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Efficacy and safety of advanced hybrid closed loop systems in children with type 1 diabetes younger than 6 years

• Authors : Novella Rapini; Mariangela Martino; Claudia Arnaldi

Subjects: T1D (type 1 diabetes); CSII (continuous subcutaneous insulin infusion); children

• Source: Frontiers in Endocrinology, Vol 15 (2024)

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Editorial: Endocrine consequences in children due to the COVID-19 pandemic social behavior changes

• Authors : Guilherme Guaragna-Filho; Stefano Stagi

Subjects: endocrine disorders; COVID - 19; precocious puberty

• Source: Frontiers in Endocrinology, Vol 14 (2023)

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ADAR1-dependent editing regulates human β cell transcriptome diversity during inflammation

• Authors : Florian Szymczak; Roni Cohen-Fultheim; Sofia Thomaidou

Subjects: beta cell (β cell); inflammation; T1D (type 1 diabetes)

• Source: Frontiers in Endocrinology, Vol 13 (2022)

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Gut microbiome and metabolic activity in type 1 diabetes: An analysis based on the presence of GADA

• Authors : Sihui Luo; Tong Yue; Ziyu Liu

Subjects: T1D (type 1 diabetes); GADA; gut microbiome

• Source: Frontiers in Endocrinology, Vol 13 (2022)

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Host-microbiota interactions shaping T-cell response and tolerance in type 1 diabetes

• Authors : Shubhabrata Majumdar; Yong Lin; Matthew L. Bettini

Subjects: mimicry; T1D (type 1 diabetes); microbiota

• Source: Frontiers in Immunology, Vol 13 (2022)

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The long and winding road: From mouse linkage studies to a novel human therapeutic pathway in type 1 diabetes

• Authors : Manuel Rojas; Luke S. Heuer; Weici Zhang

Subjects: NOD; T1D (type 1 diabetes); t cell

• Source: Frontiers in Immunology, Vol 13 (2022)

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Editorial: Beta-Cell Fate: From Gene Circuits to Disease Mechanisms

• Authors : Luiza Ghila; Kenichiro Furuyama; Shane T. Grey

Subjects: MODY (mature onset diabetes of the young); T1D (type 1 diabetes); T2D (type 2 diabetes)

• Source: Frontiers in Genetics, Vol 13 (2022)

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Altered Tim-1 and IL-10 Expression in Regulatory B Cell Subsets in Type 1 Diabetes

• Authors : Yikai Liu; Zhiying Chen; Junlin Qiu

Subjects: Tim-1; IL-10; T1D (type 1 diabetes)

• Source: Frontiers in Immunology, Vol 12 (2021)

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Figure 7. Top five HLA-restricted clusters (continued on following page). ; Details on the TCR sequences, occurrence patterns, and annotations for the five most significant clusters (labeled 1–5 in Figure 6) based on size and TCR co-occurrence scores. Each panel consists of a TCRdist dendrogram (left side, labeled with annotation, CDR3 sequence, and occurrence counts for the member TCRs) and a per-subject TCR count profile (right side) showing the aggregate occurrence pattern of the member TCRs (blue curve) and a control pattern (green curve) produced by averaging occurrence counts from multiple independent randomizations of the subject set for each TCR. The numbers in the two ‘Counts’ columns represent the number of HLA+ (left) and HLA- (right) subjects whose repertoire contained the corresponding TCR, where HLA± means positive/negative for the restricting allele (for example, A*24:02 in the case of cluster 1). Annotations use the following abbreviations: B19 (parvovirus B19), INF (influenza virus), YFV (yellow fever virus), MELA (melanoma), T1D (type 1 diabetes), EBV (Epstein-Barr virus), RA (rheumatoid arthritis). In cases where the peptide epitope for the annotation match is known, the first three peptide amino acids are given after ‘-p’. Non-germline CDR3 amino acids with 2 or 3 non-templated nucleotides in their codon are shown in uppercase, while amino acids with only a single non-templated coding nucleotide are shown in lowercase.

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DataSheet_1_Gut microbiome and metabolic activity in type 1 diabetes: An analysis based on the presence of GADA.docx

• Authors : Sihui Luo; Tong Yue; Ziyu Liu

Subjects: Endocrinology; Reproduction; Cell Metabolism

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