[Research progress on active ingredients of Coicis Semen].

As a common medicinal and edible resource in China, Coicis Semen has a long history of cultivation and medicinal use. Traditional Chinese medicine(TCM) clinically believes that Coicis Semen has the effect of strengthening the spleen and tonifying the lungs, clearing heat and dampness, removing pus and paralysis, and stopping diarrhea. Therefore, it is used to treat edema, foot odor, spleen deficiency, diarrhea, and other symptoms. The above effects are closely related to the active ingredients of Coicis Semen, such as esters, fatty acids, polysaccharides, proteins, as well as phenolic acids, sterols, flavonoids, lactams, triterpenes, alkaloids, and adenosine. Modern research has found that Coicis Semen also has anti-cancer, anti-inflammatory, antioxidant, hypoglycemic, and hypotensive effects and other pharmacological activities, and it can improve immunity and regulate lipid metabolism. Coicis Semen is widely distributed in China, mainly produced in Guizhou, Yunnan, Fujian, Sichuan, and other places, and the quality of Coicis Semen from different origins varies. From ancient times to the present, Coicis Semen processing methods have experienced the process from simple to complex, and the types of auxiliary materials are more extensive, such as soil, bran, and river sand. These processing methods have been inherited from generation to generation. Nowadays, the commonly used methods are bran-fried, stir-fried, sand-fried, etc. In this paper, by reviewing the relevant literature in China and abroad in recent years, the main active ingredients and related pharmacological effects of Coicis Semen are sorted out, and the effects of different origins and processing methods on the chemical composition of Coicis Semen are summarized, with a view to providing references for the comprehensive development and utilization of Coicis Semen and the further study of its mechanism of action.

Megafossils of Betulaceae from the Oligocene of Qaidam Basin and their paleoenvironmental and phytogeographic implications.

Understanding the paleoenvironment and phytogeographical history of the Tibetan Plateau, China relies on discovering new plant fossils. The Qaidam Basin has long been regarded as an ideal 'field laboratory' to investigate the paleoclimate and paleobiological evolution of the northern Tibetan Plateau. However, fossil angiosperms from the Qaidam Basin are rare, and our knowledge of its paleovegetation is poor. Here, we report fossil leaves and fruits of Betulaceae found from the Oligocene Shangganchaigou Formation of northwestern Qaidam Basin (Huatugou area). Comparative morphological analysis led us to assign the fruits to the Betula subgenus Betula and the leaves to Carpinus grandis. These findings, together with other reported fossil plants from the same locality, reveal a close floristic linkage between the Qaidam Basin and Europe during the Oligocene. The northern pathway of this floristic exchange may have crossed through the Qaidam Basin during the late Paleogene. This floristic linkage may have been facilitated by the continuous narrowing of the Turgai Strait and stronger westerlies, which transported moisture and provided favorable climatic conditions. Indeed, fossil plants collected from the Qaidam Basin suggest that during the Oligocene this region had warm and humid deciduous broad-leaf forest, which differs from the region's modern vegetation and indicates that the Qaidam Basin may have been a suitable region for these plants to flourish and spread during the Oligocene.

Inorganic-Organic Nanoarchitectonics: MXene/Covalent Organic Framework Heterostructure for Superior Microextraction.

One of the difficulties limiting covalent organic frameworks (COFs) from becoming excellent adsorbents is their stacking/aggregation architectures owing to poor morphology/structure control during the synthesis process. Herein, an inorganic-organic nanoarchitectonics strategy to synthesize the MXene/COF heterostructure (Ti3 C2 Tx /TAPT-TFP) is developed by the assembly of ß-ketoenamine-linked COF on the Ti3 C2 Tx MXene nanosheets. The as-prepared Ti3 C2 Tx /TAPT-TFP retains the 2D architecture and high adsorption capacity of MXenes as well as large specific surface area and hierarchical porous structure of COFs. As a proof of concept, the potential of Ti3 C2 Tx /TAPT-TFP for solid-phase microextraction (SPME) of trace organochlorine pesticides (OCPs) is investigated. The Ti3 C2 Tx /TAPT-TFP based SPME method achieves low limits of detection (0.036-0.126 ng g-1 ), wide linearity ranges (0.12-20.0 ng g-1 ), and acceptable repeatabilities for preconcentrating trace OCPs from fruit and vegetable samples. This study offers insights into the potential of constructing COF or MXene-based heterostructures for the microextraction of environmental pollutants.

Nitrogen removal from pharmaceutical wastewater using simultaneous nitrification-denitrification coupled with sulfur denitrification in full-scale system.

Fermentation pharmaceutical wastewater (FPW) containing excessive ammonium and low chemical oxygen demand (COD)/nitrogen ratio (C/N ratio) brings serious environmental risks. The stepwise nitrogen removal was achieved in a full-scale anaerobic/aerobic/anoxic treatment system with well-constructed consortia, that enables simultaneous partial nitrification-denitrification coupled with sulfur autotrophic denitrification (SPND-SAD) (∼99 % (NH4+-N) and ∼98 % (TN) removals) at the rate of 0.8-1.2 kg-N/m3/d. Inoculating simultaneous nitrification-denitrification (SND) consortia in O1 tank decreased the consumed ΔCOD and ΔCOD/ΔTN of A1 + O1 tank, resulting in the occurrence of short-cut SND at low C/N ratio. In SAD process (A2 tank), bio-generated polysulfides reacted with HS- to rearrange into shorter polysulfides, enhancing sulfur bioavailability and promoting synergistic SAD removal. PICRUSt2 functional prediction indicated that bioaugmentation increased genes related to Nitrogen/Sulfur/Carbohydrate/Xenobiotics metabolism. Key functional gene analysis highlighted the enrichment of nirS and soxB critical for SPND-SAD system. This work provides new insights into the application of bioaugmentation for FPW treatment.

Unveiling immunogenic cell death-related genes in colorectal cancer: an integrated study incorporating transcriptome and Mendelian randomization analyses.

Immunogenic cell death (ICD), a type of cell death that activates the tumor-specific immune response and thus exerts anti-tumor effects, is an emerging target in tumor therapy, but research on ICD-related genes (ICDGs) in colorectal cancer (CRC) remains limited. This study aimed to identify the CRC-specific ICDGs and explore their potential roles. Through RNA sequencing for tissue samples from CRC patients and integration with The Cancer Genome Atlas (TCGA) data, we identified 33 differentially expressed ICDGs in CRC. We defined the ICD score based on these genes in single-cell data, where a high score indicated an immune-active microenvironment. Additionally, molecular subtypes identified in bulk RNA data showed distinct immune landscapes. The ICD-related signature constructed with machine learning effectively distinguished patients' prognosis. The summary data-based Mendelian randomization (SMR) and colocalization analysis prioritized CFLAR for its positive association with CRC risk. Molecular docking revealed its stable binding with chemotherapeutic drugs like irinotecan. Furthermore, experimental validation confirmed CFLAR overexpression in CRC samples, and its knockdown inhibited tumor cell proliferation. Overall, this study expands the understanding of the potential roles and mechanisms of ICDGs in CRC and highlights CFLAR as a promising target for CRC.

Periodic, n-soliton and variable separation solutions for an extended (3+1)-dimensional KP-Boussinesq equation.

An extended (3+1)-dimensional Kadomtsev-Petviashvili-Boussinesq equation is studied in this paper to construct periodic solution, n-soliton solution and folded localized excitation. Firstly, with the help of the Hirota's bilinear method and ansatz, some periodic solutions have been derived. Secondly, taking Burgers equation as an auxiliary function, we have obtained n-soliton solution and n-shock wave. Lastly, we present a new variable separation method for (3+1)-dimensional and higher dimensional models, and use it to derive localized excitation solutions. To be specific, we have constructed various novel structures and discussed the interaction dynamics of folded solitary waves. Compared with the other methods, the variable separation solutions obtained in this paper not only directly give the analytical form of the solution u instead of its potential [Formula: see text], but also provide us a straightforward approach to construct localized excitation for higher order dimensional nonlinear partial differential equation.

Natural products for treating cytokine storm-related diseases: Therapeutic effects and mechanisms.

BACKGROUND: A cytokine storm (CS) is a rapidly occurring, complex, and highly lethal systemic acute inflammatory response induced by pathogens and other factors. Currently, no clinical therapeutic drugs are available with a significant effect and minimal side effects. Given the pathogenesis of CS, natural products have become important resources for bioactive agents in the discovery of anti-CS drugs. PURPOSE: This study aimed to provide guidance for preventing and treating CS-related diseases by reviewing the natural products identified to inhibit CS in recent years. METHODS: A comprehensive literature review was conducted on CS and natural products, utilizing databases such as PubMed and Web of Science. The quality of the studies was evaluated and summarized for further analysis. RESULTS: This study summarized more than 30 types of natural products, including 9 classes of flavonoids, phenols, and terpenoids, among others. In vivo and in vitro experiments demonstrated that these natural products could effectively inhibit CS via nuclear factor kappa-B, mitogen-activated protein kinase, and Mammalian target of rapamycin (mTOR) signaling pathways. Moreover, the enzyme inhibition assays revealed that more than 20 chemical components had the potential to inhibit ACE2, 3CL-protease, and papain-like protease activity. The experimental results were obtained using advanced technologies such as biochips and omics. CONCLUSIONS: Various natural compounds in traditional Chinese medicine (TCM) extracts could directly or indirectly inhibit CS occurrence, potentially serving as effective drugs for treating CS-related diseases. This study may guide further exploration of the therapeutic effects and biochemical mechanisms of natural products on CS.

Predicting carbon futures prices based on a new hybrid machine learning: Comparative study of carbon prices in different periods.

Accurate prediction of carbon price is of great significance to national energy security and climate environment policies. This paper comes up with a new forecasting model variational mode decomposition, convolutional neural network, bidirectional long short-term memory, and multi-layer perceptron (VMD-CNN-BILSTM-MLP) to predict EUA carbon futures prices in two periods of five years before and after the introduction of emission reduction policies. The parameters of the VMD model are determined by genetic algorithm (GA) firstly, carbon futures prices are broken down into subsequences of different frequencies using the model. The MLP model is then applied to predict the highest frequency sequence. The CNN-BILSTM model is applied to predict other subsequences later. Finally, the predicted values of each subsequence are linearly added to obtain the final result of the entire model. The prediction effect of the model is mainly tested by root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), coefficient of determination (R2) and the modification of Diebold-Mariano test (MDM). In both periods, the proposed model predicts better than the other models, and the prediction effect of carbon futures price in the first five years is a little better than that in the second five years. In general, the experiment of predicting carbon futures prices in two different periods, the experiment of changing the proportion of data set and the experiment of predicting the whole sample all prove that the mixed model proposed in this paper has good prediction effect.

GsPKS24, a calcineurin B-like protein-interacting protein kinase gene from Glycine soja, positively regulates tolerance to pH stress and ABA signal transduction.

SOS2-like protein kinases (PKS/CIPK) family genes are known to be involved in various abiotic stresses in plants. Even though, its functions have been well characterized under salt and drought stresses. The roles of PKS genes associated with alkaline stress response are not fully established yet. In this study, we identified 56 PKS family genes which could be mainly classified into three groups in wild soybean (Glycine soja). PKS family genes transcript profiles revealed different expression patterns under alkali stress. Furthermore, we confirmed the regulatory roles of GsPKS24 in response to NaHCO3, pH and ABA treatments. Overexpression of GsPKS24 enhanced plant tolerance to pH stress in Arabidopsis and soybean hairy roots but conferred suppressed pH tolerance in Arabidopsis atpks mutant. Additionally, Overexpression of GsPKS24 decreased the ABA sensitivity compared to Arabidopsis atpks mutant which displayed more sensitivity towards ABA. Moreover, upregulated expression of stress responsive and ABA signal-related genes were detected in GsPKS24 overexpression lines. In conclusion, we identified the wild soybean PKS family genes, and explored the roles of GsPKS24 in positive response to pH stress tolerance, and in alleviation of ABA sensitivity.

Throughput-scalable manufacturing of SARS-CoV-2 mRNA lipid nanoparticle vaccines.

Lipid nanoparticles (LNPs) are a potent delivery technology that have made it possible for the recent clinical breakthroughs in mRNA therapeutics and vaccines. A key challenge to the broader implementation of mRNA therapeutics and vaccines is the development of technology to produce precisely defined LNP formulations, with throughput that can scale from discovery to commercial manufacturing and meet the stringent manufacturing standards of the pharmaceutical industry. To address these challenges, we have developed a microfluidic chip that incorporates 1×, 10×, or 256× LNP-generating units that achieve scalable production rates of up to 17 L/h of precisely defined LNPs. Using these chips, we demonstrate that LNP physical properties and potency in vivo are unchanged as throughput is scaled. Our chips are fabricated out of silicon and glass substrates, which have excellent solvent compatibility, compatibility with pharmaceutical manufacturing, and can be fully reset and reused. SARS-CoV-2 mRNA-LNP vaccines formulated by our chips triggered potent antibody responses in a preclinical study. These results demonstrate the feasibility of directly translating microfluidic-generated LNPs to the scale necessary for commercial production.

Experimental Investigation of Fatigue Capacity of Bending-Anchored CFRP Cables.

In this study, the variation of fatigue stiffness, fatigue life, and residual strength, as well as the macroscopic damage initiation, expansion, and fracture of CFRP (carbon fiber reinforced polymer) rods in bending-anchored CFRP cable, were investigated experimentally to verify the anchoring performance of the bending anchoring system and evaluate the additional shear effect caused by bending anchoring. Additionally, the acoustic emission technique was used to monitor the progression of critical microscopic damage to CFRP rods in a bending anchoring system, which is closely related to the compression-shear fracture of CFRP rods within the anchor. The experimental results indicate that after the fatigue cycles of two million, the residual strength retention rate of CFRP rod was as high as 95.1% and 76.7% under the stress amplitudes of 500 MPa and 600 MPa, indicating good fatigue resistance. Moreover, the bending-anchored CFRP cable could withstand 2 million cycles of fatigue loading with a maximum stress of 0.4 σult and an amplitude of 500 MPa without obvious fatigue damage. Moreover, under more severe fatigue-loading conditions, it can be found that fiber splitting in CFRP rods in the free section of cable and compression-shear fracture of CFRP rods are the predominant macroscopic damage modes, and the spatial distribution of macroscopic fatigue damage of CFRP rods reveals that the additional shear effect has become the determining factor in the fatigue resistance of the cable. This study demonstrates the good fatigue-bearing capacity of CFRP cable with a bending anchoring system, and the findings can be used for the optimization of the bending anchoring system to further enhance its fatigue resistance, which further promotes the application and development of CFRP cable and bending anchoring system in bridge structures.

Subtypes analysis and prognostic model construction based on lysosome-related genes in colon adenocarcinoma.

Background: Lysosomes are essential for the development and recurrence of cancer. The relationship between a single lysosome-related gene and cancer has previously been studied, but the relationship between the lysosome-related genes (LRGs) and colon adenocarcinoma (COAD) remains unknown. This research examined the role of lysosome-related genes in colon adenocarcinoma. Methods: 28 lysosome-related genes associated with prognosis (PLRGs) were found by fusing the gene set that is differently expressed between tumor and non-tumor in colon adenocarcinoma with the gene set that is related to lysosomes. Using consensus unsupervised clustering of PLRGs, the colon adenocarcinoma cohort was divided into two subtypes. Prognostic and tumor microenvironment (TME) comparisons between the two subtypes were then made. The PLRGs_score was constructed using the least absolute shrinkage and selection operator regression (LASSO) method to quantify each patient's prognosis and provide advice for treatment. Lastly, Western Blot and immunohistochemistry (IHC) were used to identify MOGS expression at the protein level in colon adenocarcinoma tissues. Results: PLRGs had more somatic mutations and changes in genetic level, and the outcomes of the two subtypes differed significantly in terms of prognosis, tumor microenvironment, and enrichment pathways. Then, PLRGs_score was established based on two clusters of differential genes in the cancer genome atlas (TCGA) database, and external verification was performed using the gene expression omnibus (GEO) database. Then, we developed a highly accurate nomogram to enhance the clinical applicability of the PLRGs_score. Finally, a higher PLRGs_score was associated with a poorer overall survival (OS), a lower tumor mutation burden (TMB), a lower cancer stem cell (CSC) index, more microsatellite stability (MSS), and a higher clinical stage. MOGS was substantially elevated at the protein level in colon adenocarcinoma as additional confirmation. Conclusion: Overall, based on PLRGs, we identified two subtypes that varied significantly in terms of prognosis and tumor microenvironment. Then, in order to forecast patient prognosis and make treatment suggestions, we developed a diagnostic model with major significance for prognosis, clinical relevance, and immunotherapy. Moreover, we were the first to demonstrate that MOGS is highly expressed in colon adenocarcinoma.

Machine learning-based glycolysis-associated molecular classification reveals differences in prognosis, TME, and immunotherapy for colorectal cancer patients.

Background: Aerobic glycolysis is a process that metabolizes glucose under aerobic conditions, finally producing pyruvate, lactic acid, and ATP for tumor cells. Nevertheless, the overall significance of glycolysis-related genes in colorectal cancer and how they affect the immune microenvironment have not been investigated. Methods: By combining the transcriptome and single-cell analysis, we summarize the various expression patterns of glycolysis-related genes in colorectal cancer. Three glycolysis-associated clusters (GAC) were identified with distinct clinical, genomic, and tumor microenvironment (TME). By mapping GAC to single-cell RNA sequencing analysis (scRNA-seq), we next discovered that the immune infiltration profile of GACs was similar to that of bulk RNA sequencing analysis (bulk RNA-seq). In order to determine the kind of GAC for each sample, we developed the GAC predictor using markers of single cells and GACs that were most pertinent to clinical prognostic indications. Additionally, potential drugs for each GAC were discovered using different algorithms. Results: GAC1 was comparable to the immune-desert type, with a low mutation probability and a relatively general prognosis; GAC2 was more likely to be immune-inflamed/excluded, with more immunosuppressive cells and stromal components, which also carried the risk of the poorest prognosis; Similar to the immune-activated type, GAC3 had a high mutation rate, more active immune cells, and excellent therapeutic potential. Conclusion: In conclusion, we combined transcriptome and single-cell data to identify new molecular subtypes using glycolysis-related genes in colorectal cancer based on machine-learning methods, which provided therapeutic direction for colorectal patients.

Identification of the joint line in revision total knee arthroplasty using a multiple linear regression model: a cadaveric study.

INTRODUCTION: The results of revision total knee arthroplasty (rTKA) may be compromised by excessive joint line (JL) elevation. It is critical but challenging in reestablishing the JL in rTKA. Previous studies have confirmed that, biomechanically and clinically, JL elevation should not exceed 4 mm. Image-based studies described several approaches to locate the JL intraoperatively, however magnification errors could occur. In this cadaveric study, we aim to define an accurate and reliable method to determine the JL. MATERIALS AND METHODS: Thirteen male and eleven female cadavers were used, with an average age of death being 48.3 years. The transepicondylar width (TEW), the distance from the medial (MEJL) and lateral (LEJL) epicondyle, adductor tubercle (ATJL), fibular head (FHJL) and tibial tubercle (TTJL) to the JL were measured in 48 knees. Intra- and interobserver reliability and validity were tested prior to any additional analysis. Pearson correlation and linear regression analysis were used to examine the correlations between landmark-JL distances (LEJL, MEJL, ATJL, FHJL and TTJL) and the TEW, and to further derive models for intraoperative JL determination. The accuracy of different models, quantified by errors between estimated and measured landmark-JL distances, was compared using the Friedman and post hoc Dunn tests. RESULTS: The intra- and inter-observer measurements for TEW, MEJL, LEJL, ATJL, TTJL and FHJL did not differ significantly (p > 0.05). Between genders, significant differences were found on TEW, MEJL, LEJL, ATJL, FHJL and TTJL (p < 0.05). There was no association between TEW and either FHJL or TTJL (p > 0.05), while ATJL, MEJL, and LEJL were found to be correlated with TEW (p < 0.05). Six models were derived: (1) MEJL = 0.37*TEW (r = 0.384), (2) LEJL = 0.28*TEW (r = 0.380), (3) ATJL = 0.47*TEW (r = 0.608), (4) MEJL = 0.413*TEW - 4.197 (R2 = 0.473), (5) LEJL = 0.236*TEW + 3.373 (R2 = 0.326), (6) ATJL = 0.455*TEW + 1.440 (R2 = 0.556). Errors were defined as deviations between estimated and actual landmark-JL distances. The mean absolute value of the errors, created by Model 1-6 was 3.18 ± 2.25, 2.53 ± 2.15, 2.64 ± 2.2, 1.85 ± 1.61, 1.60 ± 1.59 and 1.71 ± 1.5, respectively. The error could be limited to 4 mm in 72.9%, 83.3%, 72.9%, 87.5%, 87.5%, and 93.8% of the cases by referencing Model 1-6, respectively. CONCLUSION: Compared to previous image-based measurements, the current cadaveric study most closely resembles a realistic view of intraoperative settings and could circumvents magnification errors. We recommend using Model 6, the JL can be best estimated by referencing the AT and the ATJL can be calculated as ATJL (mm) = 0.455*TEW (mm) + 1.440 (mm).

Genetic variants in the calcium signaling pathway participate in the pathogenesis of colorectal cancer through the tumor microenvironment.

Background: Cancer risk is influenced by calcium signaling in intracellular and intercellular signaling pathways. However, the relationship between the calcium signaling pathway and colorectal cancer risk remains unknown. We aim to evaluate the role of genetic variants in calcium signaling pathway genes in colorectal cancer risk through the tumor microenvironment. Methods: An analysis of genetic variants in the calcium signaling pathway was conducted using a case-control study that included 1150 colorectal cancer patients and 1342 non-cancer patients. Using the regression model, we assessed whether single-nucleotide polymorphisms (SNPs) increase the risk of colorectal cancer. We also performed a dual luciferase reporter gene assay using HCT116 cell lines and DLD1 cell lines to demonstrate the regulatory relationship between SNP and candidate risk gene. We evaluated the expression of candidate risk gene in different populations. In addition, we also evaluated candidate risk gene and 22 immune cells correlation studies. Results: There was a significant association between the PDE1C rs12538364 T allele and colorectal cancer risk [odds ratio (OR) = 1.57, 95% confidence interval (CI) = 1.30 - 1.90, P = 3.07 × 10-6, P FDR = 0.004]. Mutation of intron region rs1538364 C to T locus reduces promoter activity of PDE1C in DLD1 and HCT116 cell lines (P < 0.05). We identified that PDE1C is significantly down-regulated in colorectal cancer, closely associated with 22 immune cells. Finally, we found that PDE1C could be the biomarker for individual immunotherapy of colorectal cancer. Conclusion: According to our findings, PDE1C may be a key factor contributing to colorectal cancer, thus improving individual immunotherapy for the disease. The potential mechanism by which polymorphisms in the calcium signaling pathway genes may participate in the pathogenesis of colorectal cancer through the tumor microenvironment.

Patterning Wettability on Solvent-Resistant Elastomers with High Spatial Resolution for Replica Mold Fabrication of Droplet Microfluidics.

Controlling the surface wetting properties of channels is crucial to the robust and reliable performance of microfluidic devices. Spatially patterned hydrophobic/hydrophilic microchannels have found utility across various applications, notably in the generation of higher-order emulsions. Unfortunately, the patterning of surface wettability currently requires multistep processes with limited spatial resolution, making it impractical for many applications. In this work, we take inspiration from soft lithography and have developed a new replica mold fabrication technique wherein both the channel geometry and surface wettability are transferred from the mold to the replica. In this approach, the mold is a silicon wafer with lithographically defined features etched into its surface to define the channel geometry and lithographically defined patterns of hydrophobic silanes to define surface wetting properties. The replica is a co-polymer network of PFPE-PEG, for which PFPE can be locally enriched by the mold's patterned silanes to define the spatially patterned wetting properties. We demonstrated the utility of this approach by fabricating a PFPE-PEG-based microfluidic chip, with hydrophobic/hydrophilic patterned microchannels, to generate double emulsions.

Identification of NPF Family Genes in Brassica rapa Reveal Their Potential Functions in Pollen Development and Response to Low Nitrate Stress.

Nitrate Transporter 1/Peptide Transporter Family (NPF) genes encode membrane transporters involved in the transport of diverse substrates. However, little is known about the diversity and functions of NPFs in Brassica rapa. In this study, 85 NPFs were identified in B. rapa (BrNPFs) which comprised eight subfamilies. Gene structure and conserved motif analysis suggested that BrNFPs were conserved throughout the genus. Stress and hormone-responsive cis-acting elements and transcription factor binding sites were identified in BrNPF promoters. Syntenic analysis suggested that tandem duplication contributed to the expansion of BrNPFs in B. rapa. Transcriptomic profiling analysis indicated that BrNPF2.6, BrNPF2.15, BrNPF7.6, and BrNPF8.9 were expressed in fertile floral buds, suggesting important roles in pollen development. Thirty-nine BrNPFs were responsive to low nitrate availability in shoots or roots. BrNPF2.10, BrNPF2.19, BrNPF2.3, BrNPF5.12, BrNPF5.16, BrNPF5.8, and BrNPF6.3 were only up-regulated in roots under low nitrate conditions, indicating that they play positive roles in nitrate absorption. Furthermore, many genes were identified in contrasting genotypes that responded to vernalization and clubroot disease. Our results increase understanding of BrNPFs as candidate genes for genetic improvement studies of B. rapa to promote low nitrate availability tolerance and for generating sterile male lines based on gene editing methods.

Evaluation of absorbent cotton for glycopeptide enrichment.

Selecting proper and efficient glycopeptide enrichment approaches are essential for mass spectrometry-based glycoproteomics since glycopeptides are usually with microheterogeneity and low abundance in most biological samples. Herein, we introduced a cotton hydrophilic interaction liquid chromatography (HILIC) approach for large-scale glycopeptide enrichment with 80% acetonitrile/1% trifluoroacetic acid as the optimal sample loading buffer. The comparison of cotton HILIC with Venusil HILIC and mixed anion-exchange (MAX) approaches indicated that cotton HILIC was superior in overall glycopeptide enrichment, whereas Venusil HILIC preferred in complex glycan structures and MAX performed better with high mannose glycans. Exploration of capacity and recovery rate of cotton HILIC illustrated that 5mg cotton packed in a 200µL tip achieved a reasonable glycopeptide enrichment performance (~6% recovery) from ~0.5mg peptides. In conclusion, cotton HILIC can be used as an optional glycopeptide enrichment approach in glycosylation analysis with its specific merit.

N7-methylguanosine-related lncRNAs: Predicting the prognosis and diagnosis of colorectal cancer in the cold and hot tumors.

Background: 7-Methylguanosine(m7G) contributes greatly to its pathogenesis and progression in colorectal cancer. We proposed building a prognostic model of m7G-related LncRNAs. Our prognostic model was used to identify differences between hot and cold tumors. Methods: The study included 647 colorectal cancer patients (51 cancer-free patients and 647 cancer patients) from The Cancer Genome Atlas (TCGA). We identified m7G-related prognostic lncRNAs by employing the univariate Cox regression method. Assessments were conducted using univariate Cox regression, multivariate Cox regression, receiver operating characteristics (ROC), nomogram, calibration curves, and Kaplan-Meier analysis. All of these procedures were used with the aim of confirming the validity and stability of the model. Besides these two analyses, we also conducted half-maximal inhibitory concentration (IC50), immune analysis, principal component analysis (PCA), and gene set enrichment analysis (GSEA). The entire set of m7G-related (lncRNAs) with respect to cold and hot tumors has been divided into two clusters for further discussion of immunotherapy. Results: The risk model was constructed with 17 m7G-related lncRNAs. A good correlation was found between the calibration plots and the prognosis prediction in the model. By assessing IC50 in a significant way across risk groups, systemic treatment can be guided. By using clusters, it may be possible to distinguish hot and cold tumors effectively and to aid in specific therapeutic interventions. Cluster 1 was identified as having the highest response to immunotherapy drugs and thus was identified as the hot tumor. Conclusion: This study shows that 17 m7G-related lncRNA can be used in clinical settings to predict prognosis and use them to determine whether a tumor is cold or hot in colorectal cancer and improve the individualization of treatment.

The Energy Saving and Emission Reduction Effect of Carbon Trading Pilot Policy in China: Evidence from a Quasi-Natural Experiment.

Promoting the carbon emission trading system has been a crucial measure for China to fulfill its carbon neutrality commitment. Taking the carbon emission trading system implemented in China in 2013 as a quasi-natural experiment, based on the provincial panel data of China from 2005 to 2019, this paper adopts the difference-in-difference (DID) method and the synthetic control method (SCM) to evaluate the impact of the carbon emission trading system on energy conservation and emission reduction in pilot provinces and cities. The research findings reveal that, on the whole, the carbon emission trading system has significantly promoted the process of energy conservation and emission reduction in pilot provinces and cities. Other robustness tests, including the parallel trend test, PSM-DID stationarity test and placebo test have also been passed. Heterogeneity analysis shows that the most significant policy effects occur in Tianjin and Shanghai, followed by Hubei. The emission reduction effect of Guangdong displays a trend of first decreasing and then increasing. The test results demonstrate that the carbon emission trading system can strengthen the process of energy conservation and emission reduction by optimizing the industrial structure and energy structure. In conclusion, policy makers should coordinate the relationship between the government and the market and speed up the transformation of environmental policy from command control type to market incentive type. Meanwhile, improve the property right system and accelerate the promotion of carbon emission trading pilot policies in China according to local conditions. By encouraging technological innovation, a new market-oriented path of energy conservation and emission reduction guided by the enhancement of energy efficiency and the optimization of energy and industrial structures ought to be formed.