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Activation of microglia by classical inflammatory mediators can convert astrocytes into a neurotoxic A1 phenotype in a variety of neurological diseases 1 , 2 . Development of agents that could inhibit the formation of A1 reactive astrocytes could be used to treat these diseases for which there are no disease-modifying therapies. Glucagon-like peptide-1 receptor (GLP1R) agonists have been indicated as potential neuroprotective agents for neurologic disorders such as Alzheimer’s disease and Parkinson’s disease 3 – 13 . The mechanisms by which GLP1R agonists are neuroprotective are not known. Here we show that a potent, brain-penetrant long-acting GLP1R agonist, NLY01, protects against the loss of dopaminergic neurons and behavioral deficits in the α-synuclein preformed fibril (α-syn PFF) mouse model of sporadic Parkinson’s disease 14 , 15 . NLY01 also prolongs the life and reduces the behavioral deficits and neuropathological abnormalities in the human A53T α-synuclein (hA53T) transgenic mouse model of α-synucleinopathy-induced neurodegeneration 16 . We found that NLY01 is a potent GLP1R agonist with favorable properties that is neuroprotective through the direct prevention of microglial-mediated conversion of astrocytes to an A1 neurotoxic phenotype. In light of its favorable properties, NLY01 should be evaluated in the treatment of Parkinson’s disease and related neurologic disorders characterized by microglial activation. Agonism of microglial glucagon-like peptide-1 receptor (GLP1R) using a brain-penetrant peptide prevents the generation of neurotoxic astrocytes and ameliorates disease progression in two rodent models of Parkinson’s disease.

Crop diseases significantly threaten agricultural productivity, leading to unstable food supply and economic losses. The current approaches to automated crop disease recognition face challenges such as limited datasets, restricted coverage of disease types, and inefficient feature extraction, which hinder their generalization across diverse crops and disease patterns. To address these challenges, we propose an efficient data augmentation method to enhance the performance of deep learning models for crop disease recognition. By constructing a new large-scale dataset comprising 24 different classes, including both fruit and leaf samples, we intend to handle a variety of disease patterns and improve model generalization capabilities. Geometric transformations and color space augmentation techniques are applied to validate the efficiency of deep learning models, specifically convolution and transformer models, in recognizing multiple crop diseases. The experimental results show that these augmentation techniques improve classification accuracy, achieving F1 scores exceeding 98%. Feature map analysis further confirms that the models effectively capture key disease characteristics. This study underscores the importance of data augmentation in developing automated, energy-efficient, and environmentally sustainable crop disease detection solutions, contributing to more sustainable agricultural practices.

Plant diseases are a major cause of reduction in agricultural output, which leads to severe economic losses and unstable food supply. The citrus plant is an economically important fruit crop grown and produced worldwide. However, citrus plants are easily affected by various factors, such as climate change, pests, and diseases, resulting in reduced yield and quality. Advances in computer vision in recent years have been widely used for plant disease detection and classification, providing opportunities for early disease detection, and resulting in improvements in agriculture. Particularly, the early and accurate detection of citrus diseases, which are vulnerable to pests, is very important to prevent the spread of pests and reduce crop damage. Research on citrus pest disease is ongoing, but it is difficult to apply research results to cultivation owing to a lack of datasets for research and limited types of pests. In this study, we built a dataset by self-collecting a total of 20,000 citrus pest images, including fruits and leaves, from actual cultivation sites. The constructed dataset was trained, verified, and tested using a model that had undergone five transfer learning steps. All models used in the experiment had an average accuracy of 97% or more and an average f1 score of 96% or more. We built a web application server using the EfficientNet-b0 model, which exhibited the best performance among the five learning models. The built web application tested citrus pest disease using image samples collected from websites other than the self-collected image samples and prepared data, and both samples correctly classified the disease. The citrus pest automatic diagnosis web system using the model proposed in this study plays a useful auxiliary role in recognizing and classifying citrus diseases. This can, in turn, help improve the overall quality of citrus fruits.

Alzheimer’s disease (AD) is the most common cause of age-related dementia. Increasing evidence suggests that neuroinflammation mediated by microglia and astrocytes contributes to disease progression and severity in AD and other neurodegenerative disorders. During AD progression, resident microglia undergo proinflammatory activation, resulting in an increased capacity to convert resting astrocytes to reactive astrocytes. Therefore, microglia are a major therapeutic target for AD and blocking microglia-astrocyte activation could limit neurodegeneration in AD. Here we report that NLY01, an engineered exedin-4, glucagon-like peptide-1 receptor (GLP-1R) agonist, selectively blocks β-amyloid (Aβ)-induced activation of microglia through GLP-1R activation and inhibits the formation of reactive astrocytes as well as preserves neurons in AD models. In two transgenic AD mouse models (5xFAD and 3xTg-AD), repeated subcutaneous administration of NLY01 blocked microglia-mediated reactive astrocyte conversion and preserved neuronal viability, resulting in improved spatial learning and memory. Our study indicates that the GLP-1 pathway plays a critical role in microglia-reactive astrocyte associated neuroinflammation in AD and the effects of NLY01 are primarily mediated through a direct action on Aβ-induced GLP-1R + microglia, contributing to the inhibition of astrocyte reactivity. These results show that targeting upregulated GLP-1R in microglia is a viable therapy for AD and other neurodegenerative disorders.

Extensive studies have led to a variety of hypotheses for the molecular basis of depression and related mood disorders, but a definite pathogenic mechanism has yet to be defined. The monoamine hypothesis, in conjunction with the efficacy of antidepressants targeting monoamine systems, has long been the central topic of depression research. While it is widely embraced that the initiation of antidepressant efficacy may involve acute changes in monoamine systems, apparently, the focus of current research is moving toward molecular mechanisms that underlie long-lasting downstream changes in the brain after chronic antidepressant treatment, thereby reaching for a detailed view of the pathophysiology of depression and related mood disorders. In this minireview, we briefly summarize major themes in current approaches to understanding mood disorders focusing on molecular views of depression and antidepressant action.

Background Mutations in glucocerebrosidase (GBA) cause Gaucher disease (GD) and increase the risk of developing Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB). Since both genetic and environmental factors contribute to the pathogenesis of sporadic PD, we investigated the susceptibility of nigrostriatal dopamine (DA) neurons in L444P GBA heterozygous knock-in (GBA +/L444P ) mice to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), a selective dopaminergic mitochondrial neurotoxin. Method We used GBA +/L444P mice, α-synuclein knockout (SNCA −/− ) mice at 8 months of age, and adeno-associated virus (AAV)-human GBA overexpression to investigate the rescue effect of DA neuronal loss and susceptibility by MPTP. Mitochondrial morphology and functional assay were used to identify mitochondrial defects in GBA +/L444P mice. Motor behavioral test, immunohistochemistry, and HPLC were performed to measure dopaminergic degeneration by MPTP and investigate the relationship between GBA mutation and α-synuclein. Mitochondrial immunostaining, qPCR, and Western blot were also used to study the effects of α-synuclein knockout or GBA overexpression on MPTP-induced mitochondrial defects and susceptibility. Results L444P GBA heterozygous mutation reduced GBA protein levels, enzymatic activity and a concomitant accumulation of α-synuclein in the midbrain of GBA +/L444P mice. Furthermore, the deficiency resulted in defects in mitochondria of cortical neurons cultured from GBA +/L444P mice. Notably, treatment with MPTP resulted in a significant loss of dopaminergic neurons and striatal dopaminergic fibers in GBA +/L444P mice compared to wild type (WT) mice. Levels of striatal DA and its metabolites were more depleted in the striatum of GBA +/L444P mice. Behavioral deficits, neuroinflammation, and mitochondrial defects were more exacerbated in GBA +/L444P mice after MPTP treatment. Importantly, MPTP induced PD-like symptoms were significantly improved by knockout of α-synuclein or augmentation of GBA via AAV5-hGBA injection in both WT and GBA +/L444P mice. Intriguingly, the degree of reduction in MPTP induced PD-like symptoms in GBA +/L444P α-synuclein (SNCA) −/− mice was nearly equal to that in SNCA −/− mice after MPTP treatment. Conclusion Our results suggest that GBA deficiency due to L444P GBA heterozygous mutation and the accompanying accumulation of α-synuclein render DA neurons more susceptible to MPTP intoxication. Thus, GBA and α-synuclein play dual physiological roles in the survival of DA neurons in response to the mitochondrial dopaminergic neurotoxin, MPTP.

The uneven deposition at the edges of an evaporating droplet, termed the coffee-ring effect, has been extensively studied during the past few decades to better understand the underlying cause, namely the flow dynamics, and the subsequent patterns formed after drying. The non-uniform evaporation rate across the colloidal droplet hampers the formation of a uniform and homogeneous film in printed electronics, rechargeable batteries, etc., and often causes device failures. This review aims to highlight the diverse range of techniques used to alleviate the coffee-ring effect, from classic methods such as adding chemical additives, applying external sources, and manipulating geometrical configurations to recently developed advancements, specifically using bubbles, humidity, confined systems, etc., which do not involve modification of surface, particle or liquid properties. Each of these methodologies mitigates the edge deposition via multi-body interactions, for example, particle–liquid, particle-particle, particle–solid interfaces and particle–flow interactions. The mechanisms behind each of these approaches help to find methods to inhibit the non-uniform film formation, and the corresponding applications have been discussed together with a critical comparison in detail. This review could pave the way for developing inks and processes to apply in functional coatings and printed electronic devices with improved efficiency and device yield.

Lab-on-a-CD (LOCD) is gaining importance as a diagnostic platform due to being low-cost, easy-to-use, and portable. During LOCD usage, mixing and reaction are two processes that play an essential role in biochemical applications such as point-of-care diagnosis. In this paper, we numerically and experimentally investigate the effects of the Coriolis and Euler forces in the mixing chamber during the acceleration and deceleration of a rotating disk. The mixing performance is investigated under various conditions that have not been reported, such as rotational condition, chamber aspect ratio at a constant volume, and obstacle arrangement in the chamber. During disk acceleration and deceleration, the Euler force difference in the radial direction causes rotating flows, while the Coriolis force induces perpendicular vortices. Increasing the maximum rotational velocity improves the maximum rotational displacement, resulting in better mixing performance. A longer rotational period increases the interfacial area between solutions and enhances mixing. Mixing performance also improves when there is a substantial difference between Euler forces at the inner and outer radii. Furthermore, adding obstacles in the angular direction also passively promotes or inhibits mixing by configuration. This quantitative investigation provides valuable information for designing and developing high throughput and multiplexed point-of-care LOCDs.

The gut microbiome is essential for the health of carnivorous mammals, including the endangered Siberian tiger (Panthera tigris altaica). However, limited research exists on the gut microbiome of captive Siberian tigers, especially regarding how diet and health status influence microbial diversity. This study addresses this gap by investigating the gut microbiome diversity and composition of six captive-born Siberian tigers housed at the Baekdudaegan National Arboretum in South Korea, using 16S rRNA gene sequencing. The study aimed to examine how diet and health status influence microbial communities, providing baseline data for managing captive tigers. Alpha diversity analysis revealed significant variation in microbial richness and evenness, with Tigers 2 and 6 exhibiting the highest microbial diversity and Tiger 3 the lowest, likely due to its surgical history and limited diet. Beta diversity analysis showed distinct microbial community structures influenced by diet and health. Taxonomic profiling identified Firmicutes and Bacteroidota as the dominant phyla, with Clostridium sensu stricto more prevalent in healthier tigers, while Escherichia-Shigella and Proteobacteria were abundant in tigers with lower diversity, suggesting dysbiosis. Comparisons with other tiger species confirm that diet, health, and captivity significantly shape the gut microbiome. These findings highlight the need for personalized health management in captive environments.

The gut microbiome plays a crucial role in the health and physiology of tigers (Panthera tigris), influencing digestion, immune function, and overall well-being. While numerous studies have characterized the gut microbiota of domestic carnivores and some wild felids, comparative analyses across different tiger subspecies under varying environmental contexts remain limited. In this exploratory study, we investigated the gut microbiome diversity and composition of 15 captive tigers, including both Siberian (P. tigris altaica) and Bengal (P. tigris tigris) subspecies, housed in two different regions in Korea. Using 16S rRNA gene sequencing of fecal samples, we analyzed microbial diversity across multiple taxonomic levels. Preliminary analyses revealed significant differences in microbial composition between geographic locations, whereas sex-based differences appeared minimal. Alpha and beta diversity metrics demonstrated substantial inter-individual variability, likely influenced by regional and environmental factors. Given the small sample size and the confounding between subspecies and housing location, the findings should be regarded as preliminary and not generalized beyond this specific cohort. Nevertheless, these insights highlight the potential utility of gut microbiome profiling for health monitoring and management in captive-tiger populations. Future research incorporating larger, more diverse cohorts will be essential to validate these trends and clarify the roles of diet, health status, and enrichment in shaping the gut microbiota.