Fluorine contamination, mobility, and risks in soils at a phosphate-gypsum waste landfill: a new analytical method and comparison with previous methods.

This study used a new X-ray fluorescence (XRF)-based analytical method with better precision and sensitivity to evaluate the fluorine concentrations in soil. It was hypothesized that the XRF method with a pellet-synthesizing procedure may effectively analyze the fluorine concentrations in soil with ease and reliability. The total fluorine concentrations determined using XRF were compared with those determined using three different types of analytical protocols-incineration/distillation, alkaline fusion, and aqua regia extraction procedures. Among the three procedures, the incineration/distillation procedure did not show reliable precision and reproducibility. In contrast, the total fluorine concentrations determined using the XRF analysis were linearly correlated with those determined using the alkaline fusion and aqua regia extraction procedures. Based on the results of the Korean waste leaching procedure and toxicity characteristics leaching procedure, the leachability of fluorine from soil and waste was not directly related to total fluorine concentrations in soil. Risk assessment also revealed that the fluorine-rich soils did not show non-carcinogenic toxic effects, despite exceeding the regulation level (800 mg/kg) in South Korea for total fluorine concentrations in soil. Our results suggest that XRF analysis in combination with the newly developed pretreatment method may be a promising alternative procedure for easily and rapidly determining the total fluorine concentration in soil. However, further efforts are needed to evaluate fluorine leachability and its associated risks in fluorine-contaminated soils.

In vivo study of newly developed albumin-conjugated urate oxidase for gout treatment.

BACKGROUND: Exogenously providing engineered Uox with enhanced half-life is one of the important urate-lowering treatments for gout. The potential of PAT101, a recombinant human albumin (rHA)-conjugated variant, was evaluated and compared as a novel gout treatment through various in vivo studies with PAT101 and competing drugs. METHODS: PAT101 was produced by site-specific conjugation of rHA and Aspergillus flavus Uox (AfUox-rHA) through clickable non-natural amino acid (frTet) and Inverse electron demand Diels-Alder (IEDDA) reaction. In vivo pharmacokinetics, efficacy tests and in vitro immunogenetic assay were performed after single or multiple doses of PAT101 and its competitors in BALB/c mice, transgenic (TG) mice, Sprague-Dawley (SD) rats, and non-human primate (NHP). RESULTS: The half-life of PAT101 in single-dose treated TG mice was more than doubled compared to pegloticase. In SD rats with 4 weeks of repeated administration of rasburicase, only 24% of Uox activity remained, whereas in PAT101, it was maintained by 86%. In the Uox KO model, the survival rate of PAT101 was comparable to that of pegloticase. In addition, human PBMC-based CD4+/CD8+ T-cell activation analysis demonstrated that PAT101 has a lower immune response compared to the original drug, rasburicase. CONCLUSION: All results suggest that this rHA-conjugated AfUox, PAT101, can be provided as a reliable source of Uox for gout treatment.

Multiparity increases the risk of diabetes by impairing the proliferative capacity of pancreatic ß cells.

Pregnancy imposes a substantial metabolic burden on women, but little is known about whether or how multiple pregnancies increase the risk of maternal postpartum diabetes. In this study, we assessed the metabolic impact of multiple pregnancies in humans and in a rodent model. Mice that underwent multiple pregnancies had increased adiposity, but their glucose tolerance was initially improved compared to those of age-matched virgin mice. Later, however, insulin resistance developed over time, but insulin secretory function and compensatory pancreatic ß cell proliferation were impaired in multiparous mice. The ß cells of multiparous mice exhibited aging features, including telomere shortening and increased expression of Cdkn2a. Single-cell RNA-seq analysis revealed that the ß cells of multiparous mice exhibited upregulation of stress-related pathways and downregulation of cellular respiration- and oxidative phosphorylation-related pathways. In humans, women who delivered more than three times were more obese, and their plasma glucose concentrations were elevated compared to women who had delivered three or fewer times, as assessed at 2 months postpartum. The disposition index, which is a measure of the insulin secretory function of ß cells, decreased when women with higher parity gained body weight after delivery. Taken together, our findings indicate that multiple pregnancies induce cellular stress and aging features in ß cells, which impair their proliferative capacity to compensate for insulin resistance.

Image quality improvement in bowtie-filter-equipped cone-beam CT using a dual-domain neural network.

BACKGROUND: The bowtie-filter in cone-beam CT (CBCT) causes spatially nonuniform x-ray beam often leading to eclipse artifacts in the reconstructed image. The artifacts are further confounded by the patient scatter, which is therefore patient-dependent as well as system-specific. PURPOSE: In this study, we propose a dual-domain network for reducing the bowtie-filter-induced artifacts in CBCT images. METHODS: In the projection domain, the network compensates for the filter-induced beam-hardening that are highly related to the eclipse artifacts. The output of the projection-domain network was used for image reconstruction and the reconstructed images were fed into the image-domain network. In the image domain, the network further reduces the remaining cupping artifacts that are associated with the scatter. A single image-domain-only network was also implemented for comparison. RESULTS: The proposed approach successfully enhanced soft-tissue contrast with much-reduced image artifacts. In the numerical study, the proposed method decreased perceptual loss and root-mean-square-error (RMSE) of the images by 84.5% and 84.9%, respectively, and increased the structure similarity index measure (SSIM) by 0.26 compared to the original input images on average. In the experimental study, the proposed method decreased perceptual loss and RMSE of the images by 87.2% and 92.1%, respectively, and increased SSIM by 0.58 compared to the original input images on average. CONCLUSIONS: We have proposed a deep-learning-based dual-domain framework to reduce the bowtie-filter artifacts and to increase the soft-tissue contrast in CBCT images. The performance of the proposed method has been successfully demonstrated in both numerical and experimental studies.

The Interplay of Adipokines and Pancreatic Beta Cells in Metabolic Regulation and Diabetes.

The interplay between adipokines and pancreatic beta cells, often referred to as the adipo-insular axis, plays a crucial role in regulating metabolic homeostasis. Adipokines are signaling molecules secreted by adipocytes that have profound effects on several physiological processes. Adipokines such as adiponectin, leptin, resistin, and visfatin influence the function of pancreatic beta cells. The reciprocal communication between adipocytes and beta cells is remarkable. Insulin secreted by beta cells affects adipose tissue metabolism, influencing lipid storage and lipolysis. Conversely, adipokines released from adipocytes can influence beta cell function and survival. Chronic obesity and insulin resistance can lead to the release of excess fatty acids and inflammatory molecules from the adipose tissue, contributing to beta cell dysfunction and apoptosis, which are key factors in developing type 2 diabetes. Understanding the complex interplay of the adipo-insular axis provides insights into the mechanisms underlying metabolic regulation and pathogenesis of metabolic disorders. By elucidating the molecular mediators involved in this interaction, new therapeutic targets and strategies may emerge to reduce the risk and progression of diseases, such as type 2 diabetes and its associated complications. This review summarizes the interactions between adipokines and pancreatic beta cells, and their roles in the pathogenesis of diabetes and metabolic diseases.

Homogenization of multi-institutional chest x-ray images in various data transformation schemes.

Purpose: Although there are several options for improving the generalizability of learned models, a data instance-based approach is desirable when stable data acquisition conditions cannot be guaranteed. Despite the wide use of data transformation methods to reduce data discrepancies between different data domains, detailed analysis for explaining the performance of data transformation methods is lacking. Approach: This study compares several data transformation methods in the tuberculosis detection task with multi-institutional chest x-ray (CXR) data. Five different data transformations, including normalization, standardization with and without lung masking, and multi-frequency-based (MFB) standardization with and without lung masking were implemented. A tuberculosis detection network was trained using a reference dataset, and the data from six other sites were used for the network performance comparison. To analyze data harmonization performance, we extracted radiomic features and calculated the Mahalanobis distance. We visualized the features with a dimensionality reduction technique. Through similar methods, deep features of the trained networks were also analyzed to examine the models' responses to the data from various sites. Results: From various numerical assessments, the MFB standardization with lung masking provided the highest network performance for the non-reference datasets. From the radiomic and deep feature analyses, the features of the multi-site CXRs after MFB with lung masking were found to be well homogenized to the reference data, whereas the others showed limited performance. Conclusions: Conventional normalization and standardization showed suboptimal performance in minimizing feature differences among various sites. Our study emphasizes the strengths of MFB standardization with lung masking in terms of network performance and feature homogenization.

Endogenous circadian reporters reveal functional differences of PERIOD paralogs and the significance of PERIOD:CK1 stable interaction.

Adverse consequences from having a faulty circadian clock include compromised sleep quality and poor performance in the short-term, and metabolic diseases and cancer in the long-term. However, our understanding of circadian disorders is limited by the incompleteness of our molecular models and our dearth of defined mutant models. Because it would be prohibitively expensive to develop live animal models to study the full range of complicated clock mechanisms, we developed PER1-luc and PER2-luc endogenous circadian reporters in a validated clock cell model, U-2 OS, where the genome can be easily manipulated, and functional consequences of mutations can be accurately studied. When major clock genes were knocked out in these cells, circadian rhythms were modulated similarly compared with corresponding mutant mice, validating the platform for genetics studies. Using these reporter cells, we uncovered critical differences between two paralogs of PER. Although PER1 and PER2 are considered redundant and either one can serve as a pacemaker alone, they were dramatically different in biochemical parameters such as stability and phosphorylation kinetics. Consistently, circadian phase was dramatically different between PER1 and PER2 knockout reporter cells. We further showed that the stable binding of casein kinase1δ/ε to PER is not required for PER phosphorylation itself, but is critical for delayed timing of phosphorylation. Our system can be used as an efficient platform to study circadian disorders associated with pathogenic mutations and their underlying molecular mechanisms.

A feasibility study on deep-neural-network-based dose-neutral dual-energy digital breast tomosynthesis.

BACKGROUND: Diagnostic performance based on x-ray breast imaging is subject to breast density. Although digital breast tomosynthesis (DBT) is reported to outperform conventional mammography in denser breasts, mass detection and malignancy characterization are often considered challenging yet. PURPOSE: As an improved diagnostic solution to the dense breast cases, we propose a dual-energy DBT imaging technique that enables breast compositional imaging at comparable scanning time and patient dose compared to the conventional single-energy DBT. METHODS: The proposed dual-energy DBT acquires projection data by alternating two different energy spectra. Then, we synthesize unmeasured projection data using a deep neural network that exploits the measured projection data and adjacent projection data obtained under the other x-ray energy spectrum. For material decomposition, we estimate partial path lengths of an x-ray through water, lipid, and protein from the measured and the synthesized projection data with the object thickness information. After material decomposition in the projection domain, we reconstruct material-selective DBT images. The deep neural network is trained with the numerical breast phantoms. A pork meat phantom is scanned with a prototype dual-energy DBT system to demonstrate the feasibility of the proposed imaging method. RESULTS: The developed deep neural network successfully synthesized missing projections. Material-selective images reconstructed from the synthesized data present comparable compositional contrast of the cancerous masses compared with those from the fully measured data. CONCLUSIONS: The proposed dual-energy DBT scheme is expected to substantially contribute to enhancing mass malignancy detection accuracy particularly in dense breasts.

Mitoribosome insufficiency in ß cells is associated with type 2 diabetes-like islet failure.

Genetic variations in mitoribosomal subunits and mitochondrial transcription factors are related to type 2 diabetes. However, the role of islet mitoribosomes in the development of type 2 diabetes has not been determined. We investigated the effects of the mitoribosomal gene on ß-cell function and glucose homeostasis. Mitoribosomal gene expression was analyzed in datasets from the NCBI GEO website (GSE25724, GSE76894, and GSE76895) and the European Nucleotide Archive (ERP017126), which contain the transcriptomes of type 2 diabetic and nondiabetic organ donors. We found deregulation of most mitoribosomal genes in islets from individuals with type 2 diabetes, including partial downregulation of CRIF1. The phenotypes of haploinsufficiency in a single mitoribosomal gene were examined using ß-cell-specific Crif1 (Mrpl59) heterozygous-deficient mice. Crif1beta+/- mice had normal glucose tolerance, but their islets showed a loss of first-phase glucose-stimulated insulin secretion. They also showed increased ß-cell mass associated with higher expression of Reg family genes. However, Crif1beta+/- mice showed earlier islet failure in response to high-fat feeding, which was exacerbated by aging. Haploinsufficiency of a single mitoribosomal gene predisposes rodents to glucose intolerance, which resembles the early stages of type 2 diabetes in humans.

Deep-learning-based projection-domain breast thickness estimation for shape-prior iterative image reconstruction in digital breast tomosynthesis.

BACKGROUND: Digital breast tomosynthesis (DBT) is a technique that can overcome the shortcomings of conventional X-ray mammography and can be effective for the early screening of breast cancer. The compression of the breast is essential during the DBT imaging. However, since the periphery of the breast cannot be compressed to a constant value, nonuniformity of thickness and in-plane shape variation happen. These cause inconvenience in diagnosis, scatter correction, and breast density estimation. PURPOSE: In this study, we propose a deep-learning-based methodology for projection-domain breast thickness estimation and demonstrate a shape-prior iterative DBT image reconstruction. METHODS: We prepared the Euclidean distance map, the thickness map, and the thickness corrected image of the simulated breast projections for thickness and shape estimation. Each pixel of the Euclidean distance map denotes a distance to the closest skin-line. The thickness map is defined as a conceptual projection of ideal breast support that differentiates the inner and outer regions of the breast phantom. The thickness projection map thus represents the X-ray path lengths of a homogeneous breast phantom. We generated the thickness corrected image by dividing the projection image by the thickness map in a pixel-wise manner. We developed a convolutional neural network for thickness estimation and correction. The network utilizes a projection image and a Euclidean distance image together as a dual input. An estimated breast thickness map is then used for constructing the breast shape mask by use of the discrete algebraic reconstruction technique. RESULTS: The proposed network effectively corrected the breast thickness in various simulation situations. Low normalized root-mean-squared error (1.976%) and high structural similarity (99.997%) indicated a good agreement between the network-generated thickness corrected image and the ground truth image. Compared to the existing methods and simple single-input network, the proposed method showed outperformance in breast thickness estimation and accordingly in breast shape recovery for various numerical phantoms without provoking any significant artifact. We have demonstrated that the uniformity of voxel value has improved by the inclusion of a shape prior for the iterative DBT reconstruction. CONCLUSIONS: We presented a novel deep-learning-based breast thickness correction and a shape reconstruction method. This approach to estimating the true thickness map and the shape of the breast undergoing compression can benefit various fields such as improvement of diagnostic breast images, scatter correction, material decomposition, and breast density estimation.

Lysosomal Ca2+-mediated TFEB activation modulates mitophagy and functional adaptation of pancreatic ß-cells to metabolic stress.

Although autophagy is critical for pancreatic ß-cell function, the role and mechanism of mitophagy in ß-cells are unclear. We studied the role of lysosomal Ca2+ in TFEB activation by mitochondrial or metabolic stress and that of TFEB-mediated mitophagy in ß-cell function. Mitochondrial or metabolic stress induced mitophagy through lysosomal Ca2+ release, increased cytosolic Ca2+ and TFEB activation. Lysosomal Ca2+ replenishment by ER- > lysosome Ca2+ refilling was essential for mitophagy. ß-cell-specific Tfeb knockout (TfebΔß-cell) abrogated high-fat diet (HFD)-induced mitophagy, accompanied by increased ROS and reduced mitochondrial cytochrome c oxidase activity or O2 consumption. TfebΔß-cell mice showed aggravation of HFD-induced glucose intolerance and impaired insulin release. Metabolic or mitochondrial stress induced TFEB-dependent expression of mitophagy receptors including Ndp52 and Optn, contributing to the increased mitophagy. These results suggest crucial roles of lysosomal Ca2+ release coupled with ER- > lysosome Ca2+ refilling and TFEB activation in mitophagy and maintenance of pancreatic ß-cell function during metabolic stress.

Three-compartment-breast (3CB) prior-guided diffuse optical tomography based on dual-energy digital breast tomosynthesis (DBT).

Diffuse optical tomography (DOT) is a non-invasive functional imaging modality that uses near-infrared (NIR) light to measure the oxygenation state and the concentration of hemoglobin. By complementarily using DOT with other anatomical imaging modalities, physicians can diagnose more accurately through additional functional image information. In breast imaging, diagnosis of dense breasts is often challenging because the bulky fibrous tissues may hinder the correct tumor characterization. In this work, we proposed a three-compartment-breast (3CB) decomposition-based prior-guided optical tomography for enhancing DOT image quality. We conjectured that the 3CB prior would lead to improvement of the spatial resolution and also of the contrast of the reconstructed tumor image, particularly for the dense breasts. We conducted a Monte-Carlo simulation to acquire dual-energy X-ray projections of a realistic 3D numerical breast phantom and performed digital breast tomosynthesis (DBT) for setting up a 3CB model. The 3CB prior was then used as a structural guide in DOT image reconstruction. The proposed method resulted in the higher spatial resolution of the recovered tumor even when the tumor is surrounded by the fibroglandular tissues compared with the typical two-composition-prior method or the standard Tikhonov regularization method.

Auraptene Enhances Junction Assembly in Cerebrovascular Endothelial Cells by Promoting Resilience to Mitochondrial Stress through Activation of Antioxidant Enzymes and mtUPR.

Junctional proteins in cerebrovascular endothelial cells are essential for maintaining the barrier function of the blood-brain barrier (BBB), thus protecting the brain from the infiltration of pathogens. The present study showed that the potential therapeutic natural compound auraptene (AUR) enhances junction assembly in cerebrovascular endothelial cells by inducing antioxidant enzymes and the mitochondrial unfolded protein response (mtUPR). Treatment of mouse cerebrovascular endothelial cells with AUR enhanced the expression of junctional proteins, such as occludin, zonula occludens-1 (ZO-1) and vascular endothelial cadherin (VE-cadherin), by increasing the levels of mRNA encoding antioxidant enzymes. AUR treatment also resulted in the depolarization of mitochondrial membrane potential and activation of mtUPR. The ability of AUR to protect against ischemic conditions was further assessed using cells deprived of oxygen and glucose. Pretreatment of these cells with AUR protected against damage to junctional proteins, including occludin, claudin-5, ZO-1 and VE-cadherin, accompanied by a stress resilience response regulated by levels of ATF5, LONP1 and HSP60 mRNAs. Collectively, these results indicate that AUR promotes resilience against oxidative stress and improves junction assembly, suggesting that AUR may help maintain intact barriers in cerebrovascular endothelial cells.

A synthesizing method for signal-enhanced and artifact-reduced mammogram from digital breast tomosynthesis.

In this paper, we propose a method for compositing a synthetic mammogram (SM) from digital breast tomosynthesis (DBT) slice images. The method consists of four parts. The first part is image reconstruction of DBT from the acquired projection data by use of backprojection-filtration (BPF) algorithm with a low-frequency boosting scheme and a high-density object reduction technique embedded. Also, a few expectation-maximization (EM) iterations have been additively implemented on top of the BPF algorithm to prepare a separate volume image. The second is generating three kinds of intermediate SMs. A forward projection image and a linear structure weighted forward projection image were computed. A maximum intensity projection of the BPF reconstructed volume image was also generated. The third part is integrating three intermediate SMs. The last is the post-processing of the SM. We scanned two physical phantoms in a prototype DBT scanner, and we have evaluated the performance of the proposed method. We also performed a clinical data study by use of 30 patient data who went through both DBT and digital mammography (DM) scans. Three experienced radiologists have read the SMs generated by several component techniques and also read the DM of each patient, and evaluated the generated SMs. The experimental phantom study and the clinical reader study consistently demonstrated the usefulness of the proposed method.

Development of digital breast tomosynthesis and diffuse optical tomography fusion imaging for breast cancer detection.

Diffuse optical tomography (DOT) non-invasively measures the functional characteristics of breast lesions using near infrared light to probe tissue optical properties. This study aimed to evaluate a new digital breast tomosynthesis (DBT)/DOT fusion imaging technique and obtain preliminary data for breast cancer detection. Twenty-eight women were prospectively enrolled and underwent both DBT and DOT examinations. DBT/DOT fusion imaging was created after acquisition of both examinations. Two breast radiologists analyzed DBT and DOT images independently, and then finally evaluated the fusion images. The diagnostic performance of each reading session was compared and interobserver agreement was assessed. The technical success rate was 96.4%, with one failure due to an error during DOT data storage. Among the 27 women finally included in the analysis, 13 had breast cancer. The areas under the receiver operating characteristic curve (AUCs) for DBT were 0.783 and 0.854 for readers 1 and 2, respectively. DOT showed comparable diagnostic performance to DBT for both readers. The AUCs were significantly improved (P = 0.004) when the DBT/DOT fusion images were used. Interobserver agreements were highest for the DBT/DOT fusion images. In conclusion, this study suggests that DBT/DOT fusion imaging technique appears to be a promising tool for breast cancer diagnosis.

Lactation improves pancreatic ß cell mass and function through serotonin production.

Pregnancy imposes a substantial metabolic burden on women through weight gain and insulin resistance. Lactation reduces the risk of maternal postpartum diabetes, but the mechanisms underlying this benefit are unknown. Here, we identified long-term beneficial effects of lactation on ß cell function, which last for years after the cessation of lactation. We analyzed metabolic phenotypes including ß cell characteristics in lactating and non-lactating humans and mice. Lactating and non-lactating women showed comparable glucose tolerance at 2 months after delivery, but after a mean of 3.6 years, glucose tolerance in lactated women had improved compared to non-lactated women. In humans, the disposition index, a measure of insulin secretory function of ß cells considering the degree of insulin sensitivity, was higher in lactated women at 3.6 years after delivery. In mice, lactation improved glucose tolerance and increased ß cell mass at 3 weeks after delivery. Amelioration of glucose tolerance and insulin secretion were maintained up to 4 months after delivery in lactated mice. During lactation, prolactin induced serotonin production in ß cells. Secreted serotonin stimulated ß cell proliferation through serotonin receptor 2B in an autocrine and paracrine manner. In addition, intracellular serotonin acted as an antioxidant to mitigate oxidative stress and improved ß cell survival. Together, our results suggest that serotonin mediates the long-term beneficial effects of lactation on female metabolic health by increasing ß cell proliferation and reducing oxidative stress in ß cells.

Subarachnoid Contrast Accumulation and Alberta Stroke Program Early Computed Tomography Score Applied to Contrast Accumulation After Thrombectomy as Predictors of Symptomatic Hemorrhage.

BACKGROUND: Areas of contrast accumulation (CA) are commonly found on routine computed tomography (CT) performed immediately after thrombectomy. In the present study, we investigated the types of CA associated with the different outcomes, including symptomatic intracranial hemorrhage (sICH). METHODS: The present study analyzed the data from 145 patients with anterior circulation stroke who had undergone non-contrast-enhanced conventional CT immediately after thrombectomy. The following variables were investigated: collateral status, failure of recanalization, Alberta stroke program early CT score (ASPECTS) applied to CA lesions and diffusion-weighted imaging infarct lesions, and sICH. RESULTS: Of the 145 patients, 102 (70.3%) had CA lesions. All types of CA (any CA, cortical CA, subarachnoid CA, and CA ASPECTS) were significantly associated with poor outcomes (modified Rankin scale score >2). In particular, subarachnoid CA (odds ratio, 23.994; 95% confidence interval, 4.696-122.589) and CA ASPECTS (odds ratio, 0.550; 95% confidence interval, 0.404-0.750) were independently associated with sICH. Patients with subarachnoid CA had poorer collateral status and a larger final infarct size than those without subarachnoid CA, although the initial National Institutes of Health stroke scale score and recanalization rate were comparable between the 2 groups. A CA ASPECTS of ≤5 predicted sICH with a sensitivity of 66.7% and a specificity of 92.6% (area under the curve, 0.854). CONCLUSIONS: Our data suggest that a subarachnoid CA location and CA ASPECTS are predictors of sICH. In particular, a subarachnoid location of CA might signify damage of the subarachnoid collateral arteries, leading to a larger infarct.

Serotonin Regulates Adult ß-Cell Mass by Stimulating Perinatal ß-Cell Proliferation.

A sufficient ß-cell mass is crucial for preventing diabetes, and perinatal ß-cell proliferation is important in determining the adult ß-cell mass. However, it is not yet known how perinatal ß-cell proliferation is regulated. Here, we report that serotonin regulates ß-cell proliferation through serotonin receptor 2B (HTR2B) in an autocrine/paracrine manner during the perinatal period. In ß-cell-specific Tph1 knockout (Tph1 ßKO) mice, perinatal ß-cell proliferation was reduced along with the loss of serotonin production in ß-cells. Adult Tph1 ßKO mice exhibited glucose intolerance with decreased ß-cell mass. Disruption of Htr2b in ß-cells also resulted in decreased perinatal ß-cell proliferation and glucose intolerance in adulthood. Growth hormone (GH) was found to induce serotonin production in ß-cells through activation of STAT5 during the perinatal period. Thus, our results indicate that GH-GH receptor-STAT5-serotonin-HTR2B signaling plays a critical role in determining the ß-cell mass by regulating perinatal ß-cell proliferation, and defects in this pathway affect metabolic phenotypes in adults.

PRMT1 Is Required for the Maintenance of Mature ß-Cell Identity.

Loss of functional ß-cell mass is an essential feature of type 2 diabetes, and maintaining mature ß-cell identity is important for preserving a functional ß-cell mass. However, it is unclear how ß-cells achieve and maintain their mature identity. Here we demonstrate a novel function of protein arginine methyltransferase 1 (PRMT1) in maintaining mature ß-cell identity. Prmt1 knockout in fetal and adult ß-cells induced diabetes, which was aggravated by high-fat diet-induced metabolic stress. Deletion of Prmt1 in adult ß-cells resulted in the immediate loss of histone H4 arginine 3 asymmetric dimethylation (H4R3me2a) and the subsequent loss of ß-cell identity. The expression levels of genes involved in mature ß-cell function and identity were robustly downregulated as soon as Prmt1 deletion was induced in adult ß-cells. Chromatin immunoprecipitation sequencing and assay for transposase-accessible chromatin sequencing analyses revealed that PRMT1-dependent H4R3me2a increases chromatin accessibility at the binding sites for CCCTC-binding factor (CTCF) and ß-cell transcription factors. In addition, PRMT1-dependent open chromatin regions may show an association with the risk of diabetes in humans. Together, our results indicate that PRMT1 plays an essential role in maintaining ß-cell identity by regulating chromatin accessibility.