The luteolytic activity of oxymetholone, and anabolic steroid, has been evaluated in 10 women. Administration early in the follicular phase of the cycle inhibited ovulation and prolonged the duration of the cycles in 2 of 3 subjects, but treatment beginning on Day 10 (3 subjects) did not prevent ovulation, although subsequent plasma progesterone concentrations were reduced. Treatment after ovulation (4 subjects) suppressed progesterone levels by 50 to 80 per cent and shortened cycle length by 6 to 8 days. Side effects were weight gain and bromosulfophthalein retention. The most likely mechanisms producing these perturbations are the inhibition of luteinizing hormone release early in the cycle and, later, inhibition of progesterone biosynthesis.
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http://dx.doi.org/10.1016/0002-9378(75)90987-4 | DOI Listing |
Genome Med
January 2025
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
Background: Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.
View Article and Find Full Text PDFThe use of single-cell combinatorial indexing sequencing via droplet microfluidics presents an attractive approach for balancing cost, scalability, robustness and accessibility. However, existing methods often require tailored protocols for individual modalities, limiting their automation potential and clinical applicability. To address this, we introduce UDA-seq, a universal workflow that integrates a post-indexing step to enhance throughput and systematically adapt existing droplet-based single-cell multimodal methods.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Software, Shandong University, No. 1500, Shunhua Road, Hi-Tech Industrial Development Zone, Jinan 250100, Shandong, China.
Single-cell high-throughput chromosome conformation capture (Hi-C) technology enables capturing chromosomal spatial structure information at the cellular level. However, to effectively investigate changes in chromosomal structure across different cell types, there is a requisite for methods that can identify cell types utilizing single-cell Hi-C data. Current frameworks for cell type prediction based on single-cell Hi-C data are limited, often struggling with features interpretability and biological significance, and lacking convincing and robust classification performance validation.
View Article and Find Full Text PDFBackground & Aims: Hepatic insulin resistance is a fundamental phenomenon observed in both Type 2 diabetes (T2D) and metabolic (dysfunction) associated fatty liver disease (MAFLD). The relative contributions of nutrients, hyperinsulinemia, hormones, inflammation, and other cues are difficult to parse as they are convoluted by interplay between the local and systemic events. Here, we used a well-established human liver microphysiological system (MPS) to establish a physiologically-relevant insulin-responsive metabolic baseline and probe how primary human hepatocytes respond to controlled perturbations in insulin, glucose, and free fatty acids (FFAs).
View Article and Find Full Text PDFAging is characterized by extensive metabolic dysregulation. Redox coenzyme nicotinamide adenine dinucleotide (NAD) can exist in oxidized (NAD+) or reduced (NADH) states, which together form a key NADH/NAD+ redox pair. Total levels of NAD decline with age in a tissue-specific manner, thereby playing a significant role in the aging process.
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