Nocturnal gibberellin biosynthesis is carbon dependent and adjusts leaf expansion rates to variable conditions

Optimal plant growth performance requires that the presence and action of growth signals, such as gibberellins (GAs), are coordinated with the availability of photo-assimilates. Here, we studied the links between GA biosynthesis and carbon availability, and the subsequent effects on growth. We established that carbon availability, light and dark cues, and the circadian clock ensure the timing and magnitude of GA biosynthesis and that disruption of these factors results in reduced GA levels and expression of downstream genes. Carbon-dependent nighttime induction of gibberellin 3-beta-dioxygenase 1 (GA3ox1) was severely hampered when preceded by reduced daytime light availability, leading specifically to reduced bioactive GA₄ levels, and coinciding with a decline in leaf expansion rate during the night. We attributed this decline in leaf expansion mostly to reduced photo-assimilates. However, plants in which GA limitation was alleviated had significantly improved leaf expansion, demonstrating the relevance of GAs in growth control under varying carbon availability. Carbon-dependent expression of upstream GA biosynthesis genes (Kaurene synthase and gibberellin 20 oxidase 1, GA20ox1) was not translated into metabolite changes within this short timeframe. We propose a model in which the extent of nighttime biosynthesis of bioactive GA₄ by GA3ox1 is determined by nighttime consumption of starch reserves, thus providing day-to-day adjustments of GA responses.

GA-sugar matching occurs specifically at night and determines day to day adjustment of GA levels and subsequent growth.     

Adjusting for time-varying confounders in survival analysis using structural nested cumulative survival time models

Accounting for time-varying confounding when assessing the causal effects of time-varying exposures on survival time is challenging. Standard survival methods that incorporate time-varying confounders as covariates generally yield biased effect estimates. Estimators using weighting by inverse probability of exposure can be unstable when confounders are highly predictive of exposure or the exposure is continuous. Structural nested accelerated failure time models (AFTMs) require artificial recensoring, which can cause estimation difficulties. Here, we introduce the structural nested cumulative survival time model (SNCSTM). This model assumes that intervening to set exposure at time $t$ to zero has an additive effect on the subsequent conditional hazard given exposure and confounder histories when all subsequent exposures have already been set to zero. We show how to fit it using standard software for generalized linear models and describe two more efficient, double robust, closed-form estimators. All three estimators avoid the artificial recensoring of AFTMs and the instability of estimators that use weighting by the inverse probability of exposure. We examine the performance of our estimators using a simulation study and illustrate their use on data from the UK Cystic Fibrosis Registry. The SNCSTM is compared with a recently proposed structural nested cumulative failure time model, and several advantages of the former are identified.     

Heterogeneous bone-marrow stromal progenitors drive myelofibrosis via a druggable alarmin axis

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Isolation and mapping of the first ruminant multidrug resistance genes

The first ruminant multiple drug resistance gene (MDR1) has been cloned and sequenced from sheep. Sequence data revealed the sheep MDR1 gene to have high sequence and structural similarity to other characterized MDR proteins from humans and rodents. A restriction fragment length polymorphism was discovered using the EcoRI enzyme and used to map the MDR1 gene to sheep chromosome 4. Physical mapping using fluorescent in situ hybridisation confirmed this map placement and assigned the MDR1 locus in the region 4q15-q21. The ovine MDR2 gene was also cloned and found to map to the same region as MDR1.     

Drought affects the rate and duration of organ growth but not inter-organ growth coordination

Drought at flowering and grain filling greatly reduces maize (Zea mays) yield. Climate change is causing earlier and longer-lasting periods of drought, which affect the growth of multiple maize organs throughout development. To study how long periods of water deficit impact the dynamic nature of growth, and to determine how these relate to reproductive drought, we employed a high-throughput phenotyping platform featuring precise irrigation, imaging systems, and image-based biomass estimations. Prolonged drought resulted in a reduction of growth rate of individual organs—though an extension of growth duration partially compensated for this—culminating in lower biomass and delayed flowering. However, long periods of drought did not affect the highly organized succession of maximal growth rates of the distinct organs, i.e. leaves, stems, and ears. Two drought treatments negatively affected distinct seed yield components: Prolonged drought mainly reduced the number of spikelets, and drought during the reproductive period increased the anthesis-silking interval. The identification of these divergent biomass and yield components, which were affected by the shift in duration and intensity of drought, will facilitate trait-specific breeding toward future climate-resilient crops.

When affected by drought, the plant responds by adjusting the growth of individual organs but not the coordination between the organs.     

The Effect of Weight Loss on Sleep‐disordered Breathing in Obese Teenagers

The objective of this study was to assess the effect of weight loss on sleep‐disordered breathing (SDB) in obese teenagers attending a residential treatment center. We also assessed whether the presence of SDB at the start of the weight management therapy was correlated with the amount of weight loss achieved. Obese teenagers were recruited and underwent anthropometry and sleep screening. Subjects with SDB (apnea hypopnea index (AHI) ≥ 2) received a follow‐up screening after weight loss therapy. Sixty‐one obese subjects were included (age = 14.8 ± 2.3; BMI z score = 2.7 ± 0.4). Thirty‐one subjects were diagnosed with SDB with 38% continuing to have residual SDB after a median weight loss of 24.0 kg. Subjects with SDB had a higher median relative decrease in BMI z score compared to subjects without SDB which was 30.5, 33.6, and 50.4% in the group with AHI of the baseline screening study < 2, 2 ≤ AHI < 5, and AHI ≥ 5, respectively (P = 0.02). AHI of the baseline screening study correlated significantly with the relative decrease in BMI z score (partial r = 0.37; P = 0.003), controlling for gender, age, initial BMI z score, and time between both studies. In conclusion, weight loss was successful in treating SDB in obese teenagers. In addition, there was a positive association between the severity of SDB at the start of the treatment and the amount of weight loss achieved. These findings are in favor of considering weight loss as a first‐line treatment for SDB in obese children and adolescents.     

Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench

As the cost of single-cell RNA-seq experiments has decreased, an increasing number of datasets are now available. Combining newly generated and publicly accessible datasets is challenging due to non-biological signals, commonly known as batch effects. Although there are several computational methods available that can remove batch effects, evaluating which method performs best is not straightforward. Here, we present BatchBench (https://github.com/cellgeni/batchbench), a modular and flexible pipeline for comparing batch correction methods for single-cell RNA-seq data. We apply BatchBench to eight methods, highlighting their methodological differences and assess their performance and computational requirements through a compendium of well-studied datasets. This systematic comparison guides users in the choice of batch correction tool, and the pipeline makes it easy to evaluate other datasets.