{"entity": "researcher", "timestamp": "2026-05-17T08:31:19.839Z", "family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "affiliations": ["Science for Life Laboratory, Department of Medical Cell Biology, Uppsala University, Uppsala, Sweden.", "Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9"}}, "publications": [{"entity": "publication", "iuid": "1ba7fd6cb1ad418a8d2424eb3f428b41", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/1ba7fd6cb1ad418a8d2424eb3f428b41.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/1ba7fd6cb1ad418a8d2424eb3f428b41"}}, "title": "Continuous Glucose Monitoring Data Analysis 2.0: Functional Data Pattern Recognition and Artificial Intelligence Applications.", "authors": [{"family": "Klonoff", "given": "David C", "initials": "DC", "orcid": "0000-0001-6394-6862", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b36d43c70e014d56992ea3e632e9ddd2.json"}}, {"family": "Bergenstal", "given": "Richard M", "initials": "RM", "orcid": "0000-0002-9050-5584", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2a986139d3454e769a8e8a3d511a6814.json"}}, {"family": "Cengiz", "given": "Eda", "initials": "E", "orcid": "0000-0001-7992-9506", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/04b39ee3dc094300965e009119e305da.json"}}, {"family": "Clements", "given": "Mark A", "initials": "MA", "orcid": "0000-0002-2368-0331", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/103c87edaf1144a18b9561e536fc6b83.json"}}, {"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}, {"family": "Espinoza", "given": "Juan", "initials": "J", "orcid": "0000-0003-0513-588X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/49cf03e271774a62be91866c41cd6cea.json"}}, {"family": "Kerr", "given": "David", "initials": "D", "orcid": "0000-0003-1335-1857", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/4bf11388c71641b0bdc17b11338939c2.json"}}, {"family": "Kovatchev", "given": "Boris", "initials": "B", "orcid": "0000-0003-0495-3901", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6a443d17f4f047c98c631a42ddb3c96d.json"}}, {"family": "Maahs", "given": "David M", "initials": "DM", "orcid": "0000-0002-4602-7909", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/56f8e0b30ecf4e6fb3dc952969dc37e3.json"}}, {"family": "Mader", "given": "Julia K", "initials": "JK", "orcid": "0000-0001-7854-4233", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f408de85903b40c49b8b3f15902941e4.json"}}, {"family": "Mathioudakis", "given": "Nestoras", "initials": "N", "orcid": "0000-0002-0210-655X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/959e2ce6ff914d7c88cc12a6f45ab999.json"}}, {"family": "Metwally", "given": "Ahmed A", "initials": "AA", "orcid": "0000-0002-0155-7412", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/42342bc2dcec4678be62cbfe6001b9e4.json"}}, {"family": "Shah", "given": "Shahid N", "initials": "SN", "orcid": "0000-0001-8481-6493", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/49966506e0b9485f9a833e7e898d7ef4.json"}}, {"family": "Sheng", "given": "Bin", "initials": "B", "orcid": "0000-0001-8678-2784", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b257f1a620534164a5a25c0ca14f1db3.json"}}, {"family": "Snyder", "given": "Michael P", "initials": "MP", "orcid": "0000-0003-0784-7987", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ce9e294ff3b64f7caa770c883d12514c.json"}}, {"family": "Umpierrez", "given": "Guillermo", "initials": "G", "orcid": "0000-0002-3252-5026", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/54d359256910489896da5592a286d422.json"}}, {"family": "Shao", "given": "Mandy M", "initials": "MM", "orcid": "0009-0004-9550-9965", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a2c321eae6694c9ca693938ba18c1833.json"}}, {"family": "Scheideman", "given": "Agatha F", "initials": "AF", "orcid": "0009-0008-4211-4934", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ef62d74664a543e8962222e6ab1e4462.json"}}, {"family": "Ayers", "given": "Alessandra T", "initials": "AT", "orcid": "0009-0000-3054-3207", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/95377512fb7141aaac09c9a22d1f9849.json"}}, {"family": "Ho", "given": "Cindy N", "initials": "CN", "orcid": "0009-0008-3067-1004", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/309593d4ec4745a684533f33aa613eae.json"}}, {"family": "Healey", "given": "Elizabeth", "initials": "E", "orcid": "0000-0002-7307-8429", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/076301395f28400da2cdabcacefc9224.json"}}], "type": "journal article", "published": "2025-11-00", "journal": {"title": "J Diabetes Sci Technol", "issn": "1932-2968", "volume": "19", "issue": "6", "pages": "1515-1527", "issn-l": null}, "abstract": "New methods of continuous glucose monitoring (CGM) data analysis are emerging that are valuable for interpreting CGM patterns and underlying metabolic physiology. These new methods use functional data analysis and artificial intelligence (AI), including machine learning (ML). Compared to traditional metrics for evaluating CGM tracing results (CGM Data Analysis 1.0), these new methods, which we refer to as CGM Data Analysis 2.0, can provide a more detailed understanding of glucose fluctuations and trends and enable more personalized and effective diabetes management strategies once translated into practical clinical solutions.", "doi": "10.1177/19322968251353228", "pmid": "40814224", "labels": {"Daniel Espes": null, "SciLifeLab Fellow": null}, "xrefs": [{"db": "pmc", "key": "PMC12356821"}], "notes": [], "created": "2025-12-03T14:54:39.195Z", "modified": "2025-12-03T14:55:21.528Z"}, {"entity": "publication", "iuid": "39af3ce3fcd64d948a39e2a6d00c2423", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/39af3ce3fcd64d948a39e2a6d00c2423.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/39af3ce3fcd64d948a39e2a6d00c2423"}}, "title": "Proximity extension assay inflammatory profiling cannot distinguish the presence of residual C-peptide in patients with long-standing type 1 diabetes.", "authors": [{"family": "Anvari", "given": "Ebrahim", "initials": "E"}, {"family": "Lundkvist", "given": "Per", "initials": "P"}, {"family": "Singh", "given": "Kailash", "initials": "K"}, {"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}], "type": "journal article", "published": "2025-11-00", "journal": {"title": "Acta diabetologica", "issn": "1432-5233", "volume": "62", "issue": "11", "pages": "1987-1996", "issn-l": "0940-5429"}, "abstract": "Many patients with long-standing type 1 diabetes (T1D) have remaining low levels of C-peptide, i.e. and indirect sign of remaining functional beta-cells. This study focused on identifying differences in immunological and inflammatory biomarkers in patients with longstanding T1D and remaining C-peptide.\n\nAdult patients (n = 120) with long-standing T1D (\u2265 10 years) and healthy controls (HC) (n = 50) were recruited at Uppsala University Hospital. Residual beta-cell function was determined with an ultrasensitive C-peptide ELISA under fasting conditions. T1D patients were divided into two groups (C-peptide positive vs. C-peptide negative). Using the OLINK Explore Inflammation proximity extension assay (PEA), 368 circulating immunological and inflammatory biomarkers were analyzed in plasma.\n\nThe three groups could not be distinguished by principal component analysis and when correcting for multiple testing we found no differences in circulating biomarkers. However, based on uncorrected p-values there were six biomarkers that were different when comparing all T1D patients with HC and eight markers that were different when comparing C-peptide positive vs. negative T1D patients.\n\nA wide inflammatory assay analysis cannot distinguish patients with longstanding T1D and remaining C-peptide from patients with a complete loss of C-peptide nor from HC.", "doi": "10.1007/s00592-025-02537-9", "pmid": "40471289", "labels": {"Daniel Espes": null, "SciLifeLab Fellow": null}, "xrefs": [{"db": "pmc", "key": "PMC12640314"}, {"db": "pii", "key": "10.1007/s00592-025-02537-9"}], "notes": [], "created": "2025-12-03T14:54:56.156Z", "modified": "2025-12-03T14:54:56.174Z"}, {"entity": "publication", "iuid": "8bdbf71377e1408ca4afcd26f9bbeb77", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/8bdbf71377e1408ca4afcd26f9bbeb77.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/8bdbf71377e1408ca4afcd26f9bbeb77"}}, "title": "Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes.", "authors": [{"family": "Dawnbringer", "given": "Jeanie", "initials": "J"}, {"family": "Hill", "given": "Henrik", "initials": "H", "orcid": "0000-0003-3549-5093", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d681d424d7f046cf9941e959e0f14674.json"}}, {"family": "Lundgren", "given": "Markus", "initials": "M"}, {"family": "Catrina", "given": "Sergiu-Bogdan", "initials": "SB"}, {"family": "Caballero-Corbalan", "given": "Jos\u00e9", "initials": "J"}, {"family": "Cederblad", "given": "Lars", "initials": "L"}, {"family": "Carlsson", "given": "Per-Ola", "initials": "PO", "orcid": "0000-0002-7666-073X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e0032500b1834f7395ea94b26c2d6244.json"}}, {"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}], "type": "journal article", "published": "2024-09-05", "journal": {"title": "BMJ Open Diabetes Res Care", "issn": "2052-4897", "volume": "12", "issue": "4", "issn-l": null}, "abstract": "Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort.\n\nRetrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB).\n\nThe dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of \u226580 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%).\n\nOur scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.", "doi": "10.1136/bmjdrc-2024-004350", "pmid": "39242123", "labels": {"Daniel Espes": null, "SciLifeLab Fellow": null}, "xrefs": [{"db": "pmc", "key": "PMC11381645"}, {"db": "pii", "key": "12/4/e004350"}], "notes": [], "created": "2024-11-26T19:20:37.074Z", "modified": "2025-04-08T06:09:42.926Z"}, {"entity": "publication", "iuid": "a03f98da2ce149848ac90aea7df2b44a", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/a03f98da2ce149848ac90aea7df2b44a.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/a03f98da2ce149848ac90aea7df2b44a"}}, "title": "Non-invasive imaging of sympathetic innervation of the pancreas in individuals with type 2 diabetes.", "authors": [{"family": "Vyakaranam", "given": "Achyut Ram", "initials": "AR", "orcid": "0000-0002-6754-9853", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/92317febeee94c66b431a397693a1837.json"}}, {"family": "Mahamed", "given": "Maryama M", "initials": "MM"}, {"family": "Hellman", "given": "Per", "initials": "P"}, {"family": "Eriksson", "given": "Olof", "initials": "O", "orcid": "0000-0002-2515-8790", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/85991bf00e4b4a26ab15599d25c58601.json"}}, {"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}, {"family": "Christoffersson", "given": "Gustaf", "initials": "G", "orcid": "0000-0002-9640-9702", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ba43613a321b466f822c516fd8ad0f77.json"}}, {"family": "Sundin", "given": "Anders", "initials": "A"}], "type": "journal article", "published": "2024-01-00", "journal": {"title": "Diabetologia", "issn": "1432-0428", "volume": "67", "issue": "1", "pages": "199-208", "issn-l": "0012-186X"}, "abstract": "Compromised pancreatic sympathetic innervation has been suggested as a factor involved in both immune-mediated beta cell destruction and endocrine dysregulation of pancreatic islets. To further explore these intriguing findings, new techniques for in vivo assessment of pancreatic innervation are required. This is a retrospective study that aimed to investigate whether the noradrenaline (norepinephrine) analogue 11C-hydroxy ephedrine (11C-HED) could be used for quantitative positron emission tomography (PET) imaging of the sympathetic innervation of the human pancreas.\n\nIn 25 individuals with type 2 diabetes and 64 individuals without diabetes, all of whom had previously undergone 11C-HED-PET/CT because of pheochromocytoma or paraganglioma (or suspicion thereof), the 11C-HED standardised uptake value (SUVmean), 11C-HED specific binding index (SBI), pancreatic functional volume (FV, in ml), functional neuronal volume (FNV, calculated as SUVmean \u00d7 FV), specific binding index with functional volume (SBI FV, calculated as SBI \u00d7 FV) and attenuation on CT (HU) were investigated in the entire pancreas, and additionally in six separate anatomical pancreatic regions.\n\nGenerally, 11C-HED uptake in the pancreas was high, with marked individual variation, suggesting variability in sympathetic innervation. Moreover, pancreatic CT attenuation (HU) (p<0.001), 11C-HED SBI (p=0.0049) and SBI FV (p=0.0142) were lower in individuals with type 2 diabetes than in individuals without diabetes, whereas 11C-HED SUVmean (p=0.15), FV (p=0.73) and FNV (p=0.30) were similar.\n\nWe demonstrate the feasibility of using 11C-HED-PET for non-invasive assessment of pancreatic sympathetic innervation in humans. These findings warrant further prospective evaluation, especially in individuals with theoretical defects in pancreatic sympathetic innervation, such as those with type 1 diabetes.", "doi": "10.1007/s00125-023-06039-7", "pmid": "37935826", "labels": {"Gustaf Christoffersson": null, "SciLifeLab Fellow": null, "Daniel Espes": null}, "xrefs": [{"db": "pmc", "key": "PMC10709256"}, {"db": "pii", "key": "10.1007/s00125-023-06039-7"}], "notes": [], "created": "2023-12-01T15:03:07.451Z", "modified": "2025-04-08T06:14:39.137Z"}, {"entity": "publication", "iuid": "82913459313442b888adbec02ab56e07", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/82913459313442b888adbec02ab56e07.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/82913459313442b888adbec02ab56e07"}}, "title": "Classification of Hypoglycemic Events in Type 1 Diabetes Using Machine Learning Algorithms.", "authors": [{"family": "Cederblad", "given": "Lars", "initials": "L"}, {"family": "Eklund", "given": "Gustav", "initials": "G"}, {"family": "Vedal", "given": "Amund", "initials": "A"}, {"family": "Hill", "given": "Henrik", "initials": "H"}, {"family": "Caballero-Corbalan", "given": "Jos\u00e9", "initials": "J"}, {"family": "Hellman", "given": "Jarl", "initials": "J"}, {"family": "Abrahamsson", "given": "Niclas", "initials": "N"}, {"family": "Wahlstr\u00f6m-Johnsson", "given": "Inger", "initials": "I"}, {"family": "Carlsson", "given": "Per-Ola", "initials": "PO"}, {"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}], "type": "journal article", "published": "2023-06-00", "journal": {"title": "Diabetes Ther", "issn": "1869-6953", "volume": "14", "issue": "6", "pages": "953-965", "issn-l": null}, "abstract": "To improve the utilization of continuous- and flash glucose monitoring (CGM/FGM) data we have tested the hypothesis that a machine learning (ML) model can be trained to identify the most likely root causes for hypoglycemic events.\n\nCGM/FGM data were collected from 449 patients with type 1 diabetes. Of the 42,120 identified hypoglycemic events, 5041 were randomly selected for classification by two clinicians. Three causes of hypoglycemia were deemed possible to interpret and later validate by insulin and carbohydrate recordings: (1) overestimated bolus (27%), (2) overcorrection of hyperglycemia (29%) and (3) excessive basal insulin presure (44%). The dataset was split into a training (n = 4026 events, 304 patients) and an internal validation dataset (n = 1015 events, 145 patients). A number of ML model architectures were applied and evaluated. A separate dataset was generated from 22 patients (13 'known' and 9 'unknown') with insulin and carbohydrate recordings. Hypoglycemic events from this dataset were also interpreted by five clinicians independently.\n\nOf the evaluated ML models, a purpose-built convolutional neural network (HypoCNN) performed best. Masking the time series, adding time features and using class weights improved the performance of this model, resulting in an average area under the curve (AUC) of 0.921 in the original train/test split. In the dataset validated by insulin and carbohydrate recordings (n = 435 events), i.e. 'ground truth,' our HypoCNN model achieved an AUC of 0.917.\n\nThe findings support the notion that ML models can be trained to interpret CGM/FGM data. Our HypoCNN model provides a robust and accurate method to identify root causes of hypoglycemic events.", "doi": "10.1007/s13300-023-01403-7", "pmid": "37052842", "labels": {"SciLifeLab Fellow": null, "Daniel Espes": null}, "xrefs": [{"db": "pmc", "key": "PMC10203083"}, {"db": "pii", "key": "10.1007/s13300-023-01403-7"}], "notes": [], "created": "2023-12-04T14:02:13.007Z", "modified": "2023-12-04T14:02:13.089Z"}, {"entity": "publication", "iuid": "3b86a46235f3427c8579b49d1b486de4", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/3b86a46235f3427c8579b49d1b486de4.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/3b86a46235f3427c8579b49d1b486de4"}}, "title": "Higher risk of severe hypoglycemia in children and adolescents with a rapid loss of C-peptide during the first 6 years after type 1 diabetes diagnosis.", "authors": [{"family": "Gr\u00f6nberg", "given": "Annika", "initials": "A", "orcid": "0000-0002-8502-8568", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0442565cd22a4d2e917c8649acc659da.json"}}, {"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}, {"family": "Carlsson", "given": "Per-Ola", "initials": "PO", "orcid": "0000-0002-7666-073X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e0032500b1834f7395ea94b26c2d6244.json"}}, {"family": "Ludvigsson", "given": "Johnny", "initials": "J"}], "type": "journal article", "published": "2022-11-00", "journal": {"title": "BMJ Open Diabetes Res Care", "issn": "2052-4897", "issn-l": null, "volume": "10", "issue": "6", "pages": "e002991"}, "abstract": "The progression to insulin deficiency in type 1 diabetes is heterogenous. This study aimed to identify early characteristics associated with rapid or slow decline of beta-cell function and how it affects the clinical course.\n\nStimulated C-peptide was assessed by mixed meal tolerance test in 50 children (<18 years) during 2004-2017, at regular intervals for 6 years from type 1 diabetes diagnosis. 40% of the children had a rapid decline of stimulated C-peptide defined as no measurable C-peptide (<0.03 nmol/L) 30 months after diagnosis.\n\nAt diagnosis, higher frequencies of detectable glutamic acid decarboxylase antibodies (GADA) and IA-2A (p=0.027) were associated with rapid loss of beta-cell function. C-peptide was predicted positively by age at 18 months (p=0.017) and 30 months duration (p=0.038). BMI SD scores (BMISDS) at diagnosis predicted higher C-peptide at diagnosis (p=0.006), 3 months (p=0.002), 9 months (p=0.005), 30 months (p=0.022), 3 years (p=0.009), 4 years (p=0.016) and 6 years (p=0.026), whereas high HbA1c and blood glucose at diagnosis predicted a lower C-peptide at diagnosis (p=<0.001) for both comparisons. Both GADA and IA-2A were negative predictors of C-peptide at 9 months (p=0.011), 18 months (p=0.008) and 30 months (p<0.001). Ten children had 22 events of severe hypoglycemia, and they had lower mean C-peptide at 18 months (p=0.025), 30 months (p=0.008) and 6 years (p=0.018) compared with others. Seven of them had a rapid decline of C-peptide (p=0.030), and the odds to experience a severe hypoglycemia were nearly fivefold increased (OR=4.846, p=0.04).\n\nLow age and presence of multiple autoantibodies at diagnosis predicts a rapid loss of beta-cell function in children with type 1 diabetes. Low C-peptide is associated with an increased risk of severe hypoglycemia and higher Hemoglobin A1C. A high BMISDS at diagnosis is predictive of remaining beta-cell function during the 6 years of follow-up.", "doi": "10.1136/bmjdrc-2022-002991", "pmid": "36384886", "labels": {"SciLifeLab Fellow": null, "Daniel Espes": null}, "xrefs": [{"db": "pmc", "key": "PMC9670837"}, {"db": "pii", "key": "10/6/e002991"}], "notes": [], "created": "2022-12-01T09:51:13.877Z", "modified": "2025-04-29T07:07:31.732Z"}, {"entity": "publication", "iuid": "7b787e6299764e628398864baab2c592", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/7b787e6299764e628398864baab2c592.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/7b787e6299764e628398864baab2c592"}}, "title": "Pregnancy induces pancreatic insulin secretion in women with long-standing type 1 diabetes.", "authors": [{"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}, {"family": "Magnusson", "given": "Louise", "initials": "L"}, {"family": "Caballero-Corbalan", "given": "Jos\u00e9", "initials": "J"}, {"family": "Schwarcz", "given": "Erik", "initials": "E"}, {"family": "Casas", "given": "Rosaura", "initials": "R"}, {"family": "Carlsson", "given": "Per-Ola", "initials": "PO", "orcid": "0000-0002-7666-073X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e0032500b1834f7395ea94b26c2d6244.json"}}], "type": "journal article", "published": "2022-11-00", "journal": {"title": "BMJ Open Diabetes Res Care", "issn": "2052-4897", "volume": "10", "issue": "6", "issn-l": null}, "abstract": "Pregnancy entails both pancreatic adaptations with increasing \u03b2-cell mass and immunological alterations in healthy women. In this study, we have examined the effects of pregnancy on \u03b2-cell function and immunological processes in long-standing type 1 diabetes (L-T1D).\n\nFasting and stimulated C-peptide were measured after an oral glucose tolerance test in pregnant women with L-T1D (n=17) during the first trimester, third trimester, and 5-8 weeks post partum. Two 92-plex Olink panels were used to measure proteins in plasma. Non-pregnant women with L-T1D (n=30) were included for comparison.\n\nFasting C-peptide was detected to a higher degree in women with L-T1D during gestation and after parturition (first trimester: 64.7%, third trimester: 76.5%, and post partum: 64.7% vs 26.7% in non-pregnant women). Also, total insulin secretion and peak C-peptide increased during pregnancy. The plasma protein levels in pregnant women with L-T1D was dynamic, but few analytes were functionally related. Specifically, peripheral levels of prolactin (PRL), prokineticin (PROK)-1, and glucagon (GCG) were elevated during gestation whereas levels of proteins related to leukocyte migration (CCL11), T cell activation (CD28), and antigen presentation (such as CD83) were reduced.\n\nIn summary, we have found that some C-peptide secretion, that is, an indirect measurement of endogenous insulin production, is regained in women with L-T1D during pregnancy, which might be attributed to elevated peripheral levels of PRL, PROK-1, or GCG.", "doi": "10.1136/bmjdrc-2022-002948", "pmid": "36351678", "labels": {"SciLifeLab Fellow": null, "Daniel Espes": null}, "xrefs": [{"db": "pmc", "key": "PMC9644305"}, {"db": "pii", "key": "10/6/e002948"}], "notes": [], "created": "2022-12-01T09:34:06.646Z", "modified": "2025-04-29T07:08:15.392Z"}, {"entity": "publication", "iuid": "5746439069a04713b8d3624ed7b71f4d", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/5746439069a04713b8d3624ed7b71f4d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/5746439069a04713b8d3624ed7b71f4d"}}, "title": "Longitudinal Assessment of 11C-5-Hydroxytryptophan Uptake in Pancreas After Debut of Type 1 Diabetes.", "authors": [{"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}, {"family": "Carlsson", "given": "Per-Ola", "initials": "PO", "orcid": "0000-0002-7666-073X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e0032500b1834f7395ea94b26c2d6244.json"}}, {"family": "Selvaraju", "given": "Ram Kumar", "initials": "RK"}, {"family": "Rosestedt", "given": "Maria", "initials": "M"}, {"family": "Cheung", "given": "Pierre", "initials": "P"}, {"family": "Ahlstr\u00f6m", "given": "H\u00e5kan", "initials": "H"}, {"family": "Korsgren", "given": "Olle", "initials": "O", "orcid": "0000-0002-8524-9547", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f4f384eeb31a4b2dba5c9301bb34c156.json"}}, {"family": "Eriksson", "given": "Olof", "initials": "O", "orcid": "0000-0002-2515-8790", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/85991bf00e4b4a26ab15599d25c58601.json"}}], "type": "journal article", "published": "2021-04-00", "journal": {"title": "Diabetes", "issn": "1939-327X", "volume": "70", "issue": "4", "pages": "966-975", "issn-l": "0012-1797"}, "abstract": "The longitudinal alterations of the pancreatic \u03b2-cell and islet mass in the progression of type 1 diabetes (T1D) are still poorly understood. The objective of this study was to repeatedly assess the endocrine volume and the morphology of the pancreas for up to 24 months after T1D diagnosis (n = 16), by 11C-5-hydroxytryptophan (11C-5-HTP) positron emission tomography (PET) and MRI. Study participants were examined four times by PET/MRI: at recruitment and then after 6, 12, and 24 months. Clinical examinations and assessment of \u03b2-cell function by a mixed-meal tolerance test and fasting blood samples were performed in connection with the imaging examination. Pancreas volume has a tendency to decrease from 50.2 \u00b1 10.3 mL at T1D debut to 42.2 \u00b1 14.6 mL after 24 months (P < 0.098). Pancreas uptake of 11C-5-HTP (e.g., the volume of the endocrine pancreas) did not decrease from T1D diagnosis (0.23 \u00b1 0.10 % of injected dose) to 24-month follow-up, 0.21 \u00b1 0.14% of injected dose, and exhibited low interindividual changes. Pancreas perfusion was unchanged from diagnosis to 24-month follow-up. The pancreas uptake of 11C-5-HTP correlated with the long-term metabolic control as estimated by HbA1c (P < 0.05). Our findings argue against a major destruction of \u03b2-cell or islet mass in the 2-year period after diagnosis of T1D.", "doi": "10.2337/db20-0776", "pmid": "33479059", "labels": {"SciLifeLab Fellow": null, "Olof Eriksson": null}, "xrefs": [{"db": "pii", "key": "db20-0776"}], "notes": [], "created": "2023-05-14T14:53:36.004Z", "modified": "2023-05-14T14:53:36.080Z"}, {"entity": "publication", "iuid": "828640fda961421082598ddb6c3a6cc6", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/828640fda961421082598ddb6c3a6cc6.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/828640fda961421082598ddb6c3a6cc6"}}, "title": "Dosimetry of [(68)Ga]Ga-DO3A-VS-Cys(40)-Exendin-4 in rodents, pigs, non-human primates and human - repeated scanning in human is possible.", "authors": [{"family": "Selvaraju", "given": "Ram Kumar", "initials": "RK"}, {"family": "Bulenga", "given": "Thomas N", "initials": "TN"}, {"family": "Espes", "given": "Daniel", "initials": "D", "orcid": "0000-0001-8843-7941", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/80736c5043194099992841a2a2a161f9.json"}}, {"family": "Lubberink", "given": "Mark", "initials": "M", "orcid": "0000-0001-8324-7399", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/e8c1d9a8e08a40d3b7a694fd293c2400.json"}}, {"family": "S\u00f6rensen", "given": "Jens", "initials": "J"}, {"family": "Eriksson", "given": "Barbro", "initials": "B"}, {"family": "Estrada", "given": "Sergio", "initials": "S"}, {"family": "Velikyan", "given": "Irina", "initials": "I", "orcid": "0000-0002-3732-8857", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/947ae561cd794e5b94c6736880620287.json"}}, {"family": "Eriksson", "given": "Olof", "initials": "O", "orcid": "0000-0002-2515-8790", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/85991bf00e4b4a26ab15599d25c58601.json"}}], "type": "journal article", "published": "2015-02-15", "journal": {"title": "American journal of nuclear medicine and molecular imaging", "issn": "2160-8407", "volume": "5", "issue": "3", "pages": "259-269", "issn-l": "2160-8407"}, "abstract": "Quantitative PET imaging with [(68)Ga]Ga-DO3A-VS-Cys(40)-Exendin-4 has potential use in diabetes and cancer. However, the radiation dose to the kidneys has been a concern for the possibility of repeated imaging studies in humans. Therefore, we investigated the dosimetry of [(68)Ga]Ga-DO3A-VS-Cys(40)-Exendin-4 based on the biodistribution data in rats, pigs, non-human primates (NHP) and a human.Organ distribution of [(68)Ga]Ga-DO3A-VS-Cys(40)-Exendin-4 in rats (Male Lewis; n=12; 30, 60, and 80 min) was measured ex vivo. The dynamic uptake of [(68)Ga]Ga-DO3A-VS-Cys(40)-Exendin-4 in the abdomen was assessed by PET/CT scanning of pigs (male; n = 4, 0-60 min), NHP (Female; cynomolgus; n=3; 0-90 min), and human (female; n=1; 0-40, 100, 120 min).The organ distribution data in each species were extrapolated to those of a human, assuming similar distribution between the species. Residence times were assessed by trapezoidal approximation of the kinetic data. Organ doses (mGy/MBq) and the whole body effective dose (mSv/MBq), was extrapolated by using the OLINDA/EXM 1.1 software. The extrapolated human whole body effective dose was 0.017 \u00b1 0.004 (rats), 0.014 \u00b1 0.004 (pigs), 0.017 \u00b1 0.004 (NHP), and 0.016 (human) mSv/MBq. The absorbed dose to the kidneys was limiting:0.33 \u00b1 0.06 (rats), 0.28\u00b10.05 (pigs), 0.65 \u00b1 0.11 (NHP), and 0.28 (human) mGy/MBq, which corresponded to the maximum yearly administered amounts of 455 (rat), 536 (pig), 231 (NHP), and 536 (human) MBq before reaching the yearly kidney limiting dose of 150 mGy. More than 200 MBq of [(68)Ga]Ga-DO3A-VS-Cys(40)-Exendin-4 can be administered yearly in a human, allowing for repeated (2-4 times) scanning. This potentially enables longitudinal clinical PET imaging studies of the GLP-1R in the pancreas, transplanted islets, or insulinoma.", "doi": null, "pmid": "26069859", "labels": {"Olof Eriksson": null, "SciLifeLab Fellow": null}, "xrefs": [{"db": "pmc", "key": "PMC4446394"}], "notes": [], "created": "2020-10-06T13:53:32.732Z", "modified": "2025-11-17T09:33:25.651Z"}]}