Are we really Bayesian? Probabilistic inference shows sub-optimal knowledge transfer.

Numerous studies have found that the Bayesian framework, which formulates the optimal integration of the knowledge of the world (i.e. prior) and current sensory evidence (i.e. likelihood), captures human behaviours sufficiently well. However, there are debates regarding whether humans use precise but cognitively demanding Bayesian computations for behaviours. Across two studies, we trained participants to estimate hidden locations of a target drawn from priors with different levels of uncertainty. In each trial, scattered dots provided noisy likelihood information about the target location. Participants showed that they learned the priors and combined prior and likelihood information to infer target locations in a Bayes fashion. We then introduced a transfer condition presenting a trained prior and a likelihood that has never been put together during training. How well participants integrate this novel likelihood with their learned prior is an indicator of whether participants perform Bayesian computations. In one study, participants experienced the newly introduced likelihood, which was paired with a different prior, during training. Participants changed likelihood weighting following expected directions although the degrees of change were significantly lower than Bayes-optimal predictions. In another group, the novel likelihoods were never used during training. We found people integrated a new likelihood within (interpolation) better than the one outside (extrapolation) the range of their previous learning experience and they were quantitatively Bayes-suboptimal in both. We replicated the findings of both studies in a validation dataset. Our results showed that Bayesian behaviours may not always be achieved by a full Bayesian computation. Future studies can apply our approach to different tasks to enhance the understanding of decision-making mechanisms.

An efficient hybrid deep learning architecture for predicting short antimicrobial peptides.

Short-length antimicrobial peptides (AMPs) have been demonstrated to have intensified antimicrobial activities against a wide spectrum of microbes. Therefore, exploration of novel and promising short AMPs is highly essential in developing various types of antimicrobial drugs or treatments. In addition to experimental approaches, computational methods have been developed to improve screening efficiency. Although existing computational methods have achieved satisfactory performance, there is still much room for model improvement. In this study, we proposed iAMP-DL, an efficient hybrid deep learning architecture, for predicting short AMPs. The model was constructed using two well-known deep learning architectures: the long short-term memory architecture and convolutional neural networks. To fairly assess the performance of the model, we compared our model with existing state-of-the-art methods using the same independent test set. Our comparative analysis shows that iAMP-DL outperformed other methods. Furthermore, to assess the robustness and stability of our model, the experiments were repeated 10 times to observe the variation in prediction efficiency. The results demonstrate that iAMP-DL is an effective, robust, and stable framework for detecting promising short AMPs. Another comparative study of different negative data sampling methods also confirms the effectiveness of our method and demonstrates that it can also be used to develop a robust model for predicting AMPs in general. The proposed framework was also deployed as an online web server with a user-friendly interface to support the research community in identifying short AMPs.

Peripuberty is a sensitive period for prefrontal parvalbumin interneuron activity to impact adult cognitive flexibility.

INTRODUCTION: Developmental windows in which experiences can elicit long-lasting effects on brain circuitry and behavior are called 'sensitive periods' and reflect a state of heightened plasticity. The classic example of a sensitive period comes from studies of sensory systems, like the visual system, where early visual experience is required for normal wiring of primary visual cortex and proper visual functioning. At a mechanistic level, loss of incoming visual input results in a decrease in activity in thalamocortical neurons representing the affected eye, resulting in an activity-dependent reduction in the representation of those inputs in the visual cortex and loss of visual perception in that eye. While associative cortical regions like the medial prefrontal cortex (mPFC) do not receive direct sensory input, recent findings demonstrate that changes in activity levels experienced by this region during defined windows in early development may also result in long-lasting changes in prefrontal cortical circuitry, network function and behavior. For example, we recently demonstrated that decreasing the activity of mPFC parvalbumin-expressing (PV) interneurons during a period of time encompassing peripuberty (postnatal day P14) to adolescence (P50) led to a long-lasting decrease in their functional inhibition of pyramidal cells, as well as impairments in cognitive flexibility. While the effects of manipulating mPFC PV interneuron activity were selective to development, and not adulthood, the exact timing of the sensitive period for this manipulation remains unknown. METHODS: To refine the sensitive period in which inhibiting mPFC PV cell activity can lead to persist effects on prefrontal functioning we used a chemogenetic approach to restrict our inhibition of mPFC PV activity to two distinct windows: 1) peripuberty (P14-P32) and 2) early adolescence (P33-P50). We then investigated adult behavior after P90. In parallel, we performed histological analysis of molecular markers associated with sensitive period onset and offset in visual cortex, to define the onset and offset of peak sensitive period plasticity in the mPFC. RESULTS: We found that inhibition of mPFC PV interneurons in peripuberty (P14-P32), but not adolescence (P33-P50), led to an impairment in set shifting behavior in adulthood manifest as an increase in trials to reach criterion performance and errors. Consistent with a pubertal onset of sensitive period plasticity in the PFC, we found histological markers of sensitive period onset and offset also demarcated P14 and P35, respectively. The time course of expression of these markers was similar in visual cortex. CONCLUSION: Both lines of research converge on the peripubertal period (P14-32) as one of heightened sensitive period plasticity in the mPFC. Further, our direct comparison of markers of sensitive period plasticity across the prefrontal and visual cortex suggests a similar time course of expression, challenging the notion that sensitive periods occur hierarchically. Together, these findings extend our knowledge about the nature and timing of sensitive period plasticity in the developing mPFC.

Zika virus co-opts microRNA networks to persist in placental niches detected by spatial transcriptomics.

BACKGROUND: Zika virus congenital infection evades double-stranded RNA detection and may persist in the placenta for the duration of pregnancy without accompanying overt histopathologic inflammation. Understanding how viruses can persist and replicate in the placenta without causing overt cellular or tissue damage is fundamental to deciphering mechanisms of maternal-fetal vertical transmission. OBJECTIVE: Placenta-specific microRNAs are believed to be a tenet of viral resistance at the maternal-fetal interface. We aimed to test the hypothesis that the Zika virus functionally disrupts placental microRNAs, enabling viral persistence and fetal pathogenesis. STUDY DESIGN: To test this hypothesis, we used orthogonal approaches in human and murine experimental models. In primary human trophoblast cultures (n=5 donor placentae), we performed Argonaute high-throughput sequencing ultraviolet-crosslinking and immunoprecipitation to identify any significant alterations in the functional loading of microRNAs and their targets onto the RNA-induced silencing complex. Trophoblasts from same-donors were split and infected with a contemporary first-passage Zika virus strain HN16 (multiplicity of infection=1 plaque forming unit per cell) or mock infected. To functionally cross-validate microRNA-messenger RNA interactions, we compared our Argonaute high-throughput sequencing ultraviolet-crosslinking and immunoprecipitation results with an independent analysis of published bulk RNA-sequencing data from human placental disk specimens (n=3 subjects; Zika virus positive in first, second, or third trimester, CD45- cells sorted by flow cytometry) and compared it with uninfected controls (n=2 subjects). To investigate the importance of these microRNA and RNA interference networks in Zika virus pathogenesis, we used a gnotobiotic mouse model uniquely susceptible to the Zika virus. We evaluated if small-molecule enhancement of microRNA and RNA interference pathways with enoxacin influenced Zika virus pathogenesis (n=20 dams total yielding 187 fetal specimens). Lastly, placentae (n=14 total) from this mouse model were analyzed with Visium spatial transcriptomics (9743 spatial transcriptomes) to identify potential Zika virus-associated alterations in immune microenvironments. RESULTS: We found that Zika virus infection of primary human trophoblast cells led to an unexpected disruption of placental microRNA regulation networks. When compared with uninfected controls, Zika virus-infected placentae had significantly altered SLC12A8, SDK1, and VLDLR RNA-induced silencing complex loading and transcript levels (-22; adjusted P value <.05; Wald-test with false discovery rate correction q<0.05). In silico microRNA target analyses revealed that 26 of 119 transcripts (22%) in the transforming growth factor-ß signaling pathway were targeted by microRNAs that were found to be dysregulated following Zika virus infection in trophoblasts. In gnotobiotic mice, relative to mock controls, Zika virus-associated fetal pathogenesis included fetal growth restriction (P=.036) and viral persistence in placental tissue (P=.011). Moreover, spatial transcriptomics of murine placentae revealed that Zika virus-specific placental niches were defined by significant up-regulation of complement cascade components and coordinated changes in transforming growth factor-ß gene expression. Finally, treatment of Zika virus-infected mice with enoxacin abolished placental Zika virus persistence, rescued the associated fetal growth restriction, and the Zika virus-associated transcriptional changes in placental immune microenvironments were no longer observed. CONCLUSION: These results collectively suggest that (1) Zika virus infection and persistence is associated with functionally perturbed microRNA and RNA interference pathways specifically related to immune regulation in placental microenvironments and (2) enhancement of placental microRNA and RNA interference pathways in mice rescued Zika virus-associated pathogenesis, specifically persistence of viral transcripts in placental microenvironments and fetal growth restriction.

iNSP-GCAAP: Identifying nonclassical secreted proteins using global composition of amino acid properties.

Nonclassical secreted proteins (NSPs) refer to a group of proteins released into the extracellular environment under the facilitation of different biological transporting pathways apart from the Sec/Tat system. As experimental determination of NSPs is often costly and requires skilled handling techniques, computational approaches are necessary. In this study, we introduce iNSP-GCAAP, a computational prediction framework, to identify NSPs. We propose using global composition of a customized set of amino acid properties to encode sequence data and use the random forest (RF) algorithm for classification. We used the training dataset introduced by Zhang et al. (Bioinformatics, 36(3), 704-712, 2020) to develop our model and test it with the independent test set in the same study. The area under the receiver operating characteristic curve on that test set was 0.9256, which outperformed other state-of-the-art methods using the same datasets. Our framework is also deployed as a user-friendly web-based application to support the research community to predict NSPs.

Drivers of Chronic Pathology Following Ischemic Stroke: A Descriptive Review.

Stroke is the third leading cause of death and long-term disability in the world. Considered largely a disease of aging, its global economic and healthcare burden is expected to rise as more people survive into advanced age. With recent advances in acute stroke management, including the expansion of time windows for treatment with intravenous thrombolysis and mechanical thrombectomy, we are likely to see an increase in survival rates. It is therefore critically important to understand the complete pathophysiology of ischemic stroke, both in the acute and subacute stages and during the chronic phase in the months and years following an ischemic event. One of the most clinically relevant aspects of the chronic sequelae of stroke is its extended negative effect on cognition. Cognitive impairment may be related to the deterioration and dysfunctional reorganization of white matter seen at later timepoints after stroke, as well as ongoing progressive neurodegeneration. The vasculature of the brain also undergoes significant insult and remodeling following stroke, undergoing changes which may further contribute to chronic stroke pathology. While inflammation and the immune response are well established drivers of acute stroke pathology, the chronicity and functional role of innate and adaptive immune responses in the post-ischemic brain and in the peripheral environment remain largely uncharacterized. In this review, we summarize the current literature on post-stroke injury progression, its chronic pathological features, and the putative secondary injury mechanisms underlying the development of cognitive impairment and dementia. We present findings from clinical and experimental studies and discuss the long-term effects of ischemic stroke on both brain anatomy and functional outcome. Identifying mechanisms that occur months to years after injury could lead to treatment strategies in the chronic phase of stroke to help mitigate stroke-associated cognitive decline in patients.

Detection and assessment of risk factors associated with Newcastle disease virus infection in birds in backyard poultry in Laichau province of Vietnam.

Newcastle disease (ND) is a highly pathogenic and contagious viral infectious disease of poultry that causes a very serious problem for poultry production and economic loss worldwide. ND has been an epizootic disease in Vietnam. Information about the risk factors that are associated with virus transmission in backyard chickens in Vietnam is limited. To provide more epidemiological information about ND in Vietnam, this study was performed to estimate NDV prevalence and identify the risk factors for ND virus (NDV) infection in birds at the backyard flock level. Choanal swabs were taken from 400 randomly selected birds from 100 apparently healthy flocks from May to July 2020. Based on RT-PCR analysis, 43 of 400 swab samples (10.75%; 95% CI 8-14.17) and 21 of 100 flocks (21%; 95% CI 14.17-29.98) were positive for the fusion (F) gene of NDV. The management practice risks were: backyard flocks contacting wild birds (OR = 3.89; P = 0.030), mixed flocks with different types and species of birds (OR = 5.46; P = 0.004), and infrequency of cleaning and disinfecting poultry houses (OR (odds ratio) = 4.43; P = 0.034). The second and third risks (above) showed a positive interaction on the risk of NDV infection in birds (OR = 39.38; P = 0.001), and the first risk showed a negative interaction. Further studies on NDV surveillance in domestic waterfowl, longitudinal studies, a well-optimized RT-qPCR assay, and genetic characterization are needed. The development of handbooks, flyers, or lessons for educating poultry keepers are also needed.RESEARCH HIGHLIGHT RT-PCR was used to detect the F gene of NDV in choanal swabs.Risk factors associated with NDV-positive samples were determined.The evidence for NDV circulation in backyard healthy birds was observed.Contact with wild birds, mixed flocks, and poor hygiene were major risk factors.

Predicting Antimalarial Activity in Natural Products Using Pretrained Bidirectional Encoder Representations from Transformers.

Malaria is a threatening disease that has claimed many lives and has a high prevalence rate annually. Through the past decade, there have been many studies to uncover effective antimalarial compounds to combat this disease. Alongside chemically synthesized chemicals, a number of natural compounds have also been proven to be as effective in their antimalarial properties. Besides experimental approaches to investigate antimalarial activities in natural products, computational methods have been developed with satisfactory outcomes obtained. In this study, we propose a novel molecular encoding scheme based on Bidirectional Encoder Representations from Transformers and used our pretrained encoding model called NPBERT with four machine learning algorithms, including k-Nearest Neighbors (k-NN), Support Vector Machines (SVM), eXtreme Gradient Boosting (XGB), and Random Forest (RF), to develop various prediction models to identify antimalarial natural products. The results show that SVM models are the best-performing classifiers, followed by the XGB, k-NN, and RF models. Additionally, comparative analysis between our proposed molecular encoding scheme and existing state-of-the-art methods indicates that NPBERT is more effective compared to the others. Moreover, the deployment of transformers in constructing molecular encoders is not limited to this study but can be utilized for other biomedical applications.

Testing early warning and response systems through a full-scale exercise in Vietnam.

BACKGROUND: Simulation exercises can functionally validate World Health Organization (WHO) International Health Regulations (IHR 2005) core capacities. In 2018, the Vietnam Ministry of Health (MOH) conducted a full-scale exercise (FSX) in response to cases of severe viral pneumonia with subsequent laboratory confirmation for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) to evaluate the country's early warning and response capabilities for high-risk events. METHODS: An exercise planning team designed a complex fictitious scenario beginning with one case of severe viral pneumonia presenting at the hospital level and developed all the materials required for the exercise. Actors, controllers and evaluators were trained. In August 2018, a 3-day exercise was conducted in Quang Ninh province and Hanoi city, with participation of public health partners at the community, district, province, regional and national levels. Immediate debriefings and an after-action review were conducted after all exercise activities. Participants assessed overall exercise design, conduction and usefulness. RESULTS: FSX findings demonstrated that the event-based surveillance component of the MOH surveillance system worked optimally at different administrative levels. Detection and reporting of signals at the community and health facility levels were appropriate. Triage, verification and risk assessment were successfully implemented to identify a high-risk event and trigger timely response. The FSX identified infection control, coordination with internal and external response partners and process documentation as response challenges. Participants positively evaluated the exercise training and design. CONCLUSIONS: This exercise documents the value of exercising surveillance capabilities as part of a real-time operational scenario before facing a true emergency. The timing of this exercise and choice of disease scenario was particularly fortuitous given the subsequent appearance of COVID-19. As a result of this exercise and subsequent improvements made by the MOH, the country may have been better able to deal with the emergence of SARS-CoV-2 and contain it.

Symmetry-breaking transitions in the early steps of protein self-assembly.

Protein misfolding and subsequent self-association are complex, intertwined processes, resulting in development of a heterogeneous population of aggregates closely related to many chronic pathological conditions including Type 2 Diabetes Mellitus and Alzheimer's disease. To address this issue, here, we develop a theoretical model in the general framework of linear stability analysis. According to this model, self-assemblies of peptides with pronounced conformational flexibility may become, under particular conditions, unstable and spontaneously evolve toward an alternating array of partially ordered and disordered monomers. The predictions of the theory were verified by atomistic molecular dynamics (MD) simulations of islet amyloid polypeptide (IAPP) used as a paradigm of aggregation-prone polypeptides (proteins). Simulations of dimeric, tetrameric, and hexameric human-IAPP self-assemblies at physiological electrolyte concentration reveal an alternating distribution of the smallest domains (of the order of the peptide mean length) formed by partially ordered (mainly ß-strands) and disordered (turns and coil) arrays. Periodicity disappears upon weakening of the inter-peptide binding, a result in line with the predictions of the theory. To further probe the general validity of our hypothesis, we extended the simulations to other peptides, the Aß(1-40) amyloid peptide, and the ovine prion peptide as well as to other proteins (SOD1 dimer) that do not belong to the broad class of intrinsically disordered proteins. In all cases, the oligomeric aggregates show an alternate distribution of partially ordered and disordered monomers. We also carried out Surface Enhanced Raman Scattering (SERS) measurements of hIAPP as an experimental validation of both the theory and in silico simulations.

Lived experience research as a resource for recovery: a mixed methods study.

BACKGROUND: Lived experience research is conducted by people who have experience of mental health issues and is therefore better placed than more traditional research to illuminate participants' experiences. Findings that focus on identifying enablers of recovery from a lived experience perspective have the potential to assist people in their recovery process. However, this lived experience research is often difficult to find, access and interpret. We co-produced user-friendly and engaging resources to disseminate findings from six lived experience research studies. This paper seeks to answer the research questions: a) Did exposure to lived experience research increase hopefulness for participants?; and b) How else did interacting with lived experience research resources influence participants' lives? METHODS: Thirty-eight participants were introduced to four resources of their choosing by peer workers over a four-week period. The helpfulness of resources was evaluated using mixed methods, including a quasi-experimental analysis of change in hope, an anonymous survey and in-depth interviews. RESULTS: Findings indicated that the resources promoted hope, but that increases in hopefulness may not be seen immediately. Other impacts include that the resources: encouraged helpful activities; provided a positive experience; increased valued knowledge; encouraged people to reflect on their journey and think constructively about mental health issues; helped people to feel less alone; and assisted people to explain their situation to others. CONCLUSIONS: The research suggests the potential usefulness of lived experience research resources, presented in user-friendly formats, in the lives of people who experience mental health issues and implies a need to nurture this type of research.

Developing monitoring and evaluation tools for event-based surveillance: experience from Vietnam.

BACKGROUND: In 2016-2017, Vietnam's Ministry of Health (MoH) implemented an event-based surveillance (EBS) pilot project in six provinces as part of Global Health Security Agenda (GHSA) efforts. This manuscript describes development and design of tools for monitoring and evaluation (M&E) of EBS in Vietnam. METHODS: A strategic EBS framework was developed based on the EBS implementation pilot project's goals and objectives. The main process and outcome components were identified and included input, activities, outputs, and outcome indicators. M&E tools were developed to collect quantitative and qualitative data. The tools included a supervisory checklist, a desk review tool, a key informant interview guide, a focus group discussion guide, a timeliness form, and an online acceptability survey. An evaluation team conducted field visits for assessment of EBS 5-9 months after implementation. RESULTS: The quantitative data collected provided evidence on the number and type of events that were being reported, the timeliness of the system, and the event-to-signal ratio. The qualitative and subjective data collected helped to increase understanding of the system's field utility and acceptance by field staff, reasons for non-compliance with established guidelines, and other factors influencing implementation. CONCLUSIONS: The use of M&E tools for the EBS pilot project in Vietnam provided data on signals and events reported, timeliness of reporting and response, perceptions and opinions of implementers, and fidelity of EBS implementation. These data were valuable for Vietnam's MoH to understand the function of the EBS program, and the success and challenges of implementing this project in Vietnam.

iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks.

BACKGROUND: Enhancers are non-coding DNA fragments which are crucial in gene regulation (e.g. transcription and translation). Having high locational variation and free scattering in 98% of non-encoding genomes, enhancer identification is, therefore, more complicated than other genetic factors. To address this biological issue, several in silico studies have been done to identify and classify enhancer sequences among a myriad of DNA sequences using computational advances. Although recent studies have come up with improved performance, shortfalls in these learning models still remain. To overcome limitations of existing learning models, we introduce iEnhancer-ECNN, an efficient prediction framework using one-hot encoding and k-mers for data transformation and ensembles of convolutional neural networks for model construction, to identify enhancers and classify their strength. The benchmark dataset from Liu et al.'s study was used to develop and evaluate the ensemble models. A comparative analysis between iEnhancer-ECNN and existing state-of-the-art methods was done to fairly assess the model performance. RESULTS: Our experimental results demonstrates that iEnhancer-ECNN has better performance compared to other state-of-the-art methods using the same dataset. The accuracy of the ensemble model for enhancer identification (layer 1) and enhancer classification (layer 2) are 0.769 and 0.678, respectively. Compared to other related studies, improvements in the Area Under the Receiver Operating Characteristic Curve (AUC), sensitivity, and Matthews's correlation coefficient (MCC) of our models are remarkable, especially for the model of layer 2 with about 11.0%, 46.5%, and 65.0%, respectively. CONCLUSIONS: iEnhancer-ECNN outperforms other previously proposed methods with significant improvement in most of the evaluation metrics. Strong growths in the MCC of both layers are highly meaningful in assuring the stability of our models.

iPseU-NCP: Identifying RNA pseudouridine sites using random forest and NCP-encoded features.

BACKGROUND: Pseudouridine modification is most commonly found among various kinds of RNA modification occurred in both prokaryotes and eukaryotes. This biochemical event has been proved to occur in multiple types of RNAs, including rRNA, mRNA, tRNA, and nuclear/nucleolar RNA. Hence, gaining a holistic understanding of pseudouridine modification can contribute to the development of drug discovery and gene therapies. Although some laboratory techniques have come up with moderately good outcomes in pseudouridine identification, they are costly and required skilled work experience. We propose iPseU-NCP - an efficient computational framework to predict pseudouridine sites using the Random Forest (RF) algorithm combined with nucleotide chemical properties (NCP) generated from RNA sequences. The benchmark dataset collected from Chen et al. (2016) was used to develop iPseU-NCP and fairly compare its performances with other methods. RESULTS: Under the same experimental settings, comparing with three state-of-the-art methods including iPseU-CNN, PseUI, and iRNA-PseU, the Matthew's correlation coefficient (MCC) of our model increased by about 20.0%, 55.0%, and 109.0% when tested on the H. sapiens (H_200) dataset and by about 6.5%, 35.0%, and 150.0% when tested on the S. cerevisiae (S_200) dataset, respectively. This significant growth in MCC is very important since it ensures the stability and performance of our model. With those two independent test datasets, our model also presented higher accuracy with a success rate boosted by 7.0%, 13.0%, and 20.0% and 2.0%, 9.5%, and 25.0% when compared to iPseU-CNN, PseUI, and iRNA-PseU, respectively. For majority of other evaluation metrics, iPseU-NCP demonstrated superior performance as well. CONCLUSIONS: iPseU-NCP combining the RF and NPC-encoded features showed better performances than other existing state-of-the-art methods in the identification of pseudouridine sites. This also shows an optimistic view in addressing biological issues related to human diseases.

Event-Based Surveillance at Community and Healthcare Facilities, Vietnam, 2016-2017.

Surveillance and outbreak reporting systems in Vietnam required improvements to function effectively as early warning and response systems. Accordingly, the Ministry of Health of Vietnam, in collaboration with the US Centers for Disease Control and Prevention, launched a pilot project in 2016 focusing on community and hospital event-based surveillance. The pilot was implemented in 4 of Vietnam's 63 provinces. The pilot demonstrated that event-based surveillance resulted in early detection and reporting of outbreaks, improved collaboration between the healthcare facilities and preventive sectors of the ministry, and increased community participation in surveillance and reporting.

Sustainable Model for Public Health Emergency Operations Centers for Global Settings.

Capacity to receive, verify, analyze, assess, and investigate public health events is essential for epidemic intelligence. Public health Emergency Operations Centers (PHEOCs) can be epidemic intelligence hubs by 1) having the capacity to receive, analyze, and visualize multiple data streams, including surveillance and 2) maintaining a trained workforce that can analyze and interpret data from real-time emerging events. Such PHEOCs could be physically located within a ministry of health epidemiology, surveillance, or equivalent department rather than exist as a stand-alone space and serve as operational hubs during nonoutbreak times but in emergencies can scale up according to the traditional Incident Command System structure.

Design of Hydrated Porphyrin-Phospholipid Bilayers with Enhanced Magnetic Resonance Contrast.

Computer simulations are used to design more hydrated bilayers, formed from amine-modified porphyrin-phospholipids (PoPs). Experiments confirm that the new constructs give rise to bilayers with greater water content. When chelated with manganese, amine-modified PoPs provide improved contrast for magnetic resonance and are safely used for imaging in vivo.

Strengthening global health security capacity--Vietnam demonstration project, 2013.

Over the past decade, Vietnam has successfully responded to global health security (GHS) challenges, including domestic elimination of severe acute respiratory syndrome (SARS) and rapid public health responses to human infections with influenza A(H5N1) virus. However, new threats such as Middle East respiratory syndrome coronavirus (MERS-CoV) and influenza A(H7N9) present continued challenges, reinforcing the need to improve the global capacity to prevent, detect, and respond to public health threats. In June 2012, Vietnam, along with many other nations, obtained a 2-year extension for meeting core surveillance and response requirements of the 2005 International Health Regulations (IHR). During March-September 2013, CDC and the Vietnamese Ministry of Health (MoH) collaborated on a GHS demonstration project to improve public health emergency detection and response capacity. The project aimed to demonstrate, in a short period, that enhancements to Vietnam's health system in surveillance and early detection of and response to diseases and outbreaks could contribute to meeting the IHR core capacities, consistent with the Asia Pacific Strategy for Emerging Diseases. Work focused on enhancements to three interrelated priority areas and included achievements in 1) establishing an emergency operations center (EOC) at the General Department of Preventive Medicine with training of personnel for public health emergency management; 2) improving the nationwide laboratory system, including enhanced testing capability for several priority pathogens (i.e., those in Vietnam most likely to contribute to public health emergencies of international concern); and 3) creating an emergency response information systems platform, including a demonstration of real-time reporting capability. Lessons learned included awareness that integrated functions within the health system for GHS require careful planning, stakeholder buy-in, and intradepartmental and interdepartmental coordination and communication.

Determinants of condom use at sexual debut among young Vietnamese.

BACKGROUND AND AIMS: Condom use at sexual debut is associated with subsequent condom use and with decreased risk of sexually transmitted infections. There is a dearth of data on determinants of condom use at first sexual intercourse. We aimed to determine factors associated with condom use at first sexual intercourse before marriage among Vietnamese adolescents and youths. METHODS: The study involved the analysis of data from the Survey Assessment of Vietnamese Youth, 2003, the first nationally representative survey of young people in Vietnam. The survey included 7584 adolescents and youths aged 14-25 years. In this study, data of 605 adolescents and youths who had engaged in premarital sex were analyzed for factors associated with condom use using descriptive analyses, and regression techniques, allowing for sampling weights, clustering and stratification. RESULTS: Of 605 adolescents and youths who had engaged in premarital sex, 28.6% reported condom use at first sexual intercourse. Condom use at sexual debut was less common in females than males [odds ratio (OR)=0.15; 95% confidence interval (95% CI)=0.07-0.30] and less common in those who experienced peer pressure to engage in social higher risk behaviors (OR=0.57; 95% CI=0.32-0.99). Condom use was more common if a friend/acquaintance or a stranger/sex worker was the first sexual partner (OR=2.20; 95% CI=1.16-4.17 and OR=17.90; 95% CI=6.88-46.54) respectively, each compared with fiancé/boyfriend/girlfriend as first sexual partner. CONCLUSIONS: These data suggest that approximately one in three unmarried Vietnamese youths used a condom at first sexual intercourse. Gender, peer pressure and the nature of the relationship to the first sexual partner were independently associated with condom use. These results can inform programs directed at preventing HIV and other sexually transmitted infections among young Vietnamese.

Reconfiguring Breast Reconstruction in the Post-Cancer Life in Vietnam.

In the context of breast cancer, women who refuse reconstruction are often portrayed as having limited agency or control over their bodies and treatment. Here we assess these assumptions by paying attention to how the local contexts and inter-relational dynamics influence women's decision-making about their mastectomized body in Central Vietnam. We situate the reconstructive decision within an under-funded public health system, but also show how the widespread perception of the surgery as merely an aesthetic practice dissuades women from seeking reconstruction. Women are shown both conform to existing gendered norms while simultaneously challenging and defying them.