Genome­wide identification and expression analysis of the UBC gene family in wheat (Triticum aestivum L.).

BACKGROUND: Ubiquitination is an important regulatory step of selective protein degradation in the plant UPS (ubiquitin-proteasome system), which is involved in various biological processes in eukaryotes. Ubiquitin-conjugating enzymes play an intermediate role in the process of protein ubiquitination reactions and thus play an essential role in regulating plant growth and response to adverse environmental conditions. However, a genome-wide analysis of the UBC gene family in wheat (Triticum aestivum L.) has not yet been performed. RESULTS: In this study, the number, physiochemical properties, gene structure, collinearity, and phylogenetic relationships of TaUBC family members in wheat were analyzed using bioinformatics methods. The expression pattern of TaUBC genes in different tissues/organs and developmental periods, as well as the transcript levels under abiotic stress treatment, were analyzed using RNA-Seq data and qRT-PCR. Meanwhile, favorable haplotypes of TaUBC25 were investigated based on wheat resequencing data of 681 wheat cultivars from the Wheat Union Database. The analyses identified a total of 93 TaUBC family members containing a UBC domain in wheat genome. These genes were unevenly distributed across 21 chromosomes, and numerous duplication events were observed between gene members. Based on phylogenetic analysis, the TaUBC family was divided into 13 E2 groups and a separate UEV group. We investigated the expression of TaUBC family genes under different tissue/organ and stress conditions by quantitative real-time PCR (qRT-PCR) analysis. The results showed that some TaUBC genes were specifically expressed in certain tissues/organs and that most TaUBC genes responded to NaCl, PEG6000, and ABA treatment with different levels of expression. In addition, we performed association analysis for the two haplotypes based on key agronomic traits such as thousand-kernel weight (TKW), kernel length (KL), kernel weight (KW), and kernel thickness (KT), examining 122 wheat accessions at three environmental sites. The results showed that TaUBC25-Hap II had significantly higher TKW, KL, KW, and KT than TaUBC25-Hap I. The distribution analysis of haplotypes showed that TaUBC25-Hap II was preferred in the natural population of wheat. CONCLUSION: Our results identified 93 members of the TaUBC family in wheat, and several genes involved in grain development and abiotic stress response. Based on the SNPs detected in the TaUBC sequence, two haplotypes, TaUBC25-Hap I and TaUBC25-Hap II, were identified among wheat cultivars, and their potential value for wheat breeding was validated by association analysis. The above results provide a theoretical basis for elucidating the evolutionary relationships of the TaUBC gene family and lay the foundation for studying the functions of family members in the future.

Population genetic structure of Hymenopellis radicata germplasm resources based on genome re-sequencing.

Through whole-genome re-sequencing of 18 Hymenopellis radicata germplasm resources collected from diverse regions in China, we identified significant variations in the form of Single Nucleotide Polymorphisms (SNPs) and Insertions and Deletions (InDels). These variations were comprehensively annotated, shedding light on the mutation types present in the entire genome of the H. radicata germplasm. This analysis revealed the number and position information of each mutation and provided insights into the overall genomic landscape of H. radicata germplasm. Utilizing SNP data, we delved into the population structure of the 18 H. radicata germplasm resources. The results indicated the presence of 2,335,179 Indel sites and 12,050,448 SNP sites. The population structure analysis unveiled two distinct subgroups among the H. radicata germplasm resources. Phenotypic statistics, principal component analysis, and phylogenetic tree results echoed the findings of the population structure analysis. Different strains of H. radicata from various regions in China exhibited notable differences in genetic diversity, mycelial growth rate, yield, and fruiting body characteristics. Significant disparities were observed between the two subgroups, while strains within each subgroup shared common characteristics. This research establishes a solid foundation for integrating H. radicata into diverse breeding programs. The data underscore the potential of H. radicata for genetic improvement and exploitation in breeding initiatives, paving the way for future advancements in this field.

Reference gene selection for quantitative real-time PCR analysis of Hymenopellis radicata under abiotic stress.

Hymenopellis radicata (H. radicata) is an edible fungus rich in protein and mineral elements, with high edible and medical value. And reference genes suitable for normalization of qRT-PCR data from this species have not been investigated. In this study, therefore, we selected 11 housekeeping genes common in biology. The expression levels of these housekeeping genes were measured in three different tissues and six different abiotic stress treatments in mycelium. They were evaluated for expression stability using online tools. The results showed that gene ACT could be stable expressed in all samples. The expressions of genes TUB and UBQ10 are the most stable under heat stress, ACT and EF are the most stable genes under salt stress, ACT and TUB are the most stable genes under oxidation stress, RPL6 and EF are the most stable genes under pH condition, ACT and RPB2 are the most stable genes under cadmium stress, and RPB2 and UBC are the most stable genes under drought condition. ACT and PP2A are the most stable genes at different tissue sites. This study is of great help to explore the gene expression pattern of H. radicata, and also provides reference for internal reference gene screening under other conditions.

Genome-wide identification, gene expression and haplotype analysis of the rhomboid-like gene family in wheat (Triticum aestivum L.).

The rhomboid-like (RBL) gene encodes serine protease, which plays an important role in the response to cell development and diverse stresses. However, genome-wide identification, expression profiles, and haplotype analysis of the RBL family genes have not been performed in wheat (Triticum aestivum L.). This study investigated the phylogeny and diversity of the RBL family genes in the wheat genome through various approaches, including gene structure analysis, evolutionary relationship analysis, promoter cis-acting element analysis, expression pattern analysis, and haplotype analysis. The 41 TaRBL genes were identified and divided into five subfamilies in the wheat genome. RBL family genes were expanded through segmented duplication and purification selection. The cis-element analysis revealed their involvement in various stress responses and plant development. The results of RNA-seq and quantitative real-time-PCR showed that TaRBL genes displayed higher expression levels in developing spike/grain and were differentially regulated under polyethylene glycol, NaCl, and abscisic acid treatments, indicating their roles in grain development and abiotic stress response. A kompetitive allele-specific PCR molecular marker was developed to confirm the single nucleotide polymorphism of TaRBL14a gene in 263 wheat accessions. We found that the elite haplotype TaRBL14a-Hap2 showed a significantly higher 1000-grain weight than TaRBL14a-Hap11 in at least three environments, and the TaRBL14a-Hap2 was positively selected in wheat breeding. The findings will provide a good insight into the evolutionary and functional characteristics of the TaRBL genes family in wheat and lay the foundation for future exploration of the regulatory mechanisms of TaRBL genes in plant growth and development, as well as their response to abiotic stresses.

Single-shot Fourier ptychographic microscopy with isotropic lateral resolution via polarization-multiplexed LED illumination.

Fourier ptychographic microscopy (FPM) has emerged as a new wide-field and high-resolution computational imaging technique in recent years. To ensure data redundancy for a stable convergence solution, conventional FPM requires dozens or hundreds of raw images, increasing the time cost for both data collection and computation. Here, we propose a single-shot Fourier ptychographic microscopy with isotropic lateral resolution via polarization-multiplexed LED illumination, termed SIFPM. Three LED elements covered with 0°/45°/135° polarization films, respectively, are used to provide numerical aperture-matched illumination for the sample simultaneously. Meanwhile, a polarization camera is utilized to record the light field distribution transmitted through the sample. Based on weak object transfer functions, we first obtain the amplitude and phase estimations of the sample by deconvolution, and then we use them as the initial guesses of the FPM algorithm to refine the accuracy of reconstruction. We validate the complex sample imaging performance of the proposed method on quantitative phase target, unstained and stained bio-samples. These results show that SIFPM can realize quantitative imaging for general samples with the resolution of the incoherent diffraction limit, permitting high-speed quantitative characterization for cells and tissues.

Genome-wide identification and analysis of the GGCT gene family in wheat.

BACKGROUND: γ-glutamylcyclotransferase (GGCT), an enzyme to maintain glutathione homeostasis, plays a vital role in the response to plant growth and development as well as the adaptation to various stresses. Although the GGCT gene family analysis has been conducted in Arabidopsis and rice, the family genes have not yet been well identified and analyzed at the genome-wide level in wheat (Triticum aestivum L.). RESULTS: In the present study, 20 TaGGCT genes were identified in the wheat genome and widely distributed on chromosomes 2A, 2B, 2D, 3A, 4A, 5A, 5B, 5D, 6A, 6B, 6D, 7A, 7B, and 7D. Phylogenetic and structural analyses showed that these TaGGCT genes could be classified into three subfamilies: ChaC, GGGACT, and GGCT-PS. They exhibited similar motif compositions and distribution patterns in the same subgroup. Gene duplication analysis suggested that the expansion of TaGGCT family genes was facilitated by segmental duplications and tandem repeats in the wheat evolutionary events. Identification of diverse cis-acting response elements in TaGGCT promoters indicated their potential fundamental roles in response to plant development and abiotic stresses. The analysis of transcriptome data combined with RT-qPCR results revealed that the TaGGCTs genes exhibited ubiquitous expression across plant organs, with highly expressed in roots, stems, and developing grains. Most TaGGCT genes were up-regulated after 6 h under 20% PEG6000 and ABA treatments. Association analysis revealed that two haplotypes of TaGGCT20 gene displayed significantly different Thousand-kernel weight (TKW), Kernel length (KL), and Kernel width (KW) in wheat. The geographical and annual distribution of the two haplotypes of TaGGCT20 gene further revealed that the frequency of the favorable haplotype TaGGCT20-Hap-I was positively selected in the historical breeding process of wheat. CONCLUSION: This study investigated the genome-wide identification, structure, evolution, and expression analysis of TaGGCT genes in wheat. The motifs of TaGGCTs were highly conserved throughout the evolutionary history of wheat. Most TaGGCT genes were highly expressed in roots, stems, and developing grains, and involved in the response to drought stresses. Two haplotypes were developed in the TaGGCT20 gene, where TaGGCT20-Hap-I, as a favorable haplotype, was significantly associated with higher TKW, KL, and KW in wheat, suggesting that the haplotype is used as a function marker for the selection in grain yield in wheat breeding.

Refractive index tomography with a physics-based optical neural network.

The non-interference three-dimensional refractive index (RI) tomography has attracted extensive attention in the life science field for its simple system implementation and robust imaging performance. However, the complexity inherent in the physical propagation process poses significant challenges when the sample under study deviates from the weak scattering approximation. Such conditions complicate the task of achieving global optimization with conventional algorithms, rendering the reconstruction process both time-consuming and potentially ineffective. To address such limitations, this paper proposes an untrained multi-slice neural network (MSNN) with an optical structure, in which each layer has a clear corresponding physical meaning according to the beam propagation model. The network does not require pre-training and performs good generalization and can be recovered through the optimization of a set of intensity images. Concurrently, MSNN can calibrate the intensity of different illumination by learnable parameters, and the multiple backscattering effects have also been taken into consideration by integrating a "scattering attenuation layer" between adjacent "RI" layers in the MSNN. Both simulations and experiments have been conducted carefully to demonstrate the effectiveness and feasibility of the proposed method. Experimental results reveal that MSNN can enhance clarity with increased efficiency in RI tomography. The implementation of MSNN introduces a novel paradigm for RI tomography.

Erratum: Fourier ptychography multi-parameter neural network with composite physical priori optimization: publisher's note.

[This corrects the article on p. 2739 in vol. 13, PMID: 35774326.].

Unsupervised adaptive coded illumination Fourier ptychographic microscopy based on a physical neural network.

Fourier Ptychographic Microscopy (FPM) is a computational technique that achieves a large space-bandwidth product imaging. It addresses the challenge of balancing a large field of view and high resolution by fusing information from multiple images taken with varying illumination angles. Nevertheless, conventional FPM framework always suffers from long acquisition time and a heavy computational burden. In this paper, we propose a novel physical neural network that generates an adaptive illumination mode by incorporating temporally-encoded illumination modes as a distinct layer, aiming to improve the acquisition and calculation efficiency. Both simulations and experiments have been conducted to validate the feasibility and effectiveness of the proposed method. It is worth mentioning that, unlike previous works that obtain the intensity of a multiplexed illumination by post-combination of each sequentially illuminated and obtained low-resolution images, our experimental data is captured directly by turning on multiple LEDs with a coded illumination pattern. Our method has exhibited state-of-the-art performance in terms of both detail fidelity and imaging velocity when assessed through a multitude of evaluative aspects.

Biosynthesis and Pharmacological Activities of Flavonoids, Triterpene Saponins and Polysaccharides Derived from Astragalus membranaceus.

Astragalus membranaceus (A. membranaceus), a well-known traditional herbal medicine, has been widely used in ailments for more than 2000 years. The main bioactive compounds including flavonoids, triterpene saponins and polysaccharides obtained from A. membranaceus have shown a wide range of biological activities and pharmacological effects. These bioactive compounds have a significant role in protecting the liver, immunomodulation, anticancer, antidiabetic, antiviral, antiinflammatory, antioxidant and anti-cardiovascular activities. The flavonoids are initially synthesized through the phenylpropanoid pathway, followed by catalysis with corresponding enzymes, while the triterpenoid saponins, especially astragalosides, are synthesized through the universal upstream pathways of mevalonate (MVA) and methylerythritol phosphate (MEP), and the downstream pathway of triterpenoid skeleton formation and modification. Moreover, the Astragalus polysaccharide (APS) possesses multiple pharmacological activities. In this review, we comprehensively discussed the biosynthesis pathway of flavonoids and triterpenoid saponins, and the structural features of polysaccharides in A. membranaceus. We further systematically summarized the pharmacological effects of bioactive ingredients in A. membranaceus, which laid the foundation for the development of clinical candidate agents. Finally, we proposed potential strategies of heterologous biosynthesis to improve the industrialized production and sustainable supply of natural products with pharmacological activities from A. membranaceus, thereby providing an important guide for their future development trend.

Consensus genomic regions for grain quality traits in wheat revealed by Meta-QTL analysis and in silico transcriptome integration.

Grain quality traits are the key factors that determine the economic value of wheat and are largely influenced by genetics and the environment. In this study, using a meta-analysis of quantitative trait loci (QTLs) and a comprehensive in silico transcriptome assessment, we identified key genomic regions and putative candidate genes for the grain quality traits protein content, gluten content, and test weight. A total of 508 original QTLs were collected from 41 articles on QTL mapping for the three quality traits in wheat published from 2003 to 2021. When these original QTLs were projected onto a high-density consensus map consisting of 14,548 markers, 313 QTLs resulted in the identification of 64 MQTLs distributed across 17 of the 21 chromosomes. Most of the meta-QTLs (MQTLs) were distributed on sub-genomes A and B. Compared with the original QTLs, the confidence interval (CI) of the MQTLs was smaller, with an average CI of 4.47 cM, while the projected QTLs CI was 11.13 cM (2.49-fold lower). The corresponding physical length of the MQTL ranged from 0.45 to 239.01 Mb. Thirty-one of these 64 MQTLs were validated in at least one genome-wide association study. In addition, five of the 64 MQTLs were selected and designated as core MQTLs. The 211 quality-related genes from rice were used to identify wheat homologs in MQTLs. In combination with transcriptional and omics analyses, 135 putative candidate genes were identified from 64 MQTL regions. The findings should contribute to a better understanding of the molecular genetic mechanisms underlying grain quality and the improvement of these traits in wheat breeding.

Application of omics technology in the research on edible fungi.

Edible fungus is a large fungus distributed all over the world and used as food and medicine. But people's understanding of edible fungi is not as much as that of ordinary crops, so people have started a number of research on edible fungi in recent years. With the development of science and technology, omics technology has gradually walked into people's vision. Omics technology has high sensitivity and wide application range, which is favored by researchers. The application of omics technology to edible fungus research is a major breakthrough, which has transferred edible fungus research from artificial cultivation to basic research. Now omics technology in edible fungi has been flexibly combined with other research methods, involving multiple studies of edible fungus, such as genetic breeding, growth and development, stress resistance, and the use of special components in edible fungus as pharmaceutical additives. It is believed that in the future, the research of edible fungi will also be brought to a deeper level with the help of omics technology. This paper introduces the application progress of modern omics technology to the study on edible fungi and mentions the application prospect of edible fungi research with the constant development of omics technology, thereby providing ideas for the follow-up in-depth research on edible fungi.

Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment.

BACKGROUND: Grain yield is a complex and polygenic trait influenced by the photosynthetic source-sink relationship in wheat. The top three leaves, especially the flag leaf, are considered the major sources of photo-assimilates accumulated in the grain. Determination of significant genomic regions and candidate genes affecting flag leaf size can be used in breeding for grain yield improvement. RESULTS: With the final purpose of understanding key genomic regions for flag leaf size, a meta-analysis of 521 initial quantitative trait loci (QTLs) from 31 independent QTL mapping studies over the past decades was performed, where 333 loci eventually were refined into 64 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs was 5.28 times less than that of the initial QTLs. Thirty-three MQTLs overlapped the marker trait associations (MTAs) previously reported in genome-wide association studies (GWAS) for flag leaf traits in wheat. A total of 2262 candidate genes for flag leaf size, which were involved in the peroxisome, basal transcription factor, and tyrosine metabolism pathways were identified in MQTL regions by the in silico transcriptome assessment. Of these, the expression analysis of the available genes revealed that 134 genes with > 2 transcripts per million (TPM) were highly and specifically expressed in the leaf. These candidate genes could be critical to affect flag leaf size in wheat. CONCLUSIONS: The findings will make further insight into the genetic determinants of flag leaf size and provide some reliable MQTLs and putative candidate genes for the genetic improvement of flag leaf size in wheat.

Meta-QTL analysis and in-silico transcriptome assessment for controlling chlorophyll traits in common wheat.

Chlorophyll is an important plant molecule for absorbing light and transferring electrons to produce energy for photosynthesis, which has a significant impact on crop yield. To identify quantitative trait loci (QTL) controlling chlorophyll traits in wheat (Triticum aestivum L.), a comprehensive meta-analysis of 411 original QTLs for six chlorophyll traits was performed, including the evolution of soil plant analysis development (SPAD), chlorophyll content index (CCI), chlorophyll a content (Chla), chlorophyll b content (Chlb), chlorophyll content (Chl), and ratio of chlorophyll a to b (Chla/b), derived from 41 independent experiments conducted over the past two decades. Fifty-six consensus meta-QTLs (MQTLs) were detected, unevenly distributed on chromosomes 1A, 1B, 2A, 2B, 2D, 3B, 3D, 4B, 4D, 5A, 5D, 6A, 6D, 7B, and 7D. The confidence interval (CI) of the identified MQTLs was 0.18 to 15.07 cM, with an average of 5.74 cM, and 3.17-times narrower than that of the original QTLs. A total of 30 MQTLs were aligned with marker-trait associations (MTAs) reported in genome-wide association studies (GWAS) for chlorophyll traits in wheat. Based on MQTL-flanking marker information and homology analyses combined with RNA-seq data, 136 putative candidate genes were identified in MQTL regions, involved in porphyrin metabolism, photosynthesis, terpene biosynthesis, glyoxylate and dicarboxylate metabolism, and secondary metabolites. The results of this study contribute to the understanding of the genetic basis for controlling chlorophyll traits and can be used in breeding wheat with high photosynthetic efficiency.

GhAP1-D3 positively regulates flowering time and early maturity with no yield and fiber quality penalties in upland cotton.

Flowering time (FTi) is a major factor determining how quickly cotton plants reach maturity. Early maturity greatly affects lint yield and fiber quality and is crucial for mechanical harvesting of cotton in northwestern China. Yet, few quantitative trait loci (QTLs) or genes regulating early maturity have been reported in cotton, and the underlying regulatory mechanisms are largely unknown. In this study, we characterized 152, 68, and 101 loci that were significantly associated with the three key early maturity traits-FTi, flower and boll period (FBP) and whole growth period (WGP), respectively, via four genome-wide association study methods in upland cotton (Gossypium hirsutum). We focused on one major early maturity-related genomic region containing three single nucleotide polymorphisms on chromosome D03, and determined that GhAP1-D3, a gene homologous to Arabidopsis thaliana APETALA1 (AP1), is the causal locus in this region. Transgenic plants overexpressing GhAP1-D3 showed significantly early flowering and early maturity without penalties for yield and fiber quality compared to wild-type (WT) plants. By contrast, the mutant lines of GhAP1-D3 generated by genome editing displayed markedly later flowering than the WT. GhAP1-D3 interacted with GhSOC1 (SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1), a pivotal regulator of FTi, both in vitro and in vivo. Changes in GhAP1-D3 transcript levels clearly affected the expression of multiple key flowering regulatory genes. Additionally, DNA hypomethylation and high levels of H3K9ac affected strong expression of GhAP1-D3 in early-maturing cotton cultivars. We propose that epigenetic modifications modulate GhAP1-D3 expression to positively regulate FTi in cotton through interaction of the encoded GhAP1 with GhSOC1 and affecting the transcription of multiple flowering-related genes. These findings may also lay a foundation for breeding early-maturing cotton varieties in the future.

Recent advances in catalytic synthesis of 2,5-furandimethanol from 5-hydroxymethylfurfural and carbohydrates.

5-Hydroxymethylfurfural (HMF) is a versatile platform chemical derived from the dehydration of renewable carbohydrates (typically glucose/fructose-based monosaccharides, oligosaccharides, and polysaccharides). Some useful compounds, such as 2,5-furandimethanol (FDM), 2,5-dimethylfuran (DMF) and 2,5-dimethyltetrahydrofuran (DMTHF), have been synthesized by reduction of HMF. Among these, FDM is a promising diol and can be further converted towards fine chemicals, liquid fuels and polymer materials. In this review, some typical catalytic systems for the synthesis of FDM from both HMF and carbohydrates were summarized. The discussion focused on controlling the reaction networks for the reduction of HMF. The reaction mechanisms and the stability of the catalysts were introduced briefly. Last but not least, the prospects of effective production of FDM were discussed as well.

Early monitoring-to-warning Internet of Things system for emerging infectious diseases via networking of light-triggered point-of-care testing devices.

Early monitoring and warning arrangements are effective ways to distinguish infectious agents and control the spread of epidemic diseases. Current testing technologies, which cannot achieve rapid detection in the field, have a risk of slowing down the response time to the disease. In addition, there is still no epidemic surveillance system, implementing prevention and control measures is slow and inefficient. Motivated by these clinical needs, a sample-to-answer genetic diagnosis platform based on light-controlled capillary modified with a photocleavable linker is first developed, which could perform nucleic acid separation and release by light irradiation in less than 30 seconds. Then, on site polymerase chain reaction was performed in a handheld closed-loop convective system. Test reports are available within 20 min. Because this method is portable, rapid, and easy to operate, it has great potential for point-of-care testing. Additionally, through multiple device networking, a real-time artificial intelligence monitoring system for pathogens was developed on a cloud server. Through data reception, analysis, and visualization, the system can send early warning signals for disease control and prevention. Thus, anti-epidemic measures can be implemented effectively, and deploying and running this system can improve the capabilities for the prevention and control of infectious diseases.

Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.).

BACKGROUND: Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes. RESULTS: The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites. CONCLUSIONS: Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.

Clinical tooth segmentation based on local enhancement.

The tooth arrangements of human beings are challenging to accurately observe when relying on dentists' naked eyes, especially for dental caries in children, which is difficult to detect. Cone-beam computer tomography (CBCT) is used as an auxiliary method to measure patients' teeth, including children. However, subjective and irreproducible manual measurements are required during this process, which wastes much time and energy for the dentists. Therefore, a fast and accurate tooth segmentation algorithm that can replace repeated calculations and annotations in manual segmentation has tremendous clinical significance. This study proposes a local contextual enhancement model for clinical dental CBCT images. The local enhancement model, which is more suitable for dental CBCT images, is proposed based on the analysis of the existing contextual models. Then, the local enhancement model is fused into an encoder-decoder framework for dental CBCT images. At last, extensive experiments are conducted to validate our method.

Robust full-pose-parameter estimation for the LED array in Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) can achieve quantitative phase imaging with a large space-bandwidth product by synthesizing a set of low-resolution intensity images captured under angularly varying illuminations. Determining accurate illumination angles is critical because the consistency between actual systematic parameters and those used in the recovery algorithm is essential for high-quality imaging. This paper presents a full-pose-parameter and physics-based method for calibrating illumination angles. Using a physics-based model constructed with general knowledge of the employed microscope and the brightfield-to-darkfield boundaries inside captured images, we can solve for the full-pose parameters of misplaced LED array, which consist of the distance between the sample and the LED array, two orthogonal lateral shifts, one in-plane rotation angle, and two tilt angles, to correct illumination angles precisely. The feasibility and effectiveness of the proposed method for recovering random or remarkable pose parameters have been demonstrated by both qualitative and quantitative experiments. Due to the completeness of the pose parameters, the clarity of the physical model, and the high robustness for arbitrary misalignments, our method can significantly facilitate the design, implementation, and application of concise and robust FPM platforms.