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Drought stress is an inevitable factor that disturbs the production of plants by altering morphological, physiological, biochemical, and molecular functions. Breeding for drought tolerance requires a complete understanding of the molecular factors controlling stress-responsive pathways. The plant responds to drought stress by adopting four mechanisms: avoidance, escape, tolerance, and recovery. Traditional plant-breeding tools have been employed to increase tolerance in cotton, but the complexity of drought tolerance has limited the use of these breeding methods. The plant adopts several key strategies against drought stress, such as activating the signaling network and activating molecular factors. Cotton breeders have been engaged in elucidating the molecular mechanisms of drought tolerance in cotton using significant molecular tools such as quantitative trait loci (QTL) mapping, transcription factor (TFs) analysis, transcriptome analysis, genome-wide association studies (GWAS), genetic engineering, and CRISPR/Cas9. Breeders have studied the functional description of genes and the interacting pathways accountable for controlling drought tolerance in cotton. Hundreds of genes/QTL have been identified, and many have been cloned for drought tolerance in cotton; however, a complete understanding of these traits still needs more study. This review presents a detailed overview of molecular tools, their application for improving drought tolerance in cotton, and their prospects. This review will help future researchers to conduct further studies to develop drought-tolerant cotton genotypes that can thrive under conditions of water scarcity. [ABSTRACT FROM AUTHOR]

Image quality and resolution are important factors affecting the application value of remote sensing images. Although increasing the optical aperture of space optical remote sensors (SORSs) improves image resolution, it exacerbates the effects of the space environment on imaging quality. Thus, this study proposes thermal active optical technology (TAO) to enhance image quality while increasing the optical aperture of SORSs by actively correcting in-orbit wavefront aberrations. Replacing traditional wavefront detection and reconstruction with numerical calculation and simulation analysis, more realistic in-orbit SORS wavefront aberrations are obtained. Numerical and finite element analyses demonstrate that nonlinearities in TAO control lead to the failure of traditional wavefront correction algorithms. To address this, we use a neural network algorithm combining CNN and ResNet. Simulation results show that the residual of the systematic wavefront RMS error for SORS reduces to 1/100 λ . The static and dynamic modular transfer functions are improved, and the structural similarity index is recovered by over 23%, highlighting the effectiveness of TAO in image quality enhancement. The static and thermal vacuum experiments demonstrate the wide applicability and engineering prospects of TAO.

ERBB2 mutations have been reported to occur in a subset of patients with lung adenocarcinomas or lung squamous cell carcinomas for some ethnicities, but it is unclear for Chinese patients with lung squamous cell carcinomas up to now. We retrospectively evaluated the status of ERBB2 mutations in a large cross-sectional cohort of 212 Chinese patients with non-small cell lung cancer (NSCLC) diagnosed in several hospitals from southern China during a time period of 1.5 years by polymerase chain reaction (PCR)-based direct sequencing and PCR-single strand conformation polymorphism (PCR-SSCP) analysis. ERBB2 mutation was found in 1 of 49 lung adenocarcinomas (2.0%) and none in lung squamous cell carcinomas and lung adenosquamous carcinomas. It implies the occurrence of ERBB2 mutations is infrequent in Chinese patients with NSCLC, especially in lung squamous cell carcinomas.