An Analysis of the Controversial Exclusion Clauses under Korean Automobile Insurance Policy

The interpretation of the Supreme Court that the exclusion clause of unlicensed driving cannot be applied to the case where there is consent of the approved insured only may leave room for criticism. It is submitted that the Supreme Court neglected the principle of the insurance law on the exclusion clause of unlicensed driving. The interpretation of it shall be interpreted more flexibly. Accordingly, as regards the case where the control or management of the insured was possible, it shall be interpreted it as including all situations with the cases under the control or management of the registered insured, approved insured and persons driving vehicles for them. In other words, if unlicensed driving was done under the express or implied consent of the registered insured, approved insured or drivers for them, the exclusion clause of unlicensed driving should be applied, depending on the detailed situation. The reason is that they all are in the position of insured under the automobile insurance policy, and persons in such positions would have the obligation not to permit driving by an unlicensed driver. According to the current provisions of Article 732-2 and Article 633 of Commercial Law, it has to be interpreted as an imperative provision that does not permit exclusion of the insurer's liability on grossly negligent accidents in personal accident insurance. However, there is a need of re-review of Article 633 that makes the relatively imperative provision for Article 732-2 of Commercial Law due to several problems including the possibility of unconstitutionality. Namely, unlike the current legal provision, the relatively imperative regulation should be made only in cases needed individually for each relevant article and shall review the ways to exclude Article 732-2 of Commercial Law from the subject of relative imperative provision

Analysis on the current interpretations of the duty of disclosure in English insurance and marine insurance contracts.

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN007796 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

A lab-on-a-disc platform enables serial monitoring of individual CTCs associated with tumor progression during EGFR-targeted therapy for patients with NSCLC

Rationale: Unlike traditional biopsy, liquid biopsy, which is a largely non-invasive diagnostic and monitoring tool, can be performed more frequently to better track tumors and mutations over time and to validate the efficiency of a cancer treatment. Circulating tumor cells (CTCs) are considered promising liquid biopsy biomarkers; however, their use in clinical settings is limited by high costs and a low throughput of standard platforms for CTC enumeration and analysis. In this study, we used a label-free, high-throughput method for CTC isolation directly from whole blood of patients using a standalone, clinical setting-friendly platform. Methods: A CTC-based liquid biopsy approach was used to examine the efficacy of therapy and emergent drug resistance via longitudinal monitoring of CTC counts, DNA mutations, and single-cell-level gene expression in a prospective cohort of 40 patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Results: The change ratio of the CTC counts was associated with tumor response, detected by CT scan, while the baseline CTC counts did not show association with progression-free survival or overall survival. We achieved a 100% concordance rate for the detection of EGFR mutation, including emergence of T790M, between tumor tissue and CTCs. More importantly, our data revealed the importance of the analysis of the epithelial/mesenchymal signature of individual pretreatment CTCs to predict drug responsiveness in patients. Conclusion: The fluid-assisted separation technology disc platform enables serial monitoring of CTC counts, DNA mutations, as well as unbiased molecular characterization of individual CTCs associated with tumor progression during targeted therapy

mHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics

Hyperspectral imaging acquires data in both the spatial and frequency domains to offer abundant physical or biological information. However, conventional hyperspectral imaging has intrinsic limitations of bulky instruments, slow data acquisition rate, and spatiospectral tradeoff. Here we introduce hyperspectral learning for snapshot hyperspectral imaging in which sampled hyperspectral data in a small subarea are incorporated into a learning algorithm to recover the hypercube. Hyperspectral learning exploits the idea that a photograph is more than merely a picture and contains detailed spectral information. A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from an RGB image. Hyperspectral learning is capable of recovering full spectroscopic resolution in the hypercube, comparable to high spectral resolutions of scientific spectrometers. Hyperspectral learning also enables ultrafast dynamic imaging, leveraging ultraslow video recording in an off-the-shelf smartphone, given that a video comprises a time series of multiple RGB images. To demonstrate its versatility, an experimental model of vascular development is used to extract hemodynamic parameters via statistical and deep-learning approaches. Subsequently, the hemodynamics of peripheral microcirculation is assessed at an ultrafast temporal resolution up to a millisecond, using a conventional smartphone camera. This spectrally informed learning method is analogous to compressed sensing; however, it further allows for reliable hypercube recovery and key feature extractions with a transparent learning algorithm. This learning-powered snapshot hyperspectral imaging method yields high spectral and temporal resolutions and eliminates the spatiospectral tradeoff, offering simple hardware requirements and potential applications of various machine-learning techniques.Comment: This paper will appear in PNAS Nexu

Copy number analysis of whole-genome data using BIC-seq2 and its application to detection of cancer susceptibility variants

Whole-genome sequencing data allow detection of copy number variation (CNV) at high resolution. However, estimation based on read coverage along the genome suffers from bias due to GC content and other factors. Here, we develop an algorithm called BIC-seq2 that combines normalization of the data at the nucleotide level and Bayesian information criterion-based segmentation to detect both somatic and germline CNVs accurately. Analysis of simulation data showed that this method outperforms existing methods. We apply this algorithm to low coverage whole-genome sequencing data from peripheral blood of nearly a thousand patients across eleven cancer types in The Cancer Genome Atlas (TCGA) to identify cancer-predisposing CNV regions. We confirm known regions and discover new ones including those covering KMT2C, GOLPH3, ERBB2 and PLAG1. Analysis of colorectal cancer genomes in particular reveals novel recurrent CNVs including deletions at two chromatin-remodeling genes RERE and NPM2. This method will be useful to many researchers interested in profiling CNVs from whole-genome sequencing data

Depression and suicide risk prediction models using blood-derived multi-omics data

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression???17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment

Single-cell RNA sequencing reveals distinct cellular factors for response to immunotherapy targeting CD73 and PD-1 in colorectal cancer

Background Although cancer immunotherapy is one of the most effective advanced-stage cancer therapies, no clinically approved cancer immunotherapies currently exist for colorectal cancer (CRC). Recently, programmed cell death protein 1 (PD-1) blockade has exhibited clinical benefits according to ongoing clinical trials. However, ongoing clinical trials for cancer immunotherapies are focused on PD-1 signaling inhibitors such as pembrolizumab, nivolumab, and atezolizumab. In this study, we focused on revealing the distinct response mechanism for the potent CD73 ectoenzyme selective inhibitor AB680 as a promising drug candidate that functions by blocking tumorigenic ATP/adenosine signaling in comparison to current therapeutics that block PD-1 to assess the value of this drug as a novel immunotherapy for CRC. Methods To understand the distinct mechanism of AB680 in comparison to that of a neutralizing antibody against murine PD-1 used as a PD-1 blocker, we performed single-cell RNA sequencing of CD45(+) tumor-infiltrating lymphocytes from untreated controls (n=3) and from AB680-treated (n=3) and PD-1-blockade-treated murine CRC in vivo models. We also used flow cytometry, Azoxymethane (AOM)/Dextran Sulfate Sodium (DSS) models, and in vitro functional assays to validate our new findings. Results We initially observed that the expressions of Nt5e (a gene for CD73) and Entpd1 (a gene for CD39) affect T cell receptor (TCR) diversity and transcriptional profiles of T cells, thus suggesting their critical roles in T cell exhaustion within tumor. Importantly, PD-1 blockade significantly increased the TCR diversity of Entpd1-negative T cells and Pdcd1-positive T cells. Additionally, we determined that AB680 improved the anticancer functions of immunosuppressed cells such as Treg and exhausted T cells, while the PD-1 blocker quantitatively reduced Malat1(high) Treg and M2 macrophages. We also verified that PD-1 blockade induced Treg depletion in AOM/DSS CRC in vivo models, and we confirmed that AB680 treatment caused increased activation of CD8(+) T cells using an in vitro T cell assay. Conclusions The intratumoral immunomodulation of CD73 inhibition is distinct from PD-1 inhibition and exhibits potential as a novel anticancer immunotherapy for CRC, possibly through a synergistic effect when combined with PD-1 blocker treatments. This study may contribute to the ongoing development of anticancer immunotherapies targeting refractory CRC

Circulating Tumor Cell Clusters Are Cloaked with Platelets and Correlate with Poor Prognosis in Unresectable Pancreatic Cancer

Simple Summary: Despite recent advances, some patients with pancreatic cancer are refractory to treatment and the disease rapidly progresses, resulting in early death. The potential prognostic value of circulating tumor cells (CTCs) has been demonstrated in other cancer types, but the clinical validity in pancreatic cancer remains elusive. Here, we show that CTC clusters, which show mesenchymal characteristics and platelet marker expression, are highly correlated with poor prognosis in patients with unresectable pancreatic cancer.Circulating tumor cells (CTCs) are known to be heterogeneous and clustered with tumor-associated cells, such as macrophages, neutrophils, fibroblasts, and platelets. However, their molecular profile and clinical significance remain largely unknown. Thus, we aimed to perform a comprehensive gene expression analysis of single CTCs and CTC clusters in patients with pancreatic cancer and to identify their potential clinical relevance to provide personalized medicine. Epitope-independent, rapid (> 3 mL of whole blood/min) isolation of single CTCs and CTC clusters was achieved from a prospective cohort of 16 patients with unresectable pancreatic cancer using a centrifugal microfluidic device. Forty-eight mRNA expressions of individual CTCs and CTC clusters were analyzed to identify pancreatic CTC phenotype. CTC clusters had a larger proportion of mesenchymal expression than single CTCs (p = 0.0004). The presence of CTC clusters positively correlated with poor prognosis (progression-free survival, p = 0.0159; overall survival, p = 0.0186). Furthermore, we found that most CTCs in these patients (90.7%) were cloaked with platelets and found the presence of a positive correlation between the increase in CTC clusters and rapid disease progression during follow-ups. Efficient CTC cluster isolation and analysis techniques will enhance the understanding of complex tumor metastasis processes and can facilitate personalized disease management

Welfare Genome Project: A Participatory Korean Personal Genome Project With Free Health Check-Up and Genetic Report Followed by Counseling.

The Welfare Genome Project (WGP) provided 1,000 healthy Korean volunteers with detailed genetic and health reports to test the social perception of integrating personal genetic and healthcare data at a large-scale. WGP was launched in 2016 in the Ulsan Metropolitan City as the first large-scale genome project with public participation in Korea. The project produced a set of genetic materials, genotype information, clinical data, and lifestyle survey answers from participants aged 20-96. As compensation, the participants received a free general health check-up on 110 clinical traits, accompanied by a genetic report of their genotypes followed by genetic counseling. In a follow-up survey, 91.0% of the participants indicated that their genetic reports motivated them to improve their health. Overall, WGP expanded not only the general awareness of genomics, DNA sequencing technologies, bioinformatics, and bioethics regulations among all the parties involved, but also the general public's understanding of how genome projects can indirectly benefit their health and lifestyle management. WGP established a data construction framework for not only scientific research but also the welfare of participants. In the future, the WGP framework can help lay the groundwork for a new personalized healthcare system that is seamlessly integrated with existing public medical infrastructure