Application of Li6.4La3Zr1.45Ta0.5Mo0.05O12/PEO Composite Solid Electrolyte in High-Performance Lithium Batteries.

Replacing the flammable liquid electrolytes with solid ones has been considered to be the most effective way to improve the safety of the lithium batteries. However, the solid electrolytes often suffer from low ionic conductivity and poor rate capability due to their relatively stable molecular/atomic architectures. In this study, we report a composite solid electrolyte, in which polyethylene oxide (PEO) is the matrix and Li6.4La3Zr1.45Ta0.5Mo0.05O12 (LLZTMO) and Li6.4La3Zr1.4Ta0.6O12 (LLZTO) are the fillers. Ta/Mo co-doping can further promote the ion transport capacity in the electrolyte. The synthesized composite electrolytes exhibit high thermal stability (up to 413 °C) and good ionic conductivity (LLZTMO-PEO 2.00 × 10-4 S·cm-1, LLZTO-PEO 1.53 × 10-4 S·cm-1) at 35 °C. Compared with a pure PEO electrolyte, whose ionic conductivity is in the range of 10-7~10-6 S·cm-1, the ionic conductivity of composite solid electrolytes is greatly improved. The full cell assembled with LiFePO4 as the positive electrode exhibits excellent rate performance and good cycling stability, indicating that prepared solid electrolytes have great potential applications in lithium batteries.

Accelerating the Rate-Determining Steps of Sulfur Conversion Reaction for Lithium-Sulfur Batteries Working at an Ultrawide Temperature Range.

Wide operation temperature is the crucial objective for an energy storage system that can be applied under harsh environmental conditions. For lithium-sulfur batteries, the "shuttle effect" of polysulfide intermediates will aggravate with the temperature increasing, while the reaction kinetics decreases sharply as the temperature decreasing. In particular, sulfur reaction mechanism at low temperatures seems to be quite different from that at room temperature. Here, through in situ Raman and electrochemical impedance spectroscopy studies, the newly emerged platform at cryogenic temperature corresponds to the reduction process of Li2S8 to Li2S4, which will be another rate-determining step of sulfur conversion reaction, in addition to the solid-phase conversion process of Li2S4 to Li2S2/Li2S at low temperatures. Porous bismuth vanadate (BiVO4) spheres are designed as sulfur host material, which achieve the rapid snap-transfer-catalytic process by shortening lithium-ion transport pathway and accelerating the targeted rate-determining steps. Such promoting effect greatly inhibits severe "shuttle effect" at high temperatures and simultaneously improves sulfur conversion efficiency in the cryogenic environment. The cell with the porous BiVO4 spheres as the host exhibits excellent rate capability and cycle performance under wide working temperatures.

Modulation of cream cheese physicochemical and functional properties with ultrafiltration and calcium reduction.

The production of cream cheese from ultrafiltered (UF) milk can reduce acid whey generation but the effect of altered protein and calcium concentration on the physicochemical properties of cream cheese is not well understood. In this study, the effect of skim milk concentration by UF (2.5 and 5 fold) was assessed both with and without calcium reduction using 2% (w/v) cation resin treatment. UF concentration increased the concentration of peptides and free amino acids and led to a more heterogeneous and porous microstructure, resulting in a softer, less viscous and less thermally stable cream cheese. Calcium reduction decreased peptide generation, increased the size of corpuscular structures, decreased porosity and increased thermal stability but did not significantly decrease cheese hardness or viscosity. The study illustrates how protein or calcium concentration, can be used to alter functional properties.

In-situ synthesis Fe3C@C/rGO as matrix for high performance lithium-sulfur batteries at room and low temperatures.

People have been focusing on how to improve the specific capacity and cycling stability of lithium-sulfur batteries at room temperature, however, on some special occasions such as cold cities and aerospace fields, the operating temperature is low, which dramatically hinders the performance of batteries. Here, we report an iron carbide (Fe3C)/rGO composite as electrode host, the Fe3C nanoparticles in the composite have strong adsorption and high catalytic ability for polysulfide. The rGO makes the distribution of Fe3C nanoparticles more disperse, and this specific structure makes the deposition of Li2S more uniform. Therefore, it realizes the rapid transformation and high performance of lithium-sulfur batteries at both room and low temperatures. At room temperature, after 100 cycles at 1C current density, the reversible specific capacity of the battery can be stabilized at 889 ± 7.1 mAh/g. Even at -40 °C, in the first cycle battery still emits 542.9 ± 3.7 mAh/g specific capacity. This broadens the operating temperature for lithium-sulfur batteries and also provides a new idea for the selection of host materials for sulfur in low-temperature lithium-sulfur batteries.

Advancements in Battery Monitoring: Harnessing Fiber Grating Sensors for Enhanced Performance and Reliability.

Batteries play a crucial role as energy storage devices across various industries. However, achieving high performance often comes at the cost of safety. Continuous monitoring is essential to ensure the safety and reliability of batteries. This paper investigates the advancements in battery monitoring technology, focusing on fiber Bragg gratings (FBGs). By examining the factors contributing to battery degradation and the principles of FBGs, this study discusses key aspects of FBG sensing, including mounting locations, monitoring targets, and their correlation with optical signals. While current FBG battery sensing can achieve high measurement accuracies for temperature (0.1 °C), strain (0.1 µÎµ), pressure (0.14 bar), and refractive index (6 × 10-5 RIU), with corresponding sensitivities of 40 pm/°C, 2.2 pm/µÎµ, -0.3 pm/bar, and -18 nm/RIU, respectively, accurately assessing battery health in real time remains a challenge. Traditional methods struggle to provide real-time and precise evaluations by analyzing the microstructure of battery materials or physical phenomena during chemical reactions. Therefore, by summarizing the current state of FBG battery sensing research, it is evident that monitoring battery material properties (e.g., refractive index and gas properties) through FBGs offers a promising solution for real-time and accurate battery health assessment. This paper also delves into the obstacles of battery monitoring, such as standardizing the FBG encapsulation process, decoupling multiple parameters, and controlling costs. Ultimately, the paper highlights the potential of FBG monitoring technology in driving advancements in battery development.

Size effects of microplastics on antibiotic resistome and core microbiome in an urban river.

Microplastics (MPs) in aquatic environments provide a new ecological niche that facilitates the attachment of antibiotic-resistance genes (ARGs) and pathogens. However, the effect of particle size on the colonization of antibiotic resistomes and pathogens remains poorly understood. To address this knowledge gap, this study explored the antibiotic resistome and core microbiome on three distinct types of MPs including polyethylene, polypropylene, and polystyrene (PS), with varying sizes of 30, 200, and 3000 µm by metagenomic sequencing. Our finding showed that the ARG abundances of the PS type increased by 4-folds with increasing particle size from 30 to 3000 µm, and significant differences in ARG profiles were found across the three MP types. In addition, the concentrations of ARGs and mobile genetic elements (MGEs) were markedly higher in the MPs than in the surrounding water, indicating their enrichment at these artificial interfaces. Notably, several pathogens such as Pseudomonas aeruginosa, Mycobacterium tuberculosis, and Legionella pneumophila were enriched in MP biofilms, and the co-occurrence of ARGs and virulence factor genes (VFGs)/MGEs suggested the presence of pathogenic antibiotic-resistant microbes with potential mobility. Both redundancy analysis (RDA) and structural equation modeling (SEM) demonstrated that physicochemical properties such as zeta potential, MP size, and contact angle were the most significant contributors to the antibiotic resistome. Strikingly, no significant differences were observed in the health risk scores of the ARG profiles among different sizes and types of MPs. This study expands our knowledge on the impact of MP size on microbial risks, thus enhancing our understanding of the potential health hazards they pose.

Experimental prognostic model integrating N6-methyladenosine-related programmed cell death genes in colorectal cancer.

Colorectal cancer (CRC) intricacies, involving dysregulated cellular processes and programmed cell death (PCD), are explored in the context of N6-methyladenosine (m6A) RNA modification. Utilizing the TCGA-COADREAD/CRC cohort, 854 m6A-related PCD genes are identified, forming the basis for a robust 10-gene risk model (CDRS) established through LASSO Cox regression. qPCR experiments using CRC cell lines and fresh tissues was performed for validation. The CDRS served as an independent risk factor for CRC and showed significant associations with clinical features, molecular subtypes, and overall survival in multiple datasets. Moreover, CDRS surpasses other predictors, unveiling distinct genomic profiles, pathway activations, and associations with the tumor microenvironment. Notably, CDRS exhibits predictive potential for drug sensitivity, presenting a novel paradigm for CRC risk stratification and personalized treatment avenues.

Network-based identification and mechanism exploration of active ingredients against Alzheimer's disease via targeting endoplasmic reticulum stress from traditional chinese medicine.

Alzheimer's disease is a neurodegenerative disease that leads to dementia and poses a serious threat to the health of the elderly. Traditional Chinese medicine (TCM) presents as a promising novel therapeutic therapy for preventing and treating dementia. Studies have shown that natural products derived from kidney-tonifying herbs can effectively inhibit AD. Furthermore, endoplasmic reticulum (ER) stress is a critical factor in the pathology of AD. Regulation of ER stress is a crucial approach to prevent and treat AD. Thus, in this study, we first collected kidney-tonifying herbs, integrated chemical ingredients from multiple TCM databases, and constructed a comprehensive drug-target network. Subsequently, we employed the endophenotype network (network proximity) method to identify potential active ingredients in kidney-tonifying herbs that prevented AD via regulating ER stress. By combining the predicted outcomes, we discovered that 32 natural products could ameliorate AD pathology via regulating ER stress. After a comprehensive evaluation of the multi-network model and systematic pharmacological analyses, we further selected several promising compounds for in vitro testing in the APP-SH-SY5Y cell model. Experimental results showed that echinacoside and danthron were able to effectively reduce ER stress-mediated neuronal apoptosis by inhibiting the expression levels of BIP, p-PERK, ATF6, and CHOP in APP-SH-SY5Y cells. Overall, this study utilized the endophenotype network to preliminarily decipher the effective material basis and potential molecular mechanism of kidney-tonifying Chinese medicine for prevention and treatment of AD.

Accurate wavelet thresholding method for ECG signals.

Current wavelet thresholding methods for cardiogram signals captured by flexible wearable sensors face a challenge in achieving both accurate thresholding and real-time signal denoising. This paper proposes a real-time accurate thresholding method based on signal estimation, specifically the normalized ACF, as an alternative to traditional noise estimation without the need for parameter fine-tuning and extensive data training. This method is experimentally validated using a variety of electrocardiogram (ECG) signals from different databases, each containing specific types of noise such as additive white Gaussian (AWG) noise, baseline wander noise, electrode motion noise, and muscle artifact noise. Although this method only slightly outperforms other methods in removing AWG noise in ECG signals, it far outperforms conventional methods in removing other real noise. This is attributed to the method's ability to accurately distinguish not only AWG noise that is significantly different spectrum of the ECG signal, but also real noise with similar spectra. In contrast, the conventional methods are effective only for AWG noise. In additional, this method improves the denoising visualization of the measured ECG signals and can be used to optimize other parameters of other wavelet methods to enhancing the denoised periodic signals, thereby improving diagnostic accuracy.

The Role of Necroptosis in Cerebral Ischemic Stroke.

Cerebral ischemia, also known as ischemic stroke, accounts for nearly 85% of all strokes and is the leading cause of disability worldwide. Due to disrupted blood supply to the brain, cerebral ischemic injury is trigged by a series of complex pathophysiological events including excitotoxicity, oxidative stress, inflammation, and cell death. Currently, there are few treatments for cerebral ischemia owing to an incomplete understanding of the molecular and cellular mechanisms. Accumulated evidence indicates that various types of programmed cell death contribute to cerebral ischemic injury, including apoptosis, ferroptosis, pyroptosis and necroptosis. Among these, necroptosis is morphologically similar to necrosis and is mediated by receptor-interacting serine/threonine protein kinase-1 and -3 and mixed lineage kinase domain-like protein. Necroptosis inhibitors have been shown to exert inhibitory effects on cerebral ischemic injury and neuroinflammation. In this review, we will discuss the current research progress regarding necroptosis in cerebral ischemia as well as the application of necroptosis inhibitors for potential therapeutic intervention in ischemic stroke.

Synthesis of Low-Cost and High-Performance Dual-Atom Doped Carbon-Based Materials with a Simple Green Route as Anodes for Sodium-Ion Batteries.

Sodium-ion batteries (SIBs) are promising alternatives to replace lithium-ion batteries as future energy storage batteries because of their abundant sodium resources, low cost, and high charging efficiency. In order to match the high energy capacity and density, designing an atomically doped carbonous material as the anode is presently one of the important strategies to commercialize SIBs. In this work, we report the preparation of high-performance dual-atom-doped carbon (C) materials using low-cost corn starch and thiourea (CH4N2S) as the precursors. The electronegativity and radii of the doped atoms and C are different, which can vary the embedding properties of sodium ions (Na+) into/on C. As sulfur (S) can effectively expand the layer spacing, it provides more channels for embedding and de-embedding Na+. The synergistic effect of N and S co-doping can remarkably boost the performance of SIBs. The capacity is preserved at 400 mAh g -1 after 200 cycles at 500 mA g-1; more notably, the initial Coulombic efficiency is 81%. Even at a high rate of high current of 10 A g-1, the cell capacity can still reach 170 mAh g-1. More importantly, after 3000 cycles at 1 A g-1, the capacity decay is less than 0.003% per cycle, which demonstrates its excellent electrochemical performance. These results indicate that high-performance carbon materials can be prepared using low-cost corn starch and thiourea.

The effect of calcium removal from skim milk by ion exchange on the properties of the ultrafiltration retentate.

New processes are needed to produce concentrated milk feedstocks with tailored calcium content, due to the direct link between calcium concentration and final product texture and functionality. Skim milk treatment with cation exchange resin 1% (w/v) or 2% (w/v) prior to ultrafiltration to a volumetric concentration factor (VCF) of 2.5 or 5 successfully decreased the calcium concentration by 20-30% and produced concentrates with solids content at ∼22-24 g 100 g-1 at a VCF of 5. Calcium reduction partially solubilized the casein micelles, increasing the concentration of soluble protein and individual caseins, leading to decreased turbidity but increased protein hydration and hydrophobicity. Decalcification (2% (w/v) resin treatment) reduced thermal stability, significantly decreasing the denaturation temperature of α-lactalbumin and ß-lactoglobulin in the milk by ∼3 °C and ∼1 °C respectively. Filtration was also altered, reducing permeation flux and the gel concentration and increased filtration time. When combined, calcium reduction and filtration altered functional properties including soluble calcium, soluble protein and sedimentable solids, with increased milk protein hydration also contributing to increased viscosity. This study provides a route to produce calcium-reduced milk concentrates with potential for use in retentate-based dairy products with tailored functionality.

Corrigendum: Systems pharmacology approach to investigate the mechanism of Kai-Xin-San in Alzheimer's disease.

[This corrects the article DOI: 10.3389/fphar.2020.00381.].

Integrative evaluation and experimental validation of the immune-modulating potential of dysregulated extracellular matrix genes in high-grade serous ovarian cancer prognosis.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is a challenging malignancy characterized by complex interactions between tumor cells and the surrounding microenvironment. Understanding the immune landscape of HGSOC, particularly the role of the extracellular matrix (ECM), is crucial for improving prognosis and guiding therapeutic interventions. METHODS AND RESULTS: Using univariate Cox regression analysis, we identified 71 ECM genes associated with prognosis in seven HGSOC populations. The ECMscore signature, consisting of 14 genes, was validated using Cox proportional hazards regression with a lasso penalty. Cox regression analyses demonstrated that ECMscore is an excellent indicator for prognostic classification in prevalent malignancies, including HGSOC. Moreover, patients with higher ECMscores exhibited more active stromal and carcinogenic activation pathways, including apical surface signaling, Notch signaling, apical junctions, Wnt signaling, epithelial-mesenchymal transition, TGF-beta signaling, and angiogenesis. In contrast, patients with relatively low ECMscores showed more active immune-related pathways, such as interferon alpha response, interferon-gamma response, and inflammatory response. The relationship between the ECMscore and genomic anomalies was further examined. Additionally, the correlation between ECMscore and immune microenvironment components and signals in HGSOC was examined in greater detail. Moreover, the expression of MGP, COL8A2, and PAPPA and its correlation with FAP were validated using qRT-PCR on samples from HGSOC. The utility of ECMscore in predicting the prospective clinical success of immunotherapy and its potential in guiding the selection of chemotherapeutic agents were also explored. Similar results were obtained from pan-cancer research. CONCLUSION: The comprehensive evaluation of the ECM may help identify immune activation and assist patients in HGSOC and even pan-cancer in receiving proper therapy.

Modulating endoplasmic reticulum stress in APP/PS1 mice by Gomisin B and Osthole in Bushen-Yizhi formula: Synergistic effects and therapeutic implications for Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder with no effective cure. Targeting endoplasmic reticulum (ER) stress pathway may offer a novel approach to ameliorate cognitive deficits in AD. Bushen-Yizhi formula (BSYZ), a traditional Chinese medicine (TCM) prescription, has shown potential benefits for AD. To facilitate the development of new therapeutic agents for AD, it is important to identify the active components and the underlying mechanisms of BSYZ against AD. PURPOSE: The aim of this study was to systematically screen the active components of BSYZ that could improve learning and memory impairment in AD by modulating ER stress pathway. METHODS: A drug-target (D-T) network was constructed to analyze the herbal components of BSYZ. Network proximity method was used to identify the potential anti-AD components that targeted ER stress and evaluate their synergistic effects. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties and the literature evidence were considered to select promising candidates for further validation. The selected components were tested in vitro using an AD cell model (APPswe-SH-SY5Y). In vivo anti-AD effects of the components were assessed in APP/PS1 double-transgenic mice. RESULTS: 58 potential anti-AD components targeting ER stress were detected by network proximity analysis, and 13 out of them were selected based on ADMET properties and literature evidence. In vitro experiments confirmed that 5 components, namely gomisin B, ß-Carotene, imperatorin, chrysophanol, and osthole (OST), exhibited anti-AD effects on the APPswe-SH-SY5Y model. Moreover, network proximity analysis suggested that OST and Gomisin B might have synergistic effects on modulating ER stress. In vivo experiments demonstrated that OST, Gomisin B, OST+Gomisin B, and BSYZ all improved learning and memory function in APP/PS1 mice. Gomisin B and OST also restored cellular morphology and tissue structure in APP/PS1 mice. Thioflavine-S (Th-S) staining revealed that they reduced amyloid plaque deposition in the brain tissue of AD model mice. The qPCR results indicated that BSYZ, OST, and Gomisin B differentially regulated IRE1α, PERK, EIF2α, DDIT3, and Caspase 12 expression levels, while the OST and Gomisin B co-administration group showed better efficacy. This trend was further confirmed by immunofluorescence experiments. CONCLUSION: This study identified the active components of BSYZ that could ameliorate learning and memory impairment in AD by targeting ER stress pathway. OST and Gomisin B exhibited synergistic effects on modulating ER stress and reducing amyloid plaque deposition in vivo. Overall, our study elucidated the molecular mechanisms of BSYZ and its active components in attenuating AD symptoms which suggested the therapeutic potential of TCM for AD.

Systems pharmacology dissection of pharmacological mechanisms of Xiaochaihu decoction against human coronavirus.

BACKGROUND: Although coronavirus disease 2019 (COVID-19) pandemic is still rage worldwide, there are still very limited treatments for human coronaviruses (HCoVs) infections. Xiaochahu decoction (XCHD), which is one of the traditional Chinese medicine (TCM) prescriptions in Qingfeipaidu decoction (QFPDD), is widely used for COVID-19 treatment in China and able to relieve the symptoms of fever, fatigue, anorexia, and sore throat. To explore the role and mechanisms of XCHD against HCoVs, we presented an integrated systems pharmacology framework in this study. METHODS: We constructed a global herb-compound-target (H-C-T) network of XCHD against HCoVs. Multi-level systems pharmacology analyses were conducted to highlight the key XCHD-regulated proteins, and reveal multiple HCoVs relevant biological functions affected by XCHD. We further utilized network-based prediction, drug-likeness analysis, combining with literature investigations to uncover the key ani-HCoV constituents in XCHD, whose effects on anit-HCoV-229E virus were validated using cytopathic effect (CPE) assay. Finally, we proposed potential molecular mechanisms of these compounds against HCoVs via subnetwork analysis. RESULTS: Based on the systems pharmacology framework, we identified 161 XCHD-derived compounds interacting with 37 HCoV-associated proteins. An integrated pathway analysis revealed that the mechanism of XCHD against HCoVs is related to TLR signaling pathway, RIG-I-like receptor signaling pathway, cytoplasmic DNA sensing pathway, and IL-6/STAT3 pro-inflammatory signaling pathway. Five compounds from XCHD, including betulinic acid, chrysin, isoliquiritigenin, schisandrin B, and (20R)-Ginsenoside Rh1 exerted inhibitory activity against HCoV-229E virus in Huh7 cells using in vitro CPE assay. CONCLUSION: Our work presented a comprehensive systems pharmacology approach to identify the effective molecules and explore the molecular mechanism of XCHD against HCoVs.

Systems pharmacology-based mechanism exploration of Acanthopanax senticosusin for Alzheimer's disease using UPLC-Q-TOF-MS, network analysis, and experimental validation.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disease, characterized by progressive cognitive dysfunction and memory loss. However, the disease-modifying treatments for AD are still lacking. Traditional Chinese herbs, have shown their potentials as novel treatments for complex diseases, such as AD. PURPOSE: This study was aimed at investigating the mechanism of action (MOA) of Acanthopanax senticosusin (AS) for treatment of AD. METHODS: In this study, we firstly identified the chemical constituents in Acanthopanax senticosusin (AS) utilizing ultra-high performance liquid chromatography coupled with Q-TOF-mass spectrometry (UPLC-Q-TOF-MS), and next built the drug-target network of these compounds. We also performed the systems pharmacology-based analysis to preliminary explore the MOA of AS against AD. Moreover, we applied the network proximity approach to identify the potential anti-AD components in AS. Finally, experimental validations, including animal behavior test, ELISA and TUNEL staining, were conducted to verify our systems pharmacology-based analysis. RESULTS: 60 chemical constituents in AS were identified via the UPLC-Q-TOF-MS approach. The systems pharmacology-based analysis indicated that AS might exert its therapeutic effects on AD via acetylcholinesterase and apoptosis signaling pathway. To explore the material basis of AS against AD, we further identified 15 potential anti-AD components in AS. Consistently, in vivo experiments demonstrated that AS could protect cholinergic nervous system damage and decrease neuronal apoptosis caused by scopolamine. CONCLUSION: Overall, this study applied systems pharmacology approach, UPLC-Q-TOF-MS, network analysis, and experimental validation to decipher the potential molecular mechanism of AS against AD.

Surface charge induced self-assembled nest-like Ni3S2/PNG composites for high-performance supercapacitors.

The paper presents a self-assembly approach to synthesize Ni3S2/N, P co-doped graphene (PNG) composite electrode materials for supercapacitors with high energy storage performance and structural stability. Innovatively, the self-assembly approach is induced via the surface charge effect utilizing a two-step hydrothermal method. The doping of nitrogen (N) and phosphorus (P) atoms regulates the surface charge distribution on graphene nanosheets. Therefore, in the synthesized Ni3S2/PNG heterostructures, Ni3S2 nanowires are interwoven into nests and uniformly attached to PNG. The design of the electrode materials with such a special structure not only supports each other to improve the stability of the materials but also facilitates the rapid diffusion of electrolyte ions. Based on the advantages of composition and structure, Ni3S2/PNG has a high specific capacitance of 1117C g-1 at a current density of 1 A/g and excellent rate performance. The asymmetric supercapacitors (ASC) assembled with Ni3S2/PNG and PNG as positive and negative materials respectively have a high energy density of 62 Wh kg-1 at a power density of 158 W kg-1.

Glutaminase 1 deficiency confined in forebrain neurons causes autism spectrum disorder-like behaviors.

An abnormal glutamate signaling pathway has been proposed in the mechanisms of autism spectrum disorder (ASD). However, less is known about the involvement of alterations of glutaminase 1 (GLS1) in the pathophysiology of ASD. We show that the transcript level of GLS1 is significantly decreased in the postmortem frontal cortex and peripheral blood of ASD subjects. Mice lacking Gls1 in CamKIIα-positive neurons display a series of ASD-like behaviors, synaptic excitatory and inhibitory (E/I) imbalance, higher spine density, and glutamate receptor expression in the prefrontal cortex, as well as a compromised expression pattern of genes involved in synapse pruning and less engulfed synaptic puncta in microglia. A low dose of lipopolysaccharide treatment restores microglial synapse pruning, corrects synaptic neurotransmission, and rescues behavioral deficits in these mice. In summary, these findings provide mechanistic insights into Gls1 loss in ASD symptoms and identify Gls1 as a target for the treatment of ASD.

Network-based drug repurposing for potential stroke therapy.

Stroke is the leading cause of death and disability worldwide, with a growing number of incidences in developing countries. However, there are currently few medical therapies for this disease. Emerged as an effective drug discovery strategy, drug repurposing which owns lower cost and shorter time, is able to identify new indications from existing drugs. In this study, we aimed at identifying potential drug candidates for stroke via computationally repurposing approved drugs from Drugbank database. We first developed a drug-target network of approved drugs, employed network-based approach to repurpose these drugs, and altogether identified 185 drug candidates for stroke. To validate the prediction accuracy of our network-based approach, we next systematically searched for previous literature, and found 68 out of 185 drug candidates (36.8 %) exerted therapeutic effects on stroke. We further selected several potential drug candidates with confirmed neuroprotective effects for testing their anti-stroke activity. Six drugs, including cinnarizine, orphenadrine, phenelzine, ketotifen, diclofenac and omeprazole, have exhibited good activity on oxygen-glucose deprivation/reoxygenation (OGD/R) induced BV2 cells. Finally, we showcased the anti-stroke mechanism of actions of cinnarizine and phenelzine via western blot and Olink inflammation panel. Experimental results revealed that they both played anti-stroke effects in the OGD/R induced BV2 cells via inhibiting the expressions of IL-6 and COX-2. In summary, this study provides efficient network-based methodologies for in silico identification of drug candidates toward stroke.