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3,741 results for “Hormons”
Ecological relationships among habitat type, food nutrients, parasites and hormones in wild boar during winter
<p>Habitat quality and parasite assembly influence wildlife health, and they are key indicators of health and survivability of wildlife populations. To investigate the potential ecological relationships among habitat type, food nutrients, parasites and hormones in wild boar (<i><span>Sus scrofa</span></i>), we collected samples of wild boar feces and available plants in their habitat <span>by line transects during winter</span><span>. </span><span>Along transects, we identified the composition of plants foraged by wild boar and measured the content of nutrients in available plants to estimate nutrient intake. We also quantified parasites and hormones in wild boar fecal samples. We compared food nutrients among different forest types and explored possible relationships among estimated nutrient intake, parasites and hormones.</span><span> We found coniferous forest</span><span> had positive effects on estimated fat intake and negative effects on estimated protein and fiber intake by wild boar</span><span>. Furthermore, we revealed that </span><span>estimated fat intake was negatively correlated with </span><i><span><span>Metastrongylus elongatus </span></span></i><span>parasites and positively correlated with triiodothyronine (T3). In contrast, estimated protein intake was positively correlated with </span><i><span><span>M. elongatus</span></span></i><span> and negatively correlated with T3. </span><span>Finally, we found </span><span>negative relationship</span><span>s</span><span> between T3 concentrations and loads of </span><i><span><span>Ascaris suum</span></span></i><span> parasites and between cortisol (COR) and loads of </span><i><span><span>Trichuris suis</span></span></i><span> parasites.</span><i> </i><span>T</span><span>hese insights on ecological relationships help identify potential dietary parameters in winter that could help predict and manage parasite and hormone responses for wild boar population recovery.</span>Habitat quality and parasite assembly influence wildlife health, and they are key indicators of health and survivability of wildlife populations. To investigate the potential ecological relationships among habitat type, food nutrients, parasites and hormones in wild boar (<i><span>Sus scrofa</span></i>), we collected samples of wild boar feces and available plants in their habitat <span>by line transects during winter</span><span>. </span><span>Along transects, we identified the composition of plants foraged by wild boar and measured the content of nutrients in available plants to estimate nutrient intake. We also quantified parasites and hormones in wild boar fecal samples. We compared food nutrients among different forest types and explored possible relationships among estimated nutrient intake, parasites and hormones.</span><span> We found coniferous forest</span><span> had positive effects on estimated fat intake and negative effects on estimated protein and fiber intake by wild boar</span><span>. Furthermore, we revealed that </span><span>estimated fat intake was negatively correlated with </span><i><span><span>Metastrongylus elongatus </span></span></i><span>parasites and positively correlated with triiodothyronine (T3). In contrast, estimated protein intake was positively correlated with </span><i><span><span>M. elongatus</span></span></i><span> and negatively correlated with T3. </span><span>Finally, we found </span><span>negative relationship</span><span>s</span><span> between T3 concentrations and loads of </span><i><span><span>Ascaris suum</span></span></i><span> parasites and between cortisol (COR) and loads of </span><i><span><span>Trichuris suis</span></span></i><span> parasites.</span><i> </i><span>T</span><span>hese insights on ecological relationships </span><span>help identify potential dietary parameters in winter that could help predict and manage parasite and hormone responses for wild boar population recovery.</span></p>
Assessing Ovastacin an Fetuin B as a Non-Hormonal Contraceptive Targets
<p>Ovastacin/Fetuin B cloning results with small scale expression</p>
Fig. 6 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 6 MCH improves survival, body weight, and adipose tissue weight in mice. A Survival curve (n = 6). B Mouse body weight change curve (n ≥ 4). C Weight increment in mice (n ≥ 4). D Macroscopic images of adipose tissue. E, F, G Statistical chart of adipose tissue weight proportion to body weight (n ≥ 4). 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, BAT brown adipose tissue, iWAT inguinal white adipose tissue, gWAT gonadal white adipose tissue
Fig. 2 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone
Fig. 2 AC Infection causes energy metabolism imbalance in mice. A Mouse body weight change curve. B Weight increment statistics at different infection stages. C, G Oxygen consumption curve and statistics in mice within 48 h. D, H Carbon dioxide production curve and statistics in mice within 48 h. E, I Food consumed curve and statistics in mice within 48 h. F, J Water consumed curve and statistics in mice within 48 h. Data are presented as mean ± SD, n ≥ 5. Compared with the control group, statistical significance is denoted as *P <0.05, **P <0.01, ***P <0.001, ****P <0.0001. AC Angiostrongylus cantonensis, dpi days post infection
FIGURE 2 in Regression of dark color in subterranean fishes involves multiple mechanisms: response to hormones and neurotransmitters
FIGURE 2 | Dose-response curves for MCH in melanophores of the species of Pimelodella. Each point is the mean ± SEM (P. transitoria, n = 6, P. speleae, n = 7, and P. kronei, n = 8). Control – melanosomes fully dispersed.
Figure 2 in Intragonadal evaluation of sexual steroid hormones during three reproductive events in two species of Peromyscus (Rodentia: Cricetidae)
Figure 2. Production and biotransformation profiles in four selected SSH of the ∆4 pathway by reproductive event in two species of Peromyscus. Mean intraovarian concentrations of sexual steroid hormones ([SSH]: progesterone, P4; androstenedione, A, testosterone, T; estradiol, E2) were assessed in free-living, adult females of P. melanotis (A) and P. difficilis (B), during estrous cycle (PRO, proestrus; EST, estrus; MET, metestrus; DIE, diestrus), pregnancy (early gestation, G1; late gestation, G2), and overall lactation. Bars depict mean [SSH] and vertical whiskers the respective standard errors; arrows signal which [SSH] had significant differences with others; when more than one [SSH] was statistically different in ANOVA analyzes, horizontal lines were added and arrows below and above them signal the respective [SSH]; number of asterisks indicate degree of significance in p-values (see Methods, Results, and the ANOVA in Table S1): * = significant; ** = very significant; *** = extremely significant; the plus sign (+) shows an almost statistically significant instance. Note that scales of plots differ.
Figure 4 in Intragonadal evaluation of sexual steroid hormones during three reproductive events in two species of Peromyscus (Rodentia: Cricetidae)
Figure 4. Comparison of intraovarian contents of each steroid hormone in two Peromyscus species: (A) progesterone [P4], (B) Androstenedione [A], (C) Testosterone [T1], (D) Estradiol [E2]. Concentrations curves include a complete estrous cycle (CEC) and a successful estrous cycle (SEC; i.e., followed by pregnancy and lactation), in free-living, adult females of P. melanotis (open markers) and P. difficilis (closed markers). The arrow and asterisk signal the only interspecific significant difference. Symbology after Fig. 1.
Figure 3 in Androgenic hormones in crustacean aquaculture: a review
Figure 3. Multiple sequence alignment of deduced primary amino acid sequences of decapod IAGs using Clustal W. Cherax quadricarinatus: ABH07705.1; Cherax destructor: ACD91988.1; Macrobrachium rosenbergii: ACJ38227.1; Portunus pelagicus: HM459854.1; Penaeus monodon: ADA67878.1; Marsupenaeus japonicus: BAK20460.1 Macrobrachium lar: BAJ78349.1; Macrobrachium nipponense: AGB56976.1. The boundary between signal peptide and B chain is represented by a dotted vertical line. Conserved amino acids are indicated in different colors. B and A chains are marked with dotted and sold lines, respectively. The asterisk indicates the positions of conserved Cys residues in all species.
Figure 2 in Androgenic hormones in crustacean aquaculture: a review
Figure 2. Organogenesis of the genital apparatus in Orchestia gammarellus. U, undifferentiated stage; ♂ juvenile male AG, androgenic gland; a AG, anlage of AG; a vd, anlage of vas deferens; g, protogonia; gp, genital papilla; mc, nucleus of mesodermal cell; nc, nucleus of nurse cell; sg, spermatogonia (embedded in stroma of mesodermal cells); spc, spermatocyte; spz, spermatozoa; vd, vas deferens (originally adapted from Charniaux-Cotton and Payen, 1985 and reproduced by Subramoniam, 2016).
PFAS and steroid hormones in human milk
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Fig. 1 in Hormonal Regulation of Testicular Development in the Finless Porpoise Neophocaena asiaeorientalis sunameri: Preliminary Evidence from Testicular Histology and Immunohistochemistry
Fig. 1. Sampling location (black dot) of the East Asian finless porpoise.
supplementary materials: Sex hormones and the immune system: a bibliometric analysis
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Data from: Influence of a growth hormone transgene on the genetic architecture of growth-related traits: a comparative analysis between transgenic and wild-type coho salmon
Genetic engineering has been increasingly applied to many commercially important plant and animal species, generating phenotypic changes that are not observed in natural populations and creating genetic interactions that have not experienced natural selection. The degree to and way in which such human-induced genetic variation interacts with the rest of the genome is currently largely unknown. Integrating such information into ecological and risk assessment frameworks is crucial to understand the potential effects of genetically modified organisms in natural environments. Here, we performed QTL mapping to investigate the genetic architecture of growth-related traits in non-transgenic (NT) and growth hormone transgenic (T) coho salmon with large changes in growth and related physiology, with the aim of identifying how an inserted transgene might influence the opportunity for selection. These fish shared the same parental genetic background, thus allowing us to determine whether the same or different loci influence these traits within the two groups. The use of over 1700 loci, derived from Restriction site Associated DNA Sequencing, revealed that different genomic regions were linked with growth over time between the two groups. Additionally, the effect sizes of detected QTL appear to have been influenced by the transgene. Direct comparison of QTL between the T and NT fish during two size-matched periods identified little overlap in their location. Taken together, the results showed that the transgene altered the genetic basis of growth-related traits in this species. The study has important implications for effective conservation and management of wild populations experiencing introduction of transgenes. Evolutionary changes and their ecological consequences may occur at different rates and in different directions in NT versus T individuals in response to selection. Thus assessments of phenotypic change, and hence ecological risk, should be determined periodically to evaluate whether initial estimates made with founder strains remain valid.
Data from: Ecotypic divergence in Crepis tectorum (Asteraceae): inferring trait lability and correlational constraints from hormonally manipulated phenotypes
Despite long-standing interest in the evolutionary role of plant hormones, relatively few studies have used hormonally manipulated phenotypes to address questions about phenotypic evolution in plants. In the present investigation, I subjected plants of Crepis tectorum subsp. pumila to simple gibberellin (GA) treatments under both field and greenhouse conditions to assess developmental lability and correlational constraints of phenotypic traits that distinguish this dwarf ecotype from conspecific populations of the much taller weed ecotype (subsp. tectorum). The hormonally manipulated plants largely phenocopied the weed ecotype in leaf shape, plant stature and branching habit, indicative of both high lability and tight integration of traits reflecting gross morphology. Floral size traits sometimes declined after GA application, especially under field conditions. The latter result conflicts with the positive correlations between floral and vegetative size traits seen in previous comparative analyses and point to a tradeoff that could act as a constraint on ecotype divergence. The response to GA was consistent in direction for most traits, as opposed to the magnitude of response, which varied depending on the trait, the population, the growing environment, and the timing and level of hormone application. Taken together, the results highlight the potential for simple hormonal changes to cause large, plastic shifts in phenotype, but also illustrate the constrained nature of such influences.
Data from: Social conflict and costs of cooperation in meerkats are reflected in measures of stress hormones
Measures of glucocorticoid stress hormones (e.g. cortisol) have often been used to characterize conflict between subordinates and dominants. In cooperative breeders where subordinates seldom breed in their natal group and assist in offspring rearing, increases in subordinate glucocorticoid levels may be caused by conflict among subordinates as well as by the energetic costs of helping behavior and fluctuations in food availability may exacerbate these effects. During a 6-year study of Kalahari meerkats (Suricata suricatta), we investigated how social, environmental, and individual characteristics influenced subordinate plasma cortisol levels. Subordinate females, who are often the target of aggression from dominant females, had higher cortisol levels when the dominant female in their group was pregnant while the cortisol levels of subordinate males were unaffected by the reproductive state of dominant females. Subordinates of both sexes had higher cortisol levels if they belonged to groups 1) where neither of the dominant breeders in the group were their parents, 2) that contained a high proportion of subordinate females, or 3) that were either very large or very small, especially when the weather was cold and dry. Subordinates in groups containing young pups had higher cortisol levels. Finally, cortisol levels were higher in subordinates of both sexes if they were lighter for their age or had lost little body mass the night prior to sampling. Our results show that both social conflict and cooperative behavior can elevate glucocorticoid levels in subordinates and that both effects can be modified by variation in weather and food availability.
Figure 3 from: Gade G, Marco H (2011) The adipokinetic hormone family in Chrysomeloidea: structural and functional considerations. ZooKeys 157: 81-94. https://doi.org/10.3897/zookeys.157.1433
Figure 3 - LC-MS analysis of an extract from the corpora cardiaca of Chrysolina kuesteri. Material from the CC of the chrysomelid beetle, Chrysolina kuesteri was extracted with 80% methanol and analysed by LC-MS. (A) The total ion chromatogram. Full scan positive ESI mass spectra of the peaks shown in (A) with a retention time of 5.02 min (B), 5.23 min (C) and 5.36 min (D).
Figure 4 from: Gade G, Marco H (2011) The adipokinetic hormone family in Chrysomeloidea: structural and functional considerations. ZooKeys 157: 81-94. https://doi.org/10.3897/zookeys.157.1433
Figure 4 - The collision-induced dissociation ESI mass spectrum of an AKH peptide in Chrysolina kuesteri, and its deduced amino acid sequence. The CID MS2 ESI spectrum of the ion MH+ at m/z 987.5 (see Fig. 3D). The inset shows the sequence of the assigned peptide (corresponding to that of Emppe-AKH), together with the theoretical calculated masses for b-type and y-type diagnostic fragment ions which are observed in the MS2 mass spectrum.
Figure 6 from: Gade G, Marco H (2011) The adipokinetic hormone family in Chrysomeloidea: structural and functional considerations. ZooKeys 157: 81-94. https://doi.org/10.3897/zookeys.157.1433
Figure 6 - Putative molecular evolution of adipokinetic peptides in chrysomeloid beetles. A proposed scheme of the molecular evolution of adipokinetic peptides to give rise to the different structures observed in investigated chrysomeloid beetles. The inset shows the genetic code for the respective amino acids involved. Differences in amino acids or code nucleotides are given in bold lettering.
Figure 5 from: Gade G, Marco H (2011) The adipokinetic hormone family in Chrysomeloidea: structural and functional considerations. ZooKeys 157: 81-94. https://doi.org/10.3897/zookeys.157.1433
Figure 5 - The collision-induced dissociation ESI mass spectrum of an additional putative AKH peptide in Chrysolina kuesteri, and its deduced amino acid sequence. The CID MS2 ESI spectrum of the ion MH+ at m/z 1031.5 (see Fig. 3C). The inset shows the sequence of the assigned peptide (corresponding to an intermediate processing form of Peram-CAH-I, i.e. a non-amidated nonapeptide with a Gly residue at position 9). Also shown are the theoretical calculated masses for b-type and y-type diagnostic fragment ions which are observed in the MS2 mass spectrum.
Figure 2 from: Gade G, Marco H (2011) The adipokinetic hormone family in Chrysomeloidea: structural and functional considerations. ZooKeys 157: 81-94. https://doi.org/10.3897/zookeys.157.1433
Figure 2 - The collision-induced dissociation ESI mass spectrum of an AKH peptide in Ceroplesis capensis, and its deduced amino acid sequence. The CID MS2-ESI spectrum of the ion MH+ (m/z 973.5) in Fig. 1B. The inset shows the assigned peptide sequence (corresponding to that of Peram-CAH-I), together with the theoretical calculated masses for b-type and y-type diagnostic fragment ions which are observed in the MS2 mass spectrum.
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