White blood cell count and risk of incident lung cancer in the UK Biobank

Background The contribution of measurable immunological/inflammatory parameters to lung cancer development remains unclear, particularly among never-smokers. We investigated the relationship between total and differential white blood cell (WBC) counts and incident lung cancer risk overall and among subgroups defined by smoking status and sex in the United Kingdom (UK). Methods We evaluated 424,407 adults aged 37-73 years from the UK Biobank. Questionnaires, physical measurements, and blood were administered/collected at baseline in 2006-2010. Complete blood cell counts were measured using standard methods. Lung cancer diagnoses and histological classifications were obtained from cancer registries. Multivariable Cox regression models were used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) of incident lung cancer in relation to quartiles (Q) of total WBC and subtype-specific counts, with Q1 as the reference. Results There were 1,493 incident cases diagnosed over an average 7-year follow-up. Overall, the highest quartile of total WBC count was significantly associated with elevated lung cancer risk (HRQ4=1.67, 95% CI:1.41-1.98). Among women, increased risks were found in current-smokers (ncases/n=244/19,464, HRQ4=2.15, 95% CI:1.46-3.16), former-smokers (ncases/n=280/69,198, HRQ4=1.75, 95% CI:1.24-2.47), and never-smokers without environmental tobacco smoke exposure (ncases/n=108/111,294, HRQ4=1.93, 95% CI:1.11-3.35). Among men, stronger associations were identified in current-smokers (ncases/n=329/22,934, HRQ4=2.95, 95% CI:2.04-4.26) and former-smokers (ncases/n= 358/71,616, HRQ4=2.38, 95% CI:1.74-3.27) but not in never-smokers. Findings were similar for lung adenocarcinoma and squamous cell carcinoma and were driven primarily by elevated neutrophil fractions. Conclusions Elevated WBCs could potentially be one of many important markers for increased lung cancer risk, especially among never-smoking women and ever-smoking men

A multiple exp-function method for nonlinear differential equations and its application

A multiple exp-function method to exact multiple wave solutions of nonlinear partial differential equations is proposed. The method is oriented towards ease of use and capability of computer algebra systems, and provides a direct and systematical solution procedure which generalizes Hirota's perturbation scheme. With help of Maple, an application of the approach to the $3+1$ dimensional potential-Yu-Toda-Sasa-Fukuyama equation yields exact explicit 1-wave and 2-wave and 3-wave solutions, which include 1-soliton, 2-soliton and 3-soliton type solutions. Two cases with specific values of the involved parameters are plotted for each of 2-wave and 3-wave solutions.Comment: 12 pages, 16 figure

SERS biosensors based on cucurbituril-mediated nanoaggregates for wastewater-based epidemiology

Hierarchical self-assembly of nanoparticles (NPs) mediated by macrocyclic molecules, cucurbiturils (CBs), provides a facile method to fabricate surface-enhanced Raman spectroscopy (SERS) sensors for potential applications in biosensing and environmental monitoring. In contrast to conventional techniques for wastewater-based epidemiology (WBE), CB-NP SERS sensors offer great opportunities for on-site quantification of trace chemical and biological markers due to its high sensitivity, selectivity, reproducibility, multiplexing capability and tolerance against contamination. The working principles of the CB-Au NP nanocomposites including fabrication, sensing mechanisms and structure-property relationships are explained while the design guidelines and selected examples of CB-Au NP SERS sensors are discussed. The review concludes by highlighting recent advances in this area and exploring opportunities in the context of WBE

Leukemia-related chromosomal loss detected in hematopoietic progenitor cells of benzene-exposed workers.

Benzene exposure causes acute myeloid leukemia and hematotoxicity, shown as suppression of mature blood and myeloid progenitor cell numbers. As the leukemia-related aneuploidies monosomy 7 and trisomy 8 previously had been detected in the mature peripheral blood cells of exposed workers, we hypothesized that benzene could cause leukemia through the induction of these aneuploidies in hematopoietic stem and progenitor cells. We measured loss and gain of chromosomes 7 and 8 by fluorescence in situ hybridization in interphase colony-forming unit-granulocyte-macrophage (CFU-GM) cells cultured from otherwise healthy benzene-exposed (n=28) and unexposed (n=14) workers. CFU-GM monosomy 7 and 8 levels (but not trisomy) were significantly increased in subjects exposed to benzene overall, compared with levels in the control subjects (P=0.0055 and P=0.0034, respectively). Levels of monosomy 7 and 8 were significantly increased in subjects exposed to <10 p.p.m. (20%, P=0.0419 and 28%, P=0.0056, respectively) and ≥ 10 p.p.m. (48%, P=0.0045 and 32%, 0.0354) benzene, compared with controls, and significant exposure-response trends were detected (P(trend)=0.0033 and 0.0057). These data show that monosomies 7 and 8 are produced in a dose-dependent manner in the blood progenitor cells of workers exposed to benzene, and may be mechanistically relevant biomarkers of early effect for benzene and other leukemogens

A variational approach to the stochastic aspects of cellular signal transduction

Cellular signaling networks have evolved to cope with intrinsic fluctuations, coming from the small numbers of constituents, and the environmental noise. Stochastic chemical kinetics equations govern the way biochemical networks process noisy signals. The essential difficulty associated with the master equation approach to solving the stochastic chemical kinetics problem is the enormous number of ordinary differential equations involved. In this work, we show how to achieve tremendous reduction in the dimensionality of specific reaction cascade dynamics by solving variationally an equivalent quantum field theoretic formulation of stochastic chemical kinetics. The present formulation avoids cumbersome commutator computations in the derivation of evolution equations, making more transparent the physical significance of the variational method. We propose novel time-dependent basis functions which work well over a wide range of rate parameters. We apply the new basis functions to describe stochastic signaling in several enzymatic cascades and compare the results so obtained with those from alternative solution techniques. The variational ansatz gives probability distributions that agree well with the exact ones, even when fluctuations are large and discreteness and nonlinearity are important. A numerical implementation of our technique is many orders of magnitude more efficient computationally compared with the traditional Monte Carlo simulation algorithms or the Langevin simulations.Comment: 15 pages, 11 figure