Multiple Evolutionary Events in Host Plant Adaptation in Lepidoptera

Plant Cell & Environment · 2026-03-29

The evolution of insect host adaptation is a key component of insect-plant coevolution, a complex process often shaped by multiple evolutionary events. In this study, we identified two UDP-glycosyltransferase (UGT) genes, SfruUGT33T10 and SfruUGT33F32, in the fall armyworm Spodoptera frugiperda, which are essential for tolerance to benzoxazinoids (BXs), key secondary metabolites in maize. These two detoxification enzymes exhibited distinct glycosylation patterns for BXs and varying detoxification efficiencies, reflecting independent evolutionary trajectories. Evolutionary analyses revealed that SfruUGT33T10 originated independently within Noctuidae, while SfruUGT33F32 resulted from tandem duplication within the UGT33F gene family and may have undergone neofunctionalization within the Spodoptera genus. Our findings provide evidence that the evolution of these two UGT paralogs contributed to the variation in the tolerance to maize BXs among different lepidopteran species. This research underscores the significance of multiple independent evolutionary routes in host plant adaptation and offers new insights into the complex evolutionary processes underlying insect-plant interactions.

DocShaDiffusion: Diffusion Model in Latent Space for Document Image Shadow Removal

ArXiv.org · 2025-07-02

Document shadow removal is a crucial task in the field of document image enhancement. However, existing methods tend to remove shadows with constant color background and ignore color shadows. In this paper, we first design a diffusion model in latent space for document image shadow removal, called DocShaDiffusion. It translates shadow images from pixel space to latent space, enabling the model to more easily capture essential features. To address the issue of color shadows, we design a shadow soft-mask generation module (SSGM). It is able to produce accurate shadow mask and add noise into shadow regions specially. Guided by the shadow mask, a shadow mask-aware guided diffusion module (SMGDM) is proposed to remove shadows from document images by supervising the diffusion and denoising process. We also propose a shadow-robust perceptual feature loss to preserve details and structures in document images. Moreover, we develop a large-scale synthetic document color shadow removal dataset (SDCSRD). It simulates the distribution of realistic color shadows and provides powerful supports for the training of models. Experiments on three public datasets validate the proposed method's superiority over state-of-the-art. Our code and dataset will be publicly available.

Differences in Brain Entropy and Cognitive Function Between Mild TBI Patients and Healthy Controls: A Longitudinal Perspective

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

Motivation: Mild traumatic brain injury (mTBI) often leads to long-term physical, cognitive, and emotional challenges. Resting-state fMRI studies have shown functional brain changes in mTBI, but a comprehensive understanding of brain alterations remains limited. Goal(s): This study aims to examine brain entropy (BEN) in mTBI patients over time, exploring its potential association with neurocognition and recovery. Approach: Using longitudinal rs-fMRI data, we assessed BEN —a novel metric linked to brain function and pathology —in mTBI patients, analyzing changes from the acute to chronic phases. Results: Our preliminary results suggest increased BEN during the acute phase of mTBI, with normalization as cognitive function improves over time. Impact: This study positions brain entropy (BEN) as a potential biomarker for tracking recovery in mTBI. BEN's sensitivity to acute functional changes and its normalization with cognitive improvement could enhance diagnostic precision and inform therapeutic interventions in mTBI management.

<i>Streptococcus salivarius</i> -derived ilexgenin A alleviates pneumonia through the gut-lung axis

mSystems · 2025-07-30

ABSTRACT The alteration of gut microbiota during critical illness is associated with adverse clinical outcomes. This connection between intestinal dysbiosis and poor outcomes has prompted the idea that restoring healthy microbial communities could offer a novel approach to life-support treatment for patients with severe pneumonia. In this study, using 16S rRNA sequencing and fecal microbiota transplantation (FMT), we demonstrated that alterations in intestinal microbiota structure during pneumonia exacerbate disease outcomes. A notable feature of these alterations is the reduction in the relative levels of Streptococcus salivarius ( S. salivarius ). In combination with metabolomics analysis, we found that the administration of S. salivarius increased the level of ilexgenin A (IA) in mice, which enhances the resistance of mice to Pseudomonas aeruginosa ( P. aeruginosa )-induced pneumonia. Mechanistically, IA regulates lipopolysaccharide-induced overexpression of macrophage inflammation through Toll-like receptor 4 (TLR4)-mediated NF-κB and MAPK signaling pathways. Our findings reveal the role of the microbial–immune axis in pneumonia, highlighting the potential of S. salivarius and IA in providing promising treatment strategies for pneumonia. IMPORTANCE One of the major challenges faced by the clinical microbiome research community is to convert the connections between dysbiosis and negative clinical outcomes into rationalized and targeted therapeutic interventions. In the present work, 30 fecal samples from pneumonia and non-pneumonia patients were subjected to FMT and 16S rRNA analysis. The results revealed that a characteristic feature of gut microbiota dysbiosis in pneumonia hosts is the reduction of S. salivarius . Supplementation with S. salivarius can effectively enhance the resistance of mice to P. aeruginosa pneumonia. Moreover, we confirmed the anti-inflammatory effects of IA derived from S. salivarius both in vivo and in vitro . Thus, these findings enhance our understanding of how gut microbiota influences the outcomes of pneumonia and underscore the potential of S. salivarius as a precision microbial therapeutic for combating pneumonia.

QEI-Net: A Deep learning-based automated quality evaluation index for ASL CBF Maps

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

Motivation: Arterial Spin Labeling (ASL) cerebral blood flow (CBF) maps can be noisy, which can bias statistical results. Quality control (QC) by visual inspection is subjective and time-consuming. Automated objective QC addresses these limitations, but previous methods lacked consistency across datasets. Goal(s): Develop a deep learning model (QEI-Net) to derive a robust quality evaluation index (QEI) for ASL CBF maps. Approach: We trained QEI-Net on manually rated multi-protocol ASL datasets and compared QEI-Net with both manual ratings and the previous state-of-the-art method. Results: QEI-Net strongly correlated with manual ratings and outperformed the reference approach. This provides reliable and reproducible assessments suitable for large-scale studies. Impact: We propose QEI-Net, a deep learning based automated quality evaluation method for Arterial Spin Labeling (ASL) derived cerebral blood flow images. QEI-Net can enable consistent and reproducible quality assessments and reduce the time burden and subjectivity in studies using ASL.

Oligodendrocyte Egr2 Mediates the Beneficial Effect of Resocialization on the Social Ability of Socially Isolated Mice

Neuroscience Bulletin · 2025-11-06 · 1 citations

Early social isolation (SI) impairs social ability, which can be partially rescued after resocialization, but the underlying mechanisms have been rarely addressed. This study reported that adolescent SI mice resocialized with group housing (GH) mice, but not with SI mice, showed improved social behavior performances, increased myelination in the medial prefrontal cortex (mPFC), and upregulated Egr2 expression in oligodendrocytes (OLs). Specific down-regulation of OL Egr2 in GH companions or overexpression of OL Egr2 in SI peers abolished or rescued their repair effects on mPFC hypomyelination and social ability defects in SI mice, respectively. Furthermore, the improving effect of GH companions on OL Egr2 expression and myelinogenesis in the mPFC of SI mice was abolished when GH mice were treated with corticosterone. RNA-sequencing analysis showed that Egr2 enhanced myelination by inhibiting PDGFRα. Together, these results revealed that the Egr2/PDGFRα axis mediates distinct peer effects in rescuing SI-induced hypomyelination and social ability impairment.

MLC-GCN: Multi-Level Connectomes Based GCN for AD Detection

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

Motivation: Alzheimer's Disease (AD) is characterized by progressive cognitive impairments that are related to alterations in brain functional connectivity (FC). Goal(s): to design a graph convolutional network (GCN) based classifier to differentiate AD from old cognitive normal controls. Approach: We assessed the FC using Pearson correlation coefficient (CC) and cross entropy (CE) measure as association analysis and proposed a multi-level generated connectome (MLC) based GCN (MLC-GCN) containing a multi-graph generation block and a GCN prediction block to classify the fMRI data. Results: Our method showed better performance than state-of-the-art GCN and rsfMRI based AD classifiers on two independent public medical datasets: ADNI and OASIS-3. Impact: The MLC-GCN classifier significantly enhances Alzheimer's disease detection by exploiting multi-level connectomes. The clinically meaningful classifier features suggest a potential of localizing disease-related nodes or regions, facilitating clinical diagnosis and future targeted interventions.

Development of radiolabeling 2-oxo-2-(4-phenylpiperazin-1-yl)acetamide derivatives as potential molecular probes for excitatory amino acid transporter 2

European Journal of Medicinal Chemistry · 2025-07-16

Age-dependent effects of intranasal oxytocin administration were revealed by resting brain entropy (BEN)

Behavioural Brain Research · 2025-12-06 · 1 citations

Sleep effects on brain, cognition, and mental health during adolescence are mediated by the glymphatic system.

PubMed · 2025-12-09

Background: Adolescence is a critical period of brain maturation and heightened vulnerability to cognitive and mental health disorders. Sleep plays a vital role in neurodevelopment, yet the mechanisms linking insufficient sleep to adverse brain and behavioral outcomes remain unclear. The glymphatic system (GS), a brain-wide clearance pathway, may provide a key mechanistic link. Methods: Leveraging baseline data from the Adolescent Brain Cognitive Development (ABCD) Study, we examined whether GS function mediates the effects of sleep on brain structure, cognition, and mental health. GS function was indexed by perivascular space (PVS) burden derived from structural MRI. Participants (n ≈ 6,800; age ≈ 11 years) were categorized into sleep-sufficient (≥9 h/night) and sleep-insufficient (<9 h/night) groups. Linear models tested associations among sleep, PVS burden, brain volumes, and behavioral outcomes. Mediation analyses evaluated whether PVS burden explained sleep-related effects. Results: ). Mediation analyses revealed that PVS burden partially mediated sleep effects on cognition (e.g., crystallized intelligence, episodic memory) and mental health (e.g., psychosis severity), with indirect proportions up to 10.9%. Sequential models suggested a pathway from sleep → PVS → brain volume → behavior as the most plausible route. Conclusions: Insufficient sleep during adolescence is linked to glymphatic dysfunction, reflected by increased PVS burden, which partially accounts for adverse effects on brain structure, cognition, and mental health. These findings highlight the glymphatic system as a potential mechanistic pathway and imaging biomarker, underscoring the importance of promoting adequate sleep to support neurodevelopment and mental health.