Nanotechnology-Based Approaches for the Management of Diabetes Mellitus: An Innovative Solution to Long-Lasting Challenges in Antidiabetic Drug Delivery.

Diabetes is a widespread metabolic illness. Mismanagement of diabetes can lead to severe complications that tremendously impact patients' quality of life. The assimilation of nanotechnology in diabetes care holds the potential to revolutionize treatment paradigms, improve patient outcomes, and reduce the economic burden associated with this pervasive disease.

Evaluation of the lymphocyte population and placental inflammation in pregnant patients with moderate or severe COVID-19 forms - a secondary analysis.

Aim: In this secondary analysis, we aimed to characterize the lymphocytes population and placental inflammation in pregnant women with moderate and severe coronavirus disease 2019 (COVID-19) forms.

Patients, Materials And Methods: In the analysis of this prospective evaluation, we included 26 pregnant women at term with moderate and severe COVID-19 forms that were evaluated in a tertiary maternity center in a one-year timeframe. Clinical data, along with blood immunophenotyping results and placental histopathological examinations were comparatively evaluated between two study groups depending on the COVID-19 severity: Group 1 (moderate COVID-19, n=14 patients) and Group 2 (severe COVID-19, n=12 patients).

Conservative management of cervical intraepithelial neoplasia 2 and prediction of its progression - a retrospective study.

Aim: Cervical intraepithelial neoplasia 2 (CIN2) evolution is controversial, and some of them regress spontaneously in a two-year follow-up. The purpose of this work was to evaluate the percentage of CIN2 progression or persistence during a 24-month follow-up, using clinical predictors such as human papillomavirus (HPV) genotype and cytology results.

Patients, Materials And Methods: This is a retrospective case-control study and included patients of reproductive age who had a new diagnosis of CIN2 who were monitored for lesion regression (Group 1, n=72 patients), and progression or persistence (Group 2, n=36 patients).

Predicting Unfavorable Pregnancy Outcomes in Polycystic Ovary Syndrome (PCOS) Patients Using Machine Learning Algorithms.

: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical outcomes. The aim of this study was to determine the predictive performance of four machine learning (ML)-based algorithms for the prediction of adverse pregnancy outcomes in pregnant patients diagnosed with PCOS. : A total of 174 patients equally divided into 2 groups depending on the PCOS diagnosis were included in this prospective study.