Notes

Crosstalk associated with Multi-Omics Systems along with Plants regarding Healing Value.
The inheritance of predisposition to nonsyndromic familial nonmedullary thyroid cancer (FNMTC) remains unclear. Here, we report six individuals with papillary thyroid cancer (PTC) in two unrelated nonsyndromic FNMTC families. Whole-exome sequencing revealed two germ-line loss-of-function variants occurring within a 28-bp fragment of WDR77, which encodes a core member of a transmethylase complex formed with the protein arginine methyltransferase PRMT5 that is responsible for histone H4 arginine 3 dimethylation (H4R3me2) in frogs and mammals. To date, the association of WDR77 with susceptibility to cancer in humans is unknown. A very rare heterozygous missense mutation (R198H) in WDR77 exon 6 was identified in one family of three affected siblings. A heterozygous splice-site mutation (c.619+1G > C) at the 5' end of intron 6 is present in three affected members from another family. The R198H variant impairs the interaction of WDR77 with PRMT5, and the splice-site mutation causes exon 6 skipping and results in a marked decrease in mutant messenger RNA, accompanied by obviously reduced H4R3me2 levels in mutation carriers. Knockdown of WDR77 results in increased growth of thyroid cancer cells. Whole-transcriptome analysis of WDR77 mutant patient-derived thyroid tissue showed changes in pathways enriched in the processes of cell cycle promotion and apoptosis inhibition. In summary, we report WDR77 mutations predisposing patients to nonsyndromic familial PTC and link germ-line WDR77 variants to human malignant disease.Genetic variance is not equal for all multivariate combinations of traits. This inequality, in which some combinations of traits have abundant genetic variation while others have very little, biases the rate and direction of multivariate phenotypic evolution. However, we still understand little about what causes genetic variance to differ among trait combinations. Here, we investigate the relative roles of mutation and selection in determining the genetic variance of multivariate phenotypes. We accumulated mutations in an outbred population of Drosophila serrata and analyzed wing shape and size traits for over 35,000 flies to simultaneously estimate the additive genetic and additive mutational (co)variances. This experimental design allowed us to gain insight into the phenotypic effects of mutation as they arise and come under selection in naturally outbred populations. Multivariate phenotypes associated with more (less) genetic variance were also associated with more (less) mutational variance, suggesting that differences in mutational input contribute to differences in genetic variance. However, mutational correlations between traits were stronger than genetic correlations, and most mutational variance was associated with only one multivariate trait combination, while genetic variance was relatively more equal across multivariate traits. Therefore, selection is implicated in breaking down trait covariance and resulting in a different pattern of genetic variance among multivariate combinations of traits than that predicted by mutation and drift. Overall, while low mutational input might slow evolution of some multivariate phenotypes, stabilizing selection appears to reduce the strength of evolutionary bias introduced by pleiotropic mutation.The p53 pathway is a universal tumor suppressor mechanism that limits tumor progression by triggering apoptosis or permanent cell cycle arrest, called senescence. In recent years, efforts to reactivate p53 function in cancer have proven to be a successful therapeutic strategy in murine models and have gained traction with the development of a range of small molecules targeting mutant p53. However, knowledge of the downstream mediators of p53 reactivation in different oncogenic contexts has been limited. Here, we utilized a panel of murine cancer cell lines from three distinct tumor types susceptible to alternative outcomes following p53 restoration to define unique and shared p53 transcriptional signatures. While we found that the majority of p53-bound sites and p53-responsive transcripts are tumor-type specific, analysis of shared targets identified a core signature of genes activated by p53 across all contexts. Furthermore, we identified repression of E2F and Myc target genes as a key feature of senescence. Characterization of p53-induced transcripts revealed core and senescence-specific long noncoding RNAs (lncRNAs) that are predominantly chromatin associated and whose production is coupled to cis-regulatory activities. Functional investigation of the contributions of p53-induced lncRNAs to p53-dependent outcomes highlighted Pvt1b, the p53-dependent isoform of Pvt1, as a mediator of p53-dependent senescence via Myc repression. Inhibition of Pvt1b led to decreased activation of senescence markers and increased levels of markers of proliferation. These findings shed light on the core and outcome-specific p53 restoration signatures across different oncogenic contexts and underscore the key role of the p53-Pvt1b-Myc regulatory axis in mediating proliferative arrest.G protein-coupled receptors (GPCRs) are important pharmaceutical targets for the treatment of a broad spectrum of diseases. Although there are structures of GPCRs in their active conformation with bound ligands and G proteins, the detailed molecular interplay between the receptors and their signaling partners remains challenging to decipher. To address this, we developed a high-sensitivity, high-throughput matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) method to interrogate the first stage of signal transduction. GPCR-G protein complex formation is detected as a proxy for the effect of ligands on GPCR conformation and on coupling selectivity. Over 70 ligand-GPCR-partner protein combinations were studied using as little as 1.25 pmol protein per sample. We determined the selectivity profile and binding affinities of three GPCRs (rhodopsin, beta-1 adrenergic receptor [β1AR], and angiotensin II type 1 receptor) to engineered Gα-proteins (mGs, mGo, mGi, and mGq) and nanobody 80 (Nb80). We found that GPCRs in the absence of ligand can bind mGo, and that the role of the G protein C terminus in GPCR recognition is receptor-specific. We exemplified our quantification method using β1AR and demonstrated the allosteric effect of Nb80 binding in assisting displacement of nadolol to isoprenaline. We also quantified complex formation with wild-type heterotrimeric Gαiβγ and β-arrestin-1 and showed that carvedilol induces an increase in coupling of β-arrestin-1 and Gαiβγ to β1AR. A normalization strategy allows us to quantitatively measure the binding affinities of GPCRs to partner proteins. We anticipate that this methodology will find broad use in screening and characterization of GPCR-targeting drugs.We extract the folding free energy landscape and the time-dependent friction function, the two ingredients of the generalized Langevin equation (GLE), from explicit-water molecular dynamics (MD) simulations of the α-helix forming polypeptide [Formula see text] for a one-dimensional reaction coordinate based on the sum of the native H-bond distances. Folding and unfolding times from numerical integration of the GLE agree accurately with MD results, which demonstrate the robustness of our GLE-based non-Markovian model. In contrast, Markovian models do not accurately describe the peptide kinetics and in particular, cannot reproduce the folding and unfolding kinetics simultaneously, even if a spatially dependent friction profile is used. Analysis of the GLE demonstrates that memory effects in the friction significantly speed up peptide folding and unfolding kinetics, as predicted by the Grote-Hynes theory, and are the cause of anomalous diffusion in configuration space. Our methods are applicable to any reaction coordinate and in principle, also to experimental trajectories from single-molecule experiments. Our results demonstrate that a consistent description of protein-folding dynamics must account for memory friction effects.The observational absence of giant convection cells near the Sun's outer surface is a long-standing conundrum for solar modelers. Selleckchem Polyethylenimine We herein propose an explanation. Rotation strongly influences the internal dynamics, leading to suppressed convective velocities, enhanced thermal-transport efficiency, and (most significantly) relatively smaller dominant length scales. We specifically predict a characteristic convection length scale of roughly 30-Mm throughout much of the convection zone, implying weak flow amplitudes at 100- to 200-Mm giant cells scales, representative of the total envelope depth. Our reasoning is such that Coriolis forces primarily balance pressure gradients (geostrophy). Background vortex stretching balances baroclinic torques. Both together balance nonlinear advection. Turbulent fluxes convey the excess part of the solar luminosity that radiative diffusion cannot. We show that these four relations determine estimates for the dominant length scales and dynamical amplitudes strictly in terms of known physical quantities. We predict that the dynamical Rossby number for convection is less than unity below the near-surface shear layer, indicating rotational constraint.Creating invariant representations from an everchanging speech signal is a major challenge for the human brain. Such an ability is particularly crucial for preverbal infants who must discover the phonological, lexical, and syntactic regularities of an extremely inconsistent signal in order to acquire language. Within the visual domain, an efficient neural solution to overcome variability consists in factorizing the input into a reduced set of orthogonal components. Here, we asked whether a similar decomposition strategy is used in early speech perception. Using a 256-channel electroencephalographic system, we recorded the neural responses of 3-mo-old infants to 120 natural consonant-vowel syllables with varying acoustic and phonetic profiles. Using multivariate pattern analyses, we show that syllables are factorized into distinct and orthogonal neural codes for consonants and vowels. Concerning consonants, we further demonstrate the existence of two stages of processing. A first phase is characterized by orthogonal and context-invariant neural codes for the dimensions of manner and place of articulation. Within the second stage, manner and place codes are integrated to recover the identity of the phoneme. We conclude that, despite the paucity of articulatory motor plans and speech production skills, pre-babbling infants are already equipped with a structured combinatorial code for speech analysis, which might account for the rapid pace of language acquisition during the first year.To mimic the mechanical response of passive biological cilia in complex fluids, we study the bending dynamics of an anchored elastic fiber submitted to a dilute granular suspension under shear. We show that the bending fluctuations of the fiber accurately encode minute variations of the granular suspension concentration. Indeed, besides the stationary bending induced by the continuous phase flow, the passage of each single particle induces an additional deflection. We demonstrate that the dominant particle/fiber interaction arises from contacts of the particles with the fiber, and we propose a simple elastohydrodynamics model to predict their amplitude. Our results provide a mechanistic and statistical framework to describe particle detection by biological ciliated systems.
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