Gata4 Interacts With Hedgehog Signaling Pathway In Regulating Outflow Tract Development

ABSTRACT Congenital heart diseases (CHDs) are among the most common type of developmental anomaly affecting 8 in 1000 live births. Approximately 30% of CHDs involve cardiac outflow tract (OFT) malformation which leads to significant morbidity and mortality in both children and adults. Development of OFT is regulated by a complex genetic network including Sonic-Hedgehog signaling pathway, TGF-β and BMP signaling pathway. Mutation of a transcription factor, Gata4, has been known to cause OFT defects including double outlet right ventricle (DORV) in both human and mice for decades. Several transcription targets of Gata4 have been identified such as Mef2c, Ccnd2 and Cdk4, however none has been shown to be functionally involved in OFT development. Thus, the important role of Gata4 during OFT development remains unclear. Here we analyzed the requirement of Gata4 in several cell progenitors which contribute to the development of OFT and found that knocking down Gata4 in myocardium, second heart field and cardiac neural crest cells was able to maintain normal OFT development. However, Gata4 haploinsufficiency in Hedgehog (Hh) receiving cells caused a high penetrance of DORV in embryos at embryonic stage 14.5. Elongation as well as rotation defect were also observed in these mutant embryos compared to wildtype. Through TUNEL apoptosis assay, we found that there was no significant increase in cell apoptosis within the outflow tract region in these mutant embryos compared to wildtype. However, BrdU proliferation assay showed a significant decrease of cell proliferation in the conal portion of outflow tract in these mutant embryos. By performing real-time PCR, luciferase assay and ChIP-qPCR, we found Gata4 directly binds to Hh signaling effector Gli1 and regulates its expression. Also, by further blocking Hh signaling pathway in Gata4 mutant embryos or reducing such blockage, we found the occurrence and severity of OFT defect increased or decreased respectively. Together these results suggest that Gata4 interacts with Hedgehog signaling pathway in regulating outflow tract development

Converting ECG Signals to Images for Efficient Image-text Retrieval via Encoding

Automated interpretation of electrocardiograms (ECG) has garnered significant attention with the advancements in machine learning methodologies. Despite the growing interest in automated ECG interpretation using machine learning, most current studies focus solely on classification or regression tasks and overlook a crucial aspect of clinical cardio-disease diagnosis: the diagnostic report generated by experienced human clinicians. In this paper, we introduce a novel approach to ECG interpretation, leveraging recent breakthroughs in Large Language Models (LLMs) and Vision-Transformer (ViT) models. Rather than treating ECG diagnosis as a classification or regression task, we propose an alternative method of automatically identifying the most similar clinical cases based on the input ECG data. Also, since interpreting ECG as images are more affordable and accessible, we process ECG as encoded images and adopt a vision-language learning paradigm to jointly learn vision-language alignment between encoded ECG images and ECG diagnosis reports. Encoding ECG into images can result in an efficient ECG retrieval system, which will be highly practical and useful in clinical applications. More importantly, our findings could serve as a crucial resource for providing diagnostic services in regions where only paper-printed ECG images are accessible due to past underdevelopment.Comment: 26 page

Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?

Recent advancements in Large Language Models (LLMs) have drawn increasing attention since the learned embeddings pretrained on large-scale datasets have shown powerful ability in various downstream applications. However, whether the learned knowledge by LLMs can be transferred to clinical cardiology remains unknown. In this work, we aim to bridge this gap by transferring the knowledge of LLMs to clinical Electrocardiography (ECG). We propose an approach for cardiovascular disease diagnosis and automatic ECG diagnosis report generation. We also introduce an additional loss function by Optimal Transport (OT) to align the distribution between ECG and language embedding. The learned embeddings are evaluated on two downstream tasks: (1) automatic ECG diagnosis report generation, and (2) zero-shot cardiovascular disease detection. Our approach is able to generate high-quality cardiac diagnosis reports and also achieves competitive zero-shot classification performance even compared with supervised baselines, which proves the feasibility of transferring knowledge from LLMs to the cardiac domain.Comment: EACL 202

Alpha-Adducin Gly460Trp Polymorphism and Hypertension Risk: A Meta-Analysis of 22 Studies Including 14303 Cases and 15961 Controls

BACKGROUND: No clear consensus has been reached on the alpha-adducin polymorphism (Gly460Trp) and essential hypertension risk. We performed a meta-analysis in an effort to systematically summarize the possible association. METHODOLOGY/PRINCIPAL FINDINGS: Studies were identified by searching MEDLINE and EMBASE databases complemented with perusal of bibliographies of retrieved articles and correspondence with original authors. The fixed-effects model and the random-effects model were applied for dichotomous outcomes to combine the results of the individual studies. We selected 22 studies that met the inclusion criteria including a total of 14303 hypertensive patients and 15961 normotensive controls. Overall, the 460Trp allele showed no statistically significant association with hypertension risk compared to Gly460 allele (P = 0.69, OR = 1.02, 95% CI 0.94-1.10, P(heterogeneity)<0.0001) in all subjects. Meta-analysis under other genetic contrasts still did not reveal any significant association in all subjects, Caucasians, East Asians and others. The results were similar but heterogeneity did not persist when sensitivity analyses were limited to these studies. CONCLUSIONS/SIGNIFICANCE: Our meta-analysis failed to provide evidence for the genetic association of α-adducin gene Gly460Trp polymorphism with hypertension. Further studies investigating the effect of genetic networks, environmental factors, individual biological characteristics and their mutual interactions are needed to elucidate the possible mechanism for hypertension in humans

The Effect of Wenxin Keli on the mRNA Expression Profile of Rabbits with Myocardial Infarction

Aims. The molecular mechanisms of Chinese traditional medicine Wenxin Keli (WXKL) were unknown. This study was aimed at exploring the effects of WXKL on the gene expression profile and pathological alteration of rabbits with myocardial infarction. Methods. Twenty male adult rabbits were randomly divided into 4 groups: sham, model, WXKL, and captopril groups. Model, WXKL, and captopril groups underwent the ligation of the left anterior descending coronary artery while sham group went through an identical procedure without ligation. WXKL (817 mg/kg/d), captopril (8 mg/kg/d), and distilled water (to model and sham groups) were administered orally to each group. After 4 weeks, the rabbits were examined with echocardiography and the hearts were taken for expression chip and pathological staining (H&E, Masson, and Tunel) studies. Results. The data revealed that WXKL downregulated genes associated with inflammation (CX3CR1, MRC1, and FPR1), apoptosis (CTSC and TTC5), and neurohumoral system (ACE and EDN1) and upregulated angiogenesis promoting genes such as RSPO3. Moreover, the results also showed that WXKL improved cardiac function and prevented histopathological injury and apoptosis. Conclusion. The present study demonstrated that WXKL might play an important role in inhibiting inflammation, renin-angiotensin system, and apoptosis. It might be a promising Chinese medicine in the treatment of patients with myocardial infarction

Systemic treatments for breast cancer brain metastasis

Breast cancer (BC) is the most common cancer in females and BC brain metastasis (BCBM) is considered as the second most frequent brain metastasis. Although the advanced treatment has significantly prolonged the survival in BC patients, the prognosis of BCBM is still poor. The management of BCBM remains challenging. Systemic treatments are important to maintain control of central nervous system disease and improve patients’ survival. BCBM medical treatment is a rapidly advancing area of research. With the emergence of new targeted drugs, more options are provided for the treatment of BM. This review features currently available BCBM treatment strategies and outlines novel drugs and ongoing clinical trials that may be available in the future. These treatment strategies are discovered to be more efficacious and potent, and present a paradigm shift in the management of BCBMs

BMI1 fine-tunes gene repression and activation to safeguard undifferentiated spermatogonia fate

Introduction: Spermatogenesis is sustained by the homeostasis of self-renewal and differentiation of undifferentiated spermatogonia throughout life, which is regulated by transcriptional and posttranscriptional mechanisms. B cell-specific Moloney murine leukemia virus integration site 1 (BMI1), one of spermatogonial stem cell markers, is a member of Polycomb repressive complex 1 (PRC1) and important to spermatogenesis. However, the mechanistic underpinnings of how BMI1 regulates spermatogonia fate remain elusive.Methods: We knocked down BMI1 by siRNA to investigate the role of BMI1 in undifferentiated spermatogonia. Differentially expressed genes were identified by RNA-seq and used for KEGG pathway analysis. We performed ChIP-seq analysis in wild type and BMI1 knockdown cells to explore the underlying molecular mechanisms exerted by BMI1. BMI1-associated alterations in repressive histone modifications were detected via Western blotting and ChIP-seq. Furthermore, we performed mass spectrometry and Co-immunoprecipitation assays to investigate BMI1 co-factors. Finally, we demonstrated the genomic regions occupied by both BMI1 and its co-factor.Results: BMI1 is required for undifferentiated spermatogonia maintenance by both repressing and activating target genes. BMI1 preserves PI3K-Akt signaling pathway for spermatogonia proliferation. Decrease of BMI1 affects the deposition of repressive histone modifications H2AK119ub1 and H3K27me3. BMI also positively regulates H3K27ac deposited genes which are associated with proliferation. Moreover, we demonstrate that BMI1 interacts with Sal-like 4 (SALL4), the transcription factor critical for spermatogonia function, to co-regulate gene expression.Discussion: Overall, our study reveals that BMI1 safeguards undifferentiated spermatogonia fate through multi-functional roles in regulating gene expression programs of undifferentiated spermatogonia

TSG-6+ Cancer-Associated Fibroblasts Modulate Myeloid Cell Responses and Impair Anti-Tumor Response to Immune Checkpoint Therapy in Pancreatic Cancer

Resistance to immune checkpoint therapy (ICT) presents a growing clinical challenge. The tumor microenvironment (TME) and its components, namely tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs), play a pivotal role in ICT resistance; however, the underlying mechanisms remain under investigation. In this study, we identify expression of TNF-Stimulated Factor 6 (TSG-6) in ICT-resistant pancreatic tumors, compared to ICT-sensitive melanoma tumors, both in mouse and human. TSG-6 is expressed by CAFs within the TME, where suppressive macrophages expressing Arg1, Mafb, and Mrc1, along with TSG-6 ligand Cd44, predominate. Furthermore, TSG-6 expressing CAFs co-localize with the CD44 expressing macrophages in the TME. TSG-6 inhibition in combination with ICT improves therapy response and survival in pancreatic tumor-bearing mice by reducing macrophages expressing immunosuppressive phenotypes and increasing CD8 T cells. Overall, our findings propose TSG-6 as a therapeutic target to enhance ICT response in non-responsive tumors

Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment

Background Dementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive and therapeutic interventions. Methods In this study, we conducted a network-based, multimodal omics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9-based genetic assay results and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimer’s disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2. Results We found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors (BSG and FURIN) and antiviral defense genes (LY6E, IFITM2, IFITM3, and IFNAR1) was elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Overall, individuals with the AD risk allele APOE E4/E4 displayed reduced expression of antiviral defense genes compared to APOE E3/E3 individuals. Conclusion Our results suggest significant mechanistic overlap between AD and COVID-19, centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions, although causal relationship and mechanistic pathways between COVID-19 and AD need future investigations

Interferon Tau Affects Mouse Intestinal Microbiota and Expression of IL-17

This study was conducted to explore the effects of interferon tau (IFNT) on the intestinal microbiota and expression of interleukin 17 (IL-17) in the intestine of mice. IFNT supplementation increased microbial diversity in the jejunum and ileum but decreased microbial diversity in the feces. IFNT supplementation influenced the composition of the intestinal microbiota as follows: (1) decreasing the percentage of Firmicutes and increasing Bacteroidetes in the jejunum and ileum; (2) enhancing the percentage of Firmicutes but decreasing Bacteroidetes in the colon and feces; (3) decreasing Lactobacillus in the jejunum and ileum; (4) increasing the percentage of Blautia, Bacteroides, Alloprevotella, and Lactobacillus in the colon; and (5) increasing the percentage of Lactobacillus, Bacteroides, and Allobaculum, while decreasing Blautia in the feces. Also, IFNT supplementation decreased the expression of IL-17 in the intestines of normal mice and of an intestinal pathogen infected mice. In conclusion, IFNT supplementation modulates the intestinal microbiota and intestinal IL-17 expression, indicating the applicability of IFNT to treat the intestinal diseases involving IL-17 expression and microbiota