a b s t r a c tElectronic cigarettes (EC) and refill fluids are distributed with little information on their pre-and postnatal health effects. This study compares the cytotoxicity of EC refill fluids using embryonic and adult cells and examines the chemical characteristics of refill fluids using HPLC. Refill solutions were tested on human embryonic stem cells (hESC), mouse neural stem cells (mNSC), and human pulmonary fibroblasts (hPF) using the MTT assay, and NOAELs and IC 50 s were determined from dose-response curves. Spectral analysis was performed when products of the same flavor had different MTT outcomes. hESC and mNSC were generally more sensitive to refill solutions than hPF. All products from one company were cytotoxic to hESC and mNSC, but non-cytotoxic to hPF. Cytotoxicity was not due to nicotine, but was correlated with the number and concentration of chemicals used to flavor fluids. Additional studies are needed to fully assess the prenatal effect of refill fluids.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

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This article is the work product of the Continuous Ketone Monitoring Consensus Panel, which was organized by Diabetes Technology Society and met virtually on April 20, 2021. The panel consisted of 20 US-based experts in the use of diabetes technology, representing adult endocrinology, pediatric endocrinology, advanced practice nursing, diabetes care and education, clinical chemistry, and bioengineering. The panelists were from universities, hospitals, freestanding research institutes, government, and private practice. Panelists reviewed the medical literature pertaining to ten topics: (1) physiology of ketone production, (2) measurement of ketones, (3) performance of the first continuous ketone monitor (CKM) reported to be used in human trials, (4) demographics and epidemiology of diabetic ketoacidosis (DKA), (5) atypical hyperketonemia, (6) prevention of DKA, (7) non-DKA states of fasting ketonemia and ketonuria, (8) potential integration of CKMs with pumps and automated insulin delivery systems to prevent DKA, (9) clinical trials of CKMs, and (10) the future of CKMs. The panelists summarized the medical literature for each of the ten topics in this report. They also developed 30 conclusions (amounting to three conclusions for each topic) about CKMs and voted unanimously to adopt the 30 conclusions. This report is intended to support the development of safe and effective continuous ketone monitoring and to apply this technology in ways that will benefit people with diabetes.

1Among the hundreds of receptor-like kinases (RLKs) in plants, the brassinosteroid (BR) hormone 2 receptor BR-INSENSITIVE 1 (BRI1) and the immunity receptor FLAGELLIN SENSING 2 3 (FLS2) share a common co-receptor kinase, but lead to distinct growth and immunity responses, 4 respectively. Here we show that the BSU1 family of phosphatases, known to mediate BR 5 inactivation of GSK3-like kinases, also mediate flagellin-FLS2 signaling to the MAP kinases, 6 through different phosphocodes. Flagellin treatment induced phosphorylation of BSU1 7 phosphatase at serine-251 (S251) located in the N-terminal kelch-repeat domain. The bsu 8 quadruple mutant (bsu-q), with loss or compromised function of all four BSU family members, 9 showed defects in flagellin-triggered MAP kinase activation. The Botrytis-induced kinase 1 10 (BIK1), a substrate of FLS2, phosphorylated BSU1 at S251 in a flagellin-dependent manner. 11Mutation of S251 to alanine in BSU1 reduced its phosphorylation by BIK1, interaction with 12 MEKK1 and ability to restore flagellin-induced MAP kinase activation of the bsu quadruple 13 mutant, without affecting its ability to activate BR-dependent growth. Our results demonstrate that 14 BSU1 acts as a substrate of BIK1 downstream of FLS2 in the innate immunity pathway, in addition 15 to its role in the BR pathway. Our results suggest that different RLKs sharing downstream 16 components may maintain signaling specificity through phosphocodes in higher plants. 17 18 Text 19The Arabidopsis genome encodes hundreds of receptor-like kinases (RLKs), which perceive 20 diverse extracellular signals and trigger distinct cellular responses such as growth, differentiation, 21 and immunity. The mechanisms that ensure specificity of RLK signal transduction are not fully 22 understood. Among over two hundred leucine-rich repeat receptor-like kinases (LRR-RLK) in Arabidopsis 1 , the brassinosteroid (BR) receptor BR-INSENSITIVE1 (BRI1) and the flagellin 1 receptor FLAGELLIN SENSING 2 (FLS2) have been most extensively studied 2, 3 . BR binding to 2 BRI1 triggers its association with and activation by the co-receptor BRI1-ASSOCIATED 3 KINASE1 (BAK1) 4, 5 . BRI1 in turn phosphorylates the BR-SIGNALING KINASE (BSK) and 4 CONSTITUTIVE DIFFERENTIAL GROWTH 1 (CDG1) family of receptor-like cytoplasmic 5 kinases (RLCKs), to activate the BRI1-SUPRESSOR1 (BSU1) family of phosphatases 6, 7 , which 6 dephosphorylate and inactivate the GSK3-like kinases, leading to PP2A-mediated 7 dephosphorylation of the BZR1 family of transcription factors and activation of growth responses 8, 8 9 . Similarly, flagellin, a pathogen associated molecular pattern (PAMP), activates FLS2 by 9 inducing association with the BAK1 co-receptor 10 , and downstream signal transduction also 10 involves RLCKs 11, 12 . Members of the RLCK VII subfamily such as Botrytis-induced kinase 1 11 (BIK1) and PBS1-LIKE (PBL) kinases lead to activation of MAP kinases 13, 14 . There is evidence 12 that BIK1 plays a role in BR signaling, and BSKs are also involved in FLS2 signaling [15][1...