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Type I polyketide synthases (T1PKSs) hold enormous potential as a rational production platform for the biosynthesis of specialty chemicals. However, despite great progress in this field, the heterologous expression of PKSs remains a major challenge. One of the first measures to improve heterologous gene expression can be codon optimization. Although controversial, choosing the wrong codon optimization strategy can have detrimental effects on the protein and product levels. In this study, we analyzed 11 different codon variants of an engineered T1PKS and investigated in a systematic approach their influence on heterologous expression in Corynebacterium glutamicum, Escherichia coli, and Pseudomonas putida. Our best performing codon variants exhibited a minimum 50-fold increase in PKS protein levels, which also enabled the production of an unnatural polyketide in each of these hosts. Furthermore, we developed a free online tool (https://basebuddy.lbl.gov) that offers transparent and highly customizable codon optimization with up-to-date codon usage tables. In this work, we not only highlight the significance of codon optimization but also establish the groundwork for the high-throughput assembly and characterization of PKS pathways in alternative hosts.

Abstract Background As genomes of many eukaryotic species, especially plants, are large and complex, their de novo sequencing and assembly is still a difficult task despite progress in sequencing technologies. An alternative to genome assembly is the assembly of transcriptome, the set of RNA products of the expressed genes. While a bunch of de novo transcriptome assemblers exists, the challenges of transcriptomes (the existence of isoforms, the uneven expression levels across genes) complicates the generation of high-quality assemblies suitable for downstream analyses. Results We developed Trans2express – a web-based tool and a pipeline of de novo hybrid transcriptome assembly and postprocessing based on rnaSPAdes with a set of subsequent filtrations. The pipeline was tested on Arabidopsis thaliana cDNA sequencing data obtained using Illumina and Oxford Nanopore Technologies platforms and three non-model plant species. The comparison of structural characteristics of the transcriptome assembly with reference Arabidopsis genome revealed the high quality of assembled transcriptome with 86.1% of Arabidopsis expressed genes assembled as a single contig. We tested the applicability of the transcriptome assembly for gene expression analysis. For both Arabidopsis and non-model species the results showed high congruence of gene expression levels and sets of differentially expressed genes between analyses based on genome and based on the transcriptome assembly. Conclusions We present Trans2express – a protocol for de novo hybrid transcriptome assembly aimed at recovering of a single transcript per gene. We expect this protocol to promote the characterization of transcriptomes and gene expression analysis in non-model plants and web-based tool to be of use to a wide range of plant biologists.

Background: As genomes of many eukaryotic species, especially plants, are large and complex, their de novo sequencing and assembly is still a difficult task despite progress in sequencing technologies. An alternative to genome assembly is the assembly of transcriptome, the set of RNA products of the expressed genes. While a bunch of de novo transcriptome assemblers exists, the challenges of transcriptomes (the existence of isoforms, the uneven expression levels across genes) complicates the generation of high-quality assemblies suitable for downstream analyses. Results: We developed Trans2express – a web-based tool and a pipeline of de novo hybrid transcriptome assembly and postprocessing based on rnaSPAdes with a set of subsequent filtrations. The pipeline was tested on Arabidopsis thaliana cDNA sequencing data obtained using Illumina and Oxford Nanopore Technologies platforms and three non-model plant species. The comparison of structural characteristics of the transcriptome assembly with reference Arabidopsis genome revealed the high quality of assembled transcriptome with 86.1% of Arabidopsis expressed genes assembled as a single contig. We tested the applicability of the transcriptome assembly for gene expression analysis. For both Arabidopsis and non-model species the results showed high congruence of gene expression levels and sets of differentially expressed genes between analyses based on genome and based on the transcriptome assembly. Conclusions: We present Trans2express – a protocol for de novo hybrid transcriptome assembly aimed at recovering of a single transcript per gene. We expect this protocol to promote the characterization of transcriptomes and gene expression analysis in non-model plants and web-based tool to be of use to a wide range of plant biologists. [ABSTRACT FROM AUTHOR]

Introduction: Pulsed Field Ablation (PFA) is a novel non-thermal method for cardiac ablation, relying on irreversible electroporation induced by high-energy pulsed electric fields (PEFs) to create localized lesions in the heart atria. A significant challenge in optimizing PFA treatments is determining the lethal electric field threshold (EFT), which governs ablation volume and varies with PEF waveform parameters. However, the proprietary nature of device developer’s waveform characteristics and the lack of standardized nonclinical testing methods have left optimal EFTs for cardiac ablation uncertain. Methods: To address this gap, we introduced a laboratory protocol employing human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) in monolayer format to evaluate the impact of a range of clinically relevant biphasic pulse parameters on lethal EFT and adiabatic heating (AH). Cell death areas were assessed using fluorescent dyes and confocal microscopy, while lethal EFTs were quantified through comparison with electric field numerical simulations. Results and conclusion: Our study confirmed a strong correlation between cell death in hiPSC-CMs and the number and duration of pulses in each train, with pulse repetition frequency exerting a comparatively weaker influence. Fitting of these results through machine learning algorithms were used to develop an open-source online calculator. By estimating lethal EFT and associated temperature increases for diverse pulse parameter combinations, this tool, once validated, has the potential to significantly reduce reliance on animal models during early-stage device de-risking and performance assessment. This tool also offers a promising avenue for advancing PFA technology for cardiac ablation medical devices to enhance patient outcomes. [ABSTRACT FROM AUTHOR]

In recent decades, climate change has demanded more and more attention. Consumers have the power to influence the carbon footprint of goods and services through their purchasing decisions, but to do this they need to learn more. To address this need, it is necessary to develop online questionnaires able to make people aware of which activities have a greater environmental impact in their daily lives. Focusing on this goal, we formulated two tools for quantifying an individual's carbon footprint over a year. The innovativeness of these tools lies in being user-friendly and providing online open access to compilers, as well as using specific emission factors for the reference context. Specifically, we focused on the main emission sources: gas and electricity consumption, mobility, food, and waste. During these last years, the tools have been proposed to Italian students at different levels of education and to employees of Italian and international companies. The responses from 3260 users revealed an average annual direct carbon footprint per capita of about 5600 kg CO2-eq, which, integrated with the estimate of indirect emissions, provides an estimate in good agreement with the value provided by the Italian National Inventory of greenhouse gases. With the developed tools, people are able to observe which sectors have the greatest impact and consequently are stimulated to emit less by adopting more sustainable behaviors. [ABSTRACT FROM AUTHOR]

Abstract Freshwater ecosystems are complex, diverse, and face multiple imminent threats that have led to changes in both structure and function. It is urgent that we develop and standardize monitoring tools that allow for rapid and comprehensive assessment of freshwater communities to understand their changing dynamics and inform conservation. Environmental DNA surveys offer a means to inventory and monitor aquatic diversity, yet most studies focus on one or a few taxonomic groups because of technical challenges. In this study, we (1) create an eDNA metabarcoding dataset (natural water bodies) with 14 validated primer pairs; (2) create a free online, user‐friendly tool for primer selection that can be used for any metabarcoding data (SNIPe); and (3) using SNIPe, explore our dataset to derive subsets of informative, cost‐effective primer pairs that maximize detection of freshwater diversity. We first evaluated the completeness of public reference sequence databases and the efficiency of 14 primer pairs in silico, in vitro on five mock communities (mix of DNA from tissues of select taxa), in vivo on water samples from aquarium samples with known taxonomic composition, and finally in vivo on water samples from freshwater systems in Eastern Canada. Results from analyses using SNIPe revealed that 13 or 14 primer pairs are necessary to recover 100% of the species in water samples (natural systems), but that four primer pairs are sufficient to recover almost 75% of taxa with little overlap. Our work highlights the power of eDNA metabarcoding for reconstructing freshwater communities, including prey, parasite, pathogen, invasive, and declining species. It also emphasizes the importance of marker choice on species resolution, and primer characteristics and filtering parameters on detection success and accuracy of biodiversity estimates. Together, these results highlight the usefulness of eDNA for freshwater monitoring and should prompt more studies of tools to survey all communities.

Thanks to medical successes and new treatment options, children and adolescents with rare diseases can now attend school more often playing an important role in their recovery as well as improving their social inclusion. For this reason, it is important for teachers to address the issue and acquire skills in dealing with rare diseases. In this context, a multi-professional team at the Salzburg University of Teacher Education organized a blended learning seminar on the topic of rare diseases at schools. Participants were provided with videos, texts, and case studies on a learning platform, which were worked on over a period of three weeks. There were also two online lectures in which questions could be asked. In order to evaluate the tool, 21 participants took part in a quantitative longitudinal study by means of a pretest and a posttest with a four-month interval. The participants completed a questionnaire consisting of a competence screening dealing with rare diseases together with questions to measure general and teacher self-efficacy. As expected, there was a statistically significant increase in both general and teacher self-efficacy with medium effect sizes. In addition, the theoretical and practical skills for supporting affected students at school were also shown to improve in a self-assessment. In view of the positive response from participants, it is recommended to further expand this offering in order to reach a broader population of teachers. In other words, only through raising awareness and increasing the competence of professionals working in schools can an environment be created for affected children and adolescents in which their specific needs are addressed. [ABSTRACT FROM AUTHOR]

Thanks to medical successes and new treatment options, children and adolescents with rare diseases can now attend school more often playing an important role in their recovery as well as improving their social inclusion. For this reason, it is important for teachers to address the issue and acquire skills in dealing with rare diseases. In this context, a multi-professional team at the Salzburg University of Teacher Education organized a blended learning seminar on the topic of rare diseases at schools. Participants were provided with videos, texts, and case studies on a learning platform, which were worked on over a period of three weeks. There were also two online lectures in which questions could be asked. In order to evaluate the tool, 21 participants took part in a quantitative longitudinal study by means of a pretest and a posttest with a four-month interval. The participants completed a questionnaire consisting of a competence screening dealing with rare diseases together with questions to measure general and teacher self-efficacy. As expected, there was a statistically significant increase in both general and teacher self-efficacy with medium effect sizes. In addition, the theoretical and practical skills for supporting affected students at school were also shown to improve in a self-assessment. In view of the positive response from participants, it is recommended to further expand this offering in order to reach a broader population of teachers. In other words, only through raising awareness and increasing the competence of professionals working in schools can an environment be created for affected children and adolescents in which their specific needs are addressed.

Businesses willing to reduce their carbon footprint embrace sustainability and positively impact the progress towards achieving climate neutrality. Well-prepared and presented information to the business customer before purchasing can be a strong driver for better decision-making towards less impactful product alternatives. This study presents the development of a tool for packaging products online marketplace that informs customers about the carbon footprint of packaging products and allows them to evaluate which of the select packaging alternatives is most preferable from an environmental perspective. The tool implements a life cycle analysis (LCA) approach, including the stages of raw material extraction, packaging production, and transportation to the customer. The impact assessment in the tool is performed according to Intergovernmental Panel on Climate Change (IPCC) 2021 methodology for assessing greenhouse gas (GHG) emissions based on information obtained from the Ecoinvent database. The final output of carbon footprint calculation is provided with an indicator marking the carbon footprint performance of customer-defined alternatives in a clear, simple, and consistent way. The tool aims to educate customers, foster informed purchasing decisions, and improve the environmental outcomes of their decisions.

Purpose: Extrapulmonary small cell carcinoma (EPSCC) is rare, and its knowledge is mainly extrapolated from small cell lung carcinoma. Reliable survival prediction tools are lacking. Methods: A total of 3,921 cases of EPSCC were collected from the Surveillance Epidemiology and End Results (SEER) database, which form the training and internal validation cohorts of the survival prediction model. The endpoint was an overall survival of 0.5-5 years. Internal validation performances of machine learning algorithms were compared, and the best model was selected. External validation (n = 68) was performed to evaluate the generalization ability of the selected model. Results: Among machine learning algorithms, the random forest model performs best on internal validation, whose area under the curve (AUC) is 0.736-0.800. The net benefit is higher than the TNM classification in decision curve analysis. The AUC of this model on the external validation cohort is 0.739-0.811. This model was then deployed online as a free, publicly available prediction tool of EPSCC (http://42.192.80.13:4399/). Conclusion: This study provides an excellent online survival prediction tool for EPSCC with machine learning and large-scale data. Age, TNM stages, and surgery (including potential performance status information) are the most critical factors for the prediction model. [ABSTRACT FROM AUTHOR]

Abstract Background The alertness and practice of health care providers (HCPs) in the correct management of suspected malaria (CMSM) (vigilance) is a central component of malaria surveillance following elimination, and it must be established before malaria elimination certification can be granted. This study was designed to develop and validate a rapid tool, Simulated Malaria Online Tool (SMOT), to evaluate HCPs’ practice in relation to the CMSM. Methods The study was conducted in East Azerbaijan Province, Islamic Republic of Iran, where no malaria transmission has been reported since 2005. An online tool presenting a suspected malaria case for detection of HCPs’ failures in recognition, diagnosis, treatment and reporting was developed based on literature review and expert opinion. A total of 360 HCPs were allocated to two groups. In one group their performance was tested by simulated patient (SP) methodology as gold standard, and one month later by the online tool to allow assessment of its sensitivity. In the other group, they were tested only by the online tool to allow assessment of any possible bias incurred by the exposure to SPs before the tool. Results The sensitivity of the tool was (98.7%; CI 93.6–99.3). The overall agreement and kappa statistics were 96.6% and 85.6%, respectively. In the group tested by both methods, the failure proportion by SP was 86.1% (CI 80.1–90.8) and by tool 87.2% (CI 81.4–91.7). In the other group, the tool found 85.6% (CI 79.5–90.3) failures. There were no significant differences in detecting failures within or between the groups. Conclusion The SMOT tool not only showed high validity for detecting HCPs’ failures in relation to CMSM, but it had high rates of agreement with the real-world situation, where malaria transmission has been interrupted. The tool can be used by program managers to evaluate HCPs’ performance and identify sub-groups, whose malaria vigilance should be strengthened. It could also contribute to the evidence base for certification of malaria elimination, and to strengthening prevention of re-establishment of malaria transmission.

Abstract Background Dizziness and vertigo affect around 15% of adults annually and represent common reasons for contacting health services, accounting for around 3% of all emergency department visits worldwide. Vertigo is also associated with excessive use of diagnostic imaging and emergency care and decreased productivity, primarily because of work absenteeism. Vestibular rehabilitation is an evidence-based treatment for chronic dizziness and supervised group exercise therapy has recently been shown to be effective after vestibular neuritis, a common cause of acute onset vertigo. However, such interventions are not readily available and there is a need for more easily accessible tools. The purpose of this study is to investigate the effects on vestibular symptoms of a 6-week online vestibular rehabilitation tool after acute onset vertigo, with the aim of aiding vestibular rehabilitation by presenting a more accessible tool that can help to reduce recovery time. Methods Three hundred twenty individuals diagnosed with acute vestibular syndrome (AVS) will be recruited from multiple hospitals in Sweden and the effects of an online vestibular rehabilitation tool, YrselTräning, on vestibular symptoms after acute onset vertigo will be compared to standard care (written instructions leaflet) in a two-armed, evaluator-blinded, multicenter randomized controlled trial. The primary outcome will be the Vertigo Symptom Scale Short Form (VSS-SF) score at 6 weeks after symptom onset. Secondary outcomes include effects of the intervention on activities of daily living, mood and anxiety, vestibular function recovery, mobility measures, health economic effects, and the reliability of the Swedish VSS-SF translation. Discussion Participants using the online vestibular rehabilitation tool are expected to recover earlier and to a greater extent from their symptoms as compared to standard care. Since up to 50% of people with AVS without treatment develop persistent symptoms, effective treatment of AVS will likely lead to a higher quality of life and help reduce the societal costs associated with dizziness and vertigo. Trial registration Clinicaltrials.gov NCT05056324 . Registered on September 24, 2021.

This study presents a web-based sentence comprehension test aimed at identifying high school students who are at risk for a language delay. By assessing linguistic skills on a sample of high school students with Italian as an L2 and their monolingual peers, attending a vocational school, we were able to identify a subgroup of L2 students with consistent difficulties in sentence comprehension, though their reading skills were within the average range. The same subgroup revealed to experience a lack of support within the school context, suggesting that poor L2 skills might be a critical variable to consider in order to identify students at risk for school exclusion. Regarding the test, accuracy to the on-line sentence comprehension task was significantly predicted by reading abilities and vocabulary skills, thus indicating that this test might represent a rapid but efficient way to assess linguistic abilities at school. We recommend that establishing a valid and practical procedure for the evaluation of linguistic skills in bilingual students who struggle with their L2 is the first step toward promoting social inclusion in the multilingual classroom, in order to increase their ability to actively participate in school and social activities.

In the search for solutions for Integrated Water Resources Management (IWRM), decision-makers frequently face governance-related challenges such as the fragmentation of institutions, the interconnection with other essential services and overlapping competences. In many cases, solutions to these challenges involve strengthening coordination between different actors and sectors. Today different digital tools and resources are available to support related decision-making processes. These tools can (1) offer a context-specific assessment of the water governance system ("Diagnosis") and (2) provide, in some cases, context-specific recommendations to tackle identified deficits ("Therapy"). In this paper, we aim to advance the understanding of the potential of digital tools for water governance and management assessments. After reviewing relevant tools, we introduce the Diagnostic Water Governance Tool (DWGT) that builds on a clear diagnosis-therapy-logic. After presenting the empirical basis and functional logic of the DWGT, we test the DWGT in two case studies: the Guadalquivir river basin in Spain and the Emscher river basin in Germany. We find that the DWGT provides context-specific, evidence-based instrument recommendations that can enhance water governance and management, albeit accompanying suitability evaluations by governance experts remain critical. We conclude by discussing the limitations of digital tools for water governance and management assessments and sketch out fields of future research. • Most water governance online tools do not allow for case-specific assessments. • Diagnostic Water Governance Tool identifies context-specific coordination deficits. • The Tool gives case-sensitive recommendations for governance instruments. • Fuzzy set Qualitative Comparative Analysis provides sound methodological framework. • The Tool's analysis can supplement but not replace expert evaluations. [ABSTRACT FROM AUTHOR]

In courses in Computing, Digital Technology and related areas, Computer Programming and Algorithms are initial subjects with a high failure rate. Remote teaching adopted as a result of the COVID-19 pandemic has brought new barriers, including the need for online tools. This work aims to identify, test and analyze free online platforms and tools that can help to overcome the adversities faced in Programming and Algorithms disciplines in the context of remote teaching. The methodology adopted was a quantitative study, in which a set of online tools was initially identified, which later had their usability level measured through questionnaires submitted to a group of students from the Technical Course in Computer Science for the Internet. The results identified that, among the analyzed tools, all have a range of positive and negative points, but only one of them presented a greater number of potentialities that facilitate the teaching-learning process in the context of remote teaching. At the end of the research, it was found that there is a wide variety of online tools that can help in the teaching of Programming and Algorithms, however, there are few tools with characteristics that meet all the needs in the context of remote teaching. [ABSTRACT FROM AUTHOR]

CRISPR-based genome-editing tools have emerged as an efficient tool for functional genomics studies. Online tools and databases have been developed to facilitate the design and selection of CRISPR single guide RNA (sgRNA) for gene modifications. However, to the best of our knowledge, none of these tools or database are designated to cell surface proteins. In a previous study, we described the development and application of surfaceome CRISPR libraries targeting to cell surface proteins on human cells. Here, we present the design and construction of an online tool and database (https://crispr-surfaceome.siais.shanghaitech.edu.cn/home), named CRISPR-Surfaceome, for the design of highly efficient sgRNA targeting to the surface proteins on human cells. To show case and validate the efficiencies of sgRNAs designed by this online tool, we chose ICAM-1 gene for knockout studies and found that all the 10 designed ICAM-1 sgRNAs could efficiently generate knockout cells, with more than 80% gene disruption rates. These ICAM-1 knockout cells were found to be resistant to the infection of rhinovirus (RV), which utilizes ICAM-1 as the receptor. Therefore, CRISPR-Surfaceome can serve the research community for the functional genomics studies on cell surface proteins, such as identification of pathogen receptors and discovery of drug targets.

Computer science students often evaluate the behavior of the code they write by running it on specific inputs and studying the outputs, and then apply their comprehension to a more general understanding of the code. While this is a good starting point in the student’s career, successful graduates must be able to reason analytically about the code they create or encounter. They must be able to reason about the behavior of the code on arbitrary inputs, without running the code. Abstraction is central for such reasoning. In our quest to help students learn to reason abstractly and develop logically correct code, we have developed tools that rely on a verification engine. Code involves assignment, conditional, and loop statements, along with objects and operations. Reasoning activities involve symbolic reasoning with simple assertions and design-by-contract assertions such as pre-and post-conditions as well as loop invariants with data abstractions. Students progress from tracing and reading code to the design and implementation of code, all relying on abstraction for verification. This paper reports some key results and findings from associated studies spanning several years.

Abstract Genetic map is a linear arrangement of the relative positions of sites in the chromosome or genome based on the recombination frequency between genetic markers. It is the important basis for genetic analysis. Several kinds of software have been designed for genetic mapping, but all these tools require users to write or edit code, making it time-costing and difficult for researchers without programming skills to handle with. Here, MG2C, a new online tool was designed, based on PERL and SVG languages. Users can get a standard genetic map, only by providing the location of genes (or quantitative trait loci) and the length of the chromosome, without writing additional code. The operation interface of MG2C contains three sections: data input, data output and parameters. There are 33 attribute parameters in MG2C, which are further divided into 8 modules. Values of the parameters can be changed according to the users’ requirements. The information submitted by users will be transformed into the genetic map in SVG file, which can be further modified by other image processing tools. MG2C is a user-friendly and time-saving online tool for drawing genetic maps, especially for those without programming skills. The tool has been running smoothly since 2015, and updated to version 2.1. It significantly lowers the technical barriers for the users, and provides great convenience for the researchers.

Background: The alertness and practice of health care providers (HCPs) in the correct management of suspected malaria (CMSM) (vigilance) is a central component of malaria surveillance following elimination, and it must be established before malaria elimination certification can be granted. This study was designed to develop and validate a rapid tool, Simulated Malaria Online Tool (SMOT), to evaluate HCPs' practice in relation to the CMSM. Methods: The study was conducted in East Azerbaijan Province, Islamic Republic of Iran, where no malaria transmission has been reported since 2005. An online tool presenting a suspected malaria case for detection of HCPs' failures in recognition, diagnosis, treatment and reporting was developed based on literature review and expert opinion. A total of 360 HCPs were allocated to two groups. In one group their performance was tested by simulated patient (SP) methodology as gold standard, and one month later by the online tool to allow assessment of its sensitivity. In the other group, they were tested only by the online tool to allow assessment of any possible bias incurred by the exposure to SPs before the tool. Results: The sensitivity of the tool was (98.7%; CI 93.6–99.3). The overall agreement and kappa statistics were 96.6% and 85.6%, respectively. In the group tested by both methods, the failure proportion by SP was 86.1% (CI 80.1–90.8) and by tool 87.2% (CI 81.4–91.7). In the other group, the tool found 85.6% (CI 79.5–90.3) failures. There were no significant differences in detecting failures within or between the groups. Conclusion: The SMOT tool not only showed high validity for detecting HCPs' failures in relation to CMSM, but it had high rates of agreement with the real-world situation, where malaria transmission has been interrupted. The tool can be used by program managers to evaluate HCPs' performance and identify sub-groups, whose malaria vigilance should be strengthened. It could also contribute to the evidence base for certification of malaria elimination, and to strengthening prevention of re-establishment of malaria transmission. [ABSTRACT FROM AUTHOR]

Power calculation is a necessary step when planning genome-wide association studies (GWAS) to ensure meaningful findings. Statistical power of GWAS depends on the genetic architecture of phenotype, sample size, and study design. While several computer programs have been developed to perform power calculation for single SNP association testing, it might be more appropriate for GWAS power calculation to address the probability of detecting any number of associated SNPs. In this paper, we derive the statistical power distribution across causal SNPs under the assumption of a point-normal effect size distribution. We demonstrate how key outcome indices of GWAS are related to the genetic architecture (heritability and polygenicity) of the phenotype through the power distribution. We also provide a fast, flexible and interactive power calculation tool which generates predictions for key GWAS outcomes including the number of independent significant SNPs, the phenotypic variance explained by these SNPs, and the predictive accuracy of resulting polygenic scores. These results could also be used to explore the future behaviour of GWAS as sample sizes increase further. Moreover, we present results from simulation studies to validate our derivation and evaluate the agreement between our predictions and reported GWAS results. [ABSTRACT FROM AUTHOR]

Many retrofit projects went wrong in the UK principally because of the application of inappropriate retrofit solutions, which resulted in damp issues, with some leaving houses in worse conditions than pre-retrofit. Various online tools were developed to inform homeowners about the benefits of retrofitting. Prior to this study, little was known about users' evaluation of these tools and the effects of calculator use. Furthermore, no retrofit tool aims to raise the awareness of homeowners about moisture risks in a retrofit project. The originality of this study is to develop and evaluate an online moisture-safe retrofit decision-making tool for homeowners. The adopted methodology consisted of two phases. Phase one aimed to develop the tool. In phase two, semi-structured interviews were conducted to evaluate the tool. The results indicate that the tool has been well received by homeowners. The tool significantly increased participants' awareness of moisture risks related to a retrofit project. Most participants considered the tool an eye-opener, while few of them found it scary. However, the tool did not result in an increased willingness to invest in energy efficiency measures. The discouragement was related to high investment costs and long payback periods of some retrofit measures. Based on our findings, we formulate a set of design recommendations to improve the proposed tool and help retrofit calculators, in general, overcome challenges. [ABSTRACT FROM AUTHOR]

This cross-sectional study aims to explore the prevalence of protein-energy wasting (PEW) in dialysis patients in Catalonia, Spain, using a new and practical online tool which enables rapid calculation and comparison with other nutritional scores. Methods: A web tool (Nutrendial) was created to introduce different variables and automatically calculate PEW, Malnutrition inflammation Score (MIS) and Subjective Global Assessment (SGA) in 1389 patients (88% in haemodialysis (HD)), 12% in peritoneal dialysis (PD) from different regions of Catalonia. Results: A prevalence of 23.3% (26% HD, 10.2% PD) of PEW was found, with a mean MIS score of 6 and SGA score of C in 7% of the patients. ROC analysis showed MIS as the best nutritional score to diagnose PEW (AUC 0.85). Albumin delivered lower diagnostic precision (AUC 0.77) and sensitivity (66%). A cut off point of 7 (86% sensitivity and 75% specificity) for MIS and 3.7 mg/dL for albumin were found to predict the appearance of PEW in this population. SGA B or C showed an 87% sensitivity and 55% specificity to diagnose PEW. Very low nutritional intervention (14%) was recorded with this tool in patients with PEW. Conclusions: This new online tool facilitated the calculation of PEW, enabling different professionals—including nephrologists, dieticians and nurses—to efficiently obtain insights into the nutritional status of the Catalonian dialysis population and implement the required nutritional interventions. MIS is the score with more sensitivity to diagnose PEW. [ABSTRACT FROM AUTHOR]

Purpose: To establish a more convenient ovarian reserve model with anti-Müllerian hormone (AMH) level and age (the AA model), with blood samples taken at any time in the menstrual cycle. Methods: We have established this AA model for predicting ovarian reserve using the AMH level and age. The outcome variable was defined as poor ovarian response (POR) with <5 oocytes retrieved during assisted reproductive technology treatment cycles. Least Absolute Shrinkage and Selection Operator logistic regression with 5-fold cross validation methods was applied to construct the model, and that with the lowest scaled log-likelihood was selected as the final one. Results: The areas under the receiver operating characteristic curve for the training, inner, and external validation sets were 0.862, 0.843, and 0.854 respectively. The main effects of AMH level and age contributing to the prediction of POR were 95.3% and 1.8%, respectively. The incidences of POR increased with its predicted probability in both the model building and in external validation datasets, indicating its stability. An online website-based tool for assessing the score of ovarian reserve (http://121.43.113.123:9999) has been developed. Conclusions: Based on external validation data, the AA model performed well in predicting POR, and was more cost-effective and convenient than our previous published models. [ABSTRACT FROM AUTHOR]

Background: Dizziness and vertigo affect around 15% of adults annually and represent common reasons for contacting health services, accounting for around 3% of all emergency department visits worldwide. Vertigo is also associated with excessive use of diagnostic imaging and emergency care and decreased productivity, primarily because of work absenteeism. Vestibular rehabilitation is an evidence-based treatment for chronic dizziness and supervised group exercise therapy has recently been shown to be effective after vestibular neuritis, a common cause of acute onset vertigo. However, such interventions are not readily available and there is a need for more easily accessible tools. The purpose of this study is to investigate the effects on vestibular symptoms of a 6-week online vestibular rehabilitation tool after acute onset vertigo, with the aim of aiding vestibular rehabilitation by presenting a more accessible tool that can help to reduce recovery time.Methods: Three hundred twenty individuals diagnosed with acute vestibular syndrome (AVS) will be recruited from multiple hospitals in Sweden and the effects of an online vestibular rehabilitation tool, YrselTräning, on vestibular symptoms after acute onset vertigo will be compared to standard care (written instructions leaflet) in a two-armed, evaluator-blinded, multicenter randomized controlled trial. The primary outcome will be the Vertigo Symptom Scale Short Form (VSS-SF) score at 6 weeks after symptom onset. Secondary outcomes include effects of the intervention on activities of daily living, mood and anxiety, vestibular function recovery, mobility measures, health economic effects, and the reliability of the Swedish VSS-SF translation.Discussion: Participants using the online vestibular rehabilitation tool are expected to recover earlier and to a greater extent from their symptoms as compared to standard care. Since up to 50% of people with AVS without treatment develop persistent symptoms, effective treatment of AVS will likely lead to a higher quality of life and help reduce the societal costs associated with dizziness and vertigo.Trial Registration: Clinicaltrials.gov NCT05056324 . Registered on September 24, 2021. [ABSTRACT FROM AUTHOR]

Background: Predicting the number of oocytes retrieved (NOR) following controlled ovarian stimulation (COS) is the only way to ensure effective and safe treatment in assisted reproductive technology (ART). To date, there have been limited studies about predicting specific NOR, which hinders the development of individualized treatment in ART. Objective: To establish an online tool for predicting NOR. Materials and Methods: In total, 621 prospective routine gonadotropin releasing hormone (GnRH) antagonist COS cycles were studied. Independent variables included age, body mass index, antral follicle counts, basal FSH, basal and increment of anti-mullerian hormone, Luteinizing hormon, estradiol, testosterone, androstenedione, and inhibin B. The outcome variable was NOR. The independent variables underwent appropriate transformation to achieve a better fit for a linear relationship with NOR. Pruned forward selection with holdback validation was then used to establish predictive models. Corrected Akaike's information criterion, Schwarz–Bayesian information criterion, scaled – log [likelihood], and the generalized coefficient of determination (R 2) were used for model evaluation. Results: A multiple negative binomial regression model was used for predicting NOR because it fitted a negative binomial distribution. We established Model 1, using basal ovarian reserve markers, and Model 2, using both basal and early dynamic markers for predicting NOR following COS. The generalized R 2 values were 0.54 and 0.51 for Model 1 and 0.64 and 0.62 for Model 2 in the training and validation sets, respectively. Conclusion: Models 1 and 2 could be applied to different scenarios. For directing the starting dose of recombinant follicle stimulation hormone (rFSH), Model 1 using basic predictors could be used prior to COS. Model 2 could be used for directing the adjustment of rFSH dosages during COS. An online tool (http://121.43.113.123:8002/) based on these two models is also developed. We anticipate that the clinical application of this tool could help the ART clinics to reduce iatrogenic ovarian under- or over-responses, and could reduce costs during COS for ART. [ABSTRACT FROM AUTHOR]

Abstract Background Most cost-effectiveness analyses in the context of cervical cancer prevention involve the use of mathematical models to simulate HPV infection, cervical disease and prevention strategies. However, it is common for professionals who would need to perform these analyses to not be familiar with the models. This work introduces the Online Cost-Effectiveness ANalysis tool, featuring an easy-to-use web interface providing health professionals, researchers and decision makers involved in cervical cancer prevention programmes with a useful instrument to conduct complex cost-effectiveness analyses, which are becoming an essential tool as an approach for supporting decision-making that involves important trade-offs. Results The users can run cost-effectiveness evaluations of cervical cancer prevention strategies without deep knowledge of the underlying mathematical model or any programming language, obtaining the most relevant costs and health outcomes in a user-friendly format. The results provided by the tool are consistent with the existing literature. Conclusions Having such a tool will be an asset to the cervical cancer prevention community, providing researchers with an easy-to-use instrument to conduct cost-effectiveness analyses.

Summary: Background: Virtually few accurate and robust prediction models of lower-grade gliomas (LGG) survival exist that may aid physicians in making clinical decisions. We aimed to develop a prognostic prediction model of LGG by incorporating demographic, clinical and transcriptional biomarkers with either main effects or gene-gene interactions. Methods: Based on gene expression profiles of 1,420 LGG patients from six independent cohorts comprising both European and Asian populations, we proposed a 3-D analysis strategy to develop and validate an Accurate Prediction mOdel of Lower-grade gLiomas Overall survival (APOLLO). We further conducted decision curve analysis to assess the net benefit (NB) of identifying true positives and the net reduction (NR) of unnecessary interventions. Finally, we compared the performance of APOLLO and the existing prediction models by the first systematic review. Findings: APOLLO possessed an excellent discriminative ability to identify patients at high mortality risk. Compared to those with less than the 20th percentile of APOLLO risk score, patients with more than the 90th percentile of APOLLO risk score had significantly worse overall survival (HR=54·18, 95% CI: 34·73-84·52, P=2·66 × 10−69). Further, APOLLO can accurately predict both 36- and 60-month survival in six independent cohorts with a pooled AUC36-month=0·901 (95% CI: 0·879-0·923), AUC60-month=0·843 (95% CI: 0·815-0·871) and C-index=0·818 (95% CI: 0·800-0·835). Moreover, APOLLO offered an effective screening strategy for detecting LGG patients susceptible to death (NB36-month=0·166, NR36-month=40·1% and NB60-month=0·258, NR60-month=19·2%). The systematic comparisons revealed APOLLO outperformed the existing models in accuracy and robustness. Interpretation: APOLLO has the demonstrated feasibility and utility of predicting LGG survival (http://bigdata.njmu.edu.cn/APOLLO). Funding: National Key Research and Development Program of China (2016YFE0204900); Natural Science Foundation of Jiangsu Province (BK20191354); National Natural Science Foundation of China (81973142 and 82103946); China Postdoctoral Science Foundation (2020M681671); National Institutes of Health (CA209414, CA249096, CA092824 and ES000002).

BackgroundPredicting the number of oocytes retrieved (NOR) following controlled ovarian stimulation (COS) is the only way to ensure effective and safe treatment in assisted reproductive technology (ART). To date, there have been limited studies about predicting specific NOR, which hinders the development of individualized treatment in ART.ObjectiveTo establish an online tool for predicting NOR.Materials and MethodsIn total, 621 prospective routine gonadotropin releasing hormone (GnRH) antagonist COS cycles were studied. Independent variables included age, body mass index, antral follicle counts, basal FSH, basal and increment of anti-mullerian hormone, Luteinizing hormon, estradiol, testosterone, androstenedione, and inhibin B. The outcome variable was NOR. The independent variables underwent appropriate transformation to achieve a better fit for a linear relationship with NOR. Pruned forward selection with holdback validation was then used to establish predictive models. Corrected Akaike’s information criterion, Schwarz–Bayesian information criterion, scaled –log[likelihood], and the generalized coefficient of determination (R2) were used for model evaluation.ResultsA multiple negative binomial regression model was used for predicting NOR because it fitted a negative binomial distribution. We established Model 1, using basal ovarian reserve markers, and Model 2, using both basal and early dynamic markers for predicting NOR following COS. The generalized R2 values were 0.54 and 0.51 for Model 1 and 0.64 and 0.62 for Model 2 in the training and validation sets, respectively.ConclusionModels 1 and 2 could be applied to different scenarios. For directing the starting dose of recombinant follicle stimulation hormone (rFSH), Model 1 using basic predictors could be used prior to COS. Model 2 could be used for directing the adjustment of rFSH dosages during COS. An online tool (http://121.43.113.123:8002/) based on these two models is also developed. We anticipate that the clinical application of this tool could help the ART clinics to reduce iatrogenic ovarian under- or over-responses, and could reduce costs during COS for ART.

Practicum is an essential and meaningful part of teacher education but due to the great diversity of educational programmes worldwide, their nature and quality depend too much on each particular situation. There is an urgent need to unify and upgrade practicum formats. This paper reports a proposal for technology enhancement and structure reconfiguration of the practicum within the wider curricula. Added to that, we present an Interactive Digital Notepad (IDN) prototype, based on Kanban and powered up by Trello, as an optimal solution to the challenges posed in practicum management in foreign language teacher education programmes. Circumscribed to the Spanish educational context, this IDN is an online tool designed to improve the monitoring of the learning process in order to foster interactive and effective communication among the participants, and to promote critical thinking and autonomy. Results are promising and further steps for further improvement and implementation are outlined.

Computer science students often evaluate the behavior of the code they write by running it on specific inputs and studying the outputs, and then apply their comprehension to a more general understanding of the code. While this is a good starting point in the student's career, successful graduates must be able to reason analytically about the code they create or encounter. They must be able to reason about the behavior of the code on arbitrary inputs, without running the code. Abstraction is central for such reasoning. In our quest to help students learn to reason abstractly and develop logically correct code, we have developed tools that rely on a verification engine. Code involves assignment, conditional, and loop statements, along with objects and operations. Reasoning activities involve symbolic reasoning with simple assertions and design-by-contract assertions such as pre-and post-conditions as well as loop invariants with data abstractions. Students progress from tracing and reading code to the design and implementation of code, all relying on abstraction for verification. This paper reports some key results and findings from associated studies spanning several years. [ABSTRACT FROM AUTHOR]

COVID-19 gives a drastic change in our lifestyle. In education, it effects on motivation, routine and the dilemma in using certain application. The university has taken various proactive measures for ensuring the productivity of their stakeholders. Students and instructors are changing their teaching and learning style which this impact on learning technology usage while having online class. This paper shares COVID-19 story in terms of learning system development online which is challenging for learners and instructors. They need to adjust themselves so that the message is conveyed, and problem is solved during the online class. This paper looks at how the learners and instructors manage their online class by using an online prototype tool, Justinmind, for assisting them to learn system development during COVID-19. The learners have been asked to plan, gather, and design the user interface according to the requirements stated previously. This study found out that there are some difficulties in conducting system development class in online mode since there is a change of routine as well as teaching and learning style. However, the difficulties have been addressed by the utilization of the technology and thus creating more exciting journey for the class regardless of the pandemic era.

Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 severe acute respiratory syndrome coronavirus 2 positive cases and 564 controls, accounting for the time course of illness using generalised multivariate logistic regression. Significant symptoms included abdominal pain, cough, diarrhoea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5 and 37.9 °C and temperature above 38 °C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, leave-one-out cross-validation confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. External validation datasets reported similar result. Our study provides a tool to discern COVID-19 patients from controls using symptoms and day from illness onset with good predictive performance. It could be considered as a framework to complement laboratory testing in order to differentiate COVID-19 from other patients presenting with acute symptoms in outpatient care. [ABSTRACT FROM AUTHOR]

Abstract Background High-throughput technologies have brought tremendous changes to biological domains, and the resulting high-dimensional data has also posed enormous challenges to computational science. A Bayesian network is a probabilistic graphical model represented by a directed acyclic graph, which provides concise semantics to describe the relationship between entities and has an independence assumption that is suitable for sparse omics data. Bayesian networks have been broadly used in biomedical research fields, including disease risk assessment and prognostic prediction. However, the inference and visualization of Bayesian networks are unfriendly to the users lacking programming skills. Results We developed an R/Shiny application, shinyBN, which is an online graphical user interface to facilitate the inference and visualization of Bayesian networks. shinyBN supports multiple types of input and provides flexible settings for network rendering and inference. For output, users can download network plots, prediction results and external validation results in publication-ready high-resolution figures. Conclusion Our user-friendly application (shinyBN) provides users with an easy method for Bayesian network modeling, inference and visualization via mouse clicks. shinyBN can be used in the R environment or online and is compatible with three major operating systems, including Windows, Linux and Mac OS. shinyBN is deployed at https://jiajin.shinyapps.io/shinyBN/. Source codes and the manual are freely available at https://github.com/JiajinChen/shinyBN.

Many retrofit projects went wrong in the UK principally because of the application of inappropriate retrofit solutions, which resulted in damp issues, with some leaving houses in worse conditions than pre-retrofit. Various online tools were developed to inform homeowners about the benefits of retrofitting. Prior to this study, little was known about users’ evaluation of these tools and the effects of calculator use. Furthermore, no retrofit tool aims to raise the awareness of homeowners about moisture risks in a retrofit project. The originality of this study is to develop and evaluate an online moisture-safe retrofit decision-making tool for homeowners. The adopted methodology consisted of two phases. Phase one aimed to develop the tool. In phase two, semi-structured interviews were conducted to evaluate the tool. The results indicate that the tool has been well received by homeowners. The tool significantly increased participants’ awareness of moisture risks related to a retrofit project. Most participants considered the tool an eye-opener, while few of them found it scary. However, the tool did not result in an increased willingness to invest in energy efficiency measures. The discouragement was related to high investment costs and long payback periods of some retrofit measures. Based on our findings, we formulate a set of design recommendations to improve the proposed tool and help retrofit calculators, in general, overcome challenges.

Early case detection and isolation of infected individuals are critical to controlling coronavirus disease 2019 (COVID-19). Reverse transcription polymerase chain reaction (RT-PCR) is considered the gold standard for the diagnosis of severe acute respiratory syndrome coronavirus 2 infection, but false negatives do occur. We built a user-friendly online tool to estimate the probability of having COVID-19 with negative RT-PCR results and thus avoid preventable transmission. [ABSTRACT FROM AUTHOR]

Despite education about the risks of excessive sun exposure, teenagers in Australia are sun-seeking, with sunburn common in summer. Conversely, some regular (time-limited) exposure to sunlight (that avoids sunburn) is necessary for vitamin D and healthy bones and other molecules important for immune and metabolic health. New interventions are thus required to better support teenagers to make healthy and balanced decisions about their sun behaviors. This paper describes the development of a prototype online tool—a smartphone app—that aimed to foster safe sun practices in teenagers. We recruited young adolescents (aged 12–13 years, n = 24) as “co-researchers” to provide ongoing input into the nature and design of the online tool. This age group was selected, as it is a critical time when young people transition from primary education, where “SunSmart” behaviors are entrenched in Australian schools, to high school, where risky behaviors emerge. Through a series of interviews and workshops, we codesigned an Apple iOS smartphone app with the co-researchers, leading health promotion professionals, researchers, and app designers. The developed app, Sun Safe, contains educational content relevant to teenagers about safe sun behaviors, complemented by other features requested by co-researchers and stakeholders to help engage young people, including gamified quizzes to test their sun health knowledge, real-time weather data on the UV Index and temperature, a sunscreen application timer, and reminders to check the UV Index. The developed prototype app was rated well by co-researchers, suggesting it is suitable for further feasibility and efficacy testing as an intervention tool to improve knowledge and promote safe sun behaviors by young adolescents.

Introduction: Total hip and total knee replacement (THR and TKR) are suggested for reducing joint pain resulting from hip and knee osteoarthritis (OA), especially when other interventions have not resulted in desired outcomes. Providing prehabilitation education can improve patients' psychological and physical well-being before and after surgery. The use of electronic health (eHealth) tools can be considered an effective method to increase patients' access to prehabilitation, particularly for those facing barriers to attending diagnosis-specific in-person education sessions. However, limited attention is paid to both caregiver and patient perspectives regarding the delivery formats, features, and characteristics of eHealth tools. Method: Patients with hip (n = 46) and knee OA (n = 14) and their family caregivers (n = 16) participated in in-person focus groups or phone interviews. Participants were shown a mock-up of an eHealth module, and asked to share their preferences regarding the formats, features, and characteristics of the eHealth prehabilitation tool. Data was transcribed verbatim and coded using primary thematic and secondary content analyses. Result: Analyses revealed 3 main themes: 1. "easier to understand" emphasizes patients' preferences on delivery formats and features; 2. "what does that mean?" highlights requests for clear and simple information; and 3. "Preparation, right?" shows patients' perspectives on the best time to have access to the eHealth tool. Discussion: Participants' preferences for prehabilitation tools included offering eHealth tools in multiple mediums of delivery (eg, written materials, pictures, videos). Participants preferred simplified information that emphasized the key points and rationale for the knowledge. There were differences in preferred timeline for having access to prehabilitation education, such as some participants wanting to receive prehabilitation well in advance, while others stated just before surgery was adequate. Our findings provide novel and actionable information about patient and caregiver perspectives on features and characteristics of prehabilitation education for patients with hip and knee OA. [ABSTRACT FROM AUTHOR]

Introduction: Breast cancer, a heterogeneous disease, is influenced by multiple genetic and epigenetic factors. The majority of prognostic models for breast cancer focus merely on the main effects of predictors, disregarding the crucial impacts of gene-gene interactions on prognosis., Objectives: Using DNA methylation data derived from nine independent breast cancer cohorts, we developed an independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions (ARTEMIS) with an innovative 3-D modeling strategy. ARTEMIS was evaluated for discrimination ability using area under the receiver operating characteristics curve (AUC), and calibration using expected and observed (E/O) ratio. Additionally, we conducted decision curve analysis to evaluate its clinical efficacy by net benefit (NB) and net reduction (NR). Furthermore, we conducted a systematic review to compare its performance with existing models., Results: ARTEMIS exhibited excellent risk stratification ability in identifying patients at high risk of mortality. Compared to those below the 25th percentile of ARTEMIS scores, patients with above the 90th percentile had significantly lower overall survival time (HR = 15.43, 95% CI: 9.57-24.88, P = 3.06 × 10 -29 ). ARTEMIS demonstrated satisfactory discrimination ability across four independent populations, with pooled AUC 3-year  = 0.844 (95% CI: 0.805-0.883), AUC 5-year  = 0.816 (95% CI: 0.775-0.857), and C-index = 0.803 (95% CI: 0.776-0.830). Meanwhile, ARTEMIS had well calibration performance with pooled E/O ratio 1.060 (95% CI: 1.038-1.083) and 1.090 (95% CI: 1.057-1.122) for 3- and 5-year survival prediction, respectively. Additionally, ARTEMIS is a clinical instrument with acceptable cost-effectiveness for detecting breast cancer patients at high risk of mortality (P t  = 0.4: NB 3-year  = 19‰, NB 5-year  = 62‰; NR 3-year  = 69.21%, NR 5-year  = 56.01%). ARTEMIS has superior performance compared to existing models in terms of accuracy, extrapolation, and sample size, as indicated by the systematic review. ARTEMIS is implemented as an interactive online tool available at http://bigdata.njmu.edu.cn/ARTEMIS/., Conclusion: ARTEMIS is an efficient and practical tool for breast cancer prognostic prediction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Production and hosting by Elsevier B.V.)

Objective: To develop, assess, and refine an online educational tool, Plan for Clarity, to support financial and legal planning in dementia., Methods: A Delphi mixed-method study with three rounds of anonymous review by lay and professional stakeholders was designed to reach consensus about the content of the online tool and explore the socio-cultural and behavioral factors that could affect access and use., Results: Consensus showed that the online tool covered key information, knowledge, and communication skills for financial and legal planning. Study themes: 1) the online tool had to be easy to navigate with relevant, easily understood information; 2) people with early signs of memory difficulties would be able to use the tool; 3) a referral from a trusted source is a primary way to facilitate access and use of the tool; and 4) discussions about financial and legal issues should be held early, ahead of barriers that can block discussion., Conclusion: These data suggest this online tool is relevant and feasible for dementia care and support as well as aging more generally., Innovation: Plan for Clarity is innovative as an evidence and theory-driven online education tool to address financial and legal planning for dementia care, particularly among underserved older adults., Competing Interests: All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background Understanding and addressing the needs of frail patients has been identified as an important strategy by the Nova Scotia Health Authority (NSHA). Primary care (PC) providers are in a key position to aid in the identification of, and response to frailty as part of routine care. Unlike singular chronic conditions such as diabetes and hypertension which garner a disease-based approach and identification as part of standard practice, frailty is only just emerging as a concept for PC. The web-based Frailty Portal was developed to aid in the identification of, assessment and care planning for frail patients in PC practice. In this study we assess the implementation feasibility and impact of the Frailty Portal by: (1) identifying factors influencing the Frailty Portal’s use in community PC practice, and (2) examination of the immediate impact of the ‘Frailty Portal’ on frail patients, their caregivers and PC providers. Methods A convergent mixed method approach was implemented among PC providers in community-based practice in the NSHA, Central Zone. Quantitative and qualitative data were collected concurrently over a 9-month period. A sample of patients who underwent assessment and/or their caregiver were approached for survey participation. Results Fourteen community PC providers (10 family physicians, 4 nurse practitioners) completed 48 patient assessments and completed or begun 41 care plans; semi-structured interviews were conducted among 9 providers. Nine patients and 5 caregivers participated in the survey. PC providers viewed frailty as an important concept but implementation challenges were met, primarily with respect to the time required for use and lack of fit with traditional practice routines. Additional barriers included tool usability and accessibility, training and care planning steps, and privacy. Impacts of the tools use with respect to confidence and knowledge showed early promise. Conclusion This feasibility study highlights the need for added health system supports, resources and financial incentives for successful implementation of the Frailty Portal in community PC practice. We suggest future implementation integrate the Frailty Portal to practice electronic medical records (EMRs) and target providers with largely geriatric practice populations and those practicing within interdisciplinary, collaborative primary healthcare (PHC) teams.

Background: Five linked studies were undertaken to inform identified evidence gaps in the childhood obesity pathway. Objectives: (1) To scope the impact of the National Child Measurement Programme (NCMP) (study A). (2) To develop a brief evidence-based electronic assessment and management tool (study B). (3) To develop evidence-based algorithms for identifying the risk of obesity comorbidities (study B). (4) To conduct an efficacy trial of the Healthy Eating and Lifestyle Programme (HELP) (study C). (5) To improve the prescribing of anti-obesity drugs in UK adolescents (study D). (6) To investigate the safety, outcomes and predictors of outcome of adolescent bariatric surgery in the UK (study E). Methods: Five substudies – (1) a parental survey before and after feedback from the National Childhood Measurement Programme, (2) risk algorithm development and piloting of a new primary care management tool, (3) a randomised controlled trial of the Healthy Eating and Lifestyle Programme, (4) quantitative and qualitative studies of anti-obesity drug treatment in adolescents and (5) a prospective clinical audit and cost-effectiveness evaluation of adolescent bariatric surgery in one centre. Results: Study A – before the National Childhood Measurement Programme feedback, three-quarters of parents of overweight and obese children did not recognise their child to be overweight. Eighty-seven per cent of parents found the National Childhood Measurement Programme feedback to be helpful. Feedback had positive effects on parental knowledge, perceptions and intentions. Study B – risk estimation models for cardiovascular and psychosocial comorbidities of obesity require further development. An online consultation tool for primary care practitioners is acceptable and feasible. Study C – the Healthy Eating and Lifestyle Programme, when delivered in the community by graduate mental health workers, showed no significant effect on body mass index at 6 months (primary outcome) when compared with enhanced usual care. Study D – anti-obesity drugs appear efficacious in meta-analysis, and their use has expanded rapidly in the last decade. However, the majority of prescriptions are rapidly discontinued after 1–3 months of treatment. Few young people described positive experiences of anti-obesity drugs. Prescribing was rarely compliant with the National Institute for Health and Care Excellence guidance. Study E – bariatric surgery appears safe, effective and highly cost-effective in adolescents in the NHS. Future work and limitations: Work is needed to evaluate behaviour and body mass index change in the National Childhood Measurement Programme more accurately and improve primary care professionals’ understanding of the National Childhood Measurement Programme feedback, update and further evaluate the Computer-Assisted Treatment of CHildren (CATCH) tool, investigate delivery of weight management interventions to young people from deprived backgrounds and those with significant psychological distress and obtain longer-term data on anti-obesity drug use and bariatric surgery outcomes in adolescence. Trial registration: Current Controlled Trials ISRCTN99840111. Funding: This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 8, No. 3. See the NIHR Journals Library website for further project information.

Abstract Background Microarray experiments comprise more than half of all series in the Gene Expression Omnibus (GEO). However, downloading and analyzing raw or semi-processed microarray data from GEO is not intuitive and requires manual error-prone analysis and a bioinformatics background. This is due to a lack of standardization in array platform fabrication as well as the lack of a simple interactive tool for clustering, plotting, differential expression testing, and testing for functional enrichment. Results We introduce the Bioinformatics Array Research Tool (BART), an R Shiny web application that automates the microarray download and analysis process across diverse microarray platforms. It provides an intuitive interface, automatically downloads and parses data from GEO, suggests groupings of samples for differential expression testing, performs batch effect correction, outputs quality control plots, converts probe IDs, generates full lists of differentially expressed genes, and performs functional enrichment analysis. We show that BART enables a more comprehensive analysis of a wider range of microarray datasets on GEO by comparing it to four leading online microarray analysis tools. Conclusions BART allows a scientist with no bioinformatics background to extract knowledge from their own microarray data or microarray experiments available from GEO. BART is functional on more microarray experiments and provides more comprehensive analyses than extant microarray analysis tools. BART is hosted on bart.salk.edu, includes a user tutorial, and is available for download from https://bitbucket.org/Luisa_amaral/bart.

The content in library courses is highly relevant for students to perform well in their studies. But the material taught by librarians is usually not part of the curriculum and will not be tested directly in summative assessments. Students therefore tend to be passive and uninvolved in these lectures. The aim of this study was to investigate whether a digital online tool can help students to be more active and engaged. The proportion of students who used this tool to interact with the lecturer varied slightly among the different classes in the study, but the participation rate was relatively high overall. A lesson learned for later use of this kind of tool is that it is important to have planned how students should use the tool, and how the teaching must be organized to make that use possible. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and efficiently if bulk three-dimensional (3D) materials are formed by layers held together by a weak binding energy that, thus, can be potentially exfoliated into 2D materials. In this work, we develop a machine-learning (ML) approach that, combined with a fast preliminary geometrical screening, is able to efficiently identify potentially exfoliable materials. Starting from a combination of descriptors for crystal structures, we work out a subset of them that are crucial for accurate predictions. Our final ML model, based on a random forest classifier, has a very high recall of 98%. Using a SHapely Additive exPlanations analysis, we also provide an intuitive explanation of the five most important variables of the model. Finally, we compare the performance of our best ML model with a deep neural network architecture using the same descriptors. To make our algorithms and models easily accessible, we publish an online tool on the Materials Cloud portal that only requires a bulk 3D crystal structure as input. Our tool thus provides a practical yet straightforward approach to assess whether any 3D compound can be exfoliated into 2D layers.