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Background and Aims: Non‐alcoholic fatty liver disease (NAFLD) has been linked to type 2 diabetes (T2D), but also to hypothyroidism. Nevertheless, the relationship between thyroid function and NAFLD in diabetes is less clear. This study investigated associations between free thyroxine (fT4) or thyroid‐stimulating hormone (TSH) and NAFLD in recent‐onset diabetes. Methods: Participants with recent‐onset type 1 diabetes (T1D, n = 358), T2D (n = 596) or without diabetes (CON, n = 175) of the German Diabetes Study (GDS), a prospective longitudinal cohort study, underwent Botnia clamp tests and assessment of fT4, TSH, fatty liver index (FLI) and in a representative subcohort 1H‐magnetic resonance spectroscopy. Results: First, fT4 levels were similar between T1D and T2D (p =.55), but higher than in CON (T1D: p <.01; T2D: p <.001), while TSH concentrations were not different between all groups. Next, fT4 correlated negatively with FLI and positively with insulin sensitivity only in T2D (ß = −.110, p <.01; ß =.126, p <.05), specifically in males (ß = −.117, p <.05; ß =.162; p <.01) upon adjustments for age, sex and BMI. However, correlations between fT4 and FLI lost statistical significance after adjustment for insulin sensitivity (T2D: ß = −.021, p = 0.67; males with T2D: ß = −.033; p =.56). TSH was associated positively with FLI only in male T2D before (ß =.116, p <.05), but not after adjustments for age and BMI (ß =.052; p =.30). Conclusions: Steatosis risk correlates with lower thyroid function in T2D, which is mediated by insulin resistance and body mass, specifically in men, whereas no such relationship is present in T1D. [ABSTRACT FROM AUTHOR]

Marawan Ahmed,1 Horia Jalily Hasani,1,* Aravindhan Ganesan,1,* Michael Houghton,2–4 Khaled Barakat1–3 1Faculty of Pharmacy and Pharmaceutical Sciences, 2Li Ka Shing Institute of Virology, 3Li Ka Shing Applied Virology Institute, 4Department of Medical Microbiology and Immunology, Katz Centre for Health Research, University of Alberta, Edmonton, AB, Canada *These authors contributed equally to this work Abstract: Abnormalities in the human Nav1.5 (hNav1.5) voltage-gated sodium ion channel (VGSC) are associated with a wide range of cardiac problems and diseases in humans. Current structural models of hNav1.5 are still far from complete and, consequently, their ability to study atomistic interactions of this channel is very limited. Here, we report a comprehensive atomistic model of the hNav1.5 ion channel, constructed using homology modeling technique and refined through long molecular dynamics simulations (680 ns) in the lipid membrane bilayer. Our model was comprehensively validated by using reported mutagenesis data, comparisons with previous models, and binding to a panel of known hNav1.5 blockers. The relatively long classical MD simulation was sufficient to observe a natural sodium permeation event across the channel’s selectivity filters to reach the channel’s central cavity, together with the identification of a unique role of the lysine residue. Electrostatic potential calculations revealed the existence of two potential binding sites for the sodium ion at the outer selectivity filters. To obtain further mechanistic insight into the permeation event from the central cavity to the intracellular region of the channel, we further employed “state-of-the-art” steered molecular dynamics (SMD) simulations. Our SMD simulations revealed two different pathways through which a sodium ion can be expelled from the channel. Further, the SMD simulations identified the key residues that are likely to control these processes. Finally, we discuss the potential binding modes of a panel of known hNav1.5 blockers to our structural model of hNav1.5. We believe that the data presented here will enhance our understanding of the structure–property relationships of the hNav1.5 ion channel and the underlying molecular mechanisms in sodium ion permeation and drug interactions. The results presented here could be useful for designing safer drugs that do not block the hNav1.5 channel. Keywords: sodium ion channel, voltage-gated sodium channel, steered molecular dynamics, cardiotoxicity, hNav1.5, channel blockers

Background: Diabetes distress is increasingly considered one of the most important psychosocial issues in the care of people with type 1 diabetes (T1D). We analyse whether diabetes distress and depression screening results of emerging adults are associated with the age at T1D onset. Methods: Data were taken from two cohort studies conducted at the German Diabetes Center, Düsseldorf, Germany. The 18–30-year-old participants had an age at onset either before the age of 5 years (childhood-onset long-term T1D study group, N = 749) or during adulthood (adult-onset short-term T1D study group from the German Diabetes Study (GDS), N = 163). Diabetes distress and depression screening were analysed by means of the 20-item Problem Areas in Diabetes (PAID-20) scale and the nine-item depression module from the Patient Health Questionnaire (PHQ-9). The average causal effect of age at onset was estimated by a doubly robust causal inference method. Results: The PAID-20 total scores were increased in the adult-onset study group [potential outcome mean (POM) 32.1 (95% confidence interval 28.0; 36.1) points] compared to the childhood-onset study group [POM 21.0 (19.6; 22.4) points, difference 11.1 (6.9; 15.3) points, p<0.001] adjusted for age, sex and haemoglobin A1c (HbA1c) levels. Moreover, more participants in the adult-onset group [POM 34.5 (24.9; 44.2) %] than in the childhood-onset group [POM 16.3 (13.3; 19.2) %] screened positive for diabetes distress [adjusted difference 18.3 (8.3; 28.2) %, p<0.001]. The PHQ-9 total score [difference 0.3 (-1.1; 1.7) points, p=0.660] and the proportion of participants with a positive screening result for depression [difference 0.0 (-12.7; 12.8) %, p=0.994] did not differ between the groups in the adjusted analyses. Conclusions: Emerging adults with short-term type 1 diabetes screened positive for diabetes distress more often than adults with type 1 diabetes onset during early childhood when age, sex and HbA1c values were considered confounding factors. Accounting for age at onset or the duration of diabetes may help explain the heterogeneity in the data when psychological factors are examined. [ABSTRACT FROM AUTHOR]

Semantic segmentation of aerial data has been one of the leading researches in the field of photogrammetry, remote sensing, and computer vision in recent years. Many applications, including airborne mapping of urban scenes, object positioning in aerial images, automatic extraction of buildings from remote sensing or high-resolution aerial images, etc., require accurate and efficient segmentation algorithms. According to the high potential of deep learning algorithms in the classification of complex scenes, this paper aims to train a deep learning model to evaluate the semantic segmentation accuracy of UAV-based images in urban areas. The proposed method implements a deep learning framework based on the U-Net encoder-decoder architecture, which extracts and classifies features through layers of convolution, max pooling, activation, and concatenation in an end-to-end process. The obtained results compare with two traditional machine learning models, Random Forest (RF) and Multi-Layer Perceptron (MLP). They rely on two steps that involve extracting features and classifying images. In this study, the experiments are performed on the UAVid2020 semantic segmentation dataset from the ISPRS database. Results show the effectiveness of the proposed deep learning framework, so that the U-Net architecture achieved the best results with 75.15% overall accuracy, compared to RF and MLP algorithms with 52.51% and 54.65% overall accuracy, respectively. [ABSTRACT FROM AUTHOR]

Background and aims: It is unclear whether socio‐economic status (SES) is associated with glycaemic control in people with recently diagnosed diabetes. The aim was to investigate whether SES is related to haemoglobin A1c (HbA1c) during the first year after diagnosis in people with type 1 and type 2 diabetes and if metabolic, quality of care or mental factors may explain the association. Methods: In the German Diabetes Study, people with type 1 (n = 274, median age 36 [25th; 75th percentile: 28; 48] years) and type 2 diabetes (n = 424, 54 [47; 60] years) underwent detailed metabolic characterisation within the first year after diagnosis. SES was documented using a standardised questionnaire. Associations between SES and HbA1c were assessed using multivariable linear regression and restricted cubic spline regression analyses. Additional covariables were patient characteristics, laboratory measurements, health behaviour, quality of care and depression variables. Models were separately fitted for diabetes type, SES and its dimensions (income, education, occupation). Results: Higher SES score was associated with lower HbA1c (−0.7 mmol/mol per unit increase in SES, 95% CI: −1.1; −0.2 mmol/mol [−0.1%, 95% CI: −0.1; 0.0%]) in people with type 1 diabetes. Included covariates did not attenuate this association. In people with type 2 diabetes, effect estimates were close to zero indicating no relevant difference. Conclusion: Socio‐economic inequalities in HbA1c already exist during the first year after diagnosis in people with type 1 diabetes. The absence of association between glycaemic control and SES in type 2 diabetes could be due to the lower complexity of diabetes therapy compared to type 1 diabetes. [ABSTRACT FROM AUTHOR]

Background: The high prevalence of virulence-associated genes observed in isolates underscores the pathogenic potential of this bacterium. The presence of these genes confers enhanced survival, evasion of host defenses, and increased virulence. In this study, we investigate the presence and distribution of genes associated with virulence and assess the antimicrobial susceptibility patterns in clinical isolates of .Materials and method: This research focused on examining the 5ulti-drugs resistant (MDR) strains that were included in this investigation. The identification of these strains was validated using Oxa-51. The presence of the and genes was determined through conventional PCR techniques.Results: The results derived from Oxa-51 PCR confirmed the identification of all 50 selected strains of . Additionally, both the and genes were successfully identified in 82% of the MDR strains.Conclusion: Moreover, the varying antibiotic resistance patterns highlight the challenge in treating infections effectively. Strategies such as combination therapy, antimicrobial stewardship, and infection control measures should be considered to combat this multidrug-resistant pathogen.

Frequencies of circulating immune cells are altered in those with type 1 and type 2 diabetes compared with healthy individuals and are associated with insulin sensitivity, glycemic control, and lipid levels. This study aimed to determine whether specific immune cell types are associated with novel diabetes subgroups. We analyzed automated white blood cell counts (n = 669) and flow cytometric data (n = 201) of participants in the German Diabetes Study with recent-onset (<1 year) diabetes, who were allocated to five subgroups based on data-driven analysis of clinical variables. Leukocyte numbers were highest in severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) and lowest in severe autoimmune diabetes (SAID). CD4+ T-cell frequencies were higher in SIRD versus SAID, MOD, and mild age-related diabetes (MARD), and frequencies of CCR4+ regulatory T cells were higher in SIRD versus SAID and MOD and in MARD versus SAID. Pairwise differences between subgroups were partially explained by differences in clustering variables. Frequencies of CD4+ T cells were positively associated with age, BMI, HOMA2 estimate of β-cell function (HOMA2-B), and HOMA2 estimate of insulin resistance (HOMA2-IR), and frequencies of CCR4+ regulatory T cells with age, HOMA2-B, and HOMA2-IR. In conclusion, different leukocyte profiles exist between novel diabetes subgroups and suggest distinct inflammatory processes in these diabetes subgroups. [ABSTRACT FROM AUTHOR]

Background: Application of mixed meal tolerance tests (MMTT) to measure beta-cell function in long-term studies is limited by modification of the commercial products occurring over time. This study assessed the intra-individual reliability of MMTTs and compared the effects of liquid meals differing in macronutrient composition on the estimation of beta-cell function in type 2 diabetes (T2DM). Methods: To test the reliability of MMTTs, 10 people with T2DM (age 58 ± 11 years, body mass index 30.0 ± 4.9 kg/m2) received Boost®high Protein 20 g protein three times. For comparing different meals, another 10 persons with T2DM (58 ± 5 years, 31.9 ± 5.3 kg/m2) ingested either Boost®high Protein 20 g protein or the isocaloric Boost®high Protein 15 g protein containing 35% less protein and 18% more carbohydrates. C-peptide, insulin and glucose release were assessed from the incremental area under the concentration time curve (iAUC) and the intra- and inter-individual variation of these parameters from the coefficients of variations (CV). Results: Repetitive ingestion of one meal revealed intra-individual CVs for the iAUCs of C-peptide, insulin and glucose, which were at least 3-times lower than the inter-individual variation of these parameters (18.2%, 19.7% and 18.9% vs. 74.2%, 70.5% and 207.7%) indicating a good reliability. Ingestion of two different meals resulted in comparable intra-individual CVs of the iAUCs of C-peptide and insulin (16.9%, 20.5%). Conclusion: MMTTs provide reliable estimation of beta-cell function in people with T2DM. Furthermore, moderate differences in the protein and carbohydrate contents in a standardized liquid meal do not result in relevant changes of C-peptide and insulin responses. Trial registration: Clinicaltrials.gov, Identifier number: NCT01055093. Registered 22 January 2010 – Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/study/NCT01055093 [ABSTRACT FROM AUTHOR]