| 51. |
- Battaglia, Manuela, et al.
(författare)
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Understanding and preventing type 1 diabetes through the unique working model of TrialNet
- 2017
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 60:11, s. 2139-2147
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Tidskriftsartikel (refereegranskat)abstract
- Type 1 diabetes is an autoimmune disease arising from the destruction of pancreatic insulin-producing beta cells. The disease represents a continuum, progressing sequentially at variable rates through identifiable stages prior to the onset of symptoms, through diagnosis and into the critical periods that follow, culminating in a variable depth of beta cell depletion. The ability to identify the very earliest of these presymptomatic stages has provided a setting in which prevention strategies can be trialled, as well as furnishing an unprecedented opportunity to study disease evolution, including intrinsic and extrinsic initiators and drivers. This niche opportunity is occupied by Type 1 Diabetes TrialNet, an international consortium of clinical trial centres that leads the field in intervention and prevention studies, accompanied by deep longitudinal bio-sampling. In this review, we focus on discoveries arising from this unique bioresource, comprising more than 70,000 samples, and outline the processes and science that have led to new biomarkers and mechanistic insights, as well as identifying new challenges and opportunities. We conclude that via integration of clinical trials and mechanistic studies, drawing in clinicians and scientists and developing partnership with industry, TrialNet embodies an enviable and unique working model for understanding a disease that to date has no cure and for designing new therapeutic approaches.
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| 52. |
- Bediaga, Naiara G, et al.
(författare)
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Simplifying prediction of disease progression in pre-symptomatic type 1 diabetes using a single blood sample
- 2021
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 64:11, s. 2432-2444
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Tidskriftsartikel (refereegranskat)abstract
- AIMS/HYPOTHESIS: Accurate prediction of disease progression in individuals with pre-symptomatic type 1 diabetes has potential to prevent ketoacidosis and accelerate development of disease-modifying therapies. Current tools for predicting risk require multiple blood samples taken during an OGTT. Our aim was to develop and validate a simpler tool based on a single blood draw.METHODS: Models to predict disease progression using a single OGTT time point (0, 30, 60, 90 or 120 min) were developed using TrialNet data collected from relatives with type 1 diabetes and validated in independent populations at high genetic risk of type 1 diabetes (TrialNet, Diabetes Prevention Trial-Type 1, The Environmental Determinants of Diabetes in the Young [1]) and in a general population of Bavarian children who participated in Fr1da.RESULTS: Cox proportional hazards models combining plasma glucose, C-peptide, sex, age, BMI, HbA1c and insulinoma antigen-2 autoantibody status predicted disease progression in all populations. In TrialNet, the AUC for receiver operating characteristic curves for models named M60, M90 and M120, based on sampling at 60, 90 and 120 min, was 0.760, 0.761 and 0.745, respectively. These were not significantly different from the AUC of 0.760 for the gold standard Diabetes Prevention Trial Risk Score, which requires five OGTT blood samples. In TEDDY, where only 120 min blood sampling had been performed, the M120 AUC was 0.865. In Fr1da, the M120 AUC of 0.742 was significantly greater than the M60 AUC of 0.615.CONCLUSIONS/INTERPRETATION: Prediction models based on a single OGTT blood draw accurately predict disease progression from stage 1 or 2 to stage 3 type 1 diabetes. The operational simplicity of M120, its validity across different at-risk populations and the requirement for 120 min sampling to stage type 1 diabetes suggest M120 could be readily applied to decrease the cost and complexity of risk stratification.
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| 53. |
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| 54. |
- Berne, Olivier, et al.
(författare)
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PDRs4All : A JWST Early Release Science Program on Radiative Feedback from Massive Stars
- 2022
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Ingår i: Publications of the Astronomical Society of the Pacific. - : IOP Publishing. - 0004-6280 .- 1538-3873. ; 134:1035
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Tidskriftsartikel (refereegranskat)abstract
- Massive stars disrupt their natal molecular cloud material through radiative and mechanical feedback processes. These processes have profound effects on the evolution of interstellar matter in our Galaxy and throughout the universe, from the era of vigorous star formation at redshifts of 1-3 to the present day. The dominant feedback processes can be probed by observations of the Photo-Dissociation Regions (PDRs) where the far-ultraviolet photons of massive stars create warm regions of gas and dust in the neutral atomic and molecular gas. PDR emission provides a unique tool to study in detail the physical and chemical processes that are relevant for most of the mass in inter- and circumstellar media including diffuse clouds, proto-planetary disks, and molecular cloud surfaces, globules, planetary nebulae, and star-forming regions. PDR emission dominates the infrared (IR) spectra of star-forming galaxies. Most of the Galactic and extragalactic observations obtained with the James Webb Space Telescope (JWST) will therefore arise in PDR emission. In this paper we present an Early Release Science program using the MIRI, NIRSpec, and NIRCam instruments dedicated to the observations of an emblematic and nearby PDR: the Orion Bar. These early JWST observations will provide template data sets designed to identify key PDR characteristics in JWST observations. These data will serve to benchmark PDR models and extend them into the JWST era. We also present the Science-Enabling products that we will provide to the community. These template data sets and Science-Enabling products will guide the preparation of future proposals on star-forming regions in our Galaxy and beyond and will facilitate data analysis and interpretation of forthcoming JWST observations.
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| 55. |
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| 56. |
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| 57. |
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| 58. |
- De Beck, Elvire, 1985, et al.
(författare)
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SMA Spectral Line Imaging Survey at 279-355 GHz of the Oxygen-rich AGB Star IK Tau
- 2015
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Ingår i: Astronomical Society of the Pacific Conference Series; Why galaxies care about AGB stars III: A closer look in space and time; Vienna, Austria; Jul 28–Aug 1, 2015. - 9781583818794 ; 497, s. 73-78
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Konferensbidrag (refereegranskat)abstract
- Dedicated, unbiased spectral scans of asymptotic giant branch stars have so far been published only for a few carbon-rich stars, with a strong focus on the nearby and bright IRC +10216. We present results from a spectral survey of the circumstellar envelope of the oxygen-rich AGB star IK Tau obtained with the Submillimeter Array (SMA) at similar to 0 ''.9 angular resolution in the frequency range 279 - 355 GHz, expanding the molecular inventory for M-type evolved stars and filling an observational gap. The survey shows over 140 emission lines, belonging to more than 30 species. The emission of AlO and of several vibrationally excited species traces the acceleration of the wind. Isotopic ratios for carbon, silicon, and sulfur will be derived from the observed emission of isotopologues of CO, SiO, SiS, HCN, SO, and SO2. This will allow us to constrain the AGB nucleosynthesis of IK Tau. We highlight the first detection of PO and PN around an oxygen-rich AGB star, detected at unexpectedly high abundances, and emphasise the importance of unbiased spectral surveys of AGB stars and the need for updated chemical models.
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