Video enhancement using adaptive spatio-temporal connective filter and piecewise mapping

This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC) noise filter and an adaptive piecewise mapping function (APMF). For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identify impulse noise pixels, and then incorporate it into the classical bilateral filter to form ASTC, aiming to reduce the mixture of the most two common types of noises - Gaussian and impulse noises in spatial and temporal directions. After noise removal, we enhance the video contrast with APMF based on the statistical information of frame segmentation results. The experiment results demonstrate that, for diverse low-quality videos corrupted by mixed noise, underexposure, overexposure, or any mixture of the above, the proposed system can automatically produce satisfactory results

Multi-Phase Cross-modal Learning for Noninvasive Gene Mutation Prediction in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the fourth most common cause of cancer-related death worldwide. Understanding the underlying gene mutations in HCC provides great prognostic value for treatment planning and targeted therapy. Radiogenomics has revealed an association between non-invasive imaging features and molecular genomics. However, imaging feature identification is laborious and error-prone. In this paper, we propose an end-to-end deep learning framework for mutation prediction in APOB, COL11A1 and ATRX genes using multiphasic CT scans. Considering intra-tumour heterogeneity (ITH) in HCC, multi-region sampling technology is implemented to generate the dataset for experiments. Experimental results demonstrate the effectiveness of the proposed model.Comment: Accepted version to be published in the 42nd IEEE Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2020, Montreal, Canad

A comprehensive survey of genomic alterations in gastric cancer reveals systematic patterns of molecular exclusivity and co-occurrence among distinct therapeutic targets

Objective: Gastric cancer is a major gastrointestinal malignancy for which targeted therapies are emerging as treatment options. This study sought to identify the most prevalent molecular targets in gastric cancer and to elucidate systematic patterns of exclusivity and co-occurrence among these targets, through comprehensive genomic analysis of a large panel of gastric cancers. Design: Using high-resolution single nucleotide polymorphism arrays, copy number alterations were profiled in a panel of 233 gastric cancers (193 primary tumours, 40 cell lines) and 98 primary matched gastric non-malignant samples. For selected alterations, their impact on gene expression and clinical outcome were evaluated. Results: 22 recurrent focal alterations (13 amplifications and nine deletions) were identified. These included both known targets (FGFR2, ERBB2) and also novel genes in gastric cancer (KLF5, GATA6). Receptor tyrosine kinase (RTK)/RAS alterations were found to be frequent in gastric cancer. This study also demonstrates, for the first time, that these alterations occur in a mutually exclusive fashion, with KRAS gene amplifications highlighting a clinically relevant but previously underappreciated gastric cancer subgroup. FGFR2-amplified gastric cancers were also shown to be sensitive to dovitinib, an orally bioavailable FGFR/VEGFR targeting agent, potentially representing a subtype-specific therapy for FGFR2-amplified gastric cancers. Conclusion: The study demonstrates the existence of five distinct gastric cancer patient subgroups, defined by the signature genomic alterations FGFR2 (9% of tumours), KRAS (9%), EGFR (8%), ERBB2 (7%) and MET (4%). Collectively, these subgroups suggest that at least 37% of gastric cancer patients may be potentially treatable by RTK/RAS directed therapies

Child, Maternal and Demographic Factors Influencing Caregiver-Reported Autistic Trait Symptomatology in Toddlers.

Current research on children's autistic traits in the general population relies predominantly on caregiver-report, yet the extent to which individual, caregiver or demographic characteristics are associated with informants' ratings has not been sufficiently explored. In this study, caregivers of 396 Singaporean two-year-olds from a birth cohort study completed the Quantitative Checklist for Autism in Toddlers. Children's gender, cognitive functioning and birth order, maternal age, and ethnic group membership were not significant predictors of caregiver-reported autistic traits. Poorer child language development and higher maternal depressive symptoms significantly predicted more social-communicative autistic traits, while lower maternal education predicted more behavioural autistic traits. Children's language and informants' educational level and depressive symptomatology may need to be considered in caregiver-reports of autistic traits.This research is supported by the Singapore National Research Foundation under its Translational and Clinical Research (TCR) Flagship Programme and administered by the Singapore Ministry of Health’s National Medical Research Council (NMRC), Singapore—NMRC/TCR/004-NUS/2008 and NMRC/TCR/012-NUHS/2014. Additional funding was provided by the Ministry of Education AcRF Tier 1 funding grant R581000130112 awarded to the corresponding/senior author and Singapore Institute for Clinical Sciences—A*STAR

Trends and predictions of metabolic risk factors for acute myocardial infarction: findings from a multiethnic nationwide cohort

BACKGROUND: Understanding the trajectories of metabolic risk factors for acute myocardial infarction (AMI) is necessary for healthcare policymaking. We estimated future projections of the incidence of metabolic diseases in a multi-ethnic population with AMI. METHODS: The incidence and mortality contributed by metabolic risk factors in the population with AMI (diabetes mellitus [T2DM], hypertension, hyperlipidemia, overweight/obesity, active/previous smokers) were projected up to year 2050, using linear and Poisson regression models based on the Singapore Myocardial Infarction Registry from 2007 to 2018. Forecast analysis was stratified based on age, sex and ethnicity. FINDINGS: From 2025 to 2050, the incidence of AMI is predicted to rise by 194.4% from 482 to 1418 per 100,000 population. The largest percentage increase in metabolic risk factors within the population with AMI is projected to be overweight/obesity (880.0% increase), followed by hypertension (248.7% increase), T2DM (215.7% increase), hyperlipidemia (205.0% increase), and active/previous smoking (164.8% increase). The number of AMI-related deaths is expected to increase by 294.7% in individuals with overweight/obesity, while mortality is predicted to decrease by 11.7% in hyperlipidemia, 29.9% in hypertension, 32.7% in T2DM and 49.6% in active/previous smokers, from 2025 to 2050. Compared with Chinese individuals, Indian and Malay individuals bear a disproportionate burden of overweight/obesity incidence and AMI-related mortality. INTERPRETATION: The incidence of AMI is projected to continue rising in the coming decades. Overweight/obesity will emerge as fastest-growing metabolic risk factor and the leading risk factor for AMI-related mortality. FUNDING: This research was supported by the NUHS Seed Fund (NUHSRO/2022/058/RO5+6/Seed-Mar/03) and National Medical Research Council Research Training Fellowship (MOH-001131). The SMIR is a national, ministry-funded registry run by the National Registry of Diseases Office and funded by the Ministry of Health, Singapore

Effect of trabecular bone loss on cortical strain rate during impact in an in vitro model of avian femur

BACKGROUND: Osteoporotic hip fractures occur due to loss of cortical and trabecular bone mass and consequent degradation in whole bone strength. The direct cause of most fractures is a fall, and hence, characterizing the mechanical behavior of a whole osteopenic bone under impact is important. However, very little is known about the mechanical interactions between cortical and trabecular bone during impact, and it is specifically unclear to what extent epiphyseal trabecular bone contributes to impact resistance of whole bones. We hypothesized that trabecular bone serves as a structural support to the cortex during impact, and hence, loss of a critical mass of trabecular bone reduces internal constraining of the cortex, and, thereby, decreases the impact tolerance of the whole bone. METHODS: To test this hypothesis, we conducted cortical strain rate measurements in adult chicken's proximal femora subjected to a Charpy impact test, after removing different trabecular bone core masses to simulate different osteopenic severities. RESULTS: We found that removal of core trabecular bone decreased by ~10-fold the cortical strain rate at the side opposite to impact (p < 0.01), i.e. from 359,815 ± 1799 μm/m per second (mean ± standard error) for an intact (control) specimen down to 35,997 ± 180 μm/m per second where 67% of the total trabecular bone mass (~0.7 grams in adult chicken) were removed. After normalizing the strain rate by the initial weight of bone specimens, a sigmoid relation emerged between normalized strain rate and removed mass of trabecular bone, showing very little effect on the cortex strain rate if below 10% of the trabecular mass is removed, but most of the effect was already apparent for less than 30% trabecular bone loss. An analytical model of the experiments supported this behavior. CONCLUSION: We conclude that in our in vitro avian model, loss of over 10% of core trabecular bone substantially altered the deformation response of whole bone to impact, which supports the above hypothesis and indicates that integrity of trabecular bone is critical for resisting impact loads

A new class of pluripotent stem cell cytotoxic small molecules

10.1371/journal.pone.0085039PLoS ONE93-POLN

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO