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.

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.

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.

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.

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.

Measuring the impact of an integrated bite case management program on the detection of canine rabies cases in Vietnam.

Introduction: Dog-mediated rabies is enzootic in Vietnam, resulting in at least 70 reported human deaths and 500,000 human rabies exposures annually. In 2016, an integrated bite cases management (IBCM) based surveillance program was developed to improve knowledge of the dog-mediated rabies burden in Phu Tho Province of Vietnam. Methods: The Vietnam Animal Rabies Surveillance Program (VARSP) was established in four stages: (1) Laboratory development, (2) Training of community One Health workers, (3) Paper-based-reporting (VARSP 1.0), and (4) Electronic case reporting (VARSP 2.0). Investigation and diagnostic data collected from March 2016 to December 2019 were compared with historical records of animal rabies cases dating back to January 2012. A risk analysis was conducted to evaluate the probability of a rabies exposure resulting in death after a dog bite, based on data collected over the course of an IBCM investigation. Results: Prior to the implementation of VARSP, between 2012 and 2015, there was an average of one rabies investigation per year, resulting in two confirmed and two probable animal rabies cases. During the 46 months that VARSP was operational (2016 - 2019), 1048 animal investigations were conducted, which identified 79 (8%) laboratory-confirmed rabies cases and 233 (22%) clinically-confirmed(probable) cases. VARSP produced a 78-fold increase in annual animal rabies case detection (one cases detected per year pre-VARSP vs 78 cases per year under VARSP). The risk of succumbing to rabies for bite victims of apparently healthy dogs available for home quarantine, was three deaths for every 10,000 untreated exposures. Discussion: A pilot IBCM model used in Phu Tho Province showed promising results for improving rabies surveillance, with a 26-fold increase in annual case detection after implementation of a One Health model. The risk for a person bitten by an apparently healthy dog to develop rabies in the absence of rabies PEP was very low, which supports the WHO recommendations to delay PEP for this category of bite victims, when trained animal assessors are available and routinely communicate with the medical sector. Recent adoption of an electronic IBCM system is likely to expedite adoption of VARSP 2.0 to other Provinces and improve accuracy of field decisions and data collection.

AMR survivors? Chronic living with antimicrobial resistant infections.

Behind the statistics forecasting millions of deaths associated with antimicrobial resistance (AMR) is an even greater burden of morbidity leaving many people with long-term chronic illnesses and disability. Despite growing recognition of the importance of inter-sectoral and inter-disciplinary knowledge in forming responses to address this global health threat, there remains a paucity of social science research to understand the social burdens of AMR. In this qualitative study we explore the experiences of people living with chronic AMR infections, their interactions with health providers and therapeutic quests for care, and the effects upon their lives and that of their families and caregivers. Our analysis reveals that the resistant infections impacted not only the physical health but also the mental health of the sufferers and their caregivers, causing major disruptions to their social and work lives. Most undertook arduous treatment regimes - of powerful antibiotics with debilitating side effects, combined a range of other complementary and alternate therapies, including travel to seek treatment overseas. Further, we question the notion of 'AMR survivorship' currently being promoted as part of a public education campaign by the World Health Organisation and whether people with the diverse AMR experience really self-identify as 'survivors' of a biosocial group.

Using the WHO Self-Reporting Questionnaire-20 (SRQ-20) to Detect Symptoms of Common Mental Disorders among Pregnant Women in Vietnam: a Validation Study.

Purpose: Detection of antenatal common mental disorders in low-resource settings like Vietnam is important and requires a reliable, valid and practical screening tool. Currently, there is no such tool validated for use among pregnant women in Vietnam. This study aims to assess the validity of the Vietnamese version of the 20-item Self Reporting Questionnaire (SRQ-20) by evaluating its reliability, factorial structure, and performance in detecting common mental disorder (CMD) symptoms, thereby identifying the optimum cut-off score for CMD screening among pregnant women in Vietnam. Participants and Methods: A total of 210 pregnant women from four rural communes participated in a face-to-face interview using the Vietnamese version of the SRQ-20, followed by a clinical diagnostic interview based on ICD-10 diagnostic criteria of CMDs. The reliability of the SRQ-20 was assessed by calculating the scale's Cronbach's alpha to measure internal consistency. Factor analyses were undertaken to examine the factor structure of the instrument. The Receiver Operating Characteristic (ROC) curve analysis was performed to assess the performance of the SRQ-20 against the clinical diagnosis and to identify the optimum cut-off score. Results: Internal consistency was good, with a Cronbach's alpha of 0.87. Factor analyses resulted in a 4-factor solution. The area under the ROC curve (AUC) for detection of CMDs was 0.90. The optimum cut-off score of the SRQ-20 for detection of CMD symptoms among Vietnamese pregnant women was 5/6. Conclusion: The Vietnamese version of the SRQ-20 has the capacity to detect CMDs among pregnant women effectively and is recommended for use as a screening tool for CMDs in antenatal care settings in Vietnam.

Efficient control of the fungal pathogens Colletotrichum gloeosporioides and Penicillium digitatum infecting citrus fruits by native soilborne Bacillus velezensis strains.

Destruction of citrus fruits by fungal pathogens during preharvest and postharvest stages can result in severe losses for the citrus industry. Antagonistic microorganisms used as biological agents to control citrus pathogens are considered alternatives to synthetic fungicides. In this study, we aimed to identify fungal pathogens causing dominant diseases on citrus fruits in a specialized citrus cultivation region of Vietnam and inspect soilborne Bacillus isolates with antifungal activity against these pathogens. Two fungal pathogens were characterized as Colletotrichum gloeosporioides and Penicillium digitatum based on morphological characteristics and ribosomal DNA internal transcribed spacer sequence analyses. Reinfection assays of orange fruits confirmed that C. gloeosporioides causes stem-end rot, and P. digitatum triggers green mold disease. By the heterologous expression of the green fluorescent protein (GFP) in C. gloeosporioides using Agrobacterium tumefaciens-mediated transformation, we could observe the fungal infection process of the citrus fruit stem-end rot caused by C. gloeosporioides for the first time. Furthermore, we isolated and selected two soilborne Bacillus strains with strong antagonistic activity for preventing the decay of citrus fruits by these pathogens. Molecular analyses of 16 S rRNA and gyrB genes showed that both isolates belong to B. velezensis. Antifungal activity assays indicated that bacterial culture suspensions could strongly inhibit C. gloeosporioides and P. digitatum, and shield orange fruits from the invasion of the pathogens. Our work provides a highly effective Bacillus-based preservative solution for combating the fungal pathogens C. gloeosporioides and P. digitatum to protect citrus fruits at the postharvest stages.

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.

eMIC-AntiKP: Estimating minimum inhibitory concentrations of antibiotics towards Klebsiella pneumoniae using deep learning.

Nowadays, antibiotic resistance has become one of the most concerning problems that directly affects the recovery process of patients. For years, numerous efforts have been made to efficiently use antimicrobial drugs with appropriate doses not only to exterminate microbes but also stringently constrain any chances for bacterial evolution. However, choosing proper antibiotics is not a straightforward and time-effective process because well-defined drugs can only be given to patients after determining microbic taxonomy and evaluating minimum inhibitory concentrations (MICs). Besides conventional methods, numerous computer-aided frameworks have been recently developed using computational advances and public data sources of clinical antimicrobial resistance. In this study, we introduce eMIC-AntiKP, a computational framework specifically designed to predict the MIC values of 20 antibiotics towards Klebsiella pneumoniae. Our prediction models were constructed using convolutional neural networks and k-mer counting-based features. The model for cefepime has the most limited performance with a test 1-tier accuracy of 0.49, while the model for ampicillin has the highest performance with a test 1-tier accuracy of 1.00. Most models have satisfactory performance, with test accuracies ranging from about 0.70-0.90. The significance of eMIC-AntiKP is the effective utilization of computing resources to make it a compact and portable tool for most moderately configured computers. We provide users with two options, including an online web server for basic analysis and an offline package for deeper analysis and technical modification.

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.

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.

Trajectories to a cancer diagnosis: Why and when women seek help for breast symptoms in Vietnam.

Women in low- and middle-income countries where the prevalence and mortality of breast cancer are growing rapidly are more likely to be diagnosed at advanced stages, which negatively affects their treatment outcomes and chance of survival. The current literature in those settings tends to focus largely on explaining patient delay in seeking medical attention for breast symptoms. Meanwhile, little is known as to what prompts women to attend screening and diagnostic services after discovering symptomatic breasts. Drawn upon the data from in-depth interviews with 33 breast cancer patients in Central Vietnam conducted in 2019, this paper examines the context of women's decisions about breast screening and how the practice of seeking cancer diagnosis occurred. Our findings reveal an absence of a national screening program and that seeking medical advice was conducted on an ad hoc basis after self-detection of breast symptoms. Women's interpretations of symptomatic breasts as suspicious signs of cancer, the co-occurrence of important life events, or encouragement by people in their social network motivated women to seek medical attention at different public and private health facilities. Their encounters with the health sector often involved multiple visits across time and space in which they experienced various forms of diagnosis delay produced by the health system. Our study carries implications for interventions to encourage women's awareness of early cancer symptoms and prompt medical presentation after self-discovery of symptomatic breasts.

Depressive Symptoms and Their Correlates Among Older People in Rural Viet Nam: A Study Highlighting the Role of Family Factors.

This study examined the prevalence of depressive symptoms among older people living in a rural district in Hanoi, Vietnam in 2021. A cross-sectional survey was conducted with a sample of 495 people aged 60 years or older, using a structured questionnaire. The prevalence of self-reported depression, based on the short-form Geriatric Depression Scale-15 items, was 28.7%. Results from multiple variable logistic regression analyses showed that there was a significant association between age, educational level, family support, domestic violence, and depression. The study findings emphasize the importance of screening for depression in older people living in rural areas and the need for interventions aimed to enhance family support and reduce family-related stressors.

Identifying Transcription Factors That Prefer Binding to Methylated DNA Using Reduced G-Gap Dipeptide Composition.

Transcription factors (TFs) play an important role in gene expression and regulation of 3D genome conformation. TFs have ability to bind to specific DNA fragments called enhancers and promoters. Some TFs bind to promoter DNA fragments which are near the transcription initiation site and form complexes that allow polymerase enzymes to bind to initiate transcription. Previous studies showed that methylated DNAs had ability to inhibit and prevent TFs from binding to DNA fragments. However, recent studies have found that there were TFs that could bind to methylated DNA fragments. The identification of these TFs is an important steppingstone to a better understanding of cellular gene expression mechanisms. However, as experimental methods are often time-consuming and labor-intensive, developing computational methods is essential. In this study, we propose two machine learning methods for two problems: (1) identifying TFs and (2) identifying TFs that prefer binding to methylated DNA targets (TFPMs). For the TF identification problem, the proposed method uses the position-specific scoring matrix for data representation and a deep convolutional neural network for modeling. This method achieved 90.56% sensitivity, 83.96% specificity, and an area under the receiver operating characteristic curve (AUC) of 0.9596 on an independent test set. For the TFPM identification problem, we propose to use the reduced g-gap dipeptide composition for data representation and the support vector machine algorithm for modeling. This method achieved 82.61% sensitivity, 64.86% specificity, and an AUC of 0.8486 on another independent test set. These results are higher than those of other studies on the same problems.

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.

Detecting Rewiring Events in Protein-Protein Interaction Networks Based on Transcriptomic Data.

Proteins rarely carry out their cellular functions in isolation. Instead, eukaryotic proteins engage in about six interactions with other proteins on average. The aggregated protein interactome of an organism forms a "hairy ball"-type protein-protein interaction (PPI) network. Yet, in a typical human cell, only about half of all proteins are expressed at a particular time. Hence, it has become common practice to prune the full PPI network to the subset of expressed proteins. If RNAseq data is available, one can further resolve the specific protein isoforms present in a cell or tissue. Here, we review various approaches, software tools and webservices that enable users to construct context-specific or tissue-specific PPI networks and how these are rewired between two cellular conditions. We illustrate their different functionalities on the example of the interactions involving the human TNR6 protein. In an outlook, we describe how PPI networks may be integrated with epigenetic data or with data on the activity of splicing factors.

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.