The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Integrative analysis of 111 reference human epigenomes

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

This Perspective explores and explains the fundamental dogma of nanoparticle delivery to tumours and answers two central questions: ‘how many nanoparticles accumulate in a tumour?’ and ‘how does this number affect the clinical translation of nanomedicines?’

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Analysis of nanoparticle delivery to tumours

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique-cross-trait LD Score regression-for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

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An atlas of genetic correlations across human diseases and traits.

AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

This contribution describes a novel non-contact fluorescence optical tomography scheme which utilizes multiple area illumination patterns, to reduce the illposedness of the inverse problem involved in recovering interior fluorescence yield distribution in biological tissue from boundary fluorescence measurements. Multiple excitation source illumination patterns are simulated by Gaussian beam sources scanning the simulated tissue phantom surface. Area measurements of fluorescence amplitude and phase are collected on the illumination plane. Multiple measurement data sets generated by scanning the excitation sources are processed simultaneously to generate the interior fluorescence distribution in tissue by implementing a dual adaptive finite element based fluorescence tomography algorithm in a parallel framework suitable for multiprocessor computers. Image reconstructions for multiple fluorescent targets (5 mm diameter) embedded in a 512 ml simulated tissue phantom are demonstrated.

Non-contact fluorescence optical tomography with scanning area illumination

Internet of Things has gained popularity nowadays and it has been estimated that in next decade more than 95% of the embedded devices would be connected to the internet. This will pose the challenge for the security in IoT network. The device authentication is one of the important tasks in IoT. PUF (Physical Unclonable Function) is powerful security tool which realizes a fingerprint of the hardware. It provides a unique hardware-intrinsic key depending on the specific device properties. However, PUF is useful for device authentication due its less area overhead. The simple device authentication protocol is proposed for IoT application using PUF. The performance parameters in terms of power and area are also evaluated and they shows adaptability of our proposed device authentication scheme in tiny IoT nodes.

Device Authentication in IoT using Reconfigurable PUF

A novel, competent, effortless, low leakage CMOS differential amplifier is explored with minimum deformation and proper power utilization. The proposed circuit can also represent a CMOS analog front-end (AFE) circuit for portable biomedical signals acquisition system. The proposed circuit is designed with the intention of supply the power either from VDD to VOUT or from VSS to VOUT. The proposed circuit has high CMRR. It means that the common mode voltage gain is minimum and differential mode voltage gain is high. The circuit is designed in such a way that the power supply couldn’t reach from VDD to VSS directly i.e. the driving power of the circuit couldn’t be short circuited. Due to this, the proposed circuit behaves like a perfect differential amplifier. Competent and speculative combinations of CMOS logic are utilized with cross coupled by Gate terminals of NMOS transistors to provide the better functionality of proposed differential amplifier circuit. The proposed circuit with unique combination of MOS has provided better performance parameters. Due to utilization of modified MOS structure with pull-up and pull-down stacked transistors, gain factor of differential amplifier is increased up to 5 dB with compare to other differential amplifier circuits and leakage power dissipation is reduced up to 49%. Proposed CMOS based differential amplifier is optimized at 45 nm CMOS technology. The simulations have been performed using cadence analog virtuoso spectre simulator. The experimental implementations have been done for analysis of leakage power and efficiency with better consistency through the proposed circuit.

Low leakage and high CMRR CMOS differential amplifier for biomedical application

Herein we present a comparison of Monte Carlo, radiative transport (RT), and diffusion based forward models for implementation into small animal optical tomography algorithm. The simulations show that the unique RT solver can accurately predict the time-dependent propagation of excitation and emission photons in diffuse as well as transport limited systems. Furthermore, the need for the accurate modeling of incident excitation illumination and the acceptance angle of the detector is demonstrated

Comparison of radiative transport, monte carlo, and diffusion forward models for small animal optical tomography

1346P Comparison of clinical outcomes of patients with METΔex14 NSCLC treated with first-line capmatinib in the GEOMETRY mono-1 study with those of a cohort of real-world patients

Amit Joshi

Papers

Non-contact fluorescence optical tomography with scanning area illumination

Device Authentication in IoT using Reconfigurable PUF

Low leakage and high CMRR CMOS differential amplifier for biomedical application

Comparison of radiative transport, monte carlo, and diffusion forward models for small animal optical tomography

1346P Comparison of clinical outcomes of patients with METΔex14 NSCLC treated with first-line capmatinib in the GEOMETRY mono-1 study with those of a cohort of real-world patients