Pharmacokinetic and pharmacodynamic studies of etodolac loaded vesicular gels on rats by transdermal delivery

BACKGROUND

The present study includes the development of liposomal and ethosomal gels for transdermal delivery to overcome the side effects associated with oral route.

METHODS

The liposomes and ethosomes were prepared by 32 factorial design using film hydration and cold methods, respectively. Different concentrations of liposomal (ETO-LG) and ethosomal (ETO-EG) gels were prepared at 1%, 2 and 3% (w/v) using carbopol 940 NF. 1%w/v ETO-LG & ETO-EG were optimized upon rheological studies of prepared gels. The optimized gels were further characterized for various physicochemical properties and biophysical studies using FTIR, pharmacokinetic (PK) and pharmacodynamic (PD) studies. The pharmacodynamic activity was performed using carrageenan paw oedema model. The prepared vesicular gels were compared with 45% v/v ethanolic ETO-solution and marketed gel PROXYM® in all the characteristic parameters.

RESULTS

The pharmacokinetic study reveals that the half life of etodolac in ETO-EG was 1.56 folds whereas ETO-LG showed 1.31 folds higher than PROXYM®. The mean residence time (MRT) of etodolac in ETO-EG and ETO-LG is increased in 1.57 and 1.25 folds, respectively, when compared to PROXYM®. The ETO-EG showed higher percentage reduction in oedema (81.67%) compared to other test products.

CONCLUSION

The pharmacokinetic and pharmacodynamic studies indicated that the vesicular gels show better results compared to PROXYM®. The correlation coefficient value between PK and PD was found to be 0.9635. Graphical abstract ᅟ.

User's guide to correlation coefficients

When writing a manuscript, we often use words such as perfect, strong, good or weak to name the strength of the relationship between variables. However, it is unclear where a good relationship turns into a strong one. The same strength of r is named differently by several researchers. Therefore, there is an absolute necessity to explicitly report the strength and direction of r while reporting correlation coefficients in manuscripts. This article aims to familiarize medical readers with several different correlation coefficients reported in medical manuscripts, clarify confounding aspects and summarize the naming practices for the strength of correlation coefficients.

Textural character of sweet potato root of Korean cultivars in relation to chemical constituents and their properties

A relationship between chemical constituents and physicochemical and textural properties of different Korean sweet potato (SP) cultivars were investigated in terms of the hardness of raw and cooked root, alcohol insoluble solid (AIS), starch and amylose content, amylase activities, and pasting properties. Correlation coefficients were analyzed and principal component analysis was performed. The hardness of cooked root was found to correlate with the hardness ratio of cooked/raw SP, AIS content (0.75**), starch content (0.64**), and peak viscosity of SP powder (0.56*). It was discovered that SP cultivars could be classified into mealy (Sincheonmi, Daeyumi, Sinyulmi), intermediate (Dahomi, Sinjami, Geonhwangmi, Yeonjami, Pungwonmi), and waxy (Juhwangmi, Sinhwangmi) types depending on the first principal component (PC1, 68%). Therefore, it was found that the texture types of SP cultivars could be predicted from hardness of cooked root and are in relation to AIS and starch contents, and peak viscosity of raw powder.

Performance of spleen stiffness measurement in prediction of clinical significant portal hypertension: A meta-analysis

AIM

Our purpose was to evaluate the correlation between spleen stiffness (SS) measured by ultrasound-based elastography and hepatic venous pressure gradient (HVPG) and assess the accuracy of SS in detecting clinical significant portal hypertension (CSPH) and severe portal hypertension.

METHOD

Nine studies were included from thorough literature research and selection processes. A random model was used to analyze the correlation between HVPG and SS. We adopted the bivariate mixed effects model to assess the diagnostic performance.

RESULTS

Regarding to correlation between SS and HVPG, the summary correlation coefficient was 0.72 (95% confidence interval [CI], 0.63-0.80). In detection of CSPH, the sensitivity, specificity, AUC and DOR were: 0.88 (0.70-0.96), 0.84 (0.72-0.92), 0.92 (0.89-0.94) and 38 (17-84) for CSPH, respectively; and 0.92 (0.82-0.96), 0.79 (0.72-0.85), 0.87 (0.84-0.90) and 41 (17-100) for severe portal hypertension, respectively.

CONCLUSION

Correlation between SS and HVPG was good. Although SS showed good sensitivity and specificity, the different cut-off values and techniques among studies might limit the impact of our results on clinical practice. Therefore, more high-quality prospective studies are required to evaluate the role of SS in predicting portal hypertension.

Genetic diversity and structure of tea plant in Qinba area in China by three types of molecular markers

Background

Qinba area has a long history of tea planting and is a northernmost region in China where Camellia sinensis L. is grown. In order to provide basic data for selection and optimization of molecular markers of tea plants. 118 markers, including 40 EST-SSR, 40 SRAP and 38 SCoT markers were used to evaluate the genetic diversity of 50 tea plant (Camellia sinensis.) samples collected from Qinb. tea germplasm, assess population structure.

Results

In this study, a total of 414 alleles were obtained using 38 pairs of SCoT primers, with an average of 10.89 alleles per primer. The percentage of polymorphic bands (PPB), polymorphism information content (PIC), resolving power (Rp), effective multiplex ratio (EMR), average band informativeness (Ib_av), and marker index (MI) were 96.14%, 0.79, 6.71, 10.47, 0.58, and 6.07 respectively. 338 alleles were amplified via 40 pairs of SRAP (8.45 per primer), with PPB, PIC, Rp, EMR, Ib_av, and MI values of 89.35%, 0.77, 5.11, 7.55, 0.61, and 4.61, respectively. Furthermore, 320 alleles have been detected using 40 EST-SSR primers (8.00 per primer), with PPB, PIC, Rp, EMR, Ib_av, and MI values of 94.06%, 0.85, 4.48, 7.53, 0.56, and 4.22 respectively. These results indicated that SCoT markers had higher efficiency.

Mantel test was used to analyze the genetic distance matrix generated by EST-SSRs, SRAPs and SCoTs. The results showed that the correlation between the genetic distance matrix based on EST-SSR and that based on SRAP was very small (r = 0.01), followed by SCoT and SRAP (r = 0.17), then by SCoT and EST-SSR (r = 0.19).

The 50 tea samples were divided into two sub-populations using STRUCTURE, Neighbor-joining (NJ) method and principal component analyses (PCA). The results produced by STRUCTURE were completely consistent with the PCA analysis. Furthermore, there is no obvious relationship between the results produced using sub-populational and geographical data.

Conclusion

Among the three types of markers, SCoT markers has many advantages in terms of NPB, PPB, Rp, EMR, and MI. Nevertheless, the values of PIC showed different trends, with the highest values generated with EST-SSR, followed by SCoT and SRAP. The average band informativeness showed similar trends. Correlation between genetic distances produced by three different molecular markers were very small, thus it is not recommended to use a single marker to evaluate genetic diversity and population structure. It is hence suggested that combining of different types of molecular markers should be used to evaluate the genetic diversity and population structure. It also seems crucial to screen out, for each type of molecular markers, core markers of Camellia sinensis. This study revealed that genes of exotic plant varieties have been constantly integrated into the gene pool of Qinba area tea. A low level of genetic diversity was observed; this is shown by an average coefficient of genetic similarity of 0.74.

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data

BACKGROUND

Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation.

NEW METHOD

A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression.

RESULT

We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods.

COMPARISON WITH EXISTING METHODS

Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail.

CONCLUSIONS

In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis.

Correlation of Two Colposcopic Indices for Predicting Premalignant Lesions of Cervix

Cervical cancer is the second most common malignancy among women in India, mainly affecting the females of Peri-Menopausal age group. Colposcopy has been very useful for diagnosing cervical cancer to guide the biopsy. Reids and Scalzi proposed the Reids Colposcopic Index (RCI) to make colposcopic diagnosis less subjective, which is currently the most accepted scoring system. Recognizing the correlation of size of the lesion with likelihood of harbouring high grade disease, a new scoring system, the Swede score, has been devised by Strander et al in 2005. In present study we compared the Reids colposcopic index with Swede score. From the present study it is evident that Swede score of 8 or more has 100% specificity and can be used for performing direct excisional procedure as a "see-and-treat" method at this cut-off. This may be the preferred method for the treatment of high-grade CIN because it reduces the number of visits to the clinic and failure to receive treatment.

Self-Optimized Computational Method Calculating Robust b Values for Earthquake Catalogs Containing Small Number of Events

In the Gutenberg-Richter relation that describes the frequency-magnitude distribution of earthquakes, the b value represents the distribution's slope. Since b values can be used for mapping the dynamic response of earthquake source, methodologies for calculating robust b values are of great importance. Although nowadays software which is meant for statistical analysis of earthquake data can determine b values with high accuracy, in occasions where catalogs that contain small number of earthquake events, the produced results are not satisfactory. In this paper we present a new self-optimized algorithm for a more efficient calculation of the b value. The algorithm's results are compared with two widely known software for statistical analysis of earthquake data, showing a better performance in evaluating b values for earthquake catalogs containing small number of events.

Adaptive neuro-fuzzy inference system for breath phase detection and breath cycle segmentation

BACKGROUND

The monitoring of the respiratory rate is vital in several medical conditions, including sleep apnea because patients with sleep apnea exhibit an irregular respiratory rate compared with controls. Therefore, monitoring the respiratory rate by detecting the different breath phases is crucial.

OBJECTIVES

This study aimed to segment the breath cycles from pulmonary acoustic signals using the newly developed adaptive neuro-fuzzy inference system (ANFIS) based on breath phase detection and to subsequently evaluate the performance of the system.

METHODS

The normalised averaged power spectral density for each segment was fuzzified, and a set of fuzzy rules was formulated. The ANFIS was developed to detect the breath phases and subsequently perform breath cycle segmentation. To evaluate the performance of the proposed method, the root mean square error (RMSE) and correlation coefficient values were calculated and analysed, and the proposed method was then validated using data collected at KIMS Hospital and the RALE standard dataset.

RESULTS

The analysis of the correlation coefficient of the neuro-fuzzy model, which was performed to evaluate its performance, revealed a correlation strength of r = 0.9925, and the RMSE for the neuro-fuzzy model was found to equal 0.0069.

CONCLUSION

The proposed neuro-fuzzy model performs better than the fuzzy inference system (FIS) in detecting the breath phases and segmenting the breath cycles and requires less rules than FIS.

Feasibility of using single photon counting X-ray for lung tumor position estimation based on 4D-CT

PURPOSE

In stereotactic body radiation therapy of lung tumors, reliable position estimation of the tumor is necessary in order to minimize normal tissue complication rate. While kV X-ray imaging is frequently used, continuous application during radiotherapy sessions is often not possible due to concerns about the additional dose. Thus, ultra low-dose (ULD) kV X-ray imaging based on a single photon counting detector is suggested. This paper addresses the lower limit of photons to locate the tumor reliably with an accuracy in the range of state-of-the-art methods, i.e. a few millimeters.

METHOD

18 patient cases with four dimensional CT (4D-CT), which serves as a-priori information, are included in the study. ULD cone beam projections are simulated from the 4D-CTs including Poisson noise. The projections from the breathing phases which correspond to different tumor positions are compared to the ULD projection by means of Poisson log-likelihood (PML) and correlation coefficient (CC), and template matching under these metrics.

RESULTS

The results indicate that in full thorax imaging five photons per pixel suffice for a standard deviation in tumor positions of less than half a breathing phase. Around 50 photons per pixel are needed to achieve this accuracy with the field of view restricted to the tumor region. Compared to CC, PML tends to perform better for low photon counts and shifts in patient setup. Template matching only improves the position estimation in high photon counts. The quality of the reconstruction is independent of the projection angle.

CONCLUSIONS

The accuracy of the proposed ULD single photon counting system is in the range of a few millimeters and therefore comparable to state-of-the-art tumor tracking methods. At the same time, a reduction in photons per pixel by three to four orders of magnitude relative to commercial systems with flatpanel detectors can be achieved. This enables continuous kV image-based position estimation during all fractions since the additional dose to the patient is negligible.

THM and HAA formation from NOM in raw and treated surface waters

The disinfection by-product (DBP) formation potential (FP) of natural organic matter (NOM) in surface water sources has been studied with reference to the key water quality determinants (WQDs) of UV absorption (UV₂₅₄), colour, and dissolved organic carbon (DOC) concentration. The data set used encompassed raw and treated water sampled over a 30-month period from 30 water treatment works (WTWs) across Scotland, all employing conventional clarification. Both trihalomethane (THM) and haloacetic acid (HAA) FPs were considered. In addition to the standard bulk WQDs, the DOC content was fractionated and analysed for the hydrophobic (HPO) and hydrophilic (HPI) fractions. Results were quantified in terms of the yield (dDBPFP/dWQD) and the linear regression coefficient R² of the yield trend. The NOM in the raw waters was found to comprise 30-84% (average 66%) of the more reactive HPO material, with this proportion falling to 18-63% (average 50%) in the treated water. Results suggested UV₂₅₄ to be as good an indicator of DBPFP as DOC or HPO for the raw waters, with R² values ranging from 0.79 to 0.82 for THMs and from 0.71 to 0.73 for HAAs for these three determinants. For treated waters the corresponding values were significantly lower at 0.52-0.67 and 0.46-0.47 respectively, reflecting the lower HPO concentration and thus UV₂₅₄ absorption and commensurately reduced precision due to the limit of detection of the analytical instrument. It is concluded that fractionation offers little benefit in attempting to discern or predict chlorinated carbonaceous DBP yield for the waters across the geographical region studied. UV₂₅₄ offered an adequate estimate of DBPFP based on a mean yield of ∼2600 and ∼2800 μg per cm^-1 absorbance for THMFP for the raw and treated waters respectively and ∼3800 and2900 μg cm^-1 for HAAFP, albeit with reduced precision for the treated waters.

El Niño Southern Oscillation as an early warning tool for malaria outbreaks in India

BACKGROUND

Risks of malaria epidemics in relation to El Niño and Southern Oscillation (ENSO) events have been mapped and studied at global level. In India, where malaria is a major public health problem, no such effort has been undertaken that inter-relates El Niño, Indian Summer Monsoon Rainfall (ISMR) and malaria. The present study has been undertaken to find out the relationship between ENSO events, ISMR and intra-annual variability in malaria cases in India, which in turn could help mitigate the malaria outbreaks.

METHODS

Correlation coefficients among 'rainfall index' (ISMR), '+ winter ONI' (NDJF) and 'malaria case index' were calculated using annual state-level data for the last 22 years. The 'malaria case index' representing 'relative change from mean' was correlated to the 4 month (November-February) average positive Oceanic Niño Index (ONI). The resultant correlations between '+ winter ONI' and 'malaria case index' were further analysed on geographical information system platform to generate spatial correlation map.

RESULTS

The correlation between '+ winter ONI' and 'rainfall index' shows that there is great disparity in effect of ENSO over ISMR distribution across the country. Correlation between 'rainfall index' and 'malaria case index' shows that malaria transmission in all geographical regions of India are not equally affected by the ISMR deficit or excess. Correlation between '+ winter ONI' and 'malaria case index' was found ranging from -0.5 to + 0.7 (p < 0.05). A positive correlation indicates that increase in El Niño intensity (+ winter ONI) will lead to rise in total malaria cases in the concurrent year in the states of Orissa, Chhattisgarh, Jharkhand, Bihar, Goa, eastern parts of Madhya Pradesh, part of Andhra Pradesh, Uttarakhand and Meghalaya. Whereas, negative correlations were found in the states of Rajasthan, Haryana, Gujarat, part of Tamil Nadu, Manipur, Mizoram and Sikkim indicating the likelihood of outbreaks in La Nina condition.

CONCLUSIONS

The generated map, representing spatial correlation between ' + winter ONI' and 'malaria case index', indicates positive correlations in eastern part, while negative correlations in western part of India. This study provides plausible guidelines to national programme for planning intervention measures in view of ENSO events. For better resolution, district level study with inclusion of IOD and 'epochal variation of monsoon rainfall' factors at micro-level is desired for better forecast of malaria outbreaks in the regions with 'no correlation'.

A novel measure and significance testing in data analysis of cell image segmentation

Background

Cell image segmentation (CIS) is an essential part of quantitative imaging of biological cells. Designing a performance measure and conducting significance testing are critical for evaluating and comparing the CIS algorithms for image-based cell assays in cytometry. Many measures and methods have been proposed and implemented to evaluate segmentation methods. However, computing the standard errors (SE) of the measures and their correlation coefficient is not described, and thus the statistical significance of performance differences between CIS algorithms cannot be assessed.

Results

We propose the total error rate (TER), a novel performance measure for segmenting all cells in the supervised evaluation. The TER statistically aggregates all misclassification error rates (MER) by taking cell sizes as weights. The MERs are for segmenting each single cell in the population. The TER is fully supported by the pairwise comparisons of MERs using 106 manually segmented ground-truth cells with different sizes and seven CIS algorithms taken from ImageJ. Further, the SE and 95% confidence interval (CI) of TER are computed based on the SE of MER that is calculated using the bootstrap method. An algorithm for computing the correlation coefficient of TERs between two CIS algorithms is also provided. Hence, the 95% CI error bars can be used to classify CIS algorithms. The SEs of TERs and their correlation coefficient can be employed to conduct the hypothesis testing, while the CIs overlap, to determine the statistical significance of the performance differences between CIS algorithms.

Conclusions

A novel measure TER of CIS is proposed. The TER’s SEs and correlation coefficient are computed. Thereafter, CIS algorithms can be evaluated and compared statistically by conducting the significance testing.

Assessing Historical Mining and Smelting Effects on Heavy Metal Pollution of River Systems over Span of Two Decades

Research was conducted on the most polluted river system in Poland, impacted by active and historical mining. Bottom sediment, suspended particulate matter and river water were collected in 2014 from Przemsza river and its tributaries. Sampling points remained the same as those chosen in a 1995 study. This allowed the comparison of heavy metal accumulation in bottom sediment over a span of almost two decades. It was concluded that Przemsza river water and its tributaries are heavily contaminated with the following (in μg/dm³): Pb (0.99-145.7), Zn (48-5020), and Cd 0.12-12.72). Concentrations of metals in bottom sediment exceeded the background values by a factor of several hundred (100 times for Zn, 150 times for Pb, and 240 times for Cd). The arithmetic mean for metal concentration in fractions <63 μm sampled in 2014 has remained comparable to the level found in 1995 (in mg/kg): Zn 16,918 and 13,505, Pb 4177 and 4758, and Cd 92 and 134. It was determined that 20-50% more metals have accumulated in suspended matter, rather than in bottom sediment (in mg/kg): 20,498 Zn, Pb 5170, and 164 Cd. This exceeds the limits of the most polluted LAWA Class IV classification. Since the concentrations of Zn, Pb, and Cd increase drastically after the outlet of the Przemsza into the Vistula, it was concluded that river Przemsza is the cause of significant degradation of Vistula's bottom sediment and suspended matter. A two-decade legacy of extremely high contamination of the Przemsza river sediments has persisted despite decreasing mining and smelting activity in the vicinity.

Chemical profiling and adulteration screening of Aquilariae Lignum Resinatum by Fourier transform infrared (FT-IR) spectroscopy and two-dimensional correlation infrared (2D-IR) spectroscopy

As a kind of expensive perfume and valuable herb, Aquilariae Lignum Resinatum (ALR) is often adulterated for economic motivations. In this research, Fourier transform infrared (FT-IR) spectroscopy is employed to establish a simple and quick method for the adulteration screening of ALR. First, the principal chemical constituents of ALR are characterized by FT-IR spectroscopy at room temperature and two-dimensional correlation infrared (2D-IR) spectroscopy with thermal perturbation. Besides the common cellulose and lignin compounds, a certain amount of resin is the characteristic constituent of ALR. Synchronous and asynchronous 2D-IR spectra indicate that the resin (an unstable secondary metabolite) is more sensitive than cellulose and lignin (stable structural constituents) to the thermal perturbation. Using a certified ALR sample as the reference, the infrared spectral correlation threshold is determined by 30 authentic samples and 6 adulterated samples. The spectral correlation coefficient of an authentic ALR sample to the standard reference should be not less than 0.9886 (p=0.01). Three commercial adulterated ALR samples are identified by the correlation threshold. Further interpretation of the infrared spectra of the adulterated samples indicates the common adulterating methods - counterfeiting with other kind of wood, adding ingredient such as sand to increase the weight, and adding the cheap resin such as rosin to increase the content of resin compounds. Results of this research prove that FT-IR spectroscopy can be used as a simple and accurate quality control method of ALR.

Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010

Drought is a type of natural disaster that has the most significant impacts on agriculture. Regional drought monitoring based on remote sensing has become popular due to the development of remote sensing technology. In this study, vegetation condition index (VCI) data recorded from 1982 to 2010 in agricultural areas of China were obtained from advanced very high resolution radiometer (AVHRR) data, and the temporal and spatial variations in each drought were analyzed. The relationships between drought and climate factors were also analyzed. The results showed that from 1982 to 2010, the agricultural areas that experienced frequent and severe droughts were mainly concentrated in the northwestern areas and Huang-Huai Plain. Moreover, the VCI increased in the majority of agricultural areas, indicating that the drought frequency decreased over time, and the decreasing trend in the southern region was more notable than that in the northern region. A correlation analysis showed that temperature and wind velocity were the main factors that influenced drought in the agricultural areas of China. From a regional perspective, excluding precipitation, the climate factors had various effects on drought in different regions. However, the correlation between the VCI and precipitation was low, possibly due to the widespread use of artificial irrigation technology, which reduces the reliance of agricultural areas on precipitation.

Assessment of seasonal variation for air pollutant accumulation by Zizyphus tree under washing treatment

A field study was carried out near Jeddah Industrial Zone to estimate the leaf impairment, physiological disorders, and air pollutant accumulation potential of Ziziphus tree. The experiment was triplicated in RCBD design with factorial arrangement having seasonality as the main plot and washing as subplot treatments along with the control. Accumulation of heavy metals and micronutrients in plant foliage varied significantly under the influence of seasons and washing treatments. The maximum accumulation of cadmium, chromium, nickel, and lead were perceived in summer season while the minimum was observed in winter. Contrarily, a greater acquisition of iron, copper, zinc, and manganese was observed in autumn. Washing significantly reduced the accumulation of Cd, Cr, Ni, and Pb by 58, 90, 80, and 96 %, while Fe, Cu, Zn, and Mn by 89, 37, 60, and 93 %, respectively. Leaf protein and nitrogen content illustrated a greater adjustment for pollutants by presenting a minimum variation (14-18 % and 2-3 %) to seasonality. In contrast, leaf area and stomatal aperture were significantly disturbed and resulted in minimum recovery under washing. Correlation analysis revealed a stronger negative interaction of heavy metal accumulation to leaf features while non-significant interaction was perceived for microelements. In conclusion, planting of Ziziphus trees along industrial areas may impede potential threats of toxic pollutants to human and ecosystem.

FTIR spectroscopy supported by statistical techniques for the structural characterization of plastic debris in the marine environment: Application to monitoring studies

We inserted 190 FTIR spectra of plastic samples in a digital database and submitted it to Independent Component Analysis (ICA) to extract the "pure" plastic polymers present. These identified plastics were polypropylene (PP), high density polyethylene (HDPE), low density polyethylene (LDPE), high density polyethylene terephthalate (HDPET), low density polyethylene terephthalate (LDPET), polystyrene (PS), Nylon (NL), polyethylene oxide (OPE), and Teflon (TEF) and they were used to establish the similarity with unknown plastics using the correlation coefficient (r), and the crosscorrelation function (CC). For samples with r<0.8 we determined the Mahalanobis Distance (MD) as additional tool of identification. For instance, for the four plastic fragments found in the Carretta carretta, one plastic sample was assigned to OPE due to its r=0.87; for all the other three plastic samples, due to the r values ranging between 0.83 and0.70, the support of MD suggested LDPET and OPE as co-polymer constituents.

Temporal correlation between two channels EEG of bipolar lead in the head midline is associated with sleep-wake stages

Whether the temporal correlation between inter-leads Electroencephalogram (EEG) that located on the boundary between left and right brain hemispheres is associated with sleep stages or not is still unknown. The purpose of this paper is to evaluate the role of correlation coefficients between EEG leads Fpz-Cz and Pz-Oz for automatic classification of sleep stages. A total number of 39 EEG recordings (about 20 h each) were selected from the expanded sleep database in European data format for temporal correlation analysis. Original waveform of EEG was decomposed into sub-bands δ (1-4 Hz), θ (4-8 Hz), α (8-13 Hz) and β (13-30 Hz). The correlation coefficient between original EEG leads Fpz-Cz and Pz-Oz within frequency band 0.5-30 Hz was defined as r(EEG) and was calculated every 30 s, while that between the two leads EEG in sub-bands δ, θ, α and β were defined as r(δ), r(θ), r(α) and r(β), respectively. Classification of wakefulness and sleep was processed by fixed threshold that derived from the probability density function of correlation coefficients. There was no correlation between EEG leads Fpz-Cz and Pz-Oz during wakefulness (|r| < 0.1 for r(θ), r(α) and r(β), while 0.3 > r > 0.1 for r(EEG) and r(δ)), while low correlation existed during sleep (r ≈ -0.4 for r(EEG), r(δ), r(θ), r(α) and r(β)). There were significant differences (analysis of variance, P < 0.001) for r(EEG), r(δ), r(θ), r(α) and r(β) during sleep when in comparison with that during wakefulness, respectively. The accuracy for distinguishing states between wakefulness and sleep was 94.2, 93.4, 89.4, 85.2 and 91.4% in terms of r(EEG), r(δ), r(θ), r(α) and r(β), respectively. However, no correlation index between EEG leads Fpz-Cz and Pz-Oz could distinguish all five types of wakefulness, rapid eye movement (REM) sleep, N1 sleep, N2 sleep and N3 sleep. In conclusion, the temporal correlation between EEG bipolar leads Fpz-Cz and Pz-Oz are highly associated with sleep-wake stages. Moreover, high accuracy of sleep-wake classification could be achieved by the temporal correlation within frequency band 0.5-30 Hz between EEG leads Fpz-Cz and Pz-Oz.

Characterizing air quality data from complex network perspective

Air quality depends mainly on changes in emission of pollutants and their precursors. Understanding its characteristics is the key to predicting and controlling air quality. In this study, complex networks were built to analyze topological characteristics of air quality data by correlation coefficient method. Firstly, PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) indexes of eight monitoring sites in Beijing were selected as samples from January 2013 to December 2014. Secondly, the C-C method was applied to determine the structure of phase space. Points in the reconstructed phase space were considered to be nodes of the network mapped. Then, edges were determined by nodes having the correlation greater than a critical threshold. Three properties of the constructed networks, degree distribution, clustering coefficient, and modularity, were used to determine the optimal value of the critical threshold. Finally, by analyzing and comparing topological properties, we pointed out that similarities and difference in the constructed complex networks revealed influence factors and their different roles on real air quality system.

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.

Characterization of particulate matter concentrations and bioaerosol on each floor at a building in Seoul, Korea

Particulate matter (PM) in buildings are mostly sourced from the transport of outdoor particles through a heating, ventilation, and air conditioning (HVAC) system and generation of particle within the building itself. We investigated the concentrations and characteristic of indoor and outdoor particles and airborne bacteria concentrations across four floors of a building located in a high-traffic area. In all the floors we studied (first, second, fifth, and eighth), the average concentrations of particles less than 10 μm (PM10) in winter for were higher than those in summer. On average, a seasonal variation in the PM10 level was found for the first, fifth, and eighth floors, such that higher values occurred in the winter season, compared to the summer season. In addition, in winter, the indoor concentrations of PM10 on the first, fifth, and eighth floors were higher than those of the outdoor PM10. The maximum level of airborne bacteria concentration was found in a fifth floor office, which held a private academy school consisting of many students. Results indicated that the airborne bacteria remained at their highest concentration throughout the weekday period and varied by students' activity. The correlation coefficient (R (2)) and slope of linear approximation for the concentrations of particulate matter were used to evaluate the relationship between the indoor and outdoor particulate matter. These results can be used to predict both the indoor particle levels and the risk of personal exposure to airborne bacteria.

Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources

OBJECTIVES

This study was performed to investigate the relationship between the incidence of national notifiable infectious diseases (NNIDs) and meteorological factors, air pollution levels, and hospital resources in Korea.

METHODS

We collected and stored 660,000 pieces of publicly available data associated with infectious diseases from public data portals and the Diseases Web Statistics System of Korea. We analyzed correlations between the monthly incidence of these diseases and monthly average temperatures and monthly average relative humidity, as well as vaccination rates, number of hospitals, and number of hospital beds by district in Seoul.

RESULTS

Of the 34 NNIDs, malaria showed the most significant correlation with temperature (r=0.949, p<0.01) and concentration of nitrogen dioxide (r=-0.884, p<0.01). We also found a strong correlation between the incidence of NNIDs and the number of hospital beds in 25 districts in Seoul (r=0.606, p<0.01). In particular, Geumcheon-gu was found to have the lowest incidence rate of NNIDs and the highest number of hospital beds per patient.

CONCLUSIONS

In this study, we conducted a correlational analysis of public data from Korean government portals that can be used as parameters to forecast the spread of outbreaks.

Kinematic analysis of knee varus and rotation movements at the initial stance phase with severe osteoarthritis of the knee

BACKGROUND

The purposes of this study were to understand the kinematics changes in the frontal and horizontal planes with severe medial knee OA at the stance phase and to examine the relationship between varus and rotational movements.

METHODS

The OA group comprised 18 knees in 12 subjects (five men, seven women) with a Kellgren-Lawrence grade of three or four in at least one knee. From the results of gait analysis, we calculated Spearman rank-correlation coefficients for the following items: varus angle at initial contact (IC); varus angle at loading response (LR); amount of varus thrust from IC to LR; rotational angle at IC; rotational angle at LR and amount of rotational angle change from IC to LR.

RESULTS

The results indicated that, as the external rotation angle at IC and internal rotational movement from IC to LR increased, the maximum varus angle to LR showed a tendency to become large. In addition, varus thrust showed a tendency to become larger as the external rotation angles increased at IC and LR. The subjects with severe knee OA showed a strong correlation between the knee varus angle at IC and at LR. Furthermore, an increase in movement to internal rotation of the knee during the initial stance phase increased the knee varus angle at LR.

CONCLUSIONS

The control of the rotational movement according to the extent of varus thrust during the initial stance phase may have possible effects to decrease the load on the medial compartment of the knee.

Hybrid algorithm for elastography to visualize both solid and fluid-filled lesions

We propose a novel strain estimation technique that can produce reliable strain images of both solid and fluid-filled lesions. In our method, a kernel-based correlation coefficient technique and a speckle tracking-based strain estimation technique are combined into a single algorithm. The elegance of our algorithm is that fluid-filled lesions are first automatically identified by three selection criteria, and strain in those parts is estimated using the kernel-based correlation coefficient technique. Strain where fluid-filled lesions have not been detected is estimated using a speckle tracking-based algorithm, and then these two estimates are merged to form the final image. Any speckle tracking algorithm can be used in our proposed technique; however, we used a modified version of the direct average spectral strain estimation technique to describe our algorithm. We modified the direct average spectral strain estimation algorithm to track smaller strain variation and to facilitate strain calculation from multiple frames. We describe the performance of our proposed hybrid algorithm using in vivo patient data. Both the solid and fluid-filled lesions are clearly visible in the strain images produced by our proposed approach and are of better quality in terms of contrast-to-noise ratio and border sharpness than the strain images generated by other reported techniques. We also validate the performance of our proposed multiframe technique using experimental phantom data and in vivo patient data. The results reveal that the quality of the strain image can be improved using the multiframe technique compared with its dual-frame counterpart.