Radiomic profiling for insular diffuse glioma stratification with distinct biologic pathway activities.

Current literature emphasizes surgical complexities and customized resection for managing insular gliomas; however, radiogenomic investigations into prognostic radiomic traits remain limited. We aimed to develop and validate a radiomic model using multiparametric magnetic resonance imaging (MRI) for prognostic prediction and to reveal the underlying biological mechanisms. Radiomic features from preoperative MRI were utilized to develop and validate a radiomic risk signature (RRS) for insular gliomas, validated through paired MRI and RNA-seq data (N = 39), to identify core pathways underlying the RRS and individual prognostic radiomic features. An 18-feature-based RRS was established for overall survival (OS) prediction. Gene set enrichment analysis (GSEA) and weighted gene coexpression network analysis (WGCNA) were used to identify intersectional pathways. In total, 364 patients with insular gliomas (training set, N = 295; validation set, N = 69) were enrolled. RRS was significantly associated with insular glioma OS (log-rank p = 0.00058; HR = 3.595, 95% CI:1.636-7.898) in the validation set. The radiomic-pathological-clinical model (R-P-CM) displayed enhanced reliability and accuracy in prognostic prediction. The radiogenomic analysis revealed 322 intersectional pathways through GSEA and WGCNA fusion; 13 prognostic radiomic features were significantly correlated with these intersectional pathways. The RRS demonstrated independent predictive value for insular glioma prognosis compared with established clinical and pathological profiles. The biological basis for prognostic radiomic indicators includes immune, proliferative, migratory, metabolic, and cellular biological function-related pathways.

Carbon Micro/Nano Machining toward Miniaturized Device: Structural Engineering, Large-Scale Fabrication, and Performance Optimization.

With the rapid development of micro/nano machining, there is an elevated demand for high-performance microdevices with high reliability and low cost. Due to their outstanding electrochemical, optical, electrical, and mechanical performance, carbon materials are extensively utilized in constructing microdevices for energy storage, sensing, and optoelectronics. Carbon micro/nano machining is fundamental in carbon-based intelligent microelectronics, multifunctional integrated microsystems, high-reliability portable/wearable consumer electronics, and portable medical diagnostic systems. Despite numerous reviews on carbon materials, a comprehensive overview is lacking that systematically encapsulates the development of high-performance microdevices based on carbon micro/nano structures, from structural design to manufacturing strategies and specific applications. This review focuses on the latest progress in carbon micro/nano machining toward miniaturized device, including structural engineering, large-scale fabrication, and performance optimization. Especially, the review targets an in-depth evaluation of carbon-based micro energy storage devices, microsensors, microactuators, miniaturized photoresponsive and electromagnetic interference shielding devices. Moreover, it highlights the challenges and opportunities in the large-scale manufacturing of carbon-based microdevices, aiming to spark further exciting research directions and application prospectives.

Icing and Adhesion Behaviors on Surfaces with Varied Lattice Constants.

Investigating droplet wetting and icing behavior is crucial for comprehending the principles of surface icing and the design of anti-icing surfaces. In this study, we present the evidence from molecular dynamics (MD) simulations that reveal a hitherto unreported behavior of droplet wetting and icing adhesion on surfaces with lattice constants from 2.7 to 4.5 Å. Here, we observe that the contact angles (CA) of droplets on a face-centered cubic (FCC) lattice surface consistently correlate positively with the lattice constant. Further examination of droplet behavior on an idealized crystal surface reveals that hydrophilic surfaces (e.g., CA = 85°) inhibit freezing more effectively than hydrophobic surfaces (e.g., CA = 97°). This finding contradicts the conventional explanation that hydrophobic surfaces reduce heterogeneous nucleation, thereby delaying icing. This study introduces a mechanistic explanation for the promotion of water icing by hydrophobic surfaces and offers a novel design concept for the development of anti-ice surfaces in future applications.

Telluride-Based Materials: A Promising Route for High Performance Supercapacitors.

As supercapacitor (SC) technology continues to evolve, there is a growing need for electrode materials with high energy/power densities and cycling stability. However, research and development of electrode materials with such characteristics is essential for commercialization the SC. To meet this demand, the development of superior electrode materials has become an increasingly critical step. The electrochemical performance of SCs is greatly influenced by various factors such as the reaction mechanism, crystal structure, and kinetics of electron/ion transfer in the electrodes, which have been challenging to address using previously investigated electrode materials like carbon and metal oxides/sulfides. Recently, tellurium and telluride-based materials have garnered increasing interest in energy storage technology owing to their high electronic conductivity, favorable crystal structure, and excellent volumetric capacity. This review provides a comprehensive understanding of the fundamental properties and energy storage performance of tellurium- and Te-based materials by introducing their physicochemical properties. First, we elaborate on the significance of tellurides. Next, the charge storage mechanism of functional telluride materials and important synthesis strategies are summarized. Then, research advancements in metal and carbon-based telluride materials, as well as the effectiveness of tellurides for SCs, were analyzed by emphasizing their essential properties and extensive advantages. Finally, the remaining challenges and prospects for improving the telluride-based supercapacitive performance are outlined.

Non-Invasive Multi-Gas Detection Enabled by Cu-CuO/PEDOT Microneedle Sensor.

Metal-oxide-based gas sensors are extensively utilized across various domains due to their cost-effectiveness, facile fabrication, and compatibility with microelectronic technologies. The copper (Cu)-based multifunctional polymer-enhanced sensor (CuMPES) represents a notably tailored design for non-invasive environmental monitoring, particularly for detecting diverse gases with a low concentration. In this investigation, the Cu-CuO/PEDOT nanocomposite was synthesized via a straightforward chemical oxidation and vapor-phase polymerization. Comprehensive characterizations employing X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), X-ray diffraction (XRD), and micro Raman elucidated the composition, morphology, and crystal structure of this nanocomposite. Gas-sensing assessments of this CuMPES based on Cu-CuO/PEDOT revealed that the response current of the microneedle-type CuMPES surpassed that of the pure Cu microsensor by nearly threefold. The electrical conductivity and surface reactivity are enhanced by poly (3,4-ethylenedioxythiophene) (PEDOT) polymerized on the CuO-coated surface, resulting in an enhanced sensor performance with an ultra-fast response/recovery of 0.3/0.5 s.

Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas.

BACKGROUND: We aimed to develop machine learning models for prediction of molecular subgroups (low-risk group and intermediate/high-risk group) and molecular marker (KIAA1549-BRAF fusion) of pediatric low-grade gliomas (PLGGs) based on radiomic features extracted from multiparametric MRI. METHODS: 61 patients with PLGGs were included in this retrospective study, which were divided into a training set and an internal validation set at a ratio of 2:1 based on the molecular subgroups or the molecular marker. The patients were classified into low-risk and intermediate/high-risk groups, BRAF fusion positive and negative groups, respectively. We extracted 5929 radiomic features from multiparametric MRI. Thereafter, we removed redundant features, trained random forest models on the training set for predicting the molecular subgroups or the molecular marker, and validated their performance on the internal validation set. The performance of the prediction model was verified by 3-fold cross-validation. RESULTS: We constructed the classification model differentiating low-risk PLGGs from intermediate/high-risk PLGGs using 4 relevant features, with an AUC of 0.833 and an accuracy of 76.2% in the internal validation set. In the prediction model for predicting KIAA1549-BRAF fusion using 4 relevant features, an AUC of 0.818 and an accuracy of 81.0% were achieved in the internal validation set. CONCLUSIONS: The current study demonstrates that MRI radiomics is able to predict molecular subgroups of PLGGs and KIAA1549-BRAF fusion with satisfying sensitivity. TRIAL REGISTRATION: This study was retrospectively registered at clinicaltrials.gov (NCT04217018).

Improving Noninvasive Classification of Molecular Subtypes of Adult Gliomas With Diffusion-Weighted MR Imaging: An Externally Validated Machine Learning Algorithm.

BACKGROUND: Genetic testing for molecular markers of gliomas sometimes is unavailable because of time-consuming and expensive, even limited tumor specimens or nonsurgery cases. PURPOSE: To train a three-class radiomic model classifying three molecular subtypes including isocitrate dehydrogenase (IDH) mutations and 1p/19q-noncodeleted (IDHmut-noncodel), IDH wild-type (IDHwt), IDH-mutant and 1p/19q-codeleted (IDHmut-codel) of adult gliomas and investigate whether radiomic features from diffusion-weighted imaging (DWI) could bring additive value. STUDY TYPE: Retrospective. POPULATION: A total of 755 patients including 111 IDHmut-noncodel, 571 IDHwt, and 73 IDHmut-codel cases were divided into training (n = 480) and internal validation set (n = 275); 139 patients including 21 IDHmut-noncodel, 104 IDHwt, and 14 IDHmut-codel cases were utilized as external validation set. FIELD STRENGTH/SEQUENCE: A 1.5 T or 3.0 T/multiparametric MRI, including T1-weighted (T1), T1-weighted gadolinium contrast-enhanced (T1c), T2-weighted (T2), fluid attenuated inversion recovery (FLAIR), and DWI. ASSESSMENT: The performance of multiparametric radiomic model (random-forest model) using 22 selected features from T1, T2, FLAIR, T1c images and apparent diffusion coefficient (ADC) maps, and conventional radiomic model using 20 selected features from T1, T2, FLAIR, and T1c images was assessed in internal and external validation sets by comparing probability values and actual incidence. STATISTICAL TESTS: Mann-Whitney U test, Chi-Squared test, Wilcoxon test, receiver operating curve (ROC), and area under the curve (AUC); DeLong analysis. P < 0.05 was statistically significant. RESULTS: The multiparametric radiomic model achieved AUC values for IDHmut-noncodel, IDHwt, and IDHmut-codel of 0.8181, 0.8524, and 0.8502 in internal validation set and 0.7571, 0.7779, and 0.7491 in external validation set, respectively. Multiparametric radiomic model showed significantly better diagnostic performance after DeLong analysis, especially in classifying IDHwt and IDHmut-noncodel subtypes. DATA CONCLUSION: Radiomic features from DWI could bring additive value and improve the performance of conventional MRI-based radiomic model for classifying the molecular subtypes especially IDHmut-noncodel and IDHwt of adult gliomas. TECHNICAL EFFICACY: Stage 2.

The Detection of Yr Genes in Xinjiang Wheat Cultivars Using Different Molecular Markers.

Wheat stripe rust is a fungal disease caused by Puccinia striiformis f. sp. Tritici (Pst). It significantly impacts wheat yields in Xinjiang, China. Breeding and promoting disease-resistant cultivars carrying disease-resistance genes remains the most cost-effective strategy with which to control the disease. In this study, 17 molecular markers were used to identify Yr5, Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr41, Yr44, and Yr50 in 82 wheat cultivars from Xinjiang. According to the differences in SNP loci, the KASP markers for Yr30, Yr52, Yr78, Yr80, and Yr81 were designed and detected in the same set of 82 wheat cultivars. The results showed that there was a diverse distribution of Yr genes across all wheat cultivars in Xinjiang, and the detection rates of Yr5, Yr15, Yr17, Yr26, Yr41, and Yr50 were the highest, ranging from 74.39% to 98.78%. In addition, Yr5 and Yr15 were prevalent in spring wheat cultivars, with detection rates of 100% and 97.56%, respectively. A substantial 85.37% of wheat cultivars carried at least six or more different combinations of Yr genes. The cultivar Xindong No.15 exhibited the remarkable presence of 11 targeted Yr genes. The pedigree analysis results showed that 33.33% of Xinjiang wheat cultivars shared similar parentage, potentially leading to a loss of resistance against Pst. The results clarified the Yr gene distribution of the Xinjiang wheat cultivars and screened out varieties with a high resistance against Pst.

Circ_LPAR3 promotes the progression of oral squamous cell carcinoma (OSCC).

BACKGROUND: circ_LPAR3 is an oncogene in esophageal squamous cell carcinoma. However, its role in oral squamous cell carcinoma (OSCC) is unknown. PURPOSE: To reveal the functions of circ_LPAR3 in OSCC. METHODS: Online bioinformatic analysis was performed to disclose the differential expression of circ_LPAR3, VEGFC, AKT1 in OSCC and also the target predictions of miR-513b-5p. Transfection was applied in OSCC cells. RT-qPCR was used to detect the RNA expression and western blot to measure the proteins, VEGFC and phosphor-AKT1 (ser473, p-AKT1). CCK8 kit was used for viability detection and Flow cytometry for apoptosis evaluation. RNA pull-down and luciferase reporter methods were used to validate the binding sites to miR-513b-5p on circ_LPAR3, VEGFC and AKT1. OSCC mice models were established to further unveil the functions of circ_LPAR3 in OSCC in vivo. H&E staining and immunohistochemistry (CD34, VEGFC and p-AKT1) were further applied to analyze the pathological changes in association with circ_LPAR3 downregulation. RESULTS: circ_LPAR3 was upregulated in OSCC. Its knockdown in cells could decrease cell survival and mobility and in mice model, could inhibit the tumor growth and angiogenesis. Circ_LPAR3 promoted VEGFC and AKT1 activity by sponging miR-513b-5p in OSCC cells. CONCLUSION: Knockdown of circ_LPAR3 could inhibit the OSCC progression by sponging miR-513b-5p and activating VEGFC and AKT1.

Facile preparation of a MXene-graphene oxide membrane and its voltage-gated ion transport behavior.

Two-dimensional MXenes have become a crucial topic in the field of ion transportation owing to their excellent electrochemical performance. Herein, a strategy for preparing a layered MXene-graphene oxide (GO) membrane via vacuum filtration is proposed, which endows the delaminated two-dimensional MXene-GO membrane (MGOm) with excellent electrical conductivity and chemical stability, achieving an excellent voltage-gated ion transport behavior. Owing to the presence of charges or dipoles within the membrane's channel, the movement of electrons or dipoles under the influence of membrane potential is possible. By varying the transmembrane potential, the transition between the closed and open states of the voltage-gated ion channel can be adjusted. When a negative potential is applied at osmotic pressure, the force between the charged MGOm sheet and the cation (K+) is enhanced, promoting ion permeation. Conversely, the application of positive potential attenuates electrostatic attraction, resulting in a decrease in ion permeability. In addition, the effects of MXene and GO with different modulation ratios on the voltage-gated ion transport have shown that when the modulation ratio of MXene : GO is 7 : 3, the optimal ion permeation rate is achieved. In conclusion, the conductive film with voltage-gated nanochannels is a promising alternative for ion transportation, opening up new avenues for the further exploration of MXene materials in energy storage devices.

An Improved Synthesis Phase Unwrapping Method Based on Three-Frequency Heterodyne.

An improved three-frequency heterodyne synthesis phase unwrapping method is proposed to improve the measurement accuracy through phase difference and phase sum operations. This method can reduce the effect of noise and increase the equivalent phase frequency. According to the distribution found in the phase difference calculation process, the Otsu segmentation is introduced to judge the phase threshold. The equivalent frequency obtained from the phase sum is more than those of all projected fringe patterns. In addition, the appropriate period combinations are also studied. The simulations and related experiments demonstrate the feasibility of the proposed method and the ability to improve the accuracy of the measurement results further.

Stepping Further from Coupling Tools: Development of Functional Polymers via the Biginelli Reaction.

Multicomponent reactions (MCRs) have been used to prepare polymers with appealing functions. The Biginelli reaction, one of the oldest and most famous MCRs, has sparked new scientific discoveries in polymer chemistry since 2013. Recent years have seen the Biginelli reaction stepping further from simple coupling tools; for example, the functions of the Biginelli product 3,4-dihydropyrimidin-2(1H)-(thi)ones (DHPM(T)) have been gradually exploited to develop new functional polymers. In this mini-review, we mainly summarize the recent progress of using the Biginelli reaction to identify polymers for biomedical applications. These polymers have been documented as antioxidants, anticancer agents, and bio-imaging probes. Moreover, we also provide a brief introduction to some emerging applications of the Biginelli reaction in materials and polymer science. Finally, we present our perspectives for the further development of the Biginelli reaction in polymer chemistry.

Schisandrin B-mediated TH17 cell differentiation attenuates bowel inflammation.

Schisandrin B (Sch B) is the major active constituent of the traditional Chinese medicine Schisandra chinensis and has anti-inflammatory activity, but the target of Sch B remains unclear. T helper 17 (TH17) cells have been involved in the pathogenesis of many autoimmune and inflammatory diseases. Here, we showed that Sch B could decrease IL-17A production of CD4+ T cells by targeting STAT3 in vitro. Importantly, Sch B has therapeutic effects on DSS-induced acute and chronic colitis, CD4+CD45RBhigh T cell-induced colitis. Furthermore, we identified TH17 cells as the direct target of Sch B for mediating its anti-inflammatory activity. Sch B could serve as a lead for developing new therapeutics against TH17 cells or IL-17A cytokine-driven diseases.

Nootkatone mitigates periodontal inflammation and reduces alveolar bone loss via Nrf2/HO-1 and NF-κB pathways in rat model of periodontitis.

INTRODUCTION: Periodontitis (PD) is a chronic inflammatory disease leading to alveolar bone loss. This study investigates the effect of nootkatone and regulatory mechanism in reducing periodontal inflammation and alveolar bone loss in a rat model. MATERIAL AND METHODS: Twenty male Sprague-Dawley rats were divided into control, periodontitis, and nootkatone-treated groups (45 or 90 mg/kg). Ligature induction method was adopted to establish the PD model. After 21 days, rats received daily gavage of either saline or nootkatone for 10 days. Alveolar bone loss was assessed using micro-CT. Histological analyses included hematoxylin and eosin (H&E), tartrate-resistant acid phosphatase (TRAP), and Masson's trichrome stainings. Immunohistochemistry for heme oxygenase 1 (HO-1) and nuclear factor erythroid-2 related factor 2 (Nrf2) were performed in periodontal tissues. Content of inflammatory cytokines IL-1ß, IL-6, and TNF-α in gingival tissues around ligature were assessed using ELISA kits. Malondialdehyde (MDA) level and superoxide dismutase (SOD) activity were analyzed and Western blot for NF-κB expression in gingival tissues were performed. RESULTS: Nootkatone significantly reduced the distance from cementoenamel junction to alveolar bone crest (CEJ-ABC), enhanced bone mineral density (BMD), bone volume (BV), and BV/total volume (TV) ratio in ligature-induced rats. Higher dose of nootkatone (90 mg/kg) did not show more significant therapeutic effect than lower dose (45 mg/kg). Histological staining showed decreased osteoclasts' number and improved bone architecture in the nootkatone group. Content of IL-1ß, IL-6, and TNF-α and inflammatory cell infiltration level in gingival tissues around the ligature were decreased by the nootkatone-treatment rats. Nootkatone increased Nrf2 and HO-1 protein expression and decreased NF-κB protein level, suppressing MDA levels and enhancing SOD activity. CONCLUSIONS: In a rat model, nootkatone effectively mitigates periodontal inflammation and alveolar bone loss through the Nrf2/HO-1 and NF-κB pathways. These findings suggest nootkatone as a promising therapeutic agent for the treatment of periodontitis.

Deep Learning for Strain Field Customization in Bioreactor with Dielectric Elastomer Actuator Array.

In the field of biomechanics, customizing complex strain fields according to specific requirements poses an important challenge for bioreactor technology, primarily due to the intricate coupling and nonlinear actuation of actuator arrays, which complicates the precise control of strain fields. This paper introduces a bioreactor designed with a 9 × 9 array of independently controllable dielectric elastomer actuators (DEAs), addressing this challenge. We employ image regression-based machine learning for both replicating target strain fields through inverse control and rapidly predicting feasible strain fields generated by the bioreactor in response to control inputs via forward control. To generate training data, a finite element analysis (FEA) simulation model was developed. In the FEA, the device was prestretched, followed by the random assignment of voltages to each pixel, yielding 10,000 distinct output strain field images for the training set. For inverse control, a multilayer perceptron (MLP) is utilized to predict control inputs from images, whereas, for forward control, MLP maps control inputs to low-resolution images, which are then upscaled to high-resolution outputs through a super-resolution generative adversarial network (SRGAN). Demonstrations include inputting biomechanically significant strain fields, where the method successfully replicated the intended fields. Additionally, by using various tumor-stroma interfaces as inputs, the bioreactor demonstrated its ability to customize strain fields accordingly, showcasing its potential as an advanced testbed for tumor biomechanics research.

High-Frequency AC Heating Strategy of Electric Vehicle Power Battery Pack in Low-Temperature Environment.

In this paper, a heating strategy using high-frequency alternating current (AC) is proposed to internally heat lithium-ion batteries (LIB) at low temperatures. The strategy aims to strike a good balance between rapid heating of the battery at low temperatures and minimizing damage to the battery's lifespan without the need for an additional power source. The strategy presents an electrochemical-thermal coupling model to simulate and predict the temperature rise and temperature distribution of a 50 A h LiFePO4 square battery at different C-rates, the effect of high-frequency AC on battery life, and the validity of the model as verified by experiments. The experimental and simulation results show that this strategy can achieve faster heating speeds and better temperature consistency without affecting battery life. The best heating effect can be achieved at a frequency of 500 Hz (4.2C), and the temperature of the battery rises from 253.15 to 278.15 K within 365 s, for an average heating rate of 3.29 K/min. Researching low-temperature AC heating methods has important value for energy conservation because it can improve heating efficiency, expand application areas, promote technological innovation, and enhance product quality.

Multi-MXene assisted large-scale manufacturing of electrochemical biosensors based on enzyme-nanoflower enhanced electrodes for the detection of H2O2 secreted from live cancer cells.

In situ monitoring of H2O2 in cellular microenvironments plays a critical role in the early diagnosis and pretreatment of cancer, but is limited by the lack of efficient and low-cost strategies for the large-scale preparation of real-time biosensors. Herein, a universal strategy for MXene-based composite inks combined with a scalable screen-printing process is validated in large-scale manufacturing of electrochemical biosensors for in situ detection of H2O2 secreted from live cells. Compositing biocompatible carboxymethyl cellulose (CMCS) with excellent conductive MXene, a water-based ink electrode (MXene/CMCS) with tunable viscosity is efficiently printed with desirable printing accuracy. Subsequently, the MXene/CMCS@HRP electrochemical biosensor exhibits stable electrochemical performance through HRP nanoflower modification, showing rapid electron transport and high electrocatalytic capacity, and demonstrating a low limit of detection (0.29 µM) with a wide linear detection range (0.5 µM-3 mM), superior sensitivity (56.45 µA mM-1 cm-2), long-term stability and high anti-interference ability. Moreover, this electrochemical biosensor is effectively employed for in situ detection of H2O2 secreted from HeLa cells, revealing good biocompatibility and outstanding biosensing capability. This proposed strategy not only extends the possibility of low-cost biomedical devices, but also provides a promising approach for early diagnosis and treatment of cancer.

Nuclear autoantigenic sperm protein facilitates glioblastoma progression and radioresistance by regulating the ANXA2/STAT3 axis.

AIMS: Although radiotherapy is a core treatment modality for various human cancers, including glioblastoma multiforme (GBM), its clinical effects are often limited by radioresistance. The specific molecular mechanisms underlying radioresistance are largely unknown, and the reduction of radioresistance is an unresolved challenge in GBM research. METHODS: We analyzed and verified the expression of nuclear autoantigenic sperm protein (NASP) in gliomas and its relationship with patient prognosis. We also explored the function of NASP in GBM cell lines. We performed further mechanistic experiments to investigate the mechanisms by which NASP facilitates GBM progression and radioresistance. An intracranial mouse model was used to verify the effectiveness of combination therapy. RESULTS: NASP was highly expressed in gliomas, and its expression was negatively correlated with the prognosis of glioma. Functionally, NASP facilitated GBM cell proliferation, migration, invasion, and radioresistance. Mechanistically, NASP interacted directly with annexin A2 (ANXA2) and promoted its nuclear localization, which may have been mediated by phospho-annexin A2 (Tyr23). The NASP/ANXA2 axis was involved in DNA damage repair after radiotherapy, which explains the radioresistance of GBM cells that highly express NASP. NASP overexpression significantly activated the signal transducer and activator of transcription 3 (STAT3) signaling pathway. The combination of WP1066 (a STAT3 pathway inhibitor) and radiotherapy significantly inhibited GBM growth in vitro and in vivo. CONCLUSION: Our findings indicate that NASP may serve as a potential biomarker of GBM radioresistance and has important implications for improving clinical radiotherapy.

Superhydrophobic Coatings Composed of Multifunctional Polymers Synthesized Using Successive Modification of Dihydropyrimidin-2(1H)-thione.

Polymer synthesis via multicomponent reactions (MCRs) has opened avenues in polymer chemistry and led to the development of various types of functional polymers. Herein, we developed a strategy to prepare multifunctional polymers via the successive modification of dihydropyrimidin-2(1H)-thione (DHPMT), which can be generated by the tricomponent Biginelli reaction. Four hydrophobic polymers were efficiently prepared by using DHPMT derivatives. These polymers can be dip-coated onto the oxidized copper mesh to obtain superhydrophobic meshes because of the strong attractive forces between the DHPMT derivatives and Cu(II). The optimized mesh has self-cleaning properties and outstanding stability in various liquid environments; it has also been successfully applied for oil/water separation with high separation efficiency and good durability. These results demonstrate that successive modification of DHPMT is a promising method for fabricating multifunctional polymers, which may have applications in polymer chemistry and materials science.

Comprehensive analysis to identify the influences of SARS-CoV-2 infections to inflammatory bowel disease.

Background: Coronavirus disease 2019 (COVID-19) and inflammatory bowel disease (IBD) are both caused by a disordered immune response and have direct and profound impacts on health care services. In this study, we implemented transcriptomic and single-cell analysis to detect common molecular and cellular intersections between COVID-19 and IBD that help understand the linkage of COVID-19 to the IBD patients. Methods: Four RNA-sequencing datasets (GSE147507, GSE126124, GSE9686 and GSE36807) from Gene Expression Omnibus (GEO) database are extracted to detect mutual differentially expressed genes (DEGs) for IBD patients with the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to find shared pathways, candidate drugs, hub genes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980) are used to analyze the immune characteristics of hub genes and the proportion of immune cell types, so as to find common immune responses between COVID-19 and IBD. Results: A total of 121 common DEGs were identified among four RNA-seq datasets, and were all involved in the functional enrichment analysis related to inflammation and immune response. Transcription factors-DEGs interactions, miRNAs-DEGs coregulatory networks, and protein-drug interactions were identified based on these datasets. Protein-protein interactions (PPIs) was built and 59 hub genes were identified. Moreover, scRNA-seq of peripheral blood monocyte cells (PBMCs) from COVID-19 patients revealed a significant increase in the proportion of CD14+ monocytes, in which 38 of 59 hub genes were highly enriched. These genes, encoding inflammatory cytokines, were also highly expressed in inflammatory macrophages (IMacrophage) of intestinal tissues of IBD patients. Conclusions: We conclude that COVID-19 may promote the progression of IBD through cytokine storms. The candidate drugs and DEGs-regulated networks may suggest effective therapeutic methods for both COVID-19 and IBD.