Histopathological Analysis of Pseudoexfoliation Material in Ocular Surgeries: Clinical Implications.

Background: Pseudoexfoliation syndrome (PEX) is a common age-related ocular condition characterized by the accumulation of a fibrillar, pseudoexfoliative material on the anterior segment of the eye. This study aims to investigate the histopathological characteristics of pseudoexfoliative material within different ocular structures, including the eyelid, conjunctiva, and anterior lens capsule.

Methods: A total of 32 anterior lens capsules, 3 eyelid fragments, and 12 conjunctival specimens were obtained from patients clinically diagnosed with PEX during ocular surgeries at the Onioptic Hospital of Ophthalmology.

Hospitalizations for Obstetrical Conditions During and After the Covid-19 Pandemic.

Background: During the Covid-19 pandemic there have been a drastic decrease in hospitalizations for non-Covid conditions. The aim of this study was to evaluate the trend in hospitalizations for obstetrical conditions during and after the Covid-19 pandemic.

Methods: For this study there we used electronical data base in order to search for all the obstetrical patients that were hospitalized in a tertiary maternity, Clinical Emergency County Hospital Craiova, during the pre-pandemic period (between March - December 2019), during pandemics (2020 March - December, 2021 March - December) and post pandemics (2022 March - December).

Artificial Intelligence in Obstetric Anomaly Scan: Heart and Brain.

Background: The ultrasound scan represents the first tool that obstetricians use in fetal evaluation, but sometimes, it can be limited by mobility or fetal position, excessive thickness of the maternal abdominal wall, or the presence of post-surgical scars on the maternal abdominal wall. Artificial intelligence (AI) has already been effectively used to measure biometric parameters, automatically recognize standard planes of fetal ultrasound evaluation, and for disease diagnosis, which helps conventional imaging methods. The usage of information, ultrasound scan images, and a machine learning program create an algorithm capable of assisting healthcare providers by reducing the workload, reducing the duration of the examination, and increasing the correct diagnosis capability.

Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE): protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection.

Introduction: Congenital anomalies are the most encountered cause of fetal death, infant mortality and morbidity. 7.9 million infants are born with congenital anomalies yearly.

Clinical Characteristics and Local Histopathological Modulators of Endometriosis and Its Progression.

Unlabelled: Endometriosis (E) and adenomyosis (A) are associated with a wide spectrum of symptoms and may present various histopathological transformations, such as the presence of hyperplasia, atypia, and malignant transformation occurring under the influence of local inflammatory, vascular and hormonal factors and by the alteration of tumor suppressor proteins and the inhibition of cell apoptosis, with an increased degree of lesion proliferation.

Material And Methods: This retrospective study included 243 patients from whom tissue with E/A or normal control uterine tissue was harvested and stained by histochemical and classical immunohistochemical staining. We assessed the symptomatology of the patients, the structure of the ectopic epithelium and the presence of neovascularization, hormone receptors, inflammatory cells and oncoproteins involved in lesion development.