The adipose-derived circulating hormone leptin plays a pivotal role in the control of energy balance and body weight. Sound data indicate that this hormone also acts as an important developmental signal impacting a number of brain regions during fetal and postnatal stages. Leptin levels surge during the two first postnatal weeks of life in rodents. This period is characterized by the presence of early network driven activity in the immature hippocampus, the so-called Giant Depolarizing Potentials (GDPs). GDPs are thought to contribute to the wiring of the hippocampal network. We therefore tested the effect of leptin on GDPs. Leptin increased GDPs frequency between the postnatal days (P) 1 and 3 via a calcium/Calmodulin-dependent kinase (CaMK) and extracellular signal-related kinase (ERK) dependent pathways. Between P6 and P7, leptin inhibited the frequency of GDPs through the activation of large conductance Ca activated K (BK) channels driven by a phosphoinositol-3 kinase (PI3K) dependent pathway. These results show that leptin exerts a bi-directional and age-dependent control of GDPs and extends the scope of leptin's action in the developing brain.
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http://dx.doi.org/10.3389/fncel.2019.00254 | DOI Listing |
J Am Chem Soc
January 2025
Molecular Sensing and Imaging Center, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China.
Nanopore technology holds great potential for single-molecule identification. However, extracting meaningful features from ionic current signals and understanding the molecular mechanisms underlying the specific features remain unresolved. In this study, we uncovered a distinctive ionic current pattern in a K238Q aerolysin nanopore, characterized by transient spikes superimposed on two stable transition states.
View Article and Find Full Text PDFCancer Res
January 2025
University of California, San Diego, La Jolla, CA, United States.
Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest solid cancers; thus, identifying more effective therapies is a major unmet need. In this study, we characterized the super enhancer (SE) landscape of human PDAC to identify drivers of the disease that might be targetable. This analysis revealed MICAL2 as a super enhancer-associated gene in human PDAC, which encodes the flavin monooxygenase MICAL2 that induces actin depolymerization and indirectly promotes SRF transcription by modulating the availability of serum response factor coactivators myocardin-related transcription factors (MRTF-A and MRTF-B).
View Article and Find Full Text PDFNano Lett
January 2025
Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey 08854, United States.
Pyrochlore materials are known for their exotic magnetic and topological phases arising from complex interactions among electron correlations, band topology, and geometric frustration. Interfaces between different pyrochlore crystals characterized by complex many-body ground states hold immense potential for novel interfacial phenomena due to the strong interactions between these phases. However, the realization of such interfaces has been severely hindered by limitations in material synthesis methods.
View Article and Find Full Text PDFCatheter Cardiovasc Interv
January 2025
Division of Cardiology, Department of Medical Science, AOU Città della Salute e della Scienza di Torino, Turin, Italy.
Introduction: In patients with chronic coronary syndromes (CCS), the benefit of percutaneous coronary intervention (PCI) added to optimal medical therapy (OMT) remains unclear. The indication to PCI may be driven either by angiographic evaluation or ischemia assessment, thus depicting different potential strategies which have not yet been thoroughly compared.
Methods: Randomized controlled trials (RCTs) comparing OMT versus PCI angio-guided or versus PCI non-invasive or invasive ischemia guided were identified and compared via network meta-analysis.
J Drug Target
January 2025
Sunirmal Bhattacharjee, Bharat Pharmaceutical Technology, Amtali, Agartala, Tripura, India.
A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attracted significant interest in biomedical research due to its features: (i) better patient care through early diagnosis and detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) lowering medical costs; (vi) reducing morbidity and mortality; (vii) enhancing performance; (viii) enhancing precision; and (ix) time efficiency. Quantitative metrics are crucial for evaluating AI implementations, providing insights, enabling informed decisions, and measuring the impact of AI-driven initiatives, thereby enhancing transparency, accountability, and overall impact.
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