Electromagnetic Decays of Heavy Baryons

The electromagnetic decays of the ground state baryon multiplets with one heavy quark are calculated using Heavy Hadron Chiral Perturbation Theory. The M1 and E2 amplitudes for S^{*}--> S gamma, S^{*} --> T gamma and S --> T gamma are separately computed. All M1 transitions are calculated up to O(1/Lambda_chi^2). The E2 amplitudes contribute at the same order for S^{*}--> S gamma, while for S^{*} --> T gamma they first appear at O(1/(m_Q \Lambda_\chi^2)) and for S --> T gamma are completely negligible. The renormalization of the chiral loops is discussed and relations among different decay amplitudes are derived. We find that chiral loops involving electromagnetic interactions of the light pseudoscalar mesons provide a sizable enhancement of these decay widths. Furthermore, we obtain an absolute prediction for the widths of Xi^{0'(*)}_c--> Xi^{0}_c gamma and Xi^{-'(*)}_b--> Xi^{-}_b gamma. Our results are compared to other estimates existing in the literature.Comment: 17 pages, 3 figures, submitted to Phys. Rev.

LHC Discovery Potential for Non-Standard Higgs Bosons in the 3b Channel

In a variety of well motivated models, such as two Higgs Doublet Models (2HDMs) and the Minimal Supersymmetric Standard Model (MSSM), there are neutral Higgs bosons that have significantly enhanced couplings to b-quarks and tau leptons in comparison to those of the SM Higgs. These so called non-standard Higgs bosons could be copiously produced at the LHC in association with b quarks, and subsequently decay into b-quark pairs. However, this production channel suffers from large irreducible QCD backgrounds. We propose a new search strategy for non-standard neutral Higgs bosons at the 7 TeV LHC in the 3b's final state topology. We perform a simulation of the signal and backgrounds, using state of the art tools and methods for different sets of selection cuts, and conclude that neutral Higgs bosons with couplings to b-quarks of about 0.3 or larger, and masses up to 400 GeV, could be seen with a luminosity of 30 fb^{-1}. In the case of the MSSM we also discuss the complementarity between the 3b channel and the inclusive tau pair channel in exploring the supersymmetric parameter space.Comment: 14 pages, 3 figures, 4 tables, references added, published versio

Probing exotic phenomena at the interface of nuclear and particle physics with the electric dipole moments of diamagnetic atoms: A unique window to hadronic and semi-leptonic CP violation

The current status of electric dipole moments of diamagnetic atoms which involves the synergy between atomic experiments and three different theoretical areas -- particle, nuclear and atomic is reviewed. Various models of particle physics that predict CP violation, which is necessary for the existence of such electric dipole moments, are presented. These include the standard model of particle physics and various extensions of it. Effective hadron level combined charge conjugation (C) and parity (P) symmetry violating interactions are derived taking into consideration different ways in which a nucleon interacts with other nucleons as well as with electrons. Nuclear structure calculations of the CP-odd nuclear Schiff moment are discussed using the shell model and other theoretical approaches. Results of the calculations of atomic electric dipole moments due to the interaction of the nuclear Schiff moment with the electrons and the P and time-reversal (T) symmetry violating tensor-pseudotensor electron-nucleus are elucidated using different relativistic many-body theories. The principles of the measurement of the electric dipole moments of diamagnetic atoms are outlined. Upper limits for the nuclear Schiff moment and tensor-pseudotensor coupling constant are obtained combining the results of atomic experiments and relativistic many-body theories. The coefficients for the different sources of CP violation have been estimated at the elementary particle level for all the diamagnetic atoms of current experimental interest and their implications for physics beyond the standard model is discussed. Possible improvements of the current results of the measurements as well as quantum chromodynamics, nuclear and atomic calculations are suggested.Comment: 46 pages, 19 tables and 16 figures. A review article accepted for EPJ

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Risk accelerators in disasters : insights from the typhoon Haiyan response on humanitarian information management and decision support

Published version of a chapter in the book: Advanced Information Systems Engineering. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-07881-6_2Modern societies are increasingly threatened by disasters that require rapid response through ad-hoc collaboration among a variety of actors and organizations. The complexity within and across today's societal, economic and environmental systems defies accurate predictions and assessments of damages, humanitarian needs, and the impact of aid. Yet, decision-makers need to plan, manage and execute aid response under conditions of high uncertainty while being prepared for further disruptions and failures. This paper argues that these challenges require a paradigm shift: instead of seeking optimality and full efficiency of procedures and plans, strategies should be developed that enable an acceptable level of aid under all foreseeable eventualities. We propose a decision- and goal-oriented approach that uses scenarios to systematically explore future developments that may have a major impact on the outcome of a decision. We discuss to what extent this approach supports robust decision-making, particularly if time is short and the availability of experts is limited. We interlace our theoretical findings with insights from experienced humanitarian decision makers we interviewed during a field research trip to the Philippines in the aftermath of Typhoon Haiyan

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Evolutionary characterization of lung adenocarcinoma morphology in TRACERx

Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and ‘tumor spread through air spaces’ were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma

Genomic–transcriptomic evolution in lung cancer and metastasis

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. 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 study2,3. 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