Lessons learned from 64,071 embryos subjected to PGT for aneuploidies: results, recurrence pattern and indications analysis.

Research Question: What is the influence of biological, technical and clinical factors on embryo outcomes in preimplantation genetic testing for aneuploidies (PGT-A) and what is the recurrence pattern?

Design: This retrospective study included 64,071 embryos undergoing PGT-A in the same laboratory between 2011 and 2019. Biopsies were performed at the day 3 embryo stage (48.32%) or blastocyst stage (51.

The Sol Braiding Method for Handling Thick Hair During Transcranial Magnetic Stimulation: An Address for Potential Bias in Brain Stimulation.

Transcranial Magnetic Stimulation (TMS) is a technique that is frequently utilized in neuroscience for both therapeutic and research purposes. TMS offers critical medical services like treating major depression and is vital in almost every research facility. Because TMS relies on scalp placement, hair is thought to affect efficacy because it varies the distance to the target site.

Return rates and pregnancy outcomes after oocyte preservation for planned fertility delay: a systematic review and meta-analysis.

Importance: Oocyte preservation for planned fertility delay, also referred to as social oocyte preservation or colloquially as "egg freezing," has become increasingly popular in the last few decades. Previous literature has suggested that there are gaps in counseling and expectations regarding the expected thaw rates and outcomes of preserved oocytes.

Objective: To characterize the literature on social oocyte preservation, specifically the return rates, thaw rates, clinical pregnancy rates, and live birth rates.

High-resolution density assessment assisted by deep learning of (Lamarck, 1816) and (Linnaeus, 1767) in rocky circalittoral shelf of Bay of Biscay.

This study presents a novel approach to high-resolution density distribution mapping of two key species of the 1170 "Reefs" habitat, and , in the Bay of Biscay using deep learning models. The main objective of this study was to establish a pipeline based on deep learning models to extract species density data from raw images obtained by a remotely operated towed vehicle (ROTV). Different object detection models were evaluated and compared in various shelf zones at the head of submarine canyon systems using metrics such as precision, recall, and F1 score.