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Serological profile of naïve patients affected by the first sars-cov-2 variant: A prospective study

Background Understanding post-infection immunity with the first SARS-CoV-2 variant may provide valuable insights into the duration and effectiveness of the humoral immune response. This study aims to characterize the serological profile of naïve individuals infected with the first SARS-CoV-2 variant. Methods A prospective study with repeated measures was conducted in Tunisia, from March to October 2020, during the first wave of COVID-19. Adults confirmed with confirmed COVID-19 were monitored during the first wave of the pandemic. ELISA blood tests were conducted at multiple intervals: day 7, day 14, and at 1, 2, 3, 4, and 6 months post-infection. Results 173 serum samples were collected from immunologically naïve individuals infected with the first circulating SARS-CoV-2 variant, ranging from 7 days to 6 months post-RT-PCR confirmation. The study revealed a robust humoral immune response in most participants, with 94.1% testing positive for IgM anti-N, 88.2% for IgM anti-S, 98% for IgG anti-N, and 100% for IgG anti-S antibodies. Anti-N IgM antibodies peaked at days 14 and 30 with high positive values (>0.260), while anti-S IgM antibodies showed elevated levels (>0.990) at days 7 and 14. For IgG, anti-N antibodies reached their highest levels (>0.810) at month 4, while anti-S IgG antibodies maintained high positive values (>0.490) at days 7 and 14, and remained elevated at months 4 and 6. No significant differences in antibody levels were observed based on gender, age, comorbidities, or symptoms presence. Conclusion A typical adaptive immune response was observed in naïve individuals infected with the initial SARS-CoV-2 variant, showing typical IgM and IgG antibody production from day 7 to month 6. We specifically investigated immunologically naïve individuals infected with the first circulating SARS-CoV-2 variant, from the earliest stage of infection, a context that is no longer reproducible.

The influence of diet-mediated exposure of avian influenza on adult survival, recruitment and territory occupancy in peregrine falcons

Reaction Discovery Involving Digital co‐Expert with a Practical Application in Atom‐Economic Cycloaddition

Abstract The discovery of new chemical transformations is central to advancing modern chemistry, yet conventional approaches often require months or years of extensive experimental screening. Here, we present a machine‐learning‐assisted and expert‐guided pipeline for reaction discovery applied to the search for atom‐economic cycloaddition reactions. Candidate reactions were generated from publicly available quantum chemical data, filtered through unsupervised machine learning, and clustered to reduce redundancy. A digital co‐expert then enabled rapid prioritization, after which human expertise provided final selection and experimental validation. This hybrid workflow is fully compatible with current laboratory infrastructure and addresses the most time‐consuming stage of reaction discovery, accelerating the expert screening bottleneck by approximately 180‐fold (from > 1200 days to 7 days). Within ∼1 week, two novel cycloaddition reactions were identified and experimentally confirmed, yielding previously undescribed products. While fully autonomous robotic platforms represent a long‐term vision, their high cost and limited availability restrict immediate application. In contrast, our approach demonstrates the practicality of human‐AI collaboration for reaction discovery, combining computational screening, machine learning and expert knowledge to efficiently expand the accessible chemical space.

Interventions to improve mental well-being and sleep in paramedics: A scoping review

Background Paramedics face unique occupational hazards, including high operational demands, trauma exposure, and shift work, all of which impact mental well-being. Suboptimal sleep is also common in this workforce and closely linked to adverse mental health outcomes. This scoping review synthesizes evidence to date on interventions to support paramedic mental well-being including sleep-based interventions. Materials and methods This review was pre-registered on the Open Science Framework ( https://doi.org/10.17605/OSF.IO/7VSD9 ). Systematic database searches were conducted in October 2024 for original research published after 2004. Data were narratively synthesised, and findings reported following established guidelines. Results Nineteen sources were included, involving 1,067 participants across seven countries. Seventeen interventions were examined, predominantly via randomized controlled trials (58%), utilizing a total of 43 different measurement scales to evaluate mental health and sleep outcomes. Interventions included psychological (37%), sleep, fatigue and/or shift work (32%), and complementary and alternative medicine (32%) approaches which primarily focussed on the individual-level (94%). Studies were limited by sample sizes, design and quality, limited long term follow-up, and low baseline symptoms. Conclusions This review highlights a critical gap in robust, evidence-based, system-level interventions to address poor sleep and mental well-being in paramedics. Future research should prioritise co-designed, context-sensitive approaches, ideally integrated within organisational structures to ensure relevance and accessibility.

Rational design of k-casein peptides to modulate GSK-3B dynamics for Alzheimer’s therapy

Abstract GSK-3β is an important therapeutic target in Alzheimer’s disease due to its central role in tau hyperphosphorylation, and synaptic dysfunction. In this study, a κ-casein-derived peptide (LALTLPFLGA) was identified via HADDOCK and introduced to MD simulations for MM/PBSA per-residue analysis, revealing four unfavorable mutation sites (L12, L14, T15, F18). Using MCSM and ΔΔG-based substitution, a 48-peptide library was generated; 22 candidates satisfied toxicity/allergenicity filters. Docking and MD simulations prioritized four leads—PEP8, PEP36, PEP40, and PEP44—with PEP8 (− 89.1 kcal·mol⁻¹) and PEP44 (− 88.4 kcal·mol⁻¹) as top binders. These mutants, all carrying L12H/L14H substitutions, demonstrated stronger HADDOCK scores (− 89.1 to − 84.6 kcal/mol) compared with the template. Additionally, PEP8 carried F18→Asp, and T15→Leu/Ile developed affinity in other mutants. PEP8 established 21 contacts, followed by PEP44 (19), PEP40 (17), and PEP36 (15), indicating that larger interaction networks are vital for binding. PEP8 contacted with the ATP-binding pocket (Val135, Thr138, and Tyr134), whereas PEP44 contacted catalytic Asp200. MD results also showed reduced RMSD, slightly lower Rg/SASA, and tighter PCA clustering, exhibiting that PEP8 and PEP44 induced compaction and restricted conformational freedom, and possibly, hindering substrate binding. MMPBSA confirmed PEP44 and PEP8 as strongest complexes (− 188.482 and − 184.404 kJ/mol), governed by van der Waals and electrostatic contacts, while PEP36 suffered solvation penalties and PEP40 remained hydrophobic-driven. Together, our computational pipeline highlights PEP8 and PEP44 as promising κ-casein-derived inhibitors of GSK-3β, illustrating a rational design of food-derived peptides as potential multifunctional candidates for Alzheimer’s disease.

Dynamic Color‐Tunable Dual Room Temperature Phosphorescence via Activation of Both Host and Guest Triplet States

ABSTRACT The design of dual organic room‐temperature phosphorescence (RTP) from both the host and guest remains a significant challenge, as most organic doping systems generally enable either the guest or the host to serve as a single static phosphorescent emitter. Here we report a host–guest dual RTP system featuring dynamically tunable colors, controllable host‐to‐guest phosphorescence ratios, and widely tunable lifetimes of 18.8–472 ms. This unique performance is enabled by bidirectional triplet energy transfer processes between host and guest, which not only activates RTP of the host molecules but also induces a blue shift of the phosphorescence from 673 to 528 nm, with CIE chromaticity coordinates ranging from (0.51, 0.45) to (0.40, 0.57). More importantly, alkyl ring groups effectively modulate the triplet energy levels of the identical π‐conjugated host molecules at the aggregate level, resulting in the lowest triplet energy levels of host crystals ranging from 2.88 to 2.53 eV. This work provides a unique insight into achieving dual RTP in organic doping systems and holds great potential for applications in multilevel information encryption and optoelectronics research.

Similarity of sputum mediator signatures between e-cigarette users and COPD depends on GOLD stage and type of e-cigarette: a pilot study

There is overlap in symptoms and airway pathobiology between COPD and e-cigarette (e-cig) users. We sought to determine if young adult e-cig users have similar sputum soluble mediator profiles to COPD and if this is related to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage and generation of e-cig device. Experimental groups (n = 20–30/group) included non-smokers, smokers at risk of COPD (“pre-COPD”), mild/moderate COPD (GOLD 1/2), and severe COPD (GOLD 3) from the SPIROMICS cohort and healthy e-cig users of 3 rd and 4 th generation devices (previously published). Sputum soluble mediator profiles were compared between COPD GOLD stages and then between e-cig users of both generation devices and COPD participants by GOLD stage using a suite of computational approaches, including correlation analyses, unsupervised machine learning, and multivariate distance metrics. Inflammatory mediators were significantly increased in pre-COPD and GOLD 3 versus non-smokers and GOLD 1/2. Soluble mediator profiles of e-cig users showed patterns of overlap with COPD that were GOLD stage specific and based on shared biological functions that included proteases (MMP9, MMP2) and elastases (neutrophil elastase, myeloperoxidase). These findings indicate similarities in soluble mediator profiles between e-cig users and patients with COPD, highlighting potentially similar biological mechanisms relating to inflammation and tissue remodeling. Future studies with younger COPD cohorts, and those with preserved ratio impaired spirometry (PRISm) or bronchitis versus apical emphysema are needed to fully understand the extent of biological mechanisms that are shared between e-cig users and COPD. This pilot study represents a first step in understanding potential similarities between mediator changes in the airways of COPD patients and otherwise healthy young adult e-cig users.

The ActivLife exergame rehabilitation program improves functional abilities in pre-frail and frail older adults: a clinical trial

Selective Carbocation Functionalization by Catalytic Transchalcogenation Reactions

ABSTRACT Introducing functionalities via acid‐mediated carbocation chemistry is conceptually straightforward, but typically lacks in selectivity and broad‐scale applicability, which is further hampered by the need for toxic reaction partners. Here, we show that small S‐ and Se‐based functionalities can be selectively and safely introduced into feedstock molecules via acid‐catalyzed transchalcogenation reactions. A designable y‐keto donor compound delivers the functionality through the formation of a trialkyl chalcogenonium intermediate that is prone to elimination in conjunction with the acid catalyst and its counteranion. We demonstrate how this strategy enables chemo‐, regio‐, and stereoselective construction of C(sp 3 )─S and ─Se bonds, offering clear advantages over classical acid‐catalyzed carbocation functionalization.

Correction: Research on energy-saving algorithm of HVAC multi-agent system consensus based on event-triggered mechanism

Experimental study of radiation shielding performance of PbO2-BaO-CaO-B2O3-Y2O3 glass systems

Abstract The purpose of this work is to prepare glass samples with the chemical formula xPbO 2 -23BaO-10CaO-(65-x)B 2 O 3 -2Y 2 O 3 (x = 10, 13, 16 and 19 mol%) using the usual melt quenching technique. These glasses are intended to be used as shielding materials designed to protect against ionizing radiation. Following the experimental measurement of the mass attenuation coefficient (G MAC ), which was done to explore the photon shielding capabilities of the prepared samples. The findings were then compared with the values that were estimated from the Phys-x database and simulated using Geant4 code. The experimental findings that were obtained demonstrated a satisfactory connection with the data that was obtained from both Phy-x and Geant4. Based on the observed G MAC , other radiation shielding characteristics were computed for each of the glass that were investigated. These parameters included the linear attenuation coefficient (G LAC ), the half-value layer (G HVL ), and the mean free path (G MFP ). Considering the data presented here, it seems that PBCBY-4 samples have the potential to be advantageous for use in shielding applications against ionizing radiation.

Leukotriene receptor antagonists and eosinophilic granulomatosis with polyangiitis: a disproportionality analysis from FAERS, JADER, CVAR databases integrated with network pharmacology

Objective The relationship between leukotriene receptor antagonists (LTRAs) usage and the subsequent occurrence of eosinophilic granulomatosis with polyangiitis (EGPA) remained highly polarizing and controversial in previous studies. We aimed to investigate the risk of EGPA caused by LTRAs and the potential toxicological mechanisms of LTRAs-related EGPA. Methods In this real-world pharmacovigilance study, we collected adverse event (AE) reports of EGPA associated with LTRAs use from the U.S. FDA Adverse Event Reporting System (FAERS), Japanese Adverse Drug Event Reporting (JADER), and Canadian Vigilance Adverse Reaction (CVAR) databases. The reporting odds ratio (ROR), proportional reporting ratio (PRR), information component (IC), and empirical Bayesian geometric mean (EBGM) were calculated to quantify the strength of the association between LTRAs and EGPA. The Weibull shape parameter (WSP) test was applied to analyze time-to-onset profiles of EGPA toxicity. Network pharmacology analysis was subsequently performed to identify the central genes to determine the potential mechanisms underlying LTRAs-induced EGPA. Results LTRAs, including montelukast, zafirlukast, and pranlukast, exhibited a strong association with EGPA in three databases (the lower limit of 95% confidence interval (CI) for ROR > 1, PRR > 2 with χ 2 values ≥4, EBGM05 > 2, and IC025 > 0). After excluding corticosteroids as concomitant medication, montelukast remained significantly associated with EGPA in the FAERS database. The median time-to-onset of EGPA associated with LTRAs was 233 (range: 76–660) days, and the WSP test indicated LTRAs had early failure-type profiles. We isolated 81 interactive target genes linking LTRAs to EGPA. Several central genes, including SRC, PTGS2, EDN1, HMOX1, KDR, and OCLN, were revealed via protein-protein interactions analysis and molecular complex detection (MCODE) algorithm. Conclusion Our study revealed LTRAs could increase the risk of EGPA, and initially explored potential genes and mechanisms of LTRAs-induced EGPA. It is helpful for clinicians to be alerted to the risk of EGPA during LTRAs administration.

Electrochemically optimized multi-component polyacrylonitrile nanofiber scaffolds as a platform for three-dimensional glioblastoma cell culture

A Metallosupramolecular Receptor for Squaraine Dyes Enabling Ultrafast Dark Resonance Energy Transfer

ABSTRACT A metal‐organic cage was obtained by combining acridone‐based dipyridyl ligands with Pd 2+ ions. The cage acts as a potent receptor for squaraine dyes, with a pronounced preference for guests with 2,6‐dihydroxyphenyl substituents. This selectivity profile differs from that of previously reported receptors for squaraine dyes. The acridone‐based cage itself is non‐emissive. Upon its photoexcitation, ultrafast (sub‐ps) dark resonance energy transfer (DRET) to the encapsulated squaraine dyes was observed, resulting in bright, near‐infrared guest emission, with pseudo‐Stokes shifts of up to 440 nm. Upon binding of a chiral dye, chirality transfer to the host could be evidenced by circular dichroism spectroscopy.

Timing of therapeutic hypothermia and outcomes in neonates with hypoxic-ischemic encephalopathy: A cohort study in a middle-income country

Background Therapeutic hypothermia improves survival and neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy when initiated within 6 hours of birth. However, in low- and middle-income countries, delays in referral and access to tertiary care often preclude early initiation and the benefits of therapeutic hypothermia beyond the recommended window remain uncertain. We aimed to assess whether initiating therapeutic hypothermia between 6 and 12 hours after birth is associated with a higher risk of mortality and/or brain injury than initiation within 6 hours in neonates with moderate or severe hypoxic-ischemic encephalopathy. Methods We conducted a retrospective cohort study of 173 neonates with moderate or severe hypoxic-ischemic encephalopathy treated with servo-controlled whole-body therapeutic hypothermia at a tertiary care center in Colombia. Neonates were categorized based on the timing of therapeutic hypothermia initiation as ≤6 h or >6–12 h after birth. The primary outcome was a composite of in-hospital mortality and/or brain injury confirmed by magnetic resonance imaging during the first week of life. Multivariate logistic regression was used to adjust for confounding variables. Results Of the 173 neonates, 44.5% received therapeutic hypothermia within 6 hours and 55.5% after 6–12 hours. A composite outcome was observed in 40.6% of the patients. Delayed therapeutic hypothermia was not significantly associated with an increased risk of the composite outcome compared to early initiation (adjusted odds ratio [OR]: 1.83; 95% CI: 0.86–3.90). Seizures and severe hypoxic-ischemic encephalopathy were found to be independent predictors of adverse outcomes. Conclusions In this cohort, initiation of therapeutic hypothermia between 6 and 12 h after birth was not significantly associated with worse neurological or mortality outcomes than initiation within 6 h. These findings suggest that delayed therapeutic hypothermia may still confer benefits in settings where early initiation is challenging, underscoring the need to strengthen referral systems and further investigate the optimal therapeutic window.

A hybrid convolution and attention-based framework with visual explanation for fruit disease identification

Abstract The objective of this study is to create a highly accurate and interpretable deep learning (DL) model for the multi-class classification of fruit using convolutional and transformer architectures. The classification performance can be enhanced by making sure that the used technique is explainable and interpretable. This research data was obtained from Kaggle which contains images of banana, grape, lemon, mango, and strawberry fruit classes. The total data was divided into 70:15:15 for training, validating and testing. To ensure consistent size and quality, all images were pre-processed before use. This study considered four pretrained models namely RegNetY-B3-GE, DarkNet53-SCSE, BEiT, and PVTv2 for performance assessment. We proposed a lightweight hybrid (convolution plus attention-based) CoAT-AgriLite model for fruit disease classification which extracts local lesion features and global context. Transferring training and data augmentation technique was utilized during training for better performance. To ensure interpretability of model decisions, Gradient-weighted Class Activation Mapping (Grad-CAM) which captures the discriminative regions from the input images for model predictions. Among all evaluated models, the proposed model achieved the highest classification accuracy of 99.37% on the testing dataset. Comparative results demonstrated that the proposed model outperformed other pretrained models in terms of precision, recall, and F1-score, confirming its robustness and effectiveness in real-world agricultural classification tasks. The experimental findings validate that the proposed model not only achieves superior classification accuracy but also provides interpretability through Grad-CAM visualizations. This hybrid framework offers a promising solution for intelligent and transparent fruit classification systems, with potential applications in precision agriculture and automated sorting systems.

Living Polymerization Strategy for Conjugated Multiblock Copolymers: A Systematic Study of Structure–Property Relationships in Stretchability and Charge Transport

ABSTRACT Achieving high mechanical stretchability while maintaining charge carrier mobility in semiconducting polymers remains a central challenge due to their intrinsic trade‐off. Conjugated multiblock copolymers (CMPs) incorporating semiconducting and elastomeric segments represent a promising design strategy to overcome this limitation, yet a systematic understanding of how structural parameters influence material properties and device performances is still lacking. To address this issue, we chose a model polymer, poly(3‐hexylthiophene) (P3HT), and systematically constructed its library precursors with independently varied molecular weight, dispersity, and end‐group fidelity. Then, these precursors were incorporated into CMPs containing flexible polydimethylsiloxane (PDMS) over a broad composition range (0–75 mol%). As a result, this design enabled deconvolution of the individual effects of each structural parameter on CMP performance. Notably, CMPs incorporating well‐defined P3HT blocks exhibited significantly enhanced stretchability (>300%) while retaining high hole mobility, in contrast to those prepared using P3HT from uncontrolled polymerization. These results underscore the advantage of living polymerization in precisely tailoring conjugated polymer architectures and optimizing the mechanical and electronic properties of stretchable semiconducting materials, while also offering a platform that may be extended to other conjugated polymers.

Identification of core genes mediating the association between obesity and hepatocellular carcinoma: A bioinformatics study based on mitochondrial metabolism and immune pathways

Purpose Obesity is strongly associated with hepatocellular carcinoma (HCC), yet the molecular mechanisms linking them remain unclear. This study aimed to identify mitochondrial metabolism-related genes bridging obesity and HCC and to investigate their role in regulating the metabolic-immune microenvironment. Methods Public transcriptomic datasets from obesity (derived from peripheral blood mononuclear cells) and HCC (derived from liver tissue) cohorts were integrated. A multi-step bioinformatic pipeline combining differential expression analysis (DEA), weighted gene co-expression network analysis (WGCNA), and machine learning (ML) algorithms was applied to identify and validate hub genes. Associations with the tumor immune microenvironment were assessed using ssGSEA and correlation analyses. Results 27 core genes were identified, significantly enriched in lipid metabolism and immune response pathways. Among these, ML highlighted ACAA1 and ADI1 as downregulated candidate genes. While discovery datasets showed high diagnostic potential, ADI1 exhibited more variable performance in obesity external validation compared to the robust consistency of ACAA1 . Downregulation of both genes correlated with effector T/NK cell lipid-mediated functional exhaustion and disrupted networks of immune checkpoints and chemokines, reflecting an immunosuppressive microenvironment. Conclusions ACAA1 and potentially ADI1 are downregulated candidate genes linking obesity to HCC. Their suppression likely drives obesity-related HCC progression by coupling mitochondrial metabolic reprogramming with immunosuppressive tumor microenvironment remodeling, representing potential therapeutic targets.

Diversity of culturable gut bacteria associated with brown planthopper, Nilaparvata lugens (Stål) and their role in imidacloprid degradation

Area‐Selective Atomic Layer Deposition of AlO _x at the Buried Interface for High‐Performance Perovskite Solar Cells

ABSTRACT Self‐assembled monolayers (SAM) have demonstrated significant potential for enhancing the performance of perovskite solar cells (PSCs). However, their incomplete surface coverage exposes defect sites on the NiO x surface, leading to detrimental non‐radiative recombination and exacerbating the perovskite degradation. To overcome these limitations, we developed a strategy of area‐selective atomic layer deposition (AS‐ALD) that precisely deposits an ultrathin AlO x layer on exposed NiO x surfaces while preserving SAM‐covered areas. This approach effectively suppresses charge recombination by blocking direct contact between NiO x and the perovskite while leveraging the intrinsic negative fixed charges in AlO x to attract holes and repel electrons. Importantly, the SAM‐covered areas remain unaffected, ensuring unhindered carrier extraction. Additionally, the deposited AlO x reduces the deleterious Ni 4+ content, which can readily trigger perovskite decomposition, thereby significantly enhancing device performance and stability. As a result, the PCE of PSCs increased to 26.41%, with perovskite modules achieving 20.88% efficiency over a 64.68 cm 2 active area. Device stability significantly improved with ∼ 95% initial PCE retained after 1500 h dark storage (ISOS‐D‐1), ∼ 80% after 800 h at 85°C (ISOS‐D‐2), ∼ 85% after 48 thermal cycles (ISOS‐T‐1), and ∼ 90% after 1300 h continuous 1‐sun illumination (ISOS‐L‐1, MPPT).