Despite the established roles of the epigenetic factor UHRF1 in oncogenesis, no UHRF1-targeting therapeutics have been reported to date. In this study, we use fragment-based ligand discovery to identify novel scaffolds for targeting the isolated UHRF1 tandem Tudor domain (TTD), which recognizes the heterochromatin-associated histone mark H3K9me3 and supports intramolecular contacts with other regions of UHRF1. Using both binding-based and function-based screens of a ~ 2300-fragment library in parallel, we identified 2,4-lutidine as a hit for follow-up NMR and X-ray crystallography studies. Unlike previous reported ligands, 2,4-lutidine binds to two binding pockets that are in close proximity on TTD and so has the potential to be evolved into more potent inhibitors using a fragment-linking strategy. Our study provides a useful starting point for developing potent chemical probes against UHRF1.The role of the gut microbiome is increasingly being recognized by health scientists and veterinarians, yet its role in wild animals remains understudied. Variations in the gut microbiome could be the result of differential diets among individuals, such as variation between sexes, across seasons, or across reproductive stages. We evaluated the hypothesis that diet alters the avian gut microbiome using stable isotope analysis (SIA) and 16S rRNA gene sequencing. We present the first description of the thick-billed murre (Uria lomvia) fecal microbiome. The murre microbiome was dominated by bacteria from the genus Catellicoccus, ubiquitous in the guts of many seabirds. Microbiome variation was explained by murre diet in terms of proportion of littoral carbon, trophic position, and sulfur isotopes, especially for the classes Actinobacteria, Bacilli, Bacteroidia, Clostridia, Alphaproteobacteria, and Gammaproteobacteria. We also observed differences in the abundance of bacterial genera such as Catellicoccus and Cetobacterium between sexes and reproductive stages. These results are in accordance with behavioural observations of changes in diet between sexes and across the reproductive season. We concluded that the observed variation in the gut microbiome may be caused by individual prey specialization and may also be reinforced by sexual and reproductive stage differences in diet.Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. HC-7366 manufacturer Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen’s kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.Although a prototypical Su-Schrieffer-Heeger (SSH) soliton exhibits various important topological concepts including particle-antiparticle (PA) symmetry and fractional fermion charges, there have been only few advances in exploring such properties of topological solitons beyond the SSH model. Here, by considering a chirally extended double-Peierls-chain model, we demonstrate novel PA duality and fractional charge e/2 of topological chiral solitons even under the chiral symmetry breaking. This provides a counterexample to the belief that chiral symmetry is necessary for such PA relation and fractionalization of topological solitons in a time-reversal invariant topological system. Furthermore, we discover that topological chiral solitons are re-fractionalized into two subsolitons which also satisfy the PA duality. As a result, such dualities and fractionalizations support the topological [Formula see text] algebraic structures. Our findings will inspire researches seeking feasible and promising topological systems, which may lead to new practical applications such as solitronics.The aim of this study was to develop a predictive model of pediatric mortality in the early stages of intensive care unit (ICU) admission using machine learning. Patients less than 18 years old who were admitted to ICUs at four tertiary referral hospitals were enrolled. Three hospitals were designated as the derivation cohort for machine learning model development and internal validation, and the other hospital was designated as the validation cohort for external validation. We developed a random forest (RF) model that predicts pediatric mortality within 72 h of ICU admission, evaluated its performance, and compared it with the Pediatric Index of Mortality 3 (PIM 3). The area under the receiver operating characteristic curve (AUROC) of RF model was 0.942 (95% confidence interval [CI] = 0.912-0.972) in the derivation cohort and 0.906 (95% CI = 0.900-0.912) in the validation cohort. In contrast, the AUROC of PIM 3 was 0.892 (95% CI = 0.878-0.906) in the derivation cohort and 0.845 (95% CI = 0.817-0.873) in the validation cohort. The RF model in our study showed improved predictive performance in terms of both internal and external validation and was superior even when compared to PIM 3.Trehalose-6-phosphate synthase (TPS) and trehalase (TRE) directly regulate trehalose metabolism and indirectly regulate chitin metabolism in insects. Real-time quantitative PCR (RT-qPCR) and RNA interference (RNAi) were used to detect the expressions and functions of the ApTPS and ApTRE genes. Abnormal phenotypes were found after RNAi of ApTRE in the Acyrthosiphon pisum. The molting deformities were observed in two color morphs, while wing deformities were only observed in the red morphs. The RNAi of ApTPS significantly down-regulated the expression of chitin metabolism-related genes, UDP-N-acetyglucosamine pyrophosphorylase (ApUAP), chitin synthase 2 (Apchs-2), Chitinase 2, 5 (ApCht2, 5), endo-beta-N-acetylglucosaminidase (ApENGase) and chitin deacetylase (ApCDA) genes at 24 h and 48 h; The RNAi of ApTRE significantly down-regulated the expression of ApUAP, ApCht1, 2, 8 and ApCDA at 24 h and 48 h, and up-regulated the expression of glucose-6-phosphate isomerase (ApGPI) and Knickkopf protein (ApKNK) genes at 48 h.