Diverse flowering responses subjecting to ambient high temperature in soybean under short-day conditions

Flowering time is one of important agronomic traits determining the crop yield and affected by high temperature. When facing high ambient temperature, plants often initiate early flowering as an adaptive strategy to escape the stress and ensure successful reproduction. However, here we find opposing ways in the short-day crop soybean to respond to different levels of high temperatures, in which flowering accelerates when temperature changes from 25 to 30 °C, but delays when temperature reaches 35 °C under short day. phyA-E1, possibly photoperiodic pathway, is crucial for 35 °C-mediated late flowering, however, does not contribute to promoting flowering at 30 °C. 30 °C-induced up-regulation of FT2a and FT5a leads to early flowering, independent of E1. Therefore, distinct responsive mechanisms are adopted by soybean when facing different levels of high temperatures for successful flowering and reproduction.     

基于Landsat的重庆市生态环境质量动态监测及其时空格局演变分析

长江流域是我国重要的生态屏障之一,重庆市作为长江上游最后一道关口,研究其生态质量发展对于有效保护长江流域生态环境具有重要指导意义。基于2011—2021年间的Landsat影像等数据,计算遥感生态指数(Remote sensing based ecological index, RSEI),并采用Sen(Theil-Sen median)趋势分析法和MK(Mann-Kendall)检验研究其变化趋势以及利用Hurst指数模型分析RSEI的持续特征。利用空间转移矩阵和重心迁移模型研究其在空间上分布特征的变化情况,最后使用降水、风速、近地表气温、海拔等辅助数据为影响因素,结合地理探测器进一步探究RSEI变化驱动力,探讨重庆市2011—2021的RSEI空间分布及演变趋势。结果表明：(1)重庆市多年平均RSEI为0.593,使用等间距法将其划分的等级为差、较差、中等、良、优的面积占比分别为2.48%、8.28%、38.32%、41,87%、9.05%。从整体来看重庆市生态质量水平较高,重庆市年际RSEI以显著趋势波动增长。(2)RSEI等级为差的地区空间上主要集中于重庆西部;较差等级主要围绕...     

Marginal proportional hazards models for clustered interval-censored data with time-dependent covariates

The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana's national adoption of a universal test and treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy modified the preventative effects of the study intervention. To address such questions, we adopt a stratified proportional hazards model for clustered interval-censored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on either the baseline hazard functions or the within-cluster dependence structure. We show that the resulting estimators for the regression parameters are consistent and asymptotically normal. We also propose and provide theoretical justification for the use of the profile composite likelihood function to construct a robust sandwich estimator for the variance. We characterize the finite-sample performance and robustness of these estimators through extensive simulation studies. Finally, we conclude by applying this stratified proportional hazards model to a re-analysis of the Botswana Combination Prevention Project, with the national adoption of a universal test and treat strategy now modeled as a time-dependent covariate.     

Pattern-based clustering of daily weigh-in trajectories using dynamic time warping

“Smart”-scales are a new tool for frequent monitoring of weight change as well as weigh-in behavior. These scales give researchers the opportunity to discover patterns in the frequency that individuals weigh themselves over time, and how these patterns are associated with overall weight loss. Our motivating data come from an 18-month behavioral weight loss study of 55 adults classified as overweight or obese who were instructed to weigh themselves daily. Adherence to daily weigh-in routines produces a binary times series for each subject, indicating whether a participant weighed in on a given day. To characterize weigh-in by time-invariant patterns rather than overall adherence, we propose using hierarchical clustering with dynamic time warping (DTW). We perform an extensive simulation study to evaluate the performance of DTW compared to Euclidean and Jaccard distances to recover underlying patterns in adherence time series. In addition, we compare cluster performance using cluster validation indices (CVIs) under the single, average, complete, and Ward linkages and evaluate how internal and external CVIs compare for clustering binary time series. We apply conclusions from the simulation to cluster our real data and summarize observed weigh-in patterns. Our analysis finds that the adherence trajectory pattern is significantly associated with weight loss.     

A carbon-13 nuclear magnetic resonance investigation of the metabolic fluxes associated withy glucose metabolism in human erythrocytes

We have used [2-¹³C]d-glucose and carbon-13 nuclear magnetic resonance (NMR) spectroscopy to investigate metabolic fluxes through the major pathways of glucose metabolism in intact human erythrocytes and to determine the interactions among these pathways under conditions that perturb metabolism. Using the method described, we have been able to measure fluxes through the pentose phosphate pathway, phosphofructokinase, the 2,3-diphosphoglycerate bypass, and phosphoglycerate kinase, as well as glucose uptake, concurrently and in a single experiment. We have measured these fluxes in normal human erythrocytes under the following conditions: (1) fully oxygenated; (2) treated with methylene blue; and (3) deoxygenated. This method makes it possible to monitor various metabolic effects of stresses in normal and pathological states. Not only has ¹³C-NMR spectroscopy proved to be a useful method for measuring in vivo flux through the pentose phosphate pathway, but it has also provided additional information about the cycling of metabolites through the non-oxidative portion of the pentose phosphate pathway. Our evidence from experiments with [1-¹³C]-, [2-¹³C]-, and [3-¹³C]d-glucoses indicates that there is an observable reverse flux of fructose 6-phosphate through the reactions catalyzed by transketolase and transaldolase, even in the presence of a net flux through the pentose phosphate pathway.     

ELF磁场对3T3细胞生长的影响及其机理的探讨

用细胞分析成像光盘记录系统测量了3T3细胞在某些ELF磁场和温度条件下生长周期的变化.实验结果表明,只有某些频率的ELF磁场才对细胞生长产生影响,磁场对细胞生长的影响还与培养细胞的生化环境有关.温度和ELF磁场都能影响细胞的生长.但二者的机理是不一样的,当撤除ELF磁场后,细胞在短时间内(2天以上)继续保持着ELF场对其生长的影响.而细胞生长周期能在短时间内(2天以内)随着温度的变化而变化.温度引起的细胞生长的变化可能与细胞内的各种生长因子、生物离子的活性有关.ELF磁场引起的细胞生长的变化可能与ELF磁场对细胞膜的影响有关,与细胞内细胞生长必不可少的生物离子(如Ca~(2+))的浓度有关.     

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.     

Toward a hypothesis-free understanding of how phosphorylation dynamically impacts protein turnover

The turnover measurement of proteins and proteoforms has been largely facilitated by workflows coupling metabolic labeling with mass spectrometry (MS), including dynamic stable isotope labeling by amino acids in cell culture (dynamic SILAC) or pulsed SILAC (pSILAC). Very recent studies including ours have integrated themeasurement of post-translational modifications (PTMs) at the proteome level (i.e., phosphoproteomics) with pSILAC experiments in steady state systems, exploring the link between PTMs and turnover at the proteome-scale. An open question in the field is how to exactly interpret these complex datasets in a biological perspective. Here, we present a novel pSILAC phosphoproteomic dataset which was obtained during a dynamic process of cell starvation using data-independent acquisition MS (DIA-MS). To provide an unbiased “hypothesis-free” analysis framework, we developed a strategy to interrogate how phosphorylation dynamically impacts protein turnover across the time series data. With this strategy, we discovered a complex relationship between phosphorylation and protein turnover that was previously underexplored. Our results further revealed a link between phosphorylation stoichiometry with the turnover of phosphorylated peptidoforms. Moreover, our results suggested that phosphoproteomic turnover diversity cannot directly explain the abundance regulation of phosphorylation during cell starvation, underscoring the importance of future studies addressing PTM site-resolved protein turnover.     

不同剂量右美托咪定联合超声引导下多点髂筋膜间隙阻滞在老年全髋关节置换术中的应用效果分析

摘要 目的：探讨超声引导下多点髂筋膜间隙阻滞联合不同剂量右美托咪定在老年全髋关节置换术（THA）中的应用效果。方法：选取2019年11月-2022年12月北京积水潭医院贵州医院择期行THA的老年患者120例,按照随机数字表法分为A组（n=40）、B组（n=40）、C组（n=40）,三组均接受超声引导下多点髂筋膜间隙阻滞治疗,在此基础上,A组、B组、C组分别给予0.5 μg/kg、1.0 μg/kg、1.5 μg/kg右美托咪定注射液。对比三组临床指标、血流动力学指标、应激反应指标、脑神经损伤情况,观察三组围术期间不良反应发生情况。结果：B组、C组的阻滞消退时间、拔管时间长于A组,首次下床时间短于A组（P<0.05）。B组、C组的阻滞消退时间、拔管时间、首次下床时间对比无差异（P>0.05）。三组麻醉诱导后即刻（T1）~手术结束时（T3）时间点心率（HR）、平均动脉压（MAP）升高后降低（P<0.05）。B组、C组的T1~T3时间点HR、MAP均低于A组,且B组低于C组（P<0.05）。三组T3时间点皮质醇（Cor）、白介素-6（IL-6）、肿瘤坏死因子-α（TNF-α）升高（P<0.05）。B组、C组的T3时间点Cor、IL-6、TNF-α均低于A组,且B组低于C组（P<0.05）。B组、C组的T3时间点中枢神经特异性蛋白（S100β）均低于A组,且B组低于C组（P<0.05）。B组、C组的T3时间点脑源性神经生长因子（BDNF）均高于A组,且B组高于C组（P<0.05）。三组不良反应发生率组间对比无差异（P>0.05）。结论：超声引导下多点髂筋膜间隙阻滞联合1.0 μg/kg右美托咪定在THA中具有更好的麻醉效果,可缩短首次下床时间,减轻机体应激反应、血流动力学波动以及脑部神经损伤。