Coronary artery disease (CAD) remains the single most important cause of mortality worldwide. Many candidate and GWAS genetic variants have been identified in the recent years. In the current study, ...we selected six SNPs from various genes that have originally been identified in GWAS studies and examined the association of SNPs individually and as a genetic risk score (GRS) with CAD and blood lipid levels in the Pakistani subjects.
Six hundred twenty-four (404 cases and 219 controls) subjects were genotyped for variants rs10757274 in CDKN2A gene, rs17465637 in MIA3 gene, rs7025486 in DAB2IP gene, rs17228212 in SMAD3 gene, rs981887 in MRAS gene and rs1746048 in CXCL12 gene, by TaqMan and KASPar allele discrimination techniques. Serum lipid parameters were measured using commercially available kits. Statistical analyses were done using SPSS version 22.
Individually, the single SNPs were not associated with CAD (p < 0.05). However, the combined GRS of 6 SNPs was significantly higher in cases than controls (4.89 ± 0.11 vs 4.58 ± 0.08, p = 0.024). Among blood lipids, GRS showed significant positive association with serum triglycerides levels (p = 0.022).
The GRS was quantitatively associated with CAD risk and showed association with serum triglycerides levels, suggesting that the mechanism of these variants is likely to be in part at least through creating an atherogenic lipid profile in subjects carrying high numbers of risk alleles.
Tendon xanthomas are atherosclerotic plaque like collections of lipids that develop with age in the Achilles tendons of patients having familial hypercholesterolemia (FH). We tested a fat-water ...discrimination technique for imaging Achilles tendon xanthomatosis.
We used the spin-warp imaging technique optimized for low-field magnetic resonance (MR) imaging to obtain separate fat and water images of the Achilles tendon. Seven patients with FH, two patients with normal tendons, and three patients with other tendon pathology were studied.
Normal tendons showed an intensity near or equal to that of the noisy background in all images. Compared with the background, the intensity of the FH tendons was approximately fivefold greater in magnitude images, fourfold in fat images, and 10-fold in water images.
The method sensitively detected even subtle xanthomatosis in young patients, but differentiation of xanthomas from other pathologic lesions was possible with this method only when the tendons were significantly thickened.
In this paper, the minimum difference (MD) method for the discrimination of individual gases/odours, using an integrated sensor array, has been presented. The decision of an unknown gas/odour is made ...by finding the minimum difference values between the training and sniffing mode parameters. The method has been illustrated successfully with the data set obtained in our laboratory for the four types of alcoholic beverage. It is envisaged that the MD method, in association with the gas sensor array, may find an application in food and/or beverage industries.
Positron probes can accurately localize malignant tumors by directly detecting positrons emitted from positron-emitting radiopharmaceuticals that accumulate in malignant tumors. In the conventional ...method for direct positron detection, multilayer scintillator detection and pulse shape discrimination techniques are used. However, some γ-rays cannot be distinguished by conventional methods. Accordingly, these γ-rays are misidentified as positrons, which may increase the error rate of positron detection.
To analyze the energy distribution in each scintillator of the multilayer scintillator detector to distinguish true positrons and γ-rays and to improve the positron detection algorithm by discriminating true and false positrons.
We used Autoencoder, an unsupervised deep learning architecture, to obtain the energy distribution data in each scintillator of the multilayer scintillator detector. The Autoencoder was trained to separate the combined signals generated from the multilayer scintillator detector into two signals of each scintillator. An energy window was then applied to the energy distribution obtained using the trained Autoencoder to distinguish true positrons from false positrons. Finally, the performance of the proposed method and conventional positron detection algorithm was evaluated in terms of the sensitivity and error rate for positron detection.
The energy distribution map obtained using the trained Autoencoder was proven to be similar to that of the simulated results. Furthermore, the proposed method demonstrated a 29.79% (+0.42%p) increase in positron detection sensitivity compared to the conventional method, both having an equal error rate of 0.48%. However, when both methods were set to have the same sensitivity of 1.83%, the proposed method had an error rate that was 25.0% (-0.16%p) lower than that of the conventional method.
We proposed and developed an Autoencoder-based positron detection algorithm that can discriminate between true and false positrons with a smaller error rate than conventional methods. We verified that the proposed method could increase the positron detection sensitivity while maintaining a low error rate compared to the conventional method. If the proposed algorithm is implemented in handheld positron detection probes or cameras, diseases such as cancers can be more accurately localized in a shorter time compared with using traditional methods.
•Improved imaging through fire and smoke is performed using quadrature lock-in discrimination (QLD) technique.•Imaging through smoke using ballistic photons filtering out diffused photons.•An ...advantageous technique for firefighters during search-and-rescue operation.•A simple, cost-effective technique based on incoherent LED source to image through fire and smoke.
Visibility is a big issue in imaging through fire and smoke, a situation often encountered by firefighters. Emission from fire is significantly higher in intensity compared to the light reflected from an object obscured by fire, leading to a drastic reduction in the signal-to-noise ratio for visualization. On the other hand, the presence of smoke scatters light in random directions, further reducing visibility. By implementing quadrature lock-in discrimination algorithm on the images captured by a sCMOS camera in the presence of a modulated blue light source and blue filter, we report a significant improvement in the image contrast measured for an object in the presence of flame and smoke. Our methodology is straightforward to realize and facilitates reliable identification of objects that are otherwise concealed in real-life situations due to poor visibility.
An increase in the global aging population is leading to an increase in age-related conditions such as dementia and movement disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), ...and dementia with Lewy bodies (DLB). The accurate prediction of risk factors associated with these disorders is crucial for early diagnosis and prevention. Biomarkers play a significant role in diagnosing and monitoring diseases. In neurodegenerative disorders like α-synucleinopathies, specific biomarkers can indicate the presence and progression of disease. We previously demonstrated the pathogenic impact of fatty acid-binding proteins (FABPs) in α-synucleinopathies. Therefore, this study investigated FABPs as potential biomarkers for Lewy body diseases. Plasma FABP levels were measured in patients with AD, PD, DLB, and mild cognitive impairment (MCI) and healthy controls. Plasma FABP3 was increased in all groups, while the levels of FABP5 and FABP7 tended to decrease in the AD group. Additionally, FABP2 levels were elevated in PD. A correlation analysis showed that higher FABP3 levels were associated with decreased cognitive function. The plasma concentrations of Tau, GFAP, NF-L, and UCHL1 correlated with cognitive decline. A scoring method was applied to discriminate between diseases, demonstrating high accuracy in distinguishing MCI vs. CN, AD vs. DLB, PD vs. DLB, and AD vs. PD. The study suggests that FABPs could serve as potential biomarkers for Lewy body diseases and aid in early disease detection and differentiation.
One of the major challenges in scientific research is to understand past climate and the mechanisms of climate change. Small vertebrates, and especially rodents, are very sensitive to shifts in ...climate and habitat, and their variations over time in terms of taxa and abundance can be successfully used to reconstruct past environments. The vast array of approaches to palaeoclimatic reconstruction reflects the great effort that has gone into this line of investigation. Recently, the UDA-ODA discrimination technique has been postulated as a more reliable ecologically-based methodology compared to the classical MER method.
To provide biogeographical information to be analysed by the UDA-ODA discrimination technique, the distributions of four species (Sorex minutus, Chionomys nivalis, Talpa europaea and Crocidura russula) documented in levels O, N, E and D of the Abric Romaní site were processed. The results reveal a statistical difference between the climatic values for the occupied distribution areas (ODA) and those for the uncertain distribution areas (UDA). This technique was then applied to small-mammal assemblages from the above-mentioned levels of Abric Romaní, to test whether the use of the ODAs of the species improves the precision of the climatic reconstruction compared to the atlas distributions of the species used in MER procedures. Our results suggest an improvement in the discrimination analysis over the previous MER reconstructions when wider distributions for an assemblage are obtained. The coldest values obtained for level O of Abric Romaní seem to reinforce the pollen interpretation of the level as coetaneous with a cold period. For the whole MIS 3 climatic scenario for Neanderthals, a colder and wetter climate is derived from the small-mammal analysis. However, as different methods and analyses have inherent limitations, a standardization of the methods applied to the different levels and sites should be carried out in order to provide comparable results.
•Species' ODAs from Abric Romaní got more accurate climatic results only in level D.•Wider mutual distributions imply high probability of precision with ODAs.•Consistency between methods is observed in the climatic tendency along the sequence.•A cold and wet scenario is deduced from the different proxies and methods applied.
This study presents random forest-based fault discrimination technique for power transformer. The proposed scheme relies on extracting features from the measured data of differential current signals ...of a power transformer. Various simulation cases consisting of internal faults including special types of turn-to-turn and primary-to-secondary winding faults and other disturbances (over-excitation and different types magnetising inrush such as initial, residual, recovery and sympathetic) have been generated with varying fault and system parameters for an existing power transformer of an Indian power transmission network using PSCAD/EMTDC software package. The performance of the proposed scheme has been evaluated over a simulation dataset of 5442 cases and the overall fault discrimination accuracy of more than 98% is achieved. The proposed scheme gives promising results for different connections and various ratings of the transformer, even though it is trained only once for a single rating and connection of a transformer. Comparative evaluation of the proposed scheme with the existing scheme clearly indicates the superiority of the proposed scheme as it remains stable during CT saturation condition and gives better stability during disturbances compared with conventional/existing schemes.
Kerosene from various refineries and crudes is used for heating and other purposes in many countries like Iraq; therefore, it is important to identify its source to recognize and tax any ...adulteration. In this study, a fast classification technique for kerosene marketed in Iraq was developed with the goal of identifying its quality. The samples were categorized using a supervised partial least squares discriminant analysis (PLS-DA) approach. Multivariate analyses using agglomerative hierarchal clustering and principal component analysis were utilized to identify outliers and sample dissimilarities. The dataset was divided into calibration and prediction sets. The prediction set was used to evaluate the model’s separation performance. The Q2 cross-validation was applied. The PLS-DA models achieved significant accuracy, sensitivity, and specificity, showing strong segregation ability, notably for the calibration set (100% accuracy and 1.00 sensitivity). It was found that kerosene processing can be classified rapidly and non-destructively without the need for complicated analyses, demonstrating the best results for classification even when compared with the classification outcomes of other fuels. This PLS-DA approach has never been looked at before for process quality detection, and the results are comparable to direct kerosene classification with soft independent modeling of class analogy and support vector machines.
Mammalian maternal care usually comes at a large energetic cost. To maximize their fitness, mothers should preferentially care for their own offspring. However, the majority of studies of ...mother–offspring recognition have focused on herd- or colony-living species and there is little information on maternal discrimination in more solitary-living species. Olfaction has been found to play a major role in mother–offspring recognition across various taxa. Therefore, our aim was to study this in a species evolved from a solitary-living ancestor, the domestic cat. We asked whether cat mothers distinguish between their own and alien offspring when providing maternal care, and whether cat mothers use olfactory cues in the offspring discrimination process. Results of Experiment 1 showed that cat mothers do not discriminate between own and alien young when retrieving them to the nest. They treated own and alien young similarly with respect to latency and order of retrieval. However, the results of Experiments 2 and 3, where we used an olfactory habituation-discrimination technique, showed that mothers were able to distinguish between the odours of their own and alien kittens. We discuss what ecological and/or behavioural factors might influence a mother’s decision when faced with discriminating between own and alien young, and why mothers might not discriminate between them when they are able to do so. Our findings support the view that maternal care alone should not be used as a measure of offspring recognition, and equal maternal care of own and alien young should not be immediately interpreted as an inability to discriminate between them.
PDF
