Adverse Childhood Experiences and HIV Risk Behaviors Among Transgender Populations

Adverse childhood experiences (ACEs) have a negative impact on health and have created a social challenge in managing HIV risk behavior in the transgender population. The aim of this study was to determine the association between ACEs and HIV risk behavior among the transgender population and identify the association between ACE score (1, 2, 3, 4, or more) and HIV risk behavior among the transgender population. This involved a quantitative methodology using a Behavioral Risk Factor Surveillance System (BRFSS) questionnaire to obtain data from 323 transgender participants. Multivariable regression analyses were conducted to determine the association between ACEs and HIV risk behavior. ACEs had a statistically significant relationship with HIV risk behavior among transgender individuals (adjusted OR: 12.7; 95% CI: 1.51 – 42.2). Distribution of ACE score was statistically significant by age (p \u3c 0.001) and race/ethnicity (p = 0.01). In addition, respondents who experienced four or more ACEs were 26 times more likely to report HIV risk behavior (OR: 25.5; 95% CI: 2.82–231.8) compared to respondents who did not report any ACEs. The results imply that ACEs have a negative impact on transgender social and behavioral health and increase risk for factors that accentuate HIV susceptibility which is a major challenge in mitigating the HIV pandemic. Therefore, the findings indicate the need for an enhanced focus on the role of ACEs and toxic stress with interventions aimed towards reducing HIV risk behavior among transgender individuals. Such social changes would positively affect society, improving the approaches to dealing with ACE, toxic stress and reducing the associated health complications

Proceedings of the 13th annual conference of INEBRIA

CITATION: Watson, R., et al. 2016. Proceedings of the 13th annual conference of INEBRIA. Addiction Science & Clinical Practice, 11:13, doi:10.1186/s13722-016-0062-9.The original publication is available at https://ascpjournal.biomedcentral.comENGLISH SUMMARY : Meeting abstracts.https://ascpjournal.biomedcentral.com/articles/10.1186/s13722-016-0062-9Publisher's versio

Language Development in the Digital Age

The digital age is changing our children’s lives and childhood dramatically. New technologies transform the way people interact with each other, the way stories are shared and distributed, and the way reality is presented and perceived. Parents experience that toddlers can handle tablets and apps with a level of sophistication the children’s grandparents can only envy. The question of how the ecology of the child affects the acquisition of competencies and skills has been approached from different angles in different disciplines. In linguistics, psychology and neuroscience, the central question addressed concerns the specific role of exposure to language. Two influential types of theory have been proposed. On one view the capacity to learn language is hard-wired in the human brain: linguistic input is merely a trigger for language to develop. On an alternative view, language acquisition depends on the linguistic environment of the child, and specifically on language input provided through child-adult communication and interaction. The latter view further specifies that factors in situated interaction are crucial for language learning to take place. In the fields of information technology, artificial intelligence and robotics a current theme is to create robots that develop, as children do, and to establish how embodiment and interaction support language learning in these machines. In the field of human-machine interaction, research is investigating whether using a physical robot, rather than a virtual agent or a computer-based video, has a positive effect on language development. The Research Topic will address the following issues: - What are the methodological challenges faced by research on language acquisition in the digital age? - How should traditional theories and models of language acquisition be revised to account for the multimodal and multichannel nature of language learning in the digital age? - How should existing and future technologies be developed and transformed so as to be most beneficial for child language learning and cognition? - Can new technologies be tailored to support child growth, and most importantly, can they be designed in order to enhance specifically vulnerable children’s language learning environment and opportunities? - What kind of learning mechanisms are involved? - How can artificial intelligence and robotics technologies, as robot tutors, support language development? These questions and issues can only be addressed by means of an interdisciplinary approach that aims at developing new methods of data collection and analysis in cross-sectional and longitudinal perspectives. We welcome contributions addressing these questions from an interdisciplinary perspective both theoretically and empirically

Editorial: Language Development in the Digital Age

INTRODUCTION The digital age is changing our children’s lives and childhood dramatically. New technologies transform the way people interact with each other, the way stories are shared and distributed, and the way reality is presented and perceived. Parents experience that toddlers can handle tablets and apps with a level of sophistication the children’s grandparents can only envy. In Great Britain, a recent survey of preschoolers shows that a rising number of toddlers are now put to bed with a tablet instead of a bedtime story. In the USA, a telephone survey of 1,009 parents of children aged 2–24 months (Zimmerman et al., 2007a) documents that by 3 months of age, about 40% of children regularly watched television, DVDs or videos, while by 24 months the proportion rose to 90%. Moreover, with the advance and exponential use of social media, children see their parents constantly interacting with mobile devices, instead of with people around them. Still, research in the US indicates that assistive social robots seem to have a favorable effect on children’s language development (Westlund et al.). Existing theories of language acquisition emphasize the role of language input and the child’s interaction with the environment as crucial to language development. From this perspective, we need to ask: What are the consequences of this new digital reality for children’s acquisition of the most fundamental of all human skills: language and communication? Are new theories needed that can help us understand how children acquire language? Do the new digital environment and the new ways of interaction change the way languages are learned, or the quality of language acquisition? Is the use of new media beneficial or harmful to children’s language and cognitive development? Can new technologies be tailored to support child growth and, most importantly, can they be designed to enhance language learning in vulnerable children? These questions and issues can only be addressed by means of an interdisciplinary approach that aims at developing new methods of data collection and analysis in a longitudinal perspective. This type of research is however not yet documented

Understanding Language Development in the Digital Age

The digital age is changing our children’s lives and childhood dramatically. New technologies transform the way people interact with each other, the way stories are shared and distributed, and the way reality is presented and perceived. Parents experience that toddlers can handle tablets and apps with a level of sophistication the children’s grandparents can only envy. In Great Britain, a recent survey of preschoolers shows that a rising number of toddlers are now put to bed with a tablet instead of a bedtime story. In the USA, a telephone survey of 1,009 parents of children aged 2–24 months (Zimmerman et al., 2007a) documents that by 3 months of age, about 40% of children regularly watched television, DVDs or videos, while by 24 months the proportion rose to 90%. Moreover, with the advance and exponential use of social media, children see their parents constantly interacting with mobile devices, instead of with people around them. Still, research in the US indicates that assistive social robots seem to have a favorable effect on children’s language development (Westlund et al.). Existing theories of language acquisition emphasize the role of language input and the child’s interaction with the environment as crucial to language development. From this perspective, we need to ask: What are the consequences of this new digital reality for children’s acquisition of the most fundamental of all human skills: language and communication? Are new theories needed that can help us understand how children acquire language? Do the new digital environment and the new ways of interaction change the way languages are learned, or the quality of language acquisition? Is the use of new media beneficial or harmful to children’s language and cognitive development? Can new technologies be tailored to support child growth and, most importantly, can they be designed to enhance language learning in vulnerable children? These questions and issues can only be addressed by means of an interdisciplinary approach that aims at developing new methods of data collection and analysis in a longitudinal perspective. This type of research is however not yet documented

HTS by NMR for the Identification of Potent and Selective Inhibitors of Metalloenzymes

We have recently proposed a novel drug discovery approach based on biophysical screening of focused positional scanning libraries in which each element of the library contained a common binding moiety for the given target or class of targets. In this Letter, we report on the implementation of this approach to target metal containing proteins. In our implementation, we first derived a focused positional scanning combinatorial library of peptide mimetics (of approximately 100,000 compounds) in which each element of the library contained the metal-chelating moiety hydroxamic acid at the C-terminal. Screening of this library by nuclear magnetic resonance spectroscopy in solution allowed the identification of a novel and selective compound series targeting MMP-12. The data supported that our general approach, perhaps applied using other metal chelating agents or other initial binding fragments, may result very effective in deriving novel and selective agents against metalloenzyme

HTS by NMR for the Identification of Potent and Selective Inhibitors of Metalloenzymes

We have recently proposed a novel drug discovery approach based on biophysical screening of focused positional scanning libraries in which each element of the library contained a common binding moiety for the given target or class of targets. In this Letter, we report on the implementation of this approach to target metal containing proteins. In our implementation, we first derived a focused positional scanning combinatorial library of peptide mimetics (of approximately 100,000 compounds) in which each element of the library contained the metal-chelating moiety hydroxamic acid at the C-terminal. Screening of this library by nuclear magnetic resonance spectroscopy in solution allowed the identification of a novel and selective compound series targeting MMP-12. The data supported that our general approach, perhaps applied using other metal chelating agents or other initial binding fragments, may result very effective in deriving novel and selective agents against metalloenzyme

Changes in Frailty Status and Risk of Depression: Results From the Progetto Veneto Anziani Longitudinal Study

Objective: To evaluate whether prefrailty was associated with the risk of developing depression and if longitudinal changes in frailty status corresponded to changes in incident depression during follow up. Methods: A population-based, prospective cohort study was conducted for 4.4 years in two separate geographic areas near the city of Padua in the Veneto Region of Northern Italy. In 891 nondepressed, nonfrail, community-dwelling Italian subjects aged ≥ 65 (46.6% men) belonging to the Progetto Veneto Anziani study, depression was defined according to the Geriatric Depression Scale and was confirmed by geriatricians skilled in psychogeriatric medicine. Prefrailty was defined by the presence of one or two criteria among the Fried criteria. Results: The incidence rate of depression was 13.3% among subjects improving their frailty status at follow-up (N = 15), 15.0% in those who remained stable (N = 79), and 26.7% among worsening participants (N = 67) (p = 0.001). Prefrailty at baseline did not predict the onset of depression (HR: 0.82; 95% CI: 0.55–1.21; Wald χ2 = 0.73; df = 1; p = 0.43), but a deterioration during follow-up in at least one additional frailty criteria was associated with a significantly higher risk (HR: 1.95; 95% CI: 1.32–2.89; Wald χ2 = 5.78; df = 2; p = 0.01). Improvement in frailty status was not associated with the risk of incident depression (HR: 0.71; 95% CI: 0.35–1.42; Wald χ2 = 0.47; df = 2; p = 0.28). Conclusion: Our data did not offer evidence that prefrailty per se predisposes to the onset of depression, but worsening in frailty status is associated with an almost twofold increased risk of incident depression, irrespective from the initial level of impairment