Igor Pantic

Online Social Networking and Mental Health

During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction.

Relationship between internet use and depression

A cross-sectional observational study was conducted on a sample of 336 adolescents.There was a positive correlation between internet addiction and depression.The detected relationship is independent from social networking activities. The aim of the research was to investigate the potential relationship between internet addiction and depression in adolescents. A cross-sectional observational study was conducted on a sample of 336 high school students in Belgrade, Serbia. Each student was given a questionnaire consisting of Center for Epidemiologic Studies of Depression Scale for Children (CES-DC), Young Internet Addiction Test (IAT) as well as general questions related to internet and social networking site (SNS) use. The results of our study indicate that internet use and level of internet addiction measured with IAT scale are positively correlated with depressive symptoms. No such relationship existed between the time spent on social networking sites and depression, as well as between depression symptoms and SNS-related activities such as the number of Facebook friends. Neither the time spent on SNSs nor SNS-related activities had significant effect on the observed relationship between level of internet addiction and depression.

Association between Facebook addiction, self-esteem and life satisfaction

In recent years, many research efforts have been focused on investigation of potential connection between social networking and mental health issues. Particularly important and controversial remains the association between Facebook use, self-esteem and life satisfaction. In our cross-sectional study, on a sample of 381 Facebook users, we tested the existence and strength of this relationship using Bergen Facebook Addiction Scale (BFAS), Facebook Intensity Scale (FBI), Rosenbergs Self-Esteem Scale (SES), and Satisfaction With Life Scale (SWLS). With k-means cluster analysis, we divided the sample into 3 groups: ordinary, intensive, and addicted Facebook users. The results of our study show that ordinary Facebook users differ statistically in self-esteem and life satisfaction from both addicted and intensive users. Facebook addiction was in relation with lower self-esteem. Facebook addiction was also negatively related to life satisfaction. These results are in accordance with the previously published findings of other authors in the fields of social networking psychology and psychiatry. We investigated the relationship between Facebook use, self-esteem and life satisfaction.The study was done on a sample of 381 Facebook users.Facebook addiction was negatively related to satisfaction with life.The results are in accordance with the previously published findings.

Gray level co-occurrence matrix texture analysis of germinal center light zone lymphocyte nuclei: physiology viewpoint with focus on apoptosis.

In our study we investigated the relationship between conventional morphometric indicators of nuclear size and shape (area and circularity) and the parameters of gray level co-occurrence matrix texture analysis (entropy, homogeneity, and angular second moment) in cells committed to apoptosis. A total of 432 lymphocyte nuclei images from the spleen germinal center light zones (cells in early stages of apoptosis) were obtained from eight healthy male guinea pigs previously immunized with sheep red blood cells (antigen). For each nucleus, area, circularity, entropy, homogeneity, and angular second moment were determined. All measured parameters of gray level co-occurrence matrix (GLCM) were significantly correlated with morphometric indicators of nuclear size and shape. The strongest correlation was observed between GLCM homogeneity and nuclear area (p < 0.0001, r(s) = 0.61). Angular second moment values were also highly significantly correlated with nuclear area (r(s)= 0.39, p < 0.0001). These results indicate that the GLCM method may be a powerful tool in evaluation of ultrastructural nuclear changes during early stages of the apoptotic process.

Changes in fractal dimension and lacunarity as early markers of UV-induced apoptosis

The aim of our study was to employ fractal analysis for evaluation of ultrastructural changes during early stages of apoptosis. Apoptosis was induced in U251 human glioma cell line by exposure to UVB light. The cells were visualized by optical phase-contrast microscopy and photographed before the UV treatment, immediately after the treatment, as well as at 30 min intervals during 5h observation period. For each of the 32 cells analyzed, cellular and nuclear fractal dimension, as well as nuclear lacunarity, were determined at each time point. Our data demonstrate that cellular ultrastructural complexity determined by fractal dimension and lacunarity significantly decreases after the UV irradiation, with the nuclear lacunarity being a particularly sensitive parameter in detecting early apoptosis. Importantly, fractal analysis was able to detect cellular apoptotic changes earlier than conventional flow cytometric analysis of phosphatidylserine exposure, DNA fragmentation and cell membrane permeabilization. These results indicate that fractal analysis might be a powerful and affordable method for non-invasive early identification of apoptosis in cell cultures.

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

To determine whether complexity of chromatin structure in kidney macula densa cells (MDC) decreases during postnatal development in mice.

Aging increases nuclear chromatin entropy of erythroid precursor cells in mice spleen hematopoietic tissue.

Despite recent advances in hematopoietic tissue research, effects of aging on hematopoietic erythroid precursor (EP) cells are unclear. In this article we present results suggesting that chromatin textural entropy of EP cells in mouse spleen increases with age, while chromatin homogeneity decreases. The experiment was conducted on a total of 32 male Swiss white mice. Spleen tissue was acquired from four age groups: 10 days, 1 month, 4 months, and 7 months old mice. A total of 640 randomly selected, nonoverlapping EP cell nuclei (20 per animal) were analyzed using the gray level co-occurrence matrix method. There was statistically highly significant difference between the age groups, both in chromatin entropy (ANOVA, F = 12.99, p < 0.0001) and in homogeneity (ANOVA, F = 7.05, p < 0.001). When the individual groups were compared (ANOVA post hoc test), statistical difference was detected in all group pairs, except between the animals 4 months and 7 months old, either in chromatin entropy or homogeneity. The detected increase of chromatin disorder in mouse juvenile period/early adulthood suggests that cell intrinsic factors such as epigenetic dysregulation and DNA damage accumulation may have an important role in EP cell aging.

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.

Cancer stem cell hypotheses: impact on modern molecular physiology and pharmacology research.

Although questioned on several occasions, the existence of cancer stem cells (CSCs) has been confirmed by a number of studies on experimental animal models. Nevertheless, it was shown that CSC hypotheses have several limitations and inconsistencies regarding the explanation of CSC origin, CSC identification and isolation, possible heterogeneity within CSC population, as well as methodology issues in some studies that were carried out in order to prove CSC existence. The aim of this article is to give a short and comprehensive review of recent advances concerning CSC hypothesis and to describe its impact on modern molecular physiology and pharmacology research.

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.