Particulate Matter 2.5 Causes Deficiency in Barrier Integrity in Human Nasal Epithelial Cells

PURPOSE: The effect of air pollution-related particulate matter (PM) on epithelial barrier function and tight junction (TJ) expression in human nasal mucosa has not been studied to date. This study therefore aimed to assess the direct impact of PM with an aerodynamic diameter less than 2.5 μ (PM2.5) on the barrier function and TJ molecular expression of human nasal epithelial cells. METHODS: Air-liquid interface cultures were established with epithelial cells derived from noninflammatory nasal mucosal tissue collected from patients undergoing paranasal sinus surgery. Confluent cultures were exposed to 50 or 100 μg/mL PM2.5 for up to 72 hours, and assessed for 1) epithelial barrier integrity as measured by transepithelial resistance (TER) and permeability of fluorescein isothiocyanate (FITC) 4 kDa; 2) expression of TJs using real-time quantitative polymerase chain reaction and immunofluorescence staining, and 3) proinflammatory cytokines by luminometric bead array or enzyme-linked immunosorbent assay. RESULTS: Compared to control medium, 50 and/or 100 μg/mL PM2.5-treatment 1) significantly decreased TER and increased FITC permeability, which could not be restored by budesonide pretreatment; 2) significantly decreased the expression of claudin-1 messenger RNA, claudin-1, occludin and ZO-1 protein; and 3) significantly increased production of the cytokines interleukin-8, TIMP metallopeptidase inhibitor 1 and thymic stromal lymphopoietin. CONCLUSIONS: Exposure to PM2.5 may lead to loss of barrier function in human nasal epithelium through decreased expression of TJ proteins and increased release of proinflammatory cytokines. These results suggest an important mechanism of susceptibility to rhinitis and rhinosinusitis in highly PM2.5-polluted areas

3D Mosaic Carbon Nanofiber Sensors for Room‐Temperature Detection of Methane and Other Dissolved Gases in Transformer Oil

Abstract Hydrocarbons and carbon oxides are typical dissolved gases in transformer oil that reflect the latent pitfalls, on‐line monitoring of their concentrations can effectively evaluate the operating status of the power transformer. However, these low‐concentration targets (especially for CH4) show high chemical inertness at room temperature, challenging the sensitive performance of current commonly used chemiresistive gas sensors. Herein, a strategy by combining traditional inorganic semiconductors to carbon nanofiber (CNF) via electrospinning–annealing route is described. Three optimized 3D mosaic films, CNFs scaffold incorporated with WO3, SnO2 and MoS2 nanoparticles, are obtained. Due to the large specific surface area of the 3D network, and the synergic and heterojunction effects between nanoparticles and CNFs, all three sensors exhibit high response to CH4 at room temperature, and also record distinguishable signals toward H2, C2H4, CO and CO2, revealing the three sensors are cross‐sensitive to the five analytes. Accordingly, preliminary discrimination of five dissolved gases is realized by principle component analysis. This study provides an effective and extendable solution of preparing room‐temperature chemiresistive sensors for the detection of CH4 and other gases, and offers a strategy for the construction of sensor array to achieve a high discrimination capability

Deubiquitinase USP19 modulates apoptotic calcium release and endoplasmic reticulum stress by deubiquitinating BAG6 in triple negative breast cancer

Abstract Background Triple‐negative breast cancer (TNBC), a heterogeneous subtype of breast cancer (BC), had poor prognosis. Endoplasmic reticulum (ER) stress was responsible for cellular processes and played a crucial role in the cell function. ER stress is a complex and dynamic process that can induce abnormal apoptosis and death. However, the underlying mechanism of ER stress involved in TNBC is not well defined. Methods We identified ubiquitin‐specific protease 19 (USP19) as a TNBC negative regulator for further investigation. The effects of USP19 on BC proliferation were assessed in vitro using proliferation test and cell‐cycle assays, while the effects in vivo were examined using a mouse tumorigenicity model. Through in vitro flow cytometric analyses and in vivo TUNEL assays, cell apoptosis was assessed. Proteomics was used to examine the proteins that interact with USP19. Results Multiple in vitro and in vivo tests showed that USP19 decreases TNBC cell growth while increasing apoptosis. Then, we demonstrated that USP19 interacts with deubiquitinates and subsequently stabilises family molecular chaperone regulator 6 (BAG6). BAG6 can boost B‐cell lymphoma 2 (BCL2) ubiquitination and degradation, thereby raising ER calcium (Ca2+) levels and causing ER stress. We also found that the N6‐methyladenosine (m6A) “writer” methyltransferase‐like 14 (METTL14) increased global m6A modification. Conclusions Our study reveals that USP19 elevates the intracellular Ca2+ concentration to alter ER stress via regulation of BAG6 and BCL2 stability and may be a viable therapeutic target for TNBC therapy

Integrated tumor genomic and immune microenvironment analysis identifies predictive biomarkers associated with the efficacy of neoadjuvant therapy for triple‐negative breast cancer

Abstract Background Although neoadjuvant chemotherapy (NAC) is currently the best therapy for triple‐negative breast cancer (TNBC), resistance still occurs in a considerable proportion, thus it is crucial to understand resistance mechanisms and identify predictive biomarkers for patients selection. Methods Biopsy samples were collected from 21 patients with TNBC who underwent NAC. Whole‐exome sequencing (WES), targeted sequencing, and multiplex immunohistochemistry (mIHC) were carried out on the clinical samples and used to identify and validate potential biomarkers associated with response to NAC. In addition, data on 190 TNBC patients who had undergone chemotherapy were obtained from The Cancer Genome Atlas (TCGA) and analyzed to further validate our findings. Results Both the tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were significantly higher in responders than in non‐responders. Higher response rates and longer survival rates were observed in patients with higher TMB. Patients with higher ratios of CD8 to M2 macrophages had higher response rates and improved survival rates. Finally, the integrated analysis demonstrated that the combination of TMB and the ratio of CD8 T cells to M2 macrophages could further distinguish patients who benefitted from the treatment in both enrolled patients and public data. Conclusions The findings of this study indicated that the combination of TMB and the ratio of CD8 T cells to M2 macrophages may be a potential biomarker for improving the recognition of NAC responders, thereby providing a basis for developing precision NAC regimens

FE modeling and simulation of the turning process considering the cutting induced hardening of workpiece materials

The accuracy of the cutting simulation model greatly depends on the constitutive models, thermophysical models, and friction models. However, accurate modeling of physical and mechanical relationships is not enough. The physical and mechanical behavior of the machined surface from the last cut should be modelled in the FE model. In this study, the cutting simulation model of S316L stainless steel was established. The above model consists of two subsequent simulated cuts. The first simulated cut was used to obtain the machined surface with the residual stress, and the second simulated cut was subsequent with the first cut to obtain the actual simulated results. The constitutive model was obtained by the split Hopkinson pressure bar (SHPB) and high-temperature hardness experiments. The specific heat capacity and thermal conductivity models were developed by laser thermal conductivity experiments with various temperatures. The friction model between the workpiece and the tool was established by orthogonal cutting experiments. The simulated cutting forces of the first and second cut were extracted and compared with the experimental results to verify the accuracy of the simulation models. The results showed that the average error of cutting forces for the first cut is 28.33 %, but that for the second cut is 8.02 %, which verifies the accuracy of the two-subsequent cutting simulation model. Additionally, the significant differences in the simulated cutting forces between the first and second cutting depict that the residual stress cannot be ignored for the accuracy verification of cutting simulation models

Potential of Recycled Silicon and Silicon-Based Thermoelectrics for Power Generation

Thermoelectrics can convert waste heat to electricity and vice versa. The energy conversion efficiency depends on materials figure of merit, zT, and Carnot efficiency. Due to the higher Carnot efficiency at a higher temperature gradient, high-temperature thermoelectrics are attractive for waste heat recycling. Among high-temperature thermoelectrics, silicon-based compounds are attractive due to the confluence of light weight, high abundance, and low cost. Adding to their attractiveness is the generally defect-tolerant nature of thermoelectrics. This makes them a suitable target application for recycled silicon waste from electronic (e-waste) and solar cell waste. In this review, we summarize the usage of high-temperature thermoelectric generators (TEGs) in applications such as commercial aviation and space voyages. Special emphasis is placed on silicon-based compounds, which include some recent works on recycled silicon and their thermoelectric properties. Besides materials design, device designing considerations to further maximize the energy conversion efficiencies are also discussed. The insights derived from this review can be used to guide sustainable recycling of e-waste into thermoelectrics for power harvesting

Potential of Recycled Silicon and Silicon-Based Thermoelectrics for Power Generation

Thermoelectrics can convert waste heat to electricity and vice versa. The energy conversion efficiency depends on materials figure of merit, zT, and Carnot efficiency. Due to the higher Carnot efficiency at a higher temperature gradient, high-temperature thermoelectrics are attractive for waste heat recycling. Among high-temperature thermoelectrics, silicon-based compounds are attractive due to the confluence of light weight, high abundance, and low cost. Adding to their attractiveness is the generally defect-tolerant nature of thermoelectrics. This makes them a suitable target application for recycled silicon waste from electronic (e-waste) and solar cell waste. In this review, we summarize the usage of high-temperature thermoelectric generators (TEGs) in applications such as commercial aviation and space voyages. Special emphasis is placed on silicon-based compounds, which include some recent works on recycled silicon and their thermoelectric properties. Besides materials design, device designing considerations to further maximize the energy conversion efficiencies are also discussed. The insights derived from this review can be used to guide sustainable recycling of e-waste into thermoelectrics for power harvesting

Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia

Abstract Purpose To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features. Methods Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP. Multivariate logistic regression was used to combine the predictive radiomics features with the independent clinical predictors. The prediction performance of the SAP models was evaluated using receiver operating characteristics (ROC), calibration curves, decision curve analysis, and subgroup analyses. Results Triglycerides, the neutrophil-to-lymphocyte ratio, dysphagia, the National Institutes of Health Stroke Scale (NIHSS) score, and internal carotid artery stenosis were identified as clinically independent risk factors for SAP. The radiomics scores in patients with SAP were generally higher than in patients without SAP (P < 0. 05). There was a linear positive correlation between radiomics scores and NIHSS scores, as well as between radiomics scores and infarct volume. Infarct volume showed moderate performance in predicting the occurrence of SAP, with an AUC of 0.635. When compared with the other models, the combined prediction model achieved the best area under the ROC (AUC) in both training (AUC = 0.859, 95% CI 0.759–0.936) and validation (AUC = 0.830, 95% CI 0.758–0.896) cohorts (P < 0.05). The calibration curves and decision curve analysis further confirmed the clinical value of the nomogram. Subgroup analysis showed that this nomogram had potential generalization ability. Conclusion The addition of the radiomics features to the clinical model improved the prediction of SAP in AIS patients, which verified its feasibility

Recent advances of sustainable short-chain length polyhydroxyalkanoates (Scl-PHAs) – plant biomass composites

Plastic pollution has become a global threat to humanity. Fortunately, humanity has always found ways of overcoming such threats through multipronged approaches. To overcome this current threat brought about by anthropogenic linear pattern of take-make-use-dispose of fossil-based plastics, an intentional approach of adopting biobased plastics which are renewable has taken shape. In this approach, governments, industry, and academia are at the forefront of making determined commitments to slow down the spiralling carbon footprint and aim at net zero carbon emissions by 2050. In this regard, PHAs which have a rich resume of desired properties to replace non-renewable fossil-based plastics are increasingly becoming popular. However, PHA production cost is still high compared with the fossil-based plastics and there exists properties performance gap because they are typically brittle, especially the short chain length PHAs (Scl-PHAs). Considerable efforts are geared towards tuning the mechanical properties as well as reducing the cost to meet the market requirements. The most authentic way of tackling these twin-challenges of reducing the cost of PHA products and their properties enhancement is the incorporation of fillers sourced from renewable sources, especially the plant biomass. In this comprehensive review, Scl-PHAs biopolymers are discussed, their modifications with plant biomass (natural fibres and components, agro-residues, and industrial residues) are elucidated. Moreover, their wide scope of applications, sustainability performance (biodegradation studies) and other viable end-of-life options are amply discussed. Finally, we draw conclusions and highlight future opportunities in this exciting bioplastic area.Agency for Science, Technology and Research (A*STAR)The authors acknowledge financial support from A* STAR ’s Science and Engineering Research Council (Grant Reference No.: GAP/2019/00314)

Pan-neuronal imaging in roaming Caenorhabditis elegans

We present an imaging system for pan-neuronal recording in crawling Caenorhabditis elegans. A spinning disk confocal microscope, modified for automated tracking of the C. elegans head ganglia, simultaneously records the activity and position of ∼80 neurons that coexpress cytoplasmic calcium indicator GCaMP6s and nuclear localized red fluorescent protein at 10 volumes per second. We developed a behavioral analysis algorithm that maps the movements of the head ganglia to the animal's posture and locomotion. Image registration and analysis software automatically assigns an index to each nucleus and calculates the corresponding calcium signal. Neurons with highly stereotyped positions can be associated with unique indexes and subsequently identified using an atlas of the worm nervous system. To test our system, we analyzed the brainwide activity patterns of moving worms subjected to thermosensory inputs. We demonstrate that our setup is able to uncover representations of sensory input and motor output of individual neurons from brainwide dynamics. Our imaging setup and analysis pipeline should facilitate mapping circuits for sensory to motor transformation in transparent behaving animals such as C. elegans and Drosophila larva