CtIP Mutations Cause Seckel and Jawad Syndromes

Seckel syndrome is a recessively inherited dwarfism disorder characterized by microcephaly and a unique head profile. Genetically, it constitutes a heterogeneous condition, with several loci mapped (SCKL1-5) but only three disease genes identified: the ATR, CENPJ, and CEP152 genes that control cellular responses to DNA damage. We previously mapped a Seckel syndrome locus to chromosome 18p11.31-q11.2 (SCKL2). Here, we report two mutations in the CtIP (RBBP8) gene within this locus that result in expression of C-terminally truncated forms of CtIP. We propose that these mutations are the molecular cause of the disease observed in the previously described SCKL2 family and in an additional unrelated family diagnosed with a similar form of congenital microcephaly termed Jawad syndrome. While an exonic frameshift mutation was found in the Jawad family, the SCKL2 family carries a splicing mutation that yields a dominant-negative form of CtIP. Further characterization of cell lines derived from the SCKL2 family revealed defective DNA damage induced formation of single-stranded DNA, a critical co-factor for ATR activation. Accordingly, SCKL2 cells present a lowered apoptopic threshold and hypersensitivity to DNA damage. Notably, over-expression of a comparable truncated CtIP variant in non-Seckel cells recapitulates SCKL2 cellular phenotypes in a dose-dependent manner. This work thus identifies CtIP as a disease gene for Seckel and Jawad syndromes and defines a new type of genetic disease mechanism in which a dominant negative mutation yields a recessively inherited disorder

Fast-Acting Insulin Aspart in Patients with Type 1 Diabetes in Real-World Clinical Practice : A Noninterventional, Retrospective Chart and Database Study

Introduction This study utilized continuous glucose monitoring data to analyze the effects of switching to treatment with fast-acting insulin aspart (faster aspart) in adults with type 1 diabetes (T1D) in clinical practice. Methods A noninterventional database review was conducted in Sweden among adults with T1D using multiple daily injection (MDI) regimens who had switched to treatment with faster aspart as part of basal-bolus treatment. Glycemic data were retrospectively collected during the 26 weeks before switching (baseline) and up to 32 weeks after switching (follow-up) to assess changes in time in glycemic range (TIR; 70–180 mg/dL), mean sensor glucose, glycated hemoglobin (HbA1c) levels, coefficient of variation, time in hyperglycemia (level 1, > 180 to ≤ 250 mg/dL; level 2, > 250 mg/dL), and time in hypoglycemia (level 1, ≥ 54 to < 70 mg/dL; level 2, < 54 mg/dL) (ClinicalTrials.gov Identifier NCT03895515). Results Overall, 178 participants were included in the study cohort. The analysis population included 82 individuals (mean age 48.5 years) with adequate glucose sensor data. From baseline to follow-up, statistically significant improvements were reported for TIR (mean increase 3.3%-points [approximately 48 min/day]; p = 0.006) with clinically relevant improvement (≥ 5%) in 43% of participants. Statistically significant improvements from baseline were observed for mean sensor glucose levels, HbA1c levels, and time in hyperglycemia (levels 1 and 2), with no statistically significant changes in time spent in hypoglycemia. Conclusions Switching to faster aspart was associated with improvements in glycemic control without increasing hypoglycemia in adults with T1D using MDI in this real-world setting

The Adipose Transcriptional Response to Insulin Is Determined by Obesity, Not Insulin Sensitivity

Metabolically healthy obese subjects display preserved insulin sensitivity and a beneficial white adipose tissue gene expression pattern. However, this observation stems from fasting studies when insulin levels are low. We investigated adipose gene expression by 5′Cap-mRNA sequencing in 17 healthy non-obese (NO), 21 insulin-sensitive severely obese (ISO), and 30 insulin-resistant severely obese (IRO) subjects, before and 2 hr into a hyperinsulinemic euglycemic clamp. ISO and IRO subjects displayed a clear but globally similar transcriptional response to insulin, which differed from the small effects observed in NO subjects. In the obese, 231 genes were altered; 71 were enriched in ISO subjects (e.g., phosphorylation processes), and 52 were enriched in IRO subjects (e.g., cellular stimuli). Common cardio-metabolic risk factors and gender do not influence these findings. This study demonstrates that differences in the acute transcriptional response to insulin are primarily driven by obesity per se, challenging the notion of healthy obese adipose tissue, at least in severe obesity

Surgeons' perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey

Background: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume data to inform predictive analytics that supports complex decision-making processes. Time-sensitive trauma and emergency contexts are often challenging. The study aims to investigate trauma and emergency surgeons' knowledge and perception of using AI-based tools in clinical decision-making processes. Methods: An online survey grounded on literature regarding AI-enabled surgical decision-making aids was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was advertised to 917 WSES members through the society's website and Twitter profile. Results: 650 surgeons from 71 countries in five continents participated in the survey. Results depict the presence of technology enthusiasts and skeptics and surgeons' preference toward more classical decision-making aids like clinical guidelines, traditional training, and the support of their multidisciplinary colleagues. A lack of knowledge about several AI-related aspects emerges and is associated with mistrust. Discussion: The trauma and emergency surgical community is divided into those who firmly believe in the potential of AI and those who do not understand or trust AI-enabled surgical decision-making aids. Academic societies and surgical training programs should promote a foundational, working knowledge of clinical AI

Time for a paradigm shift in shared decision-making in trauma and emergency surgery? Results from an international survey

Background Shared decision-making (SDM) between clinicians and patients is one of the pillars of the modern patient-centric philosophy of care. This study aims to explore SDM in the discipline of trauma and emergency surgery, investigating its interpretation as well as the barriers and facilitators for its implementation among surgeons. Methods Grounding on the literature on the topics of the understanding, barriers, and facilitators of SDM in trauma and emergency surgery, a survey was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was sent to all 917 WSES members, advertised through the society’s website, and shared on the society’s Twitter profile. Results A total of 650 trauma and emergency surgeons from 71 countries in five continents participated in the initiative. Less than half of the surgeons understood SDM, and 30% still saw the value in exclusively engaging multidisciplinary provider teams without involving the patient. Several barriers to effectively partnering with the patient in the decision-making process were identified, such as the lack of time and the need to concentrate on making medical teams work smoothly. Discussion Our investigation underlines how only a minority of trauma and emergency surgeons understand SDM, and perhaps, the value of SDM is not fully accepted in trauma and emergency situations. The inclusion of SDM practices in clinical guidelines may represent the most feasible and advocated solutions