Effects of the cone angle on the SERS detection sensitivity of tapered fiber probes.

In this paper, we investigate the effects of taper angle on the SERS detection sensitivity using tapered fiber probes with single-layer uniform gold spherical nanoparticles (GSNs). We show that the photothermal damage caused by excessive excitation laser power is the main factor that restricts the improvement of detection sensitivity of tapered fiber probes. Only when the cone angle is appropriate can a balance be achieved between increasing the excitation laser power and suppression of the transmission and scattering losses of the nanoparticles on the tapered fiber surface, thereby obtaining the best SERS detection sensitivity. Furthermore, the optimal cone angle depends on the complex refractive index of the equivalent composite dielectric (ECD) layer containing GSNs. For three SERS fiber probes with different ECD layers, the optimal cone angles measured are between 11-13°.

The genetic architecture of amylose biosynthesis in maize kernel.

Starch is the most abundant storage carbohydrate in maize kernel. The content of amylose and amylopectin confers unique properties in food processing and industrial application. Thus, the resurgent interest has been switched to the study of individual amylose or amylopectin rather than total starch, whereas the enzymatic machinery for amylose synthesis remains elusive. We took advantage of the phenotype of amylose content and the genotype of 9,007,194 single nucleotide polymorphisms from 464 inbred maize lines. The genome-wide association study identified 27 associated loci involving 39 candidate genes that were linked to amylose content including transcription factors, glycosyltransferases, glycosidases, as well as hydrolases. Except the waxy gene that encodes the granule-bound starch synthase, the remaining candidate genes were located in the upstream pathway of amylose synthesis, while the downstream members were already known from prior studies. The linked candidate genes could be transferred to manipulate amylose content and thus add value to maize kernel in the breeding programme.

Effects of waterlogging at different growth stages on the photosynthetic characteristics and grain yield of sorghum (Sorghum bicolor L.).

Various plants, including sorghum (Sorghum bicolor L.), are exposed to waterlogging; however, little is known about the effects of waterlogging at different growth stages on sorghum. A pot experiment was conducted using two sorghum hybrids, Jinuoliang 01 (JN01) and Jinza 31 (JZ31), to investigate the effects of waterlogging at different growth stages on the photosynthesis enzyme activity, chlorophyll content, malondialdehyde (MDA) content, photosynthetic parameters, dry matter accumulation, and grain yield. The experiment was conducted using waterlogging treatments implemented at the five-leaf stage (T1), flowering stage (T2), and filling stage (T3), using standard management (no waterlogging) as a control (CK). The adverse effects of waterlogging on sorghum growth varied with the waterlogging timing, with the maximum impact at T1, followed by T2 and T3. JZ31 was more sensitive to waterlogging compared to JN01. Waterlogged conditions inhibited the photosynthetic enzyme activity and reduced the chlorophyll content and photosynthesis, ultimately lowering the biomass yield and grain yield. The maximum yield loss was observed with the T1 waterlogging treatment; the grain yield of JN01 and JZ31 decreased by 52.01-54.58% and 69.52-71.97%, respectively, compared with CK. Furthermore, the decline in grain yield in T1 was associated with reducing grain number per panicle. These findings indicate that sorghum is sensitive to waterlogging at the five-leaf stage and JZ31 is more sensitive to waterlogging than JN01, which may provide a basis for selecting genotypes and management measures to cope with waterlogging in sorghum.

Graph Convolution and Self-attention Enhanced CNN with Domain Adaptation for Multi-site COVID-19 Diagnosis.

In 2019, coronavirus disease (COVID-19) is an acute disease that can rapidly develop into a very serious state. Therefore, it is of great significance to realize automatic COVID-19 diagnosis. However, due to the small difference in the characteristics of computed tomography (CT) between community acquire pneumonia (CP) and COVID-19, the existing model is unsuitable for the three-class classifications of healthy control, CP and COVID-19. The current model rarely optimizes the data from multiple centers. Therefore, we propose a diagnosis model for COVID-19 patients based on graph enhanced 3D convolution neural network (CNN) and cross-center domain feature adaptation. Specifically, we first design a 3D CNN with graph convolution module to enhance the global feature extraction capability of the CNN. Meanwhile, we use the domain adaptive feature alignment method to optimize the feature distance between different centers, which can effectively realize multi-center COVID-19 diagnosis. Our experimental results achieve quite promising COVID-19 diagnosis results, which show that the accuracy in the mixed dataset is 98.05%, and the accuracy in cross-center tasks are 85.29% and 87.53%.

GIONet: Global information optimized network for multi-center COVID-19 diagnosis via COVID-GAN and domain adversarial strategy.

The outbreak of coronavirus disease (COVID-19) in 2019 has highlighted the need for automatic diagnosis of the disease, which can develop rapidly into a severe condition. Nevertheless, distinguishing between COVID-19 pneumonia and community-acquired pneumonia (CAP) through computed tomography scans can be challenging due to their similar characteristics. The existing methods often perform poorly in the 3-class classification task of healthy, CAP, and COVID-19 pneumonia, and they have poor ability to handle the heterogeneity of multi-centers data. To address these challenges, we design a COVID-19 classification model using global information optimized network (GIONet) and cross-centers domain adversarial learning strategy. Our approach includes proposing a 3D convolutional neural network with graph enhanced aggregation unit and multi-scale self-attention fusion unit to improve the global feature extraction capability. We also verified that domain adversarial training can effectively reduce feature distance between different centers to address the heterogeneity of multi-center data, and used specialized generative adversarial networks to balance data distribution and improve diagnostic performance. Our experiments demonstrate satisfying diagnosis results, with a mixed dataset accuracy of 99.17% and cross-centers task accuracies of 86.73% and 89.61%.

Heterogeneous root zone salinity mitigates salt injury to Sorghum bicolor (L.) Moench in a split-root system.

The heterogeneous distribution of soil salinity across the rhizosphere can moderate salt injury and improve sorghum growth. However, the essential molecular mechanisms used by sorghum to adapt to such environmental conditions remain uncharacterized. The present study evaluated physiological parameters such as the photosynthetic rate, antioxidative enzyme activities, leaf Na+ and K+ contents, and osmolyte contents and investigated gene expression patterns via RNA sequencing (RNA-seq) analysis under various conditions of nonuniformly distributed salt. Totals of 5691 and 2047 differentially expressed genes (DEGs) in the leaves and roots, respectively, were identified by RNA-seq under nonuniform (NaCl-free and 200 mmol·L-1 NaCl) and uniform (100 mmol·L-1 and 100 mmol·L-1 NaCl) salinity conditions. The expression of genes related to photosynthesis, Na+ compartmentalization, phytohormone metabolism, antioxidative enzymes, and transcription factors (TFs) was enhanced in leaves under nonuniform salinity stress compared with uniform salinity stress. Similarly, the expression of the majority of aquaporins and essential mineral transporters was upregulated in the NaCl-free root side in the nonuniform salinity treatment, whereas abscisic acid (ABA)-related and salt stress-responsive TF transcripts were more abundant in the high-saline root side in the nonuniform salinity treatment. In contrast, the expression of the DEGs identified in the nonuniform salinity treatment remained virtually unaffected and was even downregulated in the uniform salinity treatment. The transcriptome findings might be supportive of the increased photosynthetic rate, reduced Na+ levels, increased antioxidative capability in the leaves and, consequently, the growth recovery of sorghum under nonuniform salinity stress as well as the inhibited sorghum growth under uniform salinity conditions. The increased expression of salt resistance genes activated in response to the nonuniform salinity distribution implied that the cross-talk between the nonsaline and high-saline sides of the roots exposed to nonuniform salt stress is potentially regulated.

Genome Sequencing and Assembly by Long Reads in Plants.

Plant genomes generated by Sanger and Next Generation Sequencing (NGS) have provided insight into species diversity and evolution. However, Sanger sequencing is limited in its applications due to high cost, labor intensity, and low throughput, while NGS reads are too short to resolve abundant repeats and polyploidy, leading to incomplete or ambiguous assemblies. The advent and improvement of long-read sequencing by Third Generation Sequencing (TGS) methods such as PacBio and Nanopore have shown promise in producing high-quality assemblies for complex genomes. Here, we review the development of sequencing, introducing the application as well as considerations of experimental design in TGS of plant genomes. We also introduce recent revolutionary scaffolding technologies including BioNano, Hi-C, and 10× Genomics. We expect that the informative guidance for genome sequencing and assembly by long reads will benefit the initiation of scientists' projects.

[Impacts of drought stress on leaf osmotic adjustment and chloroplast ultrastructure of stay-green sorghum].

Taking stay-green sorghum (B35) and non-stay green sorghum (Sanchisan) as test materials, a pot experiment was conducted to study their leaf osmotic adjustment and chloroplast ultrastructure at flowering and filling stages under impacts of drought stress (45% -50% of maximum field capacity). For the two sorghum lines, drought stress caused the reduction of their leaf free water content and relative water content, and increased the leaf bound water content, water saturation deficit, and electrical conductivity, with the increment or dement being larger for Sanchisan than for B35. Drought stress increased the leaf soluble sugar content and proline content, with the increment of the soluble sugar content being larger for Sanchisan and the increment of the proline content being larger for B35, while decreased the leaf soluble protein content, with the decrement being larger for Sanchisan than for B35. The chloroplast ultrastructure of both B35 and Sanchisan under drought stress was damaged to some extent, but the damaged degree was obviously lower for B35 than for Sanchisan. The findings indicated that stay-green sorghum had a greater adaptation to drought stress through stronger osmotic adjustment.

Cytoskeleton and plant salt stress tolerance.

The plant cytoskeleton is a highly dynamic component of plant cells and mainly based on microtubules (MTs), and actin filaments (AFs). The important functions of dynamic cytoskeletal networks have been indicated for almost every intracellular activity, from cell division to cell movement, cell morphogenesis and cell signal transduction. Recent studies have also indicated a close relationship between the plant cytoskeleton and plant salt stress tolerance. Salt stress is a significant factor that adversely affects crop productivity and quality of agricultural fields worldwide. The complicated regulatory mechanisms of plant salt tolerance have been the subject of intense research for decades. It is well accepted that cellular changes are very important in plant responses to salt stress. Because the organization and dynamics of cytoskeleton may play an important role in enhancing plant tolerance through various cell activities, study on salt stress-induced cytoskeletal network has been a vital topic in the subject of plant salt stress tolerance mechanisms. In this article, we introduce our recent work and review some current information on the dynamic changes and functions of cytoskeletal organization in response to salt stress. The accumulated data point to the existence of highly dynamic cytoskeletal arrays and the activation of complex cytoskeletal regulatory networks in response to salt stresses. The important role played by cytoskeleton in mediating the plant cell's response to salt stresses is particularly emphasized.