Publications by authors named "Gabriela Monaco"
Article Synopsis
- Islet autoantibodies are crucial for diagnosing and understanding the variability in type 1 diabetes (T1D) progression and response to treatments.
- A review of 152 studies indicated that the majority focused on autoantibody characteristics before T1D diagnosis, highlighting correlations between autoantibody types, numbers, and disease progression.
- The findings emphasize the need for precise definitions of T1D based on autoantibodies and suggest improving research methods through standardization to enhance the effectiveness of precision medicine in T1D.
Article Synopsis
- Precision medicine is an evolving approach in healthcare that aims to enhance decision-making and health outcomes, particularly in managing diabetes, which poses serious health risks for millions globally.
- The second international consensus report on precision diabetes medicine reviews current findings on prevention, diagnosis, treatment, and prognosis across different forms of diabetes, highlighting the potential for translating research into clinical practice.
- The report also identifies knowledge gaps and sets out key milestones for better clinical implementation, emphasizing the need for standards addressing cost-effectiveness, health equity, and accessibility in treatment options.
Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification.
Methods: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument.
Article Synopsis
- Type 1 diabetes (T1D) is caused by immune system attacks on insulin-producing cells, prompting a need for personalized prevention strategies due to varying disease progression and treatment responses.
- Researchers conducted a systematic review of 75 studies over 25 years focused on therapies for T1D prevention and treatment, but found inconsistencies in how precision analyses were conducted, leading to challenges in clinical application.
- Future studies should ensure well-defined and thorough precision analyses to enhance the understanding and effectiveness of T1D prevention strategies.
Aim/hypothesis: The risk of progressing from autoantibody positivity to type 1 diabetes is inversely related to age. Separately, whether age influences patterns of C-peptide loss or changes in insulin sensitivity in autoantibody-positive individuals who progress to stage 3 type 1 diabetes is unclear.
Methods: Beta cell function and insulin sensitivity were determined by modelling of OGTTs performed in 658 autoantibody-positive participants followed longitudinally in the Diabetes Prevention Trial-Type 1 (DPT-1).
The link between COVID-19 infection and diabetes has been explored in several studies since the start of the pandemic, with associations between comorbid diabetes and poorer prognosis in patients infected with the virus and reports of diabetic ketoacidosis occurring with COVID-19 infection. As such, significant interest has been generated surrounding mechanisms by which the virus may exert effects on the pancreatic β cells. In this review, we consider possible routes by which SARS-CoV-2 may impact β cells.
View Article and Find Full Text PDFThe preservation of mould-ripened salami was investigated during 48 days at 19-20 °C under different packaging conditions: () high barrier film filled with air, 100% N or under vacuum, () biaxially oriented polypropylene film, () microperforated polyethylene film and () unpackaged. Sensory, texture profile, physicochemical and microbiological analyses were performed. Fungal quantification revealed two data groups.
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