52 research outputs found
ANALYSIS OF FUNCTIONS FOR THE EXTRAPOLATION OF RHEOLOGICAL PHENOMENA OF PRESTRESSING STEEL
BACKGROUND: The spread of artemisinin-resistance in Plasmodium falciparum is a threat to current global malaria control initiatives. Targeted malaria treatment (TMT), which combines mass anti-malarial administration with conventional malaria prevention and control measures, has been proposed as a strategy to tackle this problem. The effectiveness of TMT depends on high levels of population coverage and is influenced by accompanying community engagement activities and the local social context. The article explores how these factors influenced attitudes and behaviours towards TMT in Kayin (Karen) State, Myanmar. METHODS: Semi-structured interviews were conducted with villagers from study villages (NΒ =Β 31) and TMT project staff (NΒ =Β 14) between March and July 2015. RESULTS: Community engagement consisted of a range of activities to communicate the local malaria situation (including anti-malarial drug resistance and asymptomatic malaria), the aims of the TMT project, and its potential benefits. Community engagement was seen by staff as integral to the TMT project as a whole and not a sub-set of activities. Attitudes towards TMT (including towards community engagement) showed that developing trusting relationships helped foster participation. After initial wariness, staff received hospitality and acceptance among villagers. Offering healthcare alongside TMT proved mutually beneficial for the study and villagers. A handful of more socially-mobile and wealthy community members were reluctant to participate. The challenges of community engagement included time constraints and the isolation of the community with its limited infrastructure and a history of conflict. CONCLUSIONS: Community engagement had to be responsive to the local community even though staff faced time constraints. Understanding the social context of engagement helped TMT to foster respectful and trusting relationships. The complex relationship between the local context and community engagement complicated evaluation of the community strategy. Nonetheless, the project did record high levels of population coverage.</p
IFNΞ² Protects Neurons from Damage in a Murine Model of HIV-1 Associated Brain Injury.
Infection with human immunodeficiency virus-1 (HIV-1) causes brain injury. Type I interferons (IFNΞ±/Ξ²) are critical mediators of any anti-viral immune response and IFNΞ² has been implicated in the temporary control of lentiviral infection in the brain. Here we show that transgenic mice expressing HIV-1 envelope glycoprotein 120 in their central nervous system (HIVgp120tg) mount a transient IFNΞ² response and provide evidence that IFNΞ² confers neuronal protection against HIVgp120 toxicity. In cerebrocortical cell cultures, neuroprotection by IFNΞ² against gp120 toxicity is dependent on IFNΞ± receptor 1 (IFNAR1) and the Ξ²-chemokine CCL4, as IFNAR1 deficiency and neutralizing antibodies against CCL4, respectively, abolish the neuroprotective effects. We find in vivo that IFNΞ² mRNA is significantly increased in HIVgp120tg brains at 1.5, but not 3 or 6 months of age. However, a four-week intranasal IFNΞ² treatment of HIVgp120tg mice starting at 3.5 months of age increases expression of CCL4 and concomitantly protects neuronal dendrites and pre-synaptic terminals in cortex and hippocampus from gp120-induced damage. Moreover, in vivo and in vitro data suggests astrocytes are a major source of IFNΞ²-induced CCL4. Altogether, our results suggest exogenous IFNΞ² as a neuroprotective factor that has potential to ameliorate in vivo HIVgp120-induced brain injury
The siRNA targeted to mdr1b and mdr1a mRNAs in vivo sensitizes murine lymphosarcoma to chemotherapy
Risks for HIV and other sexually transmitted infections among Asian men who have sex with men in Vancouver, British Columbia: a cross-sectional survey
Computational Identification of Transcriptional Regulators in Human Endotoxemia
One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically βcoregulatedβ genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes
Building resilience against COVID-19 pandemic using artificial intelligence, machine learning, and IoT: a survey of recent progress
Coronavirus disease 2019 (COVID-19) has significantly impacted the entire world today and stalled off regular human activities in such an unprecedented way that it will have an unforgettable footprint on the history of mankind. Different countries have adopted numerous measures to build resilience against this life-threatening disease. However, the highly contagious nature of this pandemic has challenged the traditional healthcare and treatment practices. Thus, artificial intelligence (AI) and machine learning (ML) open up new mechanisms for effective healthcare during this pandemic. AI and ML can be useful for medicine development, designing efficient diagnosis strategies and producing predictions of the disease spread. These applications are highly dependent on real-time monitoring of the patients and effective coordination of the information, where the Internet of Things (IoT) plays a key role. IoT can also help with applications such as automated drug delivery, responding to patient queries, and tracking the causes of disease spread. This paper represents a comprehensive analysis of the potential AI, ML, and IoT technologies for defending against the COVID-19 pandemic. The existing and potential applications of AI, ML, and IoT, along with a detailed analysis of the enabling tools and techniques are outlined. A critical discussion on the risks and limitations of the aforementioned technologies are also included
Marginal dietary protein restriction reduced nonprotein nitrogen, but not protein nitrogen, components of human milk.
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