PDX1-MODY: A rare missense mutation as a cause of monogenic diabetes

Maturity-Onset Diabetes of the Young type 4 is a rare form of diabetes mellitus, caused by mutations in the PDX1 gene. However, only a few mutations in this gene have been associated as a cause of monogenic diabetes up to date. It makes difficult to create a clinical manifestation profile of this disease and, consequently, to improve the therapeutic management for these patients. Here we report a normal weight woman, diagnosed with diabetes mellitus at 27 years old, during her first pregnancy. At the time of the recruitment, she was 40 years old and had a body mass index of 23.9 kg/m², glycated hemoglobin level of 9.6%, and fasting plasma glucose (FPG) of 254 mg/dL. She presented no diabetic complications and she was being treated with insulin. She reported a family history of diabetes mellitus characteristic of an autosomal dominant mode of inheritance. Molecular analysis of the PDX1 gene revealed the missense variant c.532G > A (p.(Glu178Lys)) segregating from the patient to her son, reported as diabetic. It was absent in her healthy daughter. The c.532G > A seems to be a rare variant, absent in human variants databases, and among 86 normoglycemic controls. Eight in silico algorithms classified this variant as probably pathogenic. Additionally, analysis of the evolutionary conservation showed the glutamic acid in the position 178 of PDX-1 protein as conserved among several species. Our findings reinforce the importance of screening rare MODY genes among families with suspicion of monogenic diabetes to help better understand the clinical manifestations of this disease.     

Cardiac Surgery in Patients With Liver Cirrhosis (CASTER) Study: Early and Long-Term Outcomes

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Gut vascular barrier impairment leads to intestinal bacteria dissemination and colorectal cancer metastasis to liver

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Therapeutic strategies for gastroenteropancreatic neuroendocrine neoplasms: State-of-the-art and future perspectives

Although gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) have always been considered rare tumors, their incidence has risen over the past few decades. They represent a highly heterogeneous group of neoplasms with several prognostic factors, including disease stage, proliferative index (Ki67), and tumor differentiation. Most of these neoplasms express somatostatin receptors on the cell surface, a feature that has important implications in terms of prognosis, diagnosis, and therapy. Although International Guidelines propose algorithms aimed at guiding therapeutic strategies, GEP-NEN patients are still very different from one another, and the need for personalized treatment continues to increase. Radical surgery is always the best option when feasible; however, up to 80% of cases are metastatic upon diagnosis. Regarding medical treatments, as GEP-NENs are characterized by relatively long overall survival, multiple therapy lines are adopted during the lifetime of these patients, but the optimum sequence to be followed has never been clearly defined. Furthermore, although new molecular markers aimed at predicting the response to therapy, as well as prognostic scores, are currently being studied, their application is still far from being part of daily clinical practice. As they represent a complex disease, with therapeutic protocols that are not completely standardized, GEP-NENs require a multidisciplinary approach. This review will provide an overview of the available therapeutic options for GEP-NENs and attempts to clarify the possible approaches for the management of these patients and to discuss future perspectives in this field.     

Desmoplastic melanoma: an updated immunohistochemical analysis of 40 cases with a proposal for an additional panel of stains for diagnosis

Desmoplastic melanoma (DM) is histologically characterized by a proliferation of spindle melanocytes dispersed in a collagenous stroma that can be mistaken for a variety of neoplasms. The purpose of this study was to analyze 40 cases of DM with a comprehensive panel of immunohistochemical markers (KBA.62, p16, Ezrin, WT‐1, MITF‐1, SOX‐10, CD117, SOX‐2, nestin, PNL2, p75, MART‐1, gp100 and S100p) to obtain a more complete understanding of the potential use of these antibodies in the diagnosis of DM. We found that all cases of DM expressed p16, WT‐1, SOX‐10, nestin and S100p and 95% of cases expressed p75. There was variable expression with Ezrin, SOX‐2, KBA.62, MART‐1 and HMB‐45. Most DMs did not express MITF‐1, PNL2 and CD117. Conditions that may enter in the histologic differential diagnosis of DM, including dermal scars, fibromatosis and dermatofibromas were also studied. Nearly all control cases also stained positive for p16 but were negative for WT1, SOX10, nestin, p75 and S‐100p, as well as for most of the other markers tested. We conclude that a panel of S‐100p, WT1, SOX10, p75 and nestin may constitute the optimal panel with the most sensitive and specific combination of immunostain available for the diagnosis of DM.     

Review of computational fluid dynamics in the assessment of nasal air flow and analysis of its limitations

Nasal breathing difficulties (NBD) are a widespread medical condition, yet decisions pertaining to the surgical treatment of chronic NBD still imply a significant degree of subjective judgement of the surgeon. The current standard objective examinations for nasal flow, e.g., rhinomanometry and acoustic rhinomanometry, do not suffice to reliably direct the surgeon on the extent of any necessary surgery. In the last two decades, several groups have therefore considered the numerical simulation of nasal airflow. Currently, these analyses take many hours of labor from the operator, and require a huge amount of computer time and the use of expensive commercial software. Most often, their results are insufficiently validated so that virtual surgery, which is the eventual application, is still absent in clinical practice. Very recently, however, attempts at considering the finest details of the flow are beginning to appear, for example unsteady turbulent simulations validated through laboratory measurements through particle image velocimetry. In this paper, we first discuss recent developments in how computational fluid dynamics (CFD) is helping surgeons improve their understanding of nasal physiology and the effect of surgical modifications on the airflow in the nasal cavity. In a second part, the procedural and modeling challenges that still prevent CFD from being routinely used in clinical practice are surveyed and critically discussed.