Multimodal charting of molecular and functional cell states via in situ electro-sequencing.

Paired mapping of single-cell gene expression and electrophysiology is essential to understand gene-to-function relationships in electrogenic tissues. Here, we developed in situ electro-sequencing (electro-seq) that combines flexible bioelectronics with in situ RNA sequencing to stably map millisecond-timescale electrical activity and profile single-cell gene expression from the same cells across intact biological networks, including cardiac and neural patches. When applied to human-induced pluripotent stem-cell-derived cardiomyocyte patches, in situ electro-seq enabled multimodal in situ analysis of cardiomyocyte electrophysiology and gene expression at the cellular level, jointly defining cell states and developmental trajectories. Using machine-learning-based cross-modal analysis, in situ electro-seq identified gene-to-electrophysiology relationships throughout cardiomyocyte development and accurately reconstructed the evolution of gene expression profiles based on long-term stable electrical measurements. In situ electro-seq could be applicable to create spatiotemporal multimodal maps in electrogenic tissues, potentiating the discovery of cell types and gene programs responsible for electrophysiological function and dysfunction.

Macrophages Facilitate Electrical Conduction in the Heart.

Organ-specific functions of tissue-resident macrophages in the steady-state heart are unknown. Here, we show that cardiac macrophages facilitate electrical conduction through the distal atrioventricular node, where conducting cells densely intersperse with elongated macrophages expressing connexin 43. When coupled to spontaneously beating cardiomyocytes via connexin-43-containing gap junctions, cardiac macrophages have a negative resting membrane potential and depolarize in synchrony with cardiomyocytes. Conversely, macrophages render the resting membrane potential of cardiomyocytes more positive and, according to computational modeling, accelerate their repolarization. Photostimulation of channelrhodopsin-2-expressing macrophages improves atrioventricular conduction, whereas conditional deletion of connexin 43 in macrophages and congenital lack of macrophages delay atrioventricular conduction. In the Cd11bDTR mouse, macrophage ablation induces progressive atrioventricular block. These observations implicate macrophages in normal and aberrant cardiac conduction.

SPARCLE, a p53-induced lncRNA, controls apoptosis after genotoxic stress by promoting PARP-1 cleavage.

p53, master transcriptional regulator of the genotoxic stress response, controls cell-cycle arrest and apoptosis following DNA damage. Here, we identify a p53-induced lncRNA suicidal PARP-1 cleavage enhancer (SPARCLE) adjacent to miR-34b/c required for p53-mediated apoptosis. SPARCLE is a ∼770-nt, nuclear lncRNA induced 1 day after DNA damage. Despite low expression (<16 copies/cell), SPARCLE deletion increases DNA repair and reduces DNA-damage-induced apoptosis as much as p53 deficiency, while its overexpression restores apoptosis in p53-deficient cells. SPARCLE does not alter gene expression. SPARCLE binds to PARP-1 with nanomolar affinity and causes apoptosis by acting as a caspase-3 cofactor for PARP-1 cleavage, which separates PARP-1's N-terminal (NT) DNA-binding domain from its catalytic domains. NT-PARP-1 inhibits DNA repair. Expressing NT-PARP-1 in SPARCLE-deficient cells increases unrepaired DNA damage and restores apoptosis after DNA damage. Thus, SPARCLE enhances p53-induced apoptosis by promoting PARP-1 cleavage, which interferes with DNA-damage repair.

Transfer learning enables predictions in network biology.

Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recently, transfer learning has revolutionized fields such as natural language understanding1,2 and computer vision3 by leveraging deep learning models pretrained on large-scale general datasets that can then be fine-tuned towards a vast array of downstream tasks with limited task-specific data. Here, we developed a context-aware, attention-based deep learning model, Geneformer, pretrained on a large-scale corpus of about 30 million single-cell transcriptomes to enable context-specific predictions in settings with limited data in network biology. During pretraining, Geneformer gained a fundamental understanding of network dynamics, encoding network hierarchy in the attention weights of the model in a completely self-supervised manner. Fine-tuning towards a diverse panel of downstream tasks relevant to chromatin and network dynamics using limited task-specific data demonstrated that Geneformer consistently boosted predictive accuracy. Applied to disease modelling with limited patient data, Geneformer identified candidate therapeutic targets for cardiomyopathy. Overall, Geneformer represents a pretrained deep learning model from which fine-tuning towards a broad range of downstream applications can be pursued to accelerate discovery of key network regulators and candidate therapeutic targets.

The p53-induced RNA-binding protein ZMAT3 is a splicing regulator that inhibits the splicing of oncogenic CD44 variants in colorectal carcinoma.

p53 is an intensely studied tumor-suppressive transcription factor. Recent studies suggest that the RNA-binding protein (RBP) ZMAT3 is important in mediating the tumor-suppressive effects of p53. Here, we globally identify ZMAT3-regulated RNAs and their binding sites at nucleotide resolution in intact colorectal cancer (CRC) cells. ZMAT3 binds to thousands of mRNA precursors, mainly at intronic uridine-rich sequences and affects their splicing. The strongest alternatively spliced ZMAT3 target was CD44, a cell adhesion gene and stem cell marker that controls tumorigenesis. Silencing ZMAT3 increased inclusion of CD44 variant exons, resulting in significant up-regulation of oncogenic CD44 isoforms (CD44v) and increased CRC cell growth that was rescued by concurrent knockdown of CD44v Silencing p53 phenocopied the loss of ZMAT3 with respect to CD44 alternative splicing, suggesting that ZMAT3-mediated regulation of CD44 splicing is vital for p53 function. Collectively, our findings uncover a p53-ZMAT3-CD44 axis in growth suppression in CRC cells.

Rice false smut virulence protein subverts host chitin perception and signaling at lemma and palea for floral infection.

The flower-infecting fungus Ustilaginoidea virens causes rice false smut, which is a severe emerging disease threatening rice (Oryza sativa) production worldwide. False smut not only reduces yield, but more importantly produces toxins on grains, posing a great threat to food safety. U. virens invades spikelets via the gap between the 2 bracts (lemma and palea) enclosing the floret and specifically infects the stamen and pistil. Molecular mechanisms for the U. virens-rice interaction are largely unknown. Here, we demonstrate that rice flowers predominantly employ chitin-triggered immunity against U. virens in the lemma and palea, rather than in the stamen and pistil. We identify a crucial U. virens virulence factor, named UvGH18.1, which carries glycoside hydrolase activity. Mechanistically, UvGH18.1 functions by binding to and hydrolyzing immune elicitor chitin and interacting with the chitin receptor CHITIN ELICITOR BINDING PROTEIN (OsCEBiP) and co-receptor CHITIN ELICITOR RECEPTOR KINASE1 (OsCERK1) to impair their chitin-induced dimerization, suppressing host immunity exerted at the lemma and palea for gaining access to the stamen and pistil. Conversely, pretreatment on spikelets with chitin induces a defense response in the lemma and palea, promoting resistance against U. virens. Collectively, our data uncover a mechanism for a U. virens virulence factor and the critical location of the host-pathogen interaction in flowers and provide a potential strategy to control rice false smut disease.

Clonal Hematopoiesis of Indeterminate Potential With Loss of Tet2 Enhances Risk for Atrial Fibrillation Through Nlrp3 Inflammasome Activation.

BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP), a common age-associated phenomenon, associates with increased risk of both hematological malignancy and cardiovascular disease. Although CHIP is known to increase the risk of myocardial infarction and heart failure, the influence of CHIP in cardiac arrhythmias, such as atrial fibrillation (AF), is less explored. METHODS: CHIP prevalence was determined in the UK Biobank, and incident AF analysis was stratified by CHIP status and clone size using Cox proportional hazard models. Lethally irradiated mice were transplanted with hematopoietic-specific loss of Tet2, hematopoietic-specific loss of Tet2 and Nlrp3, or wild-type control and fed a Western diet, compounded with or without NLRP3 (NLR [NACHT, LRR {leucine rich repeat}] family pyrin domain containing protein 3) inhibitor, NP3-361, for 6 to 9 weeks. Mice underwent in vivo invasive electrophysiology studies and ex vivo optical mapping. Cardiomyocytes from Ldlr-/- mice with hematopoietic-specific loss of Tet2 or wild-type control and fed a Western diet were isolated to evaluate calcium signaling dynamics and analysis. Cocultures of pluripotent stem cell-derived atrial cardiomyocytes were incubated with Tet2-deficient bone marrow-derived macrophages, wild-type control, or cytokines IL-1ß (interleukin 1ß) or IL-6 (interleukin 6). RESULTS: Analysis of the UK Biobank showed individuals with CHIP, in particular TET2 CHIP, have increased incident AF. Hematopoietic-specific inactivation of Tet2 increases AF propensity in atherogenic and nonatherogenic mouse models and is associated with increased Nlrp3 expression and CaMKII (Ca2+/calmodulin-dependent protein kinase II) activation, with AF susceptibility prevented by inactivation of Nlrp3. Cardiomyocytes isolated from Ldlr-/- mice with hematopoietic inactivation of Tet2 and fed a Western diet have impaired calcium release from the sarcoplasmic reticulum into the cytosol, contributing to atrial arrhythmogenesis. Abnormal sarcoplasmic reticulum calcium release was recapitulated in cocultures of cardiomyocytes with the addition of Tet2-deficient macrophages or cytokines IL-1ß or IL-6. CONCLUSIONS: We identified a modest association between CHIP, particularly TET2 CHIP, and incident AF in the UK Biobank population. In a mouse model of AF resulting from hematopoietic-specific inactivation of Tet2, we propose altered calcium handling as an arrhythmogenic mechanism, dependent on Nlrp3 inflammasome activation. Our data are in keeping with previous studies of CHIP in cardiovascular disease, and further studies into the therapeutic potential of NLRP3 inhibition for individuals with TET2 CHIP may be warranted.

Loss of the Atrial Fibrillation-Related Gene, Zfhx3, Results in Atrial Dilation and Arrhythmias.

BACKGROUND: ZFHX3 (zinc finger homeobox 3), a gene that encodes a large transcription factor, is at the second-most significantly associated locus with atrial fibrillation (AF), but its function in the heart is unknown. This study aims to identify causative genetic variation related to AF at the ZFHX3 locus and examine the impact of Zfhx3 loss on cardiac function in mice. METHODS: CRISPR-Cas9 genome editing, chromatin immunoprecipitation, and luciferase assays in pluripotent stem cell-derived cardiomyocytes were used to identify causative genetic variation related to AF at the ZFHX3 locus. Cardiac function was assessed by echocardiography, magnetic resonance imaging, electrophysiology studies, calcium imaging, and RNA sequencing in mice with heterozygous and homozygous cardiomyocyte-restricted Zfhx3 loss (Zfhx3 Het and knockout, respectively). Human cardiac single-nucleus ATAC (assay for transposase-accessible chromatin)-sequencing data was analyzed to determine which genes in atrial cardiomyocytes are directly regulated by ZFHX3. RESULTS: We found single-nucleotide polymorphism (SNP) rs12931021 modulates an enhancer regulating ZFHX3 expression, and the AF risk allele is associated with decreased ZFHX3 transcription. We observed a gene-dose response in AF susceptibility with Zfhx3 knockout mice having higher incidence, frequency, and burden of AF than Zfhx3 Het and wild-type mice, with alterations in conduction velocity, atrial action potential duration, calcium handling and the development of atrial enlargement and thrombus, and dilated cardiomyopathy. Zfhx3 loss results in atrial-specific differential effects on genes and signaling pathways involved in cardiac pathophysiology and AF. CONCLUSIONS: Our findings implicate ZFHX3 as the causative gene at the 16q22 locus for AF, and cardiac abnormalities caused by loss of cardiac Zfhx3 are due to atrial-specific dysregulation of pathways involved in AF susceptibility. Together, these data reveal a novel and important role for Zfhx3 in the control of cardiac genes and signaling pathways essential for normal atrial function.

Unraveling CCL20's role by regulating Th17 cell chemotaxis in experimental autoimmune prostatitis.

Chronic prostatitis and chronic pelvic pain syndrome (CP/CPPS), a prevalent urological ailment, exerts a profound influence upon the well-being of the males. Autoimmunity driven by Th17 cells has been postulated as a potential factor in CP/CPPS pathogenesis. Nonetheless, elucidating the precise mechanisms governing Th17 cell recruitment to the prostate, triggering inflammation, remained an urgent inquiry. This study illuminated that CCL20 played a pivotal role in attracting Th17 cells to the prostate, thereby contributing to prostatitis development. Furthermore, it identified prostate stromal cells and immune cells as likely sources of CCL20. Additionally, this research unveiled that IL-17A, released by Th17 cells, could stimulate macrophages to produce CCL20 through the NF-κB/MAPK/PI3K pathway. The interplay between IL-17A and CCL20 establishes a positive feedback loop, which might serve as a critical mechanism underpinning the development of chronic prostatitis, thus adding complexity to its treatment challenges.

Age-Dependent Female Survival Advantage in Hepatocellular Carcinoma: A Multicenter Cohort Study.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) has a higher incidence in males, but the association of sex with survival remains controversial. This study aimed to examine the effect of sex on HCC survival and its association with age. METHODS: Among 33,238 patients with HCC from 12 Chinese tertiary hospitals, 4175 patients who underwent curative-intent hepatectomy or ablation were analyzed. Cancer-specific survival (CSS) was analyzed using Cox regression and Kaplan-Meier methods. Two propensity score methods and multiple mediation analysis were applied to mitigate confounding. To explore the effect of estrogen, a candidate sex-specific factor that changes with age, female participants' history of estrogen use, and survival were analyzed. RESULTS: There were 3321 males and 854 females included. A sex-related disparity of CSS was present and showed a typical age-dependent pattern: a female survival advantage over males appeared at the perimenopausal age of 45 to 54 years (hazard risk [HR], 0.77; 5-year CSS, 85.7% vs 70.6%; P = .018), peaked at the early postmenopausal age of 55 to 59 years (HR, 0.57; 5-year CSS, 89.8% vs 73.5%; P = .015), and was not present in the premenopausal (<45 y) and late postmenopausal groups (≥60 y). Consistent patterns were observed in patients after either ablation or hepatectomy. These results were sustained with propensity score analyses. Confounding or mediation effects accounted for only 19.5% of sex survival disparity. Female estrogen users had significantly longer CSS than nonusers (HR, 0.74; 5-year CSS, 79.6% vs 72.5%; P = .038). CONCLUSIONS: A female survival advantage in HCC depends on age, and this may be associated with age-dependent, sex-specific factors.

Overexpression of PavHIPP16 from Prunus avium enhances cold stress tolerance in transgenic tobacco.

BACKGROUND: The heavy metal-associated isoprenylated plant protein (HIPP) is an important regulatory element in response to abiotic stresses, especially playing a key role in low-temperature response. RESULTS: This study investigated the potential function of PavHIPP16 up-regulated in sweet cherry under cold stress by heterologous overexpression in tobacco. The results showed that the overexpression (OE) lines' growth state was better than wild type (WT), and the germination rate, root length, and fresh weight of OE lines were significantly higher than those of WT. In addition, the relative conductivity and malondialdehyde (MDA) content of the OE of tobacco under low-temperature treatment were substantially lower than those of WT. In contrast, peroxidase (POD), superoxide dismutase (SOD), catalase (CAT) activities, hydrogen peroxide (H2O2), proline, soluble protein, and soluble sugar contents were significantly higher than those of WT. Yeast two-hybrid assay (Y2H) and luciferase complementation assay verified the interactions between PavbHLH106 and PavHIPP16, suggesting that these two proteins co-regulated the cold tolerance mechanism in plants. The research results indicated that the transgenic lines could perform better under low-temperature stress by increasing the antioxidant enzyme activity and osmoregulatory substance content of the transgenic plants. CONCLUSIONS: This study provides genetic resources for analyzing the biological functions of PavHIPPs, which is important for elucidating the mechanisms of cold resistance in sweet cherry.

Single-nucleus transcriptomic analysis reveals the relationship between gene expression in oligodendrocyte lineage and major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a common mental illness that affects millions of people worldwide and imposes a heavy burden on individuals, families and society. Previous studies on MDD predominantly focused on neurons and employed bulk homogenates of brain tissues. This paper aims to decipher the relationship between oligodendrocyte lineage (OL) development and MDD at the single-cell resolution level. METHODS: Here, we present the use of a guided regularized random forest (GRRF) algorithm to explore single-nucleus RNA sequencing profiles (GSE144136) of the OL at four developmental stages, which contains dorsolateral prefrontal cortex of 17 healthy controls (HC) and 17 MDD cases, generated by Nagy C et al. We prioritized and ordered differentially expressed genes (DEGs) based on Nagy et al., which could predominantly discriminate cells in the four developmental stages and two adjacent developmental stages of the OL. We further screened top-ranked genes that distinguished between HC and MDD in four developmental stages. Moreover, we estimated the performance of the GRRF model via the area under the curve value. Additionally, we validated the pivotal candidate gene Malat1 in animal models. RESULTS: We found that, among the four developmental stages, the onset development of OL (OPC2) possesses the best predictive power for distinguishing HC and MDD, and long noncoding RNA MALAT1 has top-ranked importance value in candidate genes of four developmental stages. In addition, results of fluorescence in situ hybridization assay showed that Malat1 plays a critical role in the occurrence of depression. CONCLUSIONS: Our work elucidates the mechanism of MDD from the perspective of OL development at the single-cell resolution level and provides novel insight into the occurrence of depression.

[18F]SynVesT-1 and [18F]FDG quantitative PET imaging in the presurgical evaluation of MRI-negative children with focal cortical dysplasia type II.

PURPOSE: MRI-negative children with focal cortical dysplasia type II (FCD II) are one of the most challenging cases in surgical epilepsy management. We aimed to utilize quantitative positron emission tomography (QPET) analysis to complement [18F]SynVesT-1 and [18F]FDG PET imaging and facilitate the localization of epileptogenic foci in pediatric MRI-negative FCD II patients. METHODS: We prospectively enrolled 17 MRI-negative children with FCD II who underwent [18F]SynVesT-1 and [18F]FDG PET before surgical resection. The QPET scans were analyzed using statistical parametric mapping (SPM) with respect to healthy controls. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of [18F]SynVesT-1 PET, [18F]FDG PET, [18F]SynVesT-1 QPET, and [18F]FDG QPET in the localization of epileptogenic foci were assessed. Additionally, we developed a multivariate prediction model based on dual trace PET/QPET assessment. RESULTS: The AUC values of [18F]FDG PET and [18F]SynVesT-1 PET were 0.861 (sensitivity = 94.1%, specificity = 78.2%, PPV = 38.1%, NPV = 98.9%) and 0.908 (sensitivity = 82.4%, specificity = 99.2%, PPV = 93.3%, NPV = 97.5%), respectively. [18F]FDG QPET showed lower sensitivity (76.5%) and NPV (96.6%) but higher specificity (95.0%) and PPV (68.4%) than visual assessment, while [18F]SynVesT-1 QPET exhibited higher sensitivity (94.1%) and NPV (99.1%) but lower specificity (97.5%) and PPV (84.2%). The multivariate prediction model had the highest AUC value (AUC = 0.996, sensitivity = 100.0%, specificity = 96.6%, PPV = 81.0%, NPV = 100%). CONCLUSIONS: The multivariate prediction model based on [18F]SynVesT-1 and [18F]FDG PET/QPET assessments holds promise in noninvasively identifying epileptogenic regions in MRI-negative children with FCD II. Furthermore, the combination of visual assessment and QPET may improve the sensitivity and specificity of diagnostic tests in localizing epileptogenic foci and achieving a preferable surgical outcome in MRI-negative FCD II.

Individual cerebellar metabolic connectome in patients with MTLE and NTLE associated with surgical prognosis.

PURPOSE: This study aimed to comprehensively explore the different metabolic connectivity topological changes in MTLE and NTLE, as well as their association with surgical outcomes. METHODS: This study enrolled a cohort of patients with intractable MTLE and NTLE. Each individual's metabolic connectome, as determined by Kullback-Leibler divergence similarity estimation for the [18F]FDG PET image, was employed to conduct a comprehensive analysis of the cerebral metabolic network. Alterations in network connectivity were assessed by extracting and evaluating the strength of edge and weighted connectivity. By utilizing these two connectivity strength metrics with the cerebellum, we explored the network properties of connectivity and its association with prognosis in surgical patients. RESULTS: Both MTLE and NTLE patients exhibited substantial alterations in the connectivity of the metabolic network at the edge and nodal levels (p < 0.01, FDR corrected). The key disparity between MTLE and NTLE was observed in the cerebellum. In MTLE, there was a predominance of increased connectivity strength in the cerebellum. Whereas, a decrease in cerebellar connectivity was identified in NTLE. It was found that in MTLE, higher edge connectivity and weighted connectivity strength in the contralateral cerebellar hemisphere correlated with improved surgical outcomes. Conversely, in NTLE, a higher edge metabolic connectivity strength in the ipsilateral cerebellar hemisphere suggested a worse surgical prognosis. CONCLUSION: The cerebellum exhibits distinct topological characteristics in the metabolic networks between MTLE and NTLE. The hyper- or hypo-metabolic connectivity in the cerebellum may be a prognostic biomarker of surgical prognosis, which might aid in therapeutic decision-making for TLE individuals.

UFMylation of HRD1 regulates endoplasmic reticulum homeostasis.

Ubiquitin fold modifier 1 is a small ubiquitin-like protein modifier that is essential for embryonic development of metazoans. Although UFMylation has been connected to endoplasmic reticulum homeostasis, the underlying mechanisms and the relevant cellular targets are largely unknown. Here, we show that HRD1, a ubiquitin ligase of ER-associated protein degradation (ERAD), is a novel substrate of UFM1 conjugation. HRD1 interacts with UFMylation components UFL1 and DDRGK1 and is UFMylated at Lys610 residue. In UFL1-depleted cells, the stability of HRD1 is increased and its ubiquitination modification is reduced. In the event of ER stress, the UFMylation and ubiquitination modification of HRD1 is gradually inhibited over time. Alteration of HRD1 Lys610 residue to arginine impairs its ability to degrade unfolded or misfolded proteins to disturb protein processing in ER. These results suggest that UFMylation of HRD1 facilitates ERAD function to maintain ER homeostasis.

Adult type I Gaucher disease with splenectomy caused by a compound heterozygous GBA1 mutation in a Chinese patient: a case report.

Gaucher disease (GD) is an autosomal recessive ailment resulting from glucocerebrosidase deficiency caused by a mutation in the GBA1 gene, leading to multi-organ problems in the liver, spleen, and bone marrow. In China, GD is extremely uncommon and has a lower incidence rate than worldwide. In this study, we report the case of an adult male with an enlarged spleen for 13 years who presented with abdominal distension, severe loss of appetite and weight, reduction of the three-line due to hypersplenism, frequent nosebleeds, and bloody stools. Regrettably, the unexpected discovery of splenic pathology suggestive of splenic Gaucher disease was only made after a splenectomy due to a lack of knowledge about rare disorders. Our patient's delayed diagnosis may have been due to the department where he was originally treated, but it highlights the need for multidisciplinary consultation in splenomegaly of unknown etiology. We then investigated the patient's clinical phenotypes and gene mutation features using genetically phenotypical analysis. The analysis of the GBA1 gene sequence indicated that the patient carried a compound heterozygous mutation consisting of two potentially disease-causing mutations: c.907C > A (p. Leu303Ile) and c.1448 T > C (p. Leu483Pro). While previous research has linked the p. Leu483Pro mutation site to neurologic GD phenotypes (GD2 and GD3), the patients in this investigation were identified as having non-neuronopathic GD1. The other mutation, p. Leu303Ile, is a new GD-related mutation not indexed in PubMed that enriches the GBA1 gene mutation spectrum. Biosignature analysis has shown that both mutations alter the protein's three-dimensional structure, which may be a pathogenic mechanism for GD1 in this patient.

Preoperative structural-functional coupling at the default mode network predicts surgical outcomes of temporal lobe epilepsy.

OBJECTIVE: Structural-functional coupling (SFC) has shown great promise in predicting postsurgical seizure recurrence in patients with temporal lobe epilepsy (TLE). In this study, we aimed to clarify the global alterations in SFC in TLE patients and predict their surgical outcomes using SFC features. METHODS: This study analyzed presurgical diffusion and functional magnetic resonance imaging data from 71 TLE patients and 48 healthy controls (HCs). TLE patients were categorized into seizure-free (SF) and non-seizure-free (nSF) groups based on postsurgical recurrence. Individual functional connectivity (FC), structural connectivity (SC), and SFC were quantified at the regional and modular levels. The data were compared between the TLE and HC groups as well as among the TLE, SF, and nSF groups. The features of SFC, SC, and FC were categorized into three datasets: the modular SFC dataset, regional SFC dataset, and SC/FC dataset. Each dataset was independently integrated into a cross-validated machine learning model to classify surgical outcomes. RESULTS: Compared with HCs, the visual and subcortical modules exhibited decoupling in TLE patients (p < .05). Multiple default mode network (DMN)-related SFCs were significantly higher in the nSF group than in the SF group (p < .05). Models trained using the modular SFC dataset demonstrated the highest predictive performance. The final prediction model achieved an area under the receiver operating characteristic curve of .893 with an overall accuracy of .887. SIGNIFICANCE: Presurgical hyper-SFC in the DMN was strongly associated with postoperative seizure recurrence. Furthermore, our results introduce a novel SFC-based machine learning model to precisely classify the surgical outcomes of TLE.

Wheel Running During Pregnancy Alleviates Anxiety-and Depression-Like Behaviors During the Postpartum Period in Mice: The Roles of NLRP3 Neuroinflammasome Activation, Prolactin, and the Prolactin Receptor in the Hippocampus.

Despite the increase in the prevalence of postpartum depression among maternal disorder, its treatment outcomes remain suboptimal. Studies have shown that exercise can reduce postpartum depressive episodes in the mother, but the effects of exercise during pregnancy on maternal behavior and the potential mechanisms involved remain poorly understood. From the second day of pregnancy to the day of birth, dams exercised for 1 h a day by running on a controlled wheel. The maternal behaviors of the dams were assessed on postpartum day 2 to postpartum day 8. Chronic restraint stress was applied from postpartum day 2 to day 12. Blood was collected on postpartum days 3 and 8, then subjected to ELISA to determine the serum concentration of prolactin. The weight of each dam and the food intake were recorded. Anxiety- and depression-like behavioral tests were conducted, and hippocampal neuroinflammation and prolactin receptor levels were measured. The dams exhibited elevated levels of anxiety and depression, decreased serum prolactin levels, decreased prolactin receptor expression, and activation of NLRP3-mediated neuroinflammation in the hippocampus following the induction of postpartum chronic restraint stress, which were reversed with controlled wheel running during pregnancy. Overall, the findings of this study revealed that the preventive effects of exercise during pregnancy on postpartum anxiety-and depression-like behaviors were accompanied by increased serum prolactin levels, hippocampal prolactin receptor expression and hippocampal NLRP3-mediated neuroinflammation.

CircRNA and Stroke: New Insight of Potential Biomarkers and Therapeutic Targets.

Stroke, the second-largest cause of death and the leading cause of disability globally, presents significant challenges in terms of prognosis and treatment. Identifying reliable prognosis biomarkers and treatment targets is crucial to address these challenges. Circular RNA (circRNA) has emerged as a promising research biomarkers and therapeutic targets because of its tissue specificity and conservation. However, the potential role of circRNA in stroke prognosis and treatment remains largely unexplored. This review briefly elucidate the mechanism underlying circRNA's involvement in stroke pathophysiology. Additionally, this review summarizes the impact of circRNA on different forms of strokes, including ischemic stroke and hemorrhagic stroke. And, this article discusses the positive effects of circRNA on promoting cerebrovascular repair and regeneration, maintaining the integrity of the blood-brain barrier (BBB), and reducing neuronal injury and immune inflammatory response. In conclusion, the significance of circRNA as a potential prognostic biomarker and a viable therapeutic target was underscored.

Artificial intelligence-assisted system for the assessment of Forrest classification of peptic ulcer bleeding: a multicenter diagnostic study.

BACKGROUND: Inaccurate Forrest classification may significantly affect clinical outcomes, especially in high risk patients. Therefore, this study aimed to develop a real-time deep convolutional neural network (DCNN) system to assess the Forrest classification of peptic ulcer bleeding (PUB). METHODS: A training dataset (3868 endoscopic images) and an internal validation dataset (834 images) were retrospectively collected from the 900th Hospital, Fuzhou, China. In addition, 521 images collected from four other hospitals were used for external validation. Finally, 46 endoscopic videos were prospectively collected to assess the real-time diagnostic performance of the DCNN system, whose diagnostic performance was also prospectively compared with that of three senior and three junior endoscopists. RESULTS: The DCNN system had a satisfactory diagnostic performance in the assessment of Forrest classification, with an accuracy of 91.2% (95%CI 89.5%-92.6%) and a macro-average area under the receiver operating characteristic curve of 0.80 in the validation dataset. Moreover, the DCNN system could judge suspicious regions automatically using Forrest classification in real-time videos, with an accuracy of 92.0% (95%CI 80.8%-97.8%). The DCNN system showed more accurate and stable diagnostic performance than endoscopists in the prospective clinical comparison test. This system helped to slightly improve the diagnostic performance of senior endoscopists and considerably enhance that of junior endoscopists. CONCLUSION: The DCNN system for the assessment of the Forrest classification of PUB showed satisfactory diagnostic performance, which was slightly superior to that of senior endoscopists. It could therefore effectively assist junior endoscopists in making such diagnoses during gastroscopy.