The stochastic digital human is now enrolling for in silico imaging trials -- Methods and tools for generating digital cohorts

Randomized clinical trials, while often viewed as the highest evidentiary bar by which to judge the quality of a medical intervention, are far from perfect. In silico imaging trials are computational studies that seek to ascertain the performance of a medical device by collecting this information entirely via computer simulations. The benefits of in silico trials for evaluating new technology include significant resource and time savings, minimization of subject risk, the ability to study devices that are not achievable in the physical world, allow for the rapid and effective investigation of new technologies and ensure representation from all relevant subgroups. To conduct in silico trials, digital representations of humans are needed. We review the latest developments in methods and tools for obtaining digital humans for in silico imaging studies. First, we introduce terminology and a classification of digital human models. Second, we survey available methodologies for generating digital humans with healthy and diseased status and examine briefly the role of augmentation methods. Finally, we discuss the trade-offs of four approaches for sampling digital cohorts and the associated potential for study bias with selecting specific patient distributions

Solving the Simplest Theory of Quantum Gravity

We solve what is quite likely the simplest model of quantum gravity, the worldsheet theory of an infinitely long, free bosonic string in Minkowski space. Contrary to naive expectations, this theory is non-trivial. We illustrate this by constructing its exact factorizable S-matrix. Despite its simplicity, the theory exhibits many of the salient features expected from more mature quantum gravity models, including the absence of local off-shell observables, a minimal length, a maximum achievable (Hagedorn) temperature, as well as (integrable relatives of) black holes. All these properties follow from the exact S-matrix. We show that the complete finite volume spectrum can be reconstructed analytically from this S-matrix with the help of the thermodynamic Bethe Ansatz. We argue that considered as a UV complete relativistic two-dimensional quantum field theory the model exhibits a new type of renormalization group flow behavior, "asymptotic fragility". Asymptotically fragile flows do not originate from a UV fixed point.Comment: 32+4 pages, 1 figure, v2: typos fixed, published versio

Exhaled nitric oxide in a population-based study of Southern California Schoolchildren

<p>Abstract</p> <p>Background</p> <p>Determinants of exhaled nitric oxide (FeNO) need to be understood better to maximize the value of FeNO measurement in clinical practice and research. Our aim was to identify significant predictors of FeNO in an initial cross-sectional survey of southern California schoolchildren, part of a larger longitudinal study of asthma incidence.</p> <p>Methods</p> <p>During one school year, we measured FeNO at 100 ml/sec flow, using a validated offline technique, in 2568 children of age 7–10 yr. We estimated online (50 ml/sec flow) FeNO using a prediction equation from a separate smaller study with adjustment for offline measurement artifacts, and analyzed its relationship to clinical and demographic characteristics.</p> <p>Results</p> <p>FeNO was lognormally distributed with geometric means ranging from 11 ppb in children without atopy or asthma to 16 ppb in children with allergic asthma. Although effects of atopy and asthma were highly significant, ranges of FeNO for children with and without those conditions overlapped substantially. FeNO was significantly higher in subjects aged > 9, compared to younger subjects. Asian-American boys showed significantly higher FeNO than children of all other sex/ethnic groups; Hispanics and African-Americans of both sexes averaged slightly higher than non-Hispanic whites. Increasing height-for-age had no significant effect, but increasing weight-for-height was associated with decreasing FeNO.</p> <p>Conclusion</p> <p>FeNO measured offline is a useful biomarker for airway inflammation in large population-based studies. Further investigation of age, ethnicity, body-size, and genetic influences is needed, since they may contribute to substantial variation in FeNO.</p

First-line therapy with gemcitabine and paclitaxel in locally, recurrent or metastatic breast cancer: A phase II study

BACKGROUND: This phase II study evaluated the efficacy and safety of gemcitabine (G) plus paclitaxel (T) as first-line therapy in recurrent or metastatic breast cancer. METHODS: Patients with locally, recurrent or metastatic breast cancer and no prior chemotherapy for metastatic disease received G 1200 mg/m(2 )on days 1 and 8, and T 175 mg/m(2 )on day 1 (before G) every 21 days for a maximum of 10 cycles. RESULTS: Forty patients, 39 metastatic breast cancer and 1 locally-advanced disease, were enrolled. Their median age was 61.5 years, and 85% had a World Health Organization performance status (PS) of 0 or 1. Poor prognostic factors at baseline included visceral involvement (87.5%) and ≥2 metastatic sites (70%). Also, 27 (67.5%) patients had prior adjuvant chemotherapy, 25 of which had prior anthracyclines. A total of 220 cycles (median 6; range, 1–10) were administered. Of the 40 enrolled patients, 2 had complete response and 12 partial response, for an overall response rate of 35.0% for intent-to-treat population. Among 35 patients evaluable for efficacy the response rate was 40%. Additional 14 patients had stable disease, and 7 had progressive disease. The median duration of response was 12 months; median time to progression, 7.2 months; median survival, 25.7 months. Common grade 3/4 toxicities were neutropenia in 17 (42.5%) patients each, grade 3 leukopenia in 19 (47.5%), and grade 3 alopecia in 30 (75.0%) patients; 1 (2.5%) patient had grade 4 thrombocytopenia. CONCLUSION: GT exhibited encouraging activity and tolerable toxicity as first-line therapy in metastatic breast cancer. Phase III trials for further evaluation are ongoing

Particulate air pollution, systemic oxidative stress, inflammation, and atherosclerosis

Air pollution has been associated with significant adverse health effects leading to increased overall morbidity and mortality of worldwide significance. Epidemiological studies have shown that the largest portion of air pollution-related mortality is due to cardiovascular diseases, predominantly those of ischemic nature. Human studies suggest an association with atherosclerosis and increasing experimental animal data support that this association is likely to be causal. While both gasses and particles have been linked to detrimental health effects, more evidence implicates the particulate matter (PM) components as major responsible for a large portion of the proatherogenic effects. Multiple experimental approaches have revealed the ability of PM components to trigger and/or enhance free radical reactions in cells and tissues, both ex vivo as well as in vivo. It appears that exposure to PM leads to the development of systemic prooxidant and proinflammatory effects that may be of great importance in the development of atherosclerotic lesions. This article reviews the epidemiological studies, experimental animal, and cellular data that support the association of air pollutants, especially the particulate components, with systemic oxidative stress, inflammation, and atherosclerosis. It also reviews the use of transcriptomic studies to elucidate molecular pathways of importance in those systemic effects

Acceleration of tissue phase mapping with sensitivity encoding at 3T

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to investigate the impact of sensitivity encoding on the quantitative assessment of cardiac motion in black blood cine tissue phase mapping (TPM) sequences. Up to now whole volume coverage of the heart is still limited by the long acquisition times. Therefore, a significant increase in imaging speed without deterioration of quantitative motion information is indispensable.</p> <p>Methods</p> <p>20 volunteers were enrolled in this study. Each volunteer underwent myocardial short-axis TPM scans with different SENSE acceleration factors. The influence of SENSE acceleration on the measured motion curves was investigated.</p> <p>Results</p> <p>It is demonstrated that all TPM sequences with SENSE acceleration have only minimum influence on the motion curves. Even with a SENSE factor of four, the decrease in the amplitude of the motion curve was less than 3%. No significant difference was observed for the global correlation coefficient and deviation between the motion curves obtained by the reproducibility and the SENSE accelerated measurements.</p> <p>Conclusions</p> <p>It is feasible to accelerate myocardial TPM measurements with SENSE factors up to 4 without losing substantial information of the motion pattern.</p

Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival

<p>Abstract</p> <p>Background</p> <p>Glioblastoma is a complex multifactorial disorder that has swift and devastating consequences. Few genes have been consistently identified as prognostic biomarkers of glioblastoma survival. The goal of this study was to identify general and clinical-dependent biomarker genes and biological processes of three complementary events: lifetime, overall and progression-free glioblastoma survival.</p> <p>Methods</p> <p>A novel analytical strategy was developed to identify general associations between the biomarkers and glioblastoma, and associations that depend on cohort groups, such as race, gender, and therapy. Gene network inference, cross-validation and functional analyses further supported the identified biomarkers.</p> <p>Results</p> <p>A total of 61, 47 and 60 gene expression profiles were significantly associated with lifetime, overall, and progression-free survival, respectively. The vast majority of these genes have been previously reported to be associated with glioblastoma (35, 24, and 35 genes, respectively) or with other cancers (10, 19, and 15 genes, respectively) and the rest (16, 4, and 10 genes, respectively) are novel associations. <it>Pik3r1</it>, <it>E2f3, Akr1c3</it>, <it>Csf1</it>, <it>Jag2</it>, <it>Plcg1</it>, <it>Rpl37a</it>, <it>Sod2</it>, <it>Topors</it>, <it>Hras</it>, <it>Mdm2, Camk2g</it>, <it>Fstl1</it>, <it>Il13ra1</it>, <it>Mtap </it>and <it>Tp53 </it>were associated with multiple survival events.</p> <p>Most genes (from 90 to 96%) were associated with survival in a general or cohort-independent manner and thus the same trend is observed across all clinical levels studied. The most extreme associations between profiles and survival were observed for <it>Syne1</it>, <it>Pdcd4</it>, <it>Ighg1</it>, <it>Tgfa</it>, <it>Pla2g7</it>, and <it>Paics</it>. Several genes were found to have a cohort-dependent association with survival and these associations are the basis for individualized prognostic and gene-based therapies. <it>C2</it>, <it>Egfr</it>, <it>Prkcb</it>, <it>Igf2bp3</it>, and <it>Gdf10 </it>had gender-dependent associations; <it>Sox10</it>, <it>Rps20</it>, <it>Rab31</it>, and <it>Vav3 </it>had race-dependent associations; <it>Chi3l1</it>, <it>Prkcb</it>, <it>Polr2d</it>, and <it>Apool </it>had therapy-dependent associations. Biological processes associated glioblastoma survival included morphogenesis, cell cycle, aging, response to stimuli, and programmed cell death.</p> <p>Conclusions</p> <p>Known biomarkers of glioblastoma survival were confirmed, and new general and clinical-dependent gene profiles were uncovered. The comparison of biomarkers across glioblastoma phases and functional analyses offered insights into the role of genes. These findings support the development of more accurate and personalized prognostic tools and gene-based therapies that improve the survival and quality of life of individuals afflicted by glioblastoma multiforme.</p