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The aim of this study was to investigate whether treatment with rapamycin plus vildagliptin restores β-cell function in patients with long-standing type 1 diabetes.

A phase 2, single-center, randomized, double-blind, placebo-controlled study was conducted in long-standing type 1 diabetes patients randomly assigned (111) to 4 weeks of rapamycin (group 2), 4 weeks of rapamycin plus 12 weeks of vildagliptin (group 3), or double placebo (group 1). The primary outcome was the proportion of participants with a positive response to the Mixed-Meal Tolerance Test (C-peptide at 90 minutes > 0.2 nmol/L) at weeks 4 and 12. Secondary end points included insulin requirement, standard measures of glycemic control, and hormonal and immunological profile.

Fifty-five patients were randomly assigned to group 1 (n = 18), group 2 (n = 19), or group 3 (n = 18). No patient in any group showed a positive C-peptide response, and there was no significant difference at 4 and 12 weeks for the primary outcome. At 4 weeks, insulin requirement decreased from 0.54 to 0.48 U/kg/day in group 2 (P = .013), from 0.59 to 0.51 U/kg/day in group 3 (P < .001), whereas it did not change in group 1. At 12 weeks, glycated hemoglobin significantly decreased both in group 2 (from 7.3% [56 mmol/mol] to 7% [53 mmol/mol]; P = .045] and in group 3 (from 7.2% [55.5 mmol/mol] to 6.9% [52 mmol/mol]; P = .001]. Rapamycin treatment was associated with a decrease in insulin antibody titer and changes in hormonal/immunological profile.

Rapamycin reduced insulin requirement, but did not restore β-cell function in patients with long-standing type 1 diabetes.

Rapamycin reduced insulin requirement, but did not restore β-cell function in patients with long-standing type 1 diabetes.

The ketogenic diet is associated with progressive skeletal demineralization, hypercalciuria, and nephrolithiasis. Acute hypercalcemia has been described as a newly recognized complication of this treatment.

To describe the clinical characteristics of acute hypercalcemia in children on the ketogenic diet through analysis of the presentation, response to treatment, and natural history in a large cohort of patients.

A multicenter case series was performed including children who developed acute hypercalcemia while treated with the ketogenic diet. Information on clinical presentation, treatment, and course of this complication was collated centrally.

There were 14 patients (median (range) age 6.3 (0.9 to 18) years) who developed hypercalcemia 2.1 (range, 0.2-12) years after starting the ketogenic diet. All had low levels of parathyroid hormone and levels of 1,25-dihydroxyvitamin D were low in all except one. Seven (50%) had impaired renal function at presentation. All except the 2 oldest had low alkaline pcemia.We present here the first evidence of the much-predicted double dissociation between the effect of stress on cognitive skills [executive functions (EFs)] dependent on prefrontal cortex (PFC) by catechol-O-methyltransferase (COMT) genotype. The COMT gene polymorphism with methionine (Met) at codon 158 results in more dopamine (DA) in PFC and generally better EFs, while with valine (Val) at codon 158 the result is less PFC DA and generally poorer EFs. Many have predicted that mild stress, by raising PFC DA levels should aid EFs of COMT-Vals (bringing their PFC DA levels up, closer to optimal) and impair EFs of COMT-Mets (raising their PFC DA levels past optimal). We tested 140 men and women in a within-subject crossover design using extremely mild social evaluative stress. On trials requiring EFs (incongruent trials) of the Flanker/Reverse Flanker task, COMT-Val158 homozygotes performed better when mildly stressed than when calmer, while COMT-Met158 carriers performed worse when mildly stressed. Two other teams previously tried to obtain this, but only found stress impairing EFs of COMT-Mets, not improving EFs of COMT-Vals. Perhaps we found both because we used a much milder stressor. Evidently, the bandwidth for stress having a facilitative effect on EFs is exceedingly narrow.

Single-cell RNA sequencing is a powerful technology to discover new cell types and study biological processes in complex biological samples. A current challenge is to predict transcription factor (TF) regulation from single-cell RNA data.

Here, we propose a novel approach for predicting gene expression at the single-cell level using cis-regulatory motifs, as well as epigenetic features. buy Lithocholic acid We designed a tree-guided multi-task learning framework that considers each cell as a task. Through this framework we were able to explain the single-cell gene expression values using either TF binding affinities or TF ChIP-seq data measured at specific genomic regions. TFs identified using these models could be validated by the literature.

Our proposed method allows us to identify distinct TFs that show cell type-specific regulation. This approach is not limited to TFs but can use any type of data that can potentially be used in explaining gene expression at the single-cell level to study factors that drive differentiation or show abnormal regulation in disease. The implementation of our workflow can be accessed under an MIT license via https//github.com/SchulzLab/Triangulate.

Our proposed method allows us to identify distinct TFs that show cell type-specific regulation. This approach is not limited to TFs but can use any type of data that can potentially be used in explaining gene expression at the single-cell level to study factors that drive differentiation or show abnormal regulation in disease. The implementation of our workflow can be accessed under an MIT license via https//github.com/SchulzLab/Triangulate.

Lung neuroendocrine neoplasms (LNENs) are rare solid cancers, with most genomic studies including a limited number of samples. Recently, generating the first multi-omic dataset for atypical pulmonary carcinoids and the first methylation dataset for large-cell neuroendocrine carcinomas led us to the discovery of clinically relevant molecular groups, as well as a new entity of pulmonary carcinoids (supra-carcinoids).

To promote the integration of LNENs molecular data, we provide here detailed information on data generation and quality control for whole-genome/exome sequencing, RNA sequencing, and EPIC 850K methylation arrays for a total of 84 patients with LNENs. We integrate the transcriptomic data with other previously published data and generate the first comprehensive molecular map of LNENs using the Uniform Manifold Approximation and Projection (UMAP) dimension reduction technique. We show that this map captures the main biological findings of previous studies and can be used as reference to integrate datasets for which RNA sequencing is available.

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