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Abstract Zero-shot stance detection is pivotal for autonomously discerning user stances on novel emerging topics. This task hinges on effective feature alignment transfer from known to unseen targets. To address this, we introduce a zero-shot stance detection framework utilizing multi-expert cooperative learning. This framework comprises two core components: a multi-expert feature extraction module and a gating mechanism for stance feature selection. Our approach involves a unique learning strategy tailored to decompose complex semantic features. This strategy harnesses the expertise of multiple specialists to unravel and learn diverse, intrinsic textual features, enhancing transferability. Furthermore, we employ a gating-based mechanism to selectively filter and fuse these intricate features, optimizing them for stance classification. Extensive experiments on standard benchmark datasets demonstrate that our model significantly surpasses existing baseline models in performance.

Abstract Macrophages play a pivotal role in the inflammatory response to the zoonotic pathogen E. coli, responsible for causing enteric infections. While considerable research has been conducted to comprehend the pathogenesis of this disease, scant attention devoted to host-derived H2S. Herein, we reported that E. coli infection enhanced the expression of CSE in macrophages, accompanied by a significantly increased inflammatory response. This process may be mediated by the involvement of excessive autophagy. Inhibition of AMPK or autophagy with pharmacological inhibitors could alleviate the inflammation. Additionally, cell model showed that the mRNA expression of classic inflammatory factors (Il-1β, Il-6), macrophage polarization markers (iNOS, Arg1) and ROS production was significantly down-regulated after employing CSE specific inhibitor PAG. And PAG is capable of inhibiting excessive autophagy through the LKB1-AMPK-ULK1 axis. Interestingly, exogenous H2S could suppress inflammation response. Our study emphasizes the importance of CSE in regulating the macrophage-mediated response to E. coli. Increased CSE in macrophages leads to excessive inflammation, which should be considered a new target for drug development to treat intestinal infection.

Abstract Previous research has demonstrated that ferredoxin 1 (FDX1) contributes to the accumulation of toxic lipoylated dihydrolipoamide S-acetyltransferase (DLAT) and results in cuproptotic cell death. However, the role that FDX1 plays in human cancer prognosis and immunology is still not well understood. The original data was obtained from TCGA and GEO databases and integrated using R 4.1.0. The TIMER2.0, GEPIA, and BioGPS databases were used to explore FDX1 expression. The impact of FDX1 on prognosis was analyzed using the GEPIA and Kaplan–Meier Plotter databases. External validation will be performed using the PrognoScan database. FDX1 expression in different immune and molecular subtypes of human cancers was evaluated using the TISIDB database. The correlation between FDX1 expression and immune checkpoints (ICP), microsatellite instability (MSI), and tumor mutational burden (TMB) in human cancers was analyzed using R 4.1.0. The TIMER2.0 and GEPIA databases were used to study the relationship between FDX1 expression and tumor-infiltrating immune cells. With the c-BioPortal database, we investigated the genomic alterations of FDX1. Pathway analysis and assessment of the sensitivity potential of FDX1-related drugs were also performed. Using the UALCAN database, we analyzed the differential expression of FDX1 in KIRC (kidney renal clear cell carcinoma) with different clinical features. Coexpression networks of FDX1 were analyzed using LinkedOmics. In general, FDX1 was expressed differently in different types of cancer in humans. Expression of FDX1 was strongly correlated with patient prognosis, ICP, MSI, and TMB. FDX1 was also participated in immune regulation and the tumor microenvironment. Coexpression networks of FDX1 were primarily involved in oxidative phosphorylation regulation. Pathway analysis revealed that the expression of FDX1 was correlated to cancer-related and immune-related pathways. FDX1 has the potential to serve as a biomarker for pan-cancer prognosis and immunology, as well as a novel target for tumor therapy.

Knowledge graphs (KGs) have become a cornerstone for structuring vast amounts of information, enabling sophisticated AI applications across domains. The progression to temporal knowledge graphs (TKGs) introduces time as an essential dimension, allowing for a dynamic representation of entity relationships. Despite their potential, TKGs often suffer from incompleteness, necessitating the development of temporal knowledge graph completion (TKGC) techniques. These methods, particularly focusing on interpolation within the known timeframe, aim to infer missing temporal facts and enhance the predictive capabilities of TKGs. The prevalent reliance on Euclidean space modeling in TKGC methods presents challenges in capturing the complex, hierarchical, and time-varying nature of TKGs. To overcome these limitations, we introduced the attention-based geometry interaction embedding (ATGIE) method, a novel approach that leverages the strengths of multiple geometric spaces, i.e., Euclidean, hyperbolic, and hypersphere, to model the intricacies of TKGs more effectively. ATGIE employs an attention mechanism to dynamically weigh the contributions of different geometric spaces, allowing it to adaptively form reliable spatial structures based on interactive geometric information. This multi-space modeling not only captures the diverse relationships within TKGs but also facilitates a nuanced understanding of how entities and their relationships evolve over time. Through extensive experiments, we demonstrate ATGIE’s superiority in TKGC tasks, showcasing its improvement over existing methods, robustness to noise, and sensitivity to temporal dynamics. The results highlight ATGIE’s potential to advance the state-of-the-art in TKGC, offering a promising direction for research and application in the field.

Abstract Background Post-stroke depression (PSD) can be conceptualized as a complex network where PSD symptoms (PSDS) interact with each other. The neural mechanism of PSD and interactions among PSDS remain to be elucidated. This study aimed to investigate the neuroanatomical substrates of, as well as the interactions between, individual PSDS to better understand the pathogenesis of early-onset PSD. Methods A total of 861 first-ever stroke patients admitted within 7 days poststroke were consecutively recruited from three independent hospitals in China. Sociodemographic, clinical and neuroimaging data were collected upon admission. PSDS assessment with Hamilton Depression Rating Scale was performed at 2 weeks after stroke. Thirteen PSDS were included to develop a psychopathological network in which central symptoms (i.e. symptoms most strongly correlated with other PSDS) were identified. Voxel-based lesion-symptom mapping (VLSM) was performed to uncover the lesion locations associated with overall PSDS severity and severities of individual PSDS, in order to test the hypothesis that strategic lesion locations for central symptoms could significantly contribute to higher overall PSDS severity. Results Depressed mood, Psychiatric anxiety and Loss of interest in work and activities were identified as central PSDS at the early stage of stroke in our relatively stable PSDS network. Lesions in bilateral (especially the right) basal ganglia and capsular regions were found significantly associated with higher overall PSDS severity. Most of the above regions were also correlated with higher severities of 3 central PSDS. The other 10 PSDS could not be mapped to any certain brain region. Conclusions There are stable interactions among early-onset PSDS with Depressed mood, Psychiatric anxiety and Loss of interest as central symptoms. The strategic lesion locations for central symptoms may indirectly induce other PSDS via the symptom network, resulting in higher overall PSDS severity. Trial registration URL: http://www.chictr.org.cn/enIndex.aspx ; Unique identifier: ChiCTR-ROC-17013993.

Staphylococcus aureus can survive within phagocytes. Indeed, we confirm in this study that approximately 10% of population persists in macrophages during S. aureus infection, while the rest are eliminated due to bacteriolysis, which is of particular interest to us. Herein, we observe that the bacteriolysis is an early event accompanied by macrophage death during S. aureus infection. Furthermore, the cell death is significantly accelerated following increased intracellular bacteriolysis, indicating that intracellular bacteriolysis induces cell death. Subsequently, we establish that the cell death is not apoptosis or pyroptosis, but AIM2-mediated necroptosis, accompanied by AIM2 inflammasome activation. This finding challenges the classical model that the cell death that accompanies inflammasome activation is always pyroptosis. In addition, we observe that the apoptosis-associated genes are highly inhibited during S. aureus infection. Finally, we establish in vivo that increased bacteriolysis significantly enhances S. aureus pathogenicity by promoting its dissemination to kidney and leading to an inflammatory cytokine storm in AIM2-mediated manner. Collectively, our data demonstrate that bacteriolysis is detrimental when triggered in excess and its side effect is mediated by AIM2. Meanwhile, we propose a potential immune manipulation strategy by which S. aureus sacrifices the minority to trigger a limited necroptosis, thereby releasing signals from dead cells to inhibit apoptosis and other anti-inflammatory cascades of live cells, eventually surviving within host cells and establishing infection.

Abstract Background Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. The occurrence, development and prognosis of PSD have long been different between males and females. The main purpose of this study was to explore the influencing factors of PSD at 3 months in males and females, and construct random forest (RF) models to rank the influencing factors. Methods This is a prospective multicenter cohort study (Registration number: ChiCTR-ROC-17013993). Stroke patients hospitalized in the department of Neurology of three hospitals in Wuhan were enrolled from May 2018 to August 2019. Scale assessments were performed 24 hours after admission and 3 months after stroke onset. Binary logistic regression analysis was used for univariate and multivariate (stepwise backward method) analysis, when p was less than 0.05, the difference between groups was considered statistically significant. Lastly, the RF models were constructed according to the results of multivariate regression analysis. Results This study found that several baseline variables were associated with PSD at 3 months in males and females. RF model ranked them as stroke severity (OR [odds ratio] =1.17, p

Abstract Poststroke depression (PSD) is a common complication of stroke. Brain network disruptions caused by stroke are potential biological determinants of PSD but their conclusive roles are unavailable. Our study aimed to identify the strategic structural disconnection (SDC) pattern for PSD at three months poststroke and assess the predictive value of SDC information. Our prospective cohort of 697 first-ever acute ischemic stroke patients were recruited from three hospitals in central China. Sociodemographic, clinical, psychological and neuroimaging data were collected at baseline and depression status was assessed at three months poststroke. Voxel-based disconnection-symptom mapping found that SDCs involving bilateral temporal white matter and posterior corpus callosum, as well as white matter next to bilateral prefrontal cortex and posterior parietal cortex, were associated with PSD. This PSD-specific SDC pattern was used to derive SDC scores for all participants. SDC score was an independent predictor of PSD after adjusting for all imaging and clinical-sociodemographic-psychological covariates (odds ratio, 1.25; 95% confidence interval, 1.07, 1.48; P = 0.006). Split-half replication showed the stability and generalizability of above results. When added to the clinical-sociodemographic-psychological prediction model, SDC score significantly improved the model performance and ranked the highest in terms of predictor importance. In conclusion, a strategic SDC pattern involving multiple lobes bilaterally is identified for PSD at 3 months poststroke. The SDC score is an independent predictor of PSD and may improve the predictive performance of the clinical-sociodemographic-psychological prediction model, providing new evidence for the brain-behavior mechanism and biopsychosocial theory of PSD.

Abstract Foamy macrophages containing prominent cytoplasmic lipid droplets (LDs) are found in a variety of infectious diseases. However, their role in Streptococcus uberis-induced mastitis is unknown. Herein, we report that S. uberis infection enhances the fatty acid synthesis pathway in macrophages, resulting in a sharp increase in LD levels, accompanied by a significantly enhanced inflammatory response. This process is mediated by the involvement of fatty acid binding protein 4 (FABP4), a subtype of the fatty acid-binding protein family that plays critical roles in metabolism and inflammation. In addition, FABP4 siRNA inhibitor cell models showed that the deposition of LDs decreased, and the mRNA expression of Tnf, Il1b and Il6 was significantly downregulated after gene silencing. As a result, the bacterial load in macrophages increased. Taken together, these data demonstrate that macrophage LD formation is a host-driven component of the immune response to S. uberis. FABP4 contributes to promoting inflammation via LDs, which should be considered a new target for drug development to treat infections.

Abstract Background Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. Studies on the underlying mechanisms and biological markers of sex differences in PSD are of great significance, but there are still few such studies. Therefore, the main objective of this study was to investigate the association of biomarkers with PSD at 3 months after minor stroke in men and women. Methods This was a prospective multicenter cohort study that enrolled 530 patients with minor stroke (males, 415; females, 115). Demographic information and blood samples of patients were collected within 24 h of admission, and followed up at 3 months after stroke onset. PSD was defined as a depressive disorder due to another medical condition with depressive features, major depressive-like episode, or mixed-mood features according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-V). Univariate analysis was performed using the chi-square test, Mann–Whitney U test, or t-test. Partial least-squares discriminant analysis (PLS-DA) was used to distinguish between patients with and without PSD. Factors with variable importance for projection (VIP) > 1.0 were classified as the most important factors in the model segregation. Results The PLS-DA model mainly included component 1 and component 2 for males and females. For males, the model could explain 13% and 16.9% of the variables, respectively, and 29.9% of the variables in total; the most meaningful predictors were exercise habit and fibrinogen level. For females, the model could explain 15.7% and 10.5% of the variables, respectively, and 26.2% of the variables in total; the most meaningful predictors in the model were brain-derived neurotrophic factor (BDNF), magnesium and free T3. Fibrinogen was positively correlated with the Hamilton Depression Scale-17 items (HAMD-17) score. BDNF, magnesium, and free T3 levels were negatively correlated with the HAMD-17 score. Conclusions This was a prospective cohort study. The most important markers found to be affecting PSD at 3 months were fibrinogen in males, and free T3, magnesium, and BDNF in females. Trial registration ChiCTR-ROC-17013993 .

BackgroundPost-stroke depression (PSD) has been proven to be associated with stroke severity. Thus, we hypothesized that the prevalence of PSD would be lower in patients with mild stroke. We aim to explore predictors of depression at 3 months after mild acute ischemic stroke (MAIS) onset and to develop a practical and convenient prediction model for the early identification of patients at high risk.MethodsA total of 519 patients with MAIS were consecutively recruited from three hospitals in Wuhan city, Hubei province. MAIS was defined as a National Institute of Health Stroke Scale (NIHSS) score of ≤5 at admission. Meeting the DSM-V diagnostic criteria and a 17-item Hamilton Rating Scale for Depression (HAMD-17) score of >7 at their 3-month follow-up were considered the primary outcomes. A multivariable logistic regression model was used to determine the factors adjusted for potential confounders, and all independent predictors were brought into the construction of a nomogram to predict PSD.ResultsThe prevalence of PSD is up to 32% at 3 months after MAIS onset. After adjusting for potential confounders, indirect bilirubin (p = 0.029), physical activity (p = 0.001), smoking (p = 0.025), hospitalization days (p = 0.014), neuroticism (p < 0.001), and MMSE (p < 0.001) remained independently and significantly related with PSD. The concordance index (C-index) of the nomogram jointly constructed by the aforementioned six factors was 0.723 (95% CI: 0.678–0.768).ConclusionThe prevalence of PSD seems equally high even if the ischemic stroke is mild, which calls for great concern from clinicians. In addition, our study found that a higher level of indirect bilirubin can lower the risk of PSD. This finding may provide a potential new approach to PSD treatment. Furthermore, the nomogram including bilirubin is convenient and practical to predict PSD after MAIS onset.

The balance between oxidation and antioxidant is crucial for maintaining homeostasis. Once disrupted, it can lead to various pathological outcomes and diseases, such as depression. Oxidative stress can result in or aggravate a battery of pathological processes including mitochondrial dysfunction, neuroinflammation, autophagical disorder and ferroptosis, which have been found to be involved in the development of depression. Inhibition of oxidative stress and related pathological processes can help improve depression. In this regard, the nuclear factor erythroid 2-related factor 2 (Nrf2) in the antioxidant defense system may play a pivotal role. Nrf2 activation can not only regulate the expression of a series of antioxidant genes that reduce oxidative stress and its damages, but also directly regulate the genes related to the above pathological processes to combat the corresponding alterations. Therefore, targeting Nrf2 has great potential for the treatment of depression. Activation of Nrf2 has antidepressant effect, but the specific mechanism remains to be elucidated. This article reviews the key role of Nrf2 in depression, focusing on the possible mechanisms of Nrf2 regulating oxidative stress and related pathological processes in depression treatment. Meanwhile, we summarize some natural and synthetic compounds targeting Nrf2 in depression therapy. All the above may provide new insights into targeting Nrf2 for the treatment of depression and provide a broad basis for clinical transformation.

ABSTRACT Klebsiella pneumoniae is an opportunistic pathogen that causes serious infections in humans and animals. However, the availability of epidemiological information on clinical mastitis due to K. pneumoniae is limited. To acquire new information regarding K. pneumoniae mastitis, data were mined about K. pneumoniae strains on dairy cattle farms (farms A to H) in 7 Chinese provinces in 2021. Hypermucoviscous strains of K. pneumoniae were obtained by the string test. MICs of antimicrobial agents were determined via the broth microdilution method. Ten antimicrobial resistance genes and virulence genes were identified by PCR. The prevalence of K. pneumoniae was 35.91% (65/181), and 100% of the bacteria were sensitive to enrofloxacin. Nine antimicrobial resistance genes and virulence genes were identified and compared among farms. The hypermucoviscous phenotype was present in 94.44% of isolates from farm B, which may be a function of the rmpA virulence gene. Based on these data, the multidrug-resistant strains SD-14 and HB-21 were chosen and sequenced. Genotypes were assayed for K. pneumoniae isolates from different countries and different hosts using multilocus sequence typing (MLST). Ninety-four sequence types (STs) were found, and 6 STs present a risk for spreading in specific regions. Interestingly, ST43 was observed in bovine isolates for the first time. Our study partially reveals the current distribution characteristics of bovine K. pneumoniae in China and may provide a theoretical basis for the prevention and treatment of bovine K. pneumoniae mastitis. IMPORTANCE K. pneumonia is ubiquitous in nature and infects a wide range of hosts, including animals, and humans. It is one of the leading inducements of clinical mastitis (CM) in dairy cows, a prevalent and costly disease that is predominantly associated with bacterial infection. In general, CM caused by Gram-negative bacteria is more difficult to cure than that associated with Gram-positive pathogens, with an average cost per case of 211.03 U.S. dollars (USD) for Gram-negative bacterial infections compared with 133.73 USD for Gram-positive bacterial CM cases. After Escherichia coli, K. pneumoniae is the second most common Gram-negative cause of bovine CM, but it is the most detrimental in terms of decreased milk yield, discarded milk, treatment costs, death, and culling. In view of the economic implications of K. pneumoniae infection in dairy farming, research into population structure and antibiotic resistance is particularly important.

Alzheimer's disease (AD), an age-dependent neurodegenerative disorder, is the most prevalent neurodegenerative disease worldwide. The primary pathological hallmarks of AD are the deposition of β-amyloid plaques and neurofibrillary tangles. Autophagy, a pathway of clearing damaged organelles, macromolecular aggregates, and long-lived proteins via lysosomal degradation, has emerged as critical for proteostasis in the central nervous system (CNS). Studies have demonstrated that defective autophagy is strongly implicated in AD pathogenesis. Transcription factor EB (TFEB), a master transcriptional regulator of autophagy, enhances the expression of related genes that control autophagosome formation, lysosome function, and autophagic flux. The study of TFEB has greatly increased over the last decade, and the dysfunction of TFEB has been reported to be strongly associated with the pathogenesis of many neurodegenerative disorders, including AD. Here, we delineate the basic understanding of TFEB dysregulation involved in AD pathogenesis, highlighting the existing work that has been conducted on TFEB-mediated autophagy in neurons and other nonneuronal cells in the CNS. Additionally, we summarize the small molecule compounds that target TFEB-regulated autophagy involved in AD therapy. Our review may yield new insights into therapeutic approaches by targeting TFEB and provide a broadly applicable basis for the clinical treatment of AD.

Neutrophil extracellular traps (NETs) are produced by neutrophil activation and usually have both anti-infective and pro-damage effects. Streptococcus uberis (S. uberis), one of the common causative organisms of mastitis, can lead to the production of NETs. Taurine, a free amino acid abundant in the organism, has been shown to have immunomodulatory effects. In this study, we investigated the molecular mechanisms of S. uberis-induced NETs formation and the regulatory role of taurine. The results showed that NETs had a disruptive effect on mammary epithelial cells and barriers, but do not significantly inhibit the proliferation of S. uberis. S. uberis induced NADPH oxidase-dependent NETs. TLR2-mediated activation of the MAPK signaling pathway was involved in this process. Taurine could inhibit the activation of MAPK signaling pathway and NADPH oxidase by modulating the activity of TAK1, thereby inhibiting the production of ROS and NETs. The effects of taurine on NADPH oxidase and NETs in S. uberis infection were also demonstrated in vivo. These results suggest that taurine can protect mammary epithelial cells and barriers from damage by reducing S. uberis-induced NETs. These data provide new insights and strategies for the prevention and control of mastitis.

Poststroke depression (PSD), affecting about one-third of stroke survivors, exerts significant impact on patients’ functional outcome and mortality. Great efforts have been made since the 1970s to unravel the neuroanatomical substrate and the brain-behavior mechanism of PSD. Thanks to advances in neuroimaging and computational neuroscience in the past two decades, new techniques for uncovering the neural basis of symptoms or behavioral deficits caused by focal brain damage have been emerging. From the time of lesion analysis to the era of brain networks, our knowledge and understanding of the neural substrates for PSD are increasing. Pooled evidence from traditional lesion analysis, univariate or multivariate lesion-symptom mapping, regional structural and functional analyses, direct or indirect connectome analysis, and neuromodulation clinical trials for PSD, to some extent, echoes the frontal-limbic theory of depression. The neural substrates of PSD may be used for risk stratification and personalized therapeutic target identification in the future. In this review, we provide an update on the recent advances about the neural basis of PSD with the clinical implications and trends of methodology as the main features of interest.

Neutrophil extracellular traps (NETs) are produced by neutrophil activation and usually have both anti-infective and pro-damage effects. Streptococcus uberis (S. uberis), one of the common causative organisms of mastitis, can lead to the production of NETs. Taurine, a free amino acid abundant in the organism, has been shown to have immunomodulatory effects. In this study, we investigated the molecular mechanisms of S. uberis-induced NETs formation and the regulatory role of taurine. The results showed that NETs had a disruptive effect on mammary epithelial cells and barriers, but do not significantly inhibit the proliferation of S. uberis. S. uberis induced NADPH oxidasedependent NETs. TLR2-mediated activation of the MAPK signaling pathway was involved in this process. Taurine could inhibit the activation of MAPK signaling pathway and NADPH oxidase by modulating the activity of TAK1, thereby inhibiting the production of ROS and NETs. The effects of taurine on NADPH oxidase and NETs in S. uberis infection were also demonstrated in vivo. These results suggest that taurine can protect mammary epithelial cells and barriers from damage by reducing S. uberis-induced NETs. These data provide new insights and strategies for the prevention and control of mastitis. [ABSTRACT FROM AUTHOR]