Measurement invariance of the Facebook intrusion questionnaire across 25 countries.

Facebook is one of the most popular social networking sites. However, Facebook intrusion or addiction is a growing concern as it involves an excessive attachment to Facebook, which disrupts daily functioning. To date, few studies have examined whether cross-cultural differences in the measurement of Facebook addiction exist. The aim of this study was to investigate the cross-cultural validity and measurement invariance of the Facebook Intrusion Questionnaire (FIQ), one of the most widely used measures of Facebook addiction, across 25 countries (N = 12,204, 62.3% female; mean age = 25 years). Multigroup confirmatory factor analyses (MGCFA) assessed cross-cultural validity as well as invariance. Additionally, individual confirmatory factor analyses evaluated the factorial structure and measurement invariance across genders in each country. The FIQ demonstrated partial metric invariance across countries and metric (13 countries), scalar (11 countries) or residual (10 countries) invariance across genders within individual countries. A one-factor model indicated a good fit in 18 countries. Cronbach's alpha for the entire sample was .85. Our findings suggest that the FIQ may provide an adequate assessment of Facebook addiction that is psychometrically equivalent across cultures. Moreover, the questionnaire seems to be universal and suitable for studying different social media in distinct cultural environments. Consequently, this robust tool can be used to explore behaviours related to specific media that are particularly popular in any given country.

Gray-Level Co-occurrence Matrix Analysis of Nuclear Textural Patterns in Laryngeal Squamous Cell Carcinoma: Focus on Artificial Intelligence Methods.

Gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT) analyses are two contemporary computational methods that can identify discrete changes in cell and tissue textural features. Previous research has indicated that these methods may be applicable in the pathology for identification and classification of various types of cancers. In this study, we present findings that squamous epithelial cells in laryngeal carcinoma, which appear morphologically intact during conventional pathohistological evaluation, have distinct nuclear GLCM and DWT features. The average values of nuclear GLCM indicators of these cells, such as angular second moment, inverse difference moment, and textural contrast, substantially differ when compared to those in noncancerous tissue. In this work, we also propose machine learning models based on random forests and support vector machine that can be successfully trained to separate the cells using GLCM and DWT quantifiers as input data. We show that, based on a limited cell sample, these models have relatively good classification accuracy and discriminatory power, which makes them suitable candidates for future development of AI-based sensors potentially applicable in laryngeal carcinoma diagnostic protocols.

Gray-Level Co-occurrence Matrix Analysis for the Detection of Discrete, Ethanol-Induced, Structural Changes in Cell Nuclei: An Artificial Intelligence Approach.

Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational method for the assessment of textural patterns, applicable in almost any area of microscopy. The aim of our research was to perform the GLCM analysis of cell nuclei in Saccharomyces cerevisiae yeast cells after the induction of sublethal cell damage with ethyl alcohol, and to evaluate the performance of various machine learning (ML) models regarding their ability to separate damaged from intact cells. For each cell nucleus, five GLCM parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, and textural variance. Based on the obtained GLCM data, we applied three ML approaches: neural network, random trees, and binomial logistic regression. Statistically significant differences in GLCM features were observed between treated and untreated cells. The multilayer perceptron neural network had the highest classification accuracy. The model also showed a relatively high level of sensitivity and specificity, as well as an excellent discriminatory power in the separation of treated from untreated cells. To the best of our knowledge, this is the first study to demonstrate that it is possible to create a relatively sensitive GLCM-based ML model for the detection of alcohol-induced damage in Saccharomyces cerevisiae cell nuclei.

Effects of Iron Oxide Nanoparticles on Structural Organization of Hepatocyte Chromatin: Gray Level Co-occurrence Matrix Analysis.

Gray level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computer-based algorithm that can be used for the quantification of subtle changes in a cellular structure. In this work, we use this method for the detection of discrete alterations in hepatocyte chromatin distribution after in vivo exposure to iron oxide nanoparticles (IONPs). The study was performed on 40 male, healthy C57BL/6 mice divided into four groups: three experimental groups that received different doses of IONPs and 1 control group. We describe the dose-dependent reduction of chromatin textural uniformity measured as GLCM angular second moment. Similar changes were detected for chromatin textural uniformity expressed as the value of inverse difference moment. To the best of our knowledge, this is the first study to investigate the impact of iron-based nanomaterials on hepatocyte GLCM parameters. Also, this is the first study to apply discrete wavelet transform analysis, as a supplementary method to GLCM, for the assessment of hepatocyte chromatin structure in these conditions. The results may present the useful basis for future research on the application of GLCM and DWT methods in pathology and other medical research areas.

Association between Chromatin Structural Organization of Peripheral Blood Neutrophils and Self-Perceived Mental Stress: Gray-Level Co-occurrence Matrix Analysis.

Methods based on the evaluation of textural patterns in microscopy, such as the "gray-level co-occurrence matrix" (GLCM) analysis are modern and innovative computer and mathematical algorithms that can be used to quantify subtle structural changes in cells and their organelles. Potential application of GLCM method in the fields of psychophysiology and psychiatry to this date has not been systematically investigated. The main objective of our study was to test the existence and strength of the association between chromatin structural organization of peripheral blood neutrophils and levels of self-perceived mental stress. The research was done on a sample of 100 healthy student athletes, and the Depression, Anxiety, and Stress Scales (DASS-21) were used for the estimation of psychological distress. Chromatin textural homogeneity and uniformity were negatively correlated (p < 0.01) with mental distress and had relatively good discriminatory power in differentiating participants with normal and elevated stress levels. As an addition, we propose the creation of a machine learning model based on binomial logistic regression that uses these and other GLCM features to predict stress elevation. To the best of our knowledge, these results are one of the first to establish the link between neutrophil chromatin structural organization quantified by the GLCM method and indicators of normal psychological functioning.

Measurement invariance of the Phubbing Scale across 20 countries.

Mobile phone addiction is a robust phenomenon observed throughout the world. The social aspect of mobile phone use is crucial; therefore, phubbing is a part of the mobile phone addiction phenomenon. Phubbing is defined as ignoring an interlocutor by glancing at one's mobile phone during a face-to-face conversation. The main aim of this study was to investigate how the Phubbing Scale (containing 10 items) might vary across countries, and between genders. Data were collected in 20 countries: Belarus, Brazil, China, Croatia, Ecuador, India, Israel, Italy, Netherlands, Pakistan, Poland, Portugal, Serbia, Slovakia, Slovenia, Spain, Turkey, UK, Ukraine and USA. The mean age across the sample (N = 7696, 65.8% women, 34.2% men) was 25.32 years (SD = 9.50). The cross-cultural invariance of the scale was investigated using multigroup confirmatory factor analyses (MGCFA) as well as the invariance analyses. Additionally, data from each country were assessed individually via confirmatory factor analyses (CFAs). We obtained two factors, based on only eight of the items: (a) communication disturbances and (b) phone obsession. The 8 items Phubbing Scale.

Gray-Level Co-Occurrence Matrix Analysis of Granule Neurons of the Hippocampal Dentate Gyrus Following Cortical Injury.

Traumatic brain injury (TBI) is a main cause of death and disabilities in young adults. Although learning and memory impairments are a major clinical manifestation of TBI, the consequences of TBI on the hippocampus are still not well understood. In particular, how lesions to the sensorimotor cortex damage the hippocampus, to which it is not directly connected, is still elusive. Here, we study the effects of sensorimotor cortex ablation (SCA) on the hippocampal dentate gyrus, by applying a highly sensitive gray-level co-occurrence matrix (GLCM) analysis. Using GLCM analysis of granule neurons, we discovered, in our TBI paradigm, subtle changes in granule cell (GC) morphology, including textual uniformity, contrast, and variance, which is not detected by conventional microscopy. We conclude that sensorimotor cortex trauma leads to specific changes in the hippocampus that advance our understanding of the cellular underpinnings of cognitive impairments in TBI. Moreover, we identified GLCM analysis as a highly sensitive method to detect subtle changes in the GC layers that is expected to significantly improve further studies investigating the impact of TBI on hippocampal neuropathology.

Gray-level co-occurrence matrix analysis of chromatin architecture in periportal and perivenous hepatocytes.

Periportal hepatocytes (PPHs) and perivenous hepatocytes (PVHs) in standard optical microscopy appear to be morphologically identical. However, the functional properties of these two cell populations and their roles in liver lobules are not the same. Despite significant differences in gene expression between these two hepatocyte populations, it is still unclear whether the differences are present at the higher levels of chromatin organization. In this study, we present results, indicating that periportal and perivenous hepatocytes, when stained using toluidine blue histological dye, have different chromatin textural patterns quantified with gray-level co-occurrence matrix (GLCM) method. Hepatic tissue was obtained from ten male, healthy mice. Chromatin structures were analyzed using GLCM. For each structure, we measured the values of angular second moment, inverse difference moment, GLCM Contrast, GLCM Variance, and GLCM Sum Variance. The results indicate that there is a statistically significant difference in all GLCM mathematical parameters except the contrast. In addition, some chromatin GLCM features were in correlation with serum aminotransferase levels in perivenous, but not in periportal hepatocytes. To the best of our knowledge, this is the first study to test the nuclear morphological differences between hepatocytes using GLCM and to investigate the respective relation with serum liver enzymes.

Application of Gray Level co-Occurrence Matrix Algorithm for Detection of Discrete Structural Changes in Cell Nuclei After Exposure to Iron Oxide Nanoparticles and 6-Hydroxydopamine.

The gray level co-occurrence matrix (GLCM) algorithm is a contemporary computational biology method which, today, is frequently used to detect small changes in texture that are not visible using conventional techniques. We demonstrate that the toxic compound 6-hydroxydopamine (6-OHDA) and iron oxide nanoparticles (IONPS) have opposite effects on GLCM features of cell nuclei. Saccharomyces cerevisiae yeast cells were treated with 6-OHDA and IONPs, and imaging with GLCM analysis was performed at three different time points: 30 min, 60 min, and 120 min after the treatment. A total of 200 cell nuclei were analyzed, and for each nucleus, 5 GLCM parameters were calculated: Angular second moment (ASM), Inverse difference moment (IDM), Contrast (CON), Correlation (COR) and Sum Variance (SVAR). Exposure to IONPs was associated with the increase of ASM and IDM while the values of SVAR and COR were reduced. Treatment with 6-OHDA was associated with the increase of SVAR and CON, while the values of nuclear ASM and IDM were reduced. This is the first study to indicate that IONPs and 6-OHDA have opposite effects on nuclear texture. Also, to the best of our knowledge, this is the first study to apply the GLCM algorithm in Saccharomyces cerevisiae yeast cells in this experimental setting.

Postnatal Developmental Changes in Fractal Complexity of Giemsa-Stained Chromatin in Mice Spleen Follicular Cells.

Although there are numerous recent works focusing on fractal properties of DNA and chromatin, many issues regarding changes in chromatin fractality during physiological aging remain unclear. In this study, we present results indicating that in mice, there is an age-related reduction of chromatin fractal complexity in a population of spleen follicular cells (SFCs). Spleen tissue was obtained from 16 mice and fixated in Carnoy solution. The youngest animal was newborn, and each animal was exactly 1 month older than the previous. We performed fractal analysis of SFC chromatin structure, stained using Giemsa technique. Fractal analysis was done in a plugin algorithm of ImageJ software. We also performed gray-level co-occurrence matrix (GLCM) analysis of all chromatin structures with the calculation of parameters such as angular second moment and inverse difference moment. Giemsa-stained SFC chromatin exhibited an age-dependent reduction of fractal dimension with statistically significant (p<0.01) linear trend. Moreover, there was a statistically significant increase of SFC chromatin lacunarity. The chromatin GLCM parameters did not significantly change. To our knowledge, this is the first study to perform fractal and GLCM analyses of SFC chromatin and to investigate potential changes of fractal parameters during postnatal development.

Gray level co-occurrence matrix algorithm as pattern recognition biosensor for oxidopamine-induced changes in lymphocyte chromatin architecture.

We demonstrate that a proapoptotic chemical agent, oxidopamine, induces dose dependent changes in chromatin textural patterns which can be quantified using the Gray level co-occurrence matrix (GLCM) method. Peripheral blood (heparin-pretreated) samples were treated with oxidopamine (6-OHDA, 6-hydroxydopamine) to achieve effective concentrations of 100, 200 and 300µM. The samples were smeared on microscope slides and fixated in methanol. The smears were stained using a modification of Feulgen method for DNA visualization. For each stained smear, a sample of 30 lymphocyte chromatin structures were visualized and analyzed. This way, textural parameters for a total of 120 nuclei micrographs were calculated. For each chromatin structure, five different GLCM features were calculated: angular second moment, GLCM entropy, inverse difference moment, GLCM correlation, and GLCM variance. Oxidopamine induced the rise of the values of GLCM entropy and variance, and the reduction of angular second moment, correlation, and inverse difference moment. The trends for GLCM parameter changes were found to be highly significant (p<0.001). These results indicate that GLCM mathematical algorithm might be successfully used in detection and evaluation of discrete early apoptotic structural changes in Feulgen-stained chromatin of peripheral blood lymphocytes that are not detectable using conventional microscopy/cell biology techniques.

Fractal analysis and Gray level co-occurrence matrix method for evaluation of reperfusion injury in kidney medulla.

Fractal analysis and Gray level co-occurrence matrix method represent two novel mathematical algorithms commonly used in medical sciences as potential parts of computer-aided diagnostic systems. In this study, we tested the ability of these methods to discriminate the kidney medullar tissue suffering from reperfusion injury, from normal tissue. A total of 320 digital micrographs of Periodic acid-Schiff (PAS) - stained kidney medulla from 16 Wistar albino mice (20 per animal), were analyzed using National Institutes of Health ImageJ software (NIH, Bethesda, MD) and its plugins. 160 micrographs were obtained from the experimental group with induced reperfusion injury, and another 160 were obtained from the controls. For each micrograph we calculated the values of fractal dimension, lacunarity, as well as five GLCM features: angular second moment, entropy, inverse difference moment, GLCM contrast, and GLCM correlation. Discriminatory value of the parameters was tested using receiver operating characteristic (ROC) analysis, by measuring the area below ROC curve. The results indicate that certain features of GLCM algorithm have excellent discriminatory ability in evaluation of damaged kidney tissue. Fractal dimension and lacunarity as parameters of fractal analysis also had a relatively good discriminatory value in differentiation of injured from the normal tissue. Both methods have potentially promising application in future design of novel techniques applicable in cell physiology, histology and pathology.

Quantification of structural changes in acute inflammation by fractal dimension, angular second moment and correlation.

The aim of the study was to examine alteration and possible application of fractal dimension, angular second moment, and correlation for quantification of structural changes in acutely inflamed tissue. Acute inflammation was induced by injection of turpentine oil into the right and left hind limb muscles of mice, whereas control animals received intramuscular saline injection. After 12 h, animals were anesthetised and treated muscles collected. The tissue was stained by hematoxylin and eosin, digital micrographs produced, enabling determination of fractal dimension of the cells, angular second moment and correlation of studied tissue. Histopathological analysis showed presence of inflammatory infiltrate and tissue damage in inflammatory group, whereas tissue structure in control group was preserved, devoid of inflammatory infiltrate. Fractal dimension of the cells, angular second moment and correlation of treated tissue in inflammatory group decreased in comparison to the control group. In this study, we were first to observe and report that fractal dimension of the cells, angular second moment, and correlation were reduced in acutely inflamed tissue, indicating loss of overall complexity of the cells in the tissue, the tissue uniformity and structure regularity. Fractal dimension, angular second moment and correlation could be useful methods for quantification of structural changes in acute inflammation.

Chromatin Fractal Organization, Textural Patterns, and Circularity of Nuclear Envelope in Adrenal Zona Fasciculata Cells.

Despite previous research efforts in the fields of histology and cell physiology, the relationship between chromatin structural organization and nuclear shape remains unclear. The aim of this research was to test the existence and strength of correlations between mathematical parameters of chromatin microarchitecture and roundness of the nuclear envelope. On a sample of 240 nuclei of adrenal zona fasciculata cells stained using the DNA-specific Feulgen method, we quantified fractal parameters such as fractal dimension and lacunarity, as well as textural parameters such as angular second moment (ASM), entropy, inverse difference moment, contrast, and variance. Circularity of the nuclear envelope was determined from the nuclear area and perimeter. The results indicate that there is a statistically significant negative correlation between chromatin ASM and circularity. Moreover, there was a statistically significant positive correlation between chromatin fractal dimension and envelope circularity. This is the first study to demonstrate these relationships in adrenal tissue, and also one of the first studies to test the connection between circularity and fractal and gray-level co-occurrence matrix parameters in DNA-specific Feulgen stain. The results could be useful both as an addition to the current knowledge on chromatin/nuclear envelope interactions, and for design of future computer-assisted research software for evaluation of nuclear morphology.

Discriminatory ability of fractal and grey level co-occurrence matrix methods in structural analysis of hippocampus layers.

Fractal and grey level co-occurrence matrix (GLCM) analysis represent two mathematical computer-assisted algorithms that are today thought to be able to accurately detect and quantify changes in tissue architecture during various physiological and pathological processes. However, despite their numerous applications in histology and pathology, their sensitivity, specificity and validity regarding evaluation of brain tissue remain unclear. In this article we present the results indicating that certain parameters of fractal and GLCM analysis have high discriminatory ability in distinguishing two morphologically similar regions of rat hippocampus: stratum lacunosum-moleculare and stratum radiatum. Fractal and GLCM algorithms were performed on a total of 240 thionine-stained hippocampus micrographs of 12 male Wistar albino rats. 120 digital micrographs represented stratum lacunosum-moleculare, and another 120 stratum radiatum. For each image, 7 parameters were calculated: fractal dimension, lacunarity, GLCM angular second moment, GLCM contrast, inverse difference moment, GLCM correlation, and GLCM variance. GLCM variance (VAR) resulted in the largest area under the Receiver operating characteristic (ROC) curve of 0.96, demonstrating an outstanding discriminatory power in analysis of stratum lacunosum-moleculare (average VAR equaled 478.1 ± 179.8) and stratum radiatum (average VAR of 145.9 ± 59.2, p < 0.0001). For the criterion VAR ≤ 227.5, sensitivity and specificity were 90% and 86.7%, respectively. GLCM correlation as a parameter also produced large area under the ROC curve of 0.95. Our results are in accordance with the findings of our previous study regarding brain white mass fractal and textural analysis. GLCM algorithm as an image analysis method has potentially high applicability in structural analysis of brain tissue cytoarcitecture.

Repetitive hyperbaric oxygenation attenuates reactive astrogliosis and suppresses expression of inflammatory mediators in the rat model of brain injury.

The exact mechanisms by which treatment with hyperbaric oxygen (HBOT) exerts its beneficial effects on recovery after brain injury are still unrevealed. Therefore, in this study we investigated the influence of repetitive HBOT on the reactive astrogliosis and expression of mediators of inflammation after cortical stab injury (CSI). CSI was performed on male Wistar rats, divided into control, sham, and lesioned groups with appropriate HBO. The HBOT protocol was as follows: 10 minutes of slow compression, 2.5 atmospheres absolute (ATA) for 60 minutes, and 10 minutes of slow decompression, once a day for 10 consecutive days. Data obtained using real-time polymerase chain reaction, Western blot, and immunohistochemical and immunofluorescence analyses revealed that repetitive HBOT applied after the CSI attenuates reactive astrogliosis and glial scarring, and reduces expression of GFAP (glial fibrillary acidic protein), vimentin, and ICAM-1 (intercellular adhesion molecule-1) both at gene and tissue levels. In addition, HBOT prevents expression of CD40 and its ligand CD40L on microglia, neutrophils, cortical neurons, and reactive astrocytes. Accordingly, repetitive HBOT, by prevention of glial scarring and limiting of expression of inflammatory mediators, supports formation of more permissive environment for repair and regeneration.

Application of fractal and grey level co-occurrence matrix analysis in evaluation of brain corpus callosum and cingulum architecture.

This aim of this study was to assess the discriminatory value of fractal and grey level co-occurrence matrix (GLCM) analysis methods in standard microscopy analysis of two histologically similar brain white mass regions that have different nerve fiber orientation. A total of 160 digital micrographs of thionine-stained rat brain white mass were acquired using a Pro-MicroScan DEM-200 instrument. Eighty micrographs from the anterior corpus callosum and eighty from the anterior cingulum areas of the brain were analyzed. The micrographs were evaluated using the National Institutes of Health ImageJ software and its plugins. For each micrograph, seven parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, GLCM variance, fractal dimension, and lacunarity. Using the Receiver operating characteristic analysis, the highest discriminatory value was determined for inverse difference moment (IDM) (area under the receiver operating characteristic (ROC) curve equaled 0.925, and for the criterion IDM≤0.610 the sensitivity and specificity were 82.5 and 87.5%, respectively). Most of the other parameters also showed good sensitivity and specificity. The results indicate that GLCM and fractal analysis methods, when applied together in brain histology analysis, are highly capable of discriminating white mass structures that have different axonal orientation.

Machine learning approaches to detect hepatocyte chromatin alterations from iron oxide nanoparticle exposure.

This study focuses on developing machine learning models to detect subtle alterations in hepatocyte chromatin organization due to Iron (II, III) oxide nanoparticle exposure, hypothesizing that exposure will significantly alter chromatin texture. A total of 2000 hepatocyte nuclear regions of interest (ROIs) from mouse liver tissue were analyzed, and for each ROI, 5 different parameters were calculated: Long Run Emphasis, Short Run Emphasis, Run Length Nonuniformity, and 2 wavelet coefficient energies obtained after the discrete wavelet transform. These parameters served as input for supervised machine learning models, specifically random forest and gradient boosting classifiers. The models demonstrated relatively robust performance in distinguishing hepatocyte chromatin structures belonging to the group exposed to IONPs from the controls. The study's findings suggest that iron oxide nanoparticles induce substantial changes in hepatocyte chromatin distribution and underscore the potential of AI techniques in advancing hepatocyte evaluation in physiological and pathological conditions.

A sustainable approach to derive sheep corneal scaffolds from stored slaughterhouse waste.

Aim: The escalating demand for corneal transplants significantly surpasses the available supply. To bridge this gap, we concentrated on ethical and sustainable corneal grafting sources. Our objective was to create viable corneal scaffolds from preserved slaughterhouse waste.Materials & methods: Corneas were extracted and decellularized from eyeballs that had been refrigerated for several days. These scaffolds underwent evaluation through DNA quantification, histological analysis, surface tension measurement, light propagation testing, and tensile strength assessment.Results: Both the native and acellular corneas (with ~90% DNA removed using a cost-effective and environmentally friendly surfactant) maintained essential optical and biomechanical properties for potential clinical use.Conclusion: Our method of repurposing slaughterhouse waste, stored at 4°C for several days, to develop corneal scaffolds offers a sustainable and economical alternative xenograft model.

[Box: see text].

Complexity reduction of chromatin architecture in macula densa cells during mouse postnatal development.

AIM: To determine whether complexity of chromatin structure in kidney macula densa cells (MDC) decreases during postnatal development in mice. METHODS: The levels of chromatin structural complexity were measured by determining fractal dimension of MDC nuclei. Kidney tissue was obtained from the total of 32 male Swiss albino mice divided into four age groups (n = 8): newborn (0 days), 10 days old, 20 days old and 30 days old. For a total of 640 MDC chromatin structures, fractal dimension, lacunarity, as well as parameters of Grey level co-occurrence matrix (GLCM) texture were determined. RESULTS: Chromatin fractal dimension in animals aged 10 days, 20 days and 30 days was significantly lower (P < 0.05, P < 0.01 and P < 0.001, respectively), compared with newborn mice. This complexity reduction of chromatin architecture is in accordance with previously published studies, which detected generalized and sustained loss of both tissue and cell complexity during aging. The loss of complexity was texture-independent, since there was no statistically significant difference (P > 0.05) in both chromatin angular second moment and inverse difference moment between the age groups. CONCLUSION: Our results indicate that age-related nuclear intrinsic factors which do not influence chromatin texture may have an important role in MDC postnatal development.