A second-generation M1-polarized CAR macrophage with antitumor efficacy.

Chimeric antigen receptor (CAR) T cell therapies have successfully treated hematological malignancies. Macrophages have also gained attention as an immunotherapy owing to their immunomodulatory capacity and ability to infiltrate solid tumors and phagocytize tumor cells. The first-generation CD3ζ-based CAR-macrophages could phagocytose tumor cells in an antigen-dependent manner. Here we engineered induced pluripotent stem cell-derived macrophages (iMACs) with toll-like receptor 4 intracellular toll/IL-1R (TIR) domain-containing CARs resulting in a markedly enhanced antitumor effect over first-generation CAR-macrophages. Moreover, the design of a tandem CD3ζ-TIR dual signaling CAR endows iMACs with both target engulfment capacity and antigen-dependent M1 polarization and M2 resistance in a nuclear factor kappa B (NF-κB)-dependent manner, as well as the capacity to modulate the tumor microenvironment. We also outline a mechanism of tumor cell elimination by CAR-induced efferocytosis against tumor cell apoptotic bodies. Taken together, we provide a second-generation CAR-iMAC with an ability for orthogonal phagocytosis and polarization and superior antitumor functions in treating solid tumors relative to first-generation CAR-macrophages.

Debiased personalized gene coexpression networks for population-scale scRNA-seq data.

Population-scale single-cell RNA-seq (scRNA-seq) data sets create unique opportunities for quantifying expression variation across individuals at the gene coexpression network level. Estimation of coexpression networks is well established for bulk RNA-seq; however, single-cell measurements pose novel challenges owing to technical limitations and noise levels of this technology. Gene-gene correlation estimates from scRNA-seq tend to be severely biased toward zero for genes with low and sparse expression. Here, we present Dozer to debias gene-gene correlation estimates from scRNA-seq data sets and accurately quantify network-level variation across individuals. Dozer corrects correlation estimates in the general Poisson measurement model and provides a metric to quantify genes measured with high noise. Computational experiments establish that Dozer estimates are robust to mean expression levels of the genes and the sequencing depths of the data sets. Compared with alternatives, Dozer results in fewer false-positive edges in the coexpression networks, yields more accurate estimates of network centrality measures and modules, and improves the faithfulness of networks estimated from separate batches of the data sets. We showcase unique analyses enabled by Dozer in two population-scale scRNA-seq applications. Coexpression network-based centrality analysis of multiple differentiating human induced pluripotent stem cell (iPSC) lines yields biologically coherent gene groups that are associated with iPSC differentiation efficiency. Application with population-scale scRNA-seq of oligodendrocytes from postmortem human tissues of Alzheimer's disease and controls uniquely reveals coexpression modules of innate immune response with distinct coexpression levels between the diagnoses. Dozer represents an important advance in estimating personalized coexpression networks from scRNA-seq data.

The functional evolution of architecturally different plant geranyl diphosphate synthases from geranylgeranyl diphosphate synthase.

Terpenoids constitute the largest class of plant primary and secondary metabolites with a broad range of biological and ecological functions. They are synthesized from isopentenyl diphosphate and dimethylallyl diphosphate, which in plastids are condensed by geranylgeranyl diphosphate synthases (GGPPSs) to produce GGPP (C20) for diterpene biosynthesis and by geranyl diphosphate synthases (GPPSs) to form GPP (C10) for monoterpene production. Depending on the plant species, unlike homomeric GGPPSs, GPPSs exist as homo- and heteromers, the latter of which contain catalytically inactive GGPPS-homologous small subunits (SSUs) that can interact with GGPPSs. By combining phylogenetic analysis with functional characterization of GGPPS homologs from a wide range of photosynthetic organisms, we investigated how different GPPS architectures have evolved within the GGPPS protein family. Our results reveal that GGPPS gene family expansion and functional divergence began early in nonvascular plants, and that independent parallel evolutionary processes gave rise to homomeric and heteromeric GPPSs. By site-directed mutagenesis and molecular dynamics simulations, we also discovered that Leu-Val/Val-Ala pairs of amino acid residues were pivotal in the functional divergence of homomeric GPPSs and GGPPSs. Overall, our study elucidated an evolutionary path for the formation of GPPSs with different architectures from GGPPSs and uncovered the molecular mechanisms involved in this differentiation.

Diamond controls epithelial polarity through the dynactin-dynein complex.

Epithelial polarity is critical for proper functions of epithelial tissues, tumorigenesis, and metastasis. The evolutionarily conserved transmembrane protein Crumbs (Crb) is a key regulator of epithelial polarity. Both Crb protein and its transcripts are apically localized in epithelial cells. However, it remains not fully understood how they are targeted to the apical domain. Here, using Drosophila ovarian follicular epithelia as a model, we show that epithelial polarity is lost and Crb protein is absent in the apical domain in follicular cells (FCs) in the absence of Diamond (Dind). Interestingly, Dind is found to associate with different components of the dynactin-dynein complex through co-IP-MS analysis. Dind stabilizes dynactin and depletion of dynactin results in almost identical defects as those observed in dind-defective FCs. Finally, both Dind and dynactin are also required for the apical localization of crb transcripts in FCs. Thus our data illustrate that Dind functions through dynactin/dynein-mediated transport of both Crb protein and its transcripts to the apical domain to control epithelial apico-basal (A/B) polarity.

Regulatory roles of dopamine D2 receptor in milk protein production and apoptosis in mammary epithelial cells.

Dopamine D2 receptors (D2Rs) play crucial roles in regulating diverse physiological functions of the central nervous system and peripheral organs. D2Rs are also expressed in mammary glands. However, which cell types express D2Rs and whether they are involved in milk production remains unclear. The present findings revealed that D2Rs are expressed in the apical regions of the lateral membranes of mammary epithelial cells (MECs) in lactating mice. We also investigated the effects of the D2R agonist bromocriptine and/or antagonist domperidone on intracellular cAMP levels, milk protein production, and apoptosis in a lactation culture model of MECs that produce major milk components like lactating MECs in vivo. We found that bromocriptine decreased intracellular cAMP levels, whereas domperidone dose-dependently neutralized this effect. Bromocriptine also inhibited casein and lactoferrin production and suppressed activities of STAT5 and glucocorticoid receptors (GRs). Domperidone neutralized the inhibition of casein production as well as STAT5 and GR inactivation induced by bromocriptine. Furthermore, D2R activation by bromocriptine induced apoptosis and inactivated ERK, a signaling molecule responsible for promoting cell proliferation and survival. Domperidone attenuated ERK inactivation and apoptosis induced by bromocriptine. These findings suggest that D2Rs play regulatory roles in milk protein production and apoptosis in MECs.

SUMO-Targeted DNA Translocase Rrp2 Protects the Genome from Top2-Induced DNA Damage.

The action of DNA topoisomerase II (Top2) creates transient DNA breaks that are normally concealed inside Top2-DNA covalent complexes. Top2 poisons, including ubiquitously present natural compounds and clinically used anti-cancer drugs, trap Top2-DNA complexes. Here, we show that cells actively prevent Top2 degradation to avoid the exposure of concealed DNA breaks. A genome-wide screen revealed that fission yeast cells lacking Rrp2, an Snf2-family DNA translocase, are strongly sensitive to Top2 poisons. Loss of Rrp2 enhances SUMOylation-dependent ubiquitination and degradation of Top2, which in turn increases DNA damage at sites where Top2-DNA complexes are trapped. Rrp2 possesses SUMO-binding ability and prevents excessive Top2 degradation by competing against the SUMO-targeted ubiquitin ligase (STUbL) for SUMO chain binding and by displacing SUMOylated Top2 from DNA. The budding yeast homolog of Rrp2, Uls1, plays a similar role, indicating that this genome protection mechanism is widely employed, a finding with implications for cancer treatment.

The Yun/Prohibitin complex regulates adult Drosophila intestinal stem cell proliferation through the transcription factor E2F1.

Stem cells constantly divide and differentiate to maintain adult tissue homeostasis, and uncontrolled stem cell proliferation leads to severe diseases such as cancer. How stem cell proliferation is precisely controlled remains poorly understood. Here, from an RNA interference (RNAi) screen in adult Drosophila intestinal stem cells (ISCs), we identify a factor, Yun, required for proliferation of normal and transformed ISCs. Yun is mainly expressed in progenitors; our genetic and biochemical evidence suggest that it acts as a scaffold to stabilize the Prohibitin (PHB) complex previously implicated in various cellular and developmental processes and diseases. We demonstrate that the Yun/PHB complex is regulated by and acts downstream of EGFR/MAPK signaling. Importantly, the Yun/PHB complex interacts with and positively affects the levels of the transcription factor E2F1 to regulate ISC proliferation. In addition, we find that the role of the PHB complex in cell proliferation is evolutionarily conserved. Thus, our study uncovers a Yun/PHB-E2F1 regulatory axis in stem cell proliferation.

Test-Time Training for Deep MS/MS Spectrum Prediction Improves Peptide Identification.

In bottom-up proteomics, peptide-spectrum matching is critical for peptide and protein identification. Recently, deep learning models have been used to predict tandem mass spectra of peptides, enabling the calculation of similarity scores between the predicted and experimental spectra for peptide-spectrum matching. These models follow the supervised learning paradigm, which trains a general model using paired peptides and spectra from standard data sets and directly employs the model on experimental data. However, this approach can lead to inaccurate predictions due to differences between the training data and the experimental data, such as sample types, enzyme specificity, and instrument calibration. To tackle this problem, we developed a test-time training paradigm that adapts the pretrained model to generate experimental data-specific models, namely, PepT3. PepT3 yields a 10-40% increase in peptide identification depending on the variability in training and experimental data. Intriguingly, when applied to a patient-derived immunopeptidomic sample, PepT3 increases the identification of tumor-specific immunopeptide candidates by 60%. Two-thirds of the newly identified candidates are predicted to bind to the patient's human leukocyte antigen isoforms. To facilitate access of the model and all the results, we have archived all the intermediate files in Zenodo.org with identifier 8231084.

Long non-coding RNA KB-1460A1.5 promotes ferroptosis by inhibiting mTOR/SREBP-1/SCD1-mediated polyunsaturated fatty acid desaturation in glioma.

Ferroptosis is a new form of regulated cell death caused by the iron-dependent peroxidation of phospholipids and is related to cell metabolism, redox homeostasis and various signalling pathways related to cancer. The long non-coding RNA (lncRNA) KB-1460A1.5 acts as a tumour suppressor gene to regulate tumour growth in gliomas, but its molecular network regulatory mechanism is still unclear. In this study, we found that KB-1460A1.5 can induce ferroptosis in glioma and enhance sensitivity to RSL3, a ferroptosis inducer. Tandem mass tag proteomics and nontargeted metabolomics suggest that KB-1460A1.5 affects polyunsaturated fatty acid metabolic processes. Gas chromatography-mass spectrometry-based medium- and long-chain fatty acid-targeted metabolomics confirmed that upregulation of KB-1460A1.5 decreased the levels of monounsaturated fatty acids, oleic acid (OA) and palmitoleic acid (PO) in glioma cells. The addition of OA and PO restored KB-1460A1.5-induced cellular ferroptosis. Molecularly, KB-1460A1.5 inhibited the mammalian target of rapamycin signalling pathway to suppress the expression of downstream sterol regulatory element-binding protein 1 (SREBP-1), thereby attenuating the stearoyl-CoA desaturase-1 (SCD1)-mediated desaturation of polyunsaturated fatty acids. Finally, an animal model of subcutaneous glioma confirmed that KB-1460A1.5 could inhibit tumour progression, SREBP-1/SCD1 expression and ferroptosis. In conclusion, increasing the expression level of KB-1460A1.5 in glioma can promote the induction of oxidative stress and ferroptosis in cancer cells through SREBP-1/SCD1-mediated adipogenesis, demonstrating therapeutic potential in preclinical models.

The combination of methionine adenosyltransferase 2A inhibitor and methyltransferase like 3 inhibitor promotes apoptosis of non-small cell lung cancer cells and produces synergistic anti-tumor activity.

Methionine adenosyltransferase 2 A (MAT2A) mediates the synthesis of methyl donor S-Adenosylmethionine (SAM), providing raw materials for methylation reactions in cells. MAT2A inhibitors are currently used for the treatment of tumors with methylthioadenosine phosphorylase (MTAP) deficiency in clinical research. Methyltransferase like 3 (METTL3) catalyzes N6-methyladenosine (m6A) modification of mRNA in mammalian cells using SAM as the substrate which has been shown to affect the tumorigenesis of non-small cell lung cancer (NSCLC) from multiple perspectives. MAT2A-induced SAM depletion may have the potential to inhibit the methyl transfer function of METTL3. Therefore, in order to expand the applicability of inhibitors, improve anti-tumor effects and reduce toxicity, the combinational effect of MAT2A inhibitor AG-270 and METTL3 inhibitor STM2457 was evaluated in NSCLC. The results showed that this combination induced cell apoptosis rather than cell cycle arrest, which was non-tissue-specific and was independent of MTAP expression status, resulting in a significant synergistic anti-tumor effect. We further elucidated that the combination-induced enhanced apoptosis was associated with the decreased m6A level, leading to downregulation of PI3K/AKT protein, ultimately activating the apoptosis-related proteins. Unexpectedly, although combination therapy resulted in metabolic recombination, no significant change in methionine metabolic metabolites was found. More importantly, the combination also exerted synergistic effects in vivo. In summary, the combination of MAT2A inhibitor and METTL3 inhibitor showed synergistic effects both in vivo and in vitro, which laid a theoretical foundation for expanding the clinical application research of the two types of drugs.

2D Ultrathin Titanium Nitride Nanosheets as Separator Coatings for Li-S Batteries.

Transition metal nitrides (TMNs) are affirmed to be an appealing candidate for boosting the performance of lithium-sulfur (Li-S) batteries due to their excellent conductivity, strong interaction with sulfur species, and the effective catalytic ability for conversion of polysulfides. However, the traditional bulk TMNs are difficult to achieve large active surface area and fast transport channels for electrons/ions simultaneously. Here, a 2D ultrathin geometry of titanium nitride (TiN) is realized by a facile topochemical conversion strategy, which can not only serve as an interconnected conductive platform but also expose abundant catalytic active sites. The ultrathin TiN nanosheets are coated on a commercial separator, serving as a multifunctional interlayer in Li-S batteries for hindering the polysulfide shuttle effect by strong capture and fast conversion of polysulfides, achieving a high initial capacity of 1357 mAh g-1 at 0.1 C and demonstrating a low capacity decay of only 0.046% per cycle over 1000 cycles at 1 C.

Deciphering the pivotal role of people with high-frequency occupational animal exposure in antibiotic resistance transmission between humans and animals.

BACKGROUND: The spread of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) among humans and food-producing animals has been widely reported. However, the transmission routes and associated risk factors remain incompletely understood. METHODS: Here, we used commensal Escherichia coli bacteria strains from faeces of pigs and local citizens [HEG: high exposure group (pig breeders, butchers or restaurant chefs) and LEG: low exposure group (other occupations)] to explore the dynamics of ARB and ARG transmission between animals and humans. RESULTS: Most ARGs (96%) present in pigs were shared with humans. Carriage rates of the shared ARGs suggest two transmission patterns among pigs, the HEG and LEG: one pattern was highest in pigs, gradually decreasing in the HEG and LEG (e.g. floR and cmlA1); the other pattern was increasing from pigs to the HEG but then decreasing in the LEG (e.g. mcr-1.1). Carriage rates of the HEG were higher than in the LEG in both patterns, implicating the HEG as a crucial medium in transmitting ARB and ARGs between food-producing animals and humans. Moreover, frequent inter/intragroup transmission via strains, plasmids and/or mobile elements was evident. Carriage of mcr-1.1 on human-gut-prevalent plasmids possibly promoted its enrichment in the HEG. CONCLUSIONS: The HEG is a crucial factor in transmitting ARB and ARGs between food-producing animals and humans. Rational measures to contain the risks of occupational exposure are urgently needed to keep dissemination of antibiotic resistance in check and safeguard public health.

MuDCoD: multi-subject community detection in personalized dynamic gene networks from single-cell RNA sequencing.

MOTIVATION: With the wide availability of single-cell RNA-seq (scRNA-seq) technology, population-scale scRNA-seq datasets across multiple individuals and time points are emerging. While the initial investigations of these datasets tend to focus on standard analysis of clustering and differential expression, leveraging the power of scRNA-seq data at the personalized dynamic gene co-expression network level has the potential to unlock subject and/or time-specific network-level variation, which is critical for understanding phenotypic differences. Community detection from co-expression networks of multiple time points or conditions has been well-studied; however, none of the existing settings included networks from multiple subjects and multiple time points simultaneously. To address this, we develop Multi-subject Dynamic Community Detection (MuDCoD) for multi-subject community detection in personalized dynamic gene networks from scRNA-seq. MuDCoD builds on the spectral clustering framework and promotes information sharing among the networks of the subjects as well as networks at different time points. It clusters genes in the personalized dynamic gene networks and reveals gene communities that are variable or shared not only across time but also among subjects. RESULTS: Evaluation and benchmarking of MuDCoD against existing approaches reveal that MuDCoD effectively leverages apparent shared signals among networks of the subjects at individual time points, and performs robustly when there is no or little information sharing among the networks. Applications to population-scale scRNA-seq datasets of human-induced pluripotent stem cells during dopaminergic neuron differentiation and CD4+ T cell activation indicate that MuDCoD enables robust inference for identifying time-varying personalized gene modules. Our results illustrate how personalized dynamic community detection can aid in the exploration of subject-specific biological processes that vary across time. AVAILABILITY AND IMPLEMENTATION: MuDCoD is publicly available at https://github.com/bo1929/MuDCoD as a Python package. Implementation includes simulation and real-data experiments together with extensive documentation.

Non-neutralizing antibodies targeting the immunogenic regions of HIV-1 envelope reduce mucosal infection and virus burden in humanized mice.

Antibodies are principal immune components elicited by vaccines to induce protection from microbial pathogens. In the Thai RV144 HIV-1 vaccine trial, vaccine efficacy was 31% and the sole primary correlate of reduced risk was shown to be vigorous antibody response targeting the V1V2 region of HIV-1 envelope. Antibodies against V3 also were inversely correlated with infection risk in subsets of vaccinees. Antibodies recognizing these regions, however, do not exhibit potent neutralizing activity. Therefore, we examined the antiviral potential of poorly neutralizing monoclonal antibodies (mAbs) against immunodominant V1V2 and V3 sites by passive administration of human mAbs to humanized mice engrafted with CD34+ hematopoietic stem cells, followed by mucosal challenge with an HIV-1 infectious molecular clone expressing the envelope of a tier 2 resistant HIV-1 strain. Treatment with anti-V1V2 mAb 2158 or anti-V3 mAb 2219 did not prevent infection, but V3 mAb 2219 displayed a superior potency compared to V1V2 mAb 2158 in reducing virus burden. While these mAbs had no or weak neutralizing activity and elicited undetectable levels of antibody-dependent cellular cytotoxicity (ADCC), V3 mAb 2219 displayed a greater capacity to bind virus- and cell-associated HIV-1 envelope and to mediate antibody-dependent cellular phagocytosis (ADCP) and C1q complement binding as compared to V1V2 mAb 2158. Mutations in the Fc region of 2219 diminished these effector activities in vitro and lessened virus control in humanized mice. These results demonstrate the importance of Fc functions other than ADCC for antibodies without potent neutralizing activity.

A major gene for chilling tolerance variation in Indica rice codes for a kinase OsCTK1 that phosphorylates multiple substrates under cold.

Rice is susceptible to chilling stress. Identifying chilling tolerance genes and their mechanisms are key to improve rice performance. Here, we performed a genome-wide association study to identify regulatory genes for chilling tolerance in rice. One major gene for chilling tolerance variation in Indica rice was identified as a casein kinase gene OsCTK1. Its function and natural variation are investigated at the physiological and molecular level by its mutants and transgenic plants. Potential substrates of OsCTK1 were identified by phosphoproteomic analysis, protein-protein interaction assay, in vitro kinase assay, and mutant characterization. OsCTK1 positively regulates rice chilling tolerance. Three of its putative substrates, acidic ribosomal protein OsP3B, cyclic nucleotide-gated ion channel OsCNGC9, and dual-specific mitogen-activated protein kinase phosphatase OsMKP1, are each involved in chilling tolerance. In addition, a natural OsCTK1 chilling-tolerant (CT) variant exhibited a higher kinase activity and conferred greater chilling tolerance compared with a chilling-sensitive (CS) variant. The CT variant is more prevalent in CT accessions and is distributed more frequently in higher latitude compared with the CS variant. This study thus enables a better understanding of chilling tolerance mechanisms and provides gene variants for genetic improvement of chilling tolerance in rice.

Malignant progression of liver cancer progenitors requires lysine acetyltransferase 7-acetylated and cytoplasm-translocated G protein GαS.

BACKGROUND AND AIMS: Hepatocarcinogenesis goes through HCC progenitor cells (HcPCs) to fully established HCC, and the mechanisms driving the development of HcPCs are still largely unknown. APPROACH AND RESULTS: Proteomic analysis in nonaggregated hepatocytes and aggregates containing HcPCs from a diethylnitrosamine-induced HCC mouse model was screened using a quantitative mass spectrometry-based approach to elucidate the dysregulated proteins in HcPCs. The heterotrimeric G stimulating protein α subunit (GαS) protein level was significantly increased in liver cancer progenitor HcPCs, which promotes their response to oncogenic and proinflammatory cytokine IL-6 and drives premalignant HcPCs to fully established HCC. Mechanistically, GαS was located at the membrane inside of hepatocytes and acetylated at K28 by acetyltransferase lysine acetyltransferase 7 (KAT7) under IL-6 in HcPCs, causing the acyl protein thioesterase 1-mediated depalmitoylation of GαS and its cytoplasmic translocation, which were determined by GαS K28A mimicking deacetylation or K28Q mimicking acetylation mutant mice and hepatic Kat7 knockout mouse. Then, cytoplasmic acetylated GαS associated with signal transducer and activator of transcription 3 (STAT3) to impede its interaction with suppressor of cytokine signaling 3, thus promoting in a feedforward manner STAT3 phosphorylation and the response to IL-6 in HcPCs. Clinically, GαS, especially K28-acetylated GαS, was determined to be increased in human hepatic premalignant dysplastic nodules and positively correlated with the enhanced STAT3 phosphorylation, which were in accordance with the data obtained in mouse models. CONCLUSIONS: Malignant progression of HcPCs requires increased K28-acetylated and cytoplasm-translocated GαS, causing enhanced response to IL-6 and driving premalignant HcPCs to fully established HCC, which provides mechanistic insight and a potential target for preventing hepatocarcinogenesis.

Hydrogen sulfide attenuates atherosclerosis induced by low shear stress by sulfhydrylating endothelium NFIL3 to restrain MEST mediated endothelial mesenchymal transformation.

BACKGROUND: Endothelial-mesenchymal transition (EndMT) induced by low shear stress plays an important role in the development of atherosclerosis. However, little is known about the correlation between hydrogen sulfide (H2S), a protective gaseous mediator in atherosclerosis and the process of EndMT. METHODS: We constructed a stable low-shear-stress-induced(2 dyn/cm2) EndMT model, acombined with the pretreatment method of hydrogen sulfide slow release agent(GYY4137). The level of MEST was detected in the common carotid artery of ApoE-/- mice with local carotid artery ligation. The effect of MEST on atherosclerosis development in vivo was verified using ApoE-/- mice were given tail-vein injection of endothelial-specific overexpressed and knock-down MEST adeno-associated virus (AAV). RESULTS: These findings confirmed that MEST is up-regulated in low-shear-stress-induced EndMT and atherosclerosis. In vivo experiments showed that MEST gene overexpression significantly promoted EndMT and aggravated the development of atherosclerotic plaques and MEST gene knockdown significantly inhibited EndMT and delayed the process of atherosclerosis. In vitro, H2S inhibits the expression of MEST and EndMT induced by low shear stress and inhibits EndMT induced by MEST overexpression. Knockdown of NFIL3 inhibit the up regulation of MEST and EndMT induced by low shear stress in HUVECs. CHIP-qPCR assay and Luciferase Reporter assay confirmed that NFIL3 binds to MEST DNA, increases its transcription and H2S inhibits the binding of NFIL3 and MEST DNA, weakening NFIL3's transcriptional promotion of MEST. Mechanistically, H2S increased the sulfhydrylation level of NFIL3, an important upstream transcription factors of MEST. In part, transcription factor NFIL3 restrain its binding to MEST DNA by sulfhydration. CONCLUSIONS: H2S negatively regulate the expression of MEST by sulfhydrylation of NFIL3, thereby inhibiting low-shear-stress-induced EndMT and atherosclerosis.

Biomimetic Slippery Surface with Exclusive Liquid-Repellent and Self-Cleaning Properties for Antifouling.

The nature always offers amazing inspiration, where it is highly desirable to endow coatings on marine equipment with powerful functions. An excellent example is slippery zone of Nepenthes pitcher, which possesses novel liquid-repellent and self-cleaning performance. Therefore, this study presents an efficient fabrication method to prepare a novel coating. The coatings were fabricated by designing biomimetic textures extracted from the lunate bodies of slippery zone on polydimethylsiloxane (PDMS) and then grafting Dictyophora indusiata polysaccharide (DIP) modifier. The as-prepared slippery coatings exhibited outstanding antifouling properties against kinds of daily life pollutants such as Chlorella and coffee. This synergistic strategy was proposed combined with environmentally friendly modifier grafting and heterogeneous microstructure on the surface to broaden new probabilities for manufacturing slippery coatings with incredible protective functionality.

Radiomics of pericoronary adipose tissue on computed tomography angiography predicts coronary heart disease in patients with type 2 diabetes mellitus.

BACKGROUND: Diabetes is a common chronic metabolic disease. The progression of the disease promotes vascular inflammation and the formation of atherosclerosis, leading to cardiovascular disease. The coronary artery perivascular adipose tissue attenuation index based on CCTA is a new noninvasive imaging biomarker that reflects the spatial changes in perivascular adipose tissue attenuation in CCTA images and the inflammation around the coronary arteries. In this study, a radiomics approach is proposed to extract a large number of image features from CCTA in a high-throughput manner and combined with clinical diagnostic data to explore the predictive ability of vascular perivascular adipose imaging data based on CCTA for coronary heart disease in diabetic patients. METHODS: R language was used for statistical analysis to screen the variables with significant differences. A presegmentation model was used for CCTA vessel segmentation, and the pericoronary adipose region was screened out. PyRadiomics was used to calculate the radiomics features of pericoronary adipose tissue, and SVM, DT and RF were used to model and analyze the clinical data and radiomics data. Model performance was evaluated using indicators such as PPV, FPR, AAC, and ROC. RESULTS: The results indicate that there are significant differences in age, blood pressure, and some biochemical indicators between diabetes patients with and without coronary heart disease. Among 1037 calculated radiomic parameters, 18.3% showed significant differences in imaging omics features. Three modeling methods were used to analyze different combinations of clinical information, internal vascular radiomics information and pericoronary vascular fat radiomics information. The results showed that the dataset of full data had the highest ACC values under different machine learning models. The support vector machine method showed the best specificity, sensitivity, and accuracy for this dataset. CONCLUSIONS: In this study, the clinical data and pericoronary radiomics data of CCTA were fused to predict the occurrence of coronary heart disease in diabetic patients. This provides information for the early detection of coronary heart disease in patients with diabetes and allows for timely intervention and treatment.