Quantitative evaluation and mechanism analysis of soil chemical factors affecting rice yield in saline-sodic paddy fields.

Salinization and sodication have become an important abiotic stress affecting soil fertility and crop production in the western of the Songnen Plain in Northeast China. And rice cultivation is considered as one of the most effective biological methods to reclaim saline-sodic soils and ensure food security. However, it is difficult to select the optimal measures to regulate rice growth for increasing yield, because the independent and comprehensive influences of the soil limitation factors on rice yield are not quantitatively evaluated. In this study, the hierarchical partitioning (HP) and the structural equation model (SEM) were used to quantitatively evaluate the influences of salinization parameters, salt ion concentrations and soil nutrients to identify the dominant limitation factors and obstacle mechanism for rice yield. The results showed that soil pH was the key index in salinization parameters, [CO32- + HCO3-] was the key index in salt ion concentrations and available nitrogen (AN) was the key index in soil nutrients to impact rice yield, which independent influences reached 53.7 %, 45.4 % (negative) and 53.2 % (positive), respectively. Soil pH was determined by [CO32- + HCO3-], and the negative effect of alkali stress on rice yield mainly caused by [CO32- + HCO3-] was greater than that of salt stress mainly caused by [Na+] in saline-sodic paddy fields. Among the soil chemical factors, soil pH and AN were the most important explanatory variables of rice yield in saline-sodic paddy fields, which standardized total effects were - 0.32 and 0.40, respectively. Furthermore, the AN showed a more significant negative correlation with soil pH and a higher yield-increasing potential in severe saline-sodic soils (9 ≤ pH < 10) than that in moderate saline-sodic soils (8 ≤ pH < 9). Therefore, decreasing [CO32- + HCO3-] and increasing the content of AN are key to improve rice yield in saline-sodic paddy fields.

Identification and validation of pyroptosis-related genes as potential biomarkers for hypertrophic cardiomyopathy: A comprehensive bioinformatics analysis.

Pyroptosis plays a key role in the death of cells including cardiomyocytes, and it is associated with a variety of cardiovascular diseases. However, the role of pyroptosis-related genes (PRGs) in hypertrophic cardiomyopathy (HCM) is not well characterized. This study aimed to identify key biomarkers and explore the molecular mechanisms underlying the functions of the PRGs in HCM. The differentially expressed genes were identified by GEO2R, and the differentially expressed pyroptosis-related genes (DEPRGs) of HCM were identified by combining with PRGs. Enrichment analysis was performed using the "clusterProfiler" package of the R software. Protein-protein interactions (PPI) network analysis was performed using the STRING database, and hub genes were screened using cytoHubba. TF-miRNA coregulatory networks and protein-chemical interactions were analyzed using NetworkAnalyst. RT-PCR/WB was used for expression validation of HCM diagnostic markers. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western Blot (WB) were used to measure and compare the expression of the identified genes in the cardiac hypertrophy model and the control group. A total of 20 DEPRGs were identified, which primarily showed enrichment for the positive regulation of cytokine production, regulation of response to biotic stimulus, tumor necrosis factor production, and other biological processes. These processes primarily involved pathways related to Renin-angiotensin system, Adipocytokine signaling pathway and NF-kappa B signaling pathway. Then, a PPI network was constructed, and 8 hub genes were identified. After verification analysis, the finally identified HCM-related diagnostic markers were upregulated gene protein tyrosine phosphatase non-receptor type 11 (PTPN11), downregulated genes interleukin-1 receptor-associated kinase 3 (IRAK3), and annexin A2 (ANXA2). Further GSEA analysis revealed these 3 biomarkers primarily related to cardiac muscle contraction, hypertrophic cardiomyopathy, fatty acid degradation and ECM - receptor interaction. Moreover, we also elucidated the interaction network of these biomarkers with the miRNA network and known compounds, respectively. RT-PCR/WB results indicated that PTPN11 expression was significantly increased, and IRAK3 and ANXA2 expressions were significantly decreased in HCM. This study identified PTPN11, IRAK3, and ANXA2 as pyroptosis-associated biomarkers of HCM, with the potential to reveal the development and pathogenesis of HCM and could be potential therapeutic targets.

Prediction of the COVID-19 infectivity and the sustainable impact on public health under deep learning algorithm.

The aim is to explore the development trend of COVID-19 (Corona Virus Disease 2019) and predict the infectivity of 2019-nCoV (2019 Novel Coronavirus), as well as its impact on public health. First, the existing data are analyzed through data pre-processing to extract useful feature factors. Then, the LSTM (Long-Short Term Memory) prediction model in the deep learning algorithm is used to predict the epidemic situation in Hubei Province, outside Hubei nationwide, and the whole country, respectively. Meanwhile, the impact of intervention time changes on the epidemic situation is compared. The results show that the prediction results are almost consistent with the actual values. Specifically, Hubei Province abolishes quarantine restrictions after the Spring Festival holiday, and the first COVID-19 peak is reached in late February, while the second COVID-19 peak has been reached in early March. Finally, the cumulative number of diagnoses reaches 85,000 cases, with an increase of 15,000 cases compared with the nationwide cases outside Hubei under the continuous implementation of prevention and control measures. Under the prediction of the proposed LSTM model, if the nationwide implementation of prevention and control interventions is postponed by 5 days, the epidemic will peak in early March, and the cumulative number of diagnoses will be about 200,000; and if the intervention measures are implemented five days earlier, the epidemic will peak in mid-February, with a cumulative number of diagnoses of approximately 40,000. Meanwhile, the proposed LSTM model predicts the RMSE values of the epidemic situation in Hubei Province, outside Hubei nationwide, and the whole country as 34.63, 75.42, and 50.27, respectively. Under model comparison analysis, the prediction error of the proposed LSTM model is small and has better applicability over similar algorithms. The results show that the LSTM model is effective and has high performance in infectious disease prediction, and the research results can provide scientific and effective references for subsequent related research.

Isolation and functional characterization of the SpCBF1 gene from Solanum pinnatisectum.

Low temperature causes a negative impact on plant growth and development, but plants evolve a series of mechanisms to respond to chilling stress, and one of them is CBF [C-repeat (CRT)/dehydration-responsive element (DRE) binding factor] gene family which has been well studied in different crops. In this paper, a new CBF1 gene, named as SpCBF1, was isolated from frost-tolerant Solanum pinnatisectum by PCR and analyzed for its function in cold-tolerance by over-expression technique. The ORF of SpCBF1 was 666 bp long and encoded a protein of 221 amino acids with a predicted molecular mass 24.5821 kDa and theoretically isoelectric point 5.0. SpCBF1 protein contained a highly conserved specific AP2/ERF domain. SpCBF1 was expressed in all tested tissues with the highest level in tuber and the lowest in root, and induced by chilling stress (0 °C). Under natural low temperature condition (1-10 °C), plants over-expressing SpCBF1 (OE) exhibited slighter necrotic lesion and lower necrotic injury, compared with untransformed Solanum tuberosum cv. Désirée (WT) and antisense-StCBF1 control lines. Over-expression of CBF1 increased the level of COR (cold-regulated) gene transcripts in OE lines, and the physiological indexes related to cold tolerance like the contents of SOD, soluble protein, MDA, proline and soluble sugar were higher in OE lines than in WT except RWC which was lower. All these results indicated that SpCBF1 gene plays a promoting role in potato responding to cold stress.

Genome-Wide Identification and Function Analyses of Heat Shock Transcription Factors in Potato.

Heat shock transcription factors (Hsfs) play vital roles in the regulation of tolerance to various stresses in living organisms. To dissect the mechanisms of the Hsfs in potato adaptation to abiotic stresses, genome and transcriptome analyses of Hsf gene family were investigated in Solanum tuberosum L. Twenty-seven StHsf members were identified by bioinformatics and phylogenetic analyses and were classified into A, B, and C groups according to their structural and phylogenetic features. StHsfs in the same class shared similar gene structures and conserved motifs. The chromosomal location analysis showed that 27 Hsfs were located in 10 of 12 chromosomes (except chromosome 1 and chromosome 5) and that 18 of these genes formed 9 paralogous pairs. Expression profiles of StHsfs in 12 different organs and tissues uncovered distinct spatial expression patterns of these genes and their potential roles in the process of growth and development. Promoter and quantitative real-time polymerase chain reaction (qRT-PCR) detections of StHsfs were conducted and demonstrated that these genes were all responsive to various stresses. StHsf004, StHsf007, StHsf009, StHsf014, and StHsf019 were constitutively expressed under non-stress conditions, and some specific Hsfs became the predominant Hsfs in response to different abiotic stresses, indicating their important and diverse regulatory roles in adverse conditions. A co-expression network between StHsfs and StHsf -co-expressed genes was generated based on the publicly-available potato transcriptomic databases and identified key candidate StHsfs for further functional studies.

Overexpression of potato miR482e enhanced plant sensitivity to Verticillium dahliae infection.

Verticillium wilt of potato is caused by the fungus pathogen Verticillium dahliae. Present sRNA sequencing data revealed that miR482 was in response to V. dahliae infection, but the function in potato is elusive. Here, we characterized potato miR482 family and its putative role resistance to Verticillium wilt. Members of the potato miR482 superfamily are variable in sequence, but all variants target a class of disease-resistance proteins with nucleotide binding site (NBS) and leucine-rich repeat (LRR) motifs. When potato plantlets were infected with V. dahliae, the expression level of miR482e was downregulated, and that of several NBS-LRR targets of miR482e were upregulated. Transgenic potato plantlets overexpressing miR482e showed hypersensitivity to V. dahliae infection. Using sRNA and degradome datasets, we validated that miR482e targets mRNAs of NBS-LRR disease-resistance proteins and triggers the production of trans-acting (ta)-siRNAs, most of which target mRNAs of defense-related proteins. Thus, the hypersensitivity of transgenic potato could be explained by enhanced miR482e and miR482e-derived ta-siRNA-mediated silencing on NBS-LRR-disease-resistance proteins. It is speculated that a miR482-mediated silencing cascade mechanism is involved in regulating potato resistance against V. dahliae infection and could be a counter defense action of plant in response to pathogen infection.

Downregulation of transketolase activity is related to inhibition of hippocampal progenitor cell proliferation induced by thiamine deficiency.

In animal experiments, hippocampal neurogenesis and the activity of thiamine-dependent transketolase decrease markedly under conditions of thiamine deficiency. To further investigate the effect of thiamine deficiency on the proliferation of hippocampal progenitor cells (HPCs) and the potential mechanisms involved in this effect, we cultured HPCs in vitro in the absence of thiamine and found that proliferation and transketolase activity were both significantly repressed. Furthermore, specific inhibition of transketolase activity by oxythiamine strongly inhibited HPC proliferation in a dose-dependent manner. However, thiamine deficiency itself inhibited the proliferation to a greater degree than did oxythiamine. Taken together, our results suggest that modulation of transketolase activity might be one of the mechanisms by which thiamine regulates the proliferation of hippocampal progenitor cells.

Overexpression of the tonoplast aquaporin AtTIP5;1 conferred tolerance to boron toxicity in Arabidopsis.

Boron (B) toxicity to plants is responsible for low crop productivity in many regions of the world. Here we report a novel and effective means to alleviate the B toxicity to plants under high B circumstance. Functional characterization of AtTIP5;1, an aquaporin gene, revealed that overexpression of AtTIP5;1 (OxAtTIP5;1) in Arabidopsis significantly increased its tolerance to high B toxicity. Compared to wild-type plants, OxAtTIP5;1 plants exhibited longer hypocotyls, accelerated development, increased silique production under high B treatments. GUS staining and quantitative RT-PCR (qRT-PCR) results demonstrated that the expression of AtTIP5;1 was induced by high B concentration treatment. Subcellular localization analysis revealed that the AtTIP5;1-GFP fusion protein was localized on the tonoplast membrane, which was consistent with the prediction based on bioinformatics. Taken together, our results suggest that AtTIP5;1 is involved in B transport pathway possibly via vacuolar compartmentation for B, and that overexpression of AtTIP5;1 in plants may provide an effective way to overcome the problem resulting from high B concentration toxicity.