Exosomal MicroRNAs modulate the cognitive function in fasudil treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice model of Alzheimer's disease.

Alzheimer's disease (AD) is characterized by cognitive decline stemming from the accumulation of beta-amyloid (Aß) plaques and the propagation of tau pathology through synapses. Exosomes, crucial mediators in neuronal development, maintenance, and intercellular communication, have gained attention in AD research. Yet, the molecular mechanisms involving exosomal miRNAs in AD remain elusive. In this study, we treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice, a model for AD, with either vehicle (ADNS) or fasudil (ADF), while C57BL/6 (control) mice received vehicle (WT). Cognitive function was evaluated using the Y-maze test, and AD pathology was confirmed through immunostaining and western blot analysis of Aß plaques and phosphorylated tau. Exosomal RNAs were extracted, sequenced, and analyzed from each mouse group. Our findings revealed that fasudil treatment improved cognitive function in AD mice, as evidenced by increased spontaneous alternation in the Y-maze test and reduced Aß plaque load and phosphorylated tau protein expression in the hippocampus. Analysis of exosomal miRNAs identified three miRNAs (mmu-let-7i-5p, mmu-miR-19a-3p, mmu-miR-451a) common to both ADNS vs ADF and WT vs ADNS groups. Utilizing miRTarBase software, we predicted and analyzed target genes associated with these miRNAs. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of miRNA target genes indicated that mmu-miR-19a-3p and mmu-miR-451a are implicated in signal transduction, immune response, cellular communication, and nervous system pathways. Specifically, mmu-miR-19a-3p targeted genes involved in the sphingolipid signaling pathway, such as Pten and Tnf, while mmu-miR-451a targeted Nsmaf, Gnai3, and Akt3. Moreover, mmu-miR-451a targeted Myc in signaling pathways regulating the pluripotency of stem cells. In conclusion, fasudil treatment enhanced cognitive function by modulating exosomal MicroRNAs, particularly mmu-miR-451a and mmu-miR-19a-3p. These miRNAs hold promise as potential biomarkers and therapeutic targets for novel AD treatments.

Electrostatic Self-Assembly of CdS Quantum Dots with Co9S8 Hollow Nanotubes for Enhanced Visible Light Photocatalytic H2 Production.

CdS quantum dots (CdS QDs) are regarded as a promising photocatalyst due to their remarkable response to visible light and suitable placement of conduction bands and valence bands. However, the problem of photocorrosion severely restricts their application. Herein, the CdS QDs-Co9S8 hollow nanotube composite photocatalyst has been successfully prepared by loading Co9S8 nanotubes onto CdS QDs through an electrostatic self-assembly method. The experimental results show that the introduction of Co9S8 cocatalyst can form a stable structure with CdS QDs, and can effectively avoid the photocorrosion of CdS QDs. Compared with blank CdS QDs, the CdS QDs-Co9S8 composite exhibits obviously better photocatalytic hydrogen evolution performance. In particular, CdS QDs loaded with 30% Co9S8 (CdS QDs-30%Co9S8) demonstrate the best photocatalytic performance, and the H2 production rate reaches 9642.7 µmol·g-1·h-1, which is 60.3 times that of the blank CdS QDs. A series of characterizations confirm that the growth of CdS QDs on Co9S8 nanotubes effectively facilitates the separation and migration of photogenerated carriers, thereby improving the photocatalytic hydrogen production properties of the composite. We expect that this work will facilitate the rational design of CdS-based photocatalysts, thereby enabling the development of more low-cost, high-efficiency and high-stability composites for photocatalysis.

Amino acid metabolomics and machine learning-driven assessment of future liver remnant growth after hepatectomy in livers of various backgrounds.

Accurate assessment of future liver remnant growth after partial hepatectomy (PH) in patients with different liver backgrounds is a pressing clinical issue. Amino acid (AA) metabolism plays a crucial role in liver regeneration. In this study, we combined metabolomics and machine learning (ML) to develop a generalized future liver remnant assessment model for multiple liver backgrounds. The liver index was calculated at 0, 6, 24, 48, 72 and 168 h after 70 % PH in healthy mice and mice with nonalcoholic steatohepatitis or liver fibrosis. The serum levels of 39 amino acids (AAs) were measured using UPLC-MS/MS. The dataset was randomly divided into training and testing sets at a 2:1 ratio, and orthogonal partial least squares regression (OPLS) and minimally biased variable selection in R (MUVR) were used to select a metabolite signature of AAs. To assess liver remnant growth, nine ML models were built, and evaluated using the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). The post-Pareto technique for order preference by similarity to the ideal solution (TOPSIS) was employed for ranking the ML algorithms, and a stacking technique was utilized to establish consensus among the superior algorithms. Compared with those of OPLS, the signature AAs set identified by MUVR (Thr, Arg, EtN, Phe, Asa, 3MHis, Abu, Asp, Tyr, Leu, Ser, and bAib) are more concise. Post-Pareto TOPSIS ranking demonstrated that the majority of ML algorithm in combinations with MUVR outperformed those with OPLS. The established SVM-KNN consensus model performed best, with an R2 of 0.79, an MAE of 0.0029, and an RMSE of 0.0035 for the testing set. This study identified a metabolite signature of 12 AAs and constructed an SVM-KNN consensus model to assess future liver remnant growth after PH in mice with different liver backgrounds. Our preclinical study is anticipated to establish an alternative and generalized assessment method for liver regeneration.

A distinct protein posttranslational modifications-linked OsATL32-OsPPKL2-OsGSK2 loop modulates rice immunity against blast disease.

Protein posttranslational modifications play crucial roles in plant immunity through modulating a complicated signaling network mediated by different hormones. We previously demonstrated that OsATL32, an ATL-type E3 ligase, negatively contributes to rice immunity against Magnaporthe oryzae. Here, we show that OsATL32 forms a loop with OsPPKL2 and OsGSK2 through distinct protein posttranslational modifications to modulate rice immunity. OsATL32 ubiquitinates OsPPKL2, a protein phosphatase with Kelch-like repeat domains that exerts positive roles in regulating rice immunity against M. oryzae and chitin-triggered immune responses, for degradation. The glycogen synthase kinase 2 (OsGSK2), which acts as a negative regulator of rice immunity against M. oryzae and chitin-triggered immune responses, phosphorylates OsATL32 to elevate its protein stability and E3 ligase activity on OsPPKL2. Moreover, OsPPKL2 directly dephosphorylates OsGSK2, affecting its kinase activity on substrates including OsATL32 for phosphorylation. Like OsGSK2 as a BR signaling repressor, OsATL32 negatively regulates BR signaling; conversely, OsPPKL2 plays a positive role in BR signaling. These findings provide a molecular mechanism in which OsATL32 serves as a node connecting BR signaling and immunity by associating with OsPPKL2 and OsGSK2, assembling into a distinct protein posttranslational modifications-linked loop that functions in rice BR signaling and immunity.

Melon CmRLCK VII-8 kinase genes CmRLCK27, CmRLCK30 and CmRLCK34 modulate resistance against bacterial and fungal diseases in Arabidopsis.

Receptor-like cytoplasmic kinases (RLCKs) represent a distinct class of receptor-like kinases crucial for various aspects of plant biology, including growth, development, and stress responses. This study delves into the characterization of RLCK VII-8 members within cucurbits, particularly in melon, examining both structural features and the phylogenetic relationships of these genes/proteins. The investigation extends to their potential involvement in disease resistance by employing ectopic overexpression in Arabidopsis. The promoters of CmRLCK VII-8 genes harbor multiple phytohormone- and stress-responsive cis-acting elements, with the majority (excluding CmRLCK39) displaying upregulated expression in response to defense hormones and fungal infection. Subcellular localization studies reveal that CmRLCK VII-8 proteins predominantly reside on the plasma membrane, with CmRLCK29 and CmRLCK30 exhibiting additional nuclear distribution. Notably, Arabidopsis plants overexpressing CmRLCK30 manifest dwarfing and delayed flowering phenotypes. Overexpression of CmRLCK27, CmRLCK30, and CmRLCK34 in Arabidopsis imparts enhanced resistance against Botrytis cinerea and Pseudomonas syringae pv. tomato DC3000, concomitant with the strengthened expression of defense genes and reactive oxygen species accumulation. The CmRLCK VII-8 members actively participate in chitin- and flg22-triggered immune responses. Furthermore, CmRLCK30 interacts with CmMAPKKK1 and CmARFGAP, adding a layer of complexity to the regulatory network. In summary, this functional characterization underscores the regulatory roles of CmRLCK27, CmRLCK30, and CmRLCK34 in immune responses by influencing pathogen-induced defense gene expression and ROS accumulation.

A NAC transcription factor MNAC3-centered regulatory network negatively modulates rice immunity against blast disease.

NAC transcription factors (TFs) are pivotal in plant immunity against diverse pathogens. Here, we report the functional and regulatory network of MNAC3, a novel NAC TF, in rice immunity. MNAC3, a transcriptional activator, negatively modulates rice immunity against blast and bacterial leaf blight diseases and pathogen-associated molecular pattern (PAMP)-triggered immune responses. MNAC3 binds to a CACG cis-element and activates the transcription of immune-negative target genes OsINO80, OsJAZ10, and OsJAZ11. The negative function of MNAC3 in rice immunity depends on its transcription of downstream genes such as OsINO80 and OsJAZ10. MNAC3 interacts with immunity-related OsPP2C41 (a protein phosphatase), ONAC066 (a NAC TF), and OsDjA6 (a DnaJ chaperone). ONAC066 and OsPP2C41 attenuate MNAC3 transcriptional activity, while OsDjA6 promotes it. Phosphorylation of MNAC3 at S163 is critical for its negative functions in rice immunity. OsPP2C41, which plays positive roles in rice blast resistance and chitin-triggered immune responses, dephosphorylates MNAC3, suppressing its transcriptional activity on the target genes OsINO80, OsJAZ10, and OsJAZ11 and promoting the translocation of MNAC3 from nucleus to cytoplasm. These results establish a MNAC3-centered regulatory network in which OsPP2C41 dephosphorylates MNAC3, attenuating its transcriptional activity on downstream immune-negative target genes in rice. Together, these findings deepen our understanding of molecular mechanisms in rice immunity and offer a novel strategy for genetic improvement of rice disease resistance.

Amino acid metabolomics and machine learning for assessment of post-hepatectomy liver regeneration.

Objective: Amino acid (AA) metabolism plays a vital role in liver regeneration. However, its measuring utility for post-hepatectomy liver regeneration under different conditions remains unclear. We aimed to combine machine learning (ML) models with AA metabolomics to assess liver regeneration in health and non-alcoholic steatohepatitis (NASH). Methods: The liver index (liver weight/body weight) was calculated following 70% hepatectomy in healthy and NASH mice. The serum levels of 39 amino acids were measured using ultra-high performance liquid chromatography-tandem mass spectrometry analysis. We used orthogonal partial least squares discriminant analysis to determine differential AAs and disturbed metabolic pathways during liver regeneration. The SHapley Additive exPlanations algorithm was performed to identify potential AA signatures, and five ML models including least absolute shrinkage and selection operator, random forest, K-nearest neighbor (KNN), support vector regression, and extreme gradient boosting were utilized to assess the liver index. Results: Eleven and twenty-two differential AAs were identified in the healthy and NASH groups, respectively. Among these metabolites, arginine and proline metabolism were commonly disturbed metabolic pathways related to liver regeneration in both groups. Five AA signatures were identified, including hydroxylysine, L-serine, 3-methylhistidine, L-tyrosine, and homocitrulline in healthy group, and L-arginine, 2-aminobutyric acid, sarcosine, beta-alanine, and L-cysteine in NASH group. The KNN model demonstrated the best evaluation performance with mean absolute error, root mean square error, and coefficient of determination values of 0.0037, 0.0047, 0.79 and 0.0028, 0.0034, 0.71 for the healthy and NASH groups, respectively. Conclusion: The KNN model based on five AA signatures performed best, which suggests that it may be a valuable tool for assessing post-hepatectomy liver regeneration in health and NASH.

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.

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.

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.

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.

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.

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.

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.

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.

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.