Journal: PLOS One

Article Title: A new mechanism regulating microglial NLRP3 inflammasome: FMR1 mediates NLRP3 mRNA stability

doi: 10.1371/journal.pone.0341867

Figure Lengend Snippet: (A) GO enrichment analysis of proteins pulled down by biotinylated NLRP3 3’UTR probes in LPS/ATP-stimulated BV2 cells. (B) Western blot analysis confirming the interaction between FMR1 and the NLRP3 3’UTR. Cell lysates (Input) and proteins pulled down by the biotinylated probe (Biotin Pull-down) were probed with an anti-FMR1 antibody. (C and D) qPCR (C) and western blot (D) analysis showing downregulation of FMR1 mRNA and protein expression in BV2 cells after LPS/ATP stimulation. Data are expressed as mean ± SD of 3 biologically independent experiments. * P < 0.05.

Article Snippet: For immunoblot analyses, we employed anti-NLRP3 mouse pAb (# GB114320 , 1:3000, Servicebio), anti-caspase-1 rabbit pAb (#ab286125, 1:200, Abcam), anti-FMR1 rabbit pAb (#13755–1-AP, 1:2000, Proteintech), anti-IGF2 BP3 rabbit pAb (#14642–1-AP, 1:30000, Proteintech), anti-IL-1β goat pAb (#AF-401-NA, 1:8000, R&D Systems), and anti-β-actin mouse mAb (#ab8226, 1:1000, Abcam).

Techniques: Western Blot, Expressing

Journal: iScience

Article Title: Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy

doi: 10.1016/j.isci.2023.108740

Figure Lengend Snippet: Allometric scaling of resting MRs by maximum likelihood Comparison of the allometric scaling of the rMR s of 20 vertebrates by (A) the conventional power law method, or (B) maximum likelihood scaling according to the optimal fit ( M 0.80 : pink circles), or two suboptimal fits ( M 0.75 , M 0.85 : gray circles).

Article Snippet: Contour plot of a hypothetical fitness landscape mapped on the relationship between the core-surface temperature gradient ( ΔTemp ) and Exp , the optimal allometric exponent for maximum likelihood fitting of cMR to the distribution of mirFam The dashed lines represent the log-based allometric exponents for field metabolic rate ( fMR ) and the theoretical heat dissipation limit ( HDL ) in mammals (Speakman and Król, 2010).

Techniques: Comparison

Journal: iScience

Article Title: Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy

doi: 10.1016/j.isci.2023.108740

Figure Lengend Snippet: “Sliding Window” comparison of the inference of sMR and cMR Staggered groups of five mammals ranked by T b were designated by the number of Boreoeutheria. (A) The effect of group composition on the mean value of mass or body temperature (right axis). (B) The effect of group composition on the allometric exponent of sMR (the slope of log rMR versus log M ), or the maximum likelihood exponent of cMR (means ±½ standard deviation).

Article Snippet: Contour plot of a hypothetical fitness landscape mapped on the relationship between the core-surface temperature gradient ( ΔTemp ) and Exp , the optimal allometric exponent for maximum likelihood fitting of cMR to the distribution of mirFam The dashed lines represent the log-based allometric exponents for field metabolic rate ( fMR ) and the theoretical heat dissipation limit ( HDL ) in mammals (Speakman and Król, 2010).

Techniques: Comparison, Standard Deviation

Journal: iScience

Article Title: Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy

doi: 10.1016/j.isci.2023.108740

Figure Lengend Snippet: Evolution of the number of microRNA families and cellular metabolic rate ( cMR ) (A) Distance tree of microRNA families. Branch lengths represent the total number of families. Node values represent the number of shared microRNA families in each clade. (B) An ultrametric reference phylogeny (inset) was assembled based on divergence times drawn from Álvarez-Carretero et al. (2022) for mammals and Irisarri et al. (2017) for earlier-branching vertebrates. The reference tree was rescaled (BayesTraits) according to the rate of evolution of cMR.75 , which corresponds to the optimal allometric scaling in a model of stabilizing selection of rMR with respect to the number of microRNA families in tetrapods and mammals (see Figure 5 ). Values of cMR.75 inferred at ancestral nodes (BayesTraits) were then mapped onto this variable rate tree (see ).

Article Snippet: Contour plot of a hypothetical fitness landscape mapped on the relationship between the core-surface temperature gradient ( ΔTemp ) and Exp , the optimal allometric exponent for maximum likelihood fitting of cMR to the distribution of mirFam The dashed lines represent the log-based allometric exponents for field metabolic rate ( fMR ) and the theoretical heat dissipation limit ( HDL ) in mammals (Speakman and Król, 2010).

Techniques: Selection

Journal: iScience

Article Title: Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy

doi: 10.1016/j.isci.2023.108740

Figure Lengend Snippet: Contour plot of a hypothetical fitness landscape mapped on the relationship between the core-surface temperature gradient ( ΔTemp ) and Exp , the optimal allometric exponent for maximum likelihood fitting of cMR to the distribution of mirFam The dashed lines represent the log-based allometric exponents for field metabolic rate ( fMR ) and the theoretical heat dissipation limit ( HDL ) in mammals (Speakman and Król, 2010). Silhouettes represent Boreoeutheria, earlier-branching mammals, and birds. (Phylophic © 2023: Marsupial, Sarah Werning; Dog, Tracy A. Heath; Bird, T. Michael Keesey). See for data sources.

Article Snippet: Contour plot of a hypothetical fitness landscape mapped on the relationship between the core-surface temperature gradient ( ΔTemp ) and Exp , the optimal allometric exponent for maximum likelihood fitting of cMR to the distribution of mirFam The dashed lines represent the log-based allometric exponents for field metabolic rate ( fMR ) and the theoretical heat dissipation limit ( HDL ) in mammals (Speakman and Król, 2010).

Techniques: