The plant specific CDKB1-CYCB1 complex mediates homologous recombination repair in Arabidopsis

Upon DNA damage, cyclin-dependent kinases (CDKs) are typically inhibited to block cell division. In many organisms, however, it has been found that CDK activity is required for DNA repair, especially for homology-dependent repair (HR), resulting in the conundrum how mitotic arrest and repair can be reconciled. Here, we show that Arabidopsis thaliana solves this dilemma by a division of labor strategy. We identify the plant-specific B1-type CDKs (CDKB1s) and the class of B1-type cyclins (CYCB1s) as major regulators of HR in plants. We find that RADIATION SENSITIVE 51 (RAD51), a core mediator of HR, is a substrate of CDKB1-CYCB1 complexes. Conversely, mutants in CDKB1 and CYCB1 fail to recruit RAD51 to damaged DNA. CYCB1; 1 is specifically activated after DNA damage and we show that this activation is directly controlled by SUPPRESSOR OF GAMMA RESPONSE 1 (SOG1), a transcription factor that acts similarly to p53 in animals. Thus, while the major mitotic cell-cycle activity is blocked after DNA damage, CDKB1-CYCB1 complexes are specifically activated to mediate HR

Agreement on Web-based Diagnoses and Severity of Mental Health Problems in Norwegian Child and Adolescent Mental Health Services

Objective: This study examined the agreement between diagnoses and severity ratings assigned by clinicians using a structured web-based interview within a child and adolescent mental health outpatient setting. Method: Information on 100 youths was obtained from multiple informants through a web-based Development and Well-Being Assessment (DAWBA). Based on this information, four experienced clinicians independently diagnosed (according to the International Classification of Diseases Revision 10) and rated the severity of mental health problems according to the Health of the Nation Outcome Scales for Children and Adolescents (HoNOSCA) and the Children’s Global Assessment Scale (C-GAS). Results: Agreement for diagnosis was κ=0.69-0.82. Intra-class correlation for single measures was 0.78 for HoNOSCA and 0.74 for C-GAS, and 0.93 and 0.92, respectively for average measures. Conclusions: Agreement was good to excellent for all diagnostic categories. Agreement for severity was moderate, but improved to substantial when the average of the ratings given by all clinicians was considered. Therefore, we conclude that experienced clinicians can assign reliable diagnoses and assess severity based on DAWBA data collected online

Tuning hardness in calcite by incorporation of amino acids

Structural biominerals are inorganic/organic composites that exhibit remarkable mechanical properties. However, the structure–property relationships of even the simplest building unit—mineral single crystals containing embedded macromolecules—remain poorly understood. Here, by means of a model biomineral made from calcite single crystals containing glycine (0–7 mol%) or aspartic acid (0–4 mol%), we elucidate the origin of the superior hardness of biogenic calcite. We analysed lattice distortions in these model crystals by using X-ray diffraction and molecular dynamics simulations, and by means of solid-state nuclear magnetic resonance show that the amino acids are incorporated as individual molecules. We also demonstrate that nanoindentation hardness increased with amino acid content, reaching values equivalent to their biogenic counterparts. A dislocation pinning model reveals that the enhanced hardness is determined by the force required to cut covalent bonds in the molecules

Molecular Mechanisms of Fiber Differential Development between G. barbadense and G. hirsutum Revealed by Genetical Genomics

Cotton fiber qualities including length, strength and fineness are known to be controlled by genes affecting cell elongation and secondary cell wall (SCW) biosynthesis, but the molecular mechanisms that govern development of fiber traits are largely unknown. Here, we evaluated an interspecific backcrossed population from G. barbadense cv. Hai7124 and G. hirsutum acc. TM-1 for fiber characteristics in four-year environments under field conditions, and detected 12 quantitative trait loci (QTL) and QTL-by-environment interactions by multi-QTL joint analysis. Further analysis of fiber growth and gene expression between TM-1 and Hai7124 showed greater differences at 10 and 25 days post-anthesis (DPA). In this two period important for fiber performances, we integrated genome-wide expression profiling with linkage analysis using the same genetic materials and identified in total 916 expression QTL (eQTL) significantly (P<0.05) affecting the expression of 394 differential genes. Many positional cis-/trans-acting eQTL and eQTL hotspots were detected across the genome. By comparative mapping of eQTL and fiber QTL, a dataset of candidate genes affecting fiber qualities was generated. Real-time quantitative RT-PCR (qRT-PCR) analysis confirmed the major differential genes regulating fiber cell elongation or SCW synthesis. These data collectively support molecular mechanism for G. hirsutum and G. barbadense through differential gene regulation causing difference of fiber qualities. The down-regulated expression of abscisic acid (ABA) and ethylene signaling pathway genes and high-level and long-term expression of positive regulators including auxin and cell wall enzyme genes for fiber cell elongation at the fiber developmental transition stage may account for superior fiber qualities

Modeling causes of death: an integrated approach using CODEm

Background: Data on causes of death by age and sex are a critical input into health decision-making. Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them. However, cause of death data are often not available or are subject to substantial problems of comparability. We propose five general principles for cause of death model development, validation, and reporting.Methods: We detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death. Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes. The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates. All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance.Results: Ensemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval. We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers.Conclusions: CODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification. We demonstrate the utility of CODEm for the estimation of several major causes of death

Mechanisms of progression of chronic kidney disease

Chronic kidney disease (CKD) occurs in all age groups, including children. Regardless of the underlying cause, CKD is characterized by progressive scarring that ultimately affects all structures of the kidney. The relentless progression of CKD is postulated to result from a self-perpetuating vicious cycle of fibrosis activated after initial injury. We will review possible mechanisms of progressive renal damage, including systemic and glomerular hypertension, various cytokines and growth factors, with special emphasis on the renin–angiotensin–aldosterone system (RAAS), podocyte loss, dyslipidemia and proteinuria. We will also discuss possible specific mechanisms of tubulointerstitial fibrosis that are not dependent on glomerulosclerosis, and possible underlying predispositions for CKD, such as genetic factors and low nephron number

A Gene Regulatory Network for Root Epidermis Cell Differentiation in Arabidopsis

The root epidermis of Arabidopsis provides an exceptional model for studying the molecular basis of cell fate and differentiation. To obtain a systems-level view of root epidermal cell differentiation, we used a genome-wide transcriptome approach to define and organize a large set of genes into a transcriptional regulatory network. Using cell fate mutants that produce only one of the two epidermal cell types, together with fluorescence-activated cell-sorting to preferentially analyze the root epidermis transcriptome, we identified 1,582 genes differentially expressed in the root-hair or non-hair cell types, including a set of 208 “core” root epidermal genes. The organization of the core genes into a network was accomplished by using 17 distinct root epidermis mutants and 2 hormone treatments to perturb the system and assess the effects on each gene's transcript accumulation. In addition, temporal gene expression information from a developmental time series dataset and predicted gene associations derived from a Bayesian modeling approach were used to aid the positioning of genes within the network. Further, a detailed functional analysis of likely bHLH regulatory genes within the network, including MYC1, bHLH54, bHLH66, and bHLH82, showed that three distinct subfamilies of bHLH proteins participate in root epidermis development in a stage-specific manner. The integration of genetic, genomic, and computational analyses provides a new view of the composition, architecture, and logic of the root epidermal transcriptional network, and it demonstrates the utility of a comprehensive systems approach for dissecting a complex regulatory network