Browse Articles

In silico metabolic profiling of non-baumannii Acinetobacter species uncovers conserved functions and provides first evidence of siderophore biosynthetic genes in Acinetobacter junii

Abstract The genus Acinetobacter is recognized for its metabolic versatility, which contributes to environmental persistence, virulence, and antimicrobial resistance. This study aimed to elucidate the metabolic pathways, particularly those associated with virulence and antimicrobial resistance (AMR), in non- baumannii Acinetobacter species. Genome-scale metabolic prediction of 19 Acinetobacter isolates identified 104 distinct pathways spanning 32 metabolic categories. Ninety-six pathways were conserved across all genomes, whereas a small subset exhibited species- or strain-specific distributions: four pathways occurred in 18 isolates, three were restricted to five A. junii isolates, and one was unique to 14 A. nosocomialis genomes. Amino acid metabolism was the most diverse (29 pathways), followed by lipid metabolism (14 pathways) and energy metabolism (8 pathways). The 96 conserved pathways supported essential cellular functions, including protein synthesis, energy production, and nucleotide metabolism. Notably, 20 pathways were associated with virulence, pathogenicity, and AMR, spanning lipid metabolism, siderophore biosynthesis, and nucleotide metabolism, among others. Eighteen of these pathways were conserved across all isolates and encompassed diverse metabolic functions, including protein N-glycosylation, heme biosynthesis, lipid IVA synthesis, fatty acid β-oxidation, tRNA maturation, triclosan resistance, and superoxide degradation. Interestingly, all A. junii isolates uniquely encoded siderophore biosynthesis systems. In silico analysis of the whole-genome sequences from the five A. junii isolates revealed the presence of genes sharing > 91% sequence identity with the acinetoferrin biosynthetic cluster ( acbABCD ) from Acinetobacter haemolyticus. Additionally, genes homologous to the acinetoferrin transport genes ( actB , actC , actA , and actD ) were identified. However, genes associated with the desferrioxamine E biosynthetic pathway were not detected in these isolates. The high degree of conservation of the acinetoferrin biosynthetic cluster in A. haemolyticus and A. junii suggests that A. junii likely produces acinetoferrin. These findings highlight the high degree of conservation of metabolic pathways in non- baumannii Acinetobacter species and represent the first report of the putative acinetoferrin biosynthetic gene cluster in A. junii .

Spatial patterns and short-term deposition of atmospheric microplastics in an urban environment

Abstract Atmospheric deposition is an important and newly recognised pathway for microplastics (MPs), influencing their transportation and distribution both on land and in aquatic environments. However, MP pollution in the air remains relatively understudied compared to aquatic environments, particularly in developing regions such as Southern Africa. Despite the growing body of literature on MPs in Southern Africa, studies investigating atmospheric MP deposition, short-term variability, and links with meteorological conditions remain limited. This study investigates the occurrence and characteristics of atmospheric MP deposition and their relationship with meteorological factors within an urban town in the Albany thicket biome of South Africa, using weekly sampling over a six-week period across three sites associated with different land-use types. MP deposition fluxes were found to be significantly different between study sites, with an average of 86.5 ± 10.4 particles/m²/day. The highest deposition fluxes were recorded at S2, located in a peri-urban area (178.1 ± 69.2 particles/m²/day) ~ 4.5 km from the town center, while the lowest were observed at S3, ~ 10 km outside the town in a semi-natural area (24.7 ± 8.2 particles/m²/day). Around 30.2% of MPs identified had particle sizes between ≥ 250 and < 500 μm. The dominant colour was transparent/clear (46.6%) and the prevalent shape was fibre/filament (95.5%). FTIR-ATR analysis revealed that polyethylene terephthalate (PET) was the predominant polymer type (42.5%). Microplastic deposition fluxes at S1 (urban area) showed a positive correlation with rainfall, suggesting that rainfall likely influences local MP deposition dynamics at this site. Microplastic deposition fluxes in the town are likely influenced by a combination of local pollution sources, including sewage seepage, poor waste disposal, wastewater management, and textile-related activities. These findings demonstrate clear spatial variation in atmospheric MP deposition linked to land use and local anthropogenic activities, emphasising the importance of atmospheric pathways in regional plastic pollution cycling. The study highlights an urgent need to incorporate atmospheric MPs into environmental monitoring and waste management policies, particularly in urbanising regions of Southern Africa where regulatory frameworks and baseline datasets are still emerging.

Analysis of spatiotemporal dynamics and driving factors of Zhejiang important agricultural heritage systems

Saddlepoint approximations for linear rank tests with left-truncated, right-censored, and cross-sectional data under randomized block design

Abstract Left-truncated data arise when events are only recorded if they occur after a pre-specified time point, while right censoring occurs when the exact event time is not fully observed. Cross-sectional data refer to data collected at a single time point without follow-up. This paper proposes saddlepoint approximations (SPA) for the mid p values of four linear rank test statistics, namely $$T^{b}_{LR}$$ , $$T^{b}_{WLR}$$ , $$T^{b}_{LRC}$$ , and $$T^{b}_{WC}$$ , applied to these data types under a randomized block design (RBD). These test statistics are newly adapted to the RBD framework, and the Skovgaard SPA formula is applied to derive accurate approximations for their mid p values. The accuracy of the proposed SPA is compared against the standard normal approximation (NA) via extensive simulation studies under extreme value and logistic distributions, and illustrated through real data examples. Results demonstrate that the SPA consistently provides more accurate approximations to the mid p values compared to the NA across all simulation scenarios and real data examples.

Rapamycin and nicotinamide treatment attenuates senescence-associated features in mesenchymal stromal cells isolated from elderly donors by modulating autophagy

Senescence inhibition by rapamycin mitigates radiation-induced atherosclerotic characteristics in human coronary endothelial cells

Abstract Ionising radiation (IR) is a recognised risk factor for cardiovascular disease (CVD), yet the mechanisms linking it to exposure remain incompletely understood. We show that IR drives a pro-atherogenic phenotype in human coronary artery endothelial cells (HCAECs) through the induction of cellular senescence, and that rapamycin attenuates these effects. IR triggered hallmark senescence features, including elevated senescence-associated-β-galactosidase activity, nuclear enlargement, and increased Cyclin dependent kinase inhibitor 1 A and p53 expression. Functionally, irradiated HCAECs displayed impaired barrier integrity and heightened monocyte adhesion. Transcriptomic and proteomic profiling revealed broad IR-induced alterations enriched in DNA damage response, cell-cycle arrest, senescence, proteostasis, and immune-related pathways. These findings establish a mechanistic link between radiation-induced endothelial senescence and early atherogenic-associated dysfunction, demonstrating that senescence is a driver of pro-atherogenic phenotypes in HCAECs in vitro. Importantly, mTOR inhibition is identified as a promising strategy to counteract radiation-associated endothelial dysfunction. This work positions senescence as a tractable therapeutic target in radiation-induced vascular injury.

Expression of circulating GRP78 and gp96, endoplasmic reticulum stress-related proteins, in menstrual and bladder pain sensitivity

Abstract Dysmenorrhea is often linked to uterine inflammation, but the additional factors and pathways that contribute to its pathophysiology remain poorly understood. Given growing evidence linking endoplasmic reticulum (ER) stress to inflammation and pain sensitization, we examined circulating ER stress-associated heat shock proteins (HSPs) GRP78 and gp96 in individuals with dysmenorrhea (n = 82), a dysmenorrhea subtype with bladder pain sensitivity (DYSB, n = 26) previously shown to increase risk for chronic pain, and controls (n = 19). After correcting for Menstrual phase, naproxen exposure, and oral contraceptive use, GRP78 was higher in DYSB than in DYS (ratio 1.33; p  = .028), while gp96 was lower in both DYS (ratio 0.62; p  = .019) and DYSB (ratio 0.59; p  = .031) compared to controls. gp96 was also lower during the menstrual phase with naproxen compared to the non-menstrual phase (ratio 0.73; p  = .014), whereas GRP78 was not significantly affected by menstrual phase, naproxen, or oral contraceptive use, and neither protein was associated with anxiety, depression, or sleep disturbance scores. These cross-sectional findings suggest that dysmenorrhea, particularly the bladder-sensitive subtype (DYSB), is associated with divergent circulating levels of two ER stress-related proteins. The inverse pattern of higher GRP78 and lower gp96 levels points to selective, rather than global, ER chaperone dysregulation as a candidate mechanism. However, future mechanistic and longitudinal investigations will be required to establish whether GRP78 and gp96 carry predictive or pathophysiological relevance.

In silico design and evaluation of a multi-epitope vaccine targeting eyach virus for the prevention of tick-borne encephalitis in humans

Abstract Eyach virus is a tick-borne pathogen associated with neurological complications resembling encephalitis, and its increasing emergence highlights a growing public health concern. The absence of specific antiviral therapies and limited surveillance data emphasize the urgent need for effective preventive strategies such as vaccine development. This study presents an immunoinformatics-driven design and in silico evaluation of a multi-epitope vaccine candidate targeting Eyach virus. Structural proteins VP5 and VP7 were analyzed to identify highly antigenic, non-allergenic, and non-toxic B-cell, CTL, and HTL epitopes. The selected epitopes demonstrated broad global population coverage of 97.94%, indicating wide immunogenic applicability. These epitopes were assembled into a 256 amino acid vaccine construct using suitable linkers and β-defensin-3 as an adjuvant. Physicochemical properties analysis revealed a stable, hydrophilic, and soluble protein profile. Structural modeling and refinement confirmed high stereochemical quality, with 96.3% of residues located in favored regions. Molecular docking analysis indicated favorable predicted interactions between the vaccine construct and TLR3 and TLR4. Molecular dynamics simulations further confirmed the structural stability, compactness, and consistent behavior of the complexes. In addition, MM/GBSA analysis revealed favorable binding free energies, with the vaccine–TLR3 complex exhibiting a stronger binding free energy of − 203.29 kcal/mol. Immune simulation predicted robust humoral and cellular immune responses, including elevated immunoglobulin levels, cytokine production, and memory cell formation following a three-dose regimen. Overall, the findings suggest that the proposed multi-epitope vaccine is a promising candidate against Eyach virus; however, experimental validation is required to confirm its safety and efficacy.

Synthesis, optical and raman spectra of cobalt ditellurite, CoTe2O5 single crystal

The neutrophil-to-lymphocyte ratio and incident chronic kidney disease in a community-based cohort: a prospective study

Climate variability and COVID-19 non-pharmaceutical interventions shaped dengue transmission in Guangdong: an integrated modeling study

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles

Reference protein-coding transcripts of human genes annotated using long-read transcriptome datasets

$$H_\infty$$ state feedback controller for power system synchronous generator modeled as singular Takagi Sugeno fuzzy with time delay

Abstract This paper presents a robust $$H_{\infty }$$ state-feedback controller design for a singular Takagi-Sugeno (T-S) fuzzy model of a synchronous generator, effectively addressing time delays, external disturbances, and algebraic constraints inherent to singular systems. The proposed controller employs a descriptor system formulation that captures both differential and algebraic equations, providing a more accurate representation of power system dynamics than conventional state-space models. Necessary and sufficient conditions for the existence of the $$H_{\infty }$$ controller are derived as strict linear matrix inequalities (LMIs), ensuring numerical tractability and guaranteeing closed-loop admissibility. The proposed controller, denoted as HITSFS (Descriptor-based $$H_{\infty }$$ control), is rigorously compared against RHITS (Non-descriptor $$H_{\infty }$$ control) and NFTSFS (Non-fragile saturation control) under exhaustive validation scenarios, including systematic parameter variations (minimum, nominal, maximum), measurement noise ( $$\sigma = 0.003$$ –0.010 p.u.), time delays ( $$\tau = 0.1$$ –0.5 s), and distinct fault conditions (0.3–1.0 p.u.). The proposed HITSFS controller achieves the lowest ISE and peak overshoot across all states, with 24 total wins compared to only 2 for RHITS and 4 for NFTSFS. It demonstrates superior noise immunity (near-zero ISE for $$\omega _d$$ ) and fault recovery, while consuming the least control energy (6.2949 pu $$^2$$ s), consistently outperforming both baseline controllers across all test scenarios.

Implicit gender bias modulates lateral prefrontal cortex activity and rejection of female advice during cooperative decision making

Abstract Despite efforts to increase gender diversity in leadership, women remain undervalued, mainly due to gender stereotypes portraying females as less competent and of lower status. This study employs a novel mixed-gender dyad collaborative task with electroencephalography (EEG) and dipole source localization to investigate the neural mechanisms underpinning gender-biased rejection decisions in a real-time social context. In half of the trials, the male participants were designated as decision-makers, who evaluated their female partners’ suggestions and provided the final team answer. EEG data collected from the male low-biased (LB) and high-biased (HB) groups, classified according to the Implicit Association Test (IAT), were analyzed during the decision periods which resulted in the rejection of female answers. The HB group rejected their female partners’ choices at 57% in trials with conflict, which was similar in the LB group (55%). However, many rejections by the HB group resulted in wrong decisions (54%) which was significantly lower in the LB group (34%). Although criterion-based bias index from the signal detection theory could not explain this difference, a novel biased-rejection index (BRI), which measured the costly rejection behavior, could significantly separate the two male groups. Dipole source localization based on EEG during the entire decision period revealed significantly lower middle frontal gyrus (MFG), but higher inferior frontal gyrus (IFG) activation in the HB group compared to the LB group. Temporal dynamics analysis (resolution: 0.34 s) further showed (but not at a statistically-significant level) less activation in MFG for the HB group during the early stage, and a similar trend in SFG during the middle stage of cognitive processing. On the other hand, the moment magnitudes of IFG dipoles during the entire decision period were significantly correlated with the IAT D-scores, i.e. less IFG activation with lower implicit bias. Given the limitations of the study (lack of EEG from female decision-makers and 10–20 system montage), these findings suggest altered lateral prefrontal cortex (LPFC) activations as part of the neural correlates of gender-biased undervaluation of female contributions during a collaborative task.

Case studies on predictive maintenance of aircraft large-opening panels using integrated planar electromagnetic sensing and dynamic Bayesian networks

BEML-sonar: a bio-inspired echolocation and machine learning-enhanced SONAR for underwater object detection and navigation

Abstract Traditional SONAR systems are widely used for underwater object detection and navigation; however, they suffer from high energy consumption, noise interference, and signal degradation in varying aquatic conditions. Inspired by biological echolocation, we propose a novel machine learning-enhanced sonar model to improve accuracy, robustness, and energy efficiency in underwater sensing applications. The proposed model employs bio-inspired echolocation principles, where transmitted acoustic pulses dynamically adjust in response to environmental conditions. Deep learning techniques, specifically Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, are employed to classify sonar echoes and enhance object detection. Additionally, digital signal processing (DSP) techniques, including Butterworth filtering, wavelet decomposition, and adaptive thresholding, are integrated to mitigate noise and improve signal clarity. Experimental evaluations demonstrate that the proposed sonar model, SonarNet, achieves 92.7% classification accuracy, outperforming conventional SONAR-based methods, which achieved 85.4% accuracy. The integration of adaptive signal processing leads to a 20.8% reduction in energy consumption compared to standard SONAR models, improves the Signal-to-Noise Ratio (SNR) by 15.3 dB, and reduces the false positive rate by 18.6%. Additionally, the sound velocity profile (SVP) correction mechanism improves depth estimation accuracy by 12.4%. All performance results reported in this work were obtained using a simulation environment parameterized by real-world oceanographic datasets.

Prediction of secondary network supply water temperature based on EEMD-DWA-CNN-BiLSTM model for energy conservation

Risk factors for visual field progression during 10-year follow-up in newly diagnosed exfoliation glaucoma patients

Abstract To identify risk factors associated with visual field progression over long-term follow-up (10 years) in patients newly diagnosed with exfoliation glaucoma. This was a non-randomised, prospective cohort study including patients newly diagnosed with exfoliation glaucoma. Visual field progression was assessed using three methods mean deviation (MD), visual field index (VFI), and guided progression analysis (GPA). Baseline variables to be evaluated included intraocular pressure (IOP), sex, age, visual fields, uni- or bilateral presentation, visual acuity, lens status (phakic/pseudophakic), central corneal thickness (CCT), optic nerve status, and gonioscopy findings. Additionally, a questionnaire on, hypertension, diabetes, migraine, smoking, and family history of glaucoma. Multivariable regression analyses were performed to identify risk factors. A total of 58 patients completed the 10-year follow-up. The IOP at inclusion was 32.06 (± 6.05) mmHg. In the MD model, significant risk factors for progression included older age ( p  = 0.002), smoking ( p  = 0.004), phakic lens status ( p  < 0.001), and lower CCT ( p  = 0.02). In the VFI model, significant risk factors were older age ( p  = 0.009) and smoking ( p  = 0.04). In the GPA model, risk factors included older age ( p  = 0.001) and smoking ( p  = 0.01). Older age at diagnosis and a history of smoking were found to be significantly associated with an increased risk of long-term visual field progression.

Mammals tolerate harmless human presence: Lessons from COVID-19 lockdown on Barro Colorado Island, Panamá

Abstract Human presence in protected forests impacts wildlife, but investigating such impacts is challenging because it is rare to isolate human presence from other anthropogenic factors. The COVID-19 lockdowns in 2020 provided a quasi-natural experiment that reduced human activity on Barro Colorado Island, a tropical forest isolated from most human footprints in Panamá. We used trail-based camera trap data from mammal species to compare a lockdown period (April–July 2020) versus non-lockdown (2019). For all observed species, we tested the hypotheses that human presence impacts activity level for 14 species, and for focal species we also tested diel activity, predator-prey dynamics, group cohesiveness, scent-marking, foraging, and vigilance. To assess lockdown effect, we analyzed our data using negative binomial, logistic and recurrent event analysis, and we contrasted null and alternative models. We also estimated diel activity patterns and used confidence intervals to examine lockdown effects. Based on camera trap observations, human presence on BCI forest was 9 times lower, while 16.2 times lower based on safety book records. Results showed no significant changes in activity level (rate of events) and diel activity for any species; in foraging duration of agouti, collared-peccary, red-brocket deer, and white-nosed coati; in predator-prey dynamic between agouti and ocelot; and in scent-marking of agouti. However, group cohesiveness and vigilance of white-nosed coati and collared-peccary were higher during lockdown. Overall, under lockdown, animal activity and diel activity patterns remained unchanged, although agouti, peccary, coati, and ocelot’s diel activity slightly increased during typical human-active hours. Our results indicate that mammals, living on a managed forest with low anthropogenic impact and disturbance, can tolerate non-consumptive human presence.