Ballsawyer2494

Bread wheat (Triticum aestivum) is a major food crop and an important plant system for agricultural genetics research. However, due to the complexity and size of its allohexaploid genome, genomic resources are limited compared to other major crops. The IWGSC recently published a reference genome and associated annotation (IWGSC CS v1.0, Chinese Spring) that has been widely adopted and utilized by the wheat community. Although this reference assembly represents all three wheat subgenomes at chromosome-scale, it was derived from short reads, and thus is missing a substantial portion of the expected 16 Gbp of genomic sequence. We earlier published an independent wheat assembly (Triticum_aestivum_3.1, Chinese Spring) that came much closer in length to the expected genome size, although it was only a contig-level assembly lacking gene annotations. Here, we describe a reference-guided effort to scaffold those contigs into chromosome-length pseudomolecules, add in any missing sequence that was unique to the IWGSC CS v1.0 assembly, and annotate the resulting pseudomolecules with genes. Our updated assembly, Triticum_aestivum_4.0, contains 15.07 Gbp of nongap sequence anchored to chromosomes, which is 1.2 Gbps more than the previous reference assembly. It includes 108,639 genes unambiguously localized to chromosomes, including over 2000 genes that were previously unplaced. We also discovered >5700 additional gene copies, facilitating the accurate annotation of functional gene duplications including at the Ppd-B1 photoperiod response locus.

To assess disease trends, testing practices, community surveillance, case-fatality and excess deaths in children as compared with adults during the first pandemic peak in England.

England.

Children with COVID-19 between January and May 2020.

Trends in confirmed COVID-19 cases, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity rates in children compared with adults; community prevalence of SARS-CoV-2 in children with acute respiratory infection (ARI) compared with adults, case-fatality rate in children with confirmed COVID-19 and excess childhood deaths compared with the previous 5 years.

Children represented 1.1% (1,408/129,704) of SARS-CoV-2 positive cases between 16 January 2020 and 3 May 2020. In total, 540 305 people were tested for SARS-COV-2 and 129,704 (24.0%) were positive. In children aged <16 years, 35,200 tests were performed and 1408 (4.0%) were positive for SARS-CoV-2, compared to 19.1%-34.9% adults. Childhood cases increased from mid-March and peaked on 11 April before declining. Among 2,961 individuals presenting with ARI in primary care, 351 were children and 10 (2.8%) were positive compared with 9.3%-45.5% in adults. Eight children died and four (case-fatality rate, 0.3%; 95% CI 0.07% to 0.7%) were due to COVID-19. We found no evidence of excess mortality in children.

Children accounted for a very small proportion of confirmed cases despite the large numbers of children tested. SARS-CoV-2 positivity was low even in children with ARI. Our findings provide further evidence against the role of children in infection and transmission of SARS-CoV-2.

Children accounted for a very small proportion of confirmed cases despite the large numbers of children tested. SARS-CoV-2 positivity was low even in children with ARI. Our findings provide further evidence against the role of children in infection and transmission of SARS-CoV-2.Neuroblastoma is a malignancy of the developing sympathetic nervous system that accounts for 12% of childhood cancer deaths. Like many childhood cancers, neuroblastoma shows a relative paucity of somatic single-nucleotide variants (SNVs) and small insertions and deletions (indels) compared to adult cancers. Here, we assessed the contribution of somatic structural variation (SV) in neuroblastoma using a combination of whole-genome sequencing (WGS) of tumor-normal pairs (n = 135) and single-nucleotide polymorphism (SNP) genotyping of primary tumors (n = 914). Our study design allowed for orthogonal validation and replication across platforms. SV frequency, type, and localization varied significantly among high-risk tumors. MYCN nonamplified high-risk tumors harbored an increased SV burden overall, including a significant excess of tandem duplication events across the genome. Genes disrupted by SV breakpoints were enriched in neuronal lineages and associated with phenotypes such as autism spectrum disorder (ASD). The postsynaptic adapter protein-coding gene, SHANK2, located on Chromosome 11q13, was disrupted by SVs in 14% of MYCN nonamplified high-risk tumors based on WGS and 10% in the SNP array cohort. Expression of SHANK2 was low across human-derived neuroblastoma cell lines and high-risk neuroblastoma tumors. Forced expression of SHANK2 in neuroblastoma cells resulted in significant growth inhibition (P = 2.6 × 10-2 to 3.4 × 10-5) and accelerated neuronal differentiation following treatment with all-trans retinoic acid (P = 3.1 × 10-13 to 2.4 × 10-30). These data further define the complex landscape of somatic structural variation in neuroblastoma and suggest that events leading to deregulation of neurodevelopmental processes, such as inactivation of SHANK2, are key mediators of tumorigenesis in this childhood cancer.

Freshmen were found to use social networking sites (SNS) as a useful medium to effectively adjust to college life, which hints at a tendency to resort to SNS for social compensation. However, the compensatory use of SNS is usually problematic.

This study explores why a subgroup of freshmen developed depressive symptoms while socially adjusting to college by investigating the antecedent role of introversion, the explanatory role of compensatory use of SNS, and the protective role of perceived family support. The study is among the first to point out the relevance of the compensatory use of SNS in explaining the indirect association between introversion and depression with a longitudinal design.

A 3-wave panel sample of freshmen (N=1137) is used to examine the moderated mediation model.

We found that introversion at Wave 1 positively predicted compensatory use of SNS at Wave 2 and subsequently increased depression at Wave 3 (unstandardized B=0.07, SE 0.02, P<.001, 95% CI 0.04-0.10; unstandardized B=0r freshmen with different levels of introversion clarifies how SNS affect young adults' lives.

Smartphone-based contact tracing apps can contribute to reducing COVID-19 transmission rates and thereby support countries emerging from lockdowns as restrictions are gradually eased.

The primary objective of our study is to determine the potential uptake of a contact tracing app in the Dutch population, depending on the characteristics of the app.

A discrete choice experiment was conducted in a nationally representative sample of 900 Dutch respondents. Simulated maximum likelihood methods were used to estimate population average and individual-level preferences using a mixed logit model specification. Individual-level uptake probabilities were calculated based on the individual-level preference estimates and subsequently aggregated into the sample as well as subgroup-specific contact tracing app adoption rates.

The predicted app adoption rates ranged from 59.3% to 65.7% for the worst and best possible contact tracing app, respectively. The most realistic contact tracing app had a predicted adoption orget uptake of 60% that has been formulated by the Dutch government. The main challenge will be to increase the uptake among older adults, who are least inclined to install and use a COVID-19 contact tracing app.

The COVID-19 pandemic has necessitated a rapid increase of space in highly infectious disease intensive care units (ICUs). At Houston Methodist Hospital (HMH), a virtual intensive care unit (vICU) was used amid the COVID-19 outbreak.

The aim of this paper was to detail the novel adaptations and rapid expansion of the vICU that were applied to achieve patient-centric solutions while protecting staff and patients' families during the pandemic.

The planned vICU implementation was redirected to meet the emerging needs of conversion of COVID-19 ICUs, including alterations to staged rollout timing, virtual and in-person staffing, and scope of application. With the majority of the hospital critical care physician workforce redirected to rapidly expanded COVID-19 ICUs, the non-COVID-19 ICUs were managed by cardiovascular surgeons, cardiologists, neurosurgeons, and acute care surgeons. HMH expanded the vICU program to fill the newly depleted critical care expertise in the non-COVID-19 units to provide urgent, emsearch is required to examine the impact of innovative applications of telecritical care in the treatment of critically ill patients.

Telecritical care has been established as an advantageous mechanism for the delivery of critical care expertise during the expedited rollout of the vICU at Houston Methodist Hospital. Overall responses from patients, families, and physicians are in favor of continued vICU care; however, further research is required to examine the impact of innovative applications of telecritical care in the treatment of critically ill patients.

Mounier-Kuhn syndrome or congenital tracheobronchomegaly is a rare disease characterized by dilation of the trachea and the main bronchi within the thoracic cavity. The predominant signs and symptoms of the disease include coughing, purulent and abundant expectoration, dyspnea, snoring, wheezing, and recurrent respiratory infection. Symptoms of the disease in some patients are believed to be pathological manifestations arising due to resident tracheobronchomalacia. Although treatment options used for the management of this disease include inhaled bronchodilators, corticosteroids, and hypertonic solution, there is no consensus on the treatment. The use of continuous positive airway pressure (CPAP) has been reported as a potential therapeutic option for tracheobronchomalacia, but no prospective studies have demonstrated its efficacy in this condition.

The purpose of this is to identify the presence of tracheobronchomalacia and an optimal CPAP pressure that reduces the tracheobronchial collapse in patients witutional review board on January 24, 2017, and approval was granted on February 2, 2017 (Brazilian Research database number CAAE 64001317.4.000.0068). Patient evaluations started in April 2018. Planned recruitment is based on volunteers' availability and clinical stability, and interventions will be conducted at least once a month to finish the project at the end of 2020. A preliminary analysis of each case will be performed after each intervention, but detailed results are expected to be reported in the first quarter of 2021.

There is no consensus on the best treatment options for managing Mounier-Kuhn syndrome. The use of positive pressure could maintain patency of the collapsed airways, functioning as a "pneumatic stent" to reduce the degree of airflow obstruction. This, in turn, could promote mobilization of thoracic secretion and improve pulmonary ventilation.

ClinicalTrails.gov NCT03101059; https//clinicaltrials.gov/ct2/show/NCT03101059.

DERR1-10.2196/14786.

DERR1-10.2196/14786.

Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences.

The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding.

We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants The model development data set was obtained from 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. A set of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures oute STEMI. The discrimination, calibration, and DCA of the model were found to be satisfactory.

ChiCTR.org ChiCTR1900027578; http//www.chictr.org.cn/showprojen.aspx?proj=45926.

ChiCTR.org ChiCTR1900027578; http//www.chictr.org.cn/showprojen.aspx?proj=45926.

Many health care organizations use social media to support a variety of activities. To ensure continuous improvement in social media performance, health care organizations must measure their social media.

The purpose of this study is to explore how health care organizations approach social media measurement and to elucidate the tools they employ.

In this exploratory qualitative research, Australian health care organizations that use social media, varying in size and locality, were invited to participate in the study. Data were collected through semistructured interviews, and the transcripts were analyzed using thematic analysis.

The study identified health care organizations' approaches to social media measurement. While some measured their social media frequently, others used infrequent measurements, and a few did not measure theirs at all. Those that measured their social media used one or a combination of the following yardsticks personal benchmarking, peer benchmarking, and metric benchmarking. Thascent stage. There is a need to improve knowledge, sophistication, and integration of social media strategy through the application of theoretical and analytical knowledge to help resolve the current challenge of effective social media measurement. This study calls for social media training in health care organizations. Such training must focus on how to use relevant tools and how to measure their use effectively.

Inappropriate asthma control reduces quality of life and causes increased exacerbations. Mobile health (mHealth) employs information and communication technology for surveying health-related issues.

This noninterventional, observational study assessed current real-world asthma control levels among Japanese patients with asthma and cough variant asthma (CVA) using the Zensoku-Log app.

We developed the app using the ResearchKit platform and conducted a mobile-based, self-reporting, observational survey among patients with asthma and CVA. The app was downloaded 7855 times between February 2016 and February 2018, and enabled collection of data on symptoms, comorbidities, quality of life, medications, asthma control, and adherence.

Of the 1744 eligible participants (median age 33 years; range 20-74 years; male-to-female ratio 38.761.3), 50.97% (889/1744) reported unscheduled visits, 62.84% (1096/1744) reported regularly scheduled visits, 23.14% (402/1737) smoked, and 40.75% (705/1730) had pets. In additionopen-bin/ctr_e/ctr_view.cgi?recptno=R000023913.

UMIN Clinical Trial Registry UMIN000021043; https//upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000023913.

Demographic and sociobehavioral factors are strong drivers of HIV infection rates in sub-Saharan Africa. These factors are often studied in qualitative research but ignored in quantitative analyses. However, they provide in-depth insight into the local behavior and may help to improve HIV prevention.

To obtain a comprehensive overview of the sociobehavioral factors influencing HIV prevalence and incidence in Malawi, we systematically reviewed the literature using a newly programmed tool for automatizing part of the systematic review process.

Due to the choice of broad search terms ("HIV AND Malawi"), our preliminary search revealed many thousands of articles. We, therefore, developed a Python tool to automatically extract, process, and categorize open-access articles published from January 1, 1987 to October 1, 2019 in the PubMed, PubMed Central, JSTOR, Paperity, and arXiV databases. We then used a topic modelling algorithm to classify and identify publications of interest.

Our tool extracted 22,709 uries.

Our software does not replace traditional systematic reviews, but it returns useful results to broad queries of open-access literature in under a week, without a priori knowledge. This produces a "seed dataset" of relevance that could be further developed. It identified known factors and factors that may be specific to Malawi. In the future, we aim to expand the tool by adding more social science databases and applying it to other sub-Saharan African countries.

Most people currently use the internet to obtain information about many subjects, including health information. Thus, medical associations need to provide accurate medical information websites. Although medical associations have their own patient education pages, it is not clear if these websites actually show up in search results.

The aim of this study was to evaluate how well medical associations function as online information providers by searching for information about musculoskeletal-related pain online and determining the ranking of the websites of medical associations.

We conducted a Google search for frequently searched keywords. Keywords were extracted using Google Ads Keyword Planner associated with "pain" relevant to the musculoskeletal system from June 2016 to December 2019. The top 20 search queries were extracted and searched using the Google search engine in Japan and the United States.

The number of suggested queries for "pain" provided by Google Ads Keyword Planner was 930 in the United States and 2400 in Japan. Among the top 20 musculoskeletal-related pain queries chosen, the probability that the medical associations' websites would appear in the top 10 results was 30% in the United States and 45% in Japan. In five queries each, the associations' websites did not appear among the top 100 results. No significant difference was found in the rank of the associations' website search results (P=.28).

To provide accurate medical information to patients, it is essential to undertake effective measures for search engine optimization. For orthopedic associations, it is necessary that their websites should appear among the top search results.

To provide accurate medical information to patients, it is essential to undertake effective measures for search engine optimization. For orthopedic associations, it is necessary that their websites should appear among the top search results.

To optimize postoperative outcomes after bariatric surgery, lifestyle changes including increased physical activity are needed. Micronutrient deficiency after surgery is also common and daily supplementation is recommended.

The aim of the PromMera study is to evaluate the effects of a 12-week smartphone app intervention on promotion of physical activity (primary outcome) and adherence to postsurgery vitamin and mineral supplementation, as well as on other lifestyle factors and overall health in patients undergoing bariatric surgery.

The PromMera study is a two-arm, randomized controlled trial comprising patients undergoing bariatric surgery. Participants are randomized postsurgery 11 to either the intervention group (ie, use of the PromMera app for 12 weeks) or the control group receiving only standard care. Clinical and lifestyle variables are assessed pre- and postsurgery after 18 weeks (postintervention assessment), 6 months, 1 year, and 2 years. Assessments include body composition using Tanita or BOD POD analyzers, muscle function using handgrip, biomarkers in blood, and an extensive questionnaire on lifestyle factors. Physical activity is objectively measured using the ActiGraph wGT3X-BT triaxial accelerometer.

A total of 154 participants have been enrolled in the study. The last study participant was recruited in May 2019. Data collection will be complete in May 2021.

Implementing lifestyle changes are crucial after bariatric surgery and new ways to reach patients and support such changes are needed. An app-based intervention is easily delivered at any time and can be a key factor in the adoption of healthier behavioral patterns in this rapidly growing group of patients.

ClinicalTrials.gov NCT03480464; https//clinicaltrials.gov/ct2/show/NCT03480464.

DERR1-10.2196/19624.

DERR1-10.2196/19624.

Alcohol accounts for 5.1% of the global burden of disease and injury, and approximately 1 in 10 people worldwide develop an alcohol use disorder. Approach bias modification (ABM) is a computerized cognitive training intervention in which patients are trained to "avoid" alcohol-related images and "approach" neutral or positive images. ABM has been shown to reduce alcohol relapse rates when delivered in residential settings (eg, withdrawal management or rehabilitation). However, many people who drink at hazardous or harmful levels do not require residential treatment or choose not to access it (eg, owing to its cost, duration, inconvenience, or concerns about privacy). Smartphone app-delivered ABM could offer a free, convenient intervention to reduce cravings and consumption that is accessible regardless of time and place, and during periods when support is most needed. Importantly, an ABM app could also easily be personalized (eg, allowing participants to select personally relevant images as training stimulilinical Trials Registry (ANZCTR) ACTRN12620000638932p; https//www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12620000638932p.

PRR1-10.2196/21278.

PRR1-10.2196/21278.

Although we are living in an era of transparency, medical documents are often still difficult to access. Blockchain technology allows records to be both immutable and transparent.

Using blockchain technology, the aim of this study was to develop a medical document monitoring system that informs patients of changes to their medical documents. We then examined whether patients can effectively verify the monitoring of their primary care clinical medical records in a system based on blockchain technology.

We enrolled participants who visited two primary care clinics in Korea. Three substudies were performed (1) a survey of the recognition of blockchain medical records changes and the digital literacy of participants; (2) an observational study on participants using the blockchain-based mobile alert app; and (3) a usability survey study. The participants' medical documents were profiled with HL7 Fast Healthcare Interoperability Resources, hashed, and transacted to the blockchain. The app checked the changes l record itself to the network. This ensures the transparency of medical records as well as patient empowerment.

Patients showed great interest in a blockchain-based system to monitor changes in their medical records. The blockchain system is useful for informing patients of changes in their records via the app without uploading the medical record itself to the network. This ensures the transparency of medical records as well as patient empowerment.

The World Health Organization recommends that a woman waits at least 24 months after a live birth before getting pregnant again; however, an estimated 25% of birth intervals in low-income countries do not meet this recommendation for adequate birth spacing, and the unmet need for postpartum family planning (PPFP) services is high. Few randomized controlled trials have assessed the causal impact of access to PPFP services, and even fewer evaluations have investigated how such interventions may affect postpartum contraceptive use, birth spacing, and measures of health and well-being.

This protocol paper aims to describe a randomized controlled trial that is being conducted to identify the causal impact of an intervention to improve access to PPFP services on contraceptive use, pregnancy, and birth spacing in urban Malawi. The causal effect of the intervention will be determined by comparing outcomes for respondents who are randomly assigned to an intervention arm against outcomes for respondents who are ran follow-up survey began in August 2018 and was completed in February 2019. A total of 1669 women, or 77.88% of women who were eligible for follow-up, were successfully contacted and reinterviewed at the second follow-up. The analysis of the primary outcomes is ongoing and is expected to be completed in 2021.

The results of this trial seek to fill the current knowledge gaps in the effectiveness of family planning interventions on improving fertility and health outcomes. The findings also show that the benefits of improving access to family planning are likely to extend beyond the fertility and health domain by improving other measures of women's well-being.

American Economics Association Registry Trial Number AEARCTR-0000697; https//www.socialscienceregistry.org/trials/697 Registry for International Development Impact Evaluations (RIDIE) Trial Number RIDIE-STUDY-ID-556784ed86956; https//ridie.3ieimpact.org/index.php?r=search/detailView&id=320.

DERR1-10.2196/16697.

DERR1-10.2196/16697.

There is a pressing need to address the unacceptable disparities and underrepresentation of racial and ethnic minority groups, including Hispanics or Latinxs, in smoking cessation trials.

Given the lack of research on recruitment strategies for this population, this study aims to assess effective recruitment methods based on enrollment and cost.

Recruitment and enrollment data were collected from a nationwide randomized controlled trial (RCT) of a Spanish-language smoking cessation intervention (N=1417). The effectiveness of each recruitment strategy was evaluated by computing the cost per participant (CPP), which is the ratio of direct cost over the number enrolled. More effective strategies yielded lower CPPs. Demographic and smoking-related characteristics of participants recruited via the two most effective strategies were also compared (n=1307).

Facebook was the most effective method (CPP=US $74.12), followed by TV advertisements (CPP=US $191.31), whereas public bus interior card advertising was Hispanic or Latinx smokers in the United States for this RCT. However, using multiple methods was necessary to recruit a more diverse sample of Spanish-preferring Hispanic or Latinx smokers.

Dental visits are unpleasant; sometimes, patients only seek treatment when they are in intolerable pain. Recently, the novel coronavirus (COVID-19) pandemic has highlighted the need for remote communication when patients and dentists cannot meet in person. Gingivitis is very common and characterized by red, swollen, bleeding gums. Gingivitis heals within 10 days of professional care and with daily, thorough oral hygiene practices. If left untreated, however, its progress may lead to teeth becoming mobile or lost. Of the many medical apps currently available, none monitor gingivitis.

This study aimed to present a characterization and development model of a mobile health (mHealth) app called iGAM, which focuses on periodontal health and improves the information flow between dentists and patients.

A focus group discussed the potential of an app to monitor gingivitis, and 3 semistructured in-depth interviews were conducted on the use of apps for monitoring gum infections. We used a qualitative design procesth the provision of mouth openers, and (2) the operation of the phone, which was alleviated by changing the app to be fully automated, with a weekly reminder and an instructions document. Final interviews showed satisfaction.

iGAM is the first mHealth app for monitoring gingivitis using self-photography. iGAM facilitates the information flow between dentists and patients between checkups and may be useful when face-to-face consultations are not possible (such as during the COVID-19 pandemic).

iGAM is the first mHealth app for monitoring gingivitis using self-photography. iGAM facilitates the information flow between dentists and patients between checkups and may be useful when face-to-face consultations are not possible (such as during the COVID-19 pandemic).

Fungal ocular involvement can develop in patients with fungal bloodstream infections and can be vision-threatening. Ocular involvement has become less common in the current era of improved antifungal therapies. Retrospectively determining the prevalence of fungal ocular involvement is important for informing clinical guidelines, such as the need for routine ophthalmologic consultations. However, manual retrospective record review to detect cases is time-consuming.

This study aimed to determine the prevalence of fungal ocular involvement in a critical care database using both structured and unstructured electronic health record (EHR) data.

We queried microbiology data from 46,467 critical care patients over 12 years (2000-2012) from the Medical Information Mart for Intensive Care III (MIMIC-III) to identify 265 patients with culture-proven fungemia. For each fungemic patient, demographic data, fungal species present in blood culture, and risk factors for fungemia (eg, presence of indwelling catheters, redite the review of narrative notes. This approach is highly relevant for ophthalmology, where diagnoses are often based on physical examination findings that are documented within clinical notes.

Up to one-third of adolescents and young adults (11-21 years old) with chronic kidney disease exhibit suboptimal rates of adherence to renal-protective antihypertensive medications. Mobile health interventions may promote higher adherence to these medicines in these individuals, but empirical research is needed to inform best practices for applying these modalities.

In this multiphase investigation, we developed and tested a theoretically informed text messaging intervention based on the COM-B model, a well-established health intervention framework stating that capability, opportunity, and motivation interactively modify health behaviors, to improve participants' antihypertensive medication adherence in a pilot randomized controlled trial. Qualitative data on user experiences were obtained.

In phase 1, intervention messages (Reminder+COM-B Message) were developed via stakeholder engagement of participants and pediatric nephrologists. In phase 2, the Reminder+COM-B Message intervention was tested against was feasible and acceptable to adolescents/young adults and demonstrated potential to promote participants' daily medication adherence beyond simple reminders. Further research is needed to determine the Reminder+COM-B Message intervention's mechanisms of adherence behavior change and to incorporate qualitative participant feedback into a modified version of this intervention to enhance its acceptability.

ClinicalTrials.gov NCT03651596; https//clinicaltrials.gov/ct2/show/NCT03651596.

ClinicalTrials.gov NCT03651596; https//clinicaltrials.gov/ct2/show/NCT03651596.The nuclear export of mRNAs is a complex process, involving the participaton of numerous proteins, the recruitement of which starts during the early steps of mRNAs biosynthesis and maturation. This strategy allows the cell to export only mature and non-defective transcripts to the cytoplasm where they are directed to the translational machinery. The vast majority of mRNAs is exported by the dimeric transport receptor TAP-p15, which is mainly recruited by the large multiprotein complex TREX-1. Other mRNAs that do not display all typical features of a mature transcript use variants of the TAP-p15 export pathway or recruit the alternative export receptor CRM1. Most DNA viruses, retroviruses, and influenza viruses, the mRNAs of which are synthesized in the nucleus, also use TAP-p15 and/or CRM1 to export their mRNAs. The highjacking of the cellular export machinery by viral mRNAs usually involves the presence of constitutive structural elements that directly load cellular export factors and/or viral adaptor proteins. Associated with the host export machinery, viral mRNAs escape host surveillance, are efficiently exported in the cytoplasm in order to be translated, and thus make possible the progress toward the later events of the virus life cycles.Dengue virus (DENV) is part of the Flaviviridae family and has been classify by the Word Health Organization (WHO) as one of the top 10 health concerns. It is the most widespread mosquito-borne human disease. Considering the increasing number of severe dengue, the expansion of the vector territory due to climate change and population movement, it is urgent to find a way to counteract the virus. Indeed, currently there is no treatment available and despite the large number of molecules that proved efficacy in vitro rare are the compounds that have been further evaluated and lead to clinical trials. Development of antiviral is a promising complementary strategy to vaccine production. This review introduces the DENV antivirals and the notions of direct acting antiviral versus host targeted antiviral. It underlines the importance to develop multiple potent antivirals and the relevance to maintain research on this matter.The Alphaherpesvirinae sub-family includes viruses primarily associated with cold sores, genital herpes, chicken pox and shingles in humans, but are responsible for several other pathologies and additionally infect many animals. These viruses are large entities that travel through various cellular compartments during their life cycle. As for the transport of cellular cargoes, this involves several budding and fusion steps as well as transport of viral particles along the cytoskeleton. Though the entry of these viruses in cells is generally well understood at the molecular level, the egress of newly assembled viral particles is poorly characterized. Albeit several viral genes have been implicated, their mode of action and the contribution of the cell remain to be clarified. The present review updates our current knowledge of the transport of herpes viruses and pinpoints open questions about the mechanisms they exploit.Medical time series of laboratory tests has been collected in electronic health records (EHRs) in many countries. Machine-learning algorithms have been proposed to analyze the condition of patients using these medical records. However, medical time series may be recorded using different laboratory parameters in different datasets. This results in the failure of applying a pretrained model on a test dataset containing a time series of different laboratory parameters. This article proposes to solve this problem with an unsupervised time-series adaptation method that generates time series across laboratory parameters. Specifically, a medical time-series generation network with similarity distillation is developed to reduce the domain gap caused by the difference in laboratory parameters. The relations of different laboratory parameters are analyzed, and the similarity information is distilled to guide the generation of target-domain specific laboratory parameters. To further improve the performance in cross-domain medical applications, a missingness-aware feature extraction network is proposed, where the missingness patterns reflect the health conditions and, thus, serve as auxiliary features for medical analysis. In addition, we also introduce domain-adversarial networks in both feature level and time-series level to enhance the adaptation across domains. Experimental results show that the proposed method achieves good performance on both private and publicly available medical datasets. Ablation studies and distribution visualization are provided to further analyze the properties of the proposed method.Dynamic changes are an important and inescapable aspect of many real-world optimization problems. Designing algorithms to find and track desirable solutions while facing challenges of dynamic optimization problems is an active research topic in the field of swarm and evolutionary computation. To evaluate and compare the performance of algorithms, it is imperative to use a suitable benchmark that generates problem instances with different controllable characteristics. In this article, we give a comprehensive review of existing benchmarks and investigate their shortcomings in capturing different problem features. We then propose a highly configurable benchmark suite, the generalized moving peaks benchmark, capable of generating problem instances whose components have a variety of properties, such as different levels of ill-conditioning, variable interactions, shape, and complexity. Moreover, components generated by the proposed benchmark can be highly dynamic with respect to the gradients, heights, optimum locations, condition numbers, shapes, complexities, and variable interactions. Finally, several well-known optimizers and dynamic optimization algorithms are chosen to solve generated problems by the proposed benchmark. The experimental results show the poor performance of the existing methods in facing new challenges posed by the addition of new properties.The herniation of cerebellum through the foramen magnum may block the normal flow of cerebrospinal fluid determining a severe disorder called Chiari I Malformation (CM-I). Different surgical options are available to help patients, but there is no standard to select the optimal treatment. This paper proposes a fully automated method to select the optimal intervention. It is based on morphological parameters of the brain, posterior fossa and cerebellum, estimated by processing sagittal magnetic resonance images (MRI). The processing algorithm is based on a non-rigid registration by a balanced multi-image generalization of demons method. Moreover, a post-processing based on active contour was used to improve the estimation of cerebellar hernia. This method allowed to delineate the boundaries of the regions of interest with a percentage of agreement with the delineation of an expert of about 85%. Different features characterizing the estimated regions were then extracted and used to develop a classifier to identify the optimal surgical treatment. Classification accuracy on a database of 50 patients was about 92%, with a predictive value of 88% (tested with a leave-one-out approach).Auscultation is the most efficient way to diagnose cardiovascular and respiratory diseases. To reach accurate diagnoses, a device must be able to recognize heart and lung sounds from various clinical situations. However, the recorded chest sounds are mixed by heart and lung sounds. Thus, effectively separating these two sounds is critical in the pre-processing stage. Recent advances in machine learning have progressed on monaural source separations, but most of the well-known techniques require paired mixed sounds and individual pure sounds for model training. As the preparation of pure heart and lung sounds is difficult, special designs must be considered to derive effective heart and lung sound separation techniques. In this study, we proposed a novel periodicity-coded deep auto-encoder (PC-DAE) approach to separate mixed heart-lung sounds in an unsupervised manner via the assumption of different periodicities between heart rate and respiration rate. The PC-DAE benefits from deep-learning-based models by extracting representative features and considers the periodicity of heart and lung sounds to carry out the separation. We evaluated PC-DAE on two datasets. The first one includes sounds from the Student Auscultation Manikin (SAM), and the second is prepared by recording chest sounds in real-world conditions. Experimental results indicate that PC-DAE outperforms several well-known separation works in terms of standardized evaluation metrics. Moreover, waveforms and spectrograms demonstrate the effectiveness of PC-DAE compared to existing approaches. It is also confirmed that by using the proposed PC-DAE as a pre-processing stage, the heart sound recognition accuracies can be notably boosted. The experimental results confirmed the effectiveness of PC-DAE and its potential to be used in clinical applications.Accurate registration of prostate magnetic resonance imaging (MRI) images of the same subject acquired at different time points helps diagnose cancer and monitor the tumor progress. However, it is very challenging especially when one image was acquired with the use of endorectal coil (ERC) but the other was not, which causes significant deformation. Classical iterative image registration methods are also computationally intensive. Deep learning based registration frameworks have recently been developed and demonstrated promising performance. However, the lack of proper constraints often results in unrealistic registration. In this paper, we propose a multi-task learning based registration network with anatomical constraint to address these issues. The proposed approach uses a cycle constraint loss to achieve forward/backward registration and an inverse constraint loss to encourage diffeomorphic registration. In addition, an adaptive anatomical constraint aiming for regularizing the registration network with the use of anatomical labels is introduced through weak supervision. Our experiments on registering prostate MRI images of the same subject obtained at different time points with and without ERC show that the proposed method achieves very promising performance under different measures in dealing with the large deformation. Compared with other existing methods, our approach works more efficiently with average running time less than a second and is able to obtain more visually realistic results.Hepatocellular carcinoma (HCC) is a common type of liver cancer and has a high mortality world-widely. The diagnosis, prognoses, and therapeutics are very poor due to the unclear molecular mechanism of progression of the disease. To unveil the molecular mechanism of progression of HCC, we extract a large sample of mRNA expression levels from the GEO database where a total of 167 samples were used for study, and out of them, 115 samples were from HCC tumor tissue. This study aims to investigate the module of differentially expressed genes (DEGs) which are co-expressed only in HCC sample data but not in normal tissue samples. Thereafter, we identified the highly significant module of significant co-expressed genes and formed a PPI network for these genes. There were only six genes (namely, MSH3, DMC1, ALPP, IL10, ZNF223, and HSD17B7) obtained after analysis of the PPI network. Out of six only MSH3, DMC1, HSD17B7, and IL10 were found enriched in GO Term & Pathway enrichment analysis and these candidate genes were mainly involved in cellular process, metabolic and catalytic activity, which promote the development & progression of HCC. Lastly, the composite 3-node FFL reveals the driver miRNAs and TFs associated with our key genes.Eye typing is a hands-free method of human computer interaction, which is especially useful for people with upper limb disabilities. Users select a desired key by gazing at it in an image of a keyboard for a fixed dwell time. There is a tradeoff in selecting the dwell time; shorter dwell times lead to errors due to unintentional selections, while longer dwell times lead to a slow input speed. We propose to speed up eye typing while maintaining low error by dynamically adjusting the dwell time for each letter based on the past input history. More likely letters are assigned shorter dwell times. Our method is based on a probabilistic generative model of gaze, which enables us to assign dwell times using a principled model that requires only a few free parameters. We evaluate our model on both able-bodied subjects and subjects with a spinal cord injury (SCI). Compared to the standard dwell time method, we find consistent increases in typing speed in both cases. e.g., 41.8% faster typing for able-bodied subjects on a transcription task and 49.5% faster typing for SCI subjects in a chatbot task. We observed more inter-subject variability for SCI subjects.In this article, we present a survey on surface remeshing techniques, classifying all collected articles in different categories and analyzing specific methods with their advantages, disadvantages, and possible future improvements. Following the systematic literature review methodology, we define step-by-step guidelines throughout the review process, including search strategy, literature inclusion/exclusion criteria, article quality assessment, and data extraction. With the aim of literature collection and classification based on data extraction, we summarized collected articles, considering the key remeshing objectives, the way the mesh quality is defined and improved, and the way their techniques are compared with other previous methods. Remeshing objectives are described by angle range control, feature preservation, error control, valence optimization, and remeshing compatibility. The metrics used in the literature for the evaluation of surface remeshing algorithms are discussed. Meshing techniques are compared with other related methods via a comprehensive table with indices of the method name, the remeshing challenge met and solved, the category the method belongs to, and the year of publication. We expect this survey to be a practical reference for surface remeshing in terms of literature classification, method analysis, and future prospects.Photoacoustic (PA) image reconstruction generally utilizes delay-and-sum (DAS) beamforming of received acoustic waves from tissue irradiated with optical illumination. However, nonadaptive DAS reconstructed cardiac PA images exhibit temporally varying noise which causes reduced myocardial PA signal specificity, making image interpretation difficult. Adaptive beamforming algorithms such as minimum variance (MV) with coherence factor (CF) weighting have been previously reported to improve the DAS image quality. In this article, we report on an adaptive beamforming algorithm by extending CF weighting to the temporal domain for preclinical cardiac PA imaging (PAI). The proposed spatiotemporal coherence factor (STCF) considers multiple temporally adjacent image acquisition events during beamforming and cancels out signals with low spatial coherence and temporal coherence, resulting in higher background noise cancellation while preserving the main features of interest (myocardial wall) in the resultant PA images. STCF has been validated using the numerical simulations and in vivo ECG and respiratory-signal-gated cardiac PAI in healthy murine hearts. The numerical simulation results demonstrate that STCF weighting outperforms DAS and MV beamforming with and without CF weighting under different levels of inherent contrast, acoustic attenuation, optical scattering, and signal-to-noise (SNR) of channel data. Performance improvement is attributed to higher sidelobe reduction (at least 5 dB) and SNR improvement (at least 10 dB). Improved myocardial signal specificity and higher signal rejection in the left ventricular chamber and acoustic gel region are observed with STCF in cardiac PAI.A spectrum-domain method, called full-matrix phase shift migration (FM-PSM), is presented for transcranial ultrasound phase correction and imaging with ideal synthetic aperture focusing technology. The simulated data obtained using the pseudospectral time-domain method are used to evaluate the feasibility of the method. The experimental data measured from a 3-D printed skull phantom are used to evaluate the algorithm performance in terms of resolution, contrast-to-noise ratio (CNR), and eccentricity comparing with the classical ray-tracing delay and sum (DAS) method. In wire imaging experiment, FM-PSM has a lateral resolution of 0.22 mm and ray-tracing DAS has a lateral resolution of 0.24 mm measured at -6-dB drop using a transducer with a center frequency of 6.25 MHz. In cylinder imaging experiment, FM-PSM has a CNR of 2.14 and ray-tracing DAS has a CNR of 1.82, which illustrates about 17% improvement. For a J -element array and an output image with pixels M ×N (lateral × axial), the computational cost of the DAS is of O(J ×M2×N2) ; on the contrary, it reduces to O(J ×M ×N2) with the proposed FM-PSM. The results suggest that FM-PSM is an efficiency method for transcranial ultrasonic imaging.Although wireless capsule endoscopy is the preferred modality for diagnosis and assessment of small bowel diseases, the poor camera resolution is a substantial limitation for both subjective and automated diagnostics. Enhanced-resolution endoscopy has shown to improve adenoma detection rate for conventional endoscopy and is likely to do the same for capsule endoscopy. In this work, we propose and quantitatively validate a novel framework to learn a mapping from low-to-high-resolution endoscopic images. We combine conditional adversarial networks with a spatial attention block to improve the resolution by up to factors of 8× , 10× , 12× , respectively. Quantitative and qualitative studies demonstrate the superiority of EndoL2H over state-of-the-art deep super-resolution methods Deep Back-Projection Networks (DBPN), Deep Residual Channel Attention Networks (RCAN) and Super Resolution Generative Adversarial Network (SRGAN). Mean Opinion Score (MOS) tests were performed by 30 gastroenterologists qualitatively assess and confirm the clinical relevance of the approach. EndoL2H is generally applicable to any endoscopic capsule system and has the potential to improve diagnosis and better harness computational approaches for polyp detection and characterization. Our code and trained models are available at https//github.com/CapsuleEndoscope/EndoL2H.We address the problem of finding reliable dense correspondences between a pair of images. This is a challenging task due to strong appearance differences between the corresponding scene elements and ambiguities generated by repetitive patterns. The contributions of this work are threefold. First, inspired by the classic idea of disambiguating feature matches using semi-local constraints, we develop an end-to-end trainable convolutional neural network architecture that identifies sets of spatially consistent matches by analyzing neighbourhood consensus patterns in the 4D space of all possible correspondences between a pair of images without the need for a global geometric model. Second, we demonstrate that the model can be trained effectively from weak supervision in the form of matching and non-matching image pairs without the need for costly manual annotation of point to point correspondences. Third, we show the proposed neighbourhood consensus network can be applied to a range of matching tasks including both category- and instance-level matching, obtaining the state-of-the-art results on the PF, TSS, InLoc and HPatches benchmarks.Providing an accurate prognosis for prolonged disorder of consciousness (pDOC) patients remains a clinical challenge. Large cross-sectional studies have demonstrated the diagnostic and prognostic value of functional brain networks measured using high-density electroencephalography (hdEEG). Nonetheless, the prognostic value of these neural measures has yet to be assessed by longitudinal follow-up. We address this gap by assessing the utility of hdEEG to prognosticate long-term behavioural outcome, employing longitudinal data collected from a cohort of patients assessed systematically with resting hdEEG and the Coma Recovery Scale-Revised (CRS-R) at the bedside over a period of two years. We used canonical correlation analysis to relate clinical (including CRS-R scores combined with demographic variables) and hdEEG variables to each other. This analysis revealed that the patient's age, and the hdEEG theta band power and alpha band connectivity, contributed most significantly to the relationship between hdEEG and clinical variables.