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The need for improved crop water use efficiency calls for flexible modeling platforms to implement new ideas in plant root uptake and its regulation mechanisms. This paper documents the details of modifying a soil infiltration and redistribution model to include (a) dynamic root growth, (b) non-uniform root distribution and water uptake, (c) the effect of water stress on plant water uptake, and (d) soil evaporation. The paper also demonstrates strategies of using the modified model to simulate soil water dynamics and plant transpiration considering different sensitivity of plants to soil dryness and different mechanisms of root water uptake. In particular, the flexibility of simulating various degrees of compensated uptake (whereby plants tend to maintain potential transpiration under mild water stress) is emphasized. The paper also describes how to estimate unknown root distribution and rooting depth parameters by the use of a simulation-based searching method. The full documentation of the computer code will allow further applications and new development.

The CRISPR (Clustered Regularly Spaced Short Palindromic Repeats) system was first discovered in prokaryotes as a unique immune mechanism to clear foreign nucleic acids. It has been rapidly and extensively used in basic and applied research owing to its strong ability of gene editing, regulation and detection in eukaryotes. Hererin in this article, we reviewed the biology, mechanisms and relevance of CRISPR-Cas technology and its applications in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis. CRISPR-Cas nucleic acid detection tools include CRISPR-Cas9, CRISPR-Cas12, CRISPR-Cas13, CRISPR-Cas14, CRISPR nucleic acid amplification detection technology, and CRISPR colorimetric readout detection system. The above CRISPR technologies have been applied to the nucleic acid detection, including SARS-CoV-2 detection. Common nucleic acid detection based on CRISPR derivation technology include SHERLOCK, DETECTR, and STOPCovid. CRISPR-Cas biosensing technology has been widely applied to point-of-care testing (POCT) by targeting recognition of both DNA molecules and RNA Molecules.

As a strong oxidizing pollutant, NO2 can cause fire or even explosion. People living in atmosphere containing NO2 for a long time will significantly affects human health. In this work, we developed a Schottky heterojunction sensor modified by g-C3N4 quantum dots (g-C3N4QDs) and rGO deposited on TiO2 nanotubes (TNTs) arrays. This sensor showed high response and extremely fast response/recovery time as well as excellent detection of ppb level of NO2 at room temperature. TNTs were obtained using a one-step anodic oxidation process. TNTs were modified with g-C3N4QDs and rGO using quasi-CVD method and cyclic voltammetry during in situ electrodeposition, respectively. TNTs/g-C3N4QDs/rGO Schottky heterojunction sensor exhibited high sensitivity to 10 ppm of NO2 (response equal to 15982) at room temperature. Below 15 ppb, sensing response also can reach 127. Sensor response was very fast and increased to 15982 in just 2 s when exposed to 10 ppm of NO2 after which it recovers 90% within 1.16 s. This work clarified the influence of abundant oxygen vacancies (VO·) in TNTs and photogenerated electrons on TNTs/g-C3N4QDs/rGO nanostructures as well as their sensing performances. Our experimental details demonstrated that Schottky barrier was established between TNTs and rGO, which was very beneficial for ppb-level NO2 detection at room temperature.

Background Hepatocellular carcinoma (HCC) has a poor prognosis and has become the sixth most common malignancy worldwide due to its high incidence. Advanced approaches to therapy, including immunotherapeutic strategies, have played crucial roles in decreasing recurrence rates and improving clinical outcomes. The HCC microenvironment is important for both tumour carcinogenesis and immunogenicity, but a classification system based on immune signatures has not yet been comprehensively described. Methods HCC datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC) were used in this study. Gene set enrichment analysis (GSEA) and the ConsensusClusterPlus algorithm were used for clustering assessments. We scored immune cell infiltration and used linear discriminant analysis (LDA) to improve HCC classification accuracy. Pearson's correlation analyses were performed to assess relationships between immune signature indices and immunotherapies. In addition, weighted gene co-expression network analysis (WGCNA) was applied to identify candidate modules closely associated with immune signature indices. Results Based on 152 immune signatures from HCC samples, we identified four distinct immune subtypes (IS1, IS2, IS3, and IS4). Subtypes IS1 and IS4 had more favourable prognoses than subtypes IS2 and IS3. These four subtypes also had different immune system characteristics. The IS1 subtype had the highest scores for IFNγ, cytolysis, angiogenesis, and immune cell infiltration among all subtypes. We also identified 11 potential genes, namely, TSPAN15, TSPO, METTL9, CD276, TP53I11, SPINT1, TSPO, TRABD2B, WARS2, C9ORF116, and LBH, that may represent potential immunological biomarkers for HCC. Furthermore, real-time PCR revealed that SPINT1, CD276, TSPO, TSPAN15, METTL9, and WARS2 expression was increased in HCC cells. Conclusions The present gene-based immune signature classification and indexing may provide novel perspectives for both HCC immunotherapy management and prognosis prediction.

The need for improved crop water use efficiency calls for flexible modeling platforms to implement new ideas in plant root uptake and its regulation mechanisms. This paper documents the details of modifying a soil infiltration and redistribution model to include (a) dynamic root growth, (b) non-uniform root distribution and water uptake, (c) the effect of water stress on plant water uptake, and (d) soil evaporation. The paper also demonstrates strategies of using the modified model to simulate soil water dynamics and plant transpiration considering different sensitivity of plants to soil dryness and different mechanisms of root water uptake. In particular, the flexibility of simulating various degrees of compensated uptake (whereby plants tend to maintain potential transpiration under mild water stress) is emphasized. The paper also describes how to estimate unknown root distribution and rooting depth parameters by the use of a simulation-based searching method. The full documentation of the computer code will allow further applications and new development.

Hemp (Cannabis sativa L. ssp. sativa) has a long history of domestication due to its versatile use. Recently, different sectors in the economy are investigating hemp cultivation to increase agronomic production and to limit delta-9-tetrahydrocannabinol (THC). Despite the rapid growth of hemp literature in recent years, it is still uncertain whether the knowledge gained from higher latitude regions is applicable to low latitude and tropical regions where hemp has not been grown traditionally. This review provides a comprehensive and updated survey of hemp agronomy, focusing on environmental and management factors influencing the growth and yield of hemp, methods of cannabinoids detection and quantification, and hemp breeding. This review suggests that some previous claims about hemp as a low input crop may not hold true in low-latitude regions. Additional research strategies, such as the integration of experimentation and modeling efforts, are encouraged to hasten new discoveries. Furthermore, to effectively increase the outputs of value products (cannabinoids, seeds, fiber and biomass, etc.) while limiting the THC level, new collaborations between hemp agronomists and economists may streamline the production process by increasing the efficiency of the total production system of hemp as a multifaceted crop.

Background and AimsPatients with decompensated HBV-related liver cirrhosis (HBV D-LC) showed compromised immune responses, which manifested as a proneness to develop infections and hyporesponsiveness to vaccines, resulting in accelerated disease progression. The alterations in T cell-dependent B cell responses in this pathophysiological process were not well understood. This study aimed to investigate T cell-dependent B cell responses in this process and discuss the mechanism from the perspective of metabolism.MethodsChanges in phenotypes and subsets of peripheral B cells between HBV D-LC patients and healthy controls (HCs) were compared by flow cytometry. Isolated B cells were activated by coculture with circulating T follicular (cTfh) cells. After coculture, the frequencies of plasmablasts and plasma cells and immunoglobin levels were analyzed. Oxidative phosphorylation (OXPHOS) and glycolysis were analyzed by a Seahorse analyzer. Mitochondrial function and the AKT/mTOR pathway were analyzed by flow cytometry.ResultsThe proliferation and differentiation capacities of B cells after T cell stimulation were impaired in D-LC. Furthermore, we found that B cells from D-LC patients showed reductions in OXPHOS and glycolysis after activation, which may result from reduced glucose uptake, mitochondrial dysfunction and attenuated activation of the AKT/mTOR pathway.ConclusionsB cells from HBV D-LC patients showed dysfunctional energy metabolism after T cell-dependent activation. Understanding the regulations of B cell metabolic pathway and their changes may provide a new direction to rescue B cell hyporesponsiveness in patients with HBV D-LC, preventing these patients be infected and improving sensitivity to vaccines.

The multi-potentiality of mesenchymal stem cells makes them excellent options for future tissue engineering and clinical therapy, including liver injury. In this study, we investigated the effects of valproic acid (VPA), a direct inhibitor of histone deacetylase (HDAC), on the hepatic differentiation of human bone marrow mesenchymal stem cells (BMMSCs). The cells were found to differentiate into a more homogeneous hepatocyte-like population when pretreated with 5 mM VPA for 72 h. The expression of liver-specific markers was significantly upregulated in the VPA-treated group at the mRNA and protein levels. VPA treatment also significantly enhanced the hepatic functions of the differentiated cells, including glycogen storage, cytochrome P450 activity, AFP and ALB synthesis, and urea production. Further analysis showed that treatment with 5 mM of VPA for 72 h greatly improved the histones H3 and H4 acetylation. These results demonstrated that VPA could considerably improve the hepatic differentiation of human BMMSCs, probably because the chromatin-acetylated state changes upon VPA treatment through its HDAC inhibitory effect. Thus, this study provides a direct research model for producing human hepatocytes for clinical purposes.

Remote-sensing using normalized difference vegetation index (NDVI) has the potential of rapidly detecting the effect of water stress on field crops. However, this detection has typically been accomplished only after the stress effect led to significant changes in crop green biomass, leaf area index, angle and position, and few studies have attempted to estimate the uncertainties of the regression models. These have limited the informed interpretation of NDVI data in agricultural applications. We built a ground-based sensing cart and used it to calibrate the relationships between NDVI and leaf water potential (LWP) for wheat, corn, and cotton growing under field conditions. Both the methods of ordinary least-squares (OLS) and weighted least-squares (WLS) were employed in data analysis, and measurement errors in both LWP and NDVI were considered. We also used statistical resampling to test the effect of measurement errors of LWP on the uncertainties of model coefficients. Our data showed that obtaining a high value of the coefficient of determination did not guarantee a high prediction precision in the obtained regression models. Large prediction uncertainties were estimated for all three crops, and the regressions obtained were not always significant. The best models were obtained for cotton with a prediction uncertainty of 27%. We found that considering measurement errors for both LWP and NDVI led to reduced uncertainties in model coefficients. Also, reducing the sample size of LWP measurement led to significantly increased uncertainties in the coefficients of the linear models describing the LWP-NDVI relationship. Finally, potential strategies for reducing the uncertainty relative to the range of NDVI measurement are discussed.

Background The aberrant expression of sperm-associated antigen 9 (SPAG9) is associated with numerous cancers, including hepatocellular carcinoma (HCC). The exploration of molecules and mechanisms regulating SPAG9 expression may provide new options for HCC therapy. Methods MiRNA target prediction programs were used to explore SPAG9-targeted miRNAs. SPAG9 and miR-141 expression were detected in HCC tissues and cell lines by Western blot and real-time PCR. Dual-luciferase reporter assay was utilized to validate SPAG9 as a direct target gene of miR-141. Cell proliferation, invasion, and migration assays were used to determine whether miR-141-mediated regulation of SPAG9 could affect HCC progression. Results An inverse correlation was observed between SPAG9 and miR-141 expression in HCC tissues and cell lines. Dual-luciferase reporter assay further showed that SPAG9 was a direct target gene of miR-141. The ectopic expression of miR-141 could markedly suppress SPAG9 expression in HCC cells. MiR-141 overexpression also resulted in significantly reduced cell proliferation, invasion, and migration, and imitation of the SPAG9 knockdown effects on HCC cells. Furthermore, SPAG9 restoration in miR-141-expressing cells sufficiently attenuated the tumor-suppressive effects of miR-141. Finally, JNK activity was found to be reduced by miR-141 overexpression the same way as by SPAG9 silencing. The overexpression of SPAG9 lacking its 3′-UTR significantly restored JNK activity and its downstream genes in miR-141-transfected HCC cells. Conclusion MiR-141 suppression may cause aberrant expression of SPAG9 and promote HCC tumorigenesis via JNK pathway.