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Abstract Climate change is predicted to increase the occurrence of extreme weather events such as heatwaves, which may thereby impact the outcome of plant-herbivore interactions. While elevated temperature is known to directly affect herbivore growth, it remains largely unclear if it indirectly influences herbivore performance by affecting the host plant they feed on. In this study, we investigated how transient exposure to high temperature influences plant herbivory-induced defenses at the transcript and metabolic level. To this end, we studied the interaction between potato (Solanum tuberosum) plants and the larvae of the potato tuber moth (Phthorimaea operculella) under different temperature regimes. We found that P. operculella larvae grew heavier on leaves co-stressed by high temperature and insect herbivory than on leaves pre-stressed by herbivory alone. We also observed that high temperature treatments altered phylotranscriptomic patterns upon herbivory, which changed from an evolutionary hourglass pattern, in which transcriptomic responses at early and late time points after elicitation are more variable than the ones in the middle, to a vase pattern. Specifically, transcripts of many herbivory-induced genes in the early and late defense stage were suppressed by HT treatment, whereas those in the intermediate stage peaked earlier. Additionally, we observed that high temperature impaired the induction of jasmonates and defense compounds upon herbivory. Moreover, using jasmonate-reduced (JA-reduced, irAOC) and -elevated (JA-Ile-elevated, irCYP94B3s) potato plants, we showed that high temperature suppresses JA signaling mediated plant-induced defense to herbivore attack. Thus, our study provides evidences on how temperature reprograms plant-induced defense to herbivores.

ObjectiveThe study aimed to explore the risk factors for hyperuricemia (HUA) in the Naxi ethnic population residing in high-altitude areas of Yunnan, China, and assess the clinical value of the triglyceride/high-density lipoprotein cholesterol (TG/HDL-c) ratio as a diagnostic marker.MethodsIn this cross-sectional study, clinical data were collected from the health checkup population in the People's Hospital of Yulong Naxi Autonomous County, Yunnan Province, from January 2021 to January 2023. Participants were divided into quartiles based on the TG/HDL-c ratio (Q1, Q2, Q3, and Q4) for group analysis using chi-square tests, t-tests, and rank sum tests. Logistic regression analysis and linear regression models were employed to further investigate the correlation between the prevalence of hyperuricemia and TG/HDL-c ratio in this high-altitude Naxi population.ResultsA total of 714 participants from the health checkup population were included in the study, of whom 61.5% were male participants and 38.5% were female participants, and the average age was 41.21 ± 11.69 years. The mean uric acid level was 388.51 ± 99.24. After correcting for confounding factors, TG/HDL-c, serum creatinine (Scr), blood urea nitrogen (BUN), triglyceride (TG), high-density lipoprotein cholesterol (HDL-c), red blood cells (RBCs), and hemoglobin (Hb) showed a positive correlation with blood uric acid. Further analysis involved categorizing the TG/HDL-c ratio from a continuous variable to a categorical variable using quartiles. The fully adjusted model showed results that were consistent with the trend observed in the continuous variable analysis when considering the TG/HDL-c ratio as a categorical variable. In addition, in all unadjusted and adjusted models, the serum uric acid (SUA) levels in the high TG/HDL-c ratio group were significantly higher than those in the low TG/HDL-c ratio group (trend p < 0.001). Further linear relationship analysis indicated that after adjusting for covariates, there was an approximate linear relationship between the TG/HDL-c and SUA levels, with a coefficient (β) of 5.421.ConclusionThe prevalence of hyperuricemia is greater in high-altitude areas of Yunnan, showing a nearly linear positive correlation with the TG/HDL-c ratio. Monitoring TG/HDL-c levels may benefit patients with hyperuricemia.

Numerous studies have shown that trust has cross-cultural differences. Currently, China has limited tools and scales for measuring trust. Referring to Wu and Huang’s three-factor model of Chinese trust, we develop a Chinese Trust Scale (CTS) for Chinese people and measure its reliability and validity. This scale contains 20 items and three factors: (1) public awareness, (2) trust from others, and (3) trust in others. We explore the dimensions and preliminary items of the CTS using item analysis and exploratory factor analysis on one sample ( N = 551) and confirmatory factor analysis on a second sample ( N = 831) to replicate the suggested factor structure and validate the scale’s reliability and validity. Both the overall and subscale scores of the CTS were significantly correlated with inclusive general trust, belief in a just world, social capital, and satisfaction with life. The results suggest that newly developed CTS could be an effective tool for Chinese trust measurement.

Abstract Background HPV-positive head and neck squamous cell carcinoma (HNSCC) exhibits different characteristics from HPV-negative tumors in terms of tumor development, clinical features, treatment response, and prognosis. Layilin (LAYN), which contains homology with C-type lectins, plays a critical role in tumorigenesis and cancer progression. However, the prognostic value of LAYN and the relationship between LAYN and immune infiltration levels in HPV-related HNSCC patients still require a comprehensive understanding. Herein, we aimed to assess the prognostic value of LAYN and to investigate its underlying immunological function in HPV-related HNSCC. Methods Through various bioinformatics methods, we analyzed the data from The Cancer Genome Atlas (TCGA), Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA) databases to explore the potential underlying oncogenic impression of LAYN, including the relevance of LAYN to survival outcomes, clinicopathological factors, immune cell infiltration, and immune marker sets in HPV-related HNSCC. The expression levels of LAYN and HPV were also verified in HNSCC patient tissues. Results LAYN was differentially expressed in a variety of tumors. The expression of LAYN in HNSCC was significantly higher than that in adjacent normal tissues (P

Abstract Ectodermal neural cortex 1 (ENC1) is a protein that plays a crucial role in the regulation of various cellular processes such as cell proliferation, differentiation, and apoptosis. Numerous studies have shown that ENC1 is overexpressed in various types of cancers, including breast, lung, pancreatic, and colorectal cancer, and its upregulation is correlated with a poorer prognosis. In addition to its role in cancer growth and spreading, ENC1 has also been linked to neuronal process development and neural crest cell differentiation. In this review, we provide an overview of the current knowledge on the relationship between ENC1 and cancer. We discuss the molecular mechanisms by which ENC1 contributes to tumorigenesis, including its involvement in multiple oncogenic signaling pathways. We also summarize the potential of targeting ENC1 for cancer therapy, as its inhibition has been shown to significantly reduce cancer cell invasion, growth, and metastasis. Finally, we highlight the remaining gaps in our understanding of ENC1’s role in cancer and propose potential directions for future research.

Abstract Background Human vision has inspired significant advancements in computer vision, yet the human eye is prone to various silent eye diseases. With the advent of deep learning, computer vision for detecting human eye diseases has gained prominence, but most studies have focused only on a limited number of eye diseases. Results Our model demonstrated a reduction in inherent bias and enhanced robustness. The fused network achieved an Accuracy of 0.9237, Kappa of 0.878, F1 Score of 0.914 (95% CI [0.875–0.954]), Precision of 0.945 (95% CI [0.928–0.963]), Recall of 0.89 (95% CI [0.821–0.958]), and an AUC value of ROC at 0.987. These metrics are notably higher than those of comparable studies. Conclusions Our deep neural network-based model exhibited improvements in eye disease recognition metrics over models from peer research, highlighting its potential application in this field. Methods In deep learning-based eye recognition, to improve the learning efficiency of the model, we train and fine-tune the network by transfer learning. In order to eliminate the decision bias of the models and improve the credibility of the decisions, we propose a model decision fusion method based on the D-S theory. However, D-S theory is an incomplete and conflicting theory, we improve and eliminate the existed paradoxes, propose the improved D-S evidence theory(ID-SET), and apply it to the decision fusion of eye disease recognition models.

ABSTRACT Aims/Introduction High glucose increases the accumulation of lipid droplets in hepatocytes, which eventually results in nonalcoholic fatty liver disease in patients with diabetes. However, the specific mechanism or communication between adipocyte and hepatocyte lipid metabolism is still ambiguous. Materials and Methods In this study, exosomes released from human adipocytes were isolated and identified by their morphology, size, and marker proteins by using transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blotting (WB). Gene expression was detected by qRT‐PCR and WB. Lipid accumulation was determined by oil red O staining and analyses of total cholesterol (TC) and triglyceride (TG) content. Results Our results showed that co‐culture of HepG2 cells with adipocytes under high glucose conditions stimulated lipid deposition and LINC01705 expression in the HepG2 cells. Exosomes extracted from adipocytes cultured under high glucose conditions had higher levels of LINC01705 than exosomes extracted from adipocytes cultured under normal glucose conditions. Moreover, LINC01705 expression was also elevated in exosomes extracted from diabetes patients when compared with exosomes isolated from normal volunteers, and exosomes from patients who had diabetes complicated with fatty liver (DCFL) had the highest levels of LINC01705 expression. Treatment of HepG2 cells with exosomes extracted from high glucose‐stimulated adipocytes promoted lipid deposition and LINC01705 expression in HepG2 cells. Further experiments showed that overexpression of LINC01705 promoted HepG2 lipid metabolism, while inhibition of LINC01705 had the opposite effect. Mechanistically, LINC01705 competitively bound to miR‐552‐3p, and treatment with miR‐552‐3p inhibitor reversed the effects induced by LINC01705 knockdown. Moreover, miR‐552‐3p was found to regulate the transcription activity of LXRα and thereby modulate lipid metabolism‐related gene expression. Conclusions When taken together, our findings showed that high glucose increased the LINC01705 levels in adipocyte exosomes, and thereby improved HepG2 lipid accumulation via an miR‐552‐3p/LXR axis.

Background: Cancer is the most fatal disease in humans and the aberrant activity of various cell cycle proteins results in uncontrolled tumor cell proliferation, thus, regulating the cell cycle is an attractive target in cancer therapy. Objectives: Aurone is a naturally occurring active compound with a wide range of biological activities, of which 3, 4, 5-trimethoxyphenyl (TMP) is an important microtubule targeting pharmacophore. Based on the pharmacophore combination principle, we incorporate the TMP pharmacophore into the aurone structure and design a novel polymethoxy derivative that is expected to inhibit tumor cell proliferation through regulating the cell cycle. Methods: By introducing different substituents on C-4′ and C-3′, a series of new 4, 5, 6-trimethoxy aurone derivatives have been designed and synthesized. DU145, MCF-7 and H1299 cell lines were selected to evaluate their anticancer activity. The compound with the best cytotoxicity was then selected and the anticancer mechanisms were investigated by network pharmacology, flow cytometry, Western blot, and cell heat transfer assay. ADMET prediction evaluated the draggability of aurone derivatives. Results: Aurones 1b and 1c have selective anti-proliferative activity against DU145 cells. Among them, the compound 1c have better cytotoxicity against DU145. Compound 1c could bind the active cavity of CyclinB1/CDK1/CKS complex protein and induced G2/M phase arrest of DU145 cells by regulating the expression of CyclinB1 and p21. Compound 1c satisfies the Lipinski rule, is suitable for the absorption and metabolism index, and has a lower risk of cardiac toxicity. Conclusions: Polymethoxy aurones 1c might function as a CyclinB1/CDK1 inhibitor that deserved to be further developed for the treatment of prostate cancer.

Convolutional neural network (CNN) is used efficiently for the classification of hyperspectral imagery (HSI). Both 3-D CNN and hybrid 2D–3D CNN have better performance due to the full extraction of joint spatial-spectral features. Most of previous acceleration research on field-programmable gate array (FPGA) has concentrated on 2-D CNN, few of which were made for 3-D CNN acceleration. More importantly, it is notable that the CNN models for HSI classification have some unique characteristics of computation and memory, different from those for object detection. Thus, the conventional accelerating approaches may be not applicable. To address this problem, we propose a dynamic configurable accelerator architecture suitable for both 2-D and 3-D CNN, ensuring fast development for various networks. The multiple nested loops are optimized delicately and the convolutional layers are fully parameterized, making it easy to scale up the network. Furthermore, we develop the parallelism-oriented memory pattern and data access strategy to optimize the data path and the local buffer. Finally, we implement the proposed architecture for 2-D, 3-D, and hybrid CNNs, validating its effectiveness and reconfigurability. To demonstrate its extensibility, we also prototype the accelerator on two FPGA platforms. We achieve the average and maximum throughput of 18.2/166.18 giga operations per second (GOPS) for HybridSN. To compare with previous FPGA accelerators, a typical baseline 3-D model is also implemented with the average and maximum throughput 160.25/225.87 GOPS, and the performance efficiency achieves up to 1.23 with 10.7% power efficiency gain.

BackgroundThe comprehensive investigation of the association between keratoplasty and wound dehiscence remains limited, despite corneal disease being a leading cause of visual impairment.MethodsA meticulous search strategy was executed across prominent databases such as Web of Science, PubMed, Cochrane Library, and Embase. Data relevant to our research objective were extracted from eligible studies. The methodological quality of each study was assessed using the ROBINS-I tool, while statistical analysis was conducted utilizing STATA 17.0. To evaluate potential publication bias, the Funnel plot and Egger’s test were employed.ResultsA total of 11 articles were deemed suitable for inclusion in our analysis. Our findings indicate that the overall incidence of wound dehiscence following keratoplasty was estimated to be 1.9% (95% CI: 0.013, 0.026), although substantial heterogeneity was observed (I2 = 72.798%). Notably, developed countries exhibited a higher incidence of wound dehiscence compared to their developing counterparts. Furthermore, the occurrence of wound dehiscence was found to be lower in deep anterior lamellar keratoplasty (DALK) procedures when compared to penetrating keratoplasty (PK). Analysis utilizing Egger’s linear regression method yielded no evidence of publication bias (p = 0.91). Moreover, within the first year post-keratoplasty, approximately 31.4% of patients experienced wound dehiscence (95% CI: 0.149, 0.503), and 43.1% exhibited a decline in best-corrected visual acuity (BCVA) (95% CI, 0.341, 0.522).ConclusionThe results of our study unveiled the occurrence rate of wound dehiscence following keratoplasty, exhibiting variations based on economic level and the specific surgical procedure employed. Furthermore, onset time of wound dehiscence and visual acuity warrant consideration.

IntroductionAlthough it is commonly acknowledged that peer feedback quality is crucial to the success of peer review, there is a lack of consensus on how it could be determined. More importantly, how feedback quality interacts with other factors like feedback features and focus, and ultimately influences peer feedback implementation remains insufficiently investigated.MethodsThe present study examined peer feedback quality and its impact on Chinese students’ feedback implementation in two argumentative writing tasks. Peer feedback quality was measured according to a self-designed two-dimensional measurement scale: accuracy and revision potential.ResultsQuantitative analyses of 5,606 implementable idea units of feedback and 440 writing drafts by 110 students revealed that feedback accuracy was at a medium level and revision potential was at a low level, with accuracy demonstrating stronger predictive power on implementation; the predictive strengths of feedback accuracy and revision potential were strongest when feedback features and focus were considered; the overall peer feedback quality was low and medium-quality feedback was implemented most frequently; feedback quality significantly and most strongly predicted implementation in combination with feedback features and focus.DiscussionThe study highlights the importance of future instructions in training students to provide and implement high-quality feedback with good accuracy and high revision potential.

Hyperspectral LiDAR (HSL) has been utilised as an efficacious technique in objects classification and recognition based on its synchronously obtaining spectral and spatial information. However, the spectral information obtained by most of the developed HSL was in the visible and near-infrared range (VNIR, 400–1000 nm). Whereas spectral information in a longer wavelength range showed more useful for classification and detection, such as detecting vegetation water content. This paper proposed and tested an eight-channel HSL prototype covering visible to near-infrared and even short-wavelength infrared (VIS-NIR-SWIR, 450–1460 nm) based on a Super-continuum (SC) laser. System calibration, range precision and spectral profiles experiments were carried out to test the HSL prototype. The spectral profiles collected by the HSL are consistent with those acquired by the commercial spectrometer (SVC© HR-1024). And these spectral profiles of plants, textiles, camouflage objects, and ore samples collected by the HSL, especially those in the SWIR range, can effectively reveal the health status of the plants, and classify the manufacturing materials and ore species. The unique characteristics of spectral profiles covering VIS-NIR-SWIR promote the HSL shows the potential applications on objects classification related to vegetation, mining and surveillance.

BackgroundIn recent years, AI has been applied to disease diagnosis in many medical and engineering researches. We aimed to explore the diagnostic performance of the models based on different imaging modalities for ovarian cancer.MethodsPubMed, EMBASE, Web of Science, and Wanfang Database were searched. The search scope was all published Chinese and English literatures about AI diagnosis of benign and malignant ovarian tumors. The literature was screened and data extracted according to inclusion and exclusion criteria. Quadas-2 was used to evaluate the quality of the included literature, STATA 17.0. was used for statistical analysis, and forest plots and funnel plots were drawn to visualize the study results.ResultsA total of 11 studies were included, 3 of them were modeled based on ultrasound, 6 based on MRI, and 2 based on CT. The pooled AUROCs of studies based on ultrasound, MRI and CT were 0.94 (95% CI 0.88-1.00), 0.82 (95% CI 0.71-0.93) and 0.82 (95% Cl 0.78-0.86), respectively. The values of I2 were 99.92%, 99.91% and 92.64% based on ultrasound, MRI and CT. Funnel plot suggested no publication bias.ConclusionThe models based on ultrasound have the best performance in diagnostic of ovarian cancer.

A novel nanoprobe based on S,O-doped carbon nitride quantum dots (S,O-CNQDs) was designed and synthesized. The as-prepared S,O-CNQDs exhibits good biocompatibility and strong fluorescence at excitation 360 nm. It is found that folic acid (FA) could efficiently quench the fluorescence of S,O-CNQDs. The obtained S,O-CNQDs is capable of acting as a sensitive and selective probe for FA detection in the range 5.0–83.3 μM with a detection limit of 90 nM. The as-prepared probe has been successfully utilized for the detection of FA in various real samples with satisfactory recoveries (98.8–107 %) and small relative standard deviation (

IntroductionThe risk of alcoholic cirrhosis increases in a dose- and time-dependent manner with alcohol consumption and ethanol metabolism in the liver. Currently, no effective antifibrotic therapies are available. We aimed to obtain a better understanding of the cellular and molecular mechanisms involved in the pathogenesis of liver cirrhosis. MethodsWe performed single-cell RNA-sequencing to analyze immune cells from the liver tissue and peripheral blood form patients with alcoholic cirrhosis and healthy controls to profile the transcriptomes of more than 100,000 single human cells and yield molecular definitions for non-parenchymal cell types. In addition, we performed single-cell RNA-sequencing analysis to reveal the immune microenvironment related to alcoholic liver cirrhosis. Hematoxylin and eosin, Immunofluorescence staining and Flow cytometric analysis were employed to study the difference between tissues and cells with or without alcoholic cirrhosis.ResultsWe identified a fibrosis-associated M1 subpopulation of macrophages that expands in liver fibrosis, differentiates from circulating monocytes, and is pro-fibrogenic. We also define mucosal-associated invariant T (MAIT) cells that expand in alcoholic cirrhosis and are topographically restricted to the fibrotic niche. Multilineage modeling of ligand and receptor interactions between the fibrosis-associated macrophages, MAIT, and NK cells revealed the intra-fibrotic activity of several pro-fibrogenic pathways, including responses to cytokines and antigen processing and presentation, natural killer cell-mediated cytotoxicity, cell adhesion molecules, Th1/Th2/Th17 cell differentiation, IL-17 signaling pathway, and Toll-like receptor signaling pathway.DiscussionOur work dissects unanticipated aspects of the cellular and molecular basis of human organ alcoholic fibrosis at the single-cell level and provides a conceptual framework for the discovery of rational therapeutic targets in liver alcoholic cirrhosis.

Objectives: The purpose of this study was to create a new delivery system that can synergistically remineralize enamel white spot lesions (WSLs).Materials and methods: The delivery system (PAA-ACP@aMBG) was prepared by using aminated mesoporous bioactive glasses (aMBG) as the carrier loaded with polyacrylic-stabilized amorphous calcium phosphate (PAA-ACP). The materials were characterized by transmission electron microscopy (TEM), X-ray powder diffraction (XRD), inductively coupled plasma–optical emission spectrometry (ICP–OES), and so on. Forty-eight artificial WSLs enamel samples were randomized to four groups: artificial saliva (negative control, NC), casein phosphopeptide-amorphous calcium phosphate (CPP-ACP), PAA-ACP@aMBG, and MBG. The effects of demineralization and remineralization of the enamel surface were compared by means of surface microhardness (SMH) measurements, surface color change measurements, fluorescence microscopy (FM), X-ray diffraction (XRD) analysis and scanning electron microscopy (SEM).Results: There was no significant difference in the surface microhardness recovery rate (SMHRR) or color recovery rate (CRR) among the CPP-ACP group, PAA-ACP@aMBG group and MBG group (P>0.05), but these values were significantly higher than those in the NC group (p < 0.01). FM demonstrated that the remineralization depth in the PAA-ACP@aMBG group was significantly greater than that of the remaining three groups (p < 0.01). SEM analysis indicated that the enamel demineralization marks in the PAA-ACP@aMBG group, CPP-ACP group, and MBG group were obscured by mineral deposition.Conclusions: PAA-ACP@aMBG showed good mineralization properties, implying its great potential for clinical application.

Even though exploiting skin-topological effects in topological insulators is attractive for topological switch design, current research has focused on theoretical demonstrations. Here, the authors experimentally demonstrate higher-order topological skin effects in nonreciprocal topoelectrical circuits.

Relativistic quantum mechanics is typically used to describe phenomena of high-energy physics but can also be applied to describe some features of quantum materials. Here, the authors use electrical circuits to simulate Dirac-like phenomena and measure Zitterbewegung and Klein tunneling for a one dimensional Bose-Hubbard model.

A better knowledge of the molecular process behind uterine corpus endometrial carcinoma (UCEC) is important for prognosis prediction and the development of innovative targeted gene therapies. The purpose of this research is to discover critical genes associated with UCEC. We analyzed the gene expression profiles of TCGA-UCEC and GSE17025, respectively, using Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. From four sets of findings, a total of 95 overlapping genes were retrieved. On the 95 overlapping genes, KEGG pathway and GO enrichment analysis were conducted. Then, we mapped the PPI network of 95 overlapping genes using the STRING database. Twenty hub genes were evaluated using the Cytohubba plugin, including NR3C1, ATF3, KLF15, THRA, NR4A1, FOSB, PER3, HLF, NTRK3, EGR3, MAPK13, ARNTL2, PKM2, SCD, EIF5A, ADHFE1, RERGL, TUB, and ENC1. The expression levels of NR3C1, PKM2, and ENC1 were shown to be adversely linked with the survival time of UCEC patients using univariate Cox regression analysis and Kaplan-Meier survival calculation. ENC1 were also overexpressed in UCEC tumor tissues or cell lines, as shown by quantitative real-time PCR and Western blotting. Then we looked into it further and discovered that ENC1 expression was linked to tumor microenvironment and predicted various immunological checkpoints. In conclusion, our data indicate that ENC1 may be required for the development of UCEC and may serve as a future biomarker for diagnosis and therapy.

Fe3C filled carbon nanotubes (CNTs) self-organized into flexible-film-morphologies (buckypapers) have been proposed for numerous applications, these include flexible data-storage-devices, exchange-bias, spin-based-systems, flexible ferromagnetic-electrodes and others. However, despite the important progress, the significant concentration of Cl-containing-hydrocarbons which is needed for the buckypaper-growth (i.e. 1 to 10 ml) represents still an important challenge for industrial-production.Here we report the experimental-growth-parameters needed for the nucleation and growth of flexible Fe3C-filled-CNT buckypapers, under very-low-concentrations of dichlorobenzene, as low as 0.05 ml.By carefully estimating both the heating- and cooling-rate parameters of the chosen chemical-vapor-deposition (CVD) reactor, we demonstrate the identification of two active-growth-regions which allow for the simultaneous nucleation and growth of ferromagnetically-filled buckypapers. The obtained films comprise of selectively grown single-wall (active-region-1) and multiwall (active-region-2) CNTs. The simultaneous growth of the two types of buckypapers within the same reactor is discussed and attributed to the dynamics of dichlorobenzene-pyrolysis, which appears to yield a higher concentration of Cl-radicals in the active-region-1. In the buckypapers grown in the latter (active-region-1) we highlight an unusual separation between the first (inner) and second CNT-cylinders, with the HRTEM analyses revealing an anomalously-large interlayer-distance varying from ∼ 1.6 to ∼ 6.6 nm (an effective void between two CNT-cylinders).

BackgroundArtificial intelligence has far surpassed previous related technologies in image recognition and is increasingly used in medical image analysis. We aimed to explore the diagnostic accuracy of the models based on deep learning or radiomics for lung cancer staging.MethodsStudies were systematically reviewed using literature searches from PubMed, EMBASE, Web of Science, and Wanfang Database, according to PRISMA guidelines. Studies about the diagnostic accuracy of radiomics and deep learning, including the identifications of lung cancer, tumor types, malignant lung nodules and lymph node metastase, were included. After identifying the articles, the methodological quality was assessed using the QUADAS-2 checklist. We extracted the characteristic of each study; the sensitivity, specificity, and AUROC for lung cancer diagnosis were summarized for subgroup analysis.ResultsThe systematic review identified 19 eligible studies, of which 14 used radiomics models and 5 used deep learning models. The pooled AUROC of 7 studies to determine whether patients had lung cancer was 0.83 (95% CI 0.78–0.88). The pooled AUROC of 9 studies to determine whether patients had NSCLC was 0.78 (95% CI 0.73–0.83). The pooled AUROC of the 6 studies that determined patients had malignant lung nodules was 0.79 (95% CI 0.77–0.82). The pooled AUROC of the other 6 studies that determined whether patients had lymph node metastases was 0.74 (95% CI 0.66–0.82).ConclusionThe models based on deep learning or radiomics have the potential to improve diagnostic accuracy for lung cancer staging.Systematic Review Registrationhttps://inplasy.com/inplasy-2022-3-0167/, identifier: INPLASY202230167.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is characterized by heterogeneous inflammatory endotypes of unknown etiology. Invariant natural killer T (iNKT) cells are multifunctional innate T cells that exhibit Th1-, Th2-, and Th17-like characteristics. We investigated functional relationships between iNKT cells and inflammatory subtypes of CRSwNP. Eighty patients with CRSwNP and thirty-two control subjects were recruited in this study. Flow cytometry was used to analyze the frequencies and functions of iNKT cells and their subsets in peripheral blood mononuclear cells (PBMCs) and tissues. Polyp tissue homogenates were used to study the multifunctionality of iNKT cells. iNKT cells were significantly increased in polyps (0.41%) than in control mucosa (0.12%). iNKT cells were determined in the paucigranunlocytic (n=20), eosinophilic (n=22), neutrophilic (n=23), and mixed granulocytic (n=13) phenotypes of CRSwNP. The percentages of iNKT cells and HLA-DR+PD-1+ subsets were lower in eosinophilic or mixed granulocytic polyps than those of other phenotypes. iNKT cells and subsets were enriched in polyp tissues than in matched PBMCs. The evaluation of surface markers, transcription factors, and signature cytokines indicated that the frequencies of iNKT2 and iNKT17 subsets were significantly increased in eosinophilic and neutrophilic polyps, respectively, than in the paucigranulocytic group. Moreover, the production of type 2 (partially dependent on IL-7) and type 17 (partially dependent on IL-23) iNKT cells could be stimulated by eosinophilic and neutrophilic homogenates, respectively. Our study revealed that type 2 and type 17 iNKT cells were involved in eosinophilic and neutrophilic inflammation, respectively, in CRSwNP, while different inflammatory microenvironments could modulate the functions of iNKT cells, suggesting a role of iNKT cells in feedback mechanisms and local inflammation.

Abstract In hepatocellular carcinoma (HCC), γδ T cells participate in mediating the anti‐tumour response and are linked with a positive prognosis. However, these cells can become pro‐tumoural in the tumour microenvironment (TME). We aimed to decipher the immune landscape and functional states of HCC‐infiltrating γδ T cells to provide fundamental evidence for the adoptive transfer of allogeneic Vδ2+ γδ T cells in HCC immunotherapy. We performed single‐cell RNA sequencing (scRNA‐seq) on γδ T cells derived from HCC tumours and healthy donor livers. Confocal microscopy, flow cytometry and a Luminex assay were applied to validate the scRNA‐seq findings. The γδ T cells in the HCC TME entered G2/M cell cycle arrest, and expressed cytotoxic molecules such as interferon‐gamma and granzyme B, but were functionally exhausted as indicated by upregulated gene and protein LAG3 expression. The γδ T cells in the HCC TME were dominated by the LAG3+Vδ1+ population, whereas the Vδ2+ γδ T population was greatly depleted. Moreover, glutamine metabolism of γδ T cells was markedly upregulated in the glutamine‐deficient TME. Both in vitro and in vivo experiments showed that glutamine deficiency upregulated LAG3 expression. Finally, our results indicated that ex vivo‐expanded Vδ2+ γδ T cells from healthy donor could complement the loss of T cell receptor clonality and effector functions of HCC‐derived γδ T cells. This work deciphered the dysfunctional signatures of HCC‐infiltrating γδ T cells in the HCC TME, providing scientific support for the use of allogeneic Vδ2+ γδ T cells in HCC cellular therapy.

BackgroundParkinson’s disease (PD) is not exclusively a motor disorder. Among non-motor features, patients with PD possess sensory visual dysfunctions. Depth perception and oculomotor deficits can significantly impact patients’ motor performance. Stereopsis and eye behavioral study using 3D stimuli may help determine their implications in disease status.ObjectiveThe objective of this study is to investigate stereopsis and eye movement abnormalities in PD with reliable tools and their correlation with indicators of PD severity. We hypothesize that patients with PD exhibit different eye behaviors and that these differences may correlate to the severity of motor symptoms and cognitive status.MethodsControl and PD participants were first evaluated for visual acuity, visual field, contrast acuity, and stereo perception with 2D and Titmus stereotests, followed by the assessment with a 3D active shutter system. Eye movement behaviors were assessed by a Tobii X2-60 eye tracker.ResultsScreening visual tests did not reveal any differences between the PD and control groups. With the 3D active shutter system, the PD group demonstrated significantly worse stereopsis. The preserved cognitive function was correlated to a more intact stereo function. Patients with PD had longer visual response times, with a higher number of fixations and bigger saccade amplitude, suggesting fixation stabilization difficulties. Such changes showed a positive correlation with the severity of motor symptoms and a negative correlation with normal cognitive status.ConclusionWe assessed stereopsis with a 3D active shutter system and oculomotor behaviors with the Tobii eye tracker. Patients with PD exhibit poorer stereopsis and impaired oculomotor behaviors during response time. These deficits were correlated with PD motor and cognitive status. The visual parameters may potentially serve as the clinical biomarkers for PD.

Using a combination of two-photon imaging and single-cell electrophysiology, the authors discover that associative learning induces the emergence of a unique subset of neurons in the auditory cortex, exhibiting high-rate bursting responses to the learned complex sounds but not to any of the constituents.

Holliday junctions (HJs) are DNA intermediates in genetic recombination that are resolved by nuclease, termed resolvase, to ensure genome stability. Here, the authors provide insights into the resolution process by resolving the crystal structure of the chloroplast resolvase MOC1 with HJs substrates.

Background: Artificial intelligence (AI) has great potential to detect fungal keratitis using in vivo confocal microscopy images, but its clinical value remains unclarified. A major limitation of its clinical utility is the lack of explainability and interpretability.Methods: An explainable AI (XAI) system based on Gradient-weighted Class Activation Mapping (Grad-CAM) and Guided Grad-CAM was established. In this randomized controlled trial, nine ophthalmologists (three expert ophthalmologists, three competent ophthalmologists, and three novice ophthalmologists) read images in each of the conditions: unassisted, AI-assisted, or XAI-assisted. In unassisted condition, only the original IVCM images were shown to the readers. AI assistance comprised a histogram of model prediction probability. For XAI assistance, explanatory maps were additionally shown. The accuracy, sensitivity, and specificity were calculated against an adjudicated reference standard. Moreover, the time spent was measured.Results: Both forms of algorithmic assistance increased the accuracy and sensitivity of competent and novice ophthalmologists significantly without reducing specificity. The improvement was more pronounced in XAI-assisted condition than that in AI-assisted condition. Time spent with XAI assistance was not significantly different from that without assistance.Conclusion: AI has shown great promise in improving the accuracy of ophthalmologists. The inexperienced readers are more likely to benefit from the XAI system. With better interpretability and explainability, XAI-assistance can boost ophthalmologist performance beyond what is achievable by the reader alone or with black-box AI assistance.

Eye-tracking can help decode the intricate control mechanism in human performance. In healthcare, physicians-in-training requires extensive practice to improve their healthcare skills. When a trainee encounters any difficulty in the practice, they will need feedback from experts to improve their performance. The personal feedback is time-consuming and subjected to bias. In this study, we tracked the eye movements of trainees during their colonoscopic performance in simulation. We applied deep learning algorithms to detect the eye-tracking metrics on the moments of navigation lost (MNL), a signature sign for performance difficulty during colonoscopy. Basic human eye gaze and pupil characteristics were learned and verified by the deep convolutional generative adversarial networks (DCGANs); the generated data were fed to the Long Short-Term Memory (LSTM) networks with three different data feeding strategies to classify MNLs from the entire colonoscopic procedure. Outputs from deep learning were compared to the expert’s judgment on the MNLs based on colonoscopic videos. The best classification outcome was achieved when we fed human eye data with 1000 synthesized eye data, where accuracy (90%), sensitivity (90%), and specificity (88%) were optimized. This study built an important foundation for our work of developing a self-adaptive education system for training healthcare skills using simulation.

Coal spontaneous combustion (CSC) is a disaster that seriously threatens safe production in coal mines. Revealing the mechanism of CSC can provide a theoretical basis for its prevention and control. Compared with experimental research is limited by the complexity of coal molecular structure, the quantum chemical calculation method can simplify the complex molecular structure and realize the exploration of the mechanism of CSC from the micro level. In this study, toluene and phenylacetaldehyde were used as model compounds, and the quantum chemical calculation method was adopted. The reaction processes of the methyl and aldehyde groups with oxygen were investigated with the aid of the Gaussian 09 software, using the B3LYP functional and the 6-311 + G(d,p) basis set and including the D3 dispersion correction. On this basis, the generation mechanisms of CO and CO2, two important indicator gases in the process of CSC, were explored. The calculation results show that the Gibbs free energy changes and enthalpy changes in the two reaction systems are both of negative values. Accordingly, it is judged that the reactions belong to spontaneous exothermic reactions. In the reaction processes, the activation energy of CO is less than that of CO2, indicating that CO is formed more easily in the above-two reaction processes. In addition, the variations in concentrations of important oxidation products (CO and CO2) and main active functional groups (such as methyl, carboxyl and carbonyl) with temperature were revealed through a low-temperature oxidation experiment. The experimental results verify the accuracy of the above quantum chemical reaction path. Moreover, it is also found that the generation mechanisms of CO and CO2 in coal samples with different metamorphic degrees are different. To be specific, for low-rank coal (HYH), CO and CO2 mainly come from the oxidation of alkyl side chains; for high-rank coal (CQ), CO is produced by the oxidation of alkyl side chains, and CO2 is attributed to the inherent oxygen-containing structure.

We report a case of meningitis in a neonate in China, which was caused by a novel multidrug-resistant Cronobacter sakazakii strain, sequence type 256, capsular profile K1:CA1. We identified genetic factors associated with bacterial pathogenicity and antimicrobial drug resistance in the genome and plasmids. Enhanced surveillance of this organism is warranted.

PurposeInfiltration of activated dendritic cells and inflammatory cells in cornea represents an important marker for defining corneal inflammation. Deep transfer learning has presented a promising potential and is gaining more importance in computer assisted diagnosis. This study aimed to develop deep transfer learning models for automatic detection of activated dendritic cells and inflammatory cells using in vivo confocal microscopy images.MethodsA total of 3453 images was used to train the models. External validation was performed on an independent test set of 558 images. A ground-truth label was assigned to each image by a panel of cornea specialists. We constructed a deep transfer learning network that consisted of a pre-trained network and an adaptation layer. In this work, five pre-trained networks were considered, namely VGG-16, ResNet-101, Inception V3, Xception, and Inception-ResNet V2. The performance of each transfer network was evaluated by calculating the area under the curve (AUC) of receiver operating characteristic, accuracy, sensitivity, specificity, and G mean.ResultsThe best performance was achieved by Inception-ResNet V2 transfer model. In the validation set, the best transfer system achieved an AUC of 0.9646 (PConclusionsThe deep transfer learning models provide a completely automated analysis of corneal inflammatory cellular components with high accuracy. The implementation of such models would greatly benefit the management of corneal diseases and reduce workloads for ophthalmologists.

Monitoring astrocytic Ca2+ activity is essential to understand the physiological and pathological roles of astrocytes in the brain. However, previous commonly used methods for studying astrocytic Ca2+ activities can be applied in only anesthetized or head-fixed animals, which significantly affects in vivo astrocytic Ca2+ dynamics. In the current study, we combined optic fiber recordings with genetically encoded Ca2+ indicators (GECIs) to monitor astrocytic activity in freely behaving mice. This approach enabled selective and reliable measurement of astrocytic Ca2+ activity, which was verified by the astrocyte-specific labeling of GECIs and few movement artifacts. Additionally, astrocytic Ca2+ activities induced by locomotion or footshock were stably recorded in the cortices and hippocampi of freely behaving mice. Furthermore, this method allowed for the longitudinal study of astrocytic activities over several weeks. This work provides a powerful approach to record astrocytic activity selectively, stably, and chronically in freely behaving mice.

In this paper, we propose a family of heavy tailed distributions, by incorporating a trigonometric function called the arcsine exponentiated-X family of distributions. Based on the proposed approach, a three-parameter extension of the Weibull distribution called the arcsine exponentiated-Weibull (ASE-W) distribution is studied in detail. Maximum likelihood is used to estimate the model parameters, and its performance is evaluated by two simulation studies. Actuarial measures including Value at Risk and Tail Value at Risk are derived for the ASE-W distribution. Furthermore, a numerical study of these measures is conducted proving that the proposed ASE-W distribution has a heavier tail than the baseline Weibull distribution. These actuarial measures are also estimated from insurance claims real data for the ASE-W and other competing distributions. The usefulness and flexibility of the proposed model is proved by analyzing a real-life heavy tailed insurance claims data. We construct a modified chi-squared goodness-of-fit test based on the Nikulin–Rao–Robson statistic to verify the validity of the proposed ASE-W model. The modified test shows that the ASE-W model can be used as a good candidate for analyzing heavy tailed insurance claims data.

Purpose. To compare femtosecond laser-assisted cataract surgery (FLACS) versus conventional phacoemulsification in shallow anterior chamber cataract patients with glaucoma or zonulysis. Methods. This was a single-center retrospective review of cataract surgeries in shallow anterior chamber and glaucoma patients between January 2016 and December 2018 in which a LenSx femtosecond laser was used. The outcome measures included pre- and postoperative uncorrected and corrected distance visual acuity (UDVA and CDVA), intraocular pressure (IOP), endothelial cell density (ECD), endothelial cell loss (ECL), and object scatter index (OSI). Results. One hundred and six eyes of 106 patients with a mean anterior chamber depth of 1.54 ± 0.51 mm were included in this study. Among them, 26 (23.2%) had zonulysis and 18 eyes had capsular tension ring implantation in general. The percentage of capsular tension ring implantation was statistically significantly lower in the FLACS group (P = 0.027). The UDVA, CDVA, ECD, and IOP were not statistically significant between the two groups at all time points. The postoperative ECL and OSI of the FLACS group was better than those of the conventional group (P

Aim: To examine the significance of team collaboration in the context of complex laparoscopic surgery, laparoscopic tasks performed by single operators are compared against that of dyad teams. Methods: The laparoscopic tasks require subjects to reach, grasp and transport a ring through a rollercoaster obstacle using a pair of laparoscopic graspers. The task was performed either bimanually (using both hands) or unimanually (using their preferred hands) in a dyad team. Results: Twelve participants completed all the tasks. The dyad teams recorded significantly greater number of anticipatory movements than individuals who performed the task bimanually (p

As an active microwave remote sensing device, synthetic aperture radar (SAR) has been widely used in the field of marine surveillance. However, moving ships appear defocused in SAR images, which seriously affects the classification and identification of ships. Considering the three-dimensional (3-D) rotational motions (roll, pitch, and yaw) of the navigating ship, a novel method for refocusing moving ships in SAR images based on inverse synthetic aperture radar (ISAR) technique is proposed. First, a rectangular window is used to extract the defocused ship subimage. Next, the subimage is transformed into the ISAR equivalent echo domain, and the range migration and phase error caused by the identical movement of all ship scatterers are compensated. Then, the optimal imaging time can be selected by the maximum image contrast search method. Finally, the iterative adaptive approach (IAA) is used to obtain the image with high resolution. This method has satisfactory imaging performance in both azimuth resolution and image focus, and the amount of calculation is small due to the processing of subimages. Simulated data and Gaofen-3 real SAR data are used to verify the effectiveness of the proposed method.

Road network is an important part of modern transportation. For the demands of accurate road information in practical applications such as urban planning and disaster assessment, we propose a multiscale method to extract road network from high-resolution synthetic aperture radar (SAR) images, which consists of three stages: potential road area segmentation, preliminary network generation, and road network refinement. Multiscale analysis is implemented using an image pyramid framework together with a fixed-size filter. First, a directional road detector is designed to highlight road targets in feature response maps. Subsequently, adaptive fusion is performed independently at each image scale, followed by a threshold method to produce potential road maps. Then, binary maps are decomposed according to the obtained direction information. For each connected component (CC), quality evaluation is conducted to further distinguish road segments and polynomial curve fitting is adopted as a thinning method. Multiscale information fusion is realized through the weighted sum of road curves. Finally, tensor voting and spatial regularization are employed to generate the final road network. Experiments on three TerraSAR images demonstrate the effectiveness of the proposed algorithm to extract road network completely and correctly.

Hyperspectral LiDAR (HSL) is a new remote sensing detection method with high spatial and spectral information detection ability. In the process of laser scanning, the laser echo intensity is affected by many factors. Therefore, it is necessary to calibrate the backscatter intensity data of HSL. Laser incidence angle is one of the important factors that affect the backscatter intensity of the target. This paper studied the radiometric calibration method of incidence angle effect for HSL. The reflectance of natural surfaces can be simulated as a combination of specular reflection and diffuse reflection. The linear combination of the Lambertian model and Beckmann model provides a comprehensive theory that can be applied to various surface conditions, from glossy to rough surfaces. Therefore, an adaptive threshold radiometric calibration method (Lambertian–Beckmann model) is proposed to solve the problem caused by the incident angle effect. The relationship between backscatter intensity and incident angle of HSL is studied by combining theory with experiments, and the model successfully quantifies the difference between diffuse and specular reflectance coefficients. Compared with the Lambertian model, the proposed model has higher calibration accuracy, and the average improvement rate to the samples in this study was 22.67%. Compared with the results before calibration with the incidence angle of less than 70°, the average improvement rate of the Lambertian–Beckmann model was 62.26%. Moreover, we also found that the green leaves have an obvious specular reflection effect near 650–720 nm, which might be related to the inner microstructure of chlorophyll. The Lambertian–Beckmann model was more helpful to the calibration of leaves in the visible wavelength range. This is a meaningful and a breakthrough exploration for HSL.

Cronobacter strains harboring CRISPR-Cas systems are important foodborne pathogens that cause serious neonatal infections. CRISPR typing is a new molecular subtyping method to track the sources of pathogenic bacterial outbreaks and shows a promise in typing Cronobacter, however, this molecular typing procedure using routine PCR method has not been established. Therefore, the purpose of this study was to establish such methodology, 257 isolates of Cronobacter sakazakii, C. malonaticus, and C. dublinensis were used to verify the feasibility of the method. Results showed that 161 C. sakazakii strains could be divided into 129 CRISPR types (CTs), among which CT15 (n = 7) was the most prevalent CT followed by CT6 (n = 4). Further, 65 C. malonaticus strains were divided into 42 CTs and CT23 (n = 8) was the most prevalent followed by CT2, CT3, and CT13 (n = 4). Finally, 31 C. dublinensis strains belonged to 31 CTs. There was also a relationship among CT, sequence type (ST), food types, and serotype. Compared to multi-locus sequence typing (MLST), this new molecular method has greater power to distinguish similar strains and had better accordance with whole genome sequence typing (WGST). More importantly, some lineages were found to harbor conserved ancestral spacers ahead of their divergent specific spacer sequences; this can be exploited to infer the divergent evolution of Cronobacter and provide phylogenetic information reflecting common origins. Compared to WGST, CRISPR typing method is simpler and more affordable, it could be used to identify sources of Cronobacter food-borne outbreaks, from clinical cases to food sources and the production sites.

Cronobacter spp. are foodborne pathogens that can infect and cause life-threatening diseases in all age groups, particularly in infants and immunocompromised elderly. This study aimed to investigate the prevalence, antibiotic susceptibility, and molecular characteristics of Cronobacter spp. isolates in edible mushrooms collected from 44 cities in China. In total, 668 edible mushrooms were collected from traditional retail markets and supermarkets and were analyzed by quantitative methods, PCR-based serotyping, multilocus sequence typing (MLST), and antibiotic susceptibility testing. Among the 668 samples tested, 89 (13.32%) were positive for Cronobacter spp., and the contamination levels exceeded the 110 most probable number (MPN)/g in 13.48% (12/89) of the samples. Flammulina velutipes samples had the highest contamination rate of 17.54% (37/211), whereas Hypsizygus marmoreus samples had the lowest contamination rate of 3.28% (2/61). Ten serotypes were identified among 115 isolates, of which the C. sakazakii serogroup O1 (n = 32) was the primary serotype. MLST indicated that there was quite high genetic diversity in Cronobacter spp. and 72 sequence types were identified, 17 of which were new. Notably, C. sakazakii ST148 (n = 10) was the most prevalent, followed by C. malonaticus ST7 (n = 5). Antibiotic susceptibility testing revealed that the majority of Cronobacter spp. strains were susceptible to the 16 antibiotics tested. However, a portion of isolates exhibited relatively high resistance to cephalothin, with resistance and intermediate rates of 93.91 and 6.09%, respectively. One isolate (cro300A) was multidrug-resistant, with resistance to five antibiotics. Overall, this large-scale study revealed the relatively high prevalence and high genetic diversity of Cronobacter spp. on edible mushrooms in China, indicating a potential public health concern. To our knowledge, this is the first large-scale and systematic study on the prevalence of Cronobacter spp. on edible mushrooms in China, and the findings can provide valuable information that can guide the establishment of effective measures for the control and precaution of Cronobacter spp on edible mushrooms during production processes.

The liver is one of the most important immunological organs that remains tolerogenic in homeostasis yet promotes rapid responses to pathogens in the presence of a systemic infection. The composition of leucocytes in the liver is highly distinct from that of the blood and other lymphoid organs, particularly with respect to enrichment of innate T cells, i.e., invariant NKT cells (iNKT cells) and Mucosal-Associated Invariant T cells (MAIT cells). In recent years, studies have revealed insights into their biology and potential roles in maintaining the immune-environment in the liver. As the primary liver-resident immune cells, they are emerging as significant players in the human immune system and are associated with an increasing number of clinical diseases. As such, innate T cells are promising targets for modifying host defense and inflammation of various liver diseases, including viral, autoimmune, and those of tumor origin. In this review, we emphasize and discuss some of the recent discoveries and advances in the biology of innate T cells, their recruitment and diversity in the liver, and their role in various liver diseases, postulating on their potential application in immunotherapy.

The vanadium-titanium black ceramic (VTBC) coating on all-ceramic solar collectors has both high absorptance (0.94) and high emissivity (90%). However, the thermal conductivity of ceramic is very low (1.256 W/mK). To improve the heat collection efficiency of VTBC solar collectors, this paper establishes a mathematical model based on the energy-conservation relationships under steady-state conditions and creates a corresponding computer program. Key parameters for VTBC solar collectors include the heat-removal factor, effective transmittance-absorptance product for the absorber, total heat loss coefficient, etc. Then, via experimental testing, this study proposes a reference model for domestic VTBC solar collectors in a cold location (η = 0.89 − 2.20Tm*). Last, this work analyzes the influences of fin design and transparent cover design on VTBC solar collectors individually, using the created computer program. Results show that the most effective optimization method is to increase the transmittance of the transparent cover. By increasing the transmittance from 0.93 to 0.96, this study creates an optimized VTBC solar collector theoretical model (η = 0.92 − 2.20Tm*).

Estimating directions of arrival (DOA) without knowledge of the source number is regarded as a challenging task, particularly when coherence among sources exists. Researchers have trained deep learning (DL)-based models to attack the problem of DOA estimation. However, existing DL-based methods for coherent sources do not adapt to variable source numbers or require signal independence. Herein, we put forward a new framework combining parallel DOA estimators with Toeplitz matrix reconstruction to address the problem. Each estimator is constructed by connecting a multi-label classifier to a spatial filter, which is based on convolutional-recurrent neural networks. Spatial filters divide the angle domain into several sectors, so that the following classifiers can extract the arrival directions. Assisted with Toeplitz-based method for source-number determination, pseudo or missed angles classified by the estimators will be reduced. Then, the spatial spectrum can be more accurately recovered. In addition, the proposed method is data-driven, so it is naturally immune to signal coherence. Simulation results demonstrate the predominance of the proposed method and show that the trained model is robust to imperfect circumstances such as limited snapshots, colored Gaussian noise, and array imperfections.

Cronobacter spp. is a foodborne pathogen that causes life-threatening and invasive diseases, such as necrotizing enterocolitis, meningitis, and sepsis. In this study, we aimed to investigate the prevalence, molecular characteristics and antimicrobial resistance of Cronobacter spp. in raw vegetables marketed in China. Based on dietary habits in China, 403 raw vegetables that could be eaten without additional cooking were collected. Of the 403 samples tested, 122 (30.27%) were positive for Cronobacter spp., and the contamination levels exceeded 110 most probable number (MPN)/g for 16.39% (20/122) of the samples. Coriander samples had the highest contamination rate of 52.81%, and the MPN values of 19.15% of positive coriander samples exceeded 100 MPN/g. Eleven serotypes were identified among 171 isolates, with Cronobacter sakazakii serogroup O1 (41 isolates) being the dominant serotype. Molecular characterization indicated that there was quite high genetic diversity in Cronobacter spp., and multilocus sequence typing analyses yielded 106 sequence types (STs), 55 of which were newly identified. Notably, the most prevalent ST (eight isolates) was C. malonaticus ST60, which appeared in a recent clinical infectious disease study in China. Five C. sakazakii ST4, seven C. malonaticus ST7, and three C. sakazakii ST8 confirmed as pathogenic STs in other countries were also detected in this study. Furthermore, all isolates were susceptible to amikacin, amoxicillin-clavulanic, cefepime, ciprofloxacin, and imipenem, but some isolates exhibited a high ratio of resistance to cephalothin (59.65%). In this study, the high contamination rate and the detection of pathogenic and new STs in raw vegetables indicated potential hazards to customers. To the best of our knowledge, this is the first report to provide valuable information on the contamination status of Cronobacter spp. in vegetables that can be eaten raw in China.

Cronobacter species are foodborne pathogens that can cause neonatal meningitis, necrotizing enterocolitis, and sepsis; they have unusual abilities to survive in environmental stresses such as acid stress. However, the factors involved in acid stress responses and biofilm formation in Cronobacter species are poorly understood. In this study, we investigated the role of grxB on cellular morphology, acid tolerance, surface hydrophobicity, auto-aggregation (AAg), motility, and biofilm formation in Cronobacter sakazakii. The deletion of grxB decreased resistance to acid stresses, and notably led to weaker surface hydrophobicity, AAg, and biofilm formation under normal and acid stress conditions, compared with those of the wild type strain; however, motility was unaffected. Therefore, grxB appears to contribute to the survival of C. sakazakii in acid stresses and biofilm formation. This is the first report to provide valuable evidence for the role of grxB in acid stress responses and biofilm formation in C. sakazakii.

In this paper, high-throughput RNA-sequencing (RNA-seq) was used to search for transcriptional biomarkers for β2-agonists. In combination with drug mechanisms, a smaller group of genes with higher detection accuracy was screened out. Unknown samples were first predicted by this group of genes, and liquid chromatograph tandem mass spectrometer (LC-MS/MS) was applied to positive samples to validate the biomarkers. The results of principal component analysis (PCA), hierarchical cluster analysis (HCA) and discriminant analysis (DA) indicated that the eight genes screened by high-throughput RNA-seq were able to distinguish samples in the experimental group and control group. Compared with the nine genes selected from an earlier literature, 17 genes including these nine genes were proven to have a more satisfactory effect, which validated the accuracy of gene selection by RNA-seq. Then, six key genes were selected from the 17 genes according to the variable importance in projection (VIP) value of greater than 1. The test results using the six genes and 17 genes were similar, revealing that the six genes were critical genes. By using the six genes, three positive samples possibly treated with drugs were screened out from 25 unknown samples through DA and partial least squares discriminant analysis (PLS-DA). Then, the three samples were verified by a standard method, and mapenterol was detected in a sample. Therefore, the six genes can be used as biomarkers to detect β2-agonists. Compared with the previous study, accurate detection of β2-agonists abuse using six key genes is an improvement method, which show great significance in the monitoring of β2-agonists abuse in animal husbandry.