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ObjectivesWith the implementation of the national “Dual Carbon Strategy” (carbon peak and carbon neutrality), it is anticipated that the existing coating structures may not meet the requirements of future gas turbine thermal protection coatings. The concept of a new type of environmental/thermal barrier coating (E/TBC) structure with high temperature corrosion resistance has been proposed to meet the demand for thermal protection coatings in hybrid hydrogen combustion engines.MethodsThe development history and research status of thermal barrier coating (TBC), environmental barrier coating (EBC), thermal/environmental barrier coating (T/EBC) and thermal and environmental barrier coating (TEBC) were reviewed and analyzed from the perspective of thermal protection coating materials and coating structures. Moreover, the gap between the above coating structures and the requirementsof thermal protection coating for mixed hydrogen gas turbines was investigated.ResultsIt is reasonable to superimpose the function of EBC onto the thermal protection coating of current mixed hydrogen gas turbines, thereby forming a new type of E/TBC structure with high temperature corrosion resistance on the high-temperature alloy substrate.ConclusionsThrough the preliminary test, it is proved that the new E/TBC structure is suitable for the thermal protection coating requirements of mixed hydrogen gas turbine against high temperature water oxygen corrosion, and it is pointed out that the theory and application research of this new E/TBC thermal protection coating should be vigorously carried out.

The coronavirus disease 2019 (COVID-19) pandemic poses an enormous threat to public health worldwide. Many retrospective studies and case reports to date have shown associations between severe COVID-19 and diseases of multi-organs. However, the research on the causal mechanisms behind this phenomenon is neither extensive nor comprehensive. We conducted a proteome-wide Mendelian randomization (MR) study using summary statistics from a Genome-Wide Association Studies (GWAS) of severe COVID-19 and diseases related to seven organs: lung, spleen, liver, heart, kidney, testis, and thyroid, based on the European ancestry. The primary analytical method used is the radial inverse variance-weighted (radial IVW) method, supplemented with the inverse variance-weighted (IVW), weighted-median (WM), MR-Egger methods. Our findings have confirmed the association between severe COVID-19 and multiple organ-related diseases, such as Hypothyroidism, strict autoimmune (HTCBSA), Thyroid disorders (TD), and Graves’ disease (GD). And we have also identified certain proteins that are associated with organ-related diseases, such as Superoxide Dismutase 2 (SOD2) and TEK Receptor Tyrosine Kinase (TEK), which are also considered potential drug targets. Phenotype scanning and sensitivity analyses were implemented to consolidate the results for Mendelian randomization. This study provides a compelling foundation for investigating COVID-19 caused diseases in future studies.

Abstract Ulcerative colitis is a chronic inflammatory bowel disorder with cellular heterogeneity. To understand the composition and spatial changes of the ulcerative colitis ecosystem, here we use imaging mass cytometry and single-cell RNA sequencing to depict the single-cell landscape of the human colon ecosystem. We find tissue topological changes featured with macrophage disappearance reaction in the ulcerative colitis region, occurring only for tissue-resident macrophages. Reactive oxygen species levels are higher in the ulcerative colitis region, but reactive oxygen species scavenging enzyme SOD2 is barely detected in resident macrophages, resulting in distinct reactive oxygen species vulnerability for inflammatory macrophages and resident macrophages. Inflammatory macrophages replace resident macrophages and cause a spatial shift of TNF production during ulcerative colitis via a cytokine production network formed with T and B cells. Our study suggests components of a mechanism for the observed macrophage disappearance reaction of resident macrophages, providing mechanistic hints for macrophage disappearance reaction in other inflammation or infection situations.

Aberrant DNA methylation is closely associated with various diseases, particularly cancer, and its precise detection plays an essential role in disease diagnosis and monitoring. In this study, we present a novel DNA methylation detection method (namely meHOLMES), which integrates both the TET2/APOBEC-mediated cytosine deamination step and the CRISPR-Cas12a-based signal readout step. TET2/APOBEC efficiently converts unmethylated cytosine to uracil, which is subsequently changed to thymine after PCR amplification. Utilizing a rationally designed crRNA, Cas12a specifically identifies unconverted methylated cytosines and generates detectable signals using either fluorescent reporters or lateral flow test strips. meHOLMES quantitatively detects methylated CpG sites with or without Protospacer Adjacent Motif (PAM) sequences in both artificial and real biological samples. In addition, meHOLMES can complete the whole detection process within 6 h, which is much faster than traditional bisulfite-based sample pre-treatment method. Above all, meHOLMES provides a simpler, faster, more accurate, and cost-effective approach for quantitation of DNA methylation levels in a sequence-independent manner.

Nowadays, the developed deep neural networks (DNNs) have been widely applied to synthetic aperture radar (SAR) image interpretation, such as target classification and recognition, which can automatically learn high-level semantic features in data-driven and task-driven manners. For the supervised learning methods, abundant labeled samples are required to avoid the over-fitting of designed networks, which is usually difficult for SAR image applications. To address these issues, a novel two-stage algorithm based on contrastive learning (CL) is proposed for SAR image target classification. In the pretraining stage, to extract self-supervised representations (SSRs) from an unlabeled train set, a convolutional neural network (CNN)-based encoder is first pretrained using a contrasting strategy. This encoder can convert SAR images into a discriminative embedding space. Meanwhile, the optimal encoder can be determined using a linear evaluation protocol, which can indirectly confirm the transferability of prelearned SSRs to downstream tasks. Therefore, in the fine-tuning stage, a SAR target classifier can be adequately trained using a few labeled SSRs in a supervised manner, which benefits from the powerful pretrained encoder. Numerical experiments are carried out on the shared MSTAR dataset to demonstrate that the model based on the proposed self-supervised feature learning algorithm is superior to the conventional supervised methods under labeled data constraints. In addition, knowledge transfer experiments are also conducted on the openSARship dataset, showing that the encoder pretrained from the MSTAR dataset can support the classifier training with high efficiency and precision. These results demonstrate the excellent training convergence and classification performance of the proposed algorithm.

MHC-peptide multimers are important reagents for detecting antigen specific T cells. Here the authors show that DNA scaffolds can be used to make MHC-peptide multimers and the avidity controlled so that low abundance or T cells with low affinity TCR can be detected using these reagents.

Mimicking multi-enzyme catalytic cascades in natural systems with spatial organization in confined structures is gaining increasing attention in the emerging field of systems chemistry. Here, the authors demonstrate that multi-shelled metal-organic frameworks can be used as a hierarchical scaffold to spatially organize enzymes on nanoscale to enhance cascade catalytic efficiency.

IntroductionExposure to air pollution has been linked to the mortality of heart failure. In this study, we sought to update the existing systematic review and meta-analysis, published in 2013, to further assess the association between air pollution and acute decompensated heart failure, including hospitalization and heart failure mortality.MethodsPubMed, Web of Science, EMBASE, and OVID databases were systematically searched till April 2022. We enrolled the studies regarding air pollution exposure and heart failure and extracted the original data to combine and obtain an overall risk estimate for each pollutant.ResultsWe analyzed 51 studies and 7,555,442 patients. Our results indicated that heart failure hospitalization or death was associated with increases in carbon monoxide (3.46% per 1 part per million; 95% CI 1.0233–1.046, P < 0.001), sulfur dioxide (2.20% per 10 parts per billion; 95% CI 1.0106–1.0335, P < 0.001), nitrogen dioxide (2.07% per 10 parts per billion; 95% CI 1.0106–1.0335, P < 0.001), and ozone (0.95% per 10 parts per billion; 95% CI 1.0024–1.0166, P < 0.001) concentrations. Increases in particulate matter concentration were related to heart failure hospitalization or death (PM2.5 1.29% per 10 μg/m3, 95% CI 1.0093–1.0165, P < 0.001; PM10 1.30% per 10 μg/m3, 95% CI 1.0102–1.0157, P < 0.001).ConclusionThe increase in the concentration of all pollutants, including gases (carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone) and particulate matter [(PM2.5), (PM10)], is positively correlated with hospitalization rates and mortality of heart failure.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021256241.

Abstract Objectives The incidence and adverse events of postoperative blood transfusion in spinal tuberculosis (TB) have attracted increasing attention. Our purpose was to develop a prediction model to evaluate blood transfusion risk after spinal fusion (SF) for spinal TB. Methods Nomogram and machine learning algorithms, support vector machine (SVM), decision tree (DT), multilayer perceptron (MLP), Naive Bayesian (NB), k-nearest neighbors (K-NN) and random forest (RF), were constructed to identified predictors of blood transfusion from all spinal TB cases treated by SF in our department between May 2010 and April 2020. The prediction performance of the models was evaluated by 10-fold cross-validation. We calculated the average AUC and the maximum AUC, then demonstrated the ROC curve with maximum AUC. Results The collected cohort ultimately was consisted of 152 patients, where 56 required allogeneic blood transfusions. The predictors were surgical duration, preoperative Hb, preoperative ABL, preoperative MCHC, number of fused vertebrae, IBL, and anticoagulant history. We obtained the average AUC of nomogram (0.75), SVM (0.62), k-NM (0.65), DT (0.56), NB (0.74), MLP (0.56) and RF (0.72). An interactive web calculator based on this model has been provided ( https://drwenleli.shinyapps.io/STTapp/ ). Conclusions We confirmed seven independent risk factors affecting blood transfusion and diagramed them with the nomogram and web calculator.

In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the single-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful applications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commercial industry. Public summary: • Single-cell sequencing can reveal molecular characteristics at the cell level • Spatial omics can reconstruct the organization of cells and their interactions • Single-cell multi-omics will picture the cell in a comprehensive way

Bemisia tabaci is the main pest of agriculture in many regions of the world. The resistance of whitefly to pesticides has increased as a consequence of the continuous irrational use of wide-spectrum pesticides. Thus, pesticides are no longer always effective as a long-term control method. The agricultural landscape can affect the occurrence of an insect population. The objective of this study was to clarify the occurrence of whitefly and its predators in tomato fields in different agricultural landscapes. Different landscapes are classified into urban, flower, water, and mountain landscapes by the principal component analysis method. In 2018–2019, whitefly had the longest main activity period and the lowest density in the flower landscape. The water landscape helped to maintain the highest densities of whitefly during the main activity period. Nine species of predators were sampled, and Nesidiocoris tenuis, Chrysoperla sinica, Menochilus sexmaculata, and Harmonia axyridis were the dominant species throughout the sampling season in both years. During the main activity period, N. tenuis had the highest density in all sampled landscapes. The density of the dominant predators was the highest in the flower landscape, and each natural predator had the largest temporal niche width in the 2-year sampling period. Bemisia tabaci, N. tenuis, and M. sexmaculata were highly synchronized temporally. The flower landscape showed satisfactory results in suppressing whitefly. Increasing the proportion of flowering plants and increasing the diversity of plant crops in the agricultural landscape can effectively reduce the densities of whitefly during an outbreak.

Staphylococcus aureus (S. aureus), as the main pathogen in milk and dairy products, usually causes intoxication with vomiting and various kinds of inflammation after entering the human body. CodY, an important transcriptional regulator in S. aureus, plays an important role in regulating metabolism, growth, and virulence. However, little is known about the role of CodY on environmental stress tolerance. In this research, we revealed the role of CodY in environmental stress tolerance in foodborne S. aureus RMSA24. codY mutation significantly reduced the tolerance of S. aureus to desiccation and oxidative, salt, and high-temperature stresses. However, S. aureus was more tolerant to low temperature stress due to mutation of codY. We found that the expressions of two important heat shock proteins—GroEL and DanJ—were significantly down-regulated in the mutant codY. This suggests that CodY may indirectly regulate the high- and low-temperature tolerance of S. aureus by regulating the expressions of groEL and danJ. This study reveals a new mechanism of environmental stress tolerance in S. aureus and provides new insights into controlling the contamination and harm caused by S. aureus in the food industry.

Klebsiella pneumoniae is a gram-negative bacterium that can cause many diseases in hospitals and communities. Intestinal K. pneumoniae infections are relatively rare. Most K. pneumoniae infections begin with the colonization of the gastrointestinal system. In this study, clinically isolated K. pneumoniae strains were used to infect intestinal epithelial Caco-2 cells to study the possible intestinal translocation mechanism of K. pneumoniae. We found that of the three K. pneumoniae strains tested, KP1821 exhibited the strongest adhesive and invasive abilities and that the adhesion to Caco-2 intestinal epithelial cells was affected by the acidic environment of the stomach. Transcriptome sequencing revealed the involvement of molecules associated with the extracellular matrix and cell adhesion, inflammatory response, calcium ion and transforming growth factor β (TGF-β) signaling pathways, and other abnormalities in biological processes and cell signaling pathways. Additionally, tolloid-like protein 1 (TLL1) was significantly upregulated. Knocking down TLL1 with shRNA significantly reduced KP1821's ability to invade and adhere to intestinal epithelial cells. TLL1 is involved in the activation of the TGF-β signaling pathway. Inhibition of this pathway using the inhibitor SB431542 induced significantly reduced adhesion and invasion capabilities of KP1821. Our findings demonstrate that TLL1 participates in K. pneumoniae adhesion and invasion of intestinal epithelial cells by activating the TGF-β signaling pathway.

Abstract Objective Sevoflurane is a common anesthetic and is widely used in pediatric clinical surgery to induce and maintain anesthesia through inhalation. Increasing studies have revealed that sevoflurane has neurotoxic effects on neurons, apoptosis, and memory impairment. miR‐384 is involved in the process of neurological diseases. However, the role of miRNA‐384‐3p in sevoflurane‐induced nerve injury is not clear. This study focused on exploring the roles and mechanisms of miRNA‐384‐3p in sevoflurane‐induced nerve injury. Methods Seven‐day‐old rats were exposed to 2.3% sevoflurane to induce nerve injury. The morphological changes in neurons in the hippocampal CA1 region were detected by HE staining and Nissl staining. Neuronal apoptosis was detected by TUNEL and Western blot assays. Spatial memory and learning ability were detected by the Morris water maze assay. The target gene of miRNA‐384‐3p was verified through a luciferase reporter assay. A rescue experiment was used to confirm the miRNA‐384‐3p pathway in sevoflurane‐induced nerve injury. Results Sevoflurane reduced miRNA‐384‐3p expression in the rat hippocampus. miRNA‐384‐3p alleviated sevoflurane‐induced morphological changes in hippocampal neurons and apoptosis of neurons in the hippocampal CA1 region. Meanwhile, miRNA‐384‐3p attenuated the decline in spatial memory and learning ability induced by sevoflurane. miRNA‐384‐3p alleviated sevoflurane‐induced nerve injury by inhibiting the expression of adaptor‐associated kinase 1 (Aak1). Conclusion Our findings revealed the role and mechanism of miRNA‐384‐3p in sevoflurane‐induced nerve injury, suggesting that miRNA‐384‐3p could be a novel and promising strategy for reducing sevoflurane‐induced neurotoxicity.

The objective of the study was to investigate the levels of plasma exosome-derived fragile site-associated tumor suppressor (FATS) and evaluate its prognostic predictive ability in ovarian cancer (OC) patients. Exosome-rich fractions were isolated from the plasma of 90 patients with OC enrolled in this study. The levels of plasma exosome-derived FATS were detected by ELISA. The levels of exosome-derived FATS in OC patients were significantly lower as compared to the healthy controls (P < 0.001). The levels of plasma exosome-derived FATS were higher in OC patients with low grade (1/2), and Federation International of Gynecology and Obstetrics (FIGO) Stages I/II than those in high grade (3/4) and Stages III/IV of the disease (p = 0.003; p < 0.001), respectively. The levels of plasma exosome-derived FATS were significantly higher in OC patients with no lymph node metastasis or no ascites as compared to those with lymph node metastasis or ascites, respectively (both p < 0.001). The levels of plasma exosome-derived FATS were higher in OC patients having CA-125 below 35 U/ml as compared to those with CA-125 greater than 35 U/ml (p < 0.001). Among all enrolled OC patients, both 5-DFS and 5-OS were shorter in patients with lower plasma exosome-derived FATS levels than those with higher levels (both p < 0.001). The area under the receiver operating characteristic curve of plasma exosome-derived FATS was 0.85 (95% CI: 0.76-0.91) for 5-DFS and 0.91 (95% CI: 0.83-0.96) for 5-OS prediction in patients with OC. Plasma exosome-derived FATS levels in OC patients were significantly downregulated. Low levels of plasma exosome-derived FATS had a significant relationship with FIGO Stages III/IV, high grade, ascites, higher levels of CA-125, lymph node metastasis, and prognosis of OC patients. Thus, our findings may provide insights for the development of a new strategy OC treatment.

To meet the demand for novel pest management strategies to combat the development of insecticide resistance, plant essential oils may be a promising alternative source. This study investigated the insecticidal activity of five essential oils from the Rutaceae plant family against Thrips flavus Schrank (Thysanoptera: Thripidae) under laboratory conditions. The plant essential oils were citrus oil (Citrus reticulata Blanco), Chuan-shan pepper oil (Zanthoxylum piasezkii Maxim.), zanthoxylum oil (Zanthoxylum bungeanum Maxim.), pomelo peel oil (Citrus maxima (Burm.) Merr.) and orange leaf oil (Citrus sinensis (L.) Osbeck). Among the essential oils evaluated, orange leaf oil (LC50 = 0.26 g/L), zanthoxylum oil (LC50 = 0.27 g/L), and pomelo peel oil (LC50 = 0.44 g/L) resulted in a higher gastric toxicity under laboratory conditions. The results of the pot experiment also showed that orange leaf oil (93.06 ± 3.67% at 540.00 g a.i.·hm−2, 97.22 ± 1.39% at 720 g a.i.·hm−2, 100.00% at 900.00 g a.i.·hm−2) zanthoxylum oil (98.73 ± 1.27% at 900 g a.i.·hm−2), and pomelo peel oil (100.00% at 900 g a.i.·hm−2) exhibited a higher control efficacy, being the most effective against T. flavus after 7 days of treatment. The essential oil components were then identified by gas chromatography–mass spectrometry (GC–MS). The insecticidal activity of orange leaf oil, pomelo peel oil, and zanthoxylum oil could be attributed to their main constituents, such as methyl jasmonate (50.92%), D-limonene (76.96%), and linalool (52.32%), respectively. In the olfactory test, adult T. flavus were attracted by zanthoxylum oil and Chuan-shan pepper oil. We speculated that linalool might be the key signaling compound that attracts T. flavus. These results showed that orange leaf oil, zanthoxylum oil, and pomelo peel oil exhibited insecticidal activities under controlled conditions. They can be implemented as effective and low-toxicity botanical insecticides and synergistic agents against T. flavus.

Adenosine-to-inosine (A-to-I) RNA editing is an important post-transcriptional modification mediated by the adenosine deaminases acting on RNA (ADAR) family of enzymes, expanding the transcriptome by altering selected nucleotides A to I in RNA molecules. Recently, A-to-I editing has been explored for correcting disease-causing mutations in RNA using therapeutic guide oligonucleotides to direct ADAR editing at specific sites. Humans have two active ADARs whose preferences and specificities are not well understood. To investigate their substrate specificity, we introduced hADAR1 and hADAR2, respectively, into Schizosaccharomyces pombe (S. pombe), which lacks endogenous ADARs, and evaluated their editing activities in vivo. Using transcriptome sequencing of S. pombe cultured at optimal growth temperature (30 °C), we identified 483 A-to-I high-confident editing sites for hADAR1 and 404 for hADAR2, compared with the non-editing wild-type control strain. However, these sites were mostly divergent between hADAR1 and hADAR2-expressing strains, sharing 33 common sites that are less than 9% for each strain. Their differential specificity for substrates was attributed to their differential preference for neighboring sequences of editing sites. We found that at the -3-position relative to the editing site, hADAR1 exhibits a tendency toward T, whereas hADAR2 leans toward A. Additionally, when varying the growth temperature for hADAR1- and hADAR2-expressing strains, we observed increased editing sites for them at both 20 and 35 °C, compared with them growing at 30 °C. However, we did not observe a significant shift in hADAR1 and hADAR2's preference for neighboring sequences across three temperatures. The vast changes in RNA editing sites at lower and higher temperatures were also observed for hADAR2 previously in budding yeast, which was likely due to the influence of RNA folding at these different temperatures, among many other factors. We noticed examples of longer lengths of dsRNA around the editing sites that induced editing at 20 or 35 °C but were absent at the other two temperature conditions. We found genes' functions can be greatly affected by editing of their transcripts, for which over 50% of RNA editing sites for both hADAR1 and hADAR2 in S. pombe were in coding sequences (CDS), with more than 60% of them resulting in amino acid changes in protein products. This study revealed the extensive differences in substrate selectivity between the two active human ADARS, i.e., ADAR1 and ADAR2, and provided novel insight when utilizing the two different enzymes for in vivo treatment of human genetic diseases using the RNA editing approach. [ABSTRACT FROM AUTHOR]

BackgroundViral hepatitis is a widespread and serious infectious disease, and most patients with liver cirrhosis and hepatocellular carcinoma are prone to viral infections. T cell immunoglobulin-and mucin-domain-containing molecule-3 (Tim-3) is an immune checkpoint molecule that negatively regulates T cell responses, playing an extremely important role in controlling infectious diseases. However, reports about the role of serum soluble Tim-3 (sTim-3) in hepatitis virus infection are limited. Therefore, this study explored changes in sTim-3 levels in patients infected with hepatitis B virus (HBV), hepatitis C virus (HCV), and hepatitis E virus (HEV).MethodsThis study applied high-sensitivity time-resolved fluorescence immunoassay for the detection of sTim-3 levels. A total of 205 cases of viral hepatitis infection (68 cases of HBV infection, 60 cases of HCV infection, and 77 cases of HEV virus infection) and 88 healthy controls were quantitatively determined. The changes in serum sTim-3 level and its clinical value in hepatitis virus infection were analyzed.ResultsPatients with HBV infection (14.00, 10.78–20.45 ng/mL), HCV infection (15.99, 11.83–27.00 ng/mL), or HEV infection (19.09, 10.85–33.93 ng/mL) had significantly higher sTim-3 levels than that in the healthy control group (7.69, 6.14–10.22 ng/mL, P < 0.0001). Patients with hepatitis and fibrosis infected with HBV (22.76, 12.82–37.53 ng/mL), HCV (33.06, 16.36–39.30 ng/mL), and HEV (28.90, 17.95–35.94 ng/mL) had significantly higher sTim-3 levels than patients with hepatitis without fibrosis (13.29, 7.75–17.28; 13.86, 11.48–18.64; 14.77, 9.79–29.79 ng/mL; P < 0.05).ConclusionsTim-3 level was elevated in patients infected with HBV, HCV, or HEV and gradually increased in patients with either hepatitis or hepatitis with hepatic fibrosis. It has a certain role in the evaluation of the course of a disease after hepatitis virus infection.