Glucose Metabolism, Islet Architecture, and Genetic Homogeneity in Imprinting of [Ca2+]i and Insulin Rhythms in Mouse Islets

We reported previously that islets isolated from individual, outbred Swiss-Webster mice displayed oscillations in intracellular calcium ([Ca2+]i) that varied little between islets of a single mouse but considerably between mice, a phenomenon we termed “islet imprinting.” We have now confirmed and extended these findings in several respects. First, imprinting occurs in both inbred (C57BL/6J) as well as outbred mouse strains (Swiss-Webster; CD1). Second, imprinting was observed in NAD(P)H oscillations, indicating a metabolic component. Further, short-term exposure to a glucose-free solution, which transiently silenced [Ca2+]i oscillations, reset the oscillatory patterns to a higher frequency. This suggests a key role for glucose metabolism in maintaining imprinting, as transiently suppressing the oscillations with diazoxide, a KATP-channel opener that blocks [Ca2+]i influx downstream of glucose metabolism, did not change the imprinted patterns. Third, imprinting was not as readily observed at the level of single beta cells, as the [Ca2+]i oscillations of single cells isolated from imprinted islets exhibited highly variable, and typically slower [Ca2+]i oscillations. Lastly, to test whether the imprinted [Ca2+]i patterns were of functional significance, a novel microchip platform was used to monitor insulin release from multiple islets in real time. Insulin release patterns correlated closely with [Ca2+]i oscillations and showed significant mouse-to-mouse differences, indicating imprinting. These results indicate that islet imprinting is a general feature of islets and is likely to be of physiological significance. While islet imprinting did not depend on the genetic background of the mice, glucose metabolism and intact islet architecture may be important for the imprinting phenomenon

The transcription factor NR4A1 is essential for the development of a novel macrophage subset in the thymus

Tissue macrophages function to maintain homeostasis and regulate immune responses. While tissue macrophages derive from one of a small number of progenitor programs, the transcriptional requirements for site-specific macrophage subset development are more complex. We have identified a new tissue macrophage subset in the thymus and have discovered that its development is dependent on transcription factor NR4A1. Functionally, we find that NR4A1-dependent macrophages are critically important for clearance of apoptotic thymocytes. These macrophages are largely reduced or absent in mice lacking NR4A1, and Nr4a1-deficient mice have impaired thymocyte engulfment and clearance. Thus, NR4A1 functions as a master transcription factor for the development of this novel thymus-specific macrophage subset

Identification of an Early Unipotent Neutrophil Progenitor with Pro-tumoral Activity in Mouse and Human Bone Marrow

Neutrophils are short-lived cells that play important roles in both health and disease. Neutrophils and monocytes originate from the granulocyte monocyte progenitor (GMP) in bone marrow; however, unipotent neutrophil progenitors are not well defined. Here, we use cytometry by time of flight (CyTOF) and single-cell RNA sequencing (scRNA-seq) methodologies to identify a committed unipotent early-stage neutrophil progenitor (NeP) in adult mouse bone marrow. Importantly, we found a similar unipotent NeP (hNeP) in human bone marrow. Both NeP and hNeP generate only neutrophils. NeP and hNeP both significantly increase tumor growth when transferred into murine cancer models, including a humanized mouse model. hNeP are present in the blood of treatment-naive melanoma patients but not of healthy subjects. hNeP can be readily identified by flow cytometry and could be used as a biomarker for early cancer discovery. Understanding the biology of hNeP should allow the development of new therapeutic targets for neutrophil-related diseases, including cancer

Single-cell immune profiling reveals long-term changes in myeloid cells and identifies a novel subset of CD9(+) monocytes associated with COVID-19 hospitalization

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can result in severe immune dysfunction, hospitalization, and death. Many patients also develop long-COVID-19, experiencing symptoms months after infection. Although significant progress has been made in understanding the immune response to acute SARS-CoV-2 infection, gaps remain in our knowledge of how innate immunity influences disease kinetics and severity. We hypothesized that cytometry by time-of-flight analysis of PBMCs from healthy and infected subjects would identify novel cell surface markers and innate immune cell subsets associated with COVID-19 severity. In this pursuit, we identified monocyte and dendritic cell subsets that changed in frequency during acute SARS-CoV-2 infection and correlated with clinical parameters of disease severity. Subsets of nonclassical monocytes decreased in frequency in hospitalized subjects, yet increased in the most severe patients and positively correlated with clinical values associated with worse disease severity. CD9, CD163, PDL1, and PDL2 expression significantly increased in hospitalized subjects, and CD9 and 6-Sulfo LacNac emerged as the markers that best distinguished monocyte subsets amongst all subjects. CD9+ monocytes remained elevated, whereas nonclassical monocytes remained decreased, in the blood of hospitalized subjects at 3-4 months postinfection. Finally, we found that CD9+ monocytes functionally released more IL-8 and MCP-1 after LPS stimulation. This study identifies new monocyte subsets present in the blood of COVID-19 patients that correlate with disease severity, and links CD9+ monocytes to COVID-19 progression

A Practical Guide to Rodent Islet Isolation and Assessment

Pancreatic islets of Langerhans secrete hormones that are vital to the regulation of blood glucose and are, therefore, a key focus of diabetes research. Purifying viable and functional islets from the pancreas for study is an intricate process. This review highlights the key elements involved with mouse and rat islet isolation, including choices of collagenase, the collagenase digestion process, purification of islets using a density gradient, and islet culture conditions. In addition, this paper reviews commonly used techniques for assessing islet viability and function, including visual assessment, fluorescent markers of cell death, glucose-stimulated insulin secretion, and intracellular calcium measurements. A detailed protocol is also included that describes a common method for rodent islet isolation that our laboratory uses to obtain viable and functional mouse islets for in vitro study of islet function, beta-cell physiology, and in vivo rodent islet transplantation. The purpose of this review is to serve as a resource and foundation for successfully procuring and purifying high-quality islets for research purposes

Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks

Quantized neural networks typically require smaller memory footprints and lower computation complexity, which is crucial for efficient deployment. However, quantization inevitably leads to a distribution divergence from the original network, which generally degrades the performance. To tackle this issue, massive efforts have been made, but most existing approaches lack statistical considerations and depend on several manual configurations. In this paper, we present an adaptive-mapping quantization method to learn an optimal latent sub-distribution that is inherent within models and smoothly approximated with a concrete Gaussian Mixture (GM). In particular, the network weights are projected in compliance with the GM-approximated sub-distribution. This sub-distribution evolves along with the weight update in a co-tuning schema guided by the direct task-objective optimization. Sufficient experiments on image classification and object detection over various modern architectures demonstrate the effectiveness, generalization property, and transferability of the proposed method. Besides, an efficient deployment flow for the mobile CPU is developed, achieving up to 7.46$\times$ inference acceleration on an octa-core ARM CPU. Our codes have been publicly released at \url{https://github.com/RunpeiDong/DGMS}.Comment: Accepted at ICML 202

Interplay of Monocytes and T Lymphocytes in COVID-19 Severity

ABSTRACT The COVID-19 pandemic represents an ongoing global crisis that has already impacted over 13 million people. The responses of specific immune cell populations to the disease remain poorly defined, which hinders improvements in treatment and care management. Here, we utilized mass cytometry (CyTOF) to thoroughly phenotype peripheral myeloid cells and T lymphocytes from 30 convalescent patients with mild, moderate, and severe cases of COVID-19. We identified 10 clusters of monocytes and dendritic cells and 17 clusters of T cells. Examination of these clusters revealed that both CD14 + CD16 + intermediate and CD14 dim CD16 + nonclassical monocytes, as well as CD4 + stem cell memory T (T SCM ) cells, correlated with COVID-19 severity, coagulation factor levels, and/or inflammatory indicators. We also identified two nonclassical monocyte subsets distinguished by expression of the sugar residue 6-Sulfo LacNac (Slan). One of these subsets (Slan lo , nMo1) was depleted in moderately and severely ill patients, while the other (Slan hi , nMo2) increased with disease severity and was linked to CD4 + T effector memory (T EM ) cell frequencies, coagulation factors, and inflammatory indicators. Intermediate monocytes tightly correlated with loss of naive T cells as well as an increased abundance of effector memory T cells expressing the exhaustion marker PD-1. Our data suggest that both intermediate and non-classical monocyte subsets shape the adaptive immune response to SARS-CoV-2. In summary, our study provides both broad and in-depth characterization of immune cell phenotypes in response to COVID-19 and suggests functional interactions between distinct cell types during the disease. One Sentence Summary Use of mass cytometry on peripheral blood mononuclear cells from convalescent COVID-19 patients allows correlation of distinct monocyte and T lymphocyte subsets with clinical factors

ATP-Binding Cassette Transporter G1 Intrinsically Regulates Invariant NKT Cell Development

ATP-binding cassette transporter G1 (ABCG1) plays a role in the intracellular transport of cholesterol. Invariant NKT (iNKT) cells are a subpopulation of T lymphocytes that recognize glycolipid Ags. In this study, we demonstrate that ABCG1 regulates iNKT cell development and functions in a cell-intrinsic manner. Abcg1(-/-) mice displayed reduced frequencies of iNKT cells in thymus and periphery. Thymic iNKT cells deficient in ABCG1 had reduced membrane lipid raft content, and showed impaired proliferation and defective maturation during the early stages of development. Moreover, we found that Abcg1(-/-) mice possess a higher frequency of V beta 7(+) iNKT cells, suggesting alterations in iNKT cell thymic selection. Furthermore, in response to CD3 epsilon/CD28 stimulation, Abcg1(-/-) thymic iNKT cells showed reduced production of IL-4 but increased production of IFN-gamma. Our results demonstrate that changes in intracellular cholesterol homeostasis by ABCG1 profoundly impact iNKT cell development and function. The Journal of Immunology, 2012, 189: 5129-5138