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Background: Glial cell line-derived neurotrophic factor (GDNF) has emerged as a potential biomarker for schizophrenia (SCZ). However, GDNF levels remain unclear in affected individuals compared to healthy controls. Therefore, we aimed to calculate a pooled estimate of GDNF levels in patients with SCZ in comparison with healthy controls.

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Sex reversal induced by 17β-estradiol may be achieved by regulating the neuroendocrine system of the Pacific white shrimp Penaeus vannamei.

BMC Genomics

January 2025

Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.

Background: Due to sexual dimorphism in growth of penaeid shrimp, all-female cultivation is desirable for the aquaculture industry. 17β-estradiol (E2) has the potential to induce the male-to-female sex reversal of decapod species. However, the mechanisms behind it remain poorly understood.

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Although DNA methyltransferase 1 (DNMT1) and RNA editor ADAR triplications exist in Down syndrome (DS), their specific roles remain unclear. DNMT methylates DNA, yielding S-adenosine homocysteine (SAH), subsequently converted to homocysteine (Hcy) and adenosine by S-adenosine homocysteine (Hcy) hydrolase (SAHH). ADAR converts adenosine to inosine and uric acid.

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Idiopathic pulmonary fibrosis (IPF) is a rapidly progressive interstitial lung disease of unknown pathogenesis with no effective treatment currently available. Given the regulatory roles of lncRNAs (TP53TG1, LINC00342, H19, MALAT1, DNM3OS, MEG3), miRNAs (miR-218-5p, miR-126-3p, miR-200a-3p, miR-18a-5p, miR-29a-3p), and their target protein-coding genes (PTEN, TGFB2, FOXO3, KEAP1) in the TGF-β/SMAD3, Wnt/β-catenin, focal adhesion, and PI3K/AKT signaling pathways, we investigated the expression levels of selected genes in peripheral blood mononuclear cells (PBMCs) and lung tissue from patients with IPF. Lung tissue and blood samples were collected from 33 newly diagnosed, treatment-naive patients and 70 healthy controls.

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Collective behavior in biological systems emerges from local interactions among individuals, enabling groups to adapt to dynamic environments. Traditional modeling approaches, such as bottom-up and top-down models, have limitations in accurately representing these complex interactions. We propose a novel potential field mechanism that integrates local interactions and environmental influences to explain collective behavior.

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