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Genome-wide association study of varenicline-aided smoking cessation.
Nicotine Tob Res
January 2025
Department of Population Health Sciences, University of Leicester, Leicester, UK.
Introduction: Varenicline is an α4β2 nicotinic acetylcholine receptor partial agonist with the highest therapeutic efficacy of any pharmacological smoking cessation aid and a 12-month cessation rate of 26%. Genetic variation may be associated with varenicline response, but to date no genome-wide association studies of varenicline response have been published.
Methods: In this study, we investigated the genetic contribution to varenicline effectiveness using two electronic health record-derived phenotypes.
Cardiac Regeneration in Adult Zebrafish: A Review of Signaling and Metabolic Coordination.
Curr Cardiol Rep
January 2025
Department of Zoology, Trivenidevi Bhalotia College (Affiliated to Kazi Nazrul University), College Para Rd, Raniganj, 713347, West Bengal, India.
Purpose Of Review: This review investigates how post-injury cellular signaling and energy metabolism are two pivotal points in zebrafish's cardiomyocyte cell cycle re-entry and proliferation. It seeks to highlight the probable mechanism of action in proliferative cardiomyocytes compared to mammals and identify gaps in the current understanding of metabolic regulation of cardiac regeneration.
Recent Findings: Metabolic substrate changes after birth correlate with reduced cardiomyocyte proliferation in mammals.
Automated insulin delivery in pregnant women with type 1 diabetes mellitus: a systematic review and meta-analysis.
Acta Diabetol
January 2025
1st Paediatric Department, School of Medicine, Faculty of Health Sciences, Ippokratio General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Aims: To assess the efficacy and safety of automated insulin delivery (AID) systems compared to standard care in managing glycaemic control during pregnancy in women with Type 1 Diabetes Mellitus (T1DM).
Methods: We searched MEDLINE, Cochrane Library, registries and conference abstracts up to June 2024 for randomized controlled trials (RCTs) and observational studies comparing AID to standard care in pregnant women with T1DM. We conducted random effects meta-analyses for % of 24-h time in range of 63-140 mg/dL (TIR), time in hyperglycaemia (> 140 mg/dl and > 180 mg/dL), hypoglycaemia (< 63 mg/dl and < 54 mg/dL), total insulin dose (units/kg/day), glycemic variability (%), changes in HbA1c (%), maternal and fetal outcomes.
ALG8-CDG: Advances in Molecular and Prenatal Phenotyping Facilitate Prenatal Diagnosis and Genetic Counseling.
QJM
January 2025
Medical Genetic Center, Guangdong Women and Children Hospital, Guangzhou, Guangdong, 510010, China.
Background: ALG8-congenital disorder of glycosylation (ALG8-CDG) is a rare inherited metabolic disorder leading to severe multisystem manifestations, with no reported prenatal patients to date.
Methods: We describe two fetuses from a single family with ALG8-CDG presenting with prenatal hydrops, undergoing comprehensive prenatal ultrasound, umbilical cord blood biochemistry, autopsy, placental pathology, and genetic testing.
Results: Prenatal ultrasound revealed fetal hydrops, skeletal anomalies, cardiac developmental abnormalities, cataracts, echogenic kidneys and bowel, oligohydramnios, choroid plexus cysts, and intrauterine growth restriction.
Development and Validation of a Deep Learning Model Based on MRI and Clinical Characteristics to Predict Risk of Prostate Cancer Progression.
Radiol Imaging Cancer
January 2025
Department of Radiology, University Medical Center Groningen, Groningen, the Netherlands.
Purpose To validate a deep learning (DL) model for predicting the risk of prostate cancer (PCa) progression based on MRI and clinical parameters and compare it with established models. Materials and Methods This retrospective study included 1607 MRI scans of 1143 male patients (median age, 64 years; IQR, 59-68 years) undergoing MRI for suspicion of clinically significant PCa (csPCa) (International Society of Urological Pathology grade > 1) between January 2012 and May 2022 who were negative for csPCa at baseline MRI. A DL model was developed using baseline MRI and clinical parameters (age, prostate-specific antigen [PSA] level, PSA density, and prostate volume) to predict the time to PCa progression (defined as csPCa diagnosis at follow-up).
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