Genome-Wide Identification and Analysis of Grape Aldehyde Dehydrogenase (ALDH) Gene Superfamily

The completion of the grape genome sequencing project has paved the way for novel gene discovery and functional analysis. Aldehyde dehydrogenases (ALDHs) comprise a gene superfamily encoding NAD(P)(+)-dependent enzymes that catalyze the irreversible oxidation of a wide range of endogenous and exogenous aromatic and aliphatic aldehydes. Although ALDHs have been systematically investigated in several plant species including Arabidopsis and rice, our knowledge concerning the ALDH genes, their evolutionary relationship and expression patterns in grape has been limited.A total of 23 ALDH genes were identified in the grape genome and grouped into ten families according to the unified nomenclature system developed by the ALDH Gene Nomenclature Committee (AGNC). Members within the same grape ALDH families possess nearly identical exon-intron structures. Evolutionary analysis indicates that both segmental and tandem duplication events have contributed significantly to the expansion of grape ALDH genes. Phylogenetic analysis of ALDH protein sequences from seven plant species indicates that grape ALDHs are more closely related to those of Arabidopsis. In addition, synteny analysis between grape and Arabidopsis shows that homologs of a number of grape ALDHs are found in the corresponding syntenic blocks of Arabidopsis, suggesting that these genes arose before the speciation of the grape and Arabidopsis. Microarray gene expression analysis revealed large number of grape ALDH genes responsive to drought or salt stress. Furthermore, we found a number of ALDH genes showed significantly changed expressions in responses to infection with different pathogens and during grape berry development, suggesting novel roles of ALDH genes in plant-pathogen interactions and berry development.The genome-wide identification, evolutionary and expression analysis of grape ALDH genes should facilitate research in this gene family and provide new insights regarding their evolution history and functional roles in plant stress tolerance

Road traffic flow prediction based on dynamic spatiotemporal graph attention network

Abstract To improve the prediction accuracy of traffic flow under the influence of nearby time traffic flow disturbance, a dynamic spatiotemporal graph attention network traffic flow prediction model based on the attention mechanism was proposed. Considering the macroscopic periodic characteristics of traffic flow, the spatiotemporal features are extracted by constructing spatiotemporal blocks with an adjacent period, daily period, and weekly period respectively. The spatiotemporal block is mainly composed of a two-layer graph attention network and a gated recurrent unit to capture the hidden features of space and time. In space, based on considering adjacent road segments, the Pearson correlation coefficient is used to capture the hidden correlation characteristics between non-adjacent road segments according to a certain time step. In terms of time, due to the random disturbance of traffic flow at the micro level, the attention mechanism is introduced to use the adjacent time as the query matrix to weight the output characteristics of daily cycle and weekly cycle, and the three are connected in series to output the prediction results through the linear layer. Finally, the experimental results on the public data sets show that the proposed model is superior to the six baseline models

Singapore Grouper Iridovirus Disturbed Glycerophospholipids Homeostasis: Cytosolic Phospholipase A2 Was Essential for Virus Replication

Singapore grouper iridovirus (SGIV), belonging to genus Ranavirus, family Iridoviridae, causes great economic losses in the aquaculture industry. Previous studies demonstrated the lipid composition of intracellular unenveloped viruses, but the changes in host-cell glyceophospholipids components and the roles of key enzymes during SGIV infection still remain largely unknown. Here, the whole cell lipidomic profiling during SGIV infection was analyzed using UPLC-Q-TOF-MS/MS. The lipidomic data showed that glycerophospholipids (GPs), including phosphatidylcholine (PC), phosphatidylserine (PS), glycerophosphoinositols (PI) and fatty acids (FAs) were significantly elevated in SGIV-infected cells, indicating that SGIV infection disturbed GPs homeostasis, and then affected the metabolism of FAs, especially arachidonic acid (AA). The roles of key enzymes, such as cytosolic phospholipase A2 (cPLA2), 5-Lipoxygenase (5-LOX), and cyclooxygenase (COX) in SGIV infection were further investigated using the corresponding specific inhibitors. The inhibition of cPLA2 by AACOCF3 decreased SGIV replication, suggesting that cPLA2 might play important roles in the process of SGIV infection. Consistent with this result, the ectopic expression of EccPLA2α or knockdown significantly enhanced or suppressed viral replication in vitro, respectively. In addition, the inhibition of both 5-LOX and COX significantly suppressed SGIV replication, indicating that AA metabolism was essential for SGIV infection. Taken together, our results demonstrated for the first time that SGIV infection in vitro disturbed GPs homeostasis and cPLA2 exerted crucial roles in SGIV replication

OpSparse: a Highly Optimized Framework for Sparse General Matrix Multiplication on GPUs

Sparse general matrix multiplication (SpGEMM) is an important and expensive computation primitive in many real-world applications. Due to SpGEMM's inherent irregularity and the vast diversity of its input matrices, developing high-performance SpGEMM implementation on modern processors such as GPUs is challenging. The state-of-the-art SpGEMM libraries (i.e., $nsparse$ and $spECK$) adopt several algorithms to tackle the challenges of global load balance, local load balance, and allocation of the result matrix. While these libraries focus on the high-level algorithm design for SpGEMM, they neglect several low-level architecture-specific optimizations, which causes inefficient implementations in their libraries. In this paper, we classify their inefficient implementations into seven categories. Based on our observations, we propose a highly optimized SpGEMM library called $OpSparse$. The optimizations in $OpSparse$ include 1) optimizing the binning method by improving the utilization of the shared memory, 2) optimizing the hashing method by reducing the access to the hash table, 3) improving the trade-off between hash collision rate and hardware utilization in the hashing method by setting appropriate binning ranges, 4) reducing the overheads of global memory utilization by minimizing the global memory usage of the metadata, and 5) improving the execution parallelism by overlapping global memory allocation with kernel execution. Performance evaluations with 26 commonly used matrices on an Nvidia Tesla V100 GPU show that $OpSparse$ achieves up to $27.8\times$, $1.81\times$, and $2.04\times$ performance speedup over three state-of-the-art libraries: $cuSPARSE$, $nsparse$, and $spECK$, respectively.Comment: This paper has been submitted to the IEEE Access since May 7, 2022, and is currently under review by IEEE Access. 20 pages, 11 fgures, 5 table

Synthesis of 3‑Aryl-2-pyrones by Palladium-Catalyzed Cross-Coupling of Aryl Iodides with Cyclic Vinyldiazo Ester

A palladium-catalyzed cross-coupling reaction of aryl iodides with cyclic vinyldiazo ester was developed. The reaction provides various 3-aryl-2-pyrones in good yields with high functional group tolerance. The synthetic application of the resulting 3-aryl-2-pyrones as the diene component in a Diels–Alder reaction was also described

Styryl Conjugated Coumarin Caged Alcohol: Efficient Photorelease by Either One-Photon Long Wavelength or Two-Photon NIR Excitation

The synthesis and photorelease properties of a new phototrigger for alcohols are described. Compared to ester <b>4</b> caged by the reported [7-(diethylamino)coumarin-4-yl]methoxycarbonyl (DEACM) phototrigger, the caged ester <b>3</b> shows an efficient single-photon photolysis efficiency upon irradiation of long wavelength light (λ = 475 nm) and a stronger two-photon photolysis sensitivity with 800 nm laser light. Its promising properties and the efficient photorelease of adenosine make it very useful as a caging group for biological applications

Hyaluronic Acid-Conjugated Fluorescent Probe-Shielded Polydopamine Nanomedicines for Targeted Imaging and Chemotherapy of Bladder Cancer

Bladder cancer is one of the most common malignancies in the urinary system, with high risk of recurrence and progression. However, the difficulty in detecting small tumor lesions and the lack of selectivity of intravesical treatment seriously affect the prognosis of patients with bladder cancer. In the present work, a nanoparticle-based delivery system with tumor targeting, high biocompatibility, simple preparation, and the ability to synergize imaging and therapy was fabricated. Specifically, this nanosystem consisted of the core of doxorubicin (DOX)-loaded polydopamine nanoparticles (PDD NPs) and the shell of hyaluronic acid (HA)-conjugated IR780 (HA-IR780). The HA-IR780-covered PDD NPs (HR-PDD NPs) demonstrated tumor targeting and visualization both in vitro and in vivo with properties of promoted cancer cell endocytosis and lysosomal escape, efficiently delivering drugs to the target site and exerting a killing effect on tumor cells. Encouragingly, intravesical instillation of HR-PDD NPs improved drug retention in the bladder and promoted its accumulation in tumor tissue, resulting in better tumor proliferation inhibition and apoptosis in an orthotopic bladder cancer model in rats. This study provides a promising strategy for the diagnosis and therapy of bladder cancer

Genome-wide mapping of structural variations reveals a copy number variant that determines reproductive morphology in cucumber

Structural variations (SVs) represent a major source of genetic diversity. However, the functional impact and formation mechanisms of SVs in plant genomes remain largely unexplored. Here, we report a nucleotide-resolution SV map of cucumber (Cucumis sativas) that comprises 26,788 SVs based on deep resequencing of 115 diverse accessions. The largest proportion of cucumber SVs was formed through nonhomologous end-joining rearrangements, and the occurrence of SVs is closely associated with regions of high nucleotide diversity. These SVs affect the coding regions of 1676 genes, some of which are associated with cucumber domestication. Based on the map, we discovered a copy number variation (CNV) involving four genes that defines the Female (F) locus and gives rise to gynoecious cucumber plants, which bear only female flowers and set fruit at almost every node. The CNV arose from a recent 30.2-kb duplication at a meiotically unstable region, likely via microhomology-mediated break-induced replication. The SV set provides a snapshot of structural variations in plants and will serve as an important resource for exploring genes underlying key traits and for facilitating practical breeding in cucumber