Suicide ideation of individuals in online social networks

Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user), and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.Comment: 4 figures, 9 table

New ophthalmosaurid ichthyosaurs from the European lower cretaceous demonstrate extensive ichthyosaur survival across the Jurassic–Cretaceous boundary

Background Ichthyosauria is a diverse clade of marine amniotes that spanned most of the Mesozoic. Until recently, most authors interpreted the fossil record as showing that three major extinction events affected this group during its history: one during the latest Triassic, one at the Jurassic–Cretaceous boundary (JCB), and one (resulting in total extinction) at the Cenomanian-Turonian boundary. The JCB was believed to eradicate most of the peculiar morphotypes found in the Late Jurassic, in favor of apparently less specialized forms in the Cretaceous. However, the record of ichthyosaurs from the Berriasian–Barremian interval is extremely limited, and the effects of the end-Jurassic extinction event on ichthyosaurs remains poorly understood. Methodology/Principal Findings Based on new material from the Hauterivian of England and Germany and on abundant material from the Cambridge Greensand Formation, we name a new ophthalmosaurid, Acamptonectes densus gen. et sp. nov. This taxon shares numerous features with Ophthalmosaurus, a genus now restricted to the Callovian–Berriasian interval. Our phylogenetic analysis indicates that Ophthalmosauridae diverged early in its history into two markedly distinct clades, Ophthalmosaurinae and Platypterygiinae, both of which cross the JCB and persist to the late Albian at least. To evaluate the effect of the JCB extinction event on ichthyosaurs, we calculated cladogenesis, extinction, and survival rates for each stage of the Oxfordian–Barremian interval, under different scenarios. The extinction rate during the JCB never surpasses the background extinction rate for the Oxfordian–Barremian interval and the JCB records one of the highest survival rates of the interval. Conclusions/Significance There is currently no evidence that ichthyosaurs were affected by the JCB extinction event, in contrast to many other marine groups. Ophthalmosaurid ichthyosaurs remained diverse from their rapid radiation in the Middle Jurassic to their total extinction at the beginning of the Late Cretaceous

Molecular and cellular mechanisms underlying the evolution of form and function in the amniote jaw.

The amniote jaw complex is a remarkable amalgamation of derivatives from distinct embryonic cell lineages. During development, the cells in these lineages experience concerted movements, migrations, and signaling interactions that take them from their initial origins to their final destinations and imbue their derivatives with aspects of form including their axial orientation, anatomical identity, size, and shape. Perturbations along the way can produce defects and disease, but also generate the variation necessary for jaw evolution and adaptation. We focus on molecular and cellular mechanisms that regulate form in the amniote jaw complex, and that enable structural and functional integration. Special emphasis is placed on the role of cranial neural crest mesenchyme (NCM) during the species-specific patterning of bone, cartilage, tendon, muscle, and other jaw tissues. We also address the effects of biomechanical forces during jaw development and discuss ways in which certain molecular and cellular responses add adaptive and evolutionary plasticity to jaw morphology. Overall, we highlight how variation in molecular and cellular programs can promote the phenomenal diversity and functional morphology achieved during amniote jaw evolution or lead to the range of jaw defects and disease that affect the human condition

Mammary stem cells, self-renewal pathways, and carcinogenesis

The mammary gland epithelial components are thought to arise from stem cells that undergo both self-renewal and differentiation. Self-renewal has been shown to be regulated by the Hedgehog, Notch, and Wnt pathways and the transcription factor B lymphoma Mo-MLV insertion region 1 (Bmi-1). We review data about the existence of stem cells in the mammary gland and the pathways regulating the self-renewal of these cells. We present evidence that deregulation of the self-renewal in stem cells/progenitors might be a key event in mammary carcinogenesis. If 'tumor stem cells' are inherently resistant to current therapies, targeting stem cell self-renewal pathways might provide a novel approach for breast cancer treatment

Systems Biology by the Rules: Hybrid Intelligent Systems for Pathway Modeling and Discovery

Background: Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. Results: A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. Conclusion: This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer

Identification of Galaxy-Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning

We perform a search for galaxy-galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey, which contains 1/4520 million astronomical sources covering 1/44000 deg2 of the southern sky to a 5σ point-source depth of g = 24.3, r = 23.9, i = 23.3, and z = 22.8 mag. Following the methodology of similar searches using Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of 1/411 million extended astronomical sources. After scoring with our CNN, the highest-scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap (b > 10 deg) and southern celestial hemisphere (decl. < 0 deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates that were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation

Differential effects of systemically administered nor-binaltorphimine (nor-BNI) on κ-opioid agonists in the mouse writhing assay

The opioid antagonist effects of systemically administered nor-binaltorphimine (nor-BNI) were evaluated against the kappa agonists CI-977, U69,593, U50,488, ethylketocyclazocine (EKC), Mr2034 and bremazocine, the mu agonist morphine and the alkaloid delta agonist BW-373U86 in the acetic acid-induced writhing assay in mice. All eight agonists completely and dose-dependently inhibited writhing. Antagonism of CI-977 was apparent 1 h after administration of 32 mg/kg nor-BNI, peaking after 4 h and was maintained for at least 4 weeks; no antagonist effects of nor-BNI were apparent after 8 weeks. Nor-BNI (32 mg/kg) caused little or no antagonism of morphine or BW-373U86 at 1 h and none at 24 h after nor-BNI administration. Subsequently, dose-effect curves for CI-977, U50,488, U69,593, EKC, Mr2034 and bremazocine were determined 24 h after pretreatment with 3.2, 10 and 32 mg/kg nor-BNI. Pretreatment with 3.2 mg/kg nor-BNI produced significant antagonism of all six kappa agonists, suggesting that their antinociceptive effects were mediated at least in part by nor-BNI-sensitive kappa receptors. At higher doses, nor-BNI dose-depend-ently shifted the agonist dose-effect curves of CI-977, U50,488, U69,593 and bremazocine, but not those of EKC and Mr2034, suggesting that the latter compounds may be producing effects via nor-BNI-insensitive receptors. Mu receptor involvement was demonstrated following a 24 h pretreatment with 32 mg/kg β -FNA in combination with nor-BNI, which significantly increased the degree of antagonism of Mr2034 and EKC from that seen with nor-BNI alone. Hence, SC administered nor-BNI selectively antagonized agonist activity mediated through kappaopioid receptors without differentiating between kappa subtypes. Nor-BNI also enabled the mu agonist activity of proposed kappa agonists to be measured.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46343/1/213_2005_Article_BF02245071.pd

The human capital transition and the role of policy

Along with information and communication technology, infrastructure, and the innovation system, human capital is a key pillar of the knowledge economy with its scope for increasing returns. With this in mind, the purpose of this chapter is to investigate how industrialized economies managed to achieve the transition from low to high levels of human capital. The first phase of the human capital transition was the result of the interaction of supply and demand, triggered by technological change and boosted by the demands for (immaterial) services. The second phase of the human capital transition (i.e., mass education) resulted from enforced legislation and major public investment. The state’s aim to influence children’s beliefs appears to have been a key driver in public investment. Nevertheless, the roles governments played differed according to the developmental status and inherent socioeconomic and political characteristics of their countries. These features of the human capital transition highlight the importance of understanding governments’ incentives and roles in transitions