Perioperative impact of liver cirrhosis on robotic liver resection for hepatocellular carcinoma: a retrospective cohort study.

BACKGROUND: The safety and efficacy of robotic liver resection (RLR) for patients with hepatocellular carcinoma (HCC) have been reported worldwide. However, the exact role of RLR in HCC patients with liver cirrhosis is not sufficiently determined. METHODS: We conducted a retrospective study on consecutive patients with cirrhosis or non-cirrhosis who received RLR for HCC from 2018 to 2023. Data on patients' demographics and perioperative outcomes were collected and analyzed. Propensity score matching (PSM) analysis was performed. Multivariate logistic regression analysis was performed to determine the risk factors of prolonged postoperative length of stay (LOS) and morbidity. RESULTS: Of the 571 patients included, 364 (64%) had cirrhosis. Among the cirrhotic patients, 48 (13%) were classified as Child-Pugh B. After PSM, the cirrhosis and non-cirrhosis group (n = 183) had similar operative time, estimated blood loss, postoperative blood transfusion, LOS, overall morbidity (p > 0.05). In addition, the intraoperative and postoperative outcomes were similar between the two groups in the subgroup analyses of patients with tumor size ≥ 5 cm, major hepatectomy, and high/expert IWATE difficulty grade. However, patients with Child-Pugh B cirrhosis had longer LOS and more overall morbidity than that of Child-Pugh A. Child-Pugh B cirrhosis, ASA score > 2, longer operative time, and multiple tumors were risk factors of prolonged LOS or morbidity in patients with cirrhosis. CONCLUSION: The presence of Child-Pugh A cirrhosis didn't significantly influence the difficulty and perioperative outcomes of RLR for selected patients with HCC. However, even in high-volume center, Child-Pugh B cirrhosis was a risk factor for poor postoperative outcomes.

Systematic identification and characterization of microRNAs with target genes involved in high night temperature stress at the filling stage of rice.

High night temperature stress is one of the main environmental factors affecting rice yield and quality. More and more evidence shows that microRNA (miRNA) plays an important role in various abiotic stresses. However, the molecular network of miRNA regulation on rice tolerance to high night temperatures remains unclear. Here, small RNA, transcriptome and degradome sequencing were integrated to identify differentially expressed miRNAs, genes, and key miRNA-target gene pairs in rice heat-sensitive and heat-tolerant lines at the filling stage suffering from high night temperature stress. It was discovered that there were notable differences in the relative expression of 102 miRNAs between the two rice lines under stress. Meanwhile, 5263 and 5405 mRNAs were differentially expressed in the heat-sensitive line and heat-tolerant line, and functional enrichment analysis revealed that these genes were involved in heat-related processes and pathways. The miRNAs-mRNAs target relationship was further verified by degradome sequencing. Eventually, 49 miRNAs-222 mRNAs target pairs with reverse expression patterns showed significant relative expression changes between the heat-tolerant and the heat-sensitive line, being suggested to be responsible for the heat tolerance difference of these two rice lines. Functional analysis of these 222 mRNA transcripts showed that high night temperature-responsive miRNAs targeted these mRNAs involved in many heat-related biological processes, such as transcription regulation, chloroplast regulation, mitochondrion regulation, protein folding, hormone regulation and redox process. This study identified possible miRNA-mRNA regulation relationships in response to high night temperature stress in rice and potentially contributed to heat resistance breeding of rice in the future.

Enhanced NK cell activation via eEF2K-mediated potentiation of the cGAS-STING pathway in hepatocellular carcinoma.

BACKGROUND: Liver cancer, particularly hepatocellular carcinoma (HCC), is characterized by a high mortality rate, attributed primarily to the establishment of an immunosuppressive microenvironment. Within this context, we aimed to elucidate the pivotal role of eukaryotic elongation factor 2 kinase (eEF2K) in orchestrating the infiltration and activation of natural killer (NK) cells within the HCC tumor microenvironment. By shedding light on the immunomodulatory mechanisms at play, our findings should clarify HCC pathogenesis and help identify potential therapeutic intervention venues. METHODS: We performed a comprehensive bioinformatics analysis to determine the functions of eEF2K in the context of HCC. We initially used paired tumor and adjacent normal tissue samples from patients with HCC to measure eEF2K expression and its correlation with prognosis. Subsequently, we enrolled a cohort of patients with HCC undergoing immunotherapy to examine the ability of eEF2K to predict treatment efficacy. To delve deeper into the mechanistic aspects, we established an eEF2K-knockout cell line using CRISPR/Cas9 gene editing. This step was crucial for verifying activation of the cGAS-STING pathway and the subsequent secretion of cytokines. To further elucidate the role of eEF2K in NK cell function, we applied siRNA-based techniques to effectively suppress eEF2K expression in vitro. For in vivo validation, we developed a tumor-bearing mouse model that enabled us to compare the infiltration and activation of NK cells within the tumor microenvironment following various treatment strategies. RESULTS: We detected elevated eEF2K expression within HCC tissues, and this was correlated with an unfavorable prognosis (30.84 vs. 20.99 months, P = 0.033). In addition, co-culturing eEF2K-knockout HepG2 cells with dendritic cells led to activation of the cGAS-STING pathway and a subsequent increase in the secretion of IL-2 and CXCL9. Moreover, inhibiting eEF2K resulted in notable NK cell proliferation along with apoptosis reduction. Remarkably, after combining NH125 and PD-1 treatments, we found a significant increase in NK cell infiltration within HCC tumors in our murine model. Our flow cytometry analysis revealed reduced NKG2A expression and elevated NKG2D expression and secretion of granzyme B, TNF-α, and IFN-γ in NK cells. Immunohistochemical examination confirmed no evidence of damage to vital organs in the mice treated with the combination therapy. Additionally, we noted higher levels of glutathione peroxidase and lipid peroxidation in the peripheral blood serum of the treated mice. CONCLUSION: Targeted eEF2K blockade may result in cGAS-STING pathway activation, leading to enhanced infiltration and activity of NK cells within HCC tumors. The synergistic effect achieved by combining an eEF2K inhibitor with PD-1 antibody therapy represents a novel and promising approach for the treatment of HCC.

Three-dimensional chromatin landscapes in hepatocellular carcinoma associated with hepatitis B virus.

BACKGROUND: Three-dimensional (3D) chromatin architecture frequently altered in cancer. However, its changes during the pathogenesis of hepatocellular carcinoma (HCC) remained elusive. METHODS: Hi-C and RNA-seq were applied to study the 3D chromatin landscapes and gene expression of HCC and ANHT. Hi-C Pro was used to generate genome-wide raw interaction matrices, which were normalized via iterative correction (ICE). Moreover, the chromosomes were divided into different compartments according to the first principal component (E1). Furthermore, topologically associated domains (TADs) were visualized via WashU Epigenome Browser. Furthermore, differential expression analysis of ANHT and HCC was performed using the DESeq2 R package. Additionally, dysregulated genes associated with 3D genome architecture altered were confirmed using TCGA, qRT-PCR, immunohistochemistry (IHC), etc. RESULTS: First, the intrachromosomal interactions of chr1, chr2, chr5, and chr11 were significantly different, and the interchromosomal interactions of chr4-chr10, chr13-chr21, chr15-chr22, and chr16-chr19 are remarkably different between ANHT and HCC, which resulted in the up-regulation of TP53I3 and ZNF738 and the down-regulation of APOC3 and APOA5 in HCC. Second, 49 compartment regions on 18 chromosomes have significantly switched (A-B or B-A) during HCC tumorigenesis, contributing to up-regulation of RAP2A. Finally, a tumor-specific TAD boundary located on chr5: 6271000-6478000 and enhancer hijacking were identified in HCC tissues, potentially associated with the elevated expression of MED10, whose expression were associated with poor prognosis of HCC patients. CONCLUSION: This study demonstrates the crucial role of chromosomal structure variation in HCC oncogenesis and potential novel biomarkers of HCC, laying a foundation for cancer precision medicine development.

Yellow-Green Leaf 19 Encoding a Specific and Conservative Protein for Photosynthetic Organisms Affects Tetrapyrrole Biosynthesis, Photosynthesis, and Reactive Oxygen Species Metabolism in Rice.

Chlorophyll is the main photosynthetic pigment and is crucial for plant photosynthesis. Leaf color mutants are widely used to identify genes involved in the synthesis or metabolism of chlorophyll. In this study, a spontaneous mutant, yellow-green leaf 19 (ygl19), was isolated from rice (Oryza sativa). This ygl19 mutant showed yellow-green leaves and decreased chlorophyll level and net photosynthetic rate. Brown necrotic spots appeared on the surface of ygl19 leaves at the tillering stage. And the agronomic traits of the ygl19 mutant, including the plant height, tiller number per plant, and total number of grains per plant, were significantly reduced. Map-based cloning revealed that the candidate YGL19 gene was LOC_Os03g21370. Complementation of the ygl19 mutant with the wild-type CDS of LOC_Os03g21370 led to the restoration of the mutant to the normal phenotype. Evolutionary analysis revealed that YGL19 protein and its homologues were unique for photoautotrophs, containing a conserved Ycf54 functional domain. A conserved amino acid substitution from proline to serine on the Ycf54 domain led to the ygl19 mutation. Sequence analysis of the YGL19 gene in 4726 rice accessions found that the YGL19 gene was conserved in natural rice variants with no resulting amino acid variation. The YGL19 gene was mainly expressed in green tissues, especially in leaf organs. And the YGL19 protein was localized in the chloroplast for function. Gene expression analysis via qRT-PCR showed that the expression levels of tetrapyrrole synthesis-related genes and photosynthesis-related genes were regulated in the ygl19 mutant. Reactive oxygen species (ROS) such as superoxide anions and hydrogen peroxide accumulated in spotted leaves of the ygl19 mutant at the tillering stage, accompanied by the regulation of ROS scavenging enzyme-encoding genes and ROS-responsive defense signaling genes. This study demonstrates that a novel yellow-green leaf gene YGL19 affects tetrapyrrole biosynthesis, photosynthesis, and ROS metabolism in rice.

Physiological, Cytological, and Transcriptomic Analysis of Magnesium Protoporphyrin IX Methyltransferase Mutant Reveal Complex Genetic Regulatory Network Linking Chlorophyll Synthesis and Chloroplast Development in Rice.

Functional defects in key genes for chlorophyll synthesis usually cause abnormal chloroplast development, but the genetic regulatory network for these key genes in regulating chloroplast development is still unclear. Magnesium protoporphyrin IX methyltransferase (ChlM) is a key rate-limiting enzyme in the process of chlorophyll synthesis. Physiological analysis showed that the chlorophyll and carotenoid contents were significantly decreased in the chlm mutant. Transmission electron microscopy demonstrated that the chloroplasts of the chlm mutant were not well developed, with poor, loose, and indistinct thylakoid membranes. Hormone content analysis found that jasmonic acid, salicylic acid, and auxin accumulated in the mutant. A comparative transcriptome profiling identified 1534 differentially expressed genes (DEGs) between chlm and the wild type, including 876 up-regulated genes and 658 down-regulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that these DEGs were highly involved in chlorophyll metabolism, chloroplast development, and photosynthesis. Protein-protein interaction network analysis found that protein translation played an essential role in the ChlM gene-regulated process. Specifically, 62 and 6 DEGs were annotated to regulate chlorophyll and carotenoid metabolism, respectively; 278 DEGs were predicted to be involved in regulating chloroplast development; 59 DEGs were found to regulate hormone regulatory pathways; 192 DEGs were annotated to regulate signal pathways; and 49 DEGs were putatively identified as transcription factors. Dozens of these genes have been well studied and reported to play essential roles in chlorophyll accumulation or chloroplast development, providing direct evidence for the reliability of the role of the identified DEGs. These findings suggest that chlorophyll synthesis and chloroplast development are actively regulated by the ChlM gene. And it is suggested that hormones, signal pathways, and transcription regulation were all involved in these regulation processes. The accuracy of transcriptome data was validated by quantitative real-time PCR (qRT-PCR) analysis. This study reveals a complex genetic regulatory network of the ChlM gene regulating chlorophyll synthesis and chloroplast development. The ChlM gene's role in retrograde signaling was discussed. Jasmonic acid, salicylic acid, or their derivatives in a certain unknown state were proposed as retrograde signaling molecules in one of the signaling pathways from the chloroplast to nucleus.

Hepatobiliary surgery based on intelligent image segmentation technology.

Liver disease is an important disease that seriously threatens human health. It accounts for the highest proportion in various malignant tumors, and its incidence rate and mortality are on the rise, seriously affecting human health. Modern imaging has developed rapidly, but the application of image segmentation in liver tumor surgery is still rare. The application of image processing technology represented by artificial intelligence (AI) in surgery can greatly improve the efficiency of surgery, reduce surgical complications, and reduce the cost of surgery. Hepatocellular carcinoma is the most common malignant tumor in the world, and its mortality is second only to lung cancer. The resection rate of liver cancer surgery is high, and it is a multidisciplinary surgery, so it is necessary to explore the possibility of effective switching between different disciplines. Resection of hepatobiliary and pancreatic tumors is one of the most challenging and lethal surgical procedures. The operation requires a high level of doctors' experience and understanding of anatomical structures. The surgical segmentation is slow and there may be obvious complications. Therefore, the surgical system needs to make full use of the relevant functions of AI technology and computer vision analysis software, and combine the processing strategy based on image processing algorithm and computer vision analysis model. Intelligent optimization algorithm, also known as modern heuristic algorithm, is an algorithm with global optimization performance, strong universality, and suitable for parallel processing. This algorithm generally has a strict theoretical basis, rather than relying solely on expert experience. In theory, the optimal solution or approximate optimal solution can be found in a certain time. This work studies the hepatobiliary surgery through intelligent image segmentation technology, and analyzes them through intelligent optimization algorithm. The research results showed that when other conditions were the same, there were three patients who had adverse reactions in hepatobiliary surgery through intelligent image segmentation technology, accounting for 10%. The number of patients with adverse reactions in hepatobiliary surgery by conventional methods was nine, accounting for 30%, which was significantly higher than the former, indicating a positive relationship between intelligent image segmentation technology and hepatobiliary surgery.

Short-term outcomes of robotic versus open hepatectomy among overweight patients with hepatocellular carcinoma: a propensity score-matched study.

BACKGROUND: Robotic hepatectomy (RH) has gradually been accepted as it has overcome some of the limitations of open hepatectomy (OH). This study was to compare short-term outcomes in RH and OH for overweight (preoperative body mass index ≥ 25 kg/m²) patients with hepatocellular carcinoma (HCC). METHODS: Perioperative and postoperative data from these patients who underwent RH or OH between January 2010 and December 2020 were retrospectively analyzed. Propensity score matching (PSM) analysis was performed to determine the impact of RH versus OH on the prognosis of overweight HCC patients. RESULTS: All 304 overweight HCC patients were included, 172 who were underwent RH, and 132 who were underwent OH. After the 1:1 PSM, there were 104 patients in both RH and OH groups. After PSM, the RH group of patients had a shorter operative time, less estimated blood loss (EBL), a longer total clamping time, a shorter postoperative length of stay (LOS), less chance of surgical site infection and less rates of blood transfusion (all P < 0.05) compared to the OH patients. The differences between operative time, EBL and LOS were more significant in obese patients. RH was found to be an independent protective factor of EBL ≥ 400ml relative to OH in overweight patients for the first time. CONCLUSIONS: RH was safe and feasible in overweight HCC patients. Compared with OH, RH has advantages in terms of operative time, EBL, postoperative LOS, and surgical site infection. Carefully selected overweight patients should be considered for RH.

Estimating soil salinity using Gaofen-2 imagery: A novel application of combined spectral and textural features.

Gaofen-2 (GF-2) imagery data has been playing an important role in environmental monitoring. However, the scarcity of spectral bands makes GF-2 difficult to use in soil salinity estimation. In this paper, we combined spectral and textual features for soil salinity estimation from GF-2 imagery. The spectral features comprised five classes of predictors: spectral value, vegetation index, salinity index, brightness index, and intensity index. Four gray-level co-occurrence matrix (GLCM) indices were used as the textural features. The least absolute shrinkage and selection operator (LASSO) was applied to select features. Four methods, namely, Random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and partial least squares regression (PLSR) were applied and compared. To this end, 211 soil samples were collected in the Yellow River Delta through field investigation. The results showed that GF-2 imagery could successfully estimate soil salinity by integrating spectral and texture features, and among the four methods, the RF had the highest accuracy with the determination coefficient for cross-validation (R2CV), a root mean square error for cross-validation (RMSECV), and the ratio of the standard deviation to the root mean square error of prediction (RPD) of 0.82, 2.36 g kg-1, and 2.28, respectively. Especially, the impact of different scale features on the soil salinity estimation accuracy was evaluated. The optimal window size for features was 9 × 9 pixels, and increasing or decreasing the window size will decrease the estimation accuracy. The study provides a novel application to soil salinity estimation from remote sensing imagery.

De novo assembly of two chromosome-level rice genomes and bin-based QTL mapping reveal genetic diversity of grain weight trait in rice.

Following the "green revolution," indica and japonica hybrid breeding has been recognized as a new breakthrough in further improving rice yields. However, heterosis-related grain weight QTLs and the basis of yield advantage among subspecies has not been well elucidated. We herein de novo assembled the chromosome level genomes of an indica/xian rice (Luohui 9) and a japonica/geng rice (RPY geng) and found that gene number differences and structural variations between these two genomes contribute to the differences in agronomic traits and also provide two different favorable allele pools to produce better derived recombinant inbred lines (RILs). In addition, we generated a high-generation (> F15) population of 272 RILs from the cross between Luohui 9 and RPY geng and two testcross hybrid populations derived from the crosses of RILs and two cytoplasmic male sterile lines (YTA, indica and Z7A, japonica). Based on three derived populations, we totally identified eight 1,000-grain weight (KGW) QTLs and eight KGW heterosis loci. Of QTLs, qKGW-6.1 and qKGW-8.1 were accepted as novel KGW QTLs that have not been reported previously. Interestingly, allele genotyping results revealed that heading date related gene (Ghd8) in qKGW-8.1 and qLH-KGW-8.1, can affect grain weight in RILs and rice core accessions and may also play an important role in grain weight heterosis. Our results provided two high-quality genomes and novel gene editing targets for grain weight for future rice yield improvement project.

Big Data Analysis and Application of Liver Cancer Gene Sequence Based on Second-Generation Sequencing Technology.

In big data analysis with the rapid improvement of computer storage capacity and the rapid development of complex algorithms, the exponential growth of massive data has also made science and technology progress with each passing day. Based on omics data such as mRNA data, microRNA data, or DNA methylation data, this study uses traditional clustering methods such as kmeans, K-nearest neighbors, hierarchical clustering, affinity propagation, and nonnegative matrix decomposition to classify samples into categories, obtained: (1) The assumption that the attributes are independent of each other reduces the classification effect of the algorithm to a certain extent. According to the idea of multilevel grid, there is a one-to-one mapping from high-dimensional space to one-dimensional. The complexity is greatly simplified by encoding the one-dimensional grid of the hierarchical grid. The logic of the algorithm is relatively simple, and it also has a very stable classification efficiency. (2) Convert the two-dimensional representation of the data into the one-dimensional representation of the binary, realize the dimensionality reduction processing of the data, and improve the organization and storage efficiency of the data. The grid coding expresses the spatial position of the data, maintains the original organization method of the data, and does not make the abstract expression of the data object. (3) The data processing of nondiscrete and missing values provides a new opportunity for the identification of protein targets of small molecule therapy and obtains a better classification effect. (4) The comparison of the three models shows that Naive Bayes is the optimal model. Each iteration is composed of alternately expected steps and maximal steps and then identified and quantified by MS.

Short- and long-term outcomes after robotic and open liver resection for elderly patients with hepatocellular carcinoma: a propensity score-matched study.

BACKGROUND: Robotic liver resection (RLR) has increasingly been accepted as it has overcome some of the limitations of open liver resection (OLR), while the outcomes following RLR in elderly patients with hepatocellular carcinoma (HCC) are still uncertain. This study aimed to evaluate the short and long-term outcomes of RLR vs. OLR in elderly HCC patients. METHODS: Perioperative data of elderly patients (≥ 65 years) with HCC who underwent RLR or OLR between January 2010 and December 2020 were retrospectively analyzed. A 1:2 propensity score-matched (PSM) analysis was performed to minimize the differences between RLR and OLR groups. Univariable and multivariable Cox regression analyses were used to identify independent prognosis factors for overall survival (OS) and recurrence-free survival (RFS) of these patients. RESULTS: Of the 427 elderly HCC patients included in this study, 113 underwent RLR and 314 underwent OLR. After the 1:2 PSM, there were 100 and 178 patients in the RLR and the OLR groups, respectively. The RLR group had a less estimated blood loss (EBL), a shorter postoperative length of stay (LOS), and a lower complications rate (all P < 0.05), compared with the OLR group before and after PSM. Univariable and multivariable analyses showed that advanced age and surgical approaches were not independent risk factors for long-term prognosis. The two groups of elderly patients who were performed RLR or OLR had similar OS (median OS 52.8 vs. 57.6 months) and RFS (median RFS 20.4 vs. 24.6 months) rates after PSM. CONCLUSIONS: RLR was comparable to OLR in feasibility and safety. For elderly patients with HCC, RLR resulted in similar oncologic and survival outcomes as OLR.

Landscapes and dynamic diversifications of B-cell receptor repertoires in COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the pandemic of coronavirus disease 2019 (COVID-19). Great international efforts have been put into the development of prophylactic vaccines and neutralizing antibodies. However, the knowledge about the B cell immune response induced by the SARS-CoV-2 virus is still limited. Here, we report a comprehensive characterization of the dynamics of immunoglobin heavy chain (IGH) repertoire in COVID-19 patients. By using next-generation sequencing technology, we examined the temporal changes in the landscape of the patient's immunological status and found dramatic changes in the IGH within the patient's immune system after the onset of COVID-19 symptoms. Although different patients have distinct immune responses to SARS-CoV-2 infection, by employing clonotype overlap, lineage expansion, and clonotype network analyses, we observed a higher clonotype overlap and substantial lineage expansion of B cell clones 2-3 weeks after the onset of illness, which is of great importance to B-cell immune responses. Meanwhile, for preferences of V gene usage during SARS-CoV-2 infection, IGHV3-74 and IGHV4-34, and IGHV4-39 in COVID-19 patients were more abundant than those of healthy controls. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic development as well as mechanistic research.

Genetic Diversity Relationship Between Grain Quality and Appearance in Rice.

Grain quality is an important breeding objective in rice, and the appearance of the grain also affects its commercial value in the market. The aim of this study was to decode the rice grain qualities and appearances, such as gelatinization temperature (GT), amylose content (AC), grain protein content (GPC), pericarp color (PC), length/width ratio (LWR), and grain volume (GV) at phenotypic and genetic levels, as well as the relationships among them. A genome-wide association study (GWAS) was used to identify the quantitative trait locus (QTLs) associated with the target traits using mixed linear model (MLM) and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) methods. In general, AC was negatively correlated with GPC and GV, while it was positively correlated with LWR and PC. GPC was positively correlated with LWR. Using the rice diversity panel 1 (RDP1) population, we identified 11, 6, 2, 7, 11, and 6 QTLs associated with GT, AC, GPC, PC, LWR, and GV, respectively. Five germplasm lines, superior in grain qualities and appearances for basic breeding materials or improvement, were identified. Notably, an F-box gene OsFbox394 was located in the linkage disequilibrium (LD) block of qLWR7-2, which specifically expresses in endosperm and seed tissues, suggesting that this gene may regulate the seed development in rice grain. Besides, different haplotypes of OsHyPRP45 showed significant differences in AC, indicating that this gene may be related to AC in rice grain.

UDP-N-Acetylglucosamine Pyrophosphorylase 2 (UAP2) and 1 (UAP1) Perform Synergetic Functions for Leaf Survival in Rice.

Functional inactivation of UDP-N-acetylglucosamine pyrophosphorylase 1 (UAP1) induces defense response-related lesion-mimic spots and subsequent early senescence in every newly grown leaf of the rice mutant uap1 after a short period's normal growth. However, the molecular mechanism of these leaves sustaining the short period's survival is still unknown. Phenotypic and molecular studies show that defense response-related lesion-mimic spots and early leaf senescence appear on the normally grown uap1 leaf and aggravate with the growth time. Bioinformatic analysis reveals that UAP proteins are evolutionarily conserved among eukaryotes, and there exists UAP2 protein except UAP1 protein in many higher organisms, including rice. Rice UAP2 and UAP1 proteins present high sequence identities and very similar predicted 3D structures. Transcriptional expression profile of the UAP2 gene decreases with the appearance and aggravating of leaf spots and early senescence of uap1, implying the role of the UAP2 gene in maintaining the initial normal growth of uap1 leaves. Enzymatic experiments verified that the UAP2 protein performs highly similar UAP enzymatic activity with the UAP1 protein, catalyzing the biosynthesis of UDP-GlcNAc. And these two UAP proteins are found to have the same subcellular localization in the cytoplasm, where they most presumably perform their functions. Overexpression of the UAP2 gene in uap1 plants succeeds to rescue their leaf mutant phenotype to normal, providing direct evidence for the similar function of the UAP2 gene as the UAP1 gene. The UAP2 gene is mainly expressed in the young leaf stage for functions, while the UAP1 gene is highly expressed during the whole leaf developmental stages. Based on these findings, it is suggested that UAP2 and UAP1 play key roles in rice leaf survival during its development in a synergetic manner, protecting the leaf from early senescence.

Global Analysis of UDP Glucose Pyrophosphorylase (UDPGP) Gene Family in Plants: Conserved Evolution Involved in Cell Death.

UDP glucose pyrophosphorylase (UDPGP) family genes have been reported to play essential roles in cell death or individual survival. However, a systematic analysis on UDPGP gene family has not been performed yet. In this study, a total of 454 UDPGP proteins from 76 different species were analyzed. The analyses of the phylogenetic tree and orthogroups divided UDPGPs into three clades, including UDP-N-acetylglucosamine pyrophosphorylase (UAP), UDP-glucose pyrophosphorylase (UGP, containing UGP-A and UGP-B), and UDP-sugar pyrophosphorylase (USP). The evolutionary history of the UDPGPs indicated that the members of UAP, USP, and UGP-B were relatively conserved while varied in UGP-A. Homologous sequences of UGP-B and USP were found only in plants. The expression profile of UDPGP genes in Oryza sativa was mainly motivated under jasmonic acid (JA), abscisic acid (ABA), cadmium, and cold treatments, indicating that UDPGPs may play an important role in plant development and environment endurance. The key amino acids regulating the activity of UDPGPs were analyzed, and almost all of them were located in the NB-loop, SB-loop, or conserved motifs. Analysis of the natural variants of UDPGPs in rice revealed that only a few missense mutants existed in coding sequences (CDSs), and most of the resulting variations were located in the non-motif sites, indicating the conserved structure and function of UDPGPs in the evolution. Furthermore, alternative splicing may play a key role in regulating the activity of UDPGPs. The spatial structure prediction, enzymatic analysis, and transgenic verification of UAP isoforms illustrated that the loss of N- and C-terminal sequences did not affect the overall 3D structures, but the N- and C-terminal sequences are important for UAP genes to maintain their enzymatic activity. These results revealed a conserved UDPGP gene family and provided valuable information for further deep functional investigation of the UDPGP gene family in plants.

Genome-wide identification and characterization of long non-coding RNAs involved in flag leaf senescence of rice.

KEY MESSAGE: This study showed the systematic identification of long non-coding RNAs (lncRNAs) involving in flag leaf senescence of rice, providing the possible lncRNA-mRNA regulatory relationships and lncRNA-miRNA-mRNA ceRNA networks during leaf senescence. LncRNAs have been reported to play crucial roles in diverse biological processes. However, no systematic identification of lncRNAs associated with leaf senescence in plants has been studied. In this study, a genome-wide high throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. A total of 3953 lncRNAs and 38757 mRNAs were identified, of which 343 lncRNAs and 9412 mRNAs were differentially expressed. Through weighted gene co-expression network analysis (WGCNA), 22 continuously down-expressed lncRNAs targeting 812 co-expressed mRNAs and 48 continuously up-expressed lncRNAs targeting 1209 co-expressed mRNAs were considered to be significantly associated with flag leaf senescence. Gene Ontology results suggested that the senescence-associated lncRNAs targeted mRNAs involving in many biological processes, including transcription, hormone response, oxidation-reduction process and substance metabolism. Additionally, 43 senescence-associated lncRNAs were predicted to target 111 co-expressed transcription factors. Interestingly, 8 down-expressed lncRNAs and 29 up-expressed lncRNAs were found to separately target 12 and 20 well-studied senescence-associated genes (SAGs). Furthermore, analysis on the competing endogenous RNA (CeRNA) network revealed that 6 down-expressed lncRNAs possibly regulated 51 co-expressed mRNAs through 15 miRNAs, and 14 up-expressed lncRNAs possibly regulated 117 co-expressed mRNAs through 21 miRNAs. Importantly, by expression validation, a conserved miR164-NAC regulatory pathway was found to be possibly involved in leaf senescence, where lncRNA MSTRG.62092.1 may serve as a ceRNA binding with miR164a and miR164e to regulate three transcription factors. And two key lncRNAs MSTRG.31014.21 and MSTRG.31014.36 also could regulate the abscisic-acid biosynthetic gene BGIOSGA025169 (OsNCED4) and BGIOSGA016313 (NAC family) through osa-miR5809. The possible regulation networks of lncRNAs involving in leaf senescence were discussed, and several candidate lncRNAs were recommended for prior transgenic analysis. These findings will extend the understanding on the regulatory roles of lncRNAs in leaf senescence, and lay a foundation for functional research on candidate lncRNAs.

Systematic identification and characterization of circular RNAs involved in flag leaf senescence of rice.

MAIN CONCLUSION: Circular RNAs (circRNAs) identification, expression profiles, and construction of circRNA-parental gene relationships and circRNA-miRNA-mRNA ceRNA networks indicate that circRNAs are involved in flag leaf senescence of rice. Circular RNAs (circRNAs) are a class of 3'-5' head-to-tail covalently closed non-coding RNAs which have been proved to play important roles in various biological processes. However, no systematic identification of circRNAs associated with leaf senescence in rice has been studied. In this study, a genome-wide high-throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. Here, a total of 6612 circRNAs were identified, among which, 113 circRNAs were differentially expressed (DE) during the leaf senescence process. Moreover, 4601 (69.59%) circRNAs were derived from the exons or introns of their parental genes, while 2110 (71%) of the parental genes produced only one circRNA. The sequence alignment analysis showed that hundreds of rice circRNAs were conserved among different plant species. Gene Ontology (GO) enrichment analysis revealed that parental genes of DE circRNAs were enriched in many biological processes closely related to leaf senescence. Through weighted gene co-expression network analysis (WGCNA), six continuously down-expressed circRNAs, 18 continuously up-expressed circRNAs and 15 turn-point high-expressed circRNAs were considered to be highly associated with leaf senescence. Additionally, a total of 17 senescence-associated circRNAs were predicted to have parental genes, in which, regulations of three circRNAs to their parental genes were validated by qRT-PCR. The competing endogenous RNA (ceRNA) networks were also constructed. And a total of 11 senescence-associated circRNAs were predicted to act as miRNA sponges to regulate mRNAs, in which, regulation of two circRNAs to eight mRNAs was validated by qRT-PCR. It is discussed that senescence-associated circRNAs were involved in flag leaf senescence probably through mediating their parental genes and ceRNA networks, to participate in several well-studied senescence-associated processes, mainly including the processes of transcription, translation, and posttranslational modification (especially protein glycosylation), oxidation-reduction process, involvement of senescence-associated genes, hormone signaling pathway, proteolysis, and DNA damage repair. This study not only showed the systematic identification of circRNAs involved in leaf senescence of rice, but also laid a foundation for functional research on candidate circRNAs.

Increased circulating level of interleukin-6 and CD8+ T cell exhaustion are associated with progression of COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is pandemic. It is critical to identify COVID-19 patients who are most likely to develop a severe disease. This study was designed to determine the clinical and epidemiological features of COVID-19 patients associated with the development of pneumonia and factors associated with disease progression. METHODS: Seventy consecutive patients with etiologically confirmed COVID-19 admitted to PLA General Hospital in Beijing, China from December 27, 2019 to March 12, 2020 were enrolled in this study and followed-up to March 16, 2020. Differences in clinical and laboratory findings between COVID-19 patients with pneumonia and those without were determined by the χ2 test or the Fisher exact test (categorical variables) and independent group t test or Mann-Whitney U test (continuous variables). The Cox proportional hazard model and Generalized Estimating Equations were applied to evaluate factors that predicted the progression of COVID-19. RESULTS: The mean incubation was 8.67 (95% confidence interval, 6.78-10.56) days. Mean duration from the first test severe acute respiratory syndrome coronavirus 2-positive to conversion was 11.38 (9.86-12.90) days. Compared to pneumonia-free patients, pneumonia patients were 16.5 years older and had higher frequencies of having hypertension, fever, and cough and higher circulating levels of neutrophil proportion, interleukin-6, low count (< 190/µl) of CD8+ T cells, and neutrophil/lymphocyte ratio. Thirteen patients deteriorated during hospitalization. Cox regression analysis indicated that older age and higher serum levels of interleukin-6, C-reactive protein, procalcitonin, and lactate at admission significantly predicted the progression of COVID-19. During hospitalization, circulating counts of T lymphocytes, CD4+ T cells, and CD8+ T cells were lower, whereas neutrophil proportion, neutrophil/lymphocyte ratio, and the circulating levels of interleukin-6, C-reactive protein, and procalcitonin were higher, in pneumonia patients than in pneumonia-free patients. CD8+ lymphocyte count in pneumonia patients did not recover when discharged. CONCLUSIONS: Older age and higher levels of C-reactive protein, procalcitionin, interleukin-6, and lactate might predict COVID-19 progression. T lymphocyte, especially CD8+ cell-mediated immunity is critical in recovery of COVID-19. This study may help in predicting disease progression and designing immunotherapy for COVID-19.