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.     

Diagnostic accuracy of lower extremity X-ray interpretation by 'specialized' emergency nurses.

OBJECTIVES: In the quest for a cost-effective and quality-preserving solution to manage crowding in the emergency department, the possibility of deploying regular emergency nurses for the treatment of acute ankle injuries was investigated. The aim of this study is to compare the diagnostic accuracy of emergency nurses with that of senior house officers in interpreting ankle and foot radiographs. METHODS: A prospective study comparing the assessment of 60 radiographs (30 feet and 30 ankles) by 16 emergency nurses before and after an educational session was performed. Each subset of 30 radiographs contained 12 fractures, hand-picked by a radiologist to represent everyday traumatology in the emergency department. The control group consisted of eight senior house officers representing everyday expertise. The outcome of the diagnostic assessment, represented as the pooled sensitivity and specificity for both groups, was compared using Z-statistics. RESULTS: Before the training session, the specialized emergency nurse group showed a sensitivity of 0.87 (confidence interval 0.83-0.91) compared with 0.93 (confidence interval 0.88-0.96) for the control group (P = 0.05). The specificity of specialized emergency nurses was 0.87 (confidence interval 0.81-0.92) compared with 0.93 (confidence interval 0.89-0.95) for the senior house officers (P < 0.05). After the training session, specialized emergency nurse diagnostic parameters did not differ significantly from the control group, displaying a sensitivity of 0.89 (confidence interval 0.86-0.92) and specificity of 0.92 (confidence interval 0.87-0.95). CONCLUSION: Before the training session, the specialized emergency nurse group showed a significantly lower accuracy than the SHO group. After training, however, the diagnostic accuracy did not differ significantly between groups. Therefore, we conclude that emergency nurses are able to accurately interpret foot and ankle radiographs after a short educational session.     

A new transthyretin variant (Glu61Gly) associated with cardiomyopathy.

We report the identification of a new transthyretin (TTR) gene mutation and variant protein, Glu61Gly, in a 55-year-old man with progressive cardiomyopathy, mild peripheral neuropathy and bilateral carpal tunnel syndrome. A diagnosis of TTR-associated familial amyloidosis (ATTR) was considered after an endomyocardial biopsy revealed amyloid deposits in the heart of a patient who had no family history of amyloidosis and no evidence of a plasma cell dyscrasia. Serum screening for a TTR variant by isoelectric focusing (IEF) was positive and prompted further studies to identify the genetic abnormality and to characterize the amyloidogenic protein. Direct DNA sequence analysis of all four coding regions in the TTR gene demonstrated heterozygosity in exon 3. Near equal amounts of guanine (G) and adenine (A) were observed at the second base position of codon 61. The wild-type (GAG) and mutated (GGG) sequences found in codon 61 correspond to glutamic acid (Glu) and glycine (Gly) residues, amino acids which differ in mass by -72 Da. Mass spectrometric analyses of TTR immunoprecipitated from serum showed the presence of both wild-type and variant proteins. The observed mass results for the wild-type and variant proteins were consistent with the predicted values calculated from the genetic analysis data.