Robust information hiding in low-resolution videos with quantization index modulation in DCT-CS domain

Video information hiding and transmission over noisy channels leads to errors on video and degradation of the visual quality notably. In this paper, a video signal fusion scheme is proposed to combine sensed host signal and the hidden signal with quantization index modulation (QIM) technology in the compressive sensing (CS) and discrete cosine transform (DCT) domain. With quantization based signal fusion, a realistic solution is provided to the receiver, which can improve the reconstruction video quality without requiring significant extra channel resource. The extensive experiments have shown that the proposed scheme can effectively achieve the better trade-off between robustness and statistical invisibility for video information hiding communication. This will be extremely important for low-resolution video analytics and protection in big data era

Silencing SARS-CoV Spike protein expression in cultured cells by RNA interference

AbstractThe severe acute respiratory syndrome (SARS) has been one of the most epidemic diseases threatening human health all over the world. Based on clinical studies, SARS-CoV (the SARS-associated coronavirus), a novel coronavirus, is reported as the pathogen responsible for the disease. To date, no effective and specific therapeutic method can be used to treat patients suffering from SARS-CoV infection. RNA interference (RNAi) is a process by which the introduced small interfering RNA (siRNA) could cause the degradation of mRNA with identical sequence specificity. The RNAi methodology has been used as a tool to silence genes in cultured cells and in animals. Recently, this technique was employed in anti-virus infections in human immunodeficiency virus and hepatitis C/B virus. In this study, RNAi technology has been applied to explore the possibility for prevention of SARS-CoV infection. We constructed specific siRNAs targeting the S gene in SARS-CoV. We demonstrated that the siRNAs could effectively and specifically inhibit gene expression of Spike protein in SARS-CoV-infected cells. Our study provided evidence that RNAi could be a tool for inhibition of SARS-CoV

Effect of different binders on the electrochemical performance of metal oxide anode for lithium-ion batteries

When testing the electrochemical performance of metal oxide anode for lithium-ion batteries (LIBs), binder played important role on the electrochemical performance. Which binder was more suitable for preparing transition metal oxides anodes of LIBs has not been systematically researched. Herein, five different binders such as polyvinylidene fluoride (PVDF) HSV900, PVDF 301F, PVDF Solvay5130, the mixture of styrene butadiene rubber and sodium carboxymethyl cellulose (SBR+CMC), and polyacrylonitrile (LA133) were studied to make anode electrodes (compared to the full battery). The electrochemical tests show that using SBR+CMC and LA133 binder which use water as solution were significantly better than PVDF. The SBR+CMC binder remarkably improve the bonding capacity, cycle stability, and rate performance of battery anode, and the capacity retention was about 87% after 50th cycle relative to the second cycle. SBR+CMC binder was more suitable for making transition metal oxides anodes of LIBs

Relevance of Spatial Heterogeneity of Immune Infiltration for Predicting Risk of Recurrence After Endocrine Therapy of ER+ Breast Cancer.

Background: Despite increasing evidence supporting the clinical utility of immune infiltration in the estrogen receptor-negative (ER-) subtype, the prognostic value of immune infiltration for ER+ disease is not well defined. Methods: Quantitative immune scores of cell abundance and spatial heterogeneity were computed using a fully automated hematoxylin and eosin-stained image analysis algorithm and spatial statistics for 1178 postmenopausal patients with ER+ breast cancer treated with five years' tamoxifen or anastrozole. The prognostic significance of immune scores was compared with Oncotype DX 21-gene recurrence score (RS), PAM50 risk of recurrence (ROR) score, IHC4, and clinical treatment score, available for 963 patients. Statistical tests were two-sided. Results: Scores of immune cell abundance were not associated with recurrence-free survival. In contrast, high immune spatial scores indicating increased cell spatial clustering were associated with poor 10-year, early (0-5 years), and late (5-10 years) recurrence-free survival (Immune Hotspot: LR-χ2 = 14.06, P < .001, for 0-10 years; LR-χ2 = 6.24, P = .01, for 0-5 years; LR-χ2 = 7.89, P = .005, for 5-10 years). The prognostic value of spatial scores for late recurrence was similar to that of IHC4 and RS in both populations, but was not as strong as other tests in comparison for recurrence across 10 years. Conclusions: These results provide a missing link between tumor immunity and disease outcome in ER+ disease by examining tumor spatial architecture. The association between spatial scores and late recurrence suggests a lasting memory of protumor immunity that may impact disease progression and evolution of endocrine treatment resistance, which may be exploited for therapeutic advances.This work was supported by the Royal Marsden National Institutes of Health Biomedical Research Centre grant A105. MD and YY acknowledge support by the Royal Marsden National Institutes of Health Biomedical Research Centre. MD acknowledges a Breast Cancer Now grant (CTR-Q4-Y1). JC and IS acknowledge a CRUK grant (C569/A16891). YY acknowledges support by CRUK (C45982/A21808), Breast Cancer Now (2015NovPR638) and the Wellcome Trust (105104/Z/14/Z)

Non-invasive detection of lymphoma with circulating tumor DNA features and protein tumor markers

BackgroundAccording to GLOBOCAN 2020, lymphoma ranked as the 9th most common cancer and the 12th leading cause of cancer-related deaths worldwide. Traditional diagnostic methods rely on the invasive excisional lymph node biopsy, which is an invasive approach with some limitations. Most lymphoma patients are diagnosed at an advanced stage since they are asymptomatic at the beginning, which has significantly impacted treatment efficacy and prognosis of the disease.MethodThis study assessed the performance and utility of a newly developed blood-based assay (SeekInCare) for lymphoma early detection. SeekInCare utilized protein tumor markers and a comprehensive set of cancer-associated genomic features, including copy number aberration (CNA), fragment size (FS), end motif, and lymphoma-related virus, which were profiled by shallow WGS of cfDNA.ResultsProtein marker CA125 could be used for lymphoma detection independent of gender, and the sensitivity was 27.8% at specificity of 98.0%. After integrating these multi-dimensional features, 77.8% sensitivity was achieved at specificity of 98.0%, while its NPV and PPV were both more than 92% for lymphoma detection. The sensitivity of early-stage (I-II) lymphoma was up to 51.3% (47.4% and 55.0% for stage I and II respectively). After 2 cycles of treatment, the molecular response of SeekInCare was correlated with the clinical outcome.ConclusionIn summary, a blood-based assay can be an alternative to detect lymphoma with adequate performance. This approach becomes particularly valuable in cases where obtaining tissue biopsy is difficult to obtain or inconclusive

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring

The evolution of lung cancer and impact of subclonal selection in TRACERx

Lung cancer is the leading cause of cancer-associated mortality worldwide. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse

Genomic–transcriptomic evolution in lung cancer and metastasis

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic–transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary–metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis