The Ser/Thr protein kinase FonKin4-poly(ADP-ribose) polymerase FonPARP1 phosphorylation cascade is required for the pathogenicity of watermelon fusarium wilt fungus Fusarium oxysporum f. sp. niveum.

Poly(ADP-ribosyl)ation (PARylation), catalyzed by poly(ADP-ribose) polymerases (PARPs) and hydrolyzed by poly(ADP-ribose) glycohydrolase (PARG), is a kind of post-translational protein modification that is involved in various cellular processes in fungi, plants, and mammals. However, the function of PARPs in plant pathogenic fungi remains unknown. The present study investigated the roles and mechanisms of FonPARP1 in watermelon Fusarium wilt fungus Fusarium oxysporum f. sp. niveum (Fon). Fon has a single PARP FonPARP1 and one PARG FonPARG1. FonPARP1 is an active PARP and contributes to Fon pathogenicity through regulating its invasive growth within watermelon plants, while FonPARG1 is not required for Fon pathogenicity. A serine/threonine protein kinase, FonKin4, was identified as a FonPARP1-interacting partner by LC-MS/MS. FonKin4 is required for vegetative growth, conidiation, macroconidia morphology, abiotic stress response and pathogenicity of Fon. The S_TKc domain is sufficient for both enzyme activity and pathogenicity function of FonKin4 in Fon. FonKin4 phosphorylates FonPARP1 in vitro to enhance its poly(ADP-ribose) polymerase activity; however, FonPARP1 does not PARylate FonKin4. These results establish the FonKin4-FonPARP1 phosphorylation cascade that positively contributes to Fon pathogenicity. The present study highlights the importance of PARP-catalyzed protein PARylation in regulating the pathogenicity of Fon and other plant pathogenic fungi.

OsATL32 ubiquitinates the reactive oxygen species-producing OsRac5-OsRbohB module to suppress rice immunity.

Ubiquitination-mediated protein degradation is integral to plant immunity, with E3 ubiquitin ligases acting as key factors in this process. Here, we report the functions of OsATL32, a plasma membrane-localized Arabidopsis Tóxicos En Levadura (ATL)-type E3 ubiquitin ligase, in rice (Oryza sativa) immunity and its associated regulatory network. We found that the expression of OsATL32 is downregulated in both compatible and incompatible interactions between rice and the rice blast fungus Magnaporthe oryzae. The OsATL32 protein level declines in response to infection by a compatible M. oryzae strain or to chitin treatment. OsATL32 negatively regulates rice resistance to blast and bacterial leaf blight diseases, as well as chitin-triggered immunity. Biochemical and genetic studies revealed that OsATL32 suppresses pathogen-induced reactive oxygen species (ROS) accumulation by mediating ubiquitination and degradation of the ROS-producing OsRac5-OsRbohB module, which enhances rice immunity against M. oryzae. The protein phosphatase PHOSPHATASE AND TENSIN HOMOLOG enhances rice blast resistance by dephosphorylating OsATL32 and promoting its degradation, preventing its negative effect on rice immunity. This study provides insights into the molecular mechanism by which the E3 ligase OsATL32 targets a ROS-producing module to undermine rice immunity.

The small heat shock protein Hsp20.8 imparts tolerance to high temperatures in the leafminer fly, Liriomyza trifolii (Diptera: Agtomyzidae).

As an environmental factor, temperature impacts the distribution of species and influences interspecific competition. The molecular chaperones encoded by small heat shock proteins (sHsps) are essential for rapid, appropriate responses to environmental stress. This study focuses on Hsp20.8, which encodes a temperature-responsive sHsp in Liriomyza trifolii, an insect pest that infests both agricultural and ornamental crops. Hsp20.8 expression was highest at 39℃ in L. trifolii pupae and adults, and expression levels were greater in pupae than in adults. Recombinant Hsp20.8 was expressed in Escherichia coli and conferred a higher survival rate than the empty vector to bacterial cells exposed to heat stress. RNA interference experiments were conducted using L. trifolii adults and prepupae and the knockdown of Hsp20.8 expression increased mortality in L. trifolii during heat stress. The results expand our understanding of sHsp function in Liriomyza spp. and the ongoing adaptation of this pest to climate change. In addition, this study is also important for predicting the distribution of invasive species and proposing new prevention and control strategies based on temperature adaptation.

Release Pattern of Light Aromatic Hydrocarbons during the Biomass Roasting Process.

Roasting is an important step in the pretreatment of biomass upgrading. Roasting can improve the fuel quality of biomass, reduce the O/C and H/C ratios in the biomass, and provide the biomass with a fuel quality comparable to that of lignite. Therefore, studying the structure and component evolution laws during biomass roasting treatment is important for the rational and efficient utilization of biomass. When the roasting temperature is 200-300 °C, the cellulose and hemicellulose in the biomass undergo a depolymerization reaction, releasing many monocyclic aromatic hydrocarbons with high reactivity. The proportion of monocyclic aromatic hydrocarbons in biomass roasting products can be effectively regulated by controlling the reaction temperature, residence time, catalyst, baking atmosphere, and other factors in the biomass roasting process. This paper focuses on the dissociation law of organic components in the pretreatment process of biomass roasting.

A machine learning stacking model accurately estimating gastric fluid volume in patients undergoing elective sedated gastrointestinal endoscopy.

BACKGROUND: The current point-of-care ultrasound (POCUS) assessment of gastric fluid volume primarily relies on the traditional linear approach, which often suffers from moderate accuracy. This study aimed to develop an advanced machine learning (ML) model to estimate gastric fluid volume more accurately. METHODS: We retrospectively analyzed the clinical data and POCUS data (D1: craniocaudal diameter, D2: anteroposterior diameter) of 1386 patients undergoing elective sedated gastrointestinal endoscopy (GIE) at Nanjing First Hospital to predict gastric fluid volume using ML techniques, including six different ML models and a stacking model. We evaluated the models using the adjusted Coefficient of Determination (R2), mean absolute error (MAE) and root mean square error (RMSE). The SHapley Additive exPlanations (SHAP) method was used to interpret the importance of the variables. Finally, a web calculator was constructed to facilitate its clinical application. RESULTS: The stacking model (Linear regression + Multilayer perceptron) performed best, with the highest adjusted R2 of 0.718 (0.632 to 0.804). The mean prediction bias was 4 ml (MAE: 4.008 (3.68 to 4.336)), which is better than that of the linear model. D1 and D2 ranked high in the SHAP plot and performed better in the right lateral decubitus (RLD) than in the supine position. The web calculator can be accessed at https://cheason.shinyapps.io/Stacking_regressor/. CONCLUSION: The stacking model and its web calculator can serve as practical tools for accurately estimating gastric fluid volume in patients undergoing elective sedated GIE. It is recommended that anesthesiologists measure D1 and D2 in the patient's RLD position.

Recent Advances of CeO2-Based Composite Materials for Photocatalytic Applications.

Photocatalysis has the advantages of practical, sustainable and environmental protection, so it plays a significant role in energy transformation and environmental utilization. CeO2 has attracted widespread attention for its unique 4 f electrons, rich defect structures, high oxygen storage capacity and great chemical stability. In this paper, we review the structure of CeO2 and the common methods for the preparation of CeO2-based composites in the first part. In particular, we highlight the co-precipitation method, template method, and sol-gel method methods. Then, in the second part, we introduce the application of CeO2-based composites in photocatalysis, including photocatalytic CO2 reduction, hydrogen production, degradation, selective organic reaction, and photocatalytic nitrogen fixation. In addition, we discuss several modification techniques to improve the photocatalytic performance of CeO2-based composites, such as elemental doping, defect engineering, constructing heterojunction and morphology regulation. Finally, the challenges faced by CeO2-based composites are analyzed and their development prospects are prospected. This review provides a systematic summary of the recent advance of CeO2-based composites in the field of photocatalysis, which can provide useful references for the rational design of efficient CeO2-based composite photocatalysts for sustainable development.

High perceived stress is associated with decreased sensory-specific satiety in humans.

Previous studies have shown that chronic stress increases food intake. One possible mechanism may be due to altered sensory-specific satiety (SSS) among people with high level of chronic stress. In the current study, seventy-six participants were divided into either high-stress or low-stress groups according to their Perceived Stress Scale (PSS) scores. Participants were assigned to consume one of two foods (banana milk and corn soup) ad libitum until they felt comfortably satiated. Before and after eating, participants rated their liking and wanting for the flavor and the odor (via retronasal and orthonasal routes) of the eaten and uneaten foods. Individual interoceptive sensibility and eating behavior were measured using the Multidimensional Assessment of Interoceptive Awareness (MAIA) and Reasons Individuals Stop Eating Questionnaire (RISE-Q-15), respectively. Compared to the low-stress group, the high-stress group demonstrated blunted SSS to the whole food flavor. No significant difference was found for olfactory-specific satiety (retronasal or orthonasal) between the two groups. In addition, across the whole sample of participants, MAIA total score was positively associated with the magnitude of SSS (r = 0.29, p = 0.01). These results indicate that chronic perceived stress may play a role in the experience of reward during eating.

Rational Photodeposition of Cobalt Phosphate on Flower-like ZnIn2S4 for Efficient Photocatalytic Hydrogen Evolution.

The high electrons and holes recombination rate of ZnIn2S4 significantly limits its photocatalytic performance. Herein, a simple in situ photodeposition strategy is adopted to introduce the cocatalyst cobalt phosphate (Co-Pi) on ZnIn2S4, aiming at facilitating the separation of electron-hole by promoting the transfer of photogenerated holes of ZnIn2S4. The study reveals that the composite catalyst has superior photocatalytic performance than blank ZnIn2S4. In particular, ZnIn2S4 loaded with 5% Co-Pi (ZnIn2S4/5%Co-Pi) has the best photocatalytic activity, and the H2 production rate reaches 3593 µmol·g-1·h-1, approximately double that of ZnIn2S4 alone. Subsequent characterization data demonstrate that the introduction of the cocatalyst Co-Pi facilitates the transfer of ZnIn2S4 holes, thus improving the efficiency of photogenerated carrier separation. This investigation focuses on the rational utilization of high-content and rich cocatalysts on earth to design low-cost and efficient composite catalysts to achieve sustainable photocatalytic hydrogen evolution.

Characterization of genes encoding heat shock proteins reveals a differential response to temperature in two geographic populations of Liriomyza trifolii (Diptera: Agromyzidae).

Liriomyza trifolii is a significant, invasive pest that damages horticultural crops and vegetables. The distribution of L. trifolii is influenced by temperature, and prior research has demonstrated that variations in thermal adaptability differ among geographic populations of the insect. Heat shock proteins (Hsps) are involved in adaptation to temperatures; however, the underlying molecular mechanism for thermal adaption in different L. trifolii populations remains unclear. This study examines the temperature adaptability of two L. trifolii populations from Hainan (HN) and Jiangsu (JS) provinces. The results indicate that the HN population has a higher survival rate and a higher critical thermal maximum (CTmax) than the JS population under high temperature stress. Transcriptome data at 42 °C revealed that the JS population has more differentially expressed genes (DEGs) than the HN population, while the HN population has more upregulated DEGs. The two populations were similar in functional annotation of DEGs, and a large number of Hsps were upregulated. However, the HN population had larger numbers and higher expression levels of Hsps during heat stress as compared to the JS population. Additionally, the expression patterns of differentially expressed Hsps varied between the HN and JS populations in response to different elevated temperatures. Notably, the transcription levels of Hsp70s were higher in the HN population as compared to the JS population, while the expression level of genes encoding small heat shock proteins was higher in the JS population. These findings have significant scientific value in understanding the underlying mechanism of temperature adaption in L. trifolii and provide a fresh perspective on the distribution of this invasive pest.

Fault-Tolerant Fuzzy-Resilient Control for Fractional-Order Stochastic Underactuated System With Unmodeled Dynamics and Actuator Saturation.

This article is considered on underactuated fractional-order stochastic systems (FOSSs) with actuator saturation and incrementally conic nonlinear terms, whose fractional-order α ∈ (0,1) . First, to bring FO dynamic signals, solving the unmodeled dynamics, in the meantime, the saturated nonlinear term of the control input is taken into account. At the time, to cope with the stability issue of FOSS under such situation, the fault tolerant resilient controller based on underactuated condition is designed. Then, according to the method of the Lyapunov and It∧ o differential formulation to design proper multiple Lyapunov-Krasovskii (L-K) functions, such that, a novel sufficient condition of the robustly asymptotically stability of fuzzy FOSS under underactuated conditions is rigorously proved in terms of linear matrix inequality (LMI). Furthermore, in order to research the mean square stability of the above-mentioned system, so the solution of FOSS is obtained to achieve this purpose. By applying the above method, which is proposed in this work that the controlled system can be obtained with faster response and higher control accuracy. At last, to display the superiority of the above-mentioned scheme is effective, tethered satellite system and numerical results are presented.

Accurately predicting the risk of unfavorable outcomes after endovascular coil therapy in patients with aneurysmal subarachnoid hemorrhage: an interpretable machine learning model.

BACKGROUND: Despite endovascular coiling as a valid modality in treatment of aneurysmal subarachnoid hemorrhage (aSAH), there is a risk of poor prognosis. However, the clinical utility of previously proposed early prediction tools remains limited. We aimed to develop a clinically generalizable machine learning (ML) models for accurately predicting unfavorable outcomes in aSAH patients after endovascular coiling. METHODS: Functional outcomes at 6 months after endovascular coiling were assessed via the modified Rankin Scale (mRS) and unfavorable outcomes were defined as mRS 3-6. Five ML algorithms (logistic regression, random forest, support vector machine, deep neural network, and extreme gradient boosting) were used for model development. The area under precision-recall curve (AUPRC) and receiver operating characteristic curve (AUROC) was used as main indices of model evaluation. SHapley Additive exPlanations (SHAP) method was applied to interpret the best-performing ML model. RESULTS: A total of 371 patients were eventually included into this study, and 85.4% of them had favorable outcomes. Among the five models, the DNN model had a better performance with AUPRC of 0.645 (AUROC of 0.905). Postoperative GCS score, size of aneurysm, and age were the top three powerful predictors. The further analysis of five random cases presented the good interpretability of the DNN model. CONCLUSION: Interpretable clinical prediction models based on different ML algorithms have been successfully constructed and validated, which would serve as reliable tools in optimizing the treatment decision-making of aSAH. Our DNN model had better performance to predict the unfavorable outcomes at 6 months in aSAH patients compared with Yan's nomogram model.

Disruption of CerS6-mediated sphingolipid metabolism by FTO deficiency aggravates ulcerative colitis.

BACKGROUND AND AIMS: Deregulation of RNA N6-methyladenosine (m6A) modification in intestinal epithelial cells (IECs) influences intestinal immune cells and leads to intestinal inflammation. We studied the function of fat mass-and obesity-associated protein (FTO), one of the m6A demethylases, in patients with ulcerative colitis (UC). METHODS: We analysed colon tissues of Ftoflox/flox; Villin-cre mice and their Ftoflox/flox littermates with dextran sulfate sodium (DSS) using real-time PCR and 16s rRNA sequencing. RNA and methylated RNA immunoprecipitation sequencing were used to analyse immunocytes and IECs. Macrophages were treated with conditioned medium of FTO-knockdown MODE-K cells or sphingosine-1-phosphate (S1P) and analysed for gene expression. Liquid chromatograph mass spectrometry identified C16-ceramide. RESULTS: FTO downregulation was identified in our in-house cohort and external cohorts of UC patients. Dysbiosis of gut microbiota, increased infiltration of proinflammatory macrophages, and enhanced differentiation of Th17 cells were observed in Ftoflox/flox;Villin-cre mice under DSS treatment. FTO deficiency resulted in an increase in m6A modification and a decrease in mRNA stability of CerS6, the gene encoding ceramide synthetase, leading to the downregulation of CerS6 and the accumulation of S1P in IECs. Subsequentially, the secretion of S1P by IECs triggered proinflammatory macrophages to secrete serum amyloid A protein 1/3, ultimately inducing Th17 cell differentiation. In addition, through bioinformatic analysis and experimental validation, we identified UC patients with lower FTO expression might respond better to vedolizumab treatment. CONCLUSIONS: FTO downregulation promoted UC by decreasing CerS6 expression, leading to increased S1P accumulation in IECs and aggravating colitis via m6A-dependent mechanisms. Lower FTO expression in UC patients may enhance their response to vedolizumab treatment.

Development and validation of a novel nomogram model to assess the risk of gastric contents in outpatients undergoing elective sedative gastrointestinal endoscopy procedures.

BACKGROUND: Gastric contents may contribute to patients' aspiration during anesthesia. Ultrasound can accurately assess the risk of gastric contents in patients undergoing sedative gastrointestinal endoscopy (GIE) procedures, but its efficiency is limited. Therefore, developing an accurate and efficient model to predict gastric contents in outpatients undergoing elective sedative GIE procedures is greatly desirable. METHODS: This study retrospectively analyzed 1501 patients undergoing sedative GIE procedures. Gastric contents were observed under direct gastroscopic vision and suctioned through the endoscope. High-risk gastric contents were defined as having solid content or liquid volume > 25 ml and pH < 2.5; otherwise, they were considered low-risk gastric contents. Univariate analysis and multivariate analysis were used to select the independent risk factors to predict high-risk gastric contents. Based on the selected independent risk factors, we assigned values to each independent risk factor and established a novel nomogram. The performance of the nomogram was verified in the testing cohort by the metrics of discrimination, calibration, and clinical usefulness. In addition, an online accessible web calculator was constructed. RESULTS: We found BMI, cerebral infarction, cirrhosis, male, age, diabetes, and gastroesophageal reflux disease were risk factors for gastric contents. The AUROCs were 0.911 and 0.864 in the development and testing cohort, respectively. Moreover, the nomogram showed good calibration ability. Decision curve analysis and Clinical impact curve demonstrated that the predictive nomogram was clinically useful. The website of the nomogram was https://medication.shinyapps.io/dynnomapp/. CONCLUSIONS: This study demonstrates that clinical variables can be combined with algorithmic techniques to predict gastric contents in outpatients. Nomogram was constructed from routine variables, and the web calculator had excellent clinical applicability to assess the risk of gastric contents accurately and efficiently in outpatients, assist anesthesiologists in assessment and identify the most appropriate patients for ultrasound.

Mitophagy in neurodegenerative disease pathogenesis.

Mitochondria are critical cellular energy resources and are central to the life of the neuron. Mitophagy selectively clears damaged or dysfunctional mitochondria through autophagic machinery to maintain mitochondrial quality control and homeostasis. Mature neurons are postmitotic and consume substantial energy, thus require highly efficient mitophagy pathways to turn over damaged or dysfunctional mitochondria. Recent evidence indicates that mitophagy is pivotal to the pathogenesis of neurological diseases. However, more work is needed to study mitophagy pathway components as potential therapeutic targets. In this review, we briefly discuss the characteristics of nonselective autophagy and selective autophagy, including ERphagy, aggrephagy, and mitophagy. We then introduce the mechanisms of Parkin-dependent and Parkin-independent mitophagy pathways under physiological conditions. Next, we summarize the diverse repertoire of mitochondrial membrane receptors and phospholipids that mediate mitophagy. Importantly, we review the critical role of mitophagy in the pathogenesis of neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Last, we discuss recent studies considering mitophagy as a potential therapeutic target for treating neurodegenerative diseases. Together, our review may provide novel views to better understand the roles of mitophagy in neurodegenerative disease pathogenesis.

A convenient machine learning model to predict full stomach and evaluate the safety and comfort improvements of preoperative oral carbohydrate in patients undergoing elective painless gastrointestinal endoscopy.

BACKGROUND AND AIMS: Assessment of the patient's gastric contents is the key to avoiding aspiration incidents, however, there is no effective method to determine whether elective painless gastrointestinal endoscopy (GIE) patients have a full stomach or an empty stomach. And previous studies have shown that preoperative oral carbohydrates (POCs) can improve the discomfort induced by fasting, but there are different perspectives on their safety. This study aimed to develop a convenient, accurate machine learning (ML) model to predict full stomach. And based on the model outcomes, evaluate the safety and comfort improvements of POCs in empty- and full stomach groups. METHODS: We enrolled 1386 painless GIE patients between October 2022 and January 2023 in Nanjing First Hospital, and 1090 patients without POCs were used to construct five different ML models to identify full stomach. The metrics of discrimination and calibration validated the robustness of the models. For the best-performance model, we further interpreted it through SHapley Additive exPlanations (SHAP) and constructed a web calculator to facilitate clinical use. We evaluated the safety and comfort improvements of POCs by propensity score matching (PSM) in the two groups, respectively. RESULTS: Random Forest (RF) model showed the greatest discrimination with the area under the receiver operating characteristic curve (AUROC) 0.837 [95% confidence interval (CI): 79.1-88.2], F1 71.5%, and best calibration with a Brier score of 15.2%. The web calculator can be visited at https://medication.shinyapps.io/RF_model/. PSM results demonstrated that POCs significantly reduced the full stomach incident in empty stomach group (p < 0.05), but no differences in full stomach group (p > 0.05). Comfort improved in both groups and was more significant in empty stomach group. CONCLUSIONS: The developed convenient RF model predicted full stomach with high accuracy and interpretability. POCs were safe and comfortably improved in both groups, with more benefit in empty stomach group. These findings may guide the patients' gastrointestinal preparation.

This study is the first model utilizing advanced ML techniques based on multiple clinical variables to identify full stomach. The model is suitable for patient-rich outpatient clinics, primary hospitals, remote regions, and specific clinical settings where POCUS is not available.The developed convenient RF model predicted full stomach with high accuracy and interpretability. The test cohort AUROC was 0.837. We further established an online accessible individualized risk calculator and provided waterfall plots to increase the interpretability of each prediction.The propensity score matching (PSM) showed that preoperative oral carbohydrate (POCs) were safe and comfortably improved in both groups, with more benefit in empty stomach group. These findings may provide information for anesthesiologists to guide patients on POCs.

Multi-kingdom gut microbiota analyses define bacterial-fungal interplay and microbial markers of pan-cancer immunotherapy across cohorts.

The effect of gut bacteria on the response to immune checkpoint inhibitors (ICIs) has been studied, but the relationship between fungi and ICI responses is not fully understood. Herein, 862 fecal metagenomes from 9 different cohorts were integrated for the identification of differentially abundant fungi and subsequent construction of random forest (RF) models to predict ICI responses. Fungal markers demonstrate excellent performance, with an average area under the curve (AUC) of 0.87. Their performance improves even further, reaching an average AUC of 0.89 when combined with bacterial markers. Higher enrichment of exhausted T cells is detected in responders, as predicted by fungal markers. Multi-kingdom network and functional analysis reveal that the fungus Schizosaccharomyces octosporus may ferment starch into short-chain fatty acids in responders. This study provides a fungal profile of the ICI response and the identification of multi-kingdom microbial markers with good performance that may improve the overall applicability of ICI therapy.

Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts.

The perturbations of the gut microbiota and metabolites are closely associated with the progression of inflammatory bowel disease (IBD). However, inconsistent findings across studies impede a comprehensive understanding of their roles in IBD and their potential as reliable diagnostic biomarkers. To address this challenge, here we comprehensively analyze 9 metagenomic and 4 metabolomics cohorts of IBD from different populations. Through cross-cohort integrative analysis (CCIA), we identify a consistent characteristic of commensal gut microbiota. Especially, three bacteria, namely Asaccharobacter celatus, Gemmiger formicilis, and Erysipelatoclostridium ramosum, which are rarely reported in IBD. Metagenomic functional analysis reveals that essential gene of Two-component system pathway, linked to fecal calprotectin, are implicated in IBD. Metabolomics analysis shows 36 identified metabolites with significant differences, while the roles of these metabolites in IBD are still unknown. To further elucidate the relationship between gut microbiota and metabolites, we construct multi-omics biological correlation (MOBC) maps, which highlights gut microbial biotransformation deficiencies and significant alterations in aminoacyl-tRNA synthetases. Finally, we identify multi-omics biomarkers for IBD diagnosis, validated across multiple global cohorts (AUROC values ranging from 0.92 to 0.98). Our results offer valuable insights and a significant resource for developing mechanistic hypotheses on host-microbiome interactions in IBD.

Phosphodiesterase 2 and Its Isoform a as Therapeutic Targets in the Central Nervous System Disorders.

Cyclic adenosine monophosphates (cAMP) and cyclic guanosine monophosphate (cGMP) are two essential second messengers, which are hydrolyzed by phosphodiesterase's (PDEs), such as PDE-2. Pharmacological inhibition of PDE-2 (PDE2A) in the central nervous system improves cAMP and cGMP signaling, which controls downstream proteins related to neuropsychiatric, neurodegenerative, and neurodevelopmental disorders. Considering that there are no specific treatments for these disorders, PDE-2 inhibitors' development has gained more attention in the recent decade. There is high demand for developing new-generation drugs targeting PDE2 for treating diseases in the central nervous and peripheral systems. This review summarizes the relationship between PDE-2 with neuropsychiatric, neurodegenerative, and neurodevelopmental disorders as well as its possible treatment, mainly involving inhibitors of PDE2.

Astragaloside IV inhibits experimental autoimmune encephalomyelitis by modulating the polarization of both microglia/macrophages and astrocytes.

Astragaloside IV (AST IV), a major saponin component and active ingredient isolated from Astragalus membranaceus, has been well known to exhibit neuroprotective effects on diverse models of neurological diseases. Accumulating evidence suggests that dynamic balance of microglia/macrophages and astrocytes plays a vital role in neuroprotection and remyelination. However, dysregulation of microglia/macrophages and astrocytes orchestrate the pathogenesis of nervous system disorders. Therefore, we hypothesized that switching the transformation of microglia/macrophages and astrocytes into the neuroprotective M2 and A2 phenotypes, respectively, could be a potential target for therapeutic intervention. In the present study, we evaluate the efficacy of AST IV intervention on the effects of microglia/macrophages and astrocytes in an experimental autoimmune encephalomyelitis (EAE) model. AST IV improved paralysis and pathology of EAE by inhibiting the neurotoxic M1 microglia/macrophage phenotype, promoting M2 phenotype, shifting astrocytes towards a neuroprotective A2 phenotype, and protecting neurons from apoptosis through inhibition of TLR4/Myd88/NF-kB signalling pathway. Our study showed that AST IV could be a potential and promising drug for multiple sclerosis treatment.