Citations

Abstract Hepatocellular endocytosis is a highly dynamic process responsible for the internalization of a variety of different receptor ligand complexes, trophic factors, lipids, and, unfortunately, many different pathogens. The uptake of these external agents has profound effects on seminal cellular processes including signaling cascades, migration, growth, and proliferation. The hepatocyte, like other well‐polarized epithelial cells, possesses a host of different endocytic mechanisms and entry routes to ensure the selective internalization of cargo molecules. These pathways include receptor‐mediated endocytosis, lipid raft associated endocytosis, caveolae, or fluid‐phase uptake, although there are likely many others. Understanding and defining the regulatory mechanisms underlying these distinct entry routes, sorting and vesicle formation, as well as the postendocytic trafficking pathways is of high importance especially in the liver, as their mis‐regulation can contribute to aberrant liver pathology and liver diseases. Further, these processes can be “hijacked” by a variety of different infectious agents and viruses. This review provides an overview of common components of the endocytic and postendocytic trafficking pathways utilized by hepatocytes. It will also discuss in more detail how these general themes apply to liver‐specific processes including iron homeostasis, HBV infection, and even hepatic steatosis. © 2014 American Physiological Society. Compr Physiol 4:1403‐1417, 2014.

Abstract The autonomic nervous system is a key regulator of the cardiovascular system. In this review, we focus on how sex and aging influence autonomic regulation of blood pressure in humans in an effort to understand general issues related to the cardiovascular system as a whole. Younger women generally have lower blood pressure and sympathetic activity than younger men. However, both sexes show marked interindividual variability across age groups with significant overlap seen. Additionally, while men across the lifespan show a clear relationship between markers of whole body sympathetic activity and vascular resistance, such a relationship is not seen in young women. In this context, the ability of the sympathetic nerves to evoke vasoconstriction is lower in young women likely as a result of concurrent β 2 ‐mediated vasodilation that offsets α‐adrenergic vasoconstriction. These differences reflect both central sympatho‐inhibitory effects of estrogen and also its influence on peripheral vasodilation at the level of the vascular smooth muscle and endothelium. By contrast postmenopausal women show a clear relationship between markers of whole body sympathetic traffic and vascular resistance, and sympathetic activity rises progressively in both sexes with aging. These major findings in humans are discussed in the context of differences in population‐based trends in blood pressure and orthostatic intolerance. The many areas where there is little sex‐specific data on how the autonomic nervous system participates in the regulation of the human cardiovascular system are highlighted. © 2015 American Physiological Society. Compr Physiol 5:193‐215, 2015.

Abstract The human microbiome consists of the microorganisms associated with the body, such as bacteria, fungi, archaea, protozoa, and viruses, along with their gene content and products. These microbes are abundant in the digestive, respiratory, renal/urinary, and reproductive systems. While microbes found in other organs/tissues are often associated with diseases, some reports suggest their presence even in healthy individuals. Lack of microbial colonization does not indicate a lack of microbial influence, as their metabolites can affect distant locations through circulation. In a healthy state, these microbes maintain a mutualistic relationship and help shape the host's physiological functions. Unlike the host's genetic content, microbial gene content and expression are dynamic and influenced by factors such as ethnicity, genetic background, sex, age, lifestyle/diet, and psychological/physical conditions. Therefore, defining a healthy microbiome becomes challenging as it is context dependent and can vary over time for an individual. Although differences in microbial composition have been observed in various diseases, these changes may reflect host alterations rather than causing the disease itself. As the field is evolving, there is increased emphasis on understanding when changes in the microbiome are an important component of pathogenesis rather than the consequence of a disease state. This article focuses on the microbial component in the digestive and respiratory tracts—the primary sites colonized by microorganisms—and the physiological functions of microbial metabolites in these systems. It also discusses their physiological functions in the central nervous and cardiovascular systems, which have no microorganism colonization under healthy conditions based on human studies. © 2024 American Physiological Society. Compr Physiol 14:5491‐5519, 2024.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, primarily due to its complex tumor microenvironment (TME), which drives both disease progression and therapy resistance. Understanding the molecular mechanisms governing TME dynamics is essential for developing new treatment strategies for this devastating disease. In this study, we uncover an oncogenic role for Galectin-1 (Gal1), a glycan-binding protein abundantly expressed by activated pancreatic stellate cells (PSCs), a key component of the PDAC TME that orchestrates tumor progression. Our findings reveal that Gal1 expression is elevated in the nucleus of human PSCs in both tissue samples and cultured cell lines. Using chromatin immunoprecipitation followed by sequencing analysis (ChIP-seq), we identify Gal1 occupancy at the promoters of several cancer-associated genes, including KRAS , a pivotal oncogene involved in PDAC pathogenesis. We demonstrate that Gal1 binds to the KRAS promoter, sustaining KRAS expression in PSCs, which, in turn, maintains PSC activation and promotes the secretion of protumorigenic cytokines. Mechanistically, Gal1 is required to preserve histone H3 lysine 4 monomethylation levels and to recruit the histone methyltransferase MLL1 to target promoters. Collectively, our findings define a nuclear function of Gal1 in modulating the transcriptional landscape of cancer-associated genes in PSCs within the PDAC TME, mediated through an epigenetic mechanism. These insights enhance our understanding of PDAC pathology and open potential avenues for therapeutic interventions targeting intracellular Gal1.

ABSTRACTObjectiveTo explore pre–hematopoietic stem cell transplant (HSCT) demographic, disease, and psychological factors predictive of future transplant regret and to determine post‐HSCT variables associated with regret.Patients and MethodsHSCT candidates participated in a prospective cohort study (June 2008–October 2013) examining health behaviors and HSCT outcomes, including completion of standardized surveys at pre‐HSCT (baseline) and 1‐year post‐HSCT. Cases were participants that endorsed regret at 1‐year post‐HSCT follow‐up, and controls were participants without regret at 1 year, matched on age, sex, and transplant type. For cases and controls, pre‐HSCT psychosocial evaluations were abstracted from the electronic health record and coded to determine the Psychosocial Assessment of Candidates for Transplantation score, psychosocial stressors, and mental health diagnoses. The association of selected factors with regret was estimated with odds ratios and 95% confidence intervals from conditional logistic regression models.ResultsAt post‐HSCT, 49 participants of 638 endorsed transplant regret (8%) and formed the case group; 98 controls were matched from remaining participants. Cases and controls were well matched on age (56.6 vs. 57.2 years), sex (both groups 34.7% female), and transplant type (both groups 81.6% autologous). After controlling for the number of hospitalizations and active treatment status, conditional logistic regression revealed that patients who endorsed regret were 3.7 times (95% CI = 1.37–9.69, p = 0.008) more likely to not be in remission compared to controls at 1‐year post‐HSCT.ConclusionMatched case–control analyses revealed that no pre‐HSCT variables collected during the pre‐HSCT evaluation period were predictive of transplant regret, while poorer outcomes at 1‐year after transplant were associated with regret.

Guideline-recommended screening programs exist for only a few single-cancer types, and these cancers represent less than one-half of all new cancer cases diagnosed each year in the U.S. In addition, these “single-cancer” standard of care (SoC) screening tests vary in accuracy, adherence, and effectiveness, though all are generally understood to lead to reductions in cancer-related mortality. Recent advances in high-throughput technologies and machine learning have facilitated the development of blood-based multi-cancer early detection (MCED) tests. The opportunity for early detection of multiple cancers with a single blood test holds promise in addressing the current unmet need in cancer screening. By complementing existing SoC screening, MCED tests have the potential to detect a wide range of cancers at earlier stages when patients are asymptomatic, enabling more effective treatment options and improved cancer outcomes. MCED tests are positioned to be utilized as a complementary screening tool to improve screening adherence at the population level, to broaden screening availability for individuals who are not adherent with SoC screening programs, as well as for those who may harbor cancers that do not have SoC testing available. Published work to date has primarily focused on test performance relating to sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). MCED tests will require approval through the pre-market approval pathway from the United States Food and Drug Administration. Additional studies will be needed to demonstrate clinical utility (i.e., improvements in health outcomes) and establish optimal implementation strategies, (i.e., testing intervals), follow-up and logistics of shared decision making. Here, we propose core attributes of MCED testing for which clinical data are needed to ideally position MCED testing for widespread use in clinical practice.

Purpose: This study aimed to compare long-term patient-reported outcomes in bowel and urinary domains between intensity-modulated radiotherapy (IMRT) and intensity-modulated proton therapy (IMPT) for localized prostate cancer. Methods and Materials: Patients with clinical T1–T2 prostate cancer receiving IMRT or IMPT at a tertiary cancer center from 2015–2018 were analyzed to determine the changes in the prospectively collected bowel function (BF), urinary irritative/obstructive symptoms (UO), and urinary incontinence (UI) domains of EPIC-26. The mean changes in EPIC-26 scores were evaluated from pretreatment to 24 months post-radiotherapy for each modality. A score change >50% of the baseline standard deviation was considered a clinically meaningful change. Results: A total of 82 patients treated with IMRT (52.2%) and 56 patients treated with IMPT (53.3%) completed the questionnaire at baseline and 24 months post-RT. There were no baseline differences in domain scores between treatment modalities. At 24 months post-radiotherapy, there was a significant and clinically meaningful decline in the BF mean score in the IMRT cohort (−4.52 (range −50, 29.17), p = 0.003), whereas the decline in BF score did not reach clinical relevance or significance (−1.88 (range −37.5, 50), p = 0.046) when accounting for the Bonferroni adjustment in the IMPT cohort. A higher proportion of patients treated with IMRT had a clinically relevant reduction in BF when compared with IMPT (47.37% vs. 25.93%, p = 0.017). The mean changes in the UI and UO scores of the IMRT and IMPT cohorts were neither statically significant nor clinically relevant. Conclusions: IMPT leads to a smaller decrease in BF than IMRT at 24 months post-RT, while there was no differential effect on UO and UI.

Cardiovascular diseases (CVDs) are the leading cause of death in the world. A total of 17.5 million people died of CVDs in the year 2012, accounting for 31% of all deaths globally. Vertebrate animal models have been used to understand cardiac disease biology, as the cellular, molecular, and physiological aspects of human CVDs can be replicated closely in these organisms. Zebrafish is a popular model organism offering an arsenal of genetic tools that allow the rapid in vivo analysis of vertebrate gene function and disease conditions. It has a short breeding cycle, high fecundity, optically transparent embryos, rapid internal organ development, and easy maintenance. This review aims to give readers an overview of zebrafish cardiac biology and a detailed account of heart development in zebrafish and its comparison with humans and the conserved genetic circuitry. We also discuss the contributions made in CVD research using the zebrafish model. The first part of this review focuses on detailed information on the morphogenetic and differentiation processes in early cardiac development. The overlap and divergence of the human heart’s genetic circuitry, structure, and physiology are emphasized wherever applicable. In the second part of the review, we overview the molecular tools and techniques available to dissect gene function and expression in zebrafish, with special mention of the use of these tools in cardiac biology.

Intensive care units (ICUs) serve patients with life-threatening conditions. However, the availability of ICU resources remains scarce worldwide. Therefore, it is critical to conduct ICU outcome predictions at an early stage and promote efficient use of ICU resources. However, the current ICU outcome prediction methods have limitations such as unsatisfactory accuracy and dependence on resource-demanding laboratory tests or expert domain knowledge. In this research, we design a wavelet transform based additive convolutional neural network (WT-A-CNN) that requires only patients’ vital sign series and information at ICU admission for real-time ICU outcome predictions. The model is evaluated using a large real-world ICU database and outperforms state-of-the-art baselines on both ICU mortality and length-of-stay prediction tasks. Furthermore, the additive structure of the model can be used for model interpretation and analyzing which input signal is more useful for ICU outcome prediction for different patient cohorts. Our work provides an efficient tool for ICU outcome predictions, allowing healthcare providers to act promptly on patients at risk and reduce the negative impacts on patient outcomes.