Biology subjects

Kuang, W.

Publications and source records attributed to Kuang, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Leveraging Pretrained Vision Transformers for classifying Alcohol Use Disorder using Raw Resting-State EEG

Alcohol Use Disorder (AUD) is a prevalent and debilitating neuropsychiatric condition characterized by compulsive alcohol consumption, impaired control, and negative emotional states, affecting about 28 million adults in the United States. Despite its significant public health burden, there are few objective biomarkers and no reliable neurophysiological tools to assist in its clinical diagnosis. In this study, we investigated the potential of deep learning to classify individuals with AUD using raw resting-state electroencephalogram (EEG) data. EEG recordings were obtained from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, longitudinal, multi-site dataset. The initial cohort included a total of 5,402 recordings from 2,710 participants (aged 12-83, mean age 24; 1,338 males and 1,372 females). To reduce confounding factors, we applied demographic matching, and to address class imbalance, we applied undersampling. Minimal preprocessing was applied to preserve the raw EEG features. We utilized EEGViT, a hybrid deep learning architecture that combines convolutional patch embedding with a Vision Transformer (ViT) pretrained on ImageNet, thereby enabling end-to-end learning directly from raw EEG input. The analysis was stratified by sex and age, and all groups were age-matched. To validate the generalization of the model, models were also trained for Cannabis Use Disorder (CUD) and Opioid Use Disorder (OUD). Results for the AUD model showed a classification accuracy of approximately 56% in the overall dataset, 54% for males, and 58% for females. The CUD model showed an accuracy of about 63% with 59% for females and 69% for males. The OUD model showed an accuracy of about 63% with 61% for females and 65% for males. Temporal analysis indicated that the models performance varied across time intervals, with higher accuracy observed in later minutes compared to earlier ones. While modest, these findings underscore the potential of transformer-based models in psychiatric classification using raw EEG data and provide a foundation for future development of EEG-based diagnostic tools for AUD.

neuroscience↗

bioRxiv2025

Structure and function of the nairovirus cap-snatching endonuclease

Nairoviruses include several human pathogens such as Crimean-Congo hemorrhagic fever virus (CCHFV) and Kasokero virus (KASV). The cap-snatching endonuclease (EN) domain of the viral polymerase is essential for transcription and represents a promising antiviral target. However, the structural and functional mechanisms of nairovirus ENs remain poorly understood. Here, we describe biochemical and structural studies of the ENs from CCHFV and KASV. Biochemical assays demonstrate that the RNA endonuclease activity of both ENs is activated by manganese ions and exhibits a preference for uridine-rich RNA substrates. This activity is inhibited by three metal-chelating inhibitors (DPBA, L-742,001, and BXA), with BXA displaying the highest binding affinity and inhibitory potency. We further determine nine crystal structures of CCHFV and KASV ENs in apo, metal ion-bound, and inhibitor-bound states. Comparative structural analysis uncovers a two-metal-ion binding mode unique to nairovirus ENs, in which conserved residues coordinate two manganese ions via bridging water molecules. In the inhibitor-bound structures of KASV EN, BXA forms additional stabilizing interactions with the enzyme, explaining its superior inhibitory effect. Functional assays further confirm that the two-metal-ion mechanism is critical for viral transcription. These findings provide a structural foundation for the rational design of antivirals against CCHFV and related pathogens.

microbiology↗

bioRxiv2025

Neuroanatomical features reveal accelerated brain age in alcohol use disorder

Background/ObjectivesBrain age is a novel measure to characterize the integrity of neurocognitive functioning and brain health in various psychiatric and neurological disorders. Although there is a literature suggesting premature aging of the brain in individuals with alcohol use disorder (AUD), studies directly examining brain age are rare. Therefore, the current study was designed to estimate brain age in AUD individuals using brain morphological features, such as cortical thickness and brain volume. MethodsThe sample included a group of 30 adult males with a history of AUD but maintaining abstinence and a group of 30 male controls without any history of AUD. Brain age was computed using an XGBoost regression model with 187 brain morphological features of cortical thickness and brain volume as predictors. An exploratory correlational analysis between brain age measures and features of neuropsychological performance, impulsivity, and alcohol consumption was also performed. ResultsFindings revealed that AUD individuals showed an increase of 1.70 years in their brain age relative to their chronological age. Further, in the AUD group, higher brain age was significantly associated with poor executive functioning, while a larger gap between brain age and actual age was associated with lower non-planning impulsivity and later age of onset for regular drinking in those with AUD. ConclusionsAUD individuals manifested accelerated brain aging, possibly representing compromised brain health. Brain age measures were found to be associated with some of the measures of neurocognition, impulsivity, and alcohol consumption. These findings may have important implications for the early identification, prevention, and treatment of AUD. However, future studies with larger sample sizes are needed to confirm these preliminary findings.

neuroscience↗

bioRxiv2025

Alcohol use disorder is associated with increases in frontocentral phase-amplitude coupling strength during resting state

Considerable evidence from functional neuroimaging and EEG coherence studies indicates that individuals afflicted with alcohol use disorder (AUD) manifest aberrant patterns of connectivity, particularly in frontal brain regions. Phase-amplitude coupling (PAC) is another form of functional connectivity, reflecting the association between the phase at one frequency and amplitude changes at a higher frequency. Significant PAC differences have been reported for other substance use disorders, but it has not yet been investigated in AUD. We compared frontomedial PAC strength during resting state, eyes closed, in adult participants with severe AUD and age-matched unaffected controls from the Collaborative Study on the Genetics of Alcoholism (COGA). Comodulograms of PAC estimates between phase frequencies (0.1-13 Hz) and amplitude frequencies (4-50 Hz) were calculated for all participants. PAC differences between AUD and unaffected groups were assessed at each phase-amplitude frequency pair in comodulograms to identify clusters of significant test results, reporting only those clusters satisfying all validation and significance testing steps. Severe AUD was associated with clusters of significantly greater PAC in alpha-gamma domains of both men and women. Candidate clusters were found in theta-gamma domains of both sexes, but were only significant greater in men with AUD. Significant PAC clusters were found in the delta-gamma domain of both sexes, though women with AUD showed significant decreases in contrast to greater PAC found in men with AUD. The significant PAC clusters identified in this exploratory study could provide new insights into the dysregulation of brain connectivity underlying AUD.

neuroscience↗

bioRxiv2025

Metabolic modulation of intratumoral cholesterol with gut microbiota for the treatment of colorectal cancer

Excess cholesterol is positively correlated with colorectal cancer (CRC). Current therapeutic strategies for modulating cholesterol levels in CRC are limited and often come with complications. Here, we demonstrated that microbiome shunting of intestinal cholesterol to anticancer metabolites is a safe and applicable therapeutic approach for CRC. By screening major microbial metabolic products of cholesterol, we found that 4-cholesten-3-one (4-C-3) was selectively depleted in fecal samples and tumor tissues of patients with CRC. 4-C-3 exhibits strong antitumor effects on human CRC cell lines, patient-derived organoids, and patient-derived xenograft (PDX) models. Mechanistically, 4-C-3 suppresses CRC tumorigenesis by dually targeting the epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homologue (KRAS). 4-C-3 directly binds to EGFR, blocking its signal transduction by inhibiting the binding of EGFR ligands. Additionally, 4-C-3 inhibits oncogenic KRAS variants, such as KRASG12D, by suppressing nucleotide exchange activity and effector engagement. By targeting both EGFR and KRAS, 4-C-3 reduces primary resistance to anti-EGFR therapies caused by KRAS mutations in CRC. As a proof-of-concept study, we showed that delivery of 4-C-3 by Oscillibacter ruminantium, a 4-C-3- producing commensal bacterium that is reduced in CRC patients, or a nonpathogenic Escherichia coli strain engineered to specifically convert intestinal cholesterol into 4-C-3, removed intratumoral cholesterol and led to rapid tumor regression in multiple models of CRC. These results suggest that microbial therapies for restoring intestinal cholesterol homeostasis represent a new therapeutic avenue for CRC.

cancer biology↗

bioRxiv2025

Reward Network Activations of Win versus Loss in a Monetary Gambling Task

Reward processing is a vital function for health and survival and is impaired in various psychiatric and neurological disorders. Using a monetary gambling task, the current study aims to elucidate neural substrates in the reward network underlying evaluation of win versus loss outcomes, and their association with behavioral characteristics, such as impulsivity and task performance, and neuropsychological functioning. Functional MRI was recorded in thirty healthy, male community volunteers (mean age = 27.4 years) while they performed a monetary gambling task in which they bet with either 10 or 50 tokens and received feedback of whether they won or lost the bet amount. Results showed that a set of key brain structures in the reward network, including putamen, caudate nucleus, superior and inferior parietal lobule, angular gyrus, and Rolandic operculum, had greater blood oxygenation level dependent (BOLD) signal during win relative to loss trials, and the BOLD signals in most of these regions were highly correlated with one another. Further, exploratory bivariate analyses between these reward related regions and behavioral and neuropsychological domains showed significant correlations with moderate effect sizes, including: (i) negative correlations between non-planning impulsivity and activations in putamen and caudate regions, (ii) positive correlations between risky bets and right putamen activation, (iii) negative correlations between safer bets and right putamen activation, (iv) a negative correlation between short-term memory capacity and right putamen activity, and (v) a negative correlation between poor planning skills and left inferior occipital cortex activation. These findings contribute to our understanding of the neural underpinnings of monetary reward processing and their relationships to aspects of behavior and cognitive function. Future studies may confirm these findings with larger samples of healthy controls and extend these findings by investigating various clinical groups with impaired reward processing.

neuroscience↗

bioRxiv2025

Neutralizing antibodies elicited by Nipah virus G-head nanoparticle target diverse sites and inhibit receptor binding and fusion

Nipah virus (NiV) and Hendra virus (HeV), two highly pathogenic Henipaviruses (HNVs), pose a significant public health threat. The attachment glycoprotein (G) plays a crucial role in viral attachment and entry, making it an attractive target for vaccine and therapeutic antibody development. However, the antigenic landscape and neutralization sensitivity of the G protein remain poorly defined. Here, we systematically characterize 27 monoclonal antibodies (mAbs) elicited by NiV G head (GH) nanoparticle-immunized mice. Among these, 25 mAbs exhibit neutralizing activity against two major NiV strains, NiV-Malaysia and NiV-Bangladesh, with five mAbs also cross-inhibiting HeV infection. Although all mAbs target GH, they inhibit viral infection through distinct mechanisms, either by blocking receptor ephrin-B2 engagement with the G protein or by preventing viral membrane fusion. Notably, mAbs from two distinct groups conferred complete protection to hamsters against lethal NiV-Malaysia infection. Structural analysis of NiV GH in complex with four representative Fabs reveals four non-overlapping epitopes, including two novel antigenic sites and one shared protective epitope identified across species. Our study provides a comprehensive map of the antigenic determinants of NiV GH, elucidates the relationship between epitopes, neutralization mechanisms, and protection, and offers new insights and opportunities for antibody-based therapies and vaccine development. HighlightsMost mAbs induced in G head nanoparticle-immunized mice are potent neutralizers MAbs recognizing the G head block receptor binding or viral fusion Structural analysis shows mAbs target four distinct epitopes on G head protein Receptor competition site on G head is a shared protective antigenic site in human and multiple animals

immunology↗

bioRxiv2025

Evaluating the toxicity of methanol, formaldehyde and formate on the growth fitness of Yarrowia lipolytica

Liquid C1 feedstock, including methanol, formaldehyde and formic acid can be easily manufactured from greenhouse gases CO2 and CH4. Yarrowia lipolytica, isolated from marine ecosystem, is a non-conventional yeast which is capable of assimilating multiple range of hydrophobic compounds including alcohols, lipids, hydrocarbons, and volatile fatty acids et al. This yeast has been extensively engineered to produce lipids, carotenoids, squalene and other natural products. Herein we tested the growth fitness of Y. lipolytica when exposed to various one-carbon (C1) liquid feedstocks (methanol, formaldehyde, and formic acid). We firstly captured the cell growth kinetics with an automatic Cell Growth Analyzer and fitted the data with a Monod-type growth model. We obtained the inhibition constants of the three liquid C1s from the growth fitness dose-response curves. We found that the lagging phase duration is exponentially correlated with the toxicity of the tested C1 solvents. Notably, Y. lipolytica exhibited tolerance to methanol (IC50 871 mM) and formic acid (IC50 42.6 mM), but showed sensitivity to formaldehyde (IC50 3.8 mM). We next chose fromate as the co-substrate to cultivate Y. lipolytica, confirmed that Y. lipolytica can upcycle formic acid to improve lipid yields and biomass in fed-batch culture. This work broadens Y. lipolyticas substrate scope and facilitates sustainable and cost-efficient production of fuels and chemicals.

synthetic biology↗

bioRxiv2025

Synergizing Network Pharmacology and Pan-Cancer Analysis in TCM Repositioning for Tumor Therapy

BackgroundRepositioning Traditional Chinese Medicine (TCM) for cancer treatment, addressing heterogeneity through synergistic effects, aligns with the evolving trend of combination therapy. However, the complexity of TCM and the lack of methodology hinders the elucidation of TCM treatment mechanisms and potential indications. The research aims to construct develop a comprehensive method combining network pharmacology and pan-cancer analysis (NetPharm-PanCan) for TCM repositioning, exemplified by the Astragali Radix-Curcumae Rhizoma (ARCR) herb pair. MethodThe TCM-component-gene network was constructed using Cytoscape3.7.2 with gene screening based on components from TCMSP and targets predicted via the Swiss Target Prediction database. The core gene set of the ARCR (CGSARCR) was identified by analyzing network via the dual algorithm, namely Degree and MCODE followed by GO and KEGG enrichment analyses. The pan-cancer analysis encompassing Gene Set Variation Analysis (GSVA), immune infiltration correlation, cancer pathway analysis, and Gene Set Enrichment Analysis (GSEA) was unveiled to identify the potential indications. Multivariate cox regression analysis was employed for identifying prognostic genes, followed by the modeling for potential therapeutic indications using the R software. The Metescape database was harnessed to reveal similarities and differences in the mechanisms for prognostic genes associated with potential indications. The XGBoost algorithm was used to construct an indication prediction system according to the analysis results above. ResultThe CGSARCR comprises 28 genes targeting all ARCR components. The pan-cancer analysis revealed that the CGSARCR showed significantly higher tumor scores than normal tissue scores across nine different types of cancer, including THCA, KIRC, LUAD, COAD, BRCA, STAD, ESCA, and others. The CGSARCR correlated strongly with cancer-related pathways and the immune microenvironment. Prognostic models evaluate the potential of these indications as follows: THCA> KIRC> LUAD> COAD> BRCA> STAD> ESCA, with enrichment analysis suggesting KIRC and LUAD as the most potential indications of ARCR. The XGBoost-based system achieved high predictive accuracy (training AUC: 0.985, testing AUC: 0.96, training logloss: 0.21, testing logloss: 0.25). ConclusionThe NetPharm-PanCan method provides a robust, network-based pan-cancer analysis framework for TCM repositioning in cancer research. It provides theoretical foundations and practical tools for TCM-based drug development, with potential applicability to broader drug repurposing efforts.

bioinformatics↗

bioRxiv2024

Targeting protein tyrosine phosphatase non-receptor type 2 with a novel inhibitor for AML therapy

Acute myeloid leukemia (AML) is a fatal disease characterized by a bleak prognosis. For over four decades, treatment options for AML have been constrained to administering high-dose cytotoxic chemotherapy. However, the emergence of drug resistance and the resultant toxic side effects have created an urgent necessity for identifying novel therapeutic targets. In this study, non-receptor protein tyrosine phosphatase type 2 (PTPN2) is highly expressed in AML. Remarkably, knock down of PTPN2 expression markedly mitigated AML burden both in vitro and in vivo. Additionally, we unveiled the direct interaction between PTPN2 and C-MYC, establishing C-MYC as a direct acting substrate of PTPN2. Then, we performed a small-molecule compound screening to identify K73, a selective inhibitor of PTPN2. At the same time, K73 showed a good safety profile and exhibited strong activity against AML in vivo. In conclusion, we have pinpointed a considerable therapeutic potential in targeting PTPN2 for AML treatment and discovered a novel class of selective PTPN2 inhibitors suitable for AML therapy.

cancer biology↗

bioRxiv2024

Prediction of brain age in individuals with and at risk for alcohol use disorder using brain morphological features

Brain age measures predicted from structural and functional brain features are increasingly being used to understand brain integrity, disorders, and health. While there is a vast literature showing aberrations in both structural and functional brain measures in individuals with and at risk for alcohol use disorder (AUD), few studies have investigated brain age in these groups. The current study examines brain age measures predicted using brain morphological features, such as cortical thickness and brain volume, in individuals with a lifetime diagnosis of AUD as well as in those at higher risk to develop AUD from families with multiple members affected with AUD (i.e., higher family history density (FHD) scores). The AUD dataset included a group of 30 adult males (mean age = 41.25 years) with a lifetime diagnosis of AUD and currently abstinent and a group of 30 male controls (mean age = 27.24 years) without any history of AUD. A second dataset of young adults who were categorized based on their FHD scores comprised a group of 40 individuals (20 males) with high FHD of AUD (mean age = 25.33 years) and a group of 31 individuals (18 males) with low FHD (mean age = 25.47 years). Brain age was predicted using 187 brain morphological features of cortical thickness and brain volume in an XGBoost regression model; a bias-correction procedure was applied to the predicted brain age. Results showed that both AUD and high FHD individuals showed an increase of 1.70 and 0.09 years (1.08 months), respectively, in their brain age relative to their chronological age, suggesting accelerated brain aging in AUD and risk for AUD. Increased brain age was associated with poor performance on neurocognitive tests of executive functioning in both AUD and high FHD individuals, indicating that brain age can also serve as a proxy for cognitive functioning and brain health. These findings on brain aging in these groups may have important implications for the prevention and treatment of AUD and ensuing cognitive decline.

neuroscience↗

bioRxiv2024

Polygenic Risk for Alcohol Use Disorder Affects Cellular Responses to Ethanol Exposure in a Human Microglial Cell Model

Polygenic risk scores (PRS) assess genetic susceptibility to Alcohol Use Disorder (AUD), yet their molecular implications remain underexplored. Neuroimmune interactions, particularly in microglia, are recognized as significant contributors to AUD pathophysiology. We investigated the interplay between AUD PRS and ethanol in human microglia derived from iPSCs from individuals with high- or low-PRS (HPRS or LPRS) of AUD. Ethanol exposure induced elevated CD68 expression and morphological changes in microglia, with differential responses between HPRS and LPRS microglial cells. Transcriptomic analysis revealed expression differences in MHCII complex and phagocytosis-related genes following ethanol exposure; HPRS microglial cells displayed enhanced phagocytosis and increased CLEC7A expression, unlike LPRS microglial cells. Synapse numbers in co-cultures of induced neurons with microglia after alcohol exposure were lower in HRPS co-cultures, suggesting possible excess synapse pruning. This study provides insights into the intricate relationship between AUD PRS, ethanol, and microglial function, potentially influencing neuronal functions in developing AUD.

neuroscience↗

bioRxiv2023

Serine hydroxymethyl transferase is a binding target of caprylic acid: Uncovering a novel molecular target for a herbicide and for producing caprylic acid-tolerant crops

Identification of new binding targets is essential for the development of herbicides and phytotoxin-tolerant crops. Caprylic acid (CAP) is a safe and non-selective bio-herbicide in uncultivated areas. However, the herbicidal action of CAP remains unclear. Herein, metabolomic and proteomic profiling indicated that a serine hydroxymethyl transferase in Conyza canadensis (CcSHMT1) is a promising candidate binding targeted for CAP. The protein abundance and activity of CcSHMT1 were decreased in a time- and dosage-dependent manners after CAP treatment. CAP competes with phenyl-serine at the binding sites, decreasing the enzymatic activity of CcSHMT1. Overexpression of CcSHMT1, AtSHMT1 and OsSHMT1 in Arabidopsis or rice endowed plants with high tolerance to CAP treatment, whereas the knockout of osshmt1 led to death of plants under normal atmospheric conditions. Furthermore, T194A, T194A/ M195V and D209N Osshmt1 mutant plants derived from base editing exhibited tolerance to CAP. CAP bound to CcSHMT1 with high affinity, and Ala191 in the key domains of N-terminus was identified to be critical for the binding site of CAP. Collectively, our findings demonstrate that CcSHMT1 is a binding target for herbicidal activity of CAP. This study marks a key step in the druggability of SHMT inhibitors and represents an attractive target for phytotoxin-tolerant crops.

plant biology↗

bioRxiv2023

Levy statistics define anxiety and depression in mice subjected to chronic stress

IntroductionAnxiety and depression are recognized as adaptive responses to external stressors in organisms. Current methods for evaluating anxiety and depression in rodents are both burdensome and stressful. The objective of this investigation is to explore a simplified methodology for identifying stress-induced and stress-free states, as well as anxiety and depression levels, by analyzing the movement patterns of rodents. MethodsTo address this issue, we utilized Levy statistics to examine the movement patterns of stressed rodents and compared them to non-stressed controls. We employed the two-dimensional Kolmogorov-Smirnov test to identify significant differences in the {gamma} and parameters derived from Levy flight (LF) between anxiety, depression, and control mice. Additionally, we employed the support vector machine algorithm to optimize the classification of each group. ResultsOur analysis revealed that stressed mice displayed heavy-tailed distributions of movement velocity in open fields, resembling the movement patterns observed in animal predators searching for scarce food sources in nature. In contrast, non-stressed mice exhibited a normal distribution of speed. Notably, the effectiveness of this methodology in the field of drug discovery was confirmed by the response of stressed mice to fluoxetine, a well-established selective serotonin reuptake inhibitor (SSRI). ConclusionThis study unveils a previously unidentified statistical walking pattern in mice experiencing anxiety and depression. These findings offer a novel and accessible approach for distinguishing between anxiety, depression, and healthy mice. This method provides a one-step gentle approach (free walk in an open field) instead of the traditional multi-step stressful tests.

animal behavior and cognition↗

bioRxiv2023

Morphine Re-arranges Chromatin Spatial Architecture of Primate Cortical Neurons

The expression of linear DNA sequences is precisely regulated by the three-dimensional (3D) architecture of chromatin. Morphine-induced aberrant gene networks of neurons have been extensively investigated; however, how morphine impacts the 3D genomic architecture of neuorns is still unknown. Here, we applied digestion-ligation-only high-throughput chromosome conformation capture (DLO Hi-C) technology to investigate the affection of morphine on 3D chromatin architecture of primate cortical neurons. After receiving continuous morphine administration for 90 days on rhesus monkeys, we discovered that morphine re-arranged chromosome territories, with a total of 391 segmented compartments being switched. Morphine altered over half of the detected topologically associated domains (TADs), most of which exhibited a variety of shifts, followed by separating and fusing types. Analysis of the looping events at kilobase-scale resolution revealed that morphine increased not only the number but also the length of differential loops. Moreover, all identified differentially expressed genes (DEGs) from the RNA sequencing (RNA-seq) were mapped to the specific TAD boundaries or differential loops, and were further validated to be significantly changed. Collectively, an altered 3D genomic architecture of cortical neurons may regulate the gene networks associated-morphine effects. Our finding provides critical hubs connecting chromosome spatial organization and gene networks associated with the morphine effects in humans.

bioinformatics↗

bioRxiv2023

Predicting alcohol-related memory problems in older adults: A machine learning study with multi-domain features

Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (Memory group) were compared with a matched Control group who did not have memory problems. The Random Forests model identified specific features from each domain that contributed to the classification of Memory vs. Control group (AUC=88.29%). Specifically, individuals from the Memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except some connections involving anterior cingulate cortex which were predominantly hypoconnected. Other significant contributing features were (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past 5 years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past 12 months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive "uplift" life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity collected [~]18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict alcohol-related memory problems that arise in later life.

neuroscience↗

bioRxiv2021

Two-color super-resolution localization microscopy via joint encoding of emitter location and color

Multi-color super-resolution localization microscopy (SRLM) provides great opportunities for studying the structural and functional details of biological samples. However, current multi-color SRLM methods either suffer from medium to high crosstalk, or require a dedicated optical system and a complicated image analysis procedure. To address these problems, here we propose a completely different method to realize multi-color SRLM. This method is built upon a customized RGBW camera with a repeated pattern of filtered (Red, Green, Blue and Near-infrared) and unfiltered (White) pixels. With a new insight that RGBW camera is advantageous for color recognition instead of color reproduction, we developed a joint encoding scheme of emitter location and color. By combing this RGBW camera with the joint encoding scheme and a simple optical set-up, we demonstrated two-color SRLM with [~]20 nm resolution and < 2% crosstalk (which is comparable to the best reported values). This study significantly reduces the complexity of two-color SRLM (and potentially multi-color SRLM), and thus offers good opportunities for general biomedical research laboratories to use multi-color SRLM, which is currently mastered only by well-trained researchers.

biophysics↗

bioRxiv2020

Antibiotics-induced alterations in gut microbiol composition leads to blood-brain barrier permeability increase in rhesus monkeys

Blood-brain barrier (BBB) contributes to maintenance of brain homeostasis. Gut microbiome composition affected BBB development and expression of tight junction proteins in rodents. However, we still do not know if theres any direct effect of gut microbiol composition on BBB permeability and function in normal adult animals. In current study, we determined temporal and spatial change of BBB permeability in rhesus monkeys receiving either oral or intravenous amoxicillin-clavulanic acid (AC), by monitoring CSF/serum albumin ratio (AR) and the volume transfer constant (Ktrans). We showed that oral, but not intravenous AC led to a significant alteration in gut microbiol composition and increase of BBB permeability in all monkeys, especially in thalamus area. Acetic acid and propionic acid might play a pivotal role in this newly found communication between gut and central nervous system. Antibiotics-induced gut microbiol composition change, especially the decreasing of acetic and propionic acid producing phyla and genera, leads to increase of BBB permeability, which may contribute to a variety of neurological and psychological diseases.

neuroscience↗