A new statistic for the analysis of association between trait and polymorphic marker loci

Inference for detecting the existence of an association between a diallelic marker and a trait locus is based on the chi-squared statistic with one degree of freedom. For polymorphic markers with m alleles (2), three approaches are mainly used in practice. First, one may use Pearson's chi-squared statistic with m-1 degrees of freedom (d.f.) but this leads to a loss in test power. Second, one can select an allele to be the most associated and then collapse the other allele categories into a single class. This reduces in a biased way, the locus to a diallelic system. Third, one may use the Terwilliger [J.D. Terwilliger, Am. J. Hum. Genet. 56 (1995) 777] likelihood ratio statistic which has a non-standard unknown limiting probability distribution. In this paper, we propose a new statistic, L(D), based on the second testing approach. We derive the asymptotic probability distribution of L(D) in an easy way. Simulation studies show that L(D) is more powerful than Pearson's chi-squared statistic with m-1 d.f.     

Circadian periodicity of urinary volume, creatinine and 5-hydroxyindole acetic acid excretion in healthy Indians

The circadian periodicity of urinary output, creatinine (Cr) and 5-hydroxyindole acetic acid (5-HIAA) excretion was studied under near-tropical conditions in 130 healthy volunteers (65 men and 65 women, 16-75 years of age) with a diurnal activity from about 06:30 to about 22:00 and nocturnal rest. These volunteers were divided into 4 groups, 16-30, 31-45, 46-60 and 61-75 years of age, comprising 20, 20, 15 and 10 participants of each gender, respectively. A marked circadian rhythm was recorded for urine volume, Cr and 5-HIAA excretion in healthy Indians of different ages. The acrophase tended to be delayed in the older age group. The relative amplitude decreased with advancing age, notably in women. Overall, men produced a larger urine volume as compared to women. Excretions of Cr and 5-HIAA in healthy Indian volunteers of different ages may be influenced by diet, societal relations, climate and/or geographic location. The contribution of such factors in metabolism and degradation warrants further study.     

Life-cycle modification in open oceans accounts for genome variability in a cosmopolitan phytoplankton

Emiliania huxleyi is the most abundant calcifying plankton in modern oceans with substantial intraspecific genome variability and a biphasic life cycle involving sexual alternation between calcified 2N and flagellated 1N cells. We show that high genome content variability in Emiliania relates to erosion of 1N-specific genes and loss of the ability to form flagellated cells. Analysis of 185 E. huxleyi strains isolated from world oceans suggests that loss of flagella occurred independently in lineages inhabiting oligotrophic open oceans over short evolutionary timescales. This environmentally linked physiogenomic change suggests life cycling is not advantageous in very large/diluted populations experiencing low biotic pressure and low ecological variability. Gene loss did not appear to reflect pressure for genome streamlining in oligotrophic oceans as previously observed in picoplankton. Life-cycle modifications might be common in plankton and cause major functional variability to be hidden from traditional taxonomic or molecular markers.     

Monitoring depth of anesthesia using combination of EEG measure and hemodynamic variables

Monitoring depth of anesthesia (DOA) via vital signs is a major ongoing challenge for anesthetists. A number of electroencephalogram (EEG)-based monitors such as the Bispectral (BIS) index have been proposed. However, anesthesia is related to central and autonomic nervous system functions whereas the EEG signal originates only from the central nervous system. This paper proposes an automated DOA detection system which consists of three steps. Initially, we introduce multiscale modified permutation entropy index which is robust in the characterization of the burst suppression pattern and combine multiscale information. This index quantifies the amount of complexity in EEG data and is computationally efficient, conceptually simple and artifact resistant. Then, autonomic nervous system activity is quantified with heart rate and mean arterial pressure which are easily acquired using routine monitoring machine. Finally, the extracted features are used as input to a linear discriminate analyzer (LDA). The method is validated with data obtained from 25 patients during the cardiac surgery requiring cardiopulmonary bypass. The experimental results indicate that an overall accuracy of 89.4 % can be obtained using combination of EEG measure and hemodynamic variables, together with LDA to classify the vital sign into awake, light, surgical and deep anesthetised states. The results demonstrate that the proposed method can estimate DOA more effectively than the commercial BIS index with a stronger artifact-resistance.     

MR Angiography Follow-Up 10 Years after Cryptogenic Nonperimesencephalic Subarachnoid Hemorrhage

ObjectivesLong-term magnetic resonance angiography (MRA) follow-up studies regarding cryptogenic nonperimesencephalic subarachnoid hemorrhage (nSAH) are scarce. This single-centre study identified all patients with angiographically verified cryptogenic nSAH from 1998 to 2007: The two main objectives were to prospectively assess the incidence of de novo aneurysm with 3.0-MRI years after cryptogenic nSAH in patients without evidence for further hemorrhage, and retrospectively assess patient demographics and outcome.MethodsFrom prospectively maintained report databases all patients with angiographically verified cryptogenic nSAH were identified. 21 of 29 patients received high-resolution 3T-MRI including time-of-flight and contrast-enhanced angiography, 10.2 ± 2.8 years after cryptogenic nSAH. MRA follow-up imaging was compared with initial digital subtraction angiography (DSA) and CT/MRA. Post-hemorrhage images were related to current MRI with reference to persistent lesions resulting from delayed cerebral ischemia (DCI) and post-hemorrhagic siderosis. Patient-based objectives were retrospectively abstracted from clinical databases.Results29 patients were identified with cryptogenic nSAH, 17 (59%) were male. Mean age at time of hemorrhage was 52.9 ± 14.4 years (range 4 – 74 years). 21 persons were available for long-term follow-up. In these, there were 213.5 person years of MRI-follow-up. No de novo aneurysm was detected. Mean modified Rankin Scale (mRS) during discharge was 1.28. Post-hemorrhage radiographic vasospasm was found in three patients (10.3%); DCI-related lesions occurred in one patient (3.4%). Five patients (17.2%) needed temporary external ventricular drainage; long-term CSF shunt dependency was necessary only in one patient (3.4%). Initial DSA retrospectively showed a 2 x 2 mm aneurysm of the right distal ICA in one patient, which remained stable. Post-hemorrhage siderosis was detected 8.1 years after the initial bleeding in one patient (4.8%).ConclusionPatients with cryptogenic nSAH have favourable outcomes and do not exhibit higher risks for de novo aneurysms. Therefore the need for long-term follow up after cryptogenic nSAH is questionable.     

Effect of Calcifications on Breast Ultrasound Shear Wave Elastography: An Investigational Study

PurposeTo investigate the effects of macrocalcifications and clustered microcalcifications associated with benign breast masses on shear wave elastography (SWE).MethodsSuperSonic Imagine (SSI) and comb-push ultrasound shear elastography (CUSE) were performed on three sets of phantoms to investigate how calcifications of different sizes and distributions influence measured elasticity. To demonstrate the effect in vivo, three female patients with benign breast masses associated with mammographically-identified calcifications were evaluated by CUSE.ResultsApparent maximum elasticity (E_max) estimates resulting from individual macrocalcifications (with diameters of 2mm, 3mm, 5mm, 6mm, 9mm, 11mm, and 15mm) showed values over 50 kPa for all cases, which represents more than 100% increase over background (~21kPa). We considered a 2cm-diameter circular region of interest for all phantom experiments. Mean elasticity (E_mean) values varied from 26 kPa to 73 kPa, depending on the macrocalcification size. Highly dense clusters of microcalcifications showed higher E_max values than clusters of microcalcification with low concentrations, but the difference in E_mean values was not significant.ConclusionsOur results demonstrate that the presence of large isolated macrocalcifications and highly concentrated clusters of microcalcifications can introduce areas with apparent high elasticity in SWE. Considering that benign breast masses normally have significantly lower elasticity values than malignant tumors, such areas with high elasticity appearing due to presence of calcification in benign breast masses may lead to misdiagnosis.     

Preload-Based Starling-Like Control for Rotary Blood Pumps: Numerical Comparison with Pulsatility Control and Constant Speed Operation

In this study, we evaluate a preload-based Starling-like controller for implantable rotary blood pumps (IRBPs) using left ventricular end-diastolic pressure (PLVED) as the feedback variable. Simulations are conducted using a validated mathematical model. The controller emulates the response of the natural left ventricle (LV) to changes in PLVED. We report the performance of the preload-based Starling-like controller in comparison with our recently designed pulsatility controller and constant speed operation. In handling the transition from a baseline state to test states, which include vigorous exercise, blood loss and a major reduction in the LV contractility (LVC), the preload controller outperformed pulsatility control and constant speed operation in all three test scenarios. In exercise, preload-control achieved an increase of 54% in mean pump flow (QP-) with minimum loading on the LV, while pulsatility control achieved only a 5% increase in flow and a decrease in mean pump speed. In a hemorrhage scenario, the preload control maintained the greatest safety margin against LV suction. PLVED for the preload controller was 4.9 mmHg, compared with 0.4 mmHg for the pulsatility controller and 0.2 mmHg for the constant speed mode. This was associated with an adequate mean arterial pressure (MAP) of 84 mmHg. In transition to low LVC, QP- for preload control remained constant at 5.22 L/min with a PLVED of 8.0 mmHg. With regards to pulsatility control, QP- fell to the nonviable level of 2.4 L/min with an associated PLVED of 16 mmHg and a MAP of 55 mmHg. Consequently, pulsatility control was deemed inferior to constant speed mode with a PLVED of 11 mmHg and a QP- of 5.13 L/min in low LVC scenario. We conclude that pulsatility control imposes a danger to the patient in the severely reduced LVC scenario, which can be overcome by using a preload-based Starling-like control approach.     

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications.