Search

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://medicaldecathlon.com/. In addition, both data and online evaluation are accessible via https://competitions.codalab.org/competitions/17094.

ObjectiveTo trace Bacillus cereus （B. cereus） from foodborne disease outbreaks toidentify pathogens and cut off transmission.MethodsPulsed-field gel electrophoresis （PFGE） was performed. Furthermore， 12 isolates of B. cereus were subjected to PFGE. Subsequently， whole-genome sequencing （WGS） analysis was conducted on ten of these isolates. The WGS data were analyzed and assembled using BioNumerics software. Multilocus sequence typing （MLST）， virulence gene profiles， and single nucleotide polymorphisms （SNPs） were analyzed using assembled sequences.ResultsPFGE analysis classified the 12 B. cereus strains into nine pulsotypes. The three B. cereus isolates with the same PFGE pattern belonged to ST1435， and there were only three SNPs in the three ST1435 strains. The two B. cereus isolates with the same PFGE patterns were ST24 with one SNP between them， and the two ST24 isolates harbored hlbACD. These results indicate that the B. cereus isolates belonged to the same clone. The remaining three B. cereus strains also contained hlbACD.ConclusionFood-borne illness events caused by B. cereus are complex and are sources of contamination. Therefore， it will be necessary to strengthen the hygiene surveillance of food sources and workers and to pay more attention to cleaning and disinfecting environments and facilities， which will be important for preventing and controlling foodborne diseases.

Genomic instability induced by DNA damage and improper DNA damage repair is one of the main causes of malignant transformation and tumorigenesis. DNA double strand breaks (DSBs) are the most detrimental form of DNA damage, and nonhomologous end-joining (NHEJ) mechanisms play dominant and priority roles in initiating DSB repair. A well-studied oncogene, the ubiquitin ligase Cullin 4A (CUL4A), is reported to be recruited to DSB sites in genomic DNA, but whether it regulates NHEJ mechanisms of DSB repair is unclear. Here, we discovered that the CUL4A-DTL ligase complex targeted the DNA-PKcs protein in the NHEJ repair pathway for nuclear degradation. Overexpression of either CUL4A or DTL reduced NHEJ repair efficiency and subsequently increased the accumulation of DSBs. Moreover, we demonstrated that overexpression of either CUL4A or DTL in normal cells led to genomic instability and malignant proliferation. Consistent with the in vitro findings, in human precancerous lesions, CUL4A expression gradually increased with increasing malignant tendency and was negatively correlated with DNA-PKcs and positively correlated with γ-H2AX expression. Collectively, this study provided strong evidence that the CUL4A-DTL axis increases genomic instability and enhances the subsequent malignant transformation of normal cells by inhibiting NHEJ repair. These results also suggested that CUL4A may be a prognostic marker of precancerous lesions and a potential therapeutic target in cancer.

Interaction between light and magnetism in magneto-optical (MO) nanophotonic devices has been actively studied in the past few years. The recent development of MO all-dielectric resonators and metasurfaces has led to the emergence of various novel MO phenomena that were not observed in their bulk counterparts. For example, a large s-polarized transverse MO Kerr effect can be observed at magnetic resonance wavelength, which cannot exist in the bare MO films. We review recent developments in nanophotonic devices based on MO materials and focus on different modes and related MO effects in nanophotonic structures with emphasis on recently discovered new MO phenomena in magnetoplasmonics and all-dielectric nanostructures, such as dark mode, all-dielectric Mie resonance and waveguide mode. Further, we discuss the potential applications of these nanostructures for biological/chemical sensing, magnetic field sensing, and magnetic field-controlled active and nonreciprocal metasurfaces.

Designing a high‐performance cathode is essential for the development of proton‐conducting solid oxide fuel cells (H‐SOFCs), and nanocomposite cathodes have proven to be an effective means of achieving this. However, the mechanism behind the nanocomposite cathodes' remarkable performance remains unknown. Doping the Co element into BaZrO3 can result in the development of BaCoO3 and BaZr0.7Co0.3O3 nanocomposites when the doping concentration exceeds 30%, according to the present study. The construction of the BaCoO3/BaZr0.7Co0.3O3 interface is essential for the enhancement of the cathode catalytic activity, as demonstrated by thin‐film studies using pulsed laser deposition to simulate the interface of the BCO and BZCO individual particles and first‐principles calculations to predict the oxygen reduction reaction steps. Eventually, the H‐SOFC with a BaZr0.4Co0.6O3 cathode produces a record‐breaking power density of 2253 mW cm−2 at 700°C. [ABSTRACT FROM AUTHOR]

In this study, we present a new forward polarimetric radar operator called the Accurate and Efficient Radar Operator designed by ZheJiang University (ZJU-AERO). This operator was designed to interface with the numerical weather prediction (NWP) model of the global forecast system/regional mesoscale model of the China Meteorological Administration (CMA-GFS/MESO). The main objective of developing this observation operator was to assimilate observations from the precipitation measurement radar (PMR). It is also capable of simulating the ground-based radar's polarimetric radar variables, excluding the Doppler variables such as radial velocity and spectrum width. To calculate the hydrometeor optical properties of ZJU-AERO, we utilize the invariant-imbedding T-matrix (IITM) method, which can handle non-spherical and inhomogeneous hydrometeor particles in the atmosphere. The optical database of ZJU-AERO was designed with a multi-layered architecture to ensure the flexibility in hydrometeor morphology and orientation specifications while maintaining operational efficiency. Specifically, three levels of databases are created that store the single-scattering properties for different shapes at discrete sizes for various fixed orientations, integrated single-scattering properties over shapes and orientations, and bulk-scattering properties incorporating the size average, respectively. In this work, we elaborate on the design concepts, physical basis, and hydrometeor specifications of ZJU-AERO. Additionally, we present a case study demonstrating the application of ZJU-AERO in simulating the radar observations of Typhoon Haishen. [ABSTRACT FROM AUTHOR]

It has been a big challenge to distinguish synchronous multiple primary lung cancer (sMPLC) from primary lung cancer with intrapulmonary metastases (IPM). We aimed to assess the clinical application of dynamic 18F-FDG PET/CT in patients with multiple lung cancer nodules. We enrolled patients with multiple pulmonary nodules who had undergone dynamic 18F-FDG PET/CT and divided them into sMPLC and IPM groups based on comprehensive features. The SUVmax, fitted K i value based on dynamic scanning, and corresponding maximum diameter ( D max ) from the two largest tumors were determined in each patient. We determined the absolute between-tumor difference of SU V max / D max and K i / D max (Δ SU V max / D max ; Δ K i / D max ) and assessed the between-group differences. Further, the diagnostic accuracy was evaluated by ROC analysis and the correlation between Δ SU V max / D max and Δ K i / D max from all groups was determined. There was no significant difference for Δ SU V max / D max between the IPM and sMPLC groups, while the IPM group had a significantly higher Δ K i / D max than the sMPLC group. The AUC of Δ K i / D max for differentiating sMPLC from IPM was 0.80 (cut-off value of K i = 0.0059 , sensitivity 79%, specificity 75%, p < 0.001). There was a good correlation (Pearson r = 0.91 , 95% CI: 0.79-0.96, p < 0.0001) between Δ SU V max / D max and Δ K i / D max in the IPM group but not in the sMPLC group (Pearson r = 0.45 , p > 0.05). Dynamic 18F-FDG PET/CT could be a useful tool for distinguishing sMPLC from IPM. K i calculation based on Patlak graphic analysis could be more sensitive than SUVmax in discriminating IPM from sMPLC in patients with multiple lung cancer nodules. [ABSTRACT FROM AUTHOR]

The AI-based Nonspherical Aerosol Optical Scheme (AI-NAOS) is a newly developed aerosol optical module that improves the representation of aerosol optical properties for radiative transfer simulations in atmospheric models. It incorporates the nonsphericity and inhomogeneity (NSIH) of internally mixed aerosol particles through a deep learning method. Specifically, the AI-NAOS considers black carbon (BC) as fractal aggregates and models soil dust (SD) as super-spheroids, encapsulated partially or completely with hygroscopic aerosols such as sulfate, nitrate, and aerosol water. To obtain AI-NAOS, a database of the optical properties for the models was constructed using the invariant imbedding T-matrix method (IITM), and deep neural networks (DNN) were trained based on this database. In this study, the AI-NAOS was integrated into the mesoscale version 5.1 of Global/Regional Assimilation and Prediction System with Chinese Unified Atmospheric Chemistry Environment (GRAPES_Meso5.1/CUACE). Real-case simulations were conducted during a winter with high pollution, comparing BC aerosols evaluated using three schemes with spherical aerosol models (external-mixing, core-shell, and volume-mixing) and the AI-NAOS scheme. The results showed that NSIH effect led to a moderate estimation of absorbing aerosol optical depth (AAOD) and obvious changes in aerosol radiative effects, short-wave heating rates, temperature profiles, and boundary layer height. The AAOD values based on three spherical schemes were 70.4 %, 125.3 %, and 129.3 % over Sichuan Basin, benchmarked to the AI-NAOS results. Compared to the external-mixing scheme, the direct radiative effect (DRE) induced by the NSIH effect reached +1.6 W/m2 at the top-of-atmosphere (TOA) and -2.9 W/m2 at surface. The NSIH effect could enhance the short-wave heating rate, reaching 20 %. Thus, the warming effect at 700 hPa and the cooling effect on the ground were strengthened by 21 % and 13 %, reaching +0.04 and –0.10 K, which led to a reduction in the height of the Planetary Boundary Layer (PBL) by –11 meters. In addition, the precipitation was inhibited by the NSIH effect, causing a 15 % further decrease. Therefore, the NSIH effects demonstrated their non-negligible impacts and highlighted the importance of incorporating them into chemical weather models. [ABSTRACT FROM AUTHOR]

Mineral dust particles are nonspherical and inhomogeneous; however, they are often simplified as homogeneous spherical particles for retrieving the refractive indices from laboratory measurements of scattering and absorption coefficients. The retrieved refractive indices are then employed for computing the optical properties of spherical or nonspherical dust model particles with downstream applications. This study aims to theoretically investigate uncertainties involved in the aforementioned rationale based on numerical simulations and focuses on a wavelength range of 355–1064 nm. Initially, the optical properties of nonspherical and inhomogeneous dust aerosols are computed as baseline cases. Subsequently, the scattering and absorption coefficients of homogeneous spheres and super-spheroids are computed at various refractive indices and compared with those of inhomogeneous dust aerosols to determine the dust refractive index. To mimic the real laboratory measurement, the size distribution of the baseline case is assumed to be unknown and determined through a process akin to using optical particle counters for sizing. The resulting size distribution differs from the original one of the baseline cases. The impact of discrepancies in size distributions on retrieving the dust refractive index is also investigated. Our findings reveal that these discrepancies affect scattering and absorption coefficients, presenting challenges in accurately determining the refractive index, particularly for the real parts. Additionally, the retrieved refractive indices are noted to vary with particle size primarily due to differences in size distribution, with imaginary parts decreasing as the particle size increases. A comparison between sphere models and super-spheroid models shows that the former tend to underestimate the imaginary parts, leading to an overestimation of single-scattering albedo. This study underscores the importance of employing consistent nonspherical models for both refractive index retrieval and subsequent optical simulation in downstream applications. Nevertheless, the impact of refractive index uncertainties on the asymmetry factor and phase matrix is found to be minimal, with particle shape playing a more significant role than differences in the imaginary parts of the dust refractive index. [ABSTRACT FROM AUTHOR]

Plasmacytoma variant translocation 1 (PVT1) is an lncRNA that plays vital roles in breast cancer (BC) pathogenesis. Increasing evidence suggests that miRNAs that reside in the PVT1 locus are the main driver of the oncogenic roles of PVT1 in cancer. However, the oncogenic role and underlying mechanism of miR-1204, located in the PVT1 locus, in human cancer is still unclear. In this study, we discovered that increased expression of miR-1204 is associated with poor prognosis in BC. Moreover, miR-1204 promotes proliferation, epithelial-mesenchymal transition and invasion of BC cells both in vitro and in vivo. Mechanistic investigations demonstrated that VDR is a novel target gene of miR-1204. Interference of VDR restored miR-1204-mediated BC cell proliferation, tumorigenesis, and metastasis. Collectively, our results demonstrated that the miR-1204-VDR pathway exerts oncogenic effects in BC with potential therapeutic applications in blocking BC development and progression.

Exposure to thirdhand smoke (THS) is a recently described health concern that arises in many indoor environments. However, the carcinogenic potential of THS, a critical consideration in risk assessment, remains untested. Here we investigated the effects of short-term early exposure to THS on lung carcinogenesis in A/J mice. Forty weeks after THS exposure from 4 to 7 weeks of age, the mice had increased incidence of lung adenocarcinoma, tumor size and, multiplicity, compared with controls. In vitro studies using cultured human lung cancer cells showed that THS exposure induced DNA double-strand breaks and increased cell proliferation and colony formation. RNA sequencing analysis revealed that THS exposure induced endoplasmic reticulum stress and activated p53 signaling. Activation of the p53 pathway was confirmed by an increase in its targets p21 and BAX. These data indicate that early exposure to THS is associated with increased lung cancer risk.

Identification of reliable predictive biomarkers and new therapeutic targets is a critical step for significant improvement in patient outcomes. Here, we developed a multi-step bioinformatics analytic strategy to mine large omics and clinical data to build a prognostic scoring system for predicting the overall survival (OS) of lung adenocarcinoma (LuADC) patients. In latter we first identified 1327 significantly and robustly deregulated genes, 600 of which were significantly associated with the OS of LuADC patients. Gene co-expression network analysis revealed the biological functions of these 600 genes in normal lung and LuADCs, which were found to be enriched for cell cycle-related processes, blood vessel development, cell-matrix adhesion and metabolic processes. Finally, we implemented a multiple resampling method combined with Cox regression analysis to identify a 27-gene signature associated with OS, and then created a prognostic scoring system based on this signature. This scoring system robustly predicted OS of LuADC patients in 100 sampling test sets and was further validated in four independent LuADC cohorts. In addition, in comparison to other existing prognostic gene signatures published in the literature, our signature was significantly superior in predicting OS of LuADC patients. In summary, our multi-omics and clinical data integration study created a 27-gene prognostic risk score that can predict OS of LuADC patients independent of age, gender and clinical stage. This score could guide therapeutic selection and allow stratification in clinical trials.

Lung cancer still remains the leading cause of cancer-related death worldwide. It is an urgent need for development of novel therapeutic agents to improve current treatment of this disease. Here we investigate whether the effective component formula of traditional Chinese Medicine could serve as new potential therapeutic drugs to treat lung cancer. We optimize the most effective component formula of Salvia miltiorrhiza and Panax Ginseng (FMG), which is composed of Salvianolic acid A, 20(S)-Ginsenoside and Ginseng polysaccharide. We discovered that FMG selectively inhibited lung cancer cell proliferation and induced apoptosis but had no any cytotoxic effects on normal lung epithelial BEAS-2B cells. Moreover, FMG inhibited lung cancer cell migration and invasion. Mechanistically, we found that FMG significantly promoted p-PTEN expression and subsequently inhibited PI3K/AKT signaling pathway. The phosphatase activity of PTEN protein was increased after FMG bound to PTEN protein, indicating that PTEN is one of the FMG targeted proteins. In addition, FMG regulated expression of some marker proteins relevant to cell apoptosis, migration and invasion. Collectively, these results provide mechanistic insight into the anti-NSCLC of FMG by enhancing the phosphatase activity of PTEN, and suggest that FMG could be as a potential option for lung cancer treatment.

Many DDB1-CUL4 associated factors (DCAFs) have been identified and serve as substrate receptors. Although the oncogenic role of CUL4A has been well established, specific DCAFs involved in cancer development remain largely unknown. Here we infer the potential impact of 19 well-defined DCAFs in human lung adenocarcinomas (LuADCs) using integrative omics analyses, and discover that mRNA levels of DTL, DCAF4, 12 and 13 are consistently elevated whereas VBRBP is reduced in LuADCs compared to normal lung tissues. The transcriptional levels of DCAFs are significantly correlated with their gene copy number variations. SKIP2, DTL, DCAF6, 7, 8, 13 and 17 are frequently gained whereas VPRBP, PHIP, DCAF10, 12 and 15 are frequently lost. We find that only transcriptional level of DTL is robustly, significantly and negatively correlated with overall survival across independent datasets. Moreover, DTL-correlated genes are enriched in cell cycle and DNA repair pathways. We also identified that the levels of 25 proteins were significantly associated with DTL overexpression in LuADCs, which include significant decreases in protein level of the tumor supressor genes such as PDCD4, NKX2-1 and PRKAA1. Our results suggest that different CUL4-DCAF axis plays the distinct roles in LuADC development with possible relevance for therapeutic target development.