Erratum. Consensus Guidance for Monitoring Individuals With Islet Autoantibody-Positive Pre-Stage 3 Type 1 Diabetes. Diabetes Care 2024;47:1276-1298.

In the article cited above, incorrect affiliation information was given for author Linda A. DiMeglio. The correct affiliation for Linda A. DiMeglio is Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN. The online version of the article (https://doi.org/10.2337/dci24-0042) has been updated to correct the error.

Gut microbial changes associated with obesity in youth with type 1 diabetes: a Pilot Study.

CONTEXT: Obesity is prevalent in type 1 diabetes (T1D) and is problematic with higher risk for diabetes complications. It is unknown to what extent gut microbiome changes are associated with obesity and T1D. OBJECTIVE: To describe the gut microbiome and microbial metabolite changes associated with obesity in T1D. We hypothesized significant gut microbial and metabolite differences in lean T1D youth (BMI: 5-<85%) vs. those with obesity (BMI: ≥95%). METHODS: We analyzed stool samples for gut microbial (using metagenomic shotgun sequencing) and short-chain fatty acid (SCFA) differences in lean (n=27) and obese (n=21) T1D youth in a pilot study. The mean±SD age was 15.3±2.2yrs, A1c 7.8±1.3%, diabetes duration 5.1±4.4yrs, 42.0% females, and 94.0% were White. RESULTS: Bacterial community composition showed between sample diversity differences (ß-diversity) by BMI group (p=0.013). There was a higher ratio of Prevotella to Bacteroides in the obese group (p=0.0058). There was a differential distribution of significantly abundant taxa in either the lean or obese groups, including increased relative abundance of Prevotella copri, among other taxa in the obese group. Functional profiling showed an upregulation of branched chain amino acid (BCAA) biosynthesis in the obese group and upregulation of BCAA degradation, tyrosine metabolism and secondary bile acid biosynthesis in the lean group. Stool SCFAs were higher in the obese versus the lean group (p<0.05 for all). CONCLUSIONS: Our findings identify a gut microbiome and microbial metabolite signature associated with obesity in T1D. These findings could help identify gut microbiome targeted therapies to manage obesity in T1D.

Consensus Guidance for Monitoring Individuals With Islet Autoantibody-Positive Pre-Stage 3 Type 1 Diabetes.

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programs are being increasingly emphasized. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk for (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in nonspecialized settings. To inform this monitoring, JDRF, in conjunction with international experts and societies, developed consensus guidance. Broad advice from this guidance includes the following: 1) partnerships should be fostered between endocrinologists and primary care providers to care for people who are IAb+; 2) when people who are IAb+ are initially identified, there is a need for confirmation using a second sample; 3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; 4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; 5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and 6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasizes significant unmet needs for further research on early-stage type 1 diabetes to increase the rigor of future recommendations and inform clinical care.

Decontamination of Chlorpyrifos Residue in Soil by Using Mentha piperita (Lamiales: Lamiaceae) for Phytoremediation and Two Bacterial Strains.

This study utilizes Mentha piperita (MI) for the first time to investigate the uptake and translocation of chlorpyrifos (CPF; 10 µg g-1) from soil, introducing a new approach to improve the efficacy of this technique, which includes using biosurfactants (Bacillus subtilis and Pseudomonas aeruginosa) at 107 CFU/mL to degrade CPF under greenhouse conditions. Moreover, antioxidant enzymes, including superoxide dismutase (SOD) and peroxidase (Prx), and oxidative stress due to hydrogen peroxide (H2O2) and malondialdehyde (MDA) in MI roots and leaves were evaluated under CPF stress. Our results demonstrated that amending soil with MI and B. subtilis followed by P. aeruginosa significantly reduced CPF levels in the soil (p > 0.05) and enhanced CPF concentrations in MI roots and leaves after 1, 3, 7, 10, and 14 days of the experiment. Furthermore, CPF showed its longest half-life (t1/2) in soil contaminated solely with CPF, lasting 15.36 days. Conversely, its shortest half-life occurred in soil contaminated with CPF and treated with MI along with B. subtilis, lasting 4.65 days. Soil contaminated with CPF and treated with MI and P. aeruginosa showed a half-life of 7.98 days. The half-life (t1/2) of CPF-contaminated soil with MI alone was 11.41 days. A batch equilibrium technique showed that B. subtilis is better than P. aeruginosa for eliminating CPF from soil in In vitro experiments. Notably, CPF-polluted soil treated with coadministration of MI and the tested bacteria improved the activities of SOD and Prx and reduced H2O2 and MDA compared with CPF-polluted soil treated with MI alone. Our findings demonstrated that using B. subtilis and P. aeruginosa as biosurfactants to augment phytoremediation represents a commendable strategy for enhancing the remediation of CPF contamination in affected sites while reducing the existence of harmful pesticide remnants in crop plants.

Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes.

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk of (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb+; (2) when people who are IAb+ are initially identified there is a need for confirmation using a second sample; (3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care.

Safety and effects of acetylated and butyrylated high amylose maize starch in recently diagnosed youths with type 1 diabetes; a Pilot Study.

Acetylated and butyrylated high amylose starch (HAMS-AB) is a prebiotic shown to be effective in type 1 diabetes (T1D) prevention in mouse models and is safe in adults with established T1D. HAMS-AB alters the gut microbiome profile with increased bacterial fermenters that produce short chain fatty acids (SCFAs) with anti-inflammatory and immune-modulatory effects. We performed a pilot study using a cross-over design to assess the safety and efficacy of 4 weeks of oral HAMS-AB consumption by recently diagnosed (< 2 years of diagnosis) youths with T1D. Seven individuals completed the study. The mean±SD age was 15.0±1.2 years, diabetes duration 19.5±6.3 months, 5/7 were female and 4/7 were White, all with a BMI of < 85th%. The prebiotic was safe. Following prebiotic intake, gut microbiome changes were seen, including a notable increase in the relative abundance of fermenters such as Bifidobacterium and Faecalibacterium. Treatment was also associated with changes in bacterial functional pathways associated with either improved energy metabolism (upregulation of tyrosine metabolism) or anti-inflammatory effects (reduced geraniol degradation). There were no differences in stool SCFA levels. Plasma metabolites associated with improved glycemia, such as hippurate, were significantly increased after treatment and there were positive and significant changes in the immune regulatory function of mucosal associated invariant T cells. There was a significant decrease in the area under the curve glucose but not C-peptide, as measured during a mixed meal tolerance testing, following the prebiotic consumption. In summary, the prebiotic HAMS-AB was safe in adolescents with T1D and showed promising effects on the gut microbiome composition, function and immune regulatory function.

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review.

BACKGROUND: Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies. METHODS: We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment. RESULTS: Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation. CONCLUSIONS: Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.

Islet autoantibodies are markers found in the blood when insulin-producing cells in the pancreas become damaged and can be used to predict future development of type 1 diabetes. We evaluated published literature to determine whether characteristics of islet antibodies (type, levels, numbers) could improve prediction and help understand differences in how individuals with type 1 diabetes respond to treatments. We found existing evidence shows that islet autoantibody type and number are most useful to predict disease progression before diagnosis. In addition, the age when islet autoantibodies first appear strongly influences rate of progression. These findings provide important information for patients and care providers on how islet autoantibodies can be used to understand future type 1 diabetes development and to identify individuals who have the potential to benefit from intervention or prevention therapy.

Early Metabolic Endpoints Identify Persistent Treatment Efficacy in Recent-Onset Type 1 Diabetes Immunotherapy Trials.

OBJECTIVE: Mixed-meal tolerance test-stimulated area under the curve (AUC) C-peptide at 12-24 months represents the primary end point for nearly all intervention trials seeking to preserve ß-cell function in recent-onset type 1 diabetes. We hypothesized that participant benefit might be detected earlier and predict outcomes at 12 months posttherapy. Such findings would support shorter trials to establish initial efficacy. RESEARCH DESIGN AND METHODS: We examined data from six Type 1 Diabetes TrialNet immunotherapy randomized controlled trials in a post hoc analysis and included additional stimulated metabolic indices beyond C-peptide AUC. We partitioned the analysis into successful and unsuccessful trials and analyzed the data both in the aggregate as well as individually for each trial. RESULTS: Among trials meeting their primary end point, we identified a treatment effect at 3 and 6 months when using C-peptide AUC (P = 0.030 and P < 0.001, respectively) as a dynamic measure (i.e., change from baseline). Importantly, no such difference was seen in the unsuccessful trials. The use of C-peptide AUC as a 6-month dynamic measure not only detected treatment efficacy but also suggested long-term C-peptide preservation (R2 for 12-month C-peptide AUC adjusted for age and baseline value was 0.80, P < 0.001), and this finding supported the concept of smaller trial sizes down to 54 participants. CONCLUSIONS: Early dynamic measures can identify a treatment effect among successful immune therapies in type 1 diabetes trials with good long-term prediction and practical sample size over a 6-month period. While external validation of these findings is required, strong rationale and data exist in support of shortening early-phase clinical trials.

Comparisons of Metabolic Measures to Predict T1D vs Detect a Preventive Treatment Effect in High-Risk Individuals.

CONTEXT: Metabolic measures are frequently used to predict type 1 diabetes (T1D) and to understand effects of disease-modifying therapies. OBJECTIVE: Compare metabolic endpoints for their ability to detect preventive treatment effects and predict T1D. METHODS: Six-month changes in metabolic endpoints were assessed for (1) detecting treatment effects by comparing placebo and treatment arms from the randomized controlled teplizumab prevention trial, a multicenter clinical trial investigating 14-day intravenous teplizumab infusion and (2) predicting T1D in the TrialNet Pathway to Prevention natural history study. For each metabolic measure, t-Values from t tests for detecting a treatment effect were compared with chi-square values from proportional hazards regression for predicting T1D. Participants in the teplizumab prevention trial and participants in the Pathway to Prevention study selected with the same inclusion criteria used for the teplizumab trial were studied. RESULTS: Six-month changes in glucose-based endpoints predicted diabetes better than C-peptide-based endpoints, yet the latter were better at detecting a teplizumab effect. Combined measures of glucose and C-peptide were more balanced than measures of glucose alone or C-peptide alone for predicting diabetes and detecting a teplizumab effect. CONCLUSION: The capacity of a metabolic endpoint to detect a treatment effect does not necessarily correspond to its accuracy for predicting T1D. However, combined glucose and C-peptide endpoints appear to be effective for both predicting diabetes and detecting a response to immunotherapy. These findings suggest that combined glucose and C-peptide endpoints should be incorporated into the design of future T1D prevention trials.

Gut microbial changes associated with obesity in youth with type 1 diabetes.

Obesity is increasingly prevalent in type 1 diabetes (T1D) and is associated with management problems and higher risk for diabetes complications. Gut microbiome changes have been described separately in each of T1D and obesity, however, it is unknown to what extent gut microbiome changes are seen when obesity and T1D concomitantly occur. OBJECTIVE: To describe the gut microbiome and microbial metabolite changes associated with obesity in T1D. We hypothesized significant gut microbial and metabolite differences between T1D youth who are lean (BMI: 5-<85%) vs. those with obesity (BMI: ≥95%). METHODS: We analyzed stool samples for gut microbial (using metagenomic shotgun sequencing) and short-chain fatty acid (SCFA) metabolite differences in lean (n=27) and obese (n=21) T1D youth. The mean±SD age was 15.3±2.2yrs, A1c 7.8±1.3%, diabetes duration 5.1±4.4yrs, 42.0% females, and 94.0% were White. Linear discriminant analysis (LDA) effect size (LEfSe) was used to identify taxa that best discriminated between the BMI groups. RESULTS: Bacterial community composition showed differences in species type (ß-diversity) by BMI group (p=0.013). At the genus level, there was a higher ratio of Prevotella to Bacteroides in the obese group (p=0.0058). LEfSe analysis showed a differential distribution of significantly abundant taxa in either the lean or obese groups, including increased relative abundance of Prevotella copri , among other taxa in the obese group. Functional profiling showed that pathways associated with decreased insulin sensitivity were upregulated in the obese group. Stool SCFAs (acetate, propionate and butyrate) were higher in the obese compared to the lean group (p<0.05 for all). CONCLUSIONS: Our findings identify gut microbiome, microbial metabolite and functional pathways differences associated with obesity in T1D. These findings could be helpful in identifying gut microbiome targeted therapies to manage obesity in T1D.

Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review.

BACKGROUND: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. METHODS: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. RESULTS: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. CONCLUSIONS: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

Type 1 diabetes (T1D) is a condition that results from the destruction of a type of cell in the pancreas that produces the hormone insulin, leading to lifelong dependence on insulin injections. T1D prevention remains a challenging goal, largely due to the immense variability in disease processes and progression. Therapies tested to date in medical research settings (clinical trials) work only in a subset of individuals, highlighting the need for more tailored prevention approaches. We reviewed clinical trials of therapies targeting the disease process in T1D. While the overall quality of trials was high, studies testing individual features affecting responses to treatments were low. This review reveals an important need to carefully plan high-quality analyses of features that affect treatment response in T1D, to ensure that tailored approaches may one day be applied to clinical practice.

Hydroxychloroquine in Stage 1 Type 1 Diabetes.

OBJECTIVE: Innate immune responses may be involved in the earliest phases of type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: To test whether blocking innate immaune cells modulated progression of the disease, we randomly assigned 273 individuals with stage 1 T1D to treatment with hydroxychloroquine (n = 183; 5 mg/kg per day to a maximum of 400 mg) or placebo (n = 90) and assessed whether hydroxychloroquine treatment delayed or prevented progression to stage 2 T1D (i.e., two or more islet autoantibodies with abnormal glucose tolerance). RESULTS: After a median follow-up of 23.3 months, the trial was stopped prematurely by the data safety monitoring board because of futility. There were no safety concerns in the hydroxychloroquine arm, including in annual ophthalmologic examinations. Preplanned secondary analyses showed a transient decrease in the glucose average area under the curve to oral glucose in the hydroxychloroquine-treated arm at month 6 and reduced titers of anti-GAD and anti-insulin autoantibodies and acquisition of positive autoantibodies in the hydroxychloroquine arm (P = 0.032). CONCLUSIONS: We conclude that hydroxychloroquine does not delay progression to stage 2 T1D in individuals with stage 1 disease. Drug treatment reduces the acquisition of additional autoantibodies and the titers of autoantibodies to GAD and insulin.

Evaluating the effect of prebiotics on the gut microbiome profile and ß cell function in youth with newly diagnosed type 1 diabetes: protocol of a pilot randomized controlled trial.

INTRODUCTION: Data show that disturbances in the gut microbiota play a role in glucose homeostasis, type 1 diabetes (T1D) risk and progression. The prebiotic high amylose maize starch (HAMS) alters the gut microbiome profile and metabolites favorably with an increase in bacteria producing short chain fatty acids (SCFAs) that have significant anti-inflammatory effects. HAMS also improves glycemia, insulin sensitivity, and secretion in healthy non-diabetic adults. Additionally, a recent study testing an acetylated and butyrylated form of HAMS (HAMS-AB) that further increases SCFA production prevented T1D in a rodent model without adverse safety effects. The overall objective of this human study will be to assess how daily HAMS-AB consumption impacts the gut microbiome profile, SCFA production, ß cell heath, function, and glycemia as well as immune responses in newly diagnosed T1D youth. METHODS AND ANALYSIS: We hypothesize that HAMS-AB intake will improve the gut microbiome profile, increase SCFA production, improve ß cell health, function and glycemia as well as modulate the immune system. We describe here a pilot, randomized crossover trial of HAMS-AB in 12 newly diagnosed T1D youth, ages 11-17 years old, with residual ß cell function. In Aim 1, we will determine the effect of HAMS-AB on the gut microbiome profile and SCFA production; in Aim 2, we will determine the effect of HAMS-AB on ß cell health, function and glycemia; and in Aim 3, we will determine the peripheral blood effect of HAMS-AB on frequency, phenotype and function of specific T cell markers. Results will be used to determine the effect-size estimate of using HAMS-AB. We anticipate beneficial effects from a simple, inexpensive, and safe dietary approach. ETHICS AND DISSEMINATION: The Institutional Review Board at Indiana University approved the study protocol. The findings of this trial will be submitted to a peer-reviewed pediatric journal. Abstracts will be submitted to relevant national and international conferences. TRIAL REGISTRATION: NCT04114357; Pre-results.

Aspect-based classification of vaccine misinformation: a spatiotemporal analysis using Twitter chatter.

BACKGROUND: The spread of misinformation of all types threatens people's safety and interrupts resolutions. COVID-19 vaccination has been a widely discussed topic on social media platforms with numerous misleading and fallacious information. This false information has a critical impact on the safety of society as it prevents many people from taking the vaccine, decelerating the world's ability to go back to normal. Therefore, it is vital to analyze the content shared on social media platforms, detect misinformation, identify aspects of misinformation, and efficiently represent related statistics to combat the spread of misleading information about the vaccine. This paper aims to support stakeholders in decision-making by providing solid and current insights into the spatiotemporal progression of the common misinformation aspects of the various available vaccines. METHODS: Approximately 3800 tweets were annotated into four expert-verified aspects of vaccine misinformation obtained from reliable medical resources. Next, an Aspect-based Misinformation Analysis Framework was designed using the Light Gradient Boosting Machine (LightGBM) model, which is one of the most advanced, fast, and efficient machine learning models to date. Based on this dataset, spatiotemporal statistical analysis was performed to infer insights into the progression of aspects of vaccine misinformation among the public. Finally, the Pearson correlation coefficient and p-values are calculated for the global misinformation count against the vaccination counts of 43 countries from December 2020 until July 2021. RESULTS: The optimized classification per class (i.e., per an aspect of misinformation) accuracy was 87.4%, 92.7%, 80.1%, and 82.5% for the "Vaccine Constituent," "Adverse Effects," "Agenda," "Efficacy and Clinical Trials" aspects, respectively. The model achieved an Area Under the ROC Curve (AUC) of 90.3% and 89.6% for validation and testing, respectively, which indicates the reliability of the proposed framework in detecting aspects of vaccine misinformation on Twitter. The correlation analysis shows that 37% of the countries addressed in this study were negatively affected by the spread of misinformation on Twitter resulting in reduced number of administered vaccines during the same timeframe. CONCLUSIONS: Twitter is a rich source of insight on the progression of vaccine misinformation among the public. Machine Learning models, such as LightGBM, are efficient for multi-class classification and proved reliable in classifying vaccine misinformation aspects even with limited samples in social media datasets.

Antiandrogens for the treatment of COVID-19 patients: A meta-analysis of randomized controlled trials.

Antiandrogens may carry a potential benefit as a therapeutic agent against COVID-19. However, studies have been yielding mixed results, thus hindering any objective recommendations. This necessitates a quantitative synthesis of data to quantify the benefits of antiandrogens. We systematically searched PubMed/MEDLINE, Cochrane Library, clinical trial registers, and reference lists of included studies to identify relevant randomized controlled trials (RCTs). Results from the trials were pooled using a random-effects model and outcomes were reported as risk ratios (RR) and mean differences (MDs) with 95% confidence intervals (CIs). Fourteen RCTs with a total sample size of 2593 patients were included. Antiandrogens yielded a significant mortality benefit (RR 0.37; 95% CI; 0.25-0.55). However, on subgroup analysis, only proxalutamide/enzalutamide and sabizabulin were found to significantly reduce mortality (RR 0.22, 95% CI: 0.16-0.30 and RR 0.42, 95% CI: 0.26-0.68, respectively), while aldosterone receptor antagonists and antigonadotropins did not show any benefit. No significant between-group difference was found in the early or late initiation of therapy. Antiandrogens also reduced hospitalizations and the duration of hospital stay, and improved recovery rates. Proxalutamide and sabizabulin may be effective against COVID-19, however, further large-scale trials are needed to confirm these findings.

Asymmetric Dimethylation of Ribosomal S6 Kinase 2 Regulates Its Cellular Localisation and Pro-Survival Function.

Ribosomal S6 kinases (S6Ks) are critical regulators of cell growth, homeostasis, and survival, with dysregulation of these kinases found to be associated with various malignancies. While S6K1 has been extensively studied, S6K2 has been neglected despite its clear involvement in cancer progression. Protein arginine methylation is a widespread post-translational modification regulating many biological processes in mammalian cells. Here, we report that p54-S6K2 is asymmetrically dimethylated at Arg-475 and Arg-477, two residues conserved amongst mammalian S6K2s and several AT-hook-containing proteins. We demonstrate that this methylation event results from the association of S6K2 with the methyltransferases PRMT1, PRMT3, and PRMT6 in vitro and in vivo and leads to nuclear the localisation of S6K2 that is essential to the pro-survival effects of this kinase to starvation-induced cell death. Taken together, our findings highlight a novel post-translational modification regulating the function of p54-S6K2 that may be particularly relevant to cancer progression where general Arg-methylation is often elevated.

Type 1 Diabetes Prevention: a systematic review of studies testing disease-modifying therapies and features linked to treatment response.

Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Efforts to prevent T1D have focused on modulating immune responses and supporting beta cell health; however, heterogeneity in disease progression and responses to therapies have made these efforts difficult to translate to clinical practice, highlighting the need for precision medicine approaches to T1D prevention. Methods: To understand the current state of knowledge regarding precision approaches to T1D prevention, we performed a systematic review of randomized-controlled trials from the past 25 years testing disease-modifying therapies in T1D and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. Results: We identified 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss in individuals at disease onset. Seventeen agents tested, mostly immunotherapies, showed benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employed precision analyses to assess features linked to treatment response. Age, measures of beta cell function and immune phenotypes were most frequently tested. However, analyses were typically not prespecified, with inconsistent methods reporting, and tended to report positive findings. Conclusions: While the quality of prevention and intervention trials was overall high, low quality of precision analyses made it difficult to draw meaningful conclusions that inform clinical practice. Thus, prespecified precision analyses should be incorporated into the design of future studies and reported in full to facilitate precision medicine approaches to T1D prevention. Plain Language Summary: Type 1 diabetes (T1D) results from the destruction of insulin-producing cells in the pancreas, necessitating lifelong insulin dependence. T1D prevention remains an elusive goal, largely due to immense variability in disease progression. Agents tested to date in clinical trials work in a subset of individuals, highlighting the need for precision medicine approaches to prevention. We systematically reviewed clinical trials of disease-modifying therapy in T1D. While age, measures of beta cell function, and immune phenotypes were most commonly identified as factors that influenced treatment response, the overall quality of these studies was low. This review reveals an important need to proactively design clinical trials with well-defined analyses to ensure that results can be interpreted and applied to clinical practice.