study presents an innovative MM-GradCAM method that combines two different data formats, providing explainability for both 1D ECG signal and 2D ECG image data. Using a dataset of more than 10,000 patients, a 17-layer CNN model capable of four-class arrhythmia detection was developed and separate explainability outputs were obtained for each data form. The resulting explainability maps were evaluated by a cardiologist and the interpretability and clinical significance of the model were verified. The signal form achieved 93.07% accuracy, while the image form achieved 97.44% accuracy. As a pioneering approach for explainability in medical diagnosis, MM-GradCAM has the potential to increase reliability and transparency in medical AI applications.

Ultra-high sensitivity gas sensors employing Bloch-like surface waves in a metal-dielectric one-dimensional photonic crystal

Abstract Bloch surface waves (BSWs), generated at the interface of a truncated one-dimensional photonic crystal (1DPhC) and the adjacent medium (analyte), are accompanied by narrow resonance dips that are very advantageous compared to too wide resonance dips associated with the surface plasmon resonance (SPR) phenomenon. Consequently, BSW-based sensors have been thoroughly studied and applied in the field of optical sensors, but their sensitivity to gaseous analytes does not outperform the sensitivity of the SPR-based sensors. One of the possible solutions to enhance the sensitivity represents a metal-dielectric 1DPhC. We report on a sensing concept for gaseous analytes based on the wavelength interrogation and resonances supported by a metal-dielectric 1DPhC in the Kretschmann configuration. For a metal-dielectric 1DPhC comprising bilayers of TiO $$_2$$ /Au with a termination layer of TiO $$_2$$ , we show that the Bloch-like SW-based resonances are resolved for both TE and TM waves. For the TE wave and the refractive index (RI) in a range of 1–1.0015, a sensitivity of 10,900 nm/RIU, a figure of merit (FOM) of 474 RIU $$^{-1}$$ , and a limit of detection (LOD) of 9.3 $$\times$$ 10 $$^{-6}$$ RIU were reached. The analysis extended to the 1DPhC with the modified thicknesses of TiO $$_2$$ layers and gas, whose RI changes in a range of 1.0002–1.0022, leads to the sensitivity and FOM in a range of 10,680–28,000 nm/RIU and 434–1217 RIU $$^{-1}$$ , respectively, and to a very low LOD of 3.6 $$\times$$ 10 $$^{-6}$$ RIU for the TM wave. This research is the demonstration of exceptional properties of the Bloch-like SW-based sensors employing metal-dielectric 1DPhCs that can be used in a simple sensing of a wide range of gaseous analytes.

The impact of virtual synchronous compensator on the transient synchronous stability of renewable energy

Abstract The virtual synchronous compensator (VSCOM) integrates virtual synchronous machine control within a static var generator (SVG), providing active voltage support and improving the adaptability of SVGs to weak grid conditions. However, the interaction between VSCOM, which adopts grid-forming control, and renewable energy grid-connected converters (REGC) based on grid-following control introduces complex transient stability characteristics. This study investigates the effect of VSCOM on the transient synchronous stability of REGC under large grid disturbances. First, a constant voltage current-limiting control strategy for VSCOM is proposed based on its operational characteristics. A mathematical model is then established to assess the enhancement of the static stability limit of REGC by VSCOM. Subsequently, a transient model of the coupled VSCOM-REGC system is developed, considering the short-circuit ratio (SCR), control parameters, and reactive power capacity, to clarify the mechanism by which VSCOM affects the transient synchronous stability of REGC. Finally, an electromagnetic transient simulation model is built using MATLAB/Simulink to verify the theoretical analysis.

PFDN2 stabilizes PYCR2 to activate Wnt/β-catenin signaling and promote colorectal cancer progression

Exploration of electrospinning hemp/polyacrylonitrile composite fiber membrane and dye adsorption capabilities

Robust RP-HPLC method for the parallel determination of quaternary mixture in cold and cough syrups with sustainability appraisal

Modeling nonlinear variable-order fractional chaotic systems using the Caputo-Fabrizio operator and radial basis function neural networks

Effects of non-pharmacological interventions on sleep in patients with critical illness: a systematic review and network meta-analysis

Abstract Adequate sleep is vital for recovery in patients with critical illness, yet sleep in intensive care units (ICUs) is widely disrupted. Although various non-pharmacological strategies have been proposed, evidence remains inconsistent, and the most effective intervention for improving ICU sleep has not been clearly established. In this review, we evaluated the effectiveness of non-pharmacological interventions for sleep promotion and identified the most effective strategies for improving sleep quality among ICU patients. Studies implementing non-pharmacological sleep-promoting interventions and evaluating sleep quality in ICU patients were identified using MEDLINE and Cumulative Index to Nursing and Allied Health Literature. The protocol was registered in PROSPERO (CRD420251184156). Thirty-six studies encompassing 16 intervention types were included. A Bayesian network meta-analysis demonstrated significant improvements for aromatherapy, eye mask, eye mask and earplugs, music therapy, and multicomponent intervention compared with control groups. Surface under the cumulative ranking curves indicated that music therapy (94.9%) had the highest probability of being the most effective intervention, followed by aromatherapy (76.2%). These interventions may improve sleep by reducing environmental disturbances and stabilizing autonomic and neurotransmitter activity.

Molecular insights into efflux pump genes in ciprofloxacin- and methicillin-resistant Staphylococcus aureus and Staphylococcus epidermidis clinical isolates from Iraq

Exploring the chemical space around Cannabis sativa L. leaves as a source of bioactive compounds of pharmaceutical interest

Functional imaging of time on task and the involvement of dopaminergic and cholinergic substrates in cognitive effort and reward

Abstract Neuroimaging studies have identified the neural substrates associated with sustained cognitive efforts and control and their modulation by rewards. Different lines of evidence implicate the prefrontal cortex (especially the anterior cingulate cortex, ACC), dopaminergic, and cholinergic substrates in this modulation. We studied here the activity of these substrates at increasing time on task (requiring increasing levels of cognitive effort) in trials within blocks with differing reward levels. In the cortex, while peaking in the ACC, activity associated with time on task was extensive, also including activity decrements outside the default mode network, primarily involving motor and somatosensory regions. Information about reward levels was carried in the ventral striatum, consistent with its motivational role, but did not reflect trade-offs with increasing efforts during time on task. Instead, the ventral tegmental area and parts of the basal forebrain (BF) corresponding to the cholinergic Ch4 nuclei increased in activity with time on task and were sensitive to reward levels. This BF activity is consistent with a cholinergic role in driving compensatory efforts modulated by reward levels. These findings identify the BF as a neuroimaging phenotype associated with sustaining task sets and cognitive efforts.

Interdependency between oxytocin and dopamine in trust-based learning in mice

Seroprevalence and determinants of hepatitis E virus infection among people living with HIV in Chiang Mai, Thailand: a cross-sectional analysis

Impaired brain intrinsic connectivity in long COVID during cognitive exertion revealed by independent component analysis

Abstract Cognitive dysfunction is a symptom of Long COVID. To characterize functional connectivity changes that may contribute to cognitive dysfunction in Long COVID (LCov), two consecutive 450 s functional magnetic resonance imaging (fMRI) scans (Runs 1 and 2) were acquired on a 7 Tesla MRI scanner. During both, the Stroop colour-word task engaged intrinsic brain networks for conflict detection, conflict resolution and response execution. In this exploratory study we acquired data from 19 LCov and 16 healthy control (HC) participants. The aggregate dataset was subjected to independent component analysis (ICA) for each run to isolate 15 components with distinct spatial and temporal signatures. For each component we tested (1) for differences between LCov and HC (inter-network) connectivity to the rest of the brain and (2) for correlation of LCov connectivity with illness duration. Stroop response times (RTs) were slower in LCov than in HC in both Runs ( p  = 0.001, 0.003). Each ICA component occupied the hubs of a known intrinsic network. LCov had different inter-network connectivity to HC for Salience, Language, Central Executive, Sensorimotor and Visual networks. LCov deficits in Salience inter-network connectivity in Run 2 were deeper and more widespread than in Run 1. In contrast, Run 2 connectivity was greater in LCov for the angular gyrus which integrates visual, motor and language inputs and responses. With longer illness duration, LCov connectivity weakened to critical networks but showed compensatory effects in Lingual gyri. Slower Stroop RTs in both Runs, and Salience, Language and Central Executive inter-network connectivity deficits, and illness duration dependence, support cognitive impairment in LCov with some compensatory connectivity increases.

Investigating the influence of expanded perlite and lime mud on cement-bonded composites containing pulp sludge

Abstract This paper presents a comprehensive study on lightweight cement-bonded composites containing pulp sludge (PS). The objective of the study was to evaluate how the incorporation of perlite (a lightweight volcanic glass aggregate) and lime mud (a pulp mill residue) influences composites’ properties including mechanical strength, insulation and fire resistance. Up to 50% of the cement binder was replaced with PS (by mass), and small fractions of cement (5–15%) were replaced with perlite or lime mud. A suite of analytical techniques, material characterization and mechanical tests with digital image correlation (DIC) for strain analysis were employed. X-ray analysis showed that the aggregates influenced the composite properties to a considerable extent due to their particle sizes and ability to form hydrated gels with cement. Adding 5% of perlite or lime mud yields optimal strength without compromising weight reduction whereas higher aggregate content (15%) led to reduced strength. The DIC system provided insights into strain distribution during loading, confirming enhanced toughness from the fibrous PS. The composites were significantly lighter (732–749 kg/m 3 ) and showed about 30% lower thermal conductivity (0.17 W/mK) than pure cement composites (0.25 W/mK). The normal incidence sound absorption of the composites was about 0.3 at mid-high frequencies due to their compact structure. The composites demonstrated potential for use as sustainable, lightweight construction materials with good acoustic and thermal insulation, as well as acceptable load-bearing capacity for non-structural applications based on EN 634-1/-2 requirements for cement-bonded particleboards.

Effectiveness of core strength training for racket sport athletes’ performance: a systematic review and meta-analysis

CFD-based optimization and experimental validation of supersonic separator design with angular injection swirler for efficient gas dehydration

Academic Tangping scale for college students in China: scale development, validation and application

Abstract In light of the universality of the Tangping phenomenon and the lack of measurement tools, this study aims to develop Academic Tangping Scale for assessing this phenomenon among for college students in China. A total of 644 valid Chinese university students participated in the research. Exploratory factor analysis supported the extraction of three dimensions, namely affective, cognitive and behavioral dimensions, and confirmatory factor analysis indicated a good model fit, further confirming the scale’s dimensional structure. High Cronbach’s alpha coefficients across the subscales further affirm its robustness as a psychometrically sound measurement instrument. Evidence for convergent and discriminant validity was rigorously substantiated, and significant Pearson correlations with the existing Lying Flat Tendency scale demonstrated criterion-related validity. Finally, the scale’s practical applicability was supported by significant correlations with depression, anxiety, and stress, indicating meaningful associations with students’ mental health outcomes. The scale acknowledges limitations and proposes corresponding suggestions. Overall, the scale demonstrates strong psychometric properties, providing a reliable tool to assess the Academic Tangping and support targeted interventions and research on student mental health.