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3,741 results for “Hormons”
How ovarian hormones influence the behaviroal activation and inhibition system through the dopamine pathway
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Stress-associated brain activation across the hormonal contraceptive cycle
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Hormone Replacement Therapy Social Media Claims
<p>The claims made in social media posts about hormone replacement therapy, the tpye of person/organisation posting these claims, whether the claims agree with NICE/BNF guidance and whether the person/organisation posting these claims has a conflict of interest. Full unredacted dataset available on request to: <a href="mailto:mm494@st-andrews.ac.uk">mm494@st-andrews.ac.uk</a></p>
Collation and orthology-based identification of hormone-related genes in bread wheat
<p>Plant hormones coordinate a plethora of developmental processes in plants, including responses to abiotic and biotic stressors. Here, we collate the findings of previous studies identifying bread wheat (<em>Triticum aestivum</em>) genes related to hormonal processes (<strong>biosynthesis</strong>, <strong>transport</strong>, <strong>signalling</strong>, and <strong>catabolism</strong>) and collect wheat orthologues from hundreds of additional hormone-related genes utilising the Ensembl Plants Compara database. We have initially conducted this procedure for <strong>abscisic acid</strong>, <strong>auxins </strong>(IAA and IBA), <strong>brassinosteroids</strong>, <strong>cytokinins</strong>, <strong>ethylene</strong>, <strong>gibberellins</strong>, and <strong>strigolactone</strong>, yielding a total of over 1,700 putative wheat orthologues. We aim to provide a community resource to aid gene annotation and subsequent analyses. We warmly welcome feedback from the community.</p> <p>Please refer to the file <strong>README.pdf</strong> for further details, including methods and references.</p>
Elevated temperature effects on animal personality: hormonal stress response underlying behavioural differences in the American bullfrog
<p>Dataset for research paper submitted to Animal Behaviour</p> <p>Behavioural_data.csv: raw data for how individual bullfrogs performed in six different trials on an 8-arm maze before and after they were submitted to thermal stress. Behaviours analyzed: movements against the wall of the maze, posture changes, total ambulatory distance (m), and time on the centre of the arena (s).</p> <p>Hormone_data.csv: raw hormone (corticosterone and testosterone) data collected from individual bullfrogs in four different time points: baseline, 12 hours after stress, 24 days after stress, and 47 days after stress.</p> <p>Mass_data.csv: raw mass data collected from individual bullfrogs at the beginning and end of the experiment. SVL = snout-vent length. Body index is calculated as the residuals of a linear regression between mass as dependent variable and SVL as independent variable.</p>
Reproductive hormones mediate changes in the gut microbiome during pregnancy and lactation in Phayre's leaf monkeys
Studies in multiple host species have shown that gut microbial diversity and composition change during pregnancy and lactation. However, the specific mechanisms underlying these shifts are not well understood. Here, we use longitudinal data from wild Phayre's leaf monkeys to test the hypothesis that fluctuations in reproductive hormone concentrations contribute to gut microbial shifts during pregnancy. We described the microbial taxonomic composition of 91 fecal samples from 15 females (n=16 cycling, n=36 pregnant, n=39 lactating) using 16S rRNA gene amplicon sequencing and assessed whether the resulting data were better explained by overall reproductive stage or by fecal estrogen (fE) and progesterone (fP) concentrations. Our results indicate that while overall reproductive stage affected gut microbiome composition, the observed patterns were driven by reproductive hormones. Females had lower gut microbial diversity during pregnancy and fP concentration was negatively correlated with diversity. Additionally, fP concentration predicted both unweighted and weighted UniFrac distances, while reproductive state only predicted unweighted UniFrac distances. Seasonality (rainfall and periods of phytoprogestin consumption) additionally influenced gut microbial diversity and composition. Our results indicate that reproductive hormones, specifically progestagens, contribute to the shifts in the gut microbiome during pregnancy and lactation.
Sex chromosomes and hormones independently influence healthy brain development but act similarly after cranial radiation
<h2><strong>Description</strong></h2> <p>Biological sex influences prevalence of developmental disorders through sex hormones and sex chromosomes. However, our understanding of their impacts in neurodevelopment and response to injury remains limited. In this project, we use high resolution magnetic resonance imaging (MRI) to investigate the four core genotype mouse model (FCG) that separates the influences of sex hormones and sex chromosomes during normal brain development and after cranial radiation therapy. </p> <p>Sex differences are attributed to either sex hormones or sex chromosomes. This can be distinguished by the FCG model which decouples the sex determining region (SRY) from the Y chromosome by moving SRY onto an autosome. This gives us four core sex genotypes: XX NULL, XY NULL, XX SRY, and XY SRY.</p> <p>This dataset represents the <em>most comprehensive mouse brain imaging study</em> employing the FCG model to date with 5 timepoints (P14, P23, P42, P63, P98), Ccl2 wildtype (+/+) and knockouts (-/-), irradiation (7Gy) and sham (0Gy) mice. All in all, a total of <strong>1071 images</strong>! The results presented here is published in PNAS.</p> <p>In vivo MRI scans were obtained using a 7-T MRI scanner (Bruker BioSpin, Ettlingen, Germany) equipped with four cryocoils for simultaneous imaging of four mice. The scans were performed with the following settings: T1-weighted, 3D-gradient echo sequence, 75μm isotropic resolution, TR=26ms, TE=8.25ms, flip angle=26°, field of view=25×22×22mm, and matrix size=334×294×294.</p> <p>All structural MR images are stored in <strong>images.tar.gz</strong>. Images were segmented and registered using an automated pipeline which are stored in <strong>labels.tar.gz</strong>. The consensus average and labels are <strong>final_average.mnc </strong>and <strong>final_labels.mnc</strong>, respectively. Extracted structure volumes alongside the metadata are included in <strong>df_micevolumes.csv</strong>. Structural MRIs are in MINC format and the <strong>readme.txt</strong> provides further information on this dataset. </p> <p>The authors express their sincere gratitude for the research funding recieved from the Canadian Institutes of Health Research (158622, 168037) and the Ontario Institute for Cancer Research (IA-024) with funding from the Government of Ontario and Restracomp from the SIckKids Research Training Centre.</p> <p><strong>Publication</strong>: https://www.pnas.org/doi/10.1073/pnas.2404042121</p> <h2><strong>Code/Software </strong></h2> <p><strong>MINC</strong><br>https://www.bic.mni.mcgill.ca/ServicesSoftware/MINC</p> <p><strong>RMINC</strong><br>https://github.com/Mouse-Imaging-Centre/RMINC</p> <p><strong>PydPiper</strong><br>https://github.com/Mouse-Imaging-Centre/pydpiper/tree/v2.0.19.1</p>
Summary statistics from "Sex-Specific Causal Relations between Steroid Hormones and Obesity—A Mendelian Randomization Study"
<p>GWAMA summary statistics of four steroid hormone levels and one steroid hormone ratio using fixed-effect model.</p> <p>When using this data, please cite: Pott J, Horn K, Zeidler R, et al.. Sex-Specific Causal Relations between Steroid Hormones and Obesity - A Mendelian Randomization Study. <em>Metabolites</em> <strong>2021</strong>, <em>11</em>, 738. https://doi.org/10.3390/metabo11110738</p> <p>All txt files contain the following columns:</p> <ul> <li>markername</li> <li>chr</li> <li>bp_hg19 (base position according to hg19)</li> <li>ea (effect allele)</li> <li>oa (other allele)</li> <li>eaf (effect allele frequency)</li> <li>info (minimal info score across all used studies)</li> <li>nSamples (sample size per SNP)</li> <li>nStudies (number of studies)</li> <li>beta (effect estimate)</li> <li>se (standard error)</li> <li>p (p-value)</li> <li>I2 (SNP heterogeneity across studies)</li> <li>phenotype (phenotyp setting)</li> </ul>
Summary statistics from "Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease"
<p>GWAMA summary statistics of four steroid hormone levels using fixed-effect model and GWAS summary statistics of four other steroid hormones.</p> <p>When using this data, please cite: Pott J, Bae YJ, Horn K, et al.. Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease. <em>J Clin Endocrinol Metab</em> <strong>2019</strong> Nov 1;104(11):5008-5023. doi: 10.1210/jc.2019-00757</p> <p>All txt files contain the following columns:</p> <ul> <li>markername</li> <li>chr</li> <li>bp_hg19 (base position according to hg19)</li> <li>effect_allele</li> <li>other_allele</li> <li>effect_allele_freq</li> <li>min_info (minimal info score across all used studies)</li> <li>n (sample size per SNP)</li> <li>beta (effect estimate)</li> <li>se (standard error)</li> <li>p (p-value)</li> <li>CochransQ (only in GWAMA; SNP heterogeneity across studies)</li> <li>pCochransQ (only in GWAMA; p-value of Cochrans Q value)</li> </ul>
Beyond depression and anxiety; a systematic review about the role of corticotropin-releasing hormone antagonists in diseases of the pelvic and abdominal organs-Worksheets
<p>This file has several worksheets corresponding to the data used for the review with the same table as indicated in the file</p>
Supplementary Material from: Suppression of Pituitary Hormone Genes in Subjects Who Died From COVID-19 Independently of Virus Detection in the Gland
<p>Supplementary Table S1A. List of target genes analysed by the Human Host Response.</p> <p>Supplementary Table S1B. List of target genes analysed by the Coronavirus Panel Plus.</p> <p>Supplementary Table S1C. List of target genes analysed by the custom panel.</p> <p>Supplementary Table S2A. Differential gene expression analysis. Virus-positive vs control adenohypophyses.</p> <p>Supplementary Table S2B. Differential gene expression analysis. Virus-negative vs control adenohypophyses.</p>
Hypothyroidism Weight and serum thyroid hormones
<p>Dataset on 50 healthy controls (HC), 25 patients before starting treatment (Hyp1), 15 out of these 25 patients before starting treatment (Hyp12) and 15 patients (same 15 patients) after 6 months of treatment with L-thyroxine (Hyp2). Variables are: ID number, patient group (HC, Hyp1,Hyp12,Hyp2), sex (1=male), age (years), weight (kg), length (m), BSA (body surface area, m^2), BMI (kg/m^2), serum-TPO (IU/ml), serum-TSH (mIU/l), serum-free T3 (pmol/l), serum-free T4 (pmol/l), ratio serum-fT3/fT4, Zulewski score (points) and difference in weight before and after treatment (Hyp2-Hyp12), and difference in TSH (Hyp2-Hyp12) and dosage of L-thyroxine (Levaxin, mg).</p>
Chemogenomics for NR1 nuclear hormone receptors
<p>Compound information sheets for our chemogenomic library (CGL) for the NR1 family of nuclear hormone receptors.</p> <p>The information sheets contain general information about the substances, the biological activity for the NR main targets and NR off-targets, as well as information about identity and purity.</p>
Fig. 4 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 4 AC infection causes imbalance in GLU and lipid metabolism in mice. A Serum biochemical tests (n = 6), including GLU, CHO, TG, HDL, LDL. B, C GLU tolerance and AUC curve (n = 3). D, E Immunohistochemical images and statistics of UCP1 in mouse gWAT (n = 3). Data are presented as mean ± SD. Compared with the control group, statistical significance is indicated as *P <0.05, **P <0.01, ***P <0.001, ****P <0.0001. GLU glucose, TG triglycerides, LDL low-density lipoprotein, HDL high-density lipoprotein, TC total cholesterol, AUC area under the curve
Fig. 3 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 3 AC infection leads to extensive loss of adipose tissue in mice. A Macroscopic images. B, C, D Statistical chart of tissue weight proportion to body weight in different parts (n = 6). E Pathological sections of adipose tissue. F, G Statistical chart of the average single-cell area of iWAT and gWAT (n = 3). Data are presented as mean ± SD. Compared with the control group, statistical significance is denoted as *P <0.05, **P <0.01, ****P <0.0001. BAT brown adipose tissue, iWAT inguinal white adipose tissue, gWAT gonadal white adipose tissue
Fig. 8 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 8 Effect of intranasal MCH on synapse-related proteins. A Transcription levels of Bcl2, Map2, PSD95, Syp in mouse cortex (n = 5). B The expression levels of MAP2, PSD95, and SYP were evaluated by western blotting. C Densitometrical quantification of the blots after normalizing with β-actin (n = 3). Data are presented as mean ± SD. Compared with the AC group, statistical significance is indicated as *P <0.05, **P <0.01. Bcl2 B cell leukemia/lymphoma 2, Map2 microtubule-associated protein 2, PSD95 postsynaptic density protein 95, Syp Synaptophysin, AC Angiostrongylus cantonensis, MCH melanin-concentrating hormone
Fig. 1 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 1 AC infection reduces MCH expression in mice. A Differential volcano plot illustrating brain transcriptome changes in AC-infected mice. B RT– qPCR analysis of Pmch mRNA transcription levels in the whole brain (n = 3) and hypothalamus (n = 4). C, D Panoramic localization of MCH in coronal brain sections. Part D is an enlarged view of part C. E, F Representative images of MCH costained with NeuN and GFAP. G, H Representative images depicting MCH immunofluorescence in hypothalamic regions, along with fluorescence intensity statistics (n = 3). Data are presented as mean ± SD. Compared with the control group, statistical significance is denoted as *P <0.05, ****P <0.0001. NotSig not significant, Pmch pro-melanin-concentrating hormone, dpi days post infection, MCH melanin-concentrating hormone, DAPI 4′,6-diamidino-2-phenylindole, NeuN neuronal nuclei, GFAP glial fibrillary acidic protein, 3V 3rd ventricle, ARH hypothalamic arcuate nucleus, DMH dorsomedial hypothalamus, LHA lateral hypothalamic area, VMH ventromedial hypothalamic nucleus, ZI zona incerta
Fig. 5 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 5 AC infection causes neurological impairment and dyskinesia in mice. A Neurological function score (n ≥ 4). B MWM trajectory. C, D, E, F Statistics of platform crossings, percentage time in target quadrant, distance, and velocity in MWM (n ≥ 4). G, H Changes in running wheel activity and statistics (n ≥ 5). Data are presented as mean ± SD. Compared with the control group, statistical significance is indicated as *P <0.05, **P <0.01, ***P <0.001, ****P <0.0001. dpi days post infection
Fig. 7 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 7 MCH improves neurological function and dyskinesia in mice. A Y-maze movement trajectory. B, C, D Statistics of Y-maze free alternation rate, distance, and velocity (n ≥ 6). E NOR test trajectory. F, G, H Statistics of recognition index, mouse travel distance, and velocity in NOR test (n ≥ 5). I MWM movement trajectory. J, K, L, M Statistics of platform crossings, percentage time in target quadrant, distance, and velocity in MWM (n ≥ 5). N Statistics of the time spent in the pole test (n = 4). O Neurological function score (n = 6). Data are presented as mean ± SD. Compared with the AC group, statistical significance is indicated as *P <0.05, **P <0.01, ***P <0.001, ****P <0.0001. AC Angiostrongylus cantonensis, MCH melanin-concentrating hormone
Fig. 1 in Effects of nucleopolyhedrovirus infection on the development of Helicoverpa armigera (Lepidoptera: Noctuidae) and expression of its 20-hydroxyecdysone- and juvenile hormone-related genes
Fig. 1. Effect of HaSNPV infection on the larval body weight of Helicoverpa armigera. (A) ♦, ■, ▲, ×, —, and ● indicate larvae infected with HaSNPV at the concentrations 0, 105, 106, 107, 108, and 109 PIB/mL, respectively. (B) a, b, c, d, e, and f show H. armigera larvae on the 5th day afer infection with HaSNPV at the concentrations 0, 105, 106, 107, 108, and 109 PIB/mL, respectively.
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