Repurposing drugs to treat cardiovascular disease in the era of precision medicine

Overcoming antibiotic resistance: the potential and pitfalls of drug repurposing

Since its emergence shortly after the discovery of penicillin, antibiotic resistance has escalated dramatically, posing a significant health threat and economic burden. Combating antibiotic resistance, especially in Gram-negative bacteria (GNB) and drug-resistant Mycobacterium tuberculosis, necessitates innovative research, substantial financial investment, and global cooperation to safeguard public health and develop sustainable solutions. Drug repositioning, or drug repurposing, involves identifying new therapeutic applications for existing drugs, utilizing their established safety profiles and pharmacological data to swiftly provide effective treatments against resistant pathogens. Several drugs, including otilonium bromide, penfluridol, eltrombopag, ibuprofen, and ceritinib, have demonstrated potent antibacterial activity against multidrug-resistant (MDR) bacteria. These drugs can disrupt biofilms, damage bacterial membranes, and inhibit bacterial growth. Furthermore, the combination of repurposed drugs with conventional antibiotics can reduce the required dosage of individual drugs, mitigate side effects, and delay the development of resistance, making it a promising strategy against MDR bacteria such as Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Escherichia coli. Despite its promise, drug repurposing faces challenges such as potential off-target effects, toxicity, and regulatory and intellectual property issues, necessitating rigorous evaluations and strategic solutions. This article aims to explore the potential of drug repurposing as a strategy to combat antibiotic resistance, examining its benefits, challenges, and future prospects. We address the legal, economic, and practical challenges associated with repurposing existing drugs, highlight successful examples, and propose solutions to enhance the efficacy and viability of this approach in combating MDR bacterial infections.

Innovative cancer therapy: Unleashing the potential of macromolecule-loaded mesoporous bioactive glasses for precision diagnosis and treatment

Cancer continues to pose a formidable threat, claiming millions of lives annually. A beacon of hope in this battle lies in the realm of bioactive glasses, which have undergone a remarkable evolution over the past five decades. Among these, mesoporous bioactive glasses (MBGs) emerge as a dynamic subset endowed with customizable attributes such as high surface area and porosity. While holding immense promise for cancer care, the full clinical potential of MBGs remains largely unexplored. This review delves into the cutting-edge advancements in MBG technology, illuminating their pivotal role in cancer management - spanning from early detection to targeted therapeutic interventions like photothermal and photodynamic treatments. Furthermore, the molecular mechanisms underpinning MBGs' anticancer properties are elucidated, alongside an exploration of existing limitations in their application. Through this comprehensive synthesis, the significance of MBGs in revolutionizing cancer therapy is underscored, underscoring the urgent need for continued research to unlock their full potential in reshaping the landscape of cancer care.

Rapid detection of drugs in blood using "molecular hook" surface-enhanced Raman spectroscopy and artificial intelligence technology for clinical applications

Accurate detection of cardiovascular drugs in blood is complicated by interference from serum biomolecules. This study introduces a novel surface-enhanced Raman spectroscopy (SERS) platform incorporating "molecular hooks" to capture small drug molecules while excluding larger biomolecules selectively. The self-assembled nanoparticles with the A13 molecule enhance Raman signals by creating dense electromagnetic "hotspot" regions, achieving detection limits of 10 pg/mL for dobutamine hydrochloride and 10 ng/mL for milrinone-substantially below therapeutic thresholds. Artificial intelligence (AI) integration enables automated spectral analysis, allowing rapid and precise drug detection in clinical blood samples. This approach offers a transformative solution for real-time diagnostics, significantly advancing personalized treatment strategies in clinical settings.

A foundation model for clinician-centered drug repurposing

Drug repurposing-identifying new therapeutic uses for approved drugs-is often a serendipitous and opportunistic endeavour to expand the use of drugs for new diseases. The clinical utility of drug-repurposing artificial intelligence (AI) models remains limited because these models focus narrowly on diseases for which some drugs already exist. Here we introduce TxGNN, a graph foundation model for zero-shot drug repurposing, identifying therapeutic candidates even for diseases with limited treatment options or no existing drugs. Trained on a medical knowledge graph, TxGNN uses a graph neural network and metric learning module to rank drugs as potential indications and contraindications for 17,080 diseases. When benchmarked against 8 methods, TxGNN improves prediction accuracy for indications by 49.2% and contraindications by 35.1% under stringent zero-shot evaluation. To facilitate model interpretation, TxGNN's Explainer module offers transparent insights into multi-hop medical knowledge paths that form TxGNN's predictive rationales. Human evaluation of TxGNN's Explainer showed that TxGNN's predictions and explanations perform encouragingly on multiple axes of performance beyond accuracy. Many of TxGNN's new predictions align well with off-label prescriptions that clinicians previously made in a large healthcare system. TxGNN's drug-repurposing predictions are accurate, consistent with off-label drug use, and can be investigated by human experts through multi-hop interpretable rationales.

Non-Negative Matrix Tri-Factorization for Representation Learning in Multi-Omics Datasets with Applications to Drug Repurposing and Selection

The vast corpus of heterogeneous biomedical data stored in databases, ontologies, and terminologies presents a unique opportunity for drug design. Integrating and fusing these sources is essential to develop data representations that can be analyzed using artificial intelligence methods to generate novel drug candidates or hypotheses. Here, we propose Non-Negative Matrix Tri-Factorization as an invaluable tool for integrating and fusing data, as well as for representation learning. Additionally, we demonstrate how representations learned by Non-Negative Matrix Tri-Factorization can effectively be utilized by traditional artificial intelligence methods. While this approach is domain-agnostic and applicable to any field with vast amounts of structured and semi-structured data, we apply it specifically to computational pharmacology and drug repurposing. This field is poised to benefit significantly from artificial intelligence, particularly in personalized medicine. We conducted extensive experiments to evaluate the performance of the proposed method, yielding exciting results, particularly compared to traditional methods. Novel drug-target predictions have also been validated in the literature, further confirming their validity. Additionally, we tested our method to predict drug synergism, where constructing a classical matrix dataset is challenging. The method demonstrated great flexibility, suggesting its applicability to a wide range of tasks in drug design and discovery.

Repurposing of glatiramer acetate to treat cardiac ischemia in rodent models

Myocardial injury may ultimately lead to adverse ventricular remodeling and development of heart failure (HF), which is a major cause of morbidity and mortality worldwide. Given the slow pace and substantial costs of developing new therapeutics, drug repurposing is an attractive alternative. Studies of many organs, including the heart, highlight the importance of the immune system in modulating injury and repair outcomes. Glatiramer acetate (GA) is an immunomodulatory drug prescribed for patients with multiple sclerosis. Here, we report that short-term GA treatment improves cardiac function and reduces scar area in a mouse model of acute myocardial infarction and a rat model of ischemic HF. We provide mechanistic evidence indicating that, in addition to its immunomodulatory functions, GA exerts beneficial pleiotropic effects, including cardiomyocyte protection and enhanced angiogenesis. Overall, these findings highlight the potential repurposing of GA as a future therapy for a myriad of heart diseases.

Tamoxifen may contribute to preserve cardiac function in Duchenne muscular dystrophy

Duchenne muscular dystrophy is life-limiting. Cardiomyopathy, which mostly ensues in the second decade of life, is the main cause of death. Treatment options are still limited. The TAMDMD (NCT03354039) trial assessed motor function, muscle strength and structure, laboratory biomarkers, and safety in 79 ambulant boys with genetically confirmed Duchenne muscular dystrophy, 6.5-12 years of age, receiving either daily tamoxifen 20 mg or placebo for 48 weeks. In this post-hoc analysis, available echocardiographic data of ambulant patients recruited at one study centre were retrieved and compared before and after treatment. Data from 14 patients, median 11 (interquartile range, IQR, 11-12) years of age was available. Baseline demographic characteristics were similar in participants assigned to placebo (n = 7) or tamoxifen (n = 7). Left ventricular end-diastolic diameter in the placebo group (median and IQR) was 39 (38-41) mm at baseline and 43 (38-44) mm at study end, while it was 44 (41-46) mm at baseline and 41 (37-46) mm after treatment in the tamoxifen group. Left ventricular fractional shortening in the placebo group was 35% (32-38%) before and 33% (32-36%) after treatment, while in the tamoxifen group it was 34% (33-34%) at baseline and 35% (33-35%) at study end. No safety signals were detected.

CONCLUSION

This hypothesis-generating post-hoc analysis suggests that tamoxifen over 48 weeks is well tolerated and may help preserving cardiac structure and function in Duchenne muscular dystrophy. Further studies are justified.

CLINICALTRIALS

gov Identifier: EudraCT 2017-004554-42, NCT03354039 What is known: • Duchenne muscular dystrophy (DMD) is life-limiting. Cardiomyopathy ensues in the second decade of life and is the main cause of death. Treatment options are still limited. • Tamoxifen reduced cardiac fibrosis in mice and improved cardiomyocyte function in human-induced pluripotent stem cell-derived cardiomyocytes.

WHAT IS NEW

• In this post-hoc analysis of the TAMDMD trial among 14 boys, median 11 years of age, treated with either tamoxifen or placebo for 48 weeks, treatment was well-tolerated. • A visual trend of improved left-ventricular dimensions and better systolic function preservation generates the hypothesis of a potential beneficial effect of tamoxifen in DMD cardiomyopathy.

The molecular basis of the anticancer effect of statins

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology.

Cysteine sulfenylation contributes to liver fibrosis via the regulation of EphB2-mediated signaling

Sulfenylation is a reversible oxidative posttranslational modification (PTM) of proteins on cysteine residues. Despite the dissection of various biological functions of cysteine sulfenylation, its roles in hepatic fibrosis remain elusive. Here, we report that EphB2, a receptor tyrosine kinase previously implicated in liver fibrosis, is regulated by cysteine sulfenylation during the fibrotic progression of liver. Specifically, EphB2 is sulfenylated at the residues of Cys636 and Cys862 in activated hepatic stellate cells (HSCs), leading to the elevation of tyrosine kinase activity and protein stability of EphB2 and stronger interactions with focal adhesion kinase for the activation of downstream mitogen-activated protein kinase signaling. The inhibitions of both EphB2 kinase activity and cysteine sulfenylation by idebenone (IDE), a marketed drug with potent antioxidant activity, can markedly suppress the activation of HSCs and ameliorate hepatic injury in two well-recognized mouse models of liver fibrosis. Collectively, this study reveals cysteine sulfenylation as a new type of PTM for EphB2 and sheds a light on the therapeutic potential of IDE for the treatment of liver fibrosis.

A foundation model for clinician-centered drug repurposing

Drug repurposing - identifying new therapeutic uses for approved drugs - is often serendipitous and opportunistic, expanding the use of drugs for new diseases. The clinical utility of drug repurposing AI models remains limited because the models focus narrowly on diseases for which some drugs already exist. Here, we introduce TXGNN, a graph foundation model for zero-shot drug repurposing, identifying therapeutic candidates even for diseases with limited treatment options or no existing drugs. Trained on a medical knowledge graph, TXGNN utilizes a graph neural network and metric-learning module to rank drugs as potential indications and contraindications across 17,080 diseases. When benchmarked against eight methods, TXGNN improves prediction accuracy for indications by 49.2% and contraindications by 35.1% under stringent zero-shot evaluation. To facilitate model interpretation, TXGNN's Explainer module offers transparent insights into multi-hop medical knowledge paths that form TXGNN's predictive rationales. Human evaluation of TXGNN's Explainer showed that TXGNN's predictions and explanations perform encouragingly on multiple axes of performance beyond accuracy. Many of TxGNN's novel predictions align with off-label prescriptions clinicians make in a large healthcare system. TXGNN's drug repurposing predictions are accurate, consistent with off-label drug use, and can be investigated by human experts through multi-hop interpretable rationales.

Lipid nanoparticle (LNP) mediated mRNA delivery in cardiovascular diseases: Advances in genome editing and CAR T cell therapy

Cardiovascular diseases (CVDs) are the leading cause of global mortality among non-communicable diseases. Current cardiac regeneration treatments have limitations and may lead to adverse reactions. Hence, innovative technologies are needed to address these shortcomings. Messenger RNA (mRNA) emerges as a promising therapeutic agent due to its versatility in encoding therapeutic proteins and targeting "undruggable" conditions. It offers low toxicity, high transfection efficiency, and controlled protein production without genome insertion or mutagenesis risk. However, mRNA faces challenges such as immunogenicity, instability, and difficulty in cellular entry and endosomal escape, hindering its clinical application. To overcome these hurdles, lipid nanoparticles (LNPs), notably used in COVID-19 vaccines, have a great potential to deliver mRNA therapeutics for CVDs. This review highlights recent progress in mRNA-LNP therapies for CVDs, including Myocardial Infarction (MI), Heart Failure (HF), and hypercholesterolemia. In addition, LNP-mediated mRNA delivery for CAR T-cell therapy and CRISPR/Cas genome editing in CVDs and the related clinical trials are explored. To enhance the efficiency, safety, and clinical translation of mRNA-LNPs, advanced technologies like artificial intelligence (AGILE platform) in RNA structure design, and optimization of LNP formulation could be integrated. We conclude that the strategies to facilitate the extra-hepatic delivery and targeted organ tropism of mRNA-LNPs (SORT, ASSET, SMRT, and barcoded LNPs) hold great prospects to accelerate the development and translation of mRNA-LNPs in CVD treatment.

Computational Approaches to Drug Repurposing: Methods, Challenges, and Opportunities

Drug repurposing refers to the inference of therapeutic relationships between a clinical indication and existing compounds. As an emerging paradigm in drug development, drug repurposing enables more efficient treatment of rare diseases, stratified patient populations, and urgent threats to public health. However, prioritizing well-suited drug candidates from among a nearly infinite number of repurposing options continues to represent a significant challenge in drug development. Over the past decade, advances in genomic profiling, database curation, and machine learning techniques have enabled more accurate identification of drug repurposing candidates for subsequent clinical evaluation. This review outlines the major methodologic classes that these approaches comprise, which rely on (a) protein structure, (b) genomic signatures, (c) biological networks, and (d) real-world clinical data. We propose that realizing the full impact of drug repurposing methodologies requires a multidisciplinary understanding of each method's advantages and limitations with respect to clinical practice.

Novel drug design and repurposing: An opportunity to improve translational research in cardiovascular diseases?

Drug repurposing is defined as the use of approved therapeutic drugs for indications different from those for which they were originally designed. Repositioning diminishes both the time and cost for drug development by omitting the discovery stage, the analysis of absorption, distribution, metabolism, and excretion routes, as well as the studies of the biochemical and physiological effects of a new compound. Besides, drug repurposing takes advantage of the increased bioinformatics knowledge and availability of big data biology. There are many examples of drugs with repurposed indications evaluated in in vitro studies, and in pharmacological, preclinical, or retrospective clinical analyses. Here, we briefly review some of the experimental strategies and technical advances that may improve translational research in cardiovascular diseases. We also describe exhaustive research from basic science to clinical studies that culminated in the final approval of new drugs and provide examples of successful drug repurposing in the field of cardiology.

Aspirin-Fisetin Combinatorial Treatment Exerts Cytotoxic and Anti-Migratory Activities in A375 Malignant Melanoma Cells

Background and Objectives: Malignant melanoma (MM) remains one of the most aggressive cancers worldwide, presenting a limited number of therapeutic options at present. Aspirin (ASA), a broadly used non-steroid anti-inflammatory medicine, has recently emerged as a candidate for repurposing in cancer management, due to its therapeutic potential in the treatment of several neoplasms which include MM. Fisetin (FIS) is a flavonoid phytoestrogen instilled with multispectral pharmacological activities, including a potent anti-melanoma property. The present study aimed to assess the potential improved anti-neoplastic effect resulting from the association of ASA and FIS for MM therapy. Materials and Methods: The study was conducted using the A375 cell line as an experimental model for MM. Cell viability was assessed via the MTT test. Cell morphology and confluence were evaluated using bright-field microscopy. The aspect of cell nuclei and tubulin fibers was observed through immunofluorescence staining. The irritant potential and the anti-angiogenic effect were determined on the chorioallantoic membrane of chicken fertilized eggs. Results: The main findings related herein demonstrated that the ASA 2.5 mM + FIS (5, 10, 15, and 20 µM) combination exerted a higher cytotoxicity in A375 MM cells compared to the individual compounds, which was outlined by the concentration-dependent and massive reduction in cell viability, loss of cell confluence, cell shrinkage and rounding, apoptotic-like nuclear features, constriction and disruption of tubulin filaments, increased apoptotic index, and suppressed migratory ability. ASA 2.5 mM + FIS 20 µM treatment lacked irritant potential on the chorioallantoic membrane and inhibited blood-vessel formation in ovo. Conclusion: These results stand as one of the first contributions presenting the anti-melanoma effect of the ASA + FIS combinatorial treatment.

MEK inhibitors: a promising targeted therapy for cardiovascular disease

Cardiovascular disease (CVD) represents the leading cause of mortality and disability all over the world. Identifying new targeted therapeutic approaches has become a priority of biomedical research to improve patient outcomes and quality of life. The RAS-RAF-MEK (mitogen-activated protein kinase kinase)-ERK (extracellular signal-regulated kinase) pathway is gaining growing interest as a potential signaling cascade implicated in the pathogenesis of CVD. This pathway is pivotal in regulating cellular processes like proliferation, growth, migration, differentiation, and survival, which are vital in maintaining cardiovascular homeostasis. In addition, ERK signaling is involved in controlling angiogenesis, vascular tone, myocardial contractility, and oxidative stress. Dysregulation of this signaling cascade has been linked to cell dysfunction and vascular and cardiac pathological remodeling, which contribute to the onset and progression of CVD. Recent and ongoing research has provided insights into potential therapeutic interventions targeting the RAS-RAF-MEK-ERK pathway to improve cardiovascular pathologies. Preclinical studies have demonstrated the efficacy of targeted therapy with MEK inhibitors (MEKI) in attenuating ERK activation and mitigating CVD progression in animal models. In this article, we first describe how ERK signaling contributes to preserving cardiovascular health. We then summarize current knowledge of the roles played by ERK in the development and progression of cardiac and vascular disorders, including atherosclerosis, myocardial infarction, cardiac hypertrophy, heart failure, and aortic aneurysm. We finally report novel therapeutic strategies for these CVDs encompassing MEKI and discuss advantages, challenges, and future developments for MEKI therapeutics.

Three-dimensional cardiac models: a pre-clinical testing platform

Major advancements in human pluripotent stem cell (hPSC) technology over recent years have yielded valuable tools for cardiovascular research. Multi-cell type 3-dimensional (3D) cardiac models in particular, are providing complementary approaches to animal studies that are better representatives than simple 2-dimensional (2D) cultures of differentiated hPSCs. These human 3D cardiac models can be broadly divided into two categories; namely those generated through aggregating pre-differentiated cells and those that form self-organizing structures during their in vitro differentiation from hPSCs. These models can either replicate aspects of cardiac development or enable the examination of interactions among constituent cell types, with some of these models showing increased maturity compared with 2D systems. Both groups have already emerged as physiologically relevant pre-clinical platforms for studying heart disease mechanisms, exhibiting key functional attributes of the human heart. In this review, we describe the different cardiac organoid models derived from hPSCs, their generation methods, applications in cardiovascular disease research and use in drug screening. We also address their current limitations and challenges as pre-clinical testing platforms and propose potential improvements to enhance their efficacy in cardiac drug discovery.

Drug repurposing: A multi targetted approach to treat cardiac disease from existing classical drugs to modern drug discovery

Cardiovascular diseases (CVDs) are characterized by abnormalities in the heart, blood vessels, and blood flow. CVDs comprise a diverse set of health issues. There are several types of CVDs like stroke, endothelial dysfunction, thrombosis, atherosclerosis, plaque instability and heart failure. Identification of a new drug for heart disease takes longer duration and its safety efficacy test takes even longer duration of research and approval. This chapter explores drug repurposing, nano-therapy, and plant-based treatments for managing CVDs from existing drugs which saves time and safety issues with testing new drugs. Existing drugs like statins, ACE inhibitor, warfarin, beta blockers, aspirin and metformin have been found to be useful in treating cardiac disease. For better drug delivery, nano therapy is opening new avenues for cardiac research by targeting interleukin (IL), TNF and other proteins by proteome interactome analysis. Nanoparticles enable precise delivery to atherosclerotic plaques, inflammation areas, and damaged cardiac tissues. Advancements in nano therapeutic agents, such as drug-eluting stents and drug-loaded nanoparticles are transforming CVDs management. Plant-based treatments, containing phytochemicals from Botanical sources, have potential cardiovascular benefits. These phytochemicals can mitigate risk factors associated with CVDs. The integration of these strategies opens new avenues for personalized, effective, and minimally invasive cardiovascular care. Altogether, traditional drugs, phytochemicals along with nanoparticles can revolutionize the future cardiac health care by identifying their signaling pathway, mechanism and interactome analysis.

Testing the predictive power of reverse screening to infer drug targets, with the help of machine learning

Estimating protein targets of compounds based on the similarity principle-similar molecules are likely to show comparable bioactivity-is a long-standing strategy in drug research. Having previously quantified this principle, we present here a large-scale evaluation of its predictive power for inferring macromolecular targets by reverse screening an unprecedented vast external test set of more than 300,000 active small molecules against another bioactivity set of more than 500,000 compounds. We show that machine-learning can predict the correct targets, with the highest probability among 2069 proteins, for more than 51% of the external molecules. The strong enrichment thus obtained demonstrates its usefulness in supporting phenotypic screens, polypharmacology, or repurposing. Moreover, we quantified the impact of the bioactivity knowledge available for proteins in terms of number and diversity of actives. Finally, we advise that developers of such approaches follow an application-oriented benchmarking strategy and use large, high-quality, non-overlapping datasets as provided here.

Stroke genetics and how it Informs novel drug discovery

INTRODUCTION

Stroke is one of the main causes of death and disability worldwide. Nevertheless, despite the global burden of this disease, our understanding is limited and there is still a lack of highly efficient etiopathology-based treatment. It is partly due to the complexity and heterogenicity of the disease. It is estimated that around one-third of ischemic stroke is heritable, emphasizing the importance of genetic factors identification and targeting for therapeutic purposes.

AREAS COVERED

In this review, the authors provide an overview of the current knowledge of stroke genetics and its value in diagnostics, personalized treatment, and prognostication.

EXPERT OPINION

As the scale of genetic testing increases and the cost decreases, integration of genetic data into clinical practice is inevitable, enabling assessing individual risk, providing personalized prognostic models and identifying new therapeutic targets and biomarkers. Although expanding stroke genetics data provides different diagnostics and treatment perspectives, there are some limitations and challenges to face. One of them is the threat of health disparities as non-European populations are underrepresented in genetic datasets. Finally, a deeper understanding of underlying mechanisms of potential targets is still lacking, delaying the application of novel therapies into routine clinical practice.

Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts

Fibroblasts are essential regulators of extracellular matrix deposition following cardiac injury. These cells exhibit highly plastic responses in phenotype during fibrosis in response to environmental stimuli. Here, we test whether and how candidate anti-fibrotic drugs differentially regulate measures of cardiac fibroblast phenotype, which may help identify treatments for cardiac fibrosis. We conducted a high-content microscopy screen of human cardiac fibroblasts treated with 13 clinically relevant drugs in the context of TGFβ and/or IL-1β, measuring phenotype across 137 single-cell features. We used the phenotypic data from our high-content imaging to train a logic-based mechanistic machine learning model (LogiMML) for fibroblast signaling. The model predicted how pirfenidone and Src inhibitor WH-4-023 reduce actin filament assembly and actin-myosin stress fiber formation, respectively. Validating the LogiMML model prediction that PI3K partially mediates the effects of Src inhibition, we found that PI3K inhibition reduces actin-myosin stress fiber formation and procollagen I production in human cardiac fibroblasts. In this study, we establish a modeling approach combining the strengths of logic-based network models and regularized regression models. We apply this approach to predict mechanisms that mediate the differential effects of drugs on fibroblasts, revealing Src inhibition acting via PI3K as a potential therapy for cardiac fibrosis.

Revolutionizing Neurological Disorder Treatment: Integrating Innovations in Pharmaceutical Interventions and Advanced Therapeutic Technologies

Neurological disorders impose a significant burden on individuals, leading to disabilities and a reduced quality of life. However, recent years have witnessed remarkable advancements in pharmaceutical interventions aimed at treating these disorders. This review article aims to provide an overview of the latest innovations and breakthroughs in neurological disorder treatment, with a specific focus on key therapeutic areas such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, and stroke. This review explores emerging trends in drug development, including the identification of novel therapeutic targets, the development of innovative drug delivery systems, and the application of personalized medicine approaches. Furthermore, it highlights the integration of advanced therapeutic technologies such as gene therapy, optogenetics, and neurostimulation techniques. These technologies hold promise for precise modulation of neural circuits, restoration of neuronal function, and even disease modification. While these advancements offer hopeful prospects for more effective and tailored treatments, challenges such as the need for improved diagnostic tools, identification of new targets for intervention, and optimization of drug delivery methods will remain. By addressing these challenges and continuing to invest in research and collaboration, we can revolutionize the treatment of neurological disorders and significantly enhance the lives of those affected by these conditions.

Bioinformatic platforms for clinical stratification of natural history of atherosclerotic cardiovascular diseases

Although bioinformatic methods gained a lot of attention in the latest years, their use in real-world studies for primary and secondary prevention of atherosclerotic cardiovascular diseases (ASCVD) is still lacking. Bioinformatic resources have been applied to thousands of individuals from the Framingham Heart Study as well as health care-associated biobanks such as the UK Biobank, the Million Veteran Program, and the CARDIoGRAMplusC4D Consortium and randomized controlled trials (i.e. ODYSSEY, FOURIER, ASPREE, and PREDIMED). These studies contributed to the development of polygenic risk scores (PRS), which emerged as novel potent genetic-oriented tools, able to calculate the individual risk of ASCVD and to predict the individual response to therapies such as statins and proprotein convertase subtilisin/kexin type 9 inhibitor. ASCVD are the first cause of death around the world including coronary heart disease (CHD), peripheral artery disease, and stroke. To achieve the goal of precision medicine and personalized therapy, advanced bioinformatic platforms are set to link clinically useful indices to heterogeneous molecular data, mainly epigenomics, transcriptomics, metabolomics, and proteomics. The DIANA study found that differential methylation of ABCA1, TCF7, PDGFA, and PRKCZ significantly discriminated patients with acute coronary syndrome from healthy subjects and their expression levels positively associated with CK-MB serum concentrations. The ARIC Study revealed several plasma proteins, acting or not in lipid metabolism, with a potential role in determining the different pleiotropic effects of statins in each subject. The implementation of molecular high-throughput studies and bioinformatic techniques into traditional cardiovascular risk prediction scores is emerging as a more accurate practice to stratify patients earlier in life and to favour timely and tailored risk reduction strategies. Of note, radiogenomics aims to combine imaging features extracted for instance by coronary computed tomography angiography and molecular biomarkers to create CHD diagnostic algorithms useful to characterize atherosclerotic lesions and myocardial abnormalities. The current view is that such platforms could be of clinical value for prevention, risk stratification, and treatment of ASCVD.

Single-Cell Meta-Analysis of Neutrophil Activation in Kawasaki Disease and Multisystem Inflammatory Syndrome in Children Reveals Potential Shared Immunological Drivers

BACKGROUND

Kawasaki disease (KD) and multisystem inflammatory syndrome in children (MIS-C) share similar clinical manifestations, including cardiovascular complications, suggesting similar underlying immunopathogenic processes. Aberrant neutrophil activation may play a crucial role in the shared pathologies of KD and MIS-C; however, the associated pathogenic mechanisms and molecular drivers remain unknown.

METHODS

We performed a single-cell meta-analysis of neutrophil activation with 103 pediatric single-cell transcriptomic peripheral blood mononuclear cell data across 9 cohorts, including healthy controls, KD, MIS-C, compared with dengue virus infection, juvenile idiopathic arthritis, and pediatric celiac disease. We used a series of computational analyses to investigate the shared neutrophil transcriptional programs of KD and MIS-C that are linked to systemic damage and cardiac pathologies, and suggested Food and Drug Administration-approved drugs to consider as KD and MIS-C treatment.

RESULTS

We meta-analyzed 521 950 high-quality cells. We found that blood signatures associated with risks of cardiovascular events are enriched in neutrophils of KD and MIS-C. We revealed the expansion of CD177+ neutrophils harboring hyperactivated effector functions in both KD and MIS-C, but not in healthy controls or in other viral-, inflammatory-, or immune-related pediatric diseases. KD and MIS-C CD177+ neutrophils had highly similar transcriptomes, marked by conserved signatures and pathways related to molecular damage. We found the induction of a shared neutrophil expression program, potentially regulated by SPI1 (Spi-1 proto-oncogene), which confers enhanced effector functions, especially neutrophil degranulation. CD177 and shared neutrophil expression program expressions were associated with acute stages and attenuated during KD intravenous immunoglobulin treatment and MIS-C recovery. Network analysis identified hub genes that correlated with the high activation of CD177+ neutrophils. Disease-gene association analysis revealed that the KD and MIS-C CD177+ neutrophils' shared expression program was associated with the development of coronary and myocardial disorders. Last, we identified and validated TSPO (translocator protein) and S100A12 (S100 calcium-binding protein A12) as main molecular targets, for which the Food and Drug Administration-approved drugs methotrexate, zaleplon, metronidazole, lorazepam, clonazepam, temazepam, and zolpidem, among others, are primary candidates for drug repurposing.

CONCLUSIONS

Our findings indicate that CD177+ neutrophils may exert systemic pathological damage contributing to the shared morbidities in KD and MIS-C. We uncovered potential regulatory drivers of CD177+ neutrophil hyperactivation and pathogenicity that may be targeted as a single therapeutic strategy for either KD or MIS-C.

Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts

Fibroblasts are essential regulators of extracellular matrix deposition following cardiac injury. These cells exhibit highly plastic responses in phenotype during fibrosis in response to environmental stimuli. Here, we test whether and how candidate anti-fibrotic drugs differentially regulate measures of cardiac fibroblast phenotype, which may help identify treatments for cardiac fibrosis. We conducted a high content microscopy screen of human cardiac fibroblasts treated with 13 clinically relevant drugs in the context of TGFβ and/or IL-1β, measuring phenotype across 137 single-cell features. We used the phenotypic data from our high content imaging to train a logic-based mechanistic machine learning model (LogiMML) for fibroblast signaling. The model predicted how pirfenidone and Src inhibitor WH-4-023 reduce actin filament assembly and actin-myosin stress fiber formation, respectively. Validating the LogiMML model prediction that PI3K partially mediates the effects of Src inhibition, we found that PI3K inhibition reduces actin-myosin stress fiber formation and procollagen I production in human cardiac fibroblasts. In this study, we establish a modeling approach combining the strengths of logic-based network models and regularized regression models, apply this approach to predict mechanisms that mediate the differential effects of drugs on fibroblasts, revealing Src inhibition acting via PI3K as a potential therapy for cardiac fibrosis.

Multifaceted Roles of ALK Family Receptors and Augmentor Ligands in Health and Disease: A Comprehensive Review

This review commemorates the 10-year anniversary of the discovery of physiological ligands Augα (Augmentor α; ALKAL2; Fam150b) and Augβ (Augmentor β; ALKAL1; Fam150a) for anaplastic lymphoma kinase (ALK) and leukocyte tyrosine kinase (LTK), previously considered orphan receptors. This manuscript provides an in-depth review of the biophysical and cellular properties of ALK family receptors and their roles in cancer, metabolism, pain, ophthalmology, pigmentation, central nervous system (CNS) function, and reproduction. ALK and LTK receptors are implicated in the development of numerous cancers, and targeted inhibition of their signaling pathways can offer therapeutic benefits. Additionally, ALK family receptors are involved in regulating body weight and metabolism, modulating pain signaling, and contributing to eye development and pigmentation. In the CNS, these receptors play a role in synapse modulation, neurogenesis, and various psychiatric pathologies. Lastly, ALK expression is linked to reproductive functions, with potential implications for patients undergoing ALK inhibitor therapy. Further research is needed to better understand the complex interactions of ALK family receptors and Aug ligands and to repurpose targeted therapy for a wide range of human diseases.

Repurposable Drugs for Immunotherapy and Strategies to Find Candidate Drugs

Conventional drug discovery involves significant steps, time, and expenses; therefore, novel methods for drug discovery remain unmet, particularly for patients with intractable diseases. For this purpose, the drug repurposing method has been recently used to search for new therapeutic agents. Repurposed drugs are mostly previously approved drugs, which were carefully tested for their efficacy for other diseases and had their safety for the human body confirmed following careful pre-clinical trials, clinical trials, and post-marketing surveillance. Therefore, using these approved drugs for other diseases that cannot be treated using conventional therapeutic methods could save time and economic costs for testing their clinical applicability. In this review, we have summarized the methods for identifying repurposable drugs focusing on immunotherapy.

Repositioning of clinically approved drug Bazi Bushen capsule for treatment of Aizheimer's disease using network pharmacology approach and in vitro experimental validation

Aims

To explore the new indications and key mechanism of Bazi Bushen capsule (BZBS) by network pharmacology and in vitro experiment.

Methods

The ingredients library of BZBS was constructed by retrieving multiple TCM databases. The potential target profiles of the components were predicted by target prediction algorithms based on different principles, and validated by using known activity data. The target spectrum of BZBS with high reliability was screened by considering the source of the targets and the node degree in compound-target (C-T) network. Subsequently, new indications for BZBS were predicted by disease ontology (DO) enrichment analysis and initially validated by GO and KEGG pathway enrichment analysis. Furthermore, the target sets of BZBS acting on AD signaling pathway were identified by intersection analysis. Based on STRING database, the PPI network of target was constructed and their node degree was calculated. Two Alzheimer's disease (AD) cell models, BV-2 and SH-SY5Y, were used to preliminarily verify the anti-AD efficacy and mechanism of BZBS in vitro.

Results

In total, 1499 non-repeated ingredients were obtained from 16 herbs in BZBS formula, and 1320 BZBS targets with high confidence were predicted. Disease enrichment results strongly suggested that BZBS formula has the potential to be used in the treatment of AD. GO and KEGG enrichment results provide a preliminary verification of this point. Among them, 113 functional targets of BZBS belong to AD pathway. A PPI network containing 113 functional targets and 1051 edges for the treatment of AD was constructed. In vitro experiments showed that BZBS could significantly reduce the release of TNF-α and IL-6 and the expression of COX-2 and PSEN1 in Aβ_25-35-induced BV-2 cells, which may be related to the regulation of ERK_1/2/NF-κB signaling pathway. BZBS reduced the apoptosis rate of Aβ_25-35 induced SH-SY5Y cells, significantly increased mitochondrial membrane potential, reduced the expression of Caspase3 active fragment and PSEN1, and increased the expression of IDE. This may be related to the regulation of GSK-3β/β-catenin signaling pathway.

Conclusions

BZBS formula has a potential use in the treatment of AD, which is achieved through regulation of ERK_1/2, NF-κB signaling pathways, and GSK-3β/β-catenin signaling pathway. Furthermore, the network pharmacology technology is a feasible drug repurposing strategy to reposition new clinical use of approved TCM and explore the mechanism of action. The study lays a foundation for the subsequent in-depth study of BZBS in the treatment of AD and provides a basis for its application in the clinical treatment of AD.

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis

The development of new immunotherapies to treat the inflammatory mechanisms that sustain atherosclerotic cardiovascular disease (ASCVD) is urgently needed. Herein, we present a path to drug repurposing to identify immunotherapies for ASCVD. The integration of time-of-flight mass cytometry and RNA sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells stimulated with ASCVD plasma. By comparing these inflammatory signatures to large-scale gene expression data from the LINCS L1000 dataset, we identified drugs that could reverse this inflammatory response. Ex vivo screens, using human samples, showed that saracatinib-a phase 2a-ready SRC and ABL inhibitor-reversed the inflammatory responses induced by ASCVD plasma. In Apoe-/- mice, saracatinib reduced atherosclerosis progression by reprogramming reparative macrophages. In a rabbit model of advanced atherosclerosis, saracatinib reduced plaque inflammation measured by [18F] fluorodeoxyglucose positron emission tomography-magnetic resonance imaging. Here we show a systems immunology-driven drug repurposing with a preclinical validation strategy to aid the development of cardiovascular immunotherapies.

Repurposing Drugs for the Treatment of COVID-19 and Its Cardiovascular Manifestations

COVID-19 is an infectious disease caused by SARS-CoV-2 leading to the ongoing global pandemic. Infected patients developed a range of respiratory symptoms, including respiratory failure, as well as other extrapulmonary complications. Multiple comorbidities, including hypertension, diabetes, cardiovascular diseases, and chronic kidney diseases, are associated with the severity and increased mortality of COVID-19. SARS-CoV-2 infection also causes a range of cardiovascular complications, including myocarditis, myocardial injury, heart failure, arrhythmias, acute coronary syndrome, and venous thromboembolism. Although a variety of methods have been developed and many clinical trials have been launched for drug repositioning for COVID-19, treatments that consider cardiovascular manifestations and cardiovascular disease comorbidities specifically are limited. In this review, we summarize recent advances in drug repositioning for COVID-19, including experimental drug repositioning, high-throughput drug screening, omics data-based, and network medicine-based computational drug repositioning, with particular attention on those drug treatments that consider cardiovascular manifestations of COVID-19. We discuss prospective opportunities and potential methods for repurposing drugs to treat cardiovascular complications of COVID-19.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

Negative findings but positive contributions in cardiovascular research

Researchers have always concluded that results that do not support the hypothesis as unimportant, unworthy, or simply not good enough for publication. However, negative findings are essential for the progress of science and its self-correcting nature. We also believe in the importance and indispensability of negative results. Therefore, in this review, we discussed the factors contributing to the publication bias of negative results and the problems to assess the factuality and validity of negative results. Moreover, we emphasized the importance of reporting negative results in cardiovascular research, including treatments, and suggest that the negative results could clarify previously controversial topics in the treatment of cardiovascular diseases and prompt the translation of research on precision cardiovascular disease prevention and treatment.

A regenerable electrochemical sensor for electro-inactive cyclovirobuxine D detection in biological samples

Based on the pK_a determination of cyclovirobuxine D (CVB-D) using the method of potentiometry, we predicted the ionization state of CVB-D at physiological pH. Thus, by taking advantage of the ionization state and consequent non-covalent interactions between protonated CVB-D and deprotonated polymerized bromothymol blue (poly-BTB) under physiological conditions, we developed a simple and reusable electrochemical sensor that contains a poly-BTB/SWNT-modified electrode for electro-inactive CVB-D detection in biological fluids using poly-BTB as both the recognition unit and the electrochemical probe. Upon being immersed in the solution of CVB-D, the poly BTB-based electrode shows a current decrease due to the interaction-driven binding of CVB-D on the electrode surface. The current decrease in the electrochemical sensor toward CVB-D concentration shows a linear relationship in the dynamic ranges of 0.01-1 μM and 1-50 μM with a detection limit of 1.65 nM based on 3σ. The sensor can be easily regenerated through the removal of the binding of CVB-D from the electrode surface by highly negatively charged heparin, and it presents high repeatability with an RSD of less than 4.0% for seven measurements. In animal experiments, the electrochemical sensor was selective and sensitive for CVB-D determination in plasma and liver homogenates. The electrochemical sensor is readily accessible, robust, and cost-effective and holds good promise for more applications in biological and clinical fields associated with CVB-D using less technically demanding and simple operating procedures.

Current Trends in Nanotheranostics: A Concise Review on Bioimaging and Smart Wearable Technology

The area of interventional nanotheranostics combines the use of interventional procedures with nanotechnology for the detection and treatment of physiological disorders. Using catheters or endoscopes, for example, interventional techniques make use of minimally invasive approaches to diagnose and treat medical disorders. It is feasible to increase the precision of these approaches and potency by integrating nanotechnology. To visualize and target various parts of the body, such as tumors or obstructed blood veins, one can utilize nanoscale probes or therapeutic delivery systems. Interventional nanotheranostics offers targeted, minimally invasive therapies that can reduce side effects and enhance patient outcomes, and it has the potential to alter the way that many medical illnesses are handled. Clinical enrollment and implementation of such laboratory scale theranostics approach in medical practice is promising for the patients where the user can benefit by tracking its physiological state. This review aims to introduce the most recent advancements in the field of clinical imaging and diagnostic techniques as well as newly developed on-body wearable devices to deliver therapeutics and monitor its due alleviation in the biological milieu.

Pharmacometabolomics for the Study of Lipid-Lowering Therapies: Opportunities and Challenges

Lipid-lowering therapies are widely used to prevent the development of atherosclerotic cardiovascular disease (ASCVD) and related mortality worldwide. "Omics" technologies have been successfully applied in recent decades to investigate the mechanisms of action of these drugs, their pleiotropic effects, and their side effects, aiming to identify novel targets for future personalized medicine with an improvement of the efficacy and safety associated with the treatment. Pharmacometabolomics is a branch of metabolomics that is focused on the study of drug effects on metabolic pathways that are implicated in the variation of response to the treatment considering also the influences from a specific disease, environment, and concomitant pharmacological therapies. In this review, we summarized the most significant metabolomic studies on the effects of lipid-lowering therapies, including the most commonly used statins and fibrates to novel drugs or nutraceutical approaches. The integration of pharmacometabolomics data with the information obtained from the other "omics" approaches could help in the comprehension of the biological mechanisms underlying the use of lipid-lowering drugs in view of defining a precision medicine to improve the efficacy and reduce the side effects associated with the treatment.

Targeting mitochondrial impairment for the treatment of cardiovascular diseases: From hypertension to ischemia-reperfusion injury, searching for new pharmacological targets

Mitochondria and mitochondrial proteins represent a group of promising pharmacological target candidates in the search of new molecular targets and drugs to counteract the onset of hypertension and more in general cardiovascular diseases (CVDs). Indeed, several mitochondrial pathways result impaired in CVDs, showing ATP depletion and ROS production as common traits of cardiac tissue degeneration. Thus, targeting mitochondrial dysfunction in cardiomyocytes can represent a successful strategy to prevent heart failure. In this context, the identification of new pharmacological targets among mitochondrial proteins paves the way for the design of new selective drugs. Thanks to the advances in omics approaches, to a greater availability of mitochondrial crystallized protein structures and to the development of new computational approaches for protein 3D-modelling and drug design, it is now possible to investigate in detail impaired mitochondrial pathways in CVDs. Furthermore, it is possible to design new powerful drugs able to hit the selected pharmacological targets in a highly selective way to rescue mitochondrial dysfunction and prevent cardiac tissue degeneration. The role of mitochondrial dysfunction in the onset of CVDs appears increasingly evident, as reflected by the impairment of proteins involved in lipid peroxidation, mitochondrial dynamics, respiratory chain complexes, and membrane polarization maintenance in CVD patients. Conversely, little is known about proteins responsible for the cross-talk between mitochondria and cytoplasm in cardiomyocytes. Mitochondrial transporters of the SLC25A family, in particular, are responsible for the translocation of nucleotides (e.g., ATP), amino acids (e.g., aspartate, glutamate, ornithine), organic acids (e.g. malate and 2-oxoglutarate), and other cofactors (e.g., inorganic phosphate, NAD⁺, FAD, carnitine, CoA derivatives) between the mitochondrial and cytosolic compartments. Thus, mitochondrial transporters play a key role in the mitochondria-cytosol cross-talk by leading metabolic pathways such as the malate/aspartate shuttle, the carnitine shuttle, the ATP export from mitochondria, and the regulation of permeability transition pore opening. Since all these pathways are crucial for maintaining healthy cardiomyocytes, mitochondrial carriers emerge as an interesting class of new possible pharmacological targets for CVD treatments.

Microfluidics for diagnosis and treatment of cardiovascular disease

Cardiovascular disease (CVD), a type of circulatory system disease related to the lesions of the cardiovascular system, has become one of the main diseases that endanger human health. Currently, the clinical diagnosis of most CVDs relies on a combination of imaging technology and blood biochemical test. However, the existing technologies for diagnosis of CVDs still have limitations in terms of specificity, detection range, and cost. In order to break through the current bottleneck, microfluidic with the advantages of low cost, simple instruments and easy integration, has been developed to play an important role in the early prevention, diagnosis and treatment of CVDs. Here, we have reviewed the recent various applications of microfluidic in the clinical diagnosis and treatment of CVDs, including microfluidic devices for detecting CVD markers, the cardiovascular models based on microfluidic, and the microfluidic used for CVDs drug screening and delivery. In addition, we have briefly looked forward to the prospects and challenges of microfluidics in diagnosis and treatment of CVDs.

The sirtuin family in health and disease

Sirtuins (SIRTs) are nicotine adenine dinucleotide(+)-dependent histone deacetylases regulating critical signaling pathways in prokaryotes and eukaryotes, and are involved in numerous biological processes. Currently, seven mammalian homologs of yeast Sir2 named SIRT1 to SIRT7 have been identified. Increasing evidence has suggested the vital roles of seven members of the SIRT family in health and disease conditions. Notably, this protein family plays a variety of important roles in cellular biology such as inflammation, metabolism, oxidative stress, and apoptosis, etc., thus, it is considered a potential therapeutic target for different kinds of pathologies including cancer, cardiovascular disease, respiratory disease, and other conditions. Moreover, identification of SIRT modulators and exploring the functions of these different modulators have prompted increased efforts to discover new small molecules, which can modify SIRT activity. Furthermore, several randomized controlled trials have indicated that different interventions might affect the expression of SIRT protein in human samples, and supplementation of SIRT modulators might have diverse impact on physiological function in different participants. In this review, we introduce the history and structure of the SIRT protein family, discuss the molecular mechanisms and biological functions of seven members of the SIRT protein family, elaborate on the regulatory roles of SIRTs in human disease, summarize SIRT inhibitors and activators, and review related clinical studies.

Drug repurposing in cardiovascular inflammation: Successes, failures, and future opportunities

Drug repurposing is an attractive, pragmatic approach to drug discovery that has yielded success across medical fields over the years. The use of existing medicines for novel indications enables dramatically reduced development costs and timescales compared with de novo drug discovery and is therefore a promising strategy in cardiovascular disease, where new drug approvals lag significantly behind that of other fields. Extensive evidence from pre-clinical and clinical studies show that chronic inflammation is a driver of pathology in cardiovascular disease, and many efforts have been made to target cardiovascular inflammation therapeutically. This approach has been met with significant challenges however, namely off-target effects associated with broad-spectrum immunosuppression, particularly in long-term conditions such as cardiovascular disease. Nevertheless, multiple anti-inflammatory medicines have been assessed for efficacy in cardiovascular clinical trials, with most of these being repurposed from their original indications in autoimmune conditions like rheumatoid arthritis. In this review, we discuss the mixed successes of clinical trials investigating anti-inflammatory drugs in cardiovascular disease, with examples such as anti-cytokine monoclonal antibodies, colchicine, and methotrexate. Looking to the future, we highlight potential new directions for drug repurposing in cardiovascular inflammation, including the emerging concepts of drug re-engineering and chrono-pharmacology.

Calcium-Sensing Receptor (CaSR)-Mediated Intracellular Communication in Cardiovascular Diseases

The calcium-sensing receptor (CaSR), a G-protein-coupled receptor (GPCR), is a cell-surface-located receptor that can induce highly diffusible messengers (IP3, Ca²⁺, cAMP) in the cytoplasm to activate various cellular responses. Recently, it has also been suggested that the CaSR mediates the intracellular communications between the endoplasmic reticulum (ER), mitochondria, nucleus, protease/proteasome, and autophagy-lysosome, which are involved in related cardiovascular diseases. The complex intracellular signaling of this receptor challenges it as a valuable therapeutic target. It is, therefore, necessary to understand the mechanisms behind the signaling characteristics of this receptor in intracellular communication. This review provides an overview of the recent research progress on the various regulatory mechanisms of the CaSR in related cardiovascular diseases and the heart-kidney interaction; the associated common causes are also discussed.