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Using citric acid, ethylene glycol, ZrOCl2·8H2O, HfOCl2·8H2O, TiCl4, NbCl5, and TaCl5 as raw materials, the (Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C high‐entropy ceramic precursor was prepared by Pechini coordination polymerization method. The precursor and pyrolysis products were analyzed and characterized by different methods. The results showed that the precursor formed a chelate structure, which greatly improved the stability of the precursor, and was clear and transparent with moderate viscosity (30–50 mPa·s). At a low pyrolysis temperature of 1600°C, single‐phase (Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C high‐entropy ceramic nanopowders with a ceramic yield of 50.8% can be obtained. The high‐entropy ceramic powder has high purity, a particle size of about 140–200 nm, and uniform element distribution. It is suitable for introduction into fiber‐reinforced ceramic matrix composite by precursor infiltration and pyrolysis (PIP) process. [ABSTRACT FROM AUTHOR]

Background: A(H1N1)pdm09 influenza viruses replicate efficiently in respiratory epithelia and are transmitted via respiratory droplets and aerosols expelled by infected hosts. The relative onward transmission potential of influenza viruses replicating in the upper and lower respiratory epithelial cells has not been fully defined.Methods: Wild-type and barcoded A(H1N1)pdm09 viruses that differed by 2 synonymous mutations per gene segment were inoculated into ferrets via intranasal and intratracheal routes. Naive recipients were exposed to the exhaled breath of inoculated donors for 8 hours on day 2 postinoculation. Onward transmission potential of wild-type and barcoded genotypes were monitored by next generation sequencing.Results: Transmissible airborne particles were respired from the upper but not the lower respiratory epithelial cells of donor ferrets. There was limited mixing of viral populations replicating in the upper and lower respiratory tissues.Conclusions: The ferret upper respiratory epithelium was mapped as the anatomic site that generated influenza virus-laden particles mediating onward transmission by air. Our results suggest that vaccines and antivirals should aim to reduce viral loads in the upper respiratory tract for prevention of influenza transmission. [ABSTRACT FROM AUTHOR]

• Deep learning provides efficient and accurate prediction of treatment response. • Transfer learning can be used in radiological task with insufficient image datasets. • Tumor microenvironment and signaling pathways are linked with radiological prediction. Deep learning is promising to predict treatment response. We aimed to evaluate and validate the predictive performance of the CT-based model using deep learning features for predicting pathologic complete response to neoadjuvant chemoradiotherapy (nCRT) in esophageal squamous cell carcinoma (ESCC). Patients were retrospectively enrolled between April 2007 and December 2018 from two institutions. We extracted deep learning features of six pre-trained convolutional neural networks, respectively, from pretreatment CT images in the training cohort (n = 161). Support vector machine was adopted as the classifier. Validation was performed in an external testing cohort (n = 70). We assessed the performance using the area under the receiver operating characteristics curve (AUC) and selected an optimal model, which was compared with a radiomics model developed from the training cohort. A clinical model consisting of clinical factors only was also built for baseline comparison. We further conducted a radiogenomics analysis using gene expression profiles to reveal underlying biology associated with radiological prediction. The optimal model with features extracted from ResNet50 achieved an AUC and accuracy of 0.805 (95% CI, 0.696–0.913) and 77.1% (65.6%-86.3%) in the testing cohort, compared with 0.725 (0.605–0.846)) and 67.1% (54.9%-77.9%) for the radiomics model. All the radiological models showed better predictive performance than the clinical model. Radiogenomics analysis suggested a potential association mainly with WNT signaling pathway and tumor microenvironment. The novel and noninvasive deep learning approach could provide efficient and accurate prediction of treatment response to nCRT in ESCC, and benefit clinical decision making of therapeutic strategy. [ABSTRACT FROM AUTHOR]

Purpose: Biomedical data frequently contain imbalance characteristics which make achieving good predictive performance with data-driven machine learning approaches a challenging task. In this study, we investigated the impact of re-sampling techniques for imbalanced datasets in PET radiomics-based prognostication model in head and neck (HNC) cancer patients. Methods: Radiomics analysis was performed in two cohorts of patients, including 166 patients newly diagnosed with nasopharyngeal carcinoma (NPC) in our centre and 182 HNC patients from open database. Conventional PET parameters and robust radiomics features were extracted for correlation analysis of the overall survival (OS) and disease progression-free survival (DFS). We investigated a cross-combination of 10 re-sampling methods (oversampling, undersampling, and hybrid sampling) with 4 machine learning classifiers for survival prediction. Diagnostic performance was assessed in hold-out test sets. Statistical differences were analysed using Monte Carlo cross-validations by post hoc Nemenyi analysis. Results: Oversampling techniques like ADASYN and SMOTE could improve prediction performance in terms of G-mean and F-measures in minority class, without significant loss of F-measures in majority class. We identified optimal PET radiomics-based prediction model of OS (AUC of 0.82, G-mean of 0.77) for our NPC cohort. Similar findings that oversampling techniques improved the prediction performance were seen when this was tested on an external dataset indicating generalisability. Conclusion: Our study showed a significant positive impact on the prediction performance in imbalanced datasets by applying re-sampling techniques. We have created an open-source solution for automated calculations and comparisons of multiple re-sampling techniques and machine learning classifiers for easy replication in future studies. [ABSTRACT FROM AUTHOR]

Background Respiratory virus–laden particles are commonly detected in the exhaled breath of symptomatic patients or in air sampled from healthcare settings. However, the temporal relationship of detecting virus-laden particles at nonhealthcare locations vs surveillance data obtained by conventional means has not been fully assessed. Methods From October 2016 to June 2018, air was sampled weekly from a university campus in Hong Kong. Viral genomes were detected and quantified by real-time reverse-transcription polymerase chain reaction. Logistic regression models were fitted to examine the adjusted odds ratios (aORs) of ecological and environmental factors associated with the detection of virus-laden airborne particles. Results Influenza A (16.9% [117/694]) and influenza B (4.5% [31/694]) viruses were detected at higher frequencies in air than rhinovirus (2.2% [6/270]), respiratory syncytial virus (0.4% [1/270]), or human coronaviruses (0% [0/270]). Multivariate analyses showed that increased crowdedness (aOR, 2.3 [95% confidence interval {CI}, 1.5–3.8]; P <.001) and higher indoor temperature (aOR, 1.2 [95% CI, 1.1–1.3]; P <.001) were associated with detection of influenza airborne particles, but absolute humidity was not (aOR, 0.9 [95% CI,.7–1.1]; P =.213). Higher copies of influenza viral genome were detected from airborne particles >4 μm in spring and <1 μm in autumn. Influenza A(H3N2) and influenza B viruses that caused epidemics during the study period were detected in air prior to observing increased influenza activities in the community. Conclusions Air sampling as a surveillance tool for monitoring influenza activity at public locations may provide early detection signals on influenza viruses that circulate in the community. [ABSTRACT FROM AUTHOR]

Purpose: Metabolic acidosis as one of the most common perioperative complications has been associated with increased risks for poor prognosis. Routine monitoring methods include blood gas analysis and electrocardiogram, which are limited by time delay effects. And the existing intravital imaging modalities are difficult to achieve in one step. Here, we present a dual-wavelength photoacoustic imaging approach to overcome this dilemma. The aim of this study was to develop a rapid approach for intensive monitoring of acid–base imbalance and cerebral oxygen metabolism. Procedures: We characterized the cerebrovascular structure by label-free dual-wavelength (532 and 559 nm) photoacoustic microscopy in healthy and diabetic mouse models with metabolic acidosis. Concurrently, we developed a single-vessel analysis method to accurately delineate the differential responses of small vessels and quantify the cerebral oxygenation following experimental alteration of pH. Results: We demonstrated that there was an increasing trend in changes of vascular measurements (density, diameter, and relative hemoglobin concentration) and cerebral microvascular oxygen metabolism with the aggravation of acidosis. Furthermore, we established a clinical nomogram for the diagnosis of disease severity and yielded good discrimination ability with area under the curve of 0.920–0.967 and accuracy of 81.9–93.0%. The nomogram was also validated well in the diabetic mouse model with metabolic acidosis. Conclusions: Our photoacoustic imaging approach has great potential for rapid detection of metabolic acidosis and brain oxygen metabolism, which could potentially be applied as a bedside monitoring method for brain protection and timely treatment of acid–base abnormalities. [ABSTRACT FROM AUTHOR]

Objective. To evaluate the application of endoscopic ultrasound (EUS) combined with multislice spiral CT (MSCT) in the diagnosis and treatment of patients with gastric eminence lesions. Methods. A total of 160 patients with gastric eminence lesions enrolled in our hospital from June 2018 to June 2021 were included and received EUS and MSCT. The results of the two examinations and the postoperative pathological results were compared. Results. The common pathological types of gastric eminence lesions include polyps and stromal tumors, with the most common sites of lesions in the gastric antrum, followed by the fundus of the stomach and the gastric body. Gastric eminence lesions mostly originate from the mucosal layer and muscularis mucosa, accounting for 83.13% of the total. With pathological results as the gold standard, the detection rate of MSCT was 90.63%, and that of EUS was 78.13%. With the joint diagnosis as a reference, the receiver operating curve (ROC) revealed a higher diagnostic efficiency of MSCT and EUS. Conclusion. The accuracy of MSCT in the diagnosis of gastric eminence lesions is significantly higher than that of EUS, both of which can offer useful guidance for the choice of endoscopic treatment methods. The combination of MSCT and EUS examination before endoscopic gastroscopy may provide a better treatment efficacy on gastric protruding lesions with high safety. [ABSTRACT FROM AUTHOR]

Elevated expression and genetic aberration of IRTKS, also named as BAIAP2L1, have been observed in many tumors, especially in tumor progression. however, the molecular and cellular mechanisms involved in the IRTKS-enhanced tumor progression are obscure. Here we show that higher IRTKS level specifically increases histone H3 lysine 9 trimethylation (H3K9me3) by promoting accumulation of the histone methyltransferase SETDB1. Furthermore, we reveal that IRTKS recruits the deubiquitinase OTUD4 to remove Lys48-linked polyubiquitination at K182/K1050 sites of SETDB1, thus blocking SETDB1 degradation via the ubiquitin-proteasome pathway. Interestingly, the enhanced IRTKS–OTUD4–SETDB1–H3K9me3 axis leads to a general decrease in chromatin accessibility, which inhibits transcription of CDH1 encoding E-cadherin, a key molecule essential for maintaining epithelial cell phenotype, and therefore results in epithelial-mesenchymal transition (EMT) and malignant cell metastasis. Clinically, the elevated IRTKS levels in tumor specimens correlate with SETDB1 levels, but negatively associate with survival time. Our data reveal a novel mechanism for the IRTKS-enhanced tumor progression, where IRTKS cooperates with OTUD4 to enhance SETDB1-mediated H3K9 trimethylation that promotes tumor metastasis via suppressing E-cadherin expression. This study also provides a potential approach to reduce the activity and stability of the known therapeutic target SETDB1 possibly through regulating IRTKS or deubiquitinase OTUD4. • Higher levels of IRTKS increase H3K9me3 by promoting SETDB1 accuumulation. • IRTKS recruits the deubiquitinase OTUD4 to blocking SETDB1 degradation. • The enhanced IRTKS–OTUD4–SETDB1–H3K9me3 axis decreases chromatin accessibility, and inhibits E-cadherin transcription, resulting in EMT and tumor metastasis. • Clinically, elevated IRTKS levels in tumor correlate with SETDB1 levels, and negatively associate with survival time. [ABSTRACT FROM AUTHOR]