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Leaf morphology plays a crucial role in plant classification and provides a significant model for studying plant diversity while directly impacting photosynthetic efficiency. In the case of melons, leaf shape not only influences production and classification but also represents a key genetic trait that requires further exploration. In this study, we utilized forward genetics to pinpoint a recessive locus, dubbed Cmrl (Round leaf), which is responsible for regulating melon leaf shape. Through bulked segregant analysis sequencing and extensive evaluation of a two-year F2 population, we successfully mapped the Cmrl locus to a 537.07 kb region on chromosome 8 of the melon genome. Subsequent genetic fine-mapping efforts, leveraging a larger F2 population encompassing 1322 plants and incorporating F2:3 phenotypic data, further refined the locus to an 80.27 kb interval housing five candidate genes. Promoter analysis and coding sequence cloning confirmed that one of these candidates, MELO3C019152.2 (Cmppr encoding a pentatricopeptide repeat-containing family protein, Cmppr), stands out as a strong candidate gene for the Cmrl locus. Notably, comparisons of Cmrl expressions across various stages of leaf development and different leaf regions suggest a pivotal role of Cmrl in the morphogenesis of melon leaves.

Ascorbic acid (AsA), also known as vitamin C, is a well-known antioxidant found in living entities that plays an essential role in growth and development, as well as in defensive mechanisms. GDP-L-galactose phosphorylase (GGP) is a candidate gene regulating AsA biosynthesis at the translational and transcriptional levels in plants. In the current study, we conducted genome-wide bioinformatic analysis and pinpointed a single AsA synthesis rate-limiting enzyme gene in melon (CmGGP1). The protein prediction analysis depicted that the CmGGP1 protein does not have a signaling peptide or transmembrane structure and mainly functions in the chloroplast or nucleus. The constructed phylogenetic tree analysis in multispecies showed that the CmGGP1 protein has a highly conserved motif in cucurbit crops. The structural variation analysis of the CmGGP1 gene in different domesticated melon germplasms showed a single non-synonymous type-base mutation and indicated that this gene was selected by domestication during evolution. Wild-type (WT) and landrace (LDR) germplasms of melon depicted close relationships to each other, and improved-type (IMP) varieties showed modern domestication selection. The endogenous quantification of AsA content in both the young and old leaves of nine melon varieties exhibited the major differentiations for AsA synthesis and metabolism. The real-time quantitative polymerase chain reaction (qRT-PCR) analysis of gene co-expression showed that AsA biosynthesis in leaves was greater than AsA metabolic consumption, and four putative interactive genes (MELO3C025552.2, MELO3C007440.2, MELO3C023324.2, and MELO3C018576.2) associated with the CmGGP1 gene were revealed. Meanwhile, the CmGGP1 gene expression pattern was noticed to be up-regulated to varying degrees in different acclimated melons. We believe that the obtained results would provide useful insights for an in-depth genetic understanding of the AsA biosynthesis mechanism, aimed at the development of improving crop plants for melon.

Introduction: Hemodynamic diagnosis indexes (HDIs) can comprehensively evaluate the health status of the cardiovascular system (CVS), particularly for people older than 50 years and prone to cardiovascular disease (CVDs). However, the accuracy of non-invasive detection remains unsatisfactory. We propose a non-invasive HDIs model based on the non-linear pulse wave theory (NonPWT) applied to four limbs.Methods: This algorithm establishes mathematical models, including pulse wave velocity and pressure information of the brachial and ankle arteries, pressure gradient, and blood flow. Blood flow is key to calculating HDIs. Herein, we derive blood flow equation for different times of the cardiac cycle considering the four different distributions of blood pressure and pulse wave of four limbs, then obtain the average blood flow in a cardiac cycle, and finally calculate the HDIs.Results: The results of the blood flow calculations reveal that the average blood flow in the upper extremity arteries is 10.78 ml/s (clinically: 2.5–12.67 ml/s), and the blood flow in the lower extremity arteries is higher than that in the upper extremity. To verify model accuracy, the consistency between the clinical and calculated values is verified with no statistically significant differences (p < 0.05). Model IV or higher-order fitting is the closest. To verify the model generalizability, considering the risk factors of cardiovascular diseases, the HDIs are recalculated using model IV, and thus, consistency is verified (p < 0.05 and Bland-Altman plot).Conclusion: We conclude our proposed algorithmic model based on NonPWT can facilitate the non-invasive hemodynamic diagnosis with simpler operational procedures and reduced medical costs.

The genetic regulatory basis of qualitative and quantitative phenotypes of watermelon is being investigated in different types of molecular and genetic breeding studies around the world. In this study, biparental F2 mapping populations were developed over two experimental years, and the collected datasets of fruit and seed traits exhibited highly significant correlations. Whole-genome resequencing of comparative parental lines was performed and detected single nucleotide polymorphism (SNP) loci were converted into cleaved amplified polymorphic sequence (CAPS) markers. The screened polymorphic markers were genotyped in segregating populations and two genetic linkage maps were constructed, which covered a total of 2834.28 and 2721.45 centimorgan (cM) genetic lengths, respectively. A total of 22 quantitative trait loci (QTLs) for seven phenotypic traits were mapped; among them, five stable and major-effect QTLs (PC-8-1, SL-9-1, SWi-9-1, SSi-9-1, and SW-6-1) and four minor-effect QTLs (PC-2-1 and PC-2-2; PT-2-1 and PT-2-2; SL-6-1 and SSi-6-2; and SWi-6-1 and SWi-6-2) were observed with 3.77–38.98% PVE. The adjacent QTL markers showed a good fit marker-trait association, and a significant allele-specific contribution was also noticed for genetic inheritance of traits. Further, a total of four candidate genes (Cla97C09G179150, Cla97C09G179350, Cla97C09G180040, and Cla97C09G180100) were spotted in the stable colocalized QTLs of seed size linked traits (SL-9-1 and SWi-9-1) that showed non-synonymous type mutations. The gene expression trends indicated that the seed morphology had been formed in the early developmental stage and showed the genetic regulation of seed shape formation. Hence, we think that our identified QTLs and genes would provide powerful genetic insights for marker-assisted breeding aimed at improving the quality traits of watermelon.

Watermelon fruits exhibit a remarkable diversity of important horticultural phenotypes. In this study, we initiated a primary quantitative trait loci (QTL) mapping to identify the candidate regions controlling the ovary, fruit, and seed phenotypes. Whole genome sequencing (WGS) was carried out for two differentiated watermelon lines, and 350 Mb (96%) and 354 Mb (97%) of re-sequenced reads covered the reference de novo genome assembly, individually. A total of 45.53% non-synonymous single nucleotide polymorphism (nsSNPs) and 54.47% synonymous SNPs (sSNPs) were spotted, which produced 210 sets of novel SNP-based cleaved amplified polymorphism sequence (CAPS) markers by depicting 46.25% co-dominant polymorphism among parent lines and offspring. A biparental F2:3 mapping population comprised of 100 families was used for trait phenotyping and CAPS genotyping, respectively. The constructed genetic map spanned a total of 2,398.40 centimorgans (cM) in length and averaged 11.42 cM, with 95.99% genome collinearity. A total of 33 QTLs were identified at different genetic positions across the eight chromosomes of watermelon (Chr-01, Chr-02, Chr-04, Chr-05, Chr-06, Chr-07, Chr-10, and Chr-11); among them, eight QTLs of the ovary, sixteen QTLs of the fruit, and nine QTLs of the seed related phenotypes were classified with 5.32–25.99% phenotypic variance explained (PVE). However, twenty-four QTLs were identified as major-effect and nine QTLs were mapped as minor-effect QTLs across the flanking regions of CAPS markers. Some QTLs were exhibited as tightly localized across the nearby genetic regions and explained the pleiotropic effects of multigenic nature. The flanking QTL markers also depicted significant allele specific contributions and accountable genes were predicted for respective traits. Gene Ontology (GO) functional enrichment was categorized in molecular function (MF), cellular components (CC), and biological process (BP); however, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were classified into three main classes of metabolism, genetic information processing, and brite hierarchies. The principal component analysis (PCA) of multivariate phenotypes widely demonstrated the major variability, consistent with the identified QTL regions. In short, we assumed that our identified QTL regions provide valuable genetic insights regarding the watermelon phenotypes and fine genetic mapping could be used to confirm them.

Fusarium wilt is one of the most destructive and less controllable diseases in melon, which is usually caused by fusarium oxysporum. In this study, transcriptome sequencing and Yeast Two-Hybrid (Y2H) methods were used for quantification of differentially expressed genes (DEGs) involved in fusarium oxysporum (f. sp. melonis race 1) stress-induced mechanisms in contrasted melon varieties (M4-45 “susceptible” and MR-1 “resistant”). The interaction factors of Fom-2 resistance genes were also explored in response to the plant-pathogen infection mechanism. Transcriptomic analysis exhibited total 1,904 new genes; however, candidate DEGs analysis revealed a total of 144 specific genes (50 upregulated and 94 downregulated) for M4-45 variety and 104 specific genes (71 upregulated and 33 downregulated) for MR-1 variety, respectively. The analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway depicted some candidate DEGs, including Phenylalanine metabolism, phenylpropane biosynthesis, plants-pathogen interaction, and signal transduction of plant hormones, which were mainly involved in disease resistance metabolic pathways. The weighted gene co-expression network analysis (WGCNA) analysis revealed a strong correlation module and exhibited the disease resistance-related genes encoding course proteins, transcription factors, protein kinase, benzene propane biosynthesis path, plants-pathogen interaction pathway, and glutathione S-transferase. Meanwhile, the resistance-related specific genes expression was relatively abundant in MR-1 compared to the M4-45, and cell wall-associated receptor kinases (MELO3C008452 and MELO3C008453), heat shock protein (Cucumis_melo_newGene_172), defensin-like protein (Cucumis_melo_newGene_5490), and disease resistance response protein (MELO3C016325), activator response protein (MELO3C021623), leucine-rich repeat receptor protein kinase (MELO3C024412), lactyl glutathione ligase (Cucumis_melo_newGene_36), and unknown protein (MELO3C007588) were persisted by exhibiting the upregulated expressions. At the transcription level, the interaction factors between the candidate genes in response to the fusarium oxysporum induced stress, and Y2H screening signified the main contribution of MYB transcription factors (MELO3C009678 and MELO3C014597), BZIP (MELO3C011839 and MELO3C019349), unknown proteins, and key enzymes in the ubiquitination process (4XM334FK014). The candidate genes were further verified in exogenously treated melon plants with f. oxysporum (Fom-2, Race 1), Abscisic acid (ABA), Methyl Jasmonite (MeJA), and Salicylic acid (SA), using the fluorescence quantitative polymerase chain reaction (qRT-PCR) analysis. The overall expression results indicated that the SA signal pathway is involved in effective regulation of the Fom-2 gene activity.

Fruit pedicel (FP) is an important determinant of premium fruit quality that directly affects commercial market value. However, in-depth molecular and genetic basis of pedicel-related traits has not been identified in watermelon. Herein, a quantitative trait locus (QTL) mapping strategy was used to identify the potential genetic regions controlling FP traits based on newly derived whole-genome single nucleotide polymorphism based cleaved amplified polymorphism sequence (SNP-CAPS) markers. Next-generation sequencing based whole-genome re-sequencing of two watermelon parent lines revealed 98.30 and 98.40% of average coverage, 4,989,869 SNP variants, and 182,949 CAPS loci pairs across the reference genome, respectively. A total of 221 sets of codominant markers exhibited 46.42% polymorphism rate and were effectively genotyped within 100-F2:3 derived mapping population. The developed linkage map covered a total of 2,630.49 cM genetic length with averaged 11.90 cM, and depicted a valid marker-trait association. In total, 6 QTLs (qFPL4.1, qFPW4.1, qFPD2.1, qFPD2.2, qFPD8.1, qFPD10.1) were mapped with five major effects and one minor effect between the whole genome adjacent markers positioned over distinct chromosomes (02, 04, 08, 10), based on the ICIM-ADD mapping approach. These significant QTLs were similarly mapped in delimited flanking regions of 675.10, 751.38, 859.24, 948.39, and 947.51 kb, which collectively explained 8.64–13.60% PVE, respectively. A highly significant and positive correlation was found among the observed variables. To our knowledge, we first time reported the mapped QTLs/genes affecting FP traits of watermelon, and our illustrated outcomes will deliver the potential insights for fine genetic mapping as well as functional gene analysis through MAS-based breeding approaches.

Through very long baseline interferometry observations of one of the closest low-luminosity active galactic nuclei, M81*, at multiple frequencies of 8.8, 22, and 44 GHz, a bright discrete knot with an unusual low apparent speed ∼0.1 c was detected. Combined with the contemporaneous monitoring of X-ray data at 2–10 keV, our data indicate that a moderate X-ray flare happened when the knot was launched from the core region. Three possible origins of the knot are proposed to explain our observational results. They are an episodic jet ejection, a low-speed shock wave, and a possible secondary black hole in a binary system. Future intensive multiwavelength monitoring can help to understand the discrete knot as well as the central black hole better.

The East Asian VLBI Network (EAVN) is an international VLBI facility in East Asia and is operated under mutual collaboration between East Asian countries, as well as part of Southeast Asian and European countries. EAVN currently consists of 16 radio telescopes and three correlators located in China, Japan, and Korea, and is operated mainly at three frequency bands, 6.7, 22, and 43 GHz with the longest baseline length of 5078 km, resulting in the highest angular resolution of 0.28 milliarcseconds at 43 GHz. One of distinct capabilities of EAVN is multi-frequency simultaneous data reception at nine telescopes, which enable us to employ the frequency phase transfer technique to obtain better sensitivity at higher observing frequencies. EAVN started its open-use program in the second half of 2018, providing a total observing time of more than 1100 h in a year. EAVN fills geographical gap in global VLBI array, resulting in enabling us to conduct contiguous high-resolution VLBI observations. EAVN has produced various scientific accomplishments especially in observations toward active galactic nuclei, evolved stars, and star-forming regions. These activities motivate us to initiate launch of the ’Global VLBI Alliance’ to provide an opportunity of VLBI observation with the longest baselines on the earth.

Analyzing the time characteristics of the aviation medical rescue process after sudden natural disasters is an extremely important guarantee for efficient rescue. In view of the problem of the significant increase in the complexity and uncertainty of the postdisaster aviation medical rescue process under time constraints, this study sorted out and analyzed the postdisaster aviation medical rescue process. The dynamic discrete modeling of the postdisaster aviation medical rescue process was carried out in combination with the stochastic Petri net (SPN) theory, and the effectiveness of the process of postdisaster aviation medical rescue was analyzed by using the isomorphism relationship between SPN and Markov chain (MC). Finally, the Sichuan Jiuzhaigou Earthquake event was taken as a case study to carry out the performance analysis and sensitivity analysis of the postdisaster aviation medical rescue process model. The results showed that information accumulation tends to occur in the process of flight planning, flight preparation, flight information transmission, and field information feedback. On-site rescue, casualty transfer, preflight preparation, and personnel preparation take a relatively long time. In the actual rescue process, emergency decision-makers and rescue crews should focus on optimizing and improving these links. The route formulation and airspace application as the main factors affecting the operation time of the postdisaster aviation medical rescue process system should be used as the key to process optimization so as to improve the efficiency of postdisaster aviation medical rescue.

The interventional treatment of cerebral aneurysm requires hemodynamics to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in calculating cerebral aneurysm hemodynamics before and after flow-diverting (FD) stent placement. However, the complex operation (such as the construction and placement simulation of fully resolved or porous-medium FD stent) and high computational cost of CFD hinder its application. To solve these problems, we applied aneurysm hemodynamics point cloud data sets and a deep learning network with double input and sampling channels. The flexible point cloud format can represent the geometry and flow distribution of different aneurysms before and after FD stent (represented by porous medium layer) placement with high resolution. The proposed network can directly analyze the relationship between aneurysm geometry and internal hemodynamics, to further realize the flow field prediction and avoid the complex operation of CFD. Statistical analysis shows that the prediction results of hemodynamics by our deep learning method are consistent with the CFD method (error function

Watermelon (Citrullus lanatus) is an important horticultural crop worldwide, but peel cracking caused by peel hardness severely decreases its quality. Lignification is one of the important functions of class III peroxidase (PRX), and its accumulation in the plant cell wall leads to cell thickening and wood hardening. For in-depth physiological and genetical understanding, we studied the relationship between peel hardness and lignin accumulation and the role of PRXs affecting peel lignin biosynthesis using genome-wide bioinformatics analysis. The obtained results showed that lignin accumulation gradually increased to form the peel stone cell structure, and tissue lignification led to peel hardness. A total of 79 ClPRXs (class III) were identified using bioinformatics analysis, which were widely distributed on 11 chromosomes. The constructed phylogenetics indicated that ClPRXs were divided into seven groups and eleven subclasses, and gene members of each group had highly conserved intron structures. Repeated pattern analysis showed that deletion and replication events occurred during the process of ClPRX amplification. However, in the whole-protein sequence alignment analysis, high homology was not observed, although all contained four conserved functional sites. Repeated pattern analysis showed that deletion and replication events occurred during ClPRXs’ amplification process. The prediction of the promoter cis-acting element and qRT-PCR analysis in four tissues (leaf, petiole, stem, and peel) showed different expression patterns for tissue specificity, abiotic stress, and hormone response by providing a genetic basis of the ClPRX gene family involved in a variety of physiological processes in plants. To our knowledge, we for the first time report the key roles of two ClPRXs in watermelon peel lignin synthesis. In conclusion, the extensive data collected in this study can be used for additional functional analysis of ClPRXs in watermelon growth and development and hormone and abiotic stress response.

Watermelon fruit texture and quality are determined by flesh firmness. As a quality trait, flesh firmness is controlled by multigenes. Defining the key regulatory factors of watermelon flesh firmness is of great significance for watermelon genetic breeding. In this study, the hard-flesh egusi seed watermelon PI186490 was used as the male parent, the soft-flesh cultivated watermelon W1-1 was used as the female parent, and 175 F2 generations were obtained from selfing F1. Primary mapping of the major genes controlling center flesh firmness was achieved by bulked-segregant analysis (BSA)-Seq analysis and molecular marker technology. Finally, major genes were delimited in the physical interval between 6,210,787 and 7,742,559 bp on chromosome 2 and between 207,553 and 403,137 bp on chromosome 8. The content of each cell wall component and hormone was measured, and comparative transcriptome analysis was performed during fruit development in watermelon. The protopectin, cellulose, hemicellulose, indole-3-acetic acid (IAA) and abscisic acid (ABA) contents were measured, and paraffin sections were made during the three fruit developmental stages. The results revealed that protopectin, celluloses, and hemicelluloses exhibited similar trends for flesh firmness, while the IAA and ABA concentrations continued to decrease with fruit ripening. Paraffin sections showed that PI186490 cells were more numerous, were more tightly packed, had clearer cell wall edges and had thicker cell walls than W1-1 cells at every developmental stage. Comparative transcriptome analysis was conducted on RNA samples of flesh during fruit development and ripening in W1-1 and PI186490. The results from the localization interval transcriptome analysis showed that Cla016033 (DUF579 family member), which may influence the cell wall component contents to adjust the flesh firmness in watermelon fruit, was different in W1-1 and PI186490 and that Cla012507 (MADS-box transcription factor) may be involved in the regulation of fruit ripening and affect the hardness of watermelon fruit.

Citrullus colocynthis L. is one of the worldwide famous traditionally medicinal plants and widely applied in watermelon breeding for its multiple resistances. The complete nucleotide sequence of desert watermelon (Citrullus colocythis L.) chloroplast genome has been determined in this study. The genome was composed of 157,147 bp containing a pair of inverted repeats (IRs) of 26,149 bp, which was separated by a large single-copy region of 86,851 bp and a small single-copy region of 17,998 bp. A total of 123 genes were predicted including 86 protein-coding genes, eight rRNA genes and 29 tRNA genes. Phylogenetic analysis revealed that C. colocynthis were closely related to other two species in the genus Citrullus. The complete chloroplast genome of C. colocynthis would provide some significant information for Cucurbitaceae evolutionary and genomic studies.

Carotenoids are the main pigments in watermelon (Citrullus lanatus L.) fruit and contribute to its aesthetic and nutritional value. Phytoene synthase (PSY) is reported to be the first rate-limiting enzyme in carotenogenesis and controls the carotenoid flux. This study aimed to identify PSY genes responsible for carotenoid biosynthesis in the red-fleshed watermelon cultivar LSW-177. The PSY gene members ClPSY1, ClPSY2 and ClPSY3 were characterized and their catalytic activities were displayed in the heterologous complementation assay. The transcript levels of ClPSY genes at the different developmental stages of LSW-177 fruit and the promoter sequence of ClPSY1 were also analyzed. Transcription factors involved in regulating the ClPSY1 expression were scanned with previous RNA-seq data of the different stages during fruit ripening. Results showed that the PSY proteins from watermelon LSW-177 contained the conserved PSY domains and exhibited the ability to condense GGPP into phytoene in E. coli. ClPSY1 is the dominant carotenogenic gene during fruit ripening; and can be induced by light and hormones. Furthermore, Cla013914 and Cla007950 that, respectively encode the transcription factors WD40-like protein and bZIP, likely upregulate ClPSY1 during fruit ripening. In conclusion, ClPSY1 play a dominant role in carotenoid biosynthesis during watermelon fruit ripening and is regulated by complex light and hormone-responsive networks.

Cucurbita pepo is an important economic plant cultivated widely in the world. The complete chloroplast genome sequence of C. pepo is reported here. The genome is 157,343 bp in length and exhibits a typical quadripartite structure of the large (LSC, 87,970 bp) and small (SSC, 18,167 bp) single-copy regions, separated by a pair of inverted repeats (IRs, 25,603 bp). A total of 131 genes were predicted including 85 protein-coding genes, eight rRNA genes and 38 tRNA genes. Further, phylogenetic analysis showed that C. pepo were closely related to other species in the family Cucurbitaceae. The complete chloroplast genome of C. pepo would be taken as a useful molecular tool for species discrimination, taxonomy, and phylogenetic relationships in the family Cucurbitaceae.

Watermelon fruits exhibit a remarkable diversity of important horticultural phenotypes. In this study, we initiated a primary quantitative trait loci (QTL) mapping to identify the candidate regions controlling the ovary, fruit, and seed phenotypes. Whole genome sequencing (WGS) was carried out for two differentiated watermelon lines, and 350 Mb (96%) and 354 Mb (97%) of resequenced reads covered the reference de novo genome assembly, individually. A total of 45.53% non-synonymous single nucleotide polymorphism (nsSNPs) and 54.47% synonymous SNPs (sSNPs) were spotted, which produced 210 sets of novel SNP-based cleaved amplified polymorphism sequence (CAPS) markers by depicting 46.25% co-dominant polymorphism among parent lines and offspring. A biparental F2:3 mapping population comprised of 100 families was used for trait phenotyping and CAPS genotyping, respectively. The constructed genetic map spanned a total of 2,398.40 centimorgans (cM) in length and averaged 11.42 cM, with 95.99% genome collinearity. A total of 33 QTLs were identified at different genetic positions across the eight chromosomes of watermelon (Chr-01, Chr-02, Chr-04, Chr-05, Chr-06, Chr-07, Chr-10, and Chr-11); among them, eight QTLs of the ovary, sixteen QTLs of the fruit, and nine QTLs of the seed related phenotypes were classified with 5.32-25.99% phenotypic variance explained (PVE). However, twenty-four QTLs were identified as major-effect and nine QTLs were mapped as minor-effect QTLs across the flanking regions of CAPS markers. Some QTLs were exhibited as tightly localized across the nearby genetic regions and explained the pleiotropic effects of multigenic nature. The flanking QTL markers also depicted significant allele specific contributions and accountable genes were predicted for respective traits. Gene Ontology (GO) functional enrichment was categorized in molecular function (MF), cellular components (CC), and biological process (BP); however, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were classified into three main classes of metabolism, genetic information processing, and brite hierarchies. The principal component analysis (PCA) of multivariate phenotypes widely demonstrated the major variability, consistent with the identified QTL regions. In short, we assumed that our identified QTL regions provide valuable genetic insights regarding the watermelon phenotypes and fine genetic mapping could be used to confirm them. [ABSTRACT FROM AUTHOR]