The diaspora model for human migration.

Migration's impact spans various social dimensions, including demography, sustainability, politics, economy, and gender disparities. Yet, the decision-making process behind migrants choosing their destination remains elusive. Existing models primarily rely on population size and travel distance to explain the spatial patterns of migration flows, overlooking significant population heterogeneities. Paradoxically, migrants often travel long distances and to smaller destinations if their diaspora is present in those locations. To address this gap, we propose the diaspora model of migration, incorporating intensity (the number of people moving to a country), and assortativity (the destination within the country). Our model considers only the existing diaspora sizes in the destination country, influencing the probability of migrants selecting a specific residence. Despite its simplicity, our model accurately reproduces the observed stable flow and distribution of migration in Austria (postal code level) and US metropolitan areas, yielding precise estimates of migrant inflow at various geographic scales. Given the increase in international migrations, this study enlightens our understanding of migration flow heterogeneities, helping design more inclusive, integrated cities.

Implicit racial biases are lower in more populous more diverse and less segregated US cities.

Implicit biases - differential attitudes towards members of distinct groups - are pervasive in human societies and create inequities across many aspects of life. Recent research has revealed that implicit biases are generally driven by social contexts, but not whether they are systematically influenced by the ways that humans self-organize in cities. We leverage complex system modeling in the framework of urban scaling theory to predict differences in these biases between cities. Our model links spatial scales from city-wide infrastructure to individual psychology to predict that cities that are more populous, more diverse, and less segregated are less biased. We find empirical support for these predictions in U.S. cities with Implicit Association Test data spanning a decade from 2.7 million individuals and U.S. Census demographic data. Additionally, we find that changes in cities' social environments precede changes in implicit biases at short time-scales, but this relationship is bi-directional at longer time-scales. We conclude that the social organization of cities may influence the strength of these biases.

On the inadequacy of nominal assortativity for assessing homophily in networks.

Nominal assortativity (or discrete assortativity) is widely used to characterize group mixing patterns and homophily in networks, enabling researchers to analyze how groups interact with one another. Here we demonstrate that the measure presents severe shortcomings when applied to networks with unequal group sizes and asymmetric mixing. We characterize these shortcomings analytically and use synthetic and empirical networks to show that nominal assortativity fails to account for group imbalance and asymmetric group interactions, thereby producing an inaccurate characterization of mixing patterns. We propose the adjusted nominal assortativity and show that this adjustment recovers the expected assortativity in networks with various level of mixing. Furthermore, we propose an analytical method to assess asymmetric mixing by estimating the tendency of inter- and intra-group connectivities. Finally, we discuss how this approach enables uncovering hidden mixing patterns in real-world networks.

Assessing the thyroid autoimmunity association with recurrent aphthous stomatitis.

BACKGROUND: Recent investigations have highlighted autoimmune origins and abnormal immune responses; particularly those related to T cell-mediated immunity and elevated T lymphocyte cells in the oral mucosa. Therefore, we investigated the relationship between recurrent aphthous stomatitis (RAS) and autoimmune thyroid diseases (ATDs) in an Iranian population. METHODS: A cross-sectional study was performed on 102 patients diagnosed with ATD (cases) and 102 healthy patients (controls) who had been referred for the routine dental treatment. All participants were asked for the history of RAS and their age, gender, other systemic diseases, medications, and frequency of RAS in a year. Matching was performed based on the propensity scores for age and sex. In addition, the number of lesions in each recurrence in both groups was assessed and compared. The type of thyroid disease has been assessed for case participants and has been confirmed by the endocrinologist. The chi-square test, t-test, and Mann-Whitney U test were used to analyze the data using SPSS 18. RESULTS: Patients with ATD had higher RAS than healthy controls (P = 0.040). ATD patients had 1.93 times more risk for RAS, and the frequency of RAS in a year was 3.15times higher in these patients (P = 0.011). Moreover, the frequency of RAS was higher in patients with hypothyroidism than in those with hyperthyroidism. However, there were no significant differences in the size and the number of lesions between the groups. CONCLUSION: The risk and frequency of RAS were significantly higher in patients with ATDs. This would provide valuable insights into the underlying mechanisms and potential treatment strategies for both conditions.

The effect of body position change on noninvasively acquired intracranial pulse waves.

Objective. Craniospinal compliance (CC) is an important metric for the characterization of space-occupying neurological pathologies. CC is obtained using invasive procedures that carry risks for the patients. Therefore, noninvasive methods for acquiring surrogates of CC have been proposed, most recently based on changes in the head's dielectric properties during the cardiac cycle. Here, we have tested whether changes in body position, which are known to influence CC, are reflected in a capacitively acquired signal (hereinafter referred to as W) originating from dynamic changes of the head's dielectric properties.Approach. eighteen young healthy volunteers were included in the study. After 10 min in supine position, subjects were tilted head-up (HUT), back to 0° (horizontal, control), and then head-down (HDT). Metrics related to cardiovascular action were extracted from W, including AMP, the peak-to-valley amplitude of the cardiac modulation of W. Computational electromagnetic simulations were performed to probe the association between intracranial volume change and W.Main results. AMP decreased during HUT (0°: 2869 ± 597 arbitrary units (au); +75°: 2307 ± 490 au,P= 0.002) and increased during HDT (-30°: 4403 ± 1428 au,P< 0.0001). The same behavior was predicted by the electromagnetic model.Significance. tilting affects the distribution of CC between cranial and spinal compartments. Cardiovascular action induces compliance-dependent oscillatory changes in the intracranial fluid composition, which causes corresponding variations in the head's dielectric properties. These manifest as increasing AMP with decreasing intracranial compliance, which suggests that W may contain information related to CC, and that it might be possible to derive CC surrogates therefrom.

Noninvasive Monitoring of Intracranial Pulse Waves.

OBJECTIVE: The clinical management of several neurological disorders benefits from the assessment of intracranial pressure and craniospinal compliance. However, the associated procedures are invasive in nature. Here, we aimed to assess whether naturally occurring periodic changes in the dielectric properties of the head could serve as the basis for deriving surrogates of craniospinal compliance noninvasively. METHODS: We designed a device and electrodes for noninvasive measurement of periodic changes of the dielectric properties of the human head. We characterized the properties of the device-electrode-head system by measurements on healthy volunteers, by computational modeling, and by electromechanical modeling. We then performed hyperventilation testing to assess whether the measured signal is of intracranial origin. RESULTS: Signals obtained with the device on volunteers showed characteristic cardiac and respiratory modulations. Signal oscillations can be attributed primarily to changes in resistive properties of the head during cardiac and respiratory cycles. Reduction of end-tidal CO2, through hyperventilation, resulted in a decrease in the signal amplitude associated with cardiovascular action. CONCLUSION: Given the higher CO2 reactivity of intracranial vessels compared to extracranial ones, the results of hyperventilation testing suggest that the acquired signal is, in part, of intracranial origin. SIGNIFICANCE: If confirmed in larger cohorts, our observations suggest that noninvasive capacitive acquisition of changes in the dielectric properties of the head could be used to derive surrogates of craniospinal compliance.

Theory for a non-invasive diagnostic biomarker for craniospinal diseases.

Monitoring intracranial pressure (ICP) and craniospinal compliance (CC) is frequently required in the treatment of patients suffering from craniospinal diseases. However, current approaches are invasive and cannot provide continuous monitoring of CC. Dynamic exchange of blood and cerebrospinal fluid (CSF) between cranial and spinal compartments due to cardiac action transiently modulates the geometry and dielectric properties of the brain. The resulting impedance changes can be measured and might be usable as a non-invasive CC surrogate. A numerically robust and computationally efficient approach based on the reciprocity theorem was developed to compute dynamic impedance changes resulting from small geometry and material property changes. The approach was successfully verified against semi-analytical benchmarks, before being combined with experimental brain pulsation data to study the information content of the impedance variation. The results indicate that the measurable signal is dominated by the pulsatile displacement of the cortical brain surface, with minor contributions from the ventricular surfaces and from changes in brain perfusion. Different electrode setups result in complementary information. The information content from the investigated three electrode pairs was employed to successfully infer subject-specific brain pulsation and motion features. This suggests that non-invasive CC surrogates based on impedance monitoring could be established.

Determinants of Bone Mineral Density in Iranian Women with Polycystic Ovary Syndrome.

Background: Whether the endocrine aberrations caused by polycystic ovary syndrome (PCOS) might influence bone density in women of reproductive age is controversial. Objectives: The present study aimed to compare PCOS women to a control group matched in terms of age and body mass index (BMI) regarding bone indices and to clarify the potential relationship between their hormonal changes and bone density. Methods: This case-control study consisted of 61 PCOS patients, and 35 women with normal ovulatory function served as controls. Bone parameters, including bone mineral content (BMC) and bone mineral density (BMD) in addition to T- and Z-scores, were measured at the lumbar vertebrae, neck of the left femur, hip, and distal part of the radial bone, using dual-energy X-ray absorptiometry. Blood samples were taken to be tested for biochemical parameters and serum concentrations of insulin, osteocalcin, parathyroid hormone (PTH), vitamin D, follicle-stimulating hormone (FSH), luteinizing hormone (LH), total testosterone, dehydroepiandrosterone sulfate (DHEAS), and estradiol were measured. Insulin resistance was evaluated through the homeostatic model assessment of insulin resistance (HOMA-IR). Results: The results revealed greater levels of HOMA-IR and total testosterone in PCOS women than in controls. Nevertheless, the two groups were comparable in terms of bone parameters. In the control group, BMI was the only determinant of bone density at most of the skeletal sites. Nonetheless, BMI and HOMA-IR were independently and positively associated with bone indices at the femoral neck (FN) and total hip in the PCOS group. Parathyroid hormone and vitamin D concentrations were not different in the two groups. However, phosphate levels were higher in PCOS patients (P = 0.025). Osteocalcin was inversely correlated to BMI, and both groups had a negative correlation between DHEAS and PTH. Serum phosphate was inversely and independently associated with estrogen in the PCOS group (r = -0.377, P = 0.004). Conclusions: Body mass index and HOMA-IR were independent and positive determinants of FN and total hip bone density in the PCOS subjects. Nonetheless, in the non-PCOS women, BMI was the only independent determinant of bone density at most of the skeletal sites. Additionally, osteocalcin was inversely correlated with BMI in both groups.

Inequality and inequity in network-based ranking and recommendation algorithms.

Though algorithms promise many benefits including efficiency, objectivity and accuracy, they may also introduce or amplify biases. Here we study two well-known algorithms, namely PageRank and Who-to-Follow (WTF), and show to what extent their ranks produce inequality and inequity when applied to directed social networks. To this end, we propose a directed network model with preferential attachment and homophily (DPAH) and demonstrate the influence of network structure on the rank distributions of these algorithms. Our main findings suggest that (i) inequality is positively correlated with inequity, (ii) inequality is driven by the interplay between preferential attachment, homophily, node activity and edge density, and (iii) inequity is driven by the interplay between homophily and minority size. In particular, these two algorithms reduce, replicate and amplify the representation of minorities in top ranks when majorities are homophilic, neutral and heterophilic, respectively. Moreover, when this representation is reduced, minorities may improve their visibility in the rank by connecting strategically in the network. For instance, by increasing their out-degree or homophily when majorities are also homophilic. These findings shed light on the social and algorithmic mechanisms that hinder equality and equity in network-based ranking and recommendation algorithms.

Advances in the agent-based modeling of economic and social behavior.

In this review we discuss advances in the agent-based modeling of economic and social systems. We show the state of the art of the heuristic design of agents and how behavioral economics and laboratory experiments have improved the modeling of agent behavior. We further discuss how economic networks and social systems can be modeled and we discuss novel methodology and data sources. Lastly, we present an overview of estimation techniques to calibrate and validate agent-based models and show avenues for future research.

Insulin resistance and bone health in adolescents.

Insulin resistance may be linked to bone health in young people. This study is the first on adolescents that jointly examined the association of bone health with insulin resistance and body composition. Our results revealed significant negative association between bone parameters and insulin resistance, even after adjustment for confounding factors. PURPOSE: Previous studies are suggestive of the protective role of insulin on bone in adults. Whether this association exists in younger individuals is not clear, yet. This investigation aimed to evaluate the association between insulin resistance, bone parameters, and body composition amongst Iranian adolescentsá¾½ population. METHODS: A cross-sectional study was conducted on 423 participants (224 girls and 199 boys) aged 9-19 years old. Insulin resistance was assessed, using a homeostatic model assessment of insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI). Bone mineral density (BMD), bone mineral content (BMC), total body fat mass (TBFM), and total body lean mass (TBLM) were measured, using dual energy X-ray absorptiometry (DXA), and bone mineral apparent density (BMAD) was calculated. RESULTS: In multiple regression analyses adjusted for potential confounders, the HOMA-IR showed statistically significant negative association with most of the bone parameters (ß = - 1.1 to - 0.002, P = 0.004 to 0.036). On the subject of QUICKI index, this relationship was detected only for lumbar spine (LS) parameters (ß = 0.062 to 37.21, P = 0.0001 to 0.026) and femoral neck bone mineral content (FNBMC) (ß = 1.297, P = 0.013). CONCLUSION: Our results suggest that insulin resistance may be inversely and independently associated with the bone indices in younger individuals. Whether high insulin levels have detrimental effects on growing bone is still unclear and has to be answered.

Pure Androgen-Secreting Adrenocortical Carcinoma Presenting with Hypoglycemia.

Adrenocortical carcinoma (ACC) is a rare and aggressive malignancy. Most patients present with steroid hormone excess or abdominal mass effect. Pure androgen-secreting ACCs are rare, while hypoglycemia is an unusual presentation of this malignancy. We present a 26-year-old woman with hypoglycemia and history of adrenalectomy due to a large adrenal mass which was diagnosed as nonfunctional adrenal adenoma. She was admitted in our hospital 10 days after her fetal loss with repeated episodes of severe hypoglycemia. She had a high serum dehydroepiandrosterone sulfate (DHEA-S) and her hypoglycemia was associated with low insulin and C-peptide levels. Imaging revealed liver metastasis and immunohistochemical studies of the biopsied lesions confirmed the diagnosis of ACC.

Computational analysis of non-invasive deep brain stimulation based on interfering electric fields.

Neuromodulation modalities are used as effective treatments for some brain disorders. Non-invasive deep brain stimulation (NDBS) via temporally interfering electric fields has emerged recently as a non-invasive strategy for electrically stimulating deep regions in the brain. The objective of this study is to provide insight into the fundamental mechanisms of this strategy and assess the potential uses of this method through computational analysis. Analytical and numerical methods are used to compute the electric potential and field distributions generated during NDBS in homogeneous and inhomogeneous models of the brain. The computational results are used for specifying the activated area in the brain (macroscopic approach), and quantifying its relationships to the stimulation parameters. Two automatic algorithms, using artificial neural network (ANN), are developed for the homogeneous model with two and four electrode pairs to estimate stimulation parameters. Additionally, the extracellular potentials are coupled to the compartmental axon cable model to determine the responses of the neurons to the modulated electric field in two developed models and to evaluate the precise activated area location (microscopic approach). Our results show that although the shape of the activated area was different in macroscopic and microscopic approaches, it located only at depth. Our optimization algorithms showed significant accuracy in estimating stimulation parameters. Moreover, it demonstrated that the more the electrode pairs, the more controllable the activated area. Finally, compartmental axon cable modeling results verified that neurons can demodulate and follow the electric field modulation envelope amplitude (MEA) in our models. The results of this study help develop the NDBS method and eliminate some limitations associated with the nonautomated optimization algorithm.

Homophily and minority-group size explain perception biases in social networks.

People's perceptions about the size of minority groups in social networks can be biased, often showing systematic over- or underestimation. These social perception biases are often attributed to biased cognitive or motivational processes. Here we show that both over- and underestimation of the size of a minority group can emerge solely from structural properties of social networks. Using a generative network model, we show that these biases depend on the level of homophily, its asymmetric nature and on the size of the minority group. Our model predictions correspond well with empirical data from a cross-cultural survey and with numerical calculations from six real-world networks. We also identify circumstances under which individuals can reduce their biases by relying on perceptions of their neighbours. This work advances our understanding of the impact of network structure on social perception biases and offers a quantitative approach for addressing related issues in society.

Homophily influences ranking of minorities in social networks.

Homophily can put minority groups at a disadvantage by restricting their ability to establish links with a majority group or to access novel information. Here, we show how this phenomenon can influence the ranking of minorities in examples of real-world networks with various levels of heterophily and homophily ranging from sexual contacts, dating contacts, scientific collaborations, and scientific citations. We devise a social network model with tunable homophily and group sizes, and demonstrate how the degree ranking of nodes from the minority group in a network is a function of (i) relative group sizes and (ii) the presence or absence of homophilic behaviour. We provide analytical insights on how the ranking of the minority can be improved to ensure the representativeness of the group and correct for potential biases. Our work presents a foundation for assessing the impact of homophilic and heterophilic behaviour on minorities in social networks.

Primary Adrenal Lymphoma Presenting with Adrenal Failure: A Case Report and Review of the Literature.

INTRODUCTION: Primary adrenal lymphoma is rare, with a few cases reported in the literature. Most often it manifests as bilateral adrenal lesions and adrenal insufficiency is a common complication. CASE PRESENTATION: A 53-year-old male was referred with abdominal discomfort and darkening of the skin since 1 month prior to admission. His workups detected large bilateral adrenal masses. The patient was admitted due to hypotension, and was diagnosed with adrenal insufficiency. Laboratory studies showed high erythrocyte sedimentation rate (ESR), lactate dehydrogenase (LDH), and adrenocorticotropin levels. There was no other organ involvement and computed tomography (CT)-guided percutaneous biopsy of the adrenal gland revealed B-cell type of non-Hodgkin lymphoma. Replacement therapy with glucocorticoid and mineralocorticoid was initiated with remission of symptoms. After 3 months of chemotherapy his condition improved, but the patient worsened thereafter and died 2 months later. CONCLUSIONS: However, this case reminded the importance of considering primary adrenal lymphoma in the differential diagnosis of bilateral adrenal masses, especially if the patient presents with adrenal insufficiency.

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

Simulating irrational human behavior to prevent resource depletion.

In a situation with a limited common resource, cooperation between individuals sharing the resource is essential. However, people often act upon self-interest in irrational ways that threaten the long-term survival of the whole group. A lack of sustainable or environmentally responsible behavior is often observed. In this study, we examine how the maximization of benefits principle works in a wider social interactive context of personality preferences in order to gain a more realistic insight into the evolution of cooperation. We used time perspective (TP), a concept reflecting individual differences in orientation towards past, present, or future, and relevant for making sustainable choices. We developed a personality-driven agent-based model that explores the role of personality in the outcomes of social dilemmas and includes multiple facets of diversity: (1) The agents have different behavior strategies: individual differences derived by applying cluster analysis to survey data from 22 countries (N = 10,940) and resulting in 7 cross-cultural profiles of TP; (2) The non-uniform distribution of the types of agents across countries; (3) The diverse interactions between the agents; and (4) diverse responses to those interactions in a well-mixed population. As one of the results, we introduced an index of overall cooperation for each of the 22 countries, which was validated against cultural, economic, and sustainability indicators (HDI, dimensions of national culture, and Environment Performance Index). It was associated with higher human development, higher individualism, lower power distance, and better environmental performance. The findings illustrate how individual differences in TP can be simulated to predict the ways people in different countries solve the personal vs. common gain dilemma in the global limited-resource situation. This interdisciplinary approach to social simulation can be adopted to explain the possible causes of global environmental issues and to predict their possible outcomes.

Thyroid disorders and the prevalence of antithyroid antibodies in Shiraz population.

BACKGROUND AND OBJECTIVES: Thyroid dysfunction is a common health problem affecting millions of patients worldwide. Autoimmune thyroid disorders are among the most common autoimmune disorders. In this population-based study, we assessed the prevalence of abnormal thyroid function, antithyroid antibodies and the probable relationship between them in Shiraz, southern Iran. METHODS: Serum thyrotropin (TSH) was determined in 981 subjects (66.8% female and 33.2% male; mean age: 39.1 ± 14.3 years), who were selected with stratified random sampling. Because of the preponderance of females over males, we performed the statistical analyses using sex-weighted data (50% for each sex). Also, antithyroid peroxidase antibodies (TPOAb), and antithyroglobulin antibodies (TgAb) were measured in two random subgroups of 376 and 537 patients respectively). Thyromegaly detected on physical examination. RESULTS: In this cross-sectional study, 8.1% of participants had elevated serum TSH level and 3.4% had low serum TSH level. A statistically significant relationship was found between gender and thyromegaly and TSH values. Positive TPOAb and positive TgAb were detected in 17% and 5.1% of participants respectively. In addition, a significant relationship was observed between elevated TSH levels and positive results for both antibodies. Detectable levels of thyroid antibodies correlated with female sex, while no correlation was observed between detectable levels of thyroid antibodies and thyromegaly. CONCLUSION: Thyroid disorders, especially elevated TSH level, are common. It seems that autoimmune mechanisms are strongly involved in the etiology of hypothyroidism in this area.