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Abstract Aims Heart transplantation is a well‐established treatment for end‐stage heart failure in paediatric patients, demonstrating excellent long‐term outcomes. Methods This retrospective study analyses 35 years of data on 244 paediatric recipients (

BackgroundA 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.MethodsWe 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.ResultsThe 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.ConclusionThe 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.

Gut microbiota impacts responses to immune checkpoint inhibitors (ICI). A high level of Faecalibacterium prausnitzii have been associated with a positive response to ICI in multiple cancer types. Here, based on fecal shotgun metagenomics data, we show in two independent cohorts of patients with non-small cell lung cancer and advanced melanoma that a high level of F. prausnitzii at baseline is positively associated with a better clinical response to ICI. In MCA205 tumor-bearing mice, administration of F. prausnitzii strain EXL01, already in clinical development for Inflammatory Bowel Disease, restores the anti-tumor response to ICI in the context of antibiotic-induced microbiota perturbation at clinical and tumor transcriptomics level. In vitro, EXL01 strain enhances T cell activation in the presence of ICI. Interestingly, oral administration of EXL01 strain did not induce any change in fecal microbiota diversity or composition, suggesting a direct effect on immune cells in the small intestine. F. prausnitzii strain EXL01 will be evaluated as an adjuvant to ICI in multiple cancers in the near future.

Abstract Background The etiology of inflammatory bowel disease (IBD) is unclear but involves both genetics and environmental factors, including the gut microbiota. Indeed, exacerbated activation of the gastrointestinal immune system toward the gut microbiota occurs in genetically susceptible hosts and under the influence of the environment. For instance, a majority of IBD susceptibility loci lie within genes involved in immune responses, such as caspase recruitment domain member 9 (Card9). However, the relative impacts of genotype versus microbiota on colitis susceptibility in the context of CARD9 deficiency remain unknown. Results Card9 gene directly contributes to recovery from dextran sodium sulfate (DSS)-induced colitis by inducing the colonic expression of the cytokine IL-22 and the antimicrobial peptides Reg3β and Reg3γ independently of the microbiota. On the other hand, Card9 is required for regulating the microbiota capacity to produce AhR ligands, which leads to the production of IL-22 in the colon, promoting recovery after colitis. In addition, cross-fostering experiments showed that 5 weeks after weaning, the microbiota transmitted from the nursing mother before weaning had a stronger impact on the tryptophan metabolism of the pups than the pups’ own genotype. Conclusions These results show the role of CARD9 and its effector IL-22 in mediating recovery from DSS-induced colitis in both microbiota-independent and microbiota-dependent manners. Card9 genotype modulates the microbiota metabolic capacity to produce AhR ligands, but this effect can be overridden by the implantation of a WT or “healthy” microbiota before weaning. It highlights the importance of the weaning reaction occurring between the immune system and microbiota for host metabolism and immune functions throughout life. A better understanding of the impact of genetics on microbiota metabolism is key to developing efficient therapeutic strategies for patients suffering from complex inflammatory disorders. Video Abstract

Objective: The European Registries for Rare Endocrine Conditions (EuRRECa, eurreb. eu) includes an e-reporting registry (e-REC) used to perform surveillance of conditions within the European Reference Network (ERN) for rare endocrine conditions (Endo-ERN). The aim of this study was to report the experience of e-REC over the 3.5 years since its launch in 2018. Methods: Electronic reporting capturing new encounters of Endo-ERN conditions was performed monthly through a bespoke platform by clinicians registered to participate in e-REC from July 2018 to December 2021. Results: The number of centres reporting on e-REC increased to a total of 61 centres from 22 countries. A median of 29 (range 11, 45) paediatric and 32 (14, 51) adult centres had reported cases monthly. A total of 9715 and 4243 new cases were reported in adults (age ≥18 years) and children, respectively. In children, sex development conditions comprised 40% of all reported conditions and transgender cases were most frequently reported, comprising 58% of sex development conditions. The median number of sex development cases reported per centre per month was 0.6 (0, 38). Amongst adults, pituitary conditions comprised 44% of reported conditions and pituitary adenomas (69% of cases) were most commonly reported. The median number of pituitary cases reported per centre per month was 4 (0.4, 33). Conclusions: e-REC has gained increasing acceptability over the last 3.5 years for capturing brief information on new encounters of rare conditions and shows wide variations in the rate of presentation of these conditions to centres within a reference network. Significance statement Endocrinology includes a very wide range of rare conditions and their occurrence is often difficult to measure. By using an electronic platform that allowed monthly reporting of new clinical encounters of several rare endocrine conditions wi thin a defined network that consisted of several reference centres in Europe, the EuRRECa project shows that a programme of e-surveillance is feasible and acceptable. The data that have been collected by the e-reporting of rare endocrine conditions (e-REC) can allow the continuous monitoring of rare conditions and may be used for clinical benchmarking, designing new studies or recruiting to clinical trials.

Water quality indicator algorithms often separate marine and freshwater systems, introducing artificial boundaries and artifacts in the freshwater to ocean continuum. Building upon the Ocean Colour- (OC) and Lakes Climate Change Initiative (CCI) projects, we propose an improved tool to assess the interactions across river–sea transition zones. Fuzzy clustering methods are used to generate optical water types (OWT) representing spectrally distinct water reflectance classes, occurring within a given region and period (here 2016–2021), which are then utilized to assign membership values to every OWT class for each pixel and seamlessly blend optimal in-water algorithms across the region. This allows a more flexible representation of water provinces across transition zones than classic hard clustering techniques. Improvements deal with expanded sensor spectral band-sets, such as Sentinel-3 OLCI, and increased spatial resolution with Sentinel-2 MSI high-resolution data. Regional clustering was found to be necessary to capture site-specific characteristics, and a method was developed to compare and merge regional cluster sets into a pan-regional representative OWT set. Fuzzy clustering OWT timeseries data allow unique insights into optical regime changes within a lagoon, estuary, or delta system, and can be used as a basis to improve WQ algorithm performance.

Abstract Background Gabon is a malaria-threatened country with a stable and hyperendemic transmission of Plasmodium falciparum monoinfection. Malaria drug resistance is widely spread in many endemic countries around the world, including Gabon. The molecular surveillance of drug resistance to antifolates and artemisinin-based combination therapy (ACT) is one of the strategies for combating malaria. As Plasmodium parasites continue to develop resistance to currently available anti-malarial drugs, this study evaluated the frequency of the polymorphisms and genetic diversity associated with this phenomenon among the parasites isolates in Gabon. Methods To assess the spread of resistant haplotypes among the malaria-infected population of Libreville, single nucleotide polymorphisms linked to sulfadoxine–pyrimethamine (SP) and artemisinin drugs resistance were screened for P. falciparum dihydrofolate reductase (Pfdhfr), P. falciparum dihydropteroate synthase (Pfdhps), and P. falciparum kelch 13-propeller domain (Pfk13) point mutations. Results The analysis of 70 malaria-positive patient samples screened for polymorphism showed 92.65% (n = 63) mutants vs. 7.35% (n = 5) wild parasite population in Pfdhfr, with high prevalence mutations at S108N(88.24%, n = 60), N51I(85.29%, n = 58), C59R(79.41%, n = 54); however, I164L(2.94%, n = 2) showed low frequency mutation. No wild haplotype existed for Pfdhps, and there were no mutations at the K540E, A581G, and A613T/S positions. However, the mutation rate at A437G(93.38%, n = 62) was the highest, followed by S436A/F(15.38%, n = 10). A higher frequency of quadruple IRNI–SGKAA (69.84%) than quintuple IRNI–(A/F)GKAA (7.94%) mutations was observed in the Pfdhfr–Pfdhps combination. Furthermore, none of the mutations associated with ACT resistance, especially those commonly found in Africa, were observed in Pfk13. Conclusions High polymorphism frequencies of Pfdhfr and Pfdhps genes were observed, with alternative alanine/phenylalanine mutation at S436A/F (7.69%, n = 5) for the first time. Similar to that of other areas of the country, the patterns of multiple polymorphisms were consistent with selection owing to drug pressure. Although there was no evidence of a medication failure haplotype in the studied population, ACT drug efficacy should be regularly monitored in Libreville, Gabon.

As the most visible and vulnerable organ of the human organism, the skin can provide an impression of its state of health. Rare forms of diabetes and endocrinopathies are often diagnosed late or primarily misinterpreted due to their rarity. Skin peculiarities associated with these rare diseases may be indicative of the underlying endocrinopathy or form of diabetes. At the same time, rare skin changes in diabetes or endocrinopathies can also be a major challenge for dermatologists, diabetologists and endocrinologists in optimal patient and therapy management. Active collaboration between these different specialist groups can therefore lead to increased patient safety, better therapeutic success and more targeted diagnostics.

Abstract Background The FIDELIO-DKD and FIGARO-DKD randomized clinical trials (RCTs) showed finerenone, a novel non-steroidal mineralocorticoid receptor antagonist (MRA), reduced the risk of renal and cardiovascular events in patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD). Using RCT inclusion and exclusion criteria, we analyzed the RCT coverage for patients with T2DM and CKD in routine clinical practice in Germany. Methods German patients from the DPV/DIVE registries who were ≥ 18 years, had T2DM and CKD (an estimated glomerular filtration rate [eGFR]

Abstract Background Effects of antibiotics on gut bacteria have been widely studied, but very little is known about the consequences of such treatments on the fungal microbiota (mycobiota). It is commonly believed that fungal load increases in the gastrointestinal tract following antibiotic treatment, but better characterization is clearly needed of how antibiotics directly or indirectly affect the mycobiota and thus the entire microbiota. Design We used samples from humans (infant cohort) and mice (conventional and human microbiota-associated mice) to study the consequences of antibiotic treatment (amoxicillin-clavulanic acid) on the intestinal microbiota. Bacterial and fungal communities were subjected to qPCR or 16S and ITS2 amplicon-based sequencing for microbiota analysis. In vitro assays further characterized bacterial-fungal interactions, with mixed cultures between specific bacteria and fungi. Results Amoxicillin-clavulanic acid treatment triggered a decrease in the total fungal population in mouse feces, while other antibiotics had opposite effects on the fungal load. This decrease is accompanied by a total remodelling of the fungal population with the enrichment in Aspergillus, Cladosporium, and Valsa genera. In the presence of amoxicillin-clavulanic acid, microbiota analysis showed a remodeling of bacterial microbiota with an increase in specific bacteria belonging to the Enterobacteriaceae. Using in vitro assays, we isolated different Enterobacteriaceae species and explored their effect on different fungal strains. We showed that Enterobacter hormaechei was able to reduce the fungal population in vitro and in vivo through yet unknown mechanisms. Conclusions Bacteria and fungi have strong interactions within the microbiota; hence, the perturbation initiated by an antibiotic treatment targeting the bacterial community can have complex consequences and can induce opposite alterations of the mycobiota. Interestingly, amoxicillin-clavulanic acid treatment has a deleterious effect on the fungal community, which may have been partially due to the overgrowth of specific bacterial strains with inhibiting or competing effects on fungi. This study provides new insights into the interactions between fungi and bacteria of the intestinal microbiota and might offer new strategies to modulate gut microbiota equilibrium. Video Abstract

Abstract Introduction A continuous process of trauma centre evaluation is essential to ensure the development and progression of trauma care at regional, national and international levels. Evaluation may be by comparison between pooled datasets or by direct benchmarking between centres. This study attempts to benchmark mortality at two trauma centres standardising this for multiple case-mix factors, which includes the prevalence of individual background pre-existing diseases within the study population. Methods Trauma patients with an Injury Severity Score (ISS) >15 admitted to the two centres in 2001 and 2002 were included in the study with the exception of those who died in the emergency department. Patient characteristics were analysed in terms of 18 case-mix factors including Glasgow Coma Scale on arrival, Injury Severity Score and the presence or absence of 9 co-morbidity types, and patient outcome was compared based on in-hospital mortality before and after standardisation. Results Crude mortality was greater at UHNS (18.2 vs 14.5%) with a non-significant odds ratio of 1.31 prior to adjusting for case-mix (P = 0.171). Adjustment for case mix using logistic regression analysis altered the odds ratio to 1.64, which was not significant (P = 0.069). Discussion This study did not demonstrate any significant difference in the outcome of patients treated at either hospital during the study period. More importantly it has raised several important methodological issues pertinent to researchers undertaking registry based benchmarking studies. Data at the two registries was collected by personnel with differing backgrounds, in formats that were not completely compatible and was collected for patients that met different admissions criteria. The inclusion of a meaningful analysis of pre-existing disease was limited by the availability of robust data and sample size. We suggest greater communication between trauma research coordinators to ensure equivalent data collection and facilitate future benchmarking studies.

ABSTRACT Many strains have been used and selected by the food industry for their capacities to ferment, produce flavors, or produce heterologous molecules. Very little is known about the diversity of foodborne yeasts and their potential effect on gut microbiota and gut health. We initiated a complete characterization of five strains belonging to five species with a long history of safe use in food: Cyberlindnera jadinii, Debaryomyces hansenii, Kazachstania unispora, Kluyveromyces lactis, and Pichia membranifaciens, with a focus on their capacity to protect against gut inflammation using an in vivo dextran sodium sulfate-induced colitis model in mice. C. jadinii and K. lactis living cells showed a clear reduction in mouse sensitivity to colitis in vivo. Interestingly, we observed that C. jadinii had the capacity to survive transit in the gut, while K. lactis did not. We demonstrated that C. jadinii was unable to efficiently adhere to epithelial cells and did not survive more than 24 to 48 h in the gut. Transcriptomic analysis using NanoString technology suggested a potential role of IL-8 through Mif and Fkbp5 in the effect of C. jadinii on the immune system. Bacterial and fungal microbiota characterization showed a modification of both microbiota after C. jadinii treatment, with a significant increase in positive microorganisms and a decrease in pathobionts. Altogether, these data suggest that both C. jadinii and K. lactis strains have potential as probiotic yeast strains to fight against inflammation in the gut, but further studies are needed to understand the mechanisms by which these strains act on gut health.IMPORTANCEThe food industry has always used many strains of microorganisms including fungi in their production processes. These strains have been widely characterized for their biotechnological value, but we still know very little about their interaction capacities with the host at a time when the intestinal microbiota is at the center of many pathologies. In this study, we characterized five yeast strains from food production which allowed us to identify two new strains with high probiotic potential and beneficial effects in a model of intestinal inflammation.

In today’s age, plastic waste is a major problem for our environment. The decomposition of plastic waste causes widespread contamination in all types of ecosystems worldwide. Micro-plastics in the lower micrometer size range and especially nano-plastics can become internalized by cells and thus become a threat to human health. To investigate the effects of internalized micro- and nano-plastics on human gene transcription, we used an in vitro assay to quantify CREB (cAMP response element binding protein) mediated transcription. Here we show that CREB mediated gene expression was mainly but not exclusively induced by phosphorylation. In addition, the amount of CREB affected transcription was also studied. We were also able to show that the strong CREB mediated stimulation of transcription was diminished by micro- and nano-plastics in any chosen setting. This indicates a threat to human health via the deregulation of transcription induced by internalized micro- and nano-plastics. However, this established quantifiable in vitro transcription test system could help to screen for toxic substances and non-toxic alternatives.

IntroductionAntibiotic effects on gut bacteria have been widely studied, but very little is known about the consequences of such treatments on the mycobiota, the fungal part of the microbiota and how the length of administration influences both microbiota. Here, we examined the effect of antibiotics (ATB) on the composition of bacterial and fungal microbiota and how the administration of Saccharomyces boulardii CNCM I-745 influences both microbiota.MethodsIn order to get closer to the human microbiota, the mice used in this study were subjected to fecal microbiota transfer (FMT) using human feces and subsequently called human microbiotaassociated (HMA) mice. These mice were then treated with amoxicillinclavulanate antibiotics and supplemented with S. boulardii during and after ATB treatment to understand the effect of the yeast probiotic on both bacterial and fungal microbiota. Bacterial and fungal microbiota analyses were done using 16S and ITS2 rRNA amplicon-based sequencing.ResultsWe showed that the administration of S. boulardii during ATB treatment had very limited effect on the fungal populations on the long term, once the yeast probiotic has been cleared from the gut. Concerning bacterial microbiota, S. boulardii administration allowed a better recovery of bacterial populations after the end of the ATB treatment period. Additionally, 16S and ITS2 rRNA sequence analysis revealed that 7 additional days of S. boulardii administration (17 days in total) enhanced the return of the initial bacterial equilibrium.DiscussionIn this study, we provide a comprehensive analysis of how probiotic yeast administration can influence the fungal and bacterial microbiota in a model of broad-spectrum antibiotherapy.

Background: Hypoglycemia rates usually increase when insulin treatment is intensified to improve glycemic control. We evaluated (post hoc) hypoglycemic rates in adult patients with type 1 diabetes (T1D) on sotagliflozin (a dual sodium-glucose cotransporter [SGLT] 1 and 2 inhibitor) in two phase 3, 52-week clinical trials (inTandem 1 and 2; NCT02384941 and NCT02421510). Materials and Methods: We analyzed rates of documented hypoglycemia (level 1, blood glucose ≥54 to

Sodium-glucose cotransporter (SGLT) inhibitors are new oral antidiabetes medications shown to effectively reduce glycated hemoglobin (A1C) and glycemic variability, blood pressure, and body weight without intrinsic properties to cause hypoglycemia in people with type 1 diabetes. However, recent studies, particularly in individuals with type 1 diabetes, have demonstrated increases in the absolute risk of diabetic ketoacidosis (DKA). Some cases presented with near-normal blood glucose levels or mild hyperglycemia, complicating the recognition/diagnosis of DKA and potentially delaying treatment. Several SGLT inhibitors are currently under review by the U.S. Food and Drug Administration and European regulatory agencies as adjuncts to insulin therapy in people with type 1 diabetes. Strategies must be developed and disseminated to the medical community to mitigate the associated DKA risk. This Consensus Report reviews current data regarding SGLT inhibitor use and provides recommendations to enhance the safety of SGLT inhibitors in people with type 1 diabetes.

Summary: Background: Type 1 diabetes is a complex heterogenous autoimmune disease without therapeutic interventions available to prevent or reverse the disease. This study aimed to identify transcriptional changes associated with the disease progression in patients with recent-onset type 1 diabetes. Methods: Whole-blood samples were collected as part of the INNODIA study at baseline and 12 months after diagnosis of type 1 diabetes. We used linear mixed-effects modelling on RNA-seq data to identify genes associated with age, sex, or disease progression. Cell-type proportions were estimated from the RNA-seq data using computational deconvolution. Associations to clinical variables were estimated using Pearson's or point-biserial correlation for continuous and dichotomous variables, respectively, using only complete pairs of observations. Findings: We found that genes and pathways related to innate immunity were downregulated during the first year after diagnosis. Significant associations of the gene expression changes were found with ZnT8A autoantibody positivity. Rate of change in the expression of 16 genes between baseline and 12 months was found to predict the decline in C-peptide at 24 months. Interestingly and consistent with earlier reports, increased B cell levels and decreased neutrophil levels were associated with the rapid progression. Interpretation: There is considerable individual variation in the rate of progression from appearance of type 1 diabetes-specific autoantibodies to clinical disease. Patient stratification and prediction of disease progression can help in developing more personalised therapeutic strategies for different disease endotypes. Funding: A full list of funding bodies can be found under Acknowledgments.

Natural language processing of medical records offers tremendous potential to improve the patient experience. Sentiment analysis of clinical notes has been performed with mixed results, often highlighting the issue that dictionary ratings are not domain specific. Here, for the first time, we re-calibrate the labMT sentiment dictionary on 3.5M clinical notes describing 10,000 patients diagnosed with lung cancer at the Department of Veterans Affairs. The sentiment score of notes was calculated for two years after date of diagnosis and evaluated against a lab test (platelet count) and a combination of data points (treatments). We found that the oncology specific labMT dictionary, after re-calibration for the clinical oncology domain, produces a promising signal in notes that can be detected based on a comparative analysis to the aforementioned parameters.

There is considerable heterogeneity within the clinical phenotype of type 1 diabetes: genetic susceptibility is complex, progression rates differ markedly, as does the efficacy of therapeutic interventions. New prevention strategies should use biomarkers to lead to personalized combination therapies analogous to the approach used in pediatric oncology. It is well known that type 1 diabetes starts with autoimmunity, the detection of 2 or more persistent diabetes-associated antibodies (stage 1). Additional subclinical dysglycemia is termed stage 2, and manifest type 1 diabetes is termed stage 3. Both genetic and immunologic parameters allow early detection in children and adolescents. Because 9 out of 10 affected children come from families without other family members with type 1 diabetes, screening approaches provide an opportunity for preservation of residual insulin-producing beta cell function. Studies of the psychological burden of screening procedures and results showed that the vast majority of families were able to live relatively unburdened by the knowledge of their child's increased diabetes risk after a short period of time. The GPPAD research network is investigating primary prevention with oral insulin (POINT study) or probiotics (S1NTIA study). The European research network INNODIA is developing a standardized study protocol ("master protocol") to accelerate the investigation of new single agents and combination therapies from the age of 5 years. Secondary prevention approaches are showing promising results in initial pilot studies to prolong the remission phase or delay disease onset in at-risk populations. Intensified insulin therapy with differential substitution of basal- and bolus insulin is the gold standard also for children with type 1 diabetes. The different absorption profiles and half-lives of insulin preparations allow insulin therapy to be tailored for the individual patient. Ultra-rapid insulin analogues show improved postprandial glucose levels, while second-generation basal analogues are associated with less hypoglycemia and reduced events of hyperglycemia and ketosis as a surrogate marker of a high risk for DKA. New parameters like time in range and time below range suitable for identifying high glycemic variability as risk factor for severe hypoglycemia complement the HbA1c targets and the ambulatory glucose profile in a shared decision making on therapeutic adjustments between the diabetes team and families with a child with diabetes. Automated insulin delivery as a hybrid closed loop or dosing advice using artificial intelligence are becoming a clinical reality. However, diabetes education as a team approach, defining clear targets with outcomes evaluated in multinational registries like SWEET remain important for shaping the future of pediatric diabetology.