Physiological reviews最新文献

Glucagon's ability to promote hepatic glucose production has been known for over a century, with initial observations touting this hormone as a diabetogenic agent. However, glucagon receptor agonism [when balanced with an incretin, including glucagon-like peptide 1 (GLP-1) to dampen glucose excursions] is now being developed as a promising therapeutic target in the treatment of metabolic diseases, like metabolic dysfunction-associated steatotic disease/metabolic dysfunction-associated steatohepatitis (MASLD/MASH), and may also have benefit for obesity and chronic kidney disease. Conventionally regarded as the opposing tag-team partner of the anabolic mediator insulin, glucagon is gradually emerging as more than just a "catabolic hormone." Glucagon action on glucose homeostasis within the liver has been well characterized. However, growing evidence, in part thanks to new and sensitive "omics" technologies, has implicated glucagon as more than just a "glucose liberator." Elucidation of glucagon's capacity to increase fatty acid oxidation while attenuating endogenous lipid synthesis speaks to the dichotomous nature of the hormone. Furthermore, glucagon action is not limited to just glucose homeostasis and lipid metabolism, as traditionally reported. Glucagon plays key regulatory roles in hepatic amino acid and ketone body metabolism, as well as mitochondrial turnover and function, indicating broader glucagon signaling consequences for metabolic homeostasis mediated by the liver. Here we examine the broadening role of glucagon signaling within the hepatocyte and question the current dogma, to appreciate glucagon as more than just that "catabolic hormone."

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

The endomembrane system consists of organellar membranes in the biosynthetic pathway [endoplasmic reticulum (ER), Golgi apparatus, and secretory vesicles] as well as those in the degradative pathway (early endosomes, macropinosomes, phagosomes, autophagosomes, late endosomes, and lysosomes). These endomembrane organelles/vesicles work together to synthesize, modify, package, transport, and degrade proteins, carbohydrates, and lipids, regulating the balance between cellular anabolism and catabolism. Large ion concentration gradients exist across endomembranes: Ca²⁺ gradients for most endomembrane organelles and H⁺ gradients for the acidic compartments. Ion (Na⁺, K⁺, H⁺, Ca²⁺, and Cl^-) channels on the organellar membranes control ion flux in response to cellular cues, allowing rapid informational exchange between the cytosol and organelle lumen. Recent advances in organelle proteomics, organellar electrophysiology, and luminal and juxtaorganellar ion imaging have led to molecular identification and functional characterization of about two dozen endomembrane ion channels. For example, whereas IP3R1-3 channels mediate Ca²⁺ release from the ER in response to neurotransmitter and hormone stimulation, TRPML1-3 and TMEM175 channels mediate lysosomal Ca²⁺ and H⁺ release, respectively, in response to nutritional and trafficking cues. This review aims to summarize the current understanding of these endomembrane channels, with a focus on their subcellular localizations, ion permeation properties, gating mechanisms, cell biological functions, and disease relevance.

The Na⁺-Cl^- cotransporter (NCC; SLC12A3) is a highly regulated integral membrane protein that is known to exist as three splice variants in primates. Its primary role in the kidney is to mediate the cosymport of Na⁺ and Cl^- across the apical membrane of the distal convoluted tubule. Through this role and the involvement of other ion transport systems, NCC allows the systemic circulation to reclaim a fraction of the ultrafiltered Na⁺, K⁺, Cl^-, and Mg⁺ loads in exchange for Ca²⁺ and [Formula: see text]. The physiological relevance of the Na⁺-Cl^- cotransport mechanism in humans is illustrated by several abnormalities that result from NCC inactivation through the administration of thiazides or in the setting of hereditary disorders. The purpose of the present review is to discuss the molecular mechanisms and overall roles of Na⁺-Cl^- cotransport as the main topics of interest. On reading the narrative proposed, one will realize that the knowledge gained in regard to these themes will continue to progress unrelentingly no matter how refined it has now become.

The collective efforts of scientists over multiple decades have led to advancements in molecular and cellular biology-based technologies including genetic engineering and animal cloning that are now being harnessed to enhance the suitability of pig organs for xenotransplantation into humans. Using organs sourced from pigs with multiple gene deletions and human transgene insertions, investigators have overcome formidable immunological and physiological barriers in pig-to-nonhuman primate (NHP) xenotransplantation and achieved prolonged pig xenograft survival. These studies informed the design of Revivicor's (Revivicor Inc, Blacksburg, VA) genetically engineered pigs with 10 genetic modifications (10 GE) (including the inactivation of 4 endogenous porcine genes and insertion of 6 human transgenes), whose hearts and kidneys have now been studied in preclinical human xenotransplantation models with brain-dead recipients. Additionally, the first two clinical cases of pig-to-human heart xenotransplantation were recently performed with hearts from this 10 GE pig at the University of Maryland. Although this review focuses on xenotransplantation of hearts and kidneys, multiple organs, tissues, and cell types from genetically engineered pigs will provide much-needed therapeutic interventions in the future.

Stress resilience is the phenomenon that some people maintain their mental health despite exposure to adversity or show only temporary impairments followed by quick recovery. Resilience research attempts to unravel the factors and mechanisms that make resilience possible and to harness its insights for the development of preventative interventions in individuals at risk for acquiring stress-related dysfunctions. Biological resilience research has been lagging behind the psychological and social sciences but has seen a massive surge in recent years. At the same time, progress in this field has been hampered by methodological challenges related to finding suitable operationalizations and study designs, replicating findings, and modeling resilience in animals. We embed a review of behavioral, neuroimaging, neurobiological, and systems biological findings in adults in a critical methods discussion. We find preliminary evidence that hippocampus-based pattern separation and prefrontal-based cognitive control functions protect against the development of pathological fears in the aftermath of singular, event-type stressors [as found in fear-related disorders, including simpler forms of posttraumatic stress disorder (PTSD)] by facilitating the perception of safety. Reward system-based pursuit and savoring of positive reinforcers appear to protect against the development of more generalized dysfunctions of the anxious-depressive spectrum resulting from more severe or longer-lasting stressors (as in depression, generalized or comorbid anxiety, or severe PTSD). Links between preserved functioning of these neural systems under stress and neuroplasticity, immunoregulation, gut microbiome composition, and integrity of the gut barrier and the blood-brain barrier are beginning to emerge. On this basis, avenues for biological interventions are pointed out.

Effective data management is crucial for scientific integrity and reproducibility, a cornerstone of scientific progress. Well-organized and well-documented data enable validation and building on results. Data management encompasses activities including organization, documentation, storage, sharing, and preservation. Robust data management establishes credibility, fostering trust within the scientific community and benefiting researchers' careers. In experimental biomedicine, comprehensive data management is vital due to the typically intricate protocols, extensive metadata, and large datasets. Low-throughput experiments, in particular, require careful management to address variations and errors in protocols and raw data quality. Transparent and accountable research practices rely on accurate documentation of procedures, data collection, and analysis methods. Proper data management ensures long-term preservation and accessibility of valuable datasets. Well-managed data can be revisited, contributing to cumulative knowledge and potential new discoveries. Publicly funded research has an added responsibility for transparency, resource allocation, and avoiding redundancy. Meeting funding agency expectations increasingly requires rigorous methodologies, adherence to standards, comprehensive documentation, and widespread sharing of data, code, and other auxiliary resources. This review provides critical insights into raw and processed data, metadata, high-throughput versus low-throughput datasets, a common language for documentation, experimental and reporting guidelines, efficient data management systems, sharing practices, and relevant repositories. We systematically present available resources and optimal practices for wide use by experimental biomedical researchers.