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.     

Coherent modeling of longitudinal causal effects on binary outcomes

Analyses of biomedical studies often necessitate modeling longitudinal causal effects. The current focus on personalized medicine and effect heterogeneity makes this task even more challenging. Toward this end, structural nested mean models (SNMMs) are fundamental tools for studying heterogeneous treatment effects in longitudinal studies. However, when outcomes are binary, current methods for estimating multiplicative and additive SNMM parameters suffer from variation dependence between the causal parameters and the noncausal nuisance parameters. This leads to a series of difficulties in interpretation, estimation, and computation. These difficulties have hindered the uptake of SNMMs in biomedical practice, where binary outcomes are very common. We solve the variation dependence problem for the binary multiplicative SNMM via a reparameterization of the noncausal nuisance parameters. Our novel nuisance parameters are variation independent of the causal parameters, and hence allow for coherent modeling of heterogeneous effects from longitudinal studies with binary outcomes. Our parameterization also provides a key building block for flexible doubly robust estimation of the causal parameters. Along the way, we prove that an additive SNMM with binary outcomes does not admit a variation independent parameterization, thereby justifying the restriction to multiplicative SNMMs.     

Elastic priors to dynamically borrow information from historical data in clinical trials

Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is to effectively borrow information from historical data while maintaining a reasonable type I error and minimal bias. We propose the elastic prior approach to address this challenge. Unlike existing approaches, this approach proactively controls the behavior of information borrowing and type I errors by incorporating a well-known concept of clinically significant difference through an elastic function, defined as a monotonic function of a congruence measure between historical data and trial data. The elastic function is constructed to satisfy a set of prespecified criteria such that the resulting prior will strongly borrow information when historical and trial data are congruent, but refrain from information borrowing when historical and trial data are incongruent. The elastic prior approach has a desirable property of being information borrowing consistent, that is, asymptotically controls type I error at the nominal value, no matter that historical data are congruent or not to the trial data. Our simulation study that evaluates the finite sample characteristic confirms that, compared to existing methods, the elastic prior has better type I error control and yields competitive or higher power. The proposed approach is applicable to binary, continuous, and survival endpoints.     

Impacts of iron on phosphate starvation-induced root hair growth in Arabidopsis

In Arabidopsis, phosphate starvation (-Pi)-induced responses of primary root and lateral root growth are documented to be correlated with ambient iron (Fe) status. However, whether and how Fe participates in -Pi-induced root hair growth (RHG) remains unclear. Here, responses of RHG to different Fe concentrations under Pi sufficiency/deficiency were verified. Generally, distinct dosage effects of Fe on RHG appeared at both Pi levels, due to the generation of reactive oxygen species. Following analyses using auxin mutants and the phr1 mutant revealed that auxin and the central regulator PHR1 are required for Fe-triggered RHG under −Pi. A further proteomic study indicated that processes of vesicle trafficking and auxin synthesis and transport were affected by Fe under −Pi, which were subsequently validated by using a vesicle trafficking inhibitor, brefeldin A, and an auxin reporter, R2D2. Moreover, vesicle trafficking-mediated recycling of PIN2, an auxin efflux transporter, was notably affected by Fe under -Pi. Correspondingly, root hairs of pin2 mutant displayed attenuated responses to Fe under -Pi. Together, we propose that Fe affects auxin signalling probably by modulating vesicle trafficking, chiefly the PIN2 recycling, which might work jointly with PHR1 on modulating -Pi-induced RHG.     

A meta-analysis on morphological,physiological and biochemical responses of plants with PGPR inoculation under drought stress

Plant growth-promoting rhizobacteria (PGPR) can help plants to resist drought stress. However, the mechanisms of how PGPR inoculation affect plant status under drought remain incompletely understood. We performed a meta-analysis of plant response to PGPR inoculation by compiling data from 57 PGPR-inoculation studies, including 2, 387 paired observations on morphological, physiological and biochemical parameters under drought and well-watered conditions. We compare the PGPR effect on plants performances among different groups of controls and treatments. Our results reveal that PGPR enables plants to restore themselves from drought-stressed to near a well-watered state, and that C4 plants recover better from drought stress than C3 plants. Furthermore, PGPR is more effective underdrought than well-watered conditions in increasing plant biomass, enhancing photosynthesis and inhibiting oxidant damage, and the responses of C4 plants to the PGPR effect was stronger than that of C3 plants under drought conditions. Additionally, PGPR belonging to different taxa and PGPR with different functional traits have varying degrees of drought-resistance effects on plants. These results are important to improve our understanding of the PGPR beneficial effects on enhanced drought-resistance of plants.     

Rhizosphere effect of nanoscale zero-valent iron on mycorrhiza-dependent maize assimilation

Rhizosphere effect of nanoscale zero-valent iron (nZVI) is crucial but little reported. Maize seeds were dressed with four nZVI concentrations (0, 1.0, 1.5, 2 g kg⁻¹) and inoculated with arbuscular mycorrhizal fungus (AMF) (Funneliformis mosseae). The SEM images illuminated that excessive nZVI particles (2 g kg⁻¹) were agglomerated on the surface of hyphae and spore, causing severe deformation and inactivation of AMF symbionts and thereafter inhibiting water uptake in maize seedlings. This restrained the scavenging effects of enzymatic (superoxide dismutase, peroxidase) and non-enzymatic compounds (proline & malondialdehyde) on ROS, and leaf photoreduction activity and gas exchange ability (p < 0.05). Interestingly, the inoculation with AMF effectively alleviated above negative effects. In contrast, appropriate dose of nZVI, that is, ≤1.5 g kg⁻¹, can be evenly distributed on the hyphae surface and form the ordered symbionts with AMF. This help massively to enhance hyphae growth and water and nutrient uptake. The enhanced mycorrhizal infection turned to promote rhizosphere symbiont activity and leaf Rubisco and Rubisco activase activity. Light compensation point was massively lowered, which increased photosynthetic carbon supply for AMF symbionts. Particularly, such priming effects were evidently enhanced by drought stress. Our findings provided a novel insight into functional role of nZVI in agriculture and AMF-led green production.     

Comment on “Is Yuan in China’s Three Gorges a Gibbon or a Langur?”

International Journal of Primatology -     

Responses of the desert green algae,Chlorella sp. to drought stress

Desert algae are important components of the desert soil crust and play an essential role in desert soil ecosystem development. Owing to their special habitat, desert algae are often exposed to harsh environments, among which drought represents the most common stress. Green algae are considered to have drought tolerance potential; however, only a few studies have investigated this. In this study, we selected the green alga Chlorella sp., which was isolated from desert soil, and studied its physiological response to polyethylene glycol (PEG) 6000-induced drought stress. The results showed that drought stress can affect the photosynthetic efficiency of Chlorella sp., reduce its water retention ability, and destroy its ultrastructure. However, Chlorella sp. can cope with drought stress through a series of physiological regulatory strategies. Protective strategies include quick recovery of photosynthetic efficiency and increased chlorophyll content. In addition, induced synthesis of soluble proteins, lipids, and extracellular polysaccharide (EPS), and accumulation of osmotic regulatory substances, such as sucrose and trehalose, also contribute to improving drought tolerance in Chlorella sp. This study provides insights into the physiological responses of Chlorella sp. to drought stress, which may be valuable for understanding the underlying drought adaptation mechanisms of desert green algae.     

A Rapid Determination of 30 Prohibited Pesticide Residues in Lycii Fructus by UPLC-MS/MS

Prohibited pesticide residues have become one of the main factors affecting the quality and safety of Lycii Fructus, However, rarely studies focus on the rapid determination of these residues. Here, a total of 30 kinds of prohibited pesticide residues were determined by ultra-performance liquid chromatography tandem triple quadrupole mass spectrometry (UPLC-MS/MS) in five different process ways. Pretreatment methods, chromatographic separation and detection conditions in mass spectrometry were all optimized accordingly. Among the five different pretreatment methods, the first and third solid phase extraction failed to provide high recoveries of sulfosulfuron compounds (both lower than 60%). Recovery of chlorphenamidine by the Quick Easy Cheap Effective Rugged and Safe multiresidue method (QuEChERS) was lower than 60%, which did not meet the requirements of trace determination. The concentrations of 30 prohibited pesticides residues treated by straightforward and solid phase extraction showed good linearity in their corresponding ranges, with correlation coefficients over 0.99. The average recoveries of straightforward ranged from 78.13% to 110.9%, while RSD ranged from 1.3% to 16.9%, albeit poor purification was observed. The recovery yield from solid phase extraction was between 67.75% and 103.08% with RSD value from 0.8% to 14.0%, which met the requirements of trace determination, this method has good precision and stability. These results could be employed to other Traditional Chinese Medicines (TCMs) in detecting prohibited pesticide residues.     

Comparative Transcriptome Analyses Reveal Genes Related to Spine Development in Cucumber (<i>Cucumis sativus</i>)

Fruit spine is an important quality trait of cucumber. To better understand the molecular basis of cucumber spine development and function, RNA-Seq was performed to identify differentially expressed genes (DEGs) in fruit spines of different development stages, namely, 8 days before anthesis (SpBA8), anthesis (SpA) and 8 days after anthesis (SpAA8). Stage-wise comparisons obtained 2,259 (SpBA8 vs. SpA), 4,551 (SpA vs. SpAA8), and 5,290 (SpBA8 vs. SpAA8) DEGs. All the DEGs were classified into eight expression clusters by trend analysis. Among these DEGs, in addition to the Mict, Tril, CsTTG1, CsMYB6, NS, and Tu genes that have been reported to regulate fruit spine formation, we found that the CsHDG11, CsSCL8, CsSPL8, CsZFP6 and CsZFP8 may also be involved in spine development in cucumber. Our study provides a theoretical basis for further research on molecular mechanisms of spine development in cucumber.