Collagen Type I Improves the Differentiation of Human Embryonic Stem Cells towards Definitive Endoderm

Human embryonic stem cells have the ability to generate all cell types in the body and can potentially provide an unlimited source of cells for cell replacement therapy to treat degenerative diseases such as diabetes. Current differentiation protocols of human embryonic stem cells towards insulin producing beta cells focus on soluble molecules whereas the impact of cell-matrix interactions has been mainly unattended. In this study almost 500 different extracellular matrix protein combinations were screened to systemically identify extracellular matrix proteins that influence differentiation of human embryonic stem cells to the definitive endoderm lineage. The percentage of definitive endoderm cells after differentiation on collagen I and fibronectin was >85% and 65%, respectively. The cells on collagen I substrates displayed different morphology and gene expression during differentiation as assessed by time lapse studies compared to cells on the other tested substrates. Global gene expression analysis showed that cells differentiated on collagen I were largely similar to cells on fibronectin after completed differentiation. Collectively, the data suggest that collagen I induces a more rapid and consistent differentiation of stem cells to definitive endoderm. The results shed light on the importance of extracellular matrix proteins for differentiation and also points to a cost effective and easy method to improve differentiation

Using Polarized Spectroscopy to Investigate Order in Thin-Films of Ionic Self-Assembled Materials Based on Azo-Dyes

Three series of ionic self-assembled materials based on anionic azo-dyes and cationic benzalkonium surfactants were synthesized and thin films were prepared by spin-casting. These thin films appear isotropic when investigated with polarized optical microscopy, although they are highly anisotropic. Here, three series of homologous materials were studied to rationalize this observation. Investigating thin films of ordered molecular materials relies to a large extent on advanced experimental methods and large research infrastructure. A statement that in particular is true for thin films with nanoscopic order, where X-ray reflectometry, X-ray and neutron scattering, electron microscopy and atom force microscopy (AFM) has to be used to elucidate film morphology and the underlying molecular structure. Here, the thin films were investigated using AFM, optical microscopy and polarized absorption spectroscopy. It was shown that by using numerical method for treating the polarized absorption spectroscopy data, the molecular structure can be elucidated. Further, it was shown that polarized optical spectroscopy is a general tool that allows determination of the molecular order in thin films. Finally, it was found that full control of thermal history and rigorous control of the ionic self-assembly conditions are required to reproducibly make these materials of high nanoscopic order. Similarly, the conditions for spin-casting are shown to be determining for the overall thin film morphology, while molecular order is maintained

Increased Time in Range and Fewer Missed Bolus Injections After Introduction of a Smart Connected Insulin Pen

Background: This observational study investigated whether the connected NovoPen® 6 could influence insulin regimen management and glycemic control in people with type 1 diabetes (T1D) using a basal-bolus insulin regimen and continuous glucose monitoring in a real-world setting. Methods: Participants from 12 Swedish diabetes clinics downloaded pen data at each visit (final cohort: n = 94). Outcomes included time in range (TIR; sensor glucose 3.9-10.0 mmol/L), time in hyperglycemia (>10 mmol/L), and hypoglycemia (L1: 3.0- <3.9 mmol/L; L2: <3.0 mmol/L). Missed bolus dose (MBD) injections were meals without bolus injection within -15 and +60 min from the start of a meal. Outcomes were compared between the baseline and follow-up periods (≥5 health care professional visits). Data were analyzed from the first 14 days following each visit. For the TIR and total insulin dose analyses (n = 94), a linear mixed model was used, and for the MBD analysis (n = 81), a mixed Poisson model was used. Results: TIR significantly increased (+1.9 [0.8; 3.0]95% CI h/day; P < 0.001) from baseline to follow-up period, with a corresponding reduction in time in hyperglycemia (-1.8 [-3.0; -0.6]95% CI h/day; P = 0.003) and L2 hypoglycemia (-0.3 [-0.6; -0.1]95% CI h/day; P = 0.005), and no change in time in L1 hypoglycemia. MBD injections decreased by 43% over the study (P = 0.002). Change in MBD injections corresponded to a decrease from 25% to 14% based on the assumption that participants had three main meals per day. Conclusions: Our study highlights the potential benefit on glycemic control and dosing behavior when reliable insulin dose data from a connected pen contribute to insulin management in people with T1D

Associations of bolus insulin injection frequency and smart pen engagement with glycaemic control in people living with type 1 diabetes

Aim To evaluate whether both bolus insulin injection frequency and smart pen engagement were associated with changes in glycaemic control, using real-world data from adults with type 1 diabetes (T1D). Materials and Methods Adults using a smart pen (NovoPen 6) to administer bolus insulin (fast-acting insulin aspart or insulin aspart) alongside continuous glucose monitoring were eligible for inclusion. Smart pen engagement was characterized by number of days with pen data uploads over the previous 14 days. Glycaemic control was evaluated by analysing glucose metrics. Results Overall, data from 1194 individuals were analysed. The number of daily bolus injections was significantly associated with time in range (TIR; 3.9-10.0 mmol/L [70-180 mg/dL]; P < 0.0001). Individuals administering, on average, three daily bolus insulin injections had an estimated 11% chance of achieving >70% TIR. The probability of achieving >70% TIR increased with the mean number of daily bolus injections. However, the percentage of TIR was lower on days when individuals administered higher-than-average numbers of injections. The observed mean number of daily bolus injections administered across the study population was lower than the optimal number required to reach glycaemic targets (4.8 injections vs. 6-8 injections). Smart pen engagement was significantly associated with improved TIR. Conclusions Glycaemic control was associated with daily bolus insulin injection frequency and smart pen engagement. A treatment regimen combining an optimal bolus injection strategy, and effective smart pen engagement, may improve glycaemic control among adults with T1D

Model Identification Using Stochastic Differential Equation Grey-Box Models in Diabetes

BACKGROUND: The acceptance of virtual preclinical testing of control algorithms is growing and thus also the need for robust and reliable models. Models based on ordinary differential equations (ODEs) can rarely be validated with standard statistical tools. Stochastic differential equations (SDEs) offer the possibility of building models that can be validated statistically and that are capable of predicting not only a realistic trajectory, but also the uncertainty of the prediction. In an SDE, the prediction error is split into two noise terms. This separation ensures that the errors are uncorrelated and provides the possibility to pinpoint model deficiencies. METHODS: An identifiable model of the glucoregulatory system in a type 1 diabetes mellitus (T1DM) patient is used as the basis for development of a stochastic-differential-equation-based grey-box model (SDE-GB). The parameters are estimated on clinical data from four T1DM patients. The optimal SDE-GB is determined from likelihood-ratio tests. Finally, parameter tracking is used to track the variation in the “time to peak of meal response” parameter. RESULTS: We found that the transformation of the ODE model into an SDE-GB resulted in a significant improvement in the prediction and uncorrelated errors. Tracking of the “peak time of meal absorption” parameter showed that the absorption rate varied according to meal type. CONCLUSIONS: This study shows the potential of using SDE-GBs in diabetes modeling. Improved model predictions were obtained due to the separation of the prediction error. SDE-GBs offer a solid framework for using statistical tools for model validation and model development

Brain proteome profiling implicates the complement and coagulation cascade in multiple system atrophy brain pathology

BACKGROUND: Multiple system atrophy (MSA) is a rare, progressive, neurodegenerative disorder presenting glia pathology. Still, disease etiology and pathophysiology are unknown, but neuro-inflammation and vascular disruption may be contributing factors to the disease progression. Here, we performed an ex vivo deep proteome profiling of the prefrontal cortex of MSA patients to reveal disease-relevant molecular neuropathological processes. Observations were validated in plasma and cerebrospinal fluid (CSF) of novel cross-sectional patient cohorts. METHODS: Brains from 45 MSA patients and 30 normal controls (CTRLs) were included. Brain samples were homogenized and trypsinized for peptide formation and analyzed by high-performance liquid chromatography tandem mass spectrometry (LC–MS/MS). Results were supplemented by western blotting, immuno-capture, tissue clearing and 3D imaging, immunohistochemistry and immunofluorescence. Subsequent measurements of glial fibrillary acid protein (GFAP) and neuro-filament light chain (NFL) levels were performed by immunoblotting in plasma of 20 MSA patients and 20 CTRLs. Finally, we performed a proteome profiling of 144 CSF samples from MSA and CTRLs, as well as other parkinsonian disorders. Data were analyzed using relevant parametric and non-parametric two-sample tests or linear regression tests followed by post hoc tests corrected for multiple testing. Additionally, high-throughput bioinformatic analyses were applied. RESULTS: We quantified more than 4,000 proteins across samples and identified 49 differentially expressed proteins with significantly different abundances in MSA patients compared with CTRLs. Pathway analyses showed enrichment of processes related to fibrinolysis and complement cascade activation. Increased fibrinogen subunit β (FGB) protein levels were further verified, and we identified an enriched recognition of FGB by IgGs as well as intra-parenchymal accumulation around blood vessels. We corroborated blood–brain barrier leakage by a significant increase in GFAP and NFL plasma levels in MSA patients that correlated to disease severity and/or duration. Proteome profiling of CSF samples acquired during the disease course, confirmed increased total fibrinogen levels and immune-related components in the soluble fraction of MSA patients. This was also true for the other atypical parkinsonian disorders, dementia with Lewy bodies and progressive supra-nuclear palsy, but not for Parkinson’s disease patients. CONCLUSION: Our results implicate activation of the fibrinolytic cascade and immune system in the brain as contributing factors in MSA associated with a more severe disease course. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00018-022-04378-z