Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Rules for body fat interventions based on an operating point mechanism.

ABSTRACT: Interventions to reduce fat are important for human health. However, they can have opposing effects such as exercise that decreases fat but increases food intake, or coherent effects such as leptin resistance which raises both. Furthermore, some interventions show an overshoot in food intake, such as recovery from a diet, whereas others do not. To explain these properties we present a graphical framework called the operating point model, based on leptin control of feeding behavior. Steady-state fat and food intake is given by the intersection of two experimental curves - steady-state fat at a given food intake and ad libitum food intake at a given fat level. Depending on which curve an intervention shifts, it has opposing or coherent effects with or without overshoot, in excellent agreement with rodent data. The model also explains the quadratic relation between leptin and fat in humans. These concepts may guide the understanding of fat regulation disorders.

SUBMITTER: Bar A

PROVIDER: S-EPMC9929596 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Rules for body fat interventions based on an operating point mechanism.

Bar Alon A Karin Omer O Mayo Avi A Ben-Zvi Danny D Alon Uri U

iScience 20230125 2

Interventions to reduce fat are important for human health. However, they can have opposing effects such as exercise that decreases fat but increases food intake, or coherent effects such as leptin resistance which raises both. Furthermore, some interventions show an overshoot in food intake, such as recovery from a diet, whereas others do not. To explain these properties we present a graphical framework called the operating point model, based on leptin control of feeding behavior. Steady-state ...[more]

PMID: 36818281

Similar Datasets

Ten simple rules on how to write a standard operating procedure.

Project description:Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.

| S-EPMC7470745 | biostudies-literature

Fat body

Project description:modENCODE_submission_5522 This submission comes from a modENCODE project of David MacAlpine. For full list of modENCODE projects, see http://www.genome.gov/26524648 Project Goal: Most terminally differentiated Drosophila tissues are either polyploid or polytene. Unlike normal chromosomes, where the entire chromosome must be replicated exactly once, polytene chromosomes are often differentially replicated with many regions underreplicated and some overreplicated. We will characterize five different polytene tissues using comparative genomic hybridization (CGH) to identify differentially replicated regions of each chromosome. These studies will also identify tissue specific amplicons, where the replication mediated amplification of specific loci is essential for up-regulation of mRNA levels encoding proteins critical for development. The differential replication of polytene chromosomes in Drosophila will provide a unique opportunity to understand how developmental cues and chromosomal domains influence replication initiation. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf EXPERIMENT TYPE: CGH. BIOLOGICAL SOURCE 1: Strain: Oregon-R Orr-Weaver(genotype : TBA outcross : TBA description : Wild-type Oregon-R population maintained by Terry Orr-Weaver. made_by : wt population ); Tissue: Fatbody; Developmental Stage: cleavage stage; Genotype: TBA; Sex: Unknown; BIOLOGICAL SOURCE 2: Strain: Oregon-R Orr-Weaver(genotype : TBA outcross : TBA description : Wild-type Oregon-R population maintained by Terry Orr-Weaver. made_by : wt population ); Tissue: Fatbody; Developmental Stage: cleavage stage; Genotype: TBA; Sex: Unknown; NUMBER OF REPLICATES: 1; EXPERIMENTAL FACTORS: Tissue Fatbody

2012-06-03 | E-GEOD-38440 | biostudies-arrayexpress

Fat body

2012-06-04 | GSE38440 | GEO

Unveiling the Hidden Rules of Spherical Viruses Using Point Arrays.

Project description:Since its introduction, the Triangulation number has been the most successful and ubiquitous scheme for classifying spherical viruses. However, despite its many successes, it fails to describe the relative angular orientations of proteins, as well as their radial mass distribution within the capsid. It also fails to provide any critical insight into sites of stability, modifications or possible mutations. We show how classifying spherical viruses using icosahedral point arrays, introduced by Keef and Twarock, unveils new geometric rules and constraints for understanding virus stability and key locations for exterior and interior modifications. We present a modified fitness measure which classifies viruses in an unambiguous and rigorous manner, irrespective of local surface chemistry, steric hinderance, solvent accessibility or Triangulation number. We then use these point arrays to explain the immutable surface loops of bacteriophage MS2, the relative reactivity of surface lysine residues in CPMV and the non-quasi-equivalent flexibility of the HBV dimers. We then explain how point arrays can be used as a predictive tool for site-directed modifications of capsids. This success builds on our previous work showing that viruses place their protruding features along the great circles of the asymmetric unit, demonstrating that viruses indeed adhere to these geometric constraints.

| S-EPMC7232142 | biostudies-literature

Seizures in Tuberous Sclerosis: Mechanism-Based Interventions EXIST.

Project description: Not available

| S-EPMC5967581 | biostudies-literature

A deep learning model based on the attention mechanism for automatic segmentation of abdominal muscle and fat for body composition assessment.

Project description:BackgroundQuantitative muscle and fat data obtained through body composition analysis are expected to be a new stable biomarker for the early and accurate prediction of treatment-related toxicity, treatment response, and prognosis in patients with lung cancer. The use of these biomarkers can enable the adjustment of individualized treatment regimens in a timely manner, which is critical to further improving patient prognosis and quality of life. We aimed to develop a deep learning model based on attention for fully automated segmentation of the abdomen from computed tomography (CT) to quantify body composition.MethodsA fully automatic segmentation deep learning model was designed based on the attention mechanism and using U-Net as the framework. Subcutaneous fat, skeletal muscle, and visceral fat were manually segmented by two experts to serve as ground truth labels. The performance of the model was evaluated using Dice similarity coefficients (DSCs) and Hausdorff distance at 95th percentile (HD95).ResultsThe mean DSC for subcutaneous fat and skeletal muscle were high for both the enhanced CT test set (0.93±0.06 and 0.96±0.02, respectively) and the plain CT test set (0.90±0.09 and 0.95±0.01, respectively). Nevertheless, the model did not perform well in the segmentation performance of visceral fat, especially for the enhanced CT test set. The mean DSC for the enhanced CT test set was 0.87±0.11, while the mean DSC for the plain CT test set was 0.92±0.03. We discuss the reasons for this result.ConclusionsThis work demonstrates a method for the automatic outlining of subcutaneous fat, skeletal muscle, and visceral fat areas at L3.

| S-EPMC10006126 | biostudies-literature

Pick-up point recommendation strategy based on user incentive mechanism.

Project description:In recent years, with the development of spatial crowdsourcing technology, online car-hailing, as a typical spatiotemporal crowdsourcing task application scenario, has attracted widespread attention. Existing researches on spatial crowdsourcing are mainly based on the coordinate positions of user and worker roles to achieve task allocation with the goal of maximum matching number or lowest cost. However, they ignores the problem of the selection of the pick-up point which needs to be solved in the actual scene of online car booking. This problem needs to take into account the four-dimensional coordinate positions of users, workers, pick-up point and destination. Based on this, this study designs a pick-up point recommendation strategy based on user incentive mechanism. Firstly, a new four-dimensional crowdsourcing model is established, which is closer to the practical application of crowdsourcing problem. Secondly, taking cost optimization as the index, a user incentive mechanism is designed to encourage users to walk to the appropriate pick-up point within a certain distance. Thirdly, a concept of forward rate is proposed to reduce the computation time. Some key factors, such as the maximum walking distance limit of users and task cost, are considered as the recommendation index for measuring the pick-up point. Then, an effective pick-up point recommendation strategy is designed based on this index. Experiments show that the strategy proposed in this article can achieve reasonable recommendation for pick-up points and improve the efficiency of drivers and reduce the total trip cost of orders to the greatest extent.

| S-EPMC10703052 | biostudies-literature

Fat body of silkworm

Project description:Transcriptome analysis of the fat body of silkworms Transcriptome

| PRJNA1173870 | ENA

Fat body of silkworm

Project description:Transcriptome analysis of the fat body of silkworms Transcriptome

| PRJNA1174360 | ENA

Fat body of silkworm

Project description:Transcriptome analysis of the fat body of silkworms Transcriptome

| PRJNA1174363 | ENA