Background: Transcutaneous auricular Vagus Nerve Stimulation (taVNS) is a noninvasive technique that activates vagal projections in the brain and brainstem by stimulating the auricular branch of the vagus nerve. taVNS may be a safer alternative to invasive vagal nerve stimulation for treating treatment-resistant mood disorders, chronic pain, inflammation, cardiovascular dysfunction, inflammatory bowel disease, and Crohn’s disease. Objective: This study aims to systematically review the current evidence on the efficacy and safety of taVNS in treating depressive disorders and its modulatory effects on the autonomic nervous system. Methods: Relevant primary and secondary sources were identified through a systematic search of the PubMed and Google Scholar databases from 2008 to 2023. The review used the Scale for Assessment of Narrative Review Articles, resulting in a 0.77% intraclass correlation coefficient, 95% CI, and 0.88 inter-rater reliability. Results: taVNS, a new noninvasive neuromodulation method, stimulates the auricular branch of the vagus nerve and regulates the sympathetic and parasympathetic branches of the ANS, increasing norepinephrine secretion, vagus nerve stimulation adaptability, and heart rate variability. Future studies should clarify the mechanisms and address inconsistencies in taVNS parameters. Standardizing treatment regimens can establish taVNS as a viable, noninvasive treatment. Conclusion: Our findings suggest that taVNS may be a safer alternative to invasive vagal nerve stimulation for treatment-resistant mood disorders, chronic pain, inflammation, cardiovascular dysfunction, inflammatory bowel disease, and Crohn’s disease. However, further empirical research is needed to elucidate the mechanisms and resolve inconsistencies in the stimulation parameters, and larger studies are required to confirm taVNS as an effective noninvasive treatment.

Cerebral cavernous malformations (CCMs) are abnormally dilated intracranial capillaries that form cerebrovascular lesions with a high risk of hemorrhagic stroke. Recently, several somatic “activating” gain-of-function (GOF) point mutations in PIK3CA (phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit p110α) were discovered as a dominant mutation in the lesions of sporadic forms of cerebral cavernous malformation (sCCM), raising the possibility that CCMs, like other types of vascular malformations, fall in the PIK3CA-related overgrowth spectrum (PROS). However, this possibility has been challenged with different interpretations. In this review, we will continue our efforts to expound the phenomenon of the coexistence of gain-of-function (GOF) point mutations in the PIK3CA gene and loss-of-function (LOF) mutations in CCM genes in the CCM lesions of sCCM and try to delineate the relationship between mutagenic events with CCM lesions in a temporospatial manner. Since GOF PIK3CA point mutations have been well studied in reproductive cancers, especially breast cancer as a driver oncogene, we will perform a comparative meta-analysis for GOF PIK3CA point mutations in an attempt to demonstrate the genetic similarities shared by both cancers and vascular anomalies.

Cerebral cavernous malformations (CCMs) arise when capillaries within the brain enlarge abnormally, causing the blood–brain barrier (BBB) to break down. The BBB serves as a sophisticated interface that controls molecular interactions between the bloodstream and the central nervous system. The neurovascular unit (NVU) is a complex structure made up of neurons, astrocytes, endothelial cells (ECs), pericytes, microglia, and basement membranes, which work together to maintain blood–brain barrier (BBB) permeability. Within the NVU, tight junctions (TJs) and adherens junctions (AJs) between endothelial cells play a critical role in regulating the permeability of the BBB. Disruptions to these junctions can compromise the BBB, potentially leading to a hemorrhagic stroke. Understanding the molecular signaling cascades that regulate BBB permeability through EC junctions is, therefore, essential. New research has demonstrated that steroids, including estrogens (ESTs), glucocorticoids (GCs), and metabolites/derivatives of progesterone (PRGs), have multifaceted effects on blood–brain barrier (BBB) permeability by regulating the expression of tight junctions (TJs) and adherens junctions (AJs). They also have anti-inflammatory effects on blood vessels. PRGs, in particular, have been found to play a significant role in maintaining BBB integrity. PRGs act through a combination of its classic and non-classic PRG receptors (nPR/mPR), which are part of a signaling network known as the CCM signaling complex (CSC). This network couples both nPR and mPR in the CmPn/CmP pathway in endothelial cells (ECs).

Liver cancer, comprising hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), is a leading cause of cancer-related deaths worldwide. The liver is a primary metabolic organ for progesterone (PRG) and PRG exerts its effects through classic nuclear PRG receptors (nPRs) and non-classic membrane PRG receptors (mPRs) or a combination of both. Previous studies have shown that the CCM signaling complex (CSC) couples both nPRs and mPRs to form the CmPn (CSC-mPR-PRG-nPR) signaling network, which is involved in multiple cellular signaling pathways, including tumorigenesis of various cancers. Despite advances in treatment, 5-year survival rates for liver cancer patients remain low, largely due to the chemoresistant nature of HCCs. The lack of sensitive and specific biomarkers for liver cancer diagnosis and prognosis emphasizes the need for identifying new potential biomarkers. We propose the potential use of CmPn members’ expression data as prognostic biomarkers or biomarker signatures for the major types of hepatic cancer, including HCCs and CCAs, as well as rare subtypes such as undifferentiated pleomorphic sarcoma (UPS) and hepatic angiosarcoma (HAS). In this study, we investigated the CmPn network through RNAseq data and immunofluorescence techniques to measure alterations to key cancer pathways during liver tumorigenesis. Our findings reveal significant differential expression of multiple CmPn members, including CCM1, PAQR7, PGRMC1, and nPRs, in both HCCs and CCAs, highlighting the crucial roles of mPRs, nPRs, and CSC signaling during liver tumorigenesis. These key members of the CmPn network may serve as potential biomarkers for the diagnosis and prognosis of liver cancer subtypes, including rare subtypes.

Liver cancer ranks sixth globally in diagnoses and second in cancer-related deaths. Cholangiocarcinoma (CCA), a relatively rare cancer originating from bile duct epithelium, constitutes 2% of all cancers, with increasing occurrences in Westerns. Incidence is influenced by inflammation, genetics, risk factors, and regional disparities, with higher rates in the Eastern hemisphere. Diagnostic and prognostic biomarkers are pivotal for effective cancer prevention and management. Recent research explores serum proteins for non-invasive CCA diagnosis and proposes targeted receptor approaches for therapeutics. This study aims to identify these biomarkers via bioinformatics analysis of public datasets, focusing on CCA patient transcriptomes to uncover gene biomarkers linked to age and survival. Pathway analysis reveals functions and pathways associated with these biomarkers. Additionally, the study employs the ESM-TFpredict machine learning model to predict transcription factors (TFs) using protein sequence data. Leveraging publicly available data enhances our understanding of liver cancer’s molecular profiles and clinical relevance, particularly concerning CCA, This study integrates bioinformatics analysis, transcriptomic exploration, and machine learning to unveil a novel set of potential diagnostic and prognostic biomarkers for CCA.

Introduction: Hepatocellular carcinoma (HCC), the most common form of liver cancer, is a global health concern and a leading cause of cancer-related deaths. HCC accounts for a significant portion of liver cancers and has low survival rates of 5% to 30%, especially for HCC patients with a survival rate of 15%. Early detection is challenging due to the absence of symptoms in the early stages. The complexity and molecular diversity of HCC contribute to its poor prognosis. Understanding its molecular subtypes and mechanisms is crucial for improved management. Methods: The study utilized publicly available data to investigate the potential diagnostic and prognostic biomarkers for hepatocellular carcinoma (HCC) based on their transcript per million (TPM) expression levels. A dataset of 407 HCC patient profiles was analyzed for survival trends and gene expression patterns. Results: Through a comprehensive approach, over 900 potential prognostic candidates were identified. Further analysis narrowed down 647 prognostic and diagnostic candidate biomarkers. The study also explored the role of the CmPn signaling network in HCC, reaffirming that its components could act as prognostic markers. Additionally, the study-utilized machine learning to discover 102 transcription factors (TFs) associated with HCC, from candidate biomarkers. Conclusions: The findings provide insights into the molecular basis of HCC and offer potential avenues for improved diagnosis, treatment, and patient outcomes. The expanded prognostic biomarker pool aids in pinpointing HCC-specific grading and staging biomarkers, facilitating targeted therapies for improved patient outcomes and survival rates