Temperature-controlled power modulation compensates for heterogeneous nanoparticle distributions: a computational optimization analysis for magnetic hyperthermia

Purpose: To study, with computational models, the utility of power modulation to reduce tissue temperature heterogeneity for variable nanoparticle distributions in magnetic nanoparticle hyperthermia.

Methods: Tumour and surrounding tissue were modeled by elliptical two- and three-dimensional computational phantoms having six different nanoparticle distributions. Nanoparticles were modeled as point heat sources having amplitude-dependent loss power. The total number of nanoparticles was fixed, and their spatial distribution and heat output were varied. Heat transfer was computed by solving the Pennes’ bioheat equation using finite element methods (FEM) with temperature-dependent blood perfusion. Local temperature was regulated using a proportional-integral-derivative (PID) controller. Tissue temperature, thermal dose and tissue damage were calculated. The required minimum thermal dose delivered to the tumor was kept constant, and heating power was adjusted for comparison of both the heating methods.

Results: Modulated power heating produced lower and more homogeneous temperature distributions than did constant power heating for all studied nanoparticle distributions. For a concentrated nanoparticle distribution, located off-center within the tumor, the maximum temperatures inside the tumor were 16% lower for modulated power heating when compared to constant power heating. This resulted in less damage to surrounding normal tissue. Modulated power heating reached target thermal doses up to nine-fold more rapidly when compared to constant power heating.

Conclusions: Controlling the temperature at the tumor-healthy tissue boundary by modulating the heating power of magnetic nanoparticles demonstrably compensates for a variable nanoparticle distribution to deliver effective treatment.     

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case–control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR_1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR_1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR_1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR_1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR_1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.     

Alterations of paraoxonase and platelet-activating factor acetylhydrolase activities in patients on peritoneal dialysis.

OBJECTIVE: The more atherogenic lipid profile seen in peritoneal dialysis (PD) patients cannot fully explain the increased incidence of atherosclerosis in this population. Oxidative modification of low-density lipoproteins (LDL) is considered to play a central role in the atherogenic process, whereas high-density lipoprotein (HDL) protects LDL from oxidation. On the other hand, it has been suggested that the LDL and HDL of PD patients are more resistant to oxidation than those of control subjects, while PD-HDL equally protects LDL from oxidation compared to control-HDL. Two HDL-associated enzymes have been shown to protect both LDL and HDL from oxidation: paraoxonase (PON1) and HDL-associated platelet-activating factor acetylhydrolase (HDL-PAF-AH). Furthermore, low PON1 activity and high total plasma PAF-AH concentration, which represents mainly the LDL-associated enzyme, have been shown to be independent risk factors for coronary artery events in the general population. However, there are limited data regarding possible alterations of these enzymes in PD patients. The aim of our study was to examine the possible alterations of PON1 and PAF-AH activities in patients undergoing PD. DESIGN: A cross-sectional study. SETTING: A university medical center. PARTICIPANTS: 56 PD patients of Caucasian origin and 86 matched controls were studied. MEASUREMENTS: In all subjects, serum PON1 activity toward paraoxon (paraoxonase) and phenylacetate (arylesterase), as well as total serum and HDL-PAF-AH activities were measured; PON1 genetic polymorphisms known to influence PON1 activity (Q192R and M55L) were determined. RESULTS: The PD patients exhibited significantly increased serum PON1 (paraoxonase) and PON1 (arylesterase) activities compared to controls, regardless of the PON1 polymorphisms or the levels of HDL cholesterol. Additionally, PD patients had significantly elevated activities of total serum PAF-AH and HDL-PAF-AH, independently of the levels of LDL or HDL cholesterol. The ratio of HDL-PAF-AH/ total PAF-AH, which has recently been suggested to be a potential marker of atherogenicity, was decreased in these patients compared to controls. Moreover, no difference in the prevalence of PON1 polymorphisms between PD patients and controls was found. CONCLUSION: The elevated activities of PON1 and HDL-PAF-AH could explain the increased resistance of PD-HDL to oxidation; the higher activity of total PAF-AH and the decreased HDL-PAF-AH/ total PAF-AH ratio could contribute to the increased incidence of atherosclerosis in these patients.     

Housing satisfaction for persons with psychiatric disabilities

Provision of residential services to people with mental illness has assumed increasing importance since deinstitutionalization and as community‐ based services have increased. This large‐scale multisite study of housing programs specifically for persons with mental illness examines one of the factors that lead to successful residential tenure for persons with serious mental illness. To date, the Lehman Quality of Life Scale has been used primarily to assess satisfaction with housing in studies of residential services. This article reports on a new measure of housing satisfaction. This new 25‐item instrument was developed, field tested in a variety of housing settings across the country, and analyzed for reliability and validity by a group of housing researchers and clinicians. The implications of using this instrument for future evaluation and research on housing for persons with mental illness are examined. © 2003 Wiley Periodicals, Inc. J Comm Psychol 31: 581–590, 2003.     

Meta-analysis of the association of beta2-adrenergic receptor polymorphisms with asthma phenotypes

BACKGROUND: Two common polymorphisms of the beta2-adrenergic receptor gene (Arg16Gly and Gln27Glu ) have been extensively studied for their possible association with asthma-related phenotypes, but the results of individual studies have been inconclusive. OBJECTIVE: We aimed to integrate quantitatively the available evidence on the association of the Arg16Gly and the Gln27Glu polymorphisms with asthma, nocturnal asthma, asthma severity, and bronchial hyperresponsiveness. METHODS: Meta-analysis of case-control and cohort studies using random effects models. RESULTS: A total of 28 studies were included in the meta-analysis. The summary estimates suggested that neither the Gly16 nor the Glu27 allele contributes to asthma susceptibility overall (odds ratio [OR], 1.01; 95% CI, 0.90-1.13; and OR, 0.95; 95% CI, 0.83-1.09, respectively) or to bronchial hyperresponsiveness (OR, 0.90; 95% CI, 0.77-1.05; and OR, 1.07; 95% CI, 0.94-1.22, respectively). There was a strong association of Gly16 with nocturnal asthma (OR, 2.20; 95% CI, 1.56-3.11) and a less strong association with severe or moderate rather than milder asthma (OR, 1.42; 95% CI, 1.04-1.94). No such effects were seen for the Glu27 allele (OR, 1.02; 95% CI, 0.74-1.40; and OR, 0.82; 95% CI, 0.59-1.14, respectively). Moreover, there was evidence that Gly16 homozygotes had a much higher risk for nocturnal asthma (OR, 5.15; 95% CI, 2.44-10.84) and asthma severity (OR, 2.84; 95% CI, 1.62-4.96) than the Arg16 homozygotes. CONCLUSION: The Gly16 allele of the beta2-adrenergic receptor gene predisposes to nocturnal asthma, and this may also explain the association with asthma severity. Neither polymorphism modulates the risk for bronchial hyperresponsiveness or mild asthma.     

Thermodynamics of ternary mixtures of random copolymers

A most general formalism based on the Lattice-Fluid theory of polymer solutions is presented for multicomponent mixtures of random copolymers which may consist of any number of different types of monomers. Particular emphasis is given to the phase stability in these mixtures. Equations for the spinodals and the critical points are presented. The formalism is subsequently applied to a number of interesting cases of ternary (co)polymer mixtures such as: mixtures of three random copolymers with the same monomers A and B but in different proportions (A B + A B + A B) mixtures of homopolymers A_m and B_n with the random copolymer A_i B_j, and mixtures of the random copolymers (A B + A B + A C). The effect of temperature on the phase behavior of these systems is discussed. The agreement of theoretical predictions with available experimental information is satisfactory. Because of its simplicity, the model may be used as a tool for studying multicomponent mixtures exhibiting lower or upper critical solution temperature behavior.