How Mixed-Methods Research Can Improve the Policy Relevance of Impact Evaluations

This paper describes how mixed methods can improve the value and policy relevance of impact evaluations, paying particular attention to how mixed methods can be used to address external validity and generalization issues. We briefly review the literature on the rationales for using mixed methods; provide documentation of the extent to which mixed methods have been used in impact evaluations in recent years; describe how we developed a list of recent impact evaluations using mixed methods and the process used to conduct full-text reviews of these articles; summarize the findings from our analysis of the articles; discuss three exemplars of using mixed methods in impact evaluations; and discuss how mixed methods have been used for studying and improving external validity and potential improvements that could be made in this area. We find that mixed methods are rarely used in impact evaluations, and we believe that increased use of mixed methods would be useful because they can reinforce findings from the quantitative analysis (triangulation), and they can also help us understand the mechanism by which programs have their impacts and the reasons why programs fail.

Unveiling the transferability of PLSR models for leaf trait estimation: lessons from a comprehensive analysis with a novel global dataset

Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time, and plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired leaf traits and spectra, with 47 393 records for > 700 species and eight PFTs at 101 globally distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits. While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water, and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R2 (0.12-0.49, 0.15-0.42, and 0.25-0.56) and increased NRMSE (3.58-18.24%, 6.27-11.55%, and 7.0-33.12%) compared with nonspatial random cross-validation. The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability. These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs, and time due to biased validation schemes, and provide guidance for future field sampling strategies and remote sensing applications.

The benefits of validation of methods for toxicity testing outweigh its costs

The 4th Annual Forum on Endocrine Disrupters organized by the European Commission brought together authors of this article around the topic: "From bench to validated test guidelines: (pre)validation of test methods". Validation activities are meant to demonstrate the relevance and reliability of methods and approaches used in regulatory safety testing. These activities are essential to facilitate regulatory use, still they are largely underfunded and unattractive to the scientific community. In the last decade, there has been large amounts of funding invested in European research towards the development of approaches that can be used in regulatory decision-making, including for the identification of endocrine disrupters. There is a vast pool of candidate test methods for potential regulatory applications, but most of them will not be used due to the absence of consideration of their relevance and reliability outside the method developer's laboratory. The article explains the reasons why such a gap exists between the outputs of research projects and the uptake in a regulatory context. In parallel, there are also increasing expectations from the regulatory science community that validation becomes more efficient with respect to time and resources. This article shares some of the lessons learned and proposes paths forward for validation of new methods that are not intended as one-to-one replacements of animal studies. This includes submitting only mature methods for validation that were developed following good practices and good documentation, proposing a greater emphasis on well-documented transferability studies, and adopting a cost-sharing model between those who benefit from validated methods.

Interest in mHealth Among Patients With Low Back Pain: Cross-Sectional Study

BACKGROUND

Digitally supported self-management tailored to an individual's need, in addition to usual care, may reduce pain-related disability compared to usual care alone, and patients with low back pain (LBP) using mobile health (mHealth) solutions express positive experiences. Hence, implementing mHealth solutions designed to support self-management is desirable from a clinical and patient perspective. Easily accessible mHealth solutions that can support the self-management of patients with LBP are available, but interest may be subgroup specific. Understanding the characteristics and preferences of patients with LBP labeled as interested may help to reach relevant LBP patient groups and inform the development and implementation of effective interventions with mHealth for patients with LBP.

OBJECTIVE

This study aims to explore the proportion of patients with LBP labeled as interested in testing an mHealth solution designed to support self-management in addition to usual care and to assess how these patients differ from those who were labeled as not interested.

METHODS

This exploratory cross-sectional study analyzed demographic and patient-reported outcomes from the SpineData registry, a Danish registry of patients with LBP in an outpatient setting. Between February and December 2019, the SpineData registry was used to assess the preliminary eligibility of patients for a clinical trial (selfBACK). Patients were labeled as interested or uninterested depending on if they responded to an invitation to be tested for eligibility for the trial Outcomes were selected from the International Classification of Functioning core set of LBP using a clinical approach. Associations were assessed in a backward selection process, and the proportion of variance explained was assessed with pseudo-R2 statistic.

RESULTS

This study included 843 patients, with 181 (21%) individuals labeled as interested in participating in the selfBACK trial. Notably, the cohort labeled as interested differed from their uninterested counterparts in two key aspects: age (36-65 years: 116/181, 64.1% vs 347/662, 52.4%; P=.003) and smoking status (smokers: 22/181, 12.5% vs 174/662, 26.6%; P<.001). Those aged 36-65 years had higher odds of being labeled as interested compared to individuals aged 18-35 years (odds ratio [OR] 0.43, 95% CI 0.26-0.71) and those 65 years or older (OR 0.77, 95% CI 0.53-1.15). Nevertheless, age accounted for only a modest proportion of variance (R2=0.014). Smokers demonstrated lower odds of being labeled as interested (OR 0.39, 95% CI 0.24-0.64), with smoking status explaining a similarly small proportion of variance (R2=0.019). Collectively, age and smoking status accounted for 3.3% of the variance.

CONCLUSIONS

Our investigation revealed that 181 (21%) individuals with LBP invited to participate in the mHealth solution trial for self-management expressed interest. Generally, the characteristics of those labeled as interested and uninterested were comparable. Of note, patients aged 36-65 years had a higher frequency of being labeled as interested compared to their younger and older counterparts.

Laparoscopic but not open surgical skills can be transferred to robot-assisted surgery: A systematic review and meta-analysis

BACKGROUND

With an increase in robot-assisted surgery across all specialties, adequate training and credentialing strategies need to be identified to ensure patients safety. The meta-analysis assesses the transferability of technical surgical skills between laparoscopic surgery, open surgery, and robot-assisted surgery.

DESIGN

A systematic search was conducted in Medline, Cochrane Central Register of Controlled Trials, and Web of Science. Outcomes were categorized into time, process, product, and composite outcome measures and pooled separately using Hedges'g (standardized mean difference [SMD]). Subgroup analyses were performed to assess the effect of study design, virtual reality platforms and task difficulty.

RESULTS

Out of 14,120 screened studies, 30 were included in the qualitative synthesis and 26 in the quantitative synthesis. Technical surgical skill transfer was demonstrated from laparoscopic to robot-assisted surgery (composite: SMD 0.40, 95%-confidence interval [CI] [0.19; 0.62], time: SMD 0.62, CI [0.33; 0.91]) and vice versa (composite: SMD 0.66, CI [0.33; 0.99], time [basic skills]: SMD 0.36, CI [0.01; 0.72]). No skill transfer was seen from open to robot-assisted surgery with limited available data.

CONCLUSION

Technical surgical skills can be transferred from laparoscopic to robot-assisted surgery and vice versa. Robot-assisted and laparoscopic surgical skills training and credentialing should not be regarded separately, but a reasonable combination could shorten overall training times and increase efficiency. Previous experience in open surgery should not be considered as an imperative prerequisite for training in robot-assisted surgery. Recommendations for studies assessing skill transfer are proposed to increase comparability and significance of future studies.

PROSPERO REGISTRATION NUMBER

PROSPERO CRD42018104507.

A Multiplex PCR System of Novel Microsatellite Loci for Population Genetic Application in Walnuts

Multiplex polymerase chain reaction (PCR) of microsatellite loci allows for simultaneous amplification of two or more pairs of primers in a single PCR reaction; hence, it is cost and time effective. However, very few attempts have been reported in non-model species. In this study, by combining a genome-based de novo development and cross-species application approach, a multiplex PCR system comprising 5 PCR reactions of 33 microsatellites consisting of 26 novel genomic and 7 literature-sourced loci was tested for polymorphisms, cross-species transferability, and the ability to assess genetic diversity and population structure of three walnut species (Juglans spp.). We found that the genome-based approach is more efficient than other methods. An allelic ladder was developed for each locus to enhance consistent genotyping among laboratories. The population genetic analysis results showed that all 33 loci were successfully transferred across the three species, showing high polymorphism and a strong genetic structure. Hence, the multiplex PCR system is highly applicable in walnut species. Furthermore, we propose an efficient pipeline to characterize and genotype polymorphic microsatellite loci. The novel toolbox developed here will aid future ecology and evolution studies in walnut and could serve as a model for other plant species.

Artificial intelligence for dementia research methods optimization

Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being used in dementia research. However, several methodological challenges exist that may limit the insights we can obtain from high-dimensional data and our ability to translate these findings into improved patient outcomes. To improve reproducibility and replicability, researchers should make their well-documented code and modeling pipelines openly available. Data should also be shared where appropriate. To enhance the acceptability of models and AI-enabled systems to users, researchers should prioritize interpretable methods that provide insights into how decisions are generated. Models should be developed using multiple, diverse datasets to improve robustness, generalizability, and reduce potentially harmful bias. To improve clarity and reproducibility, researchers should adhere to reporting guidelines that are co-produced with multiple stakeholders. If these methodological challenges are overcome, AI and ML hold enormous promise for changing the landscape of dementia research and care. HIGHLIGHTS: Machine learning (ML) can improve diagnosis, prevention, and management of dementia. Inadequate reporting of ML procedures affects reproduction/replication of results. ML models built on unrepresentative datasets do not generalize to new datasets. Obligatory metrics for certain model structures and use cases have not been defined. Interpretability and trust in ML predictions are barriers to clinical translation.

Power of inclusion: Enhancing polygenic prediction with admixed individuals

Admixed individuals offer unique opportunities for addressing limited transferability in polygenic scores (PGSs), given the substantial trans-ancestry genetic correlation in many complex traits. However, they are rarely considered in PGS training, given the challenges in representing ancestry-matched linkage-disequilibrium reference panels for admixed individuals. Here we present inclusive PGS (iPGS), which captures ancestry-shared genetic effects by finding the exact solution for penalized regression on individual-level data and is thus naturally applicable to admixed individuals. We validate our approach in a simulation study across 33 configurations with varying heritability, polygenicity, and ancestry composition in the training set. When iPGS is applied to n = 237,055 ancestry-diverse individuals in the UK Biobank, it shows the greatest improvements in Africans by 48.9% on average across 60 quantitative traits and up to 50-fold improvements for some traits (neutrophil count, R2 = 0.058) over the baseline model trained on the same number of European individuals. When we allowed iPGS to use n = 284,661 individuals, we observed an average improvement of 60.8% for African, 11.6% for South Asian, 7.3% for non-British White, 4.8% for White British, and 17.8% for the other individuals. We further developed iPGS+refit to jointly model the ancestry-shared and -dependent genetic effects when heterogeneous genetic associations were present. For neutrophil count, for example, iPGS+refit showed the highest predictive performance in the African group (R2 = 0.115), which exceeds the best predictive performance for the White British group (R2 = 0.090 in the iPGS model), even though only 1.49% of individuals used in the iPGS training are of African ancestry. Our results indicate the power of including diverse individuals for developing more equitable PGS models.

Fooling Examples: Another Intriguing Property of Neural Networks

Neural networks have been proven to be vulnerable to adversarial examples; these are examples that can be recognized by both humans and neural networks, although neural networks give incorrect predictions. As an intriguing property of neural networks, adversarial examples pose a serious threat to the secure application of neural networks. In this article, we present another intriguing property of neural networks: the fact that well-trained models believe some examples to be recognizable objects (often with high confidence), while humans cannot recognize such examples. We refer to these as "fooling examples". Specifically, we take inspiration from the construction of adversarial examples and develop an iterative method for generating fooling examples. The experimental results show that fooling examples can not only be easily generated, with a success rate of nearly 100% in the white-box scenario, but also exhibit strong transferability across different models in the black-box scenario. Tests on the Google Cloud Vision API show that fooling examples can also be recognized by real-world computer vision systems. Our findings reveal a new cognitive deficit of neural networks, and we hope that these potential security threats will be addressed in future neural network applications.

Antibiotic Resistance Patterns and Molecular Characterization of Streptococcus suis Isolates from Swine and Humans in China

Streptococcus suis is a zoonotic pathogen that causes disease in humans after exposure to infected pigs or pig-derived food products. In this study, we examined the serotype distribution, antimicrobial resistance phenotypes and genotypes, integrative and conjugative elements (ICEs), and associated genomic environments of S. suis isolates from humans and pigs in China from 2008 to 2019. We identified isolates of 13 serotypes, predominated by serotype 2 (40/96; 41.7%), serotype 3 (10/96; 10.4%), and serotype 1 (6/96; 6.3%). Whole-genome sequencing analysis revealed that these isolates possessed 36 different sequence types (STs), and ST242 and ST117 were the most prevalent. Phylogenetic analysis revealed possible animal and human clonal transmission, while antimicrobial susceptibility testing indicated high-level resistance to macrolides, tetracyclines, and aminoglycosides. These isolates carried 24 antibiotic resistance genes (ARGs) that conferred resistance to 7 antibiotic classes. The antibiotic resistance genotypes were directly correlated with the observed phenotypes. We also identified ICEs in 10 isolates, which were present in 4 different genetic environments and possessed differing ARG combinations. We also predicted and confirmed by PCR analysis the existence of a translocatable unit (TU) in which the oxazolidinone resistance gene optrA was flanked by IS1216E elements. One-half (5/10) of the ICE-carrying strains could be mobilized by conjugation. A comparison of the parental recipient with an ICE-carrying transconjugant in a mouse in vivo thigh infection model indicated that the ICE strain could not be eliminated with tetracycline treatment. S. suis therefore poses a significant challenge to global public health and requires continuous monitoring, especially for the presence of ICEs and associated ARGs that can be transferred via conjugation. IMPORTANCE S. suis is a serious zoonotic pathogen. In this study, we investigated the epidemiological and molecular characteristics of 96 S. suis isolates from 10 different provinces of China from 2008 to 2019. A subset of these isolates (10) carried ICEs that were able to be horizontally transferred among isolates of different S. suis serotypes. A mouse thigh infection model revealed that ICE-facilitated ARG transfer promoted resistance development. S. suis requires continuous monitoring, especially for the presence of ICEs and associated ARGs that can be transferred via conjugation.

Re-orientating systematic reviews to rigorously examine what works, for whom and how: Example of a realist systematic review of school-based prevention of dating and gender violence

Conventional systematic reviews offer few insights into for whom and how interventions work. 'Realist reviews' examine such questions via examining 'context-mechanism-outcome configurations' (CMOCs) but are insufficiently rigorous in how evidence is identified, assessed and synthesised. We developed 'realist systematic reviews', addressing similar questions to realist reviews but using rigorous methods. We applied this to synthesising evidence on school-based prevention of dating and relationship violence (DRV) and gender-based violence (GBV). This paper reflects on overall methods and findings, drawing on papers reporting each analysis. Drawing on intervention descriptions, theories of change and process evaluations, we developed initial CMOC hypotheses: interventions triggering 'school-transformation' mechanisms (preventing violence by changing school environments) will achieve larger effects than those triggering 'basic-safety' (stopping violence by emphasising its unacceptability) or 'positive-development' (developing students' broader skills and relationships) mechanisms; however, school transformation would only work in schools with high organisational capacity. We used various innovative analyses, some of which aimed to test these hypotheses and some of which were inductive, drawing on available findings to augment and refine the CMOCs. Overall, interventions were effective in reducing long-term DRV but not GBV or short-term DRV. DRV prevention occurred most effectively via the 'basic-safety' mechanism. 'School-transformation' mechanisms were more effective in preventing GBV but only in high-income countries. Impacts on long-term DRV victimisation were greater when working with a critical mass of participating girls. Impacts on long-term DRV perpetration were greater for boys. Interventions were more effective when focusing on skills, attitudes and relationships, or lacking parental involvement or victim stories. Our method provided novel insights and should be useful to policy-makers seeking the best interventions for their contexts and the most information to inform implementation.

A Multimodal Protein Representation Framework for Quantifying Transferability Across Biochemical Downstream Tasks

Proteins are the building blocks of life, carrying out fundamental functions in biology. In computational biology, an effective protein representation facilitates many important biological quantifications. Most existing protein representation methods are derived from self-supervised language models designed for text analysis. Proteins, however, are more than linear sequences of amino acids. Here, a multimodal deep learning framework for incorporating ≈1 million protein sequence, structure, and functional annotation (MASSA) is proposed. A multitask learning process with five specific pretraining objectives is presented to extract a fine-grained protein-domain feature. Through pretraining, multimodal protein representation achieves state-of-the-art performance in specific downstream tasks such as protein properties (stability and fluorescence), protein-protein interactions (shs27k/shs148k/string/skempi), and protein-ligand interactions (kinase, DUD-E), while achieving competitive results in secondary structure and remote homology tasks. Moreover, a novel optimal-transport-based metric with rich geometry awareness is introduced to quantify the dynamic transferability from the pretrained representation to the related downstream tasks, which provides a panoramic view of the step-by-step learning process. The pairwise distances between these downstream tasks are also calculated, and a strong correlation between the inter-task feature space distributions and adaptability is observed.

Machine learning of spectra-property relationship for imperfect and small chemistry data

Machine learning (ML) is causing profound changes to chemical research through its powerful statistical and mathematical methodological capabilities. However, the nature of chemistry experiments often sets very high hurdles to collect high-quality data that are deficiency free, contradicting the need of ML to learn from big data. Even worse, the black-box nature of most ML methods requires more abundant data to ensure good transferability. Herein, we combine physics-based spectral descriptors with a symbolic regression method to establish interpretable spectra-property relationship. Using the machine-learned mathematical formulas, we have predicted the adsorption energy and charge transfer of the CO-adsorbed Cu-based MOF systems from their infrared and Raman spectra. The explicit prediction models are robust, allowing them to be transferrable to small and low-quality dataset containing partial errors. Surprisingly, they can be used to identify and clean error data, which are common data scenarios in real experiments. Such robust learning protocol will significantly enhance the applicability of machine-learned spectroscopy for chemical science.

Guidance on using real-world evidence from Western Europe in Central and Eastern European health policy decision making

Aim: Real-world data and real-world evidence (RWE) are becoming more important for healthcare decision making and health technology assessment. We aimed to propose solutions to overcome barriers preventing Central and Eastern European (CEE) countries from using RWE generated in Western Europe. Materials & methods: To achieve this, following a scoping review and a webinar, the most important barriers were selected through a survey. A workshop was held with CEE experts to discuss proposed solutions. Results: Based on survey results, we selected the nine most important barriers. Multiple solutions were proposed, for example, the need for a European consensus, and building trust in using RWE. Conclusion: Through collaboration with regional stakeholders, we proposed a list of solutions to overcome barriers on transferring RWE from Western Europe to CEE countries.

Artificial Intelligence for Dementia Research Methods Optimization

INTRODUCTION

Machine learning (ML) has been extremely successful in identifying key features from high-dimensional datasets and executing complicated tasks with human expert levels of accuracy or greater.

METHODS

We summarize and critically evaluate current applications of ML in dementia research and highlight directions for future research.

RESULTS

We present an overview of ML algorithms most frequently used in dementia research and highlight future opportunities for the use of ML in clinical practice, experimental medicine, and clinical trials. We discuss issues of reproducibility, replicability and interpretability and how these impact the clinical applicability of dementia research. Finally, we give examples of how state-of-the-art methods, such as transfer learning, multi-task learning, and reinforcement learning, may be applied to overcome these issues and aid the translation of research to clinical practice in the future.

DISCUSSION

ML-based models hold great promise to advance our understanding of the underlying causes and pathological mechanisms of dementia.

The Prevalence of Plasmid-Mediated Colistin Resistance Gene mcr-1 and Different Transferability and Fitness of mcr-1-Bearing IncX4 Plasmids in Escherichia coli from Pigeons

The prevalence of colistin-resistant bacteria limited the usage of colistin in the treatment of clinical multidrug-resistant Gram-negative bacterial infections. Here, we aimed to investigate the prevalence and molecular characterization of mcr-1-carrying isolates from pigeons close to humans following the ban on the use of colistin as an animal feed additive in China. Methods, including PCR, antimicrobial susceptibility testing, conjugation experiments, plasmid replicon typing, genome sequencing, bioinformatics analysis, measurement of growth curves, competition experiments, and plasmid stability assays were used to identify and characterize mcr-1-positive isolates. In total, 45 mcr-1-positive E. coli isolates were acquired from 100 fecal samples, and MICs of colistin ranged from 4 to 8 mg/L. The prevalence of mcr-1-positive E. coli isolates from pigeons was mainly mediated by IncX4 plasmids (39/45), including transferable mcr-1-bearing IncX4 plasmids with fitness advantage in 21 isolates, and nontransferable mcr-1-bearing IncX4 plasmids with fitness disadvantage in 18 isolates. There is a similar structure among the 6 mcr-1-bearing nontransferable IncX4 plasmids and 10 mcr-1-bearing transferable IncX4 plasmids in 16 E. coli isolates that have been sequenced. Plasmid transferability evaluation indicated that the same IncX4 plasmid has different transferability in different E. coli isolates. In conclusion, this study demonstrates that pigeons could act as potential reservoirs for the spread of mcr-1-positive E. coli in China. Transferability of IncX4 plasmids may be influenced by host chromosome in the same bacterial species. Additional research on the factors influencing the transferability of IncX4 plasmids in different bacterial hosts is required to help combat antimicrobial resistance. IMPORTANCE The emergence of plasmid-mediated colistin resistance gene mcr-1 incurs great concerns. Since the close proximity of pigeons with humans, it is significant to understand the prevalence and molecular characterization of mcr-1-positive isolates in pigeons, to provide a rationale for controlling its spread. Here, we found that the prevalence of mcr-1-positive E. coli from pigeons was mainly mediated by IncX4 plasmids. However, different transferability and fitness of mcr-1-bearing IncX4 plasmids in E. coli were observed, which demonstrated that transferability of IncX4 plasmids could be affected not only by genes on plasmids, but also by chromosomal factors in the same bacterial species. Our finding provided a new insight on studying the factors influencing the transferability of plasmids.

De Novo Transcriptome Assembly and EST-SSR Marker Development and Application in Chrysosplenium macrophyllum

Chrysosplenium macrophyllum Oliv., belonging to the family Saxifragaceae, is a traditional and unique Chinese herbal medicine. However, the lack of adequate molecular markers has hampered the progress regarding population genetics and evolution within this species. In this research, we used the DNBSEQ-T7 Sequencer (MGI) sequencing assay to analyze the transcriptome profiles of C. macrophyllum. SSR markers were developed on the basis of transcriptomic sequences and further validated on C. macrophyllum and other Chrysosplenium species. The genetic diversity and structure of the 12 populations were analyzed by using polymorphic expressed sequence tag simple sequence repeat (EST-SSR) markers. A potential pool of 3127 non-redundant EST-SSR markers were identified for C. macrophyllum in this study. The developed EST-SSR markers had high amplification rates and cross-species transferability in Chrysosplenium. Our results also showed that the natural populations of C. macrophyllum had a high level of genetic diversity. Genetic distance, principal component analysis, and popular structure analysis revealed that all 60 samples clustered into two major groups that were consistent with their geographical origins. This study provided a batch of highly polymorphic EST-SSR molecular markers that were developed via transcriptome sequencing. These markers will be of great significance for the study of the genetic diversity and evolutionary history of C. macrophyllum and other Chrysosplenium species.

[The operating room, a place of training with multiple benefits for future professionals]

The importance of internships, as part of the alternating training of nursing students, is no longer in question. Thus, to obtain their diploma, out of the 180 European credits expected, 60 come from these placements. Although very specific and not very much involved in the training of students in initial training, an internship in the operating room is very instructive and contributes to the development of multiple nursing knowledge and skills.

Design and development of a self-propelled indoor wheelchair with direct toilet accessibility

PURPOSE

Existing wheelchair (WC) designs lack independent toilet accessibility, transferability and indoor manoeuvrability combined in a WC. In this regard, a new WC model is proposed to simultaneously accommodate these distinct and essential features. In this open-source hardware project, the design, analysis and fabrication of a new active commode WC for indoor applications are performed.

MATERIALS AND METHOD

A field survey is conducted to identify the requirements of users so as to choose specific features and design constraints for the WC. In this multipurpose self-propelled model, a temporarily detachable circular section is fitted in the seat position to access the water closet bowl. This hinged portion can be released by gravity before reaching above the closet basin. After the toilet usage, the circular lid can be brought back to the initial seating using a lever mechanism and a spring-loaded lock restrains its downward movement. Thereafter, it can be used as an ordinary WC for indoor applications. Moreover, a small wheel with 22 in diameter and removable hand-rests ensured the transferability between utilities. A CAD model is prepared and numerical simulation is performed to verify the structural stability of the design.

RESULTS

The optimized model is fabricated using standard manufacturing practices and is delivered to different persons with disabilities to collect user feedback. A systematic skill test is conducted to validate the compliance of the prototype with the user requirements including transferability and independent restroom access.

CONCLUSION

The opinions from most of the users are positive which categorically indicated that the proposed design addresses the multipurpose mobility requirements at indoors.Implications for rehabilitationThe expected outcomes and implications of the current commode WC project with regard to rehabilitation purpose are enlisted below:In the present scenario, a WC user is heavily dependent on external assistance to access private spaces in general and toilets in particular. The introduced model is capable to address this shortcoming by enabling the user to access the toilet utility directly by self propelling.Indeed, for a person with locomotor disability, a WC is the natural extension of his physical body. Thereby, this multipurpose commode WC design offers much Independence and greater flexibility to the indoor movements.The proposed design instils confidence to a WC user to access and transfer between facilities by means of self effort. Consequently it is expected to improve the quality of one's personal life significantly.Importantly, this is an open-source project, those who are interested in rehabilitation motives can modify the present design to suit their local requirements especially in resource-limited settings.

Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index

Polygenic risk scores (PRS) have led to enthusiasm for precision medicine. However, it is well documented that PRS do not generalize across groups differing in ancestry or sample characteristics e.g., age. Quantifying performance of PRS across different groups of study participants, using genome-wide association study (GWAS) summary statistics from multiple ancestry groups and sample sizes, and using different linkage disequilibrium (LD) reference panels may clarify which factors are limiting PRS transferability. To evaluate these factors in the PRS generation process, we generated body mass index (BMI) PRS (PRSBMI) in the Electronic Medical Records and Genomics (eMERGE) network (N=75,661). Analyses were conducted in two ancestry groups (European and African) and three age ranges (adult, teenagers, and children). For PRSBMI calculations, we evaluated five LD reference panels and three sets of GWAS summary statistics of varying sample size and ancestry. PRSBMI performance increased for both African and European ancestry individuals using cross-ancestry GWAS summary statistics compared to European-only summary statistics (6.3% and 3.7% relative R2 increase, respectively, pAfrican=0.038, pEuropean=6.26x10-4). The effects of LD reference panels were more pronounced in African ancestry study datasets. PRSBMI performance degraded in children; R2 was less than half of teenagers or adults. The effect of GWAS summary statistics sample size was small when modeled with the other factors. Additionally, the potential of using a PRS generated for one trait to predict risk for comorbid diseases is not well understood especially in the context of cross-ancestry analyses - we explored clinical comorbidities from the electronic health record associated with PRSBMI and identified significant associations with type 2 diabetes and coronary atherosclerosis. In summary, this study quantifies the effects that ancestry, GWAS summary statistic sample size, and LD reference panel have on PRS performance, especially in cross-ancestry and age-specific analyses.

Integrative Analysis of Rhythmicity: From Biology to Urban Environments and Sustainability

From biological to socio-technical systems, rhythmic processes are pervasive in our environment. However, methods for their comprehensive analysis are prevalent only in specific fields that limit the transfer of knowledge across scientific disciplines. This hinders interdisciplinary research and integrative analyses of rhythms across different domains and datasets. In this paper, we review recent developments in cross-disciplinary rhythmicity research, with a focus on the importance of rhythmic analyses in urban planning and biomedical research. Furthermore, we describe the current state of the art of (integrative) computational methods for the investigation of rhythmic data. Finally, we discuss the further potential and propose necessary future developments for cross-disciplinary rhythmicity analysis to foster integration of heterogeneous datasets across different domains, as well as guide data-driven decision making beyond the boundaries of traditional intradisciplinary research, especially in the context of sustainable and healthy cities.

Inhibitory Control Training Improves Attention Deficit-Hyperactivity Disorder Symptoms and Externalizing Behavior

BACKGROUND

Based on dysexecutive function theory of Attention deficit-hyperactivity disorder (ADHD), inhibitory control plays a crucial role in ADHD symptoms and respective behavioral problems.

METHODS

In the present study, 30 preschoolers with ADHD were recruited in a random clinical trial design in two control and intervention groups. The Flanker and Go/No-Go tasks, Swanson, Nolan, and Pelham Rating Scale, and Child Behavior Checklist were used for assessment at baseline, after the intervention, and 1-month follow-up sessions. The program for attentive rehabilitation of inhibition and selective attention (PARISA) was used for intervention in 10-12 sessions.

RESULTS

Findings showed an improvement in prepotent inhibition and interference control in the intervention group. Furthermore, the hyperactivity/impulsivity symptoms were ameliorated, and the externalizing behavioral problems were improved after the intervention.

CONCLUSION

Inhibitory control in preschoolers with ADHD is trainable, and the training gain could be transferred to ADHD symptoms and externalizing behavior.

Transferability of real-world data across borders for regulatory and health technology assessment decision-making

Recently, there has been increased consideration of real-world data (RWD) and real-world evidence (RWE) in regulatory and health technology assessment (HTA) decision-making. Due to challenges in identifying high-quality and relevant RWD sources, researchers and regulatory/HTA bodies may turn to RWD generated in locales outside of the locale of interest (referred to as "transferring RWD"). We therefore performed a review of stakeholder guidance as well as selected case studies to identify themes for researchers to consider when transferring RWD from one jurisdiction to another. Our review highlighted that there is limited consensus on defining decision-grade, transferred RWD; certain stakeholders have issued relevant guidance, but the recommendations are high-level and additional effort is needed to generate comprehensive guidance. Additionally, the case studies revealed that RWD transferability has not been a consistent concern for regulatory/HTA bodies and that more focus has been put on the evaluation of internal validity. To help develop transferability best practices (alongside internal validity best practices), we suggest that researchers address the following considerations in their justification for transferring RWD: treatment pathways, nature of the healthcare system, incidence/prevalence of indication, and patient demographics. We also recommend that RWD transferability should garner more attention as the use of imported RWD could open doors to high-quality data sources and potentially reduce methodological issues that often arise in the use of local RWD; we thus hope this review provides a foundation for further dialogue around the suitability and utility of transferred RWD in the regulatory/HTA decision-making space.

Could a phase model help to improve translational animal research?

BACKGROUND

Animal models are widely applied in medical research for different purposes. In particular, results from translational experiments may be used for subsequent clinical development. However, transferability of these findings to the human organism is controversial. Among other factors, this may be traced back to a lack of clear differentiation of the evidence (explorative vs. confirmatory) provided by such experimental results. In general, inferential statistics (i.e. p values) should not be interpreted in as confirmatory unless crucial methodological requirements are met.

METHODS

Therefore, we propose a phase model which reflects the well-established process of clinical research, and we discuss its potential to improve decision making in translational research. The model aims to clarify the reliability of results derived from animal models.

RESULTS

The phase model proposes subdividing translational, pre-clinical research into pilot, exploration, and confirmation phases. Experiments for which there is no valid estimation of the expected effect size are designated as pilot studies. Based on these data, experiments in subsequent phases may be planned using both appropriate design and statistical methods.

CONCLUSION

Separating the entire process of translational animal research into three phases could contribute to improved transparency of the evidence derived from such experiments.

Diversity Matters: Optimal Collision Energies for Tandem Mass Spectrometric Analysis of a Large Set of N-Glycopeptides

Identification and characterization of N-glycopeptides from complex samples are usually based on tandem mass spectrometric measurements. Experimental settings, especially the collision energy selection method, fundamentally influence the obtained fragmentation pattern and hence the confidence of the database search results ("score"). Using standards of naturally occurring glycoproteins, we mapped the Byonic and pGlyco search engine scores of almost 200 individual N-glycopeptides as a function of collision energy settings on a quadrupole time of flight instrument. The resulting unprecedented amount of peptide-level information on such a large and diverse set of N-glycopeptides revealed that the peptide sequence heavily influences the energy for the highest score on top of an expected general linear trend with m/z. Search engine dependence may also be noteworthy. Based on the trends, we designed an experimental method and tested it on HeLa, blood plasma, and monoclonal antibody samples. As compared to the literature, these notably lower collision energies in our workflow led to 10-50% more identified N-glycopeptides, with higher scores. We recommend a simple approach based on a small set of reference N-glycopeptides easily accessible from glycoprotein standards to ease the precise determination of optimal methods on other instruments. Data sets can be accessed via the MassIVE repository (MSV000089657 and MSV000090218).

A Novel Steganography Method for Character-Level Text Image Based on Adversarial Attacks

The Internet has become the main channel of information communication, which contains a large amount of secret information. Although network communication provides a convenient channel for human communication, there is also a risk of information leakage. Traditional image steganography algorithms use manually crafted steganographic algorithms or custom models for steganography, while our approach uses ordinary OCR models for information embedding and extraction. Even if our OCR models for steganography are intercepted, it is difficult to find their relevance to steganography. We propose a novel steganography method for character-level text images based on adversarial attacks. We exploit the complexity and uniqueness of neural network boundaries and use neural networks as a tool for information embedding and extraction. We use an adversarial attack to embed the steganographic information into the character region of the image. To avoid detection by other OCR models, we optimize the generation of the adversarial samples and use a verification model to filter the generated steganographic images, which, in turn, ensures that the embedded information can only be recognized by our local model. The decoupling experiments show that the strategies we adopt to weaken the transferability can reduce the possibility of other OCR models recognizing the embedded information while ensuring the success rate of information embedding. Meanwhile, the perturbations we add to embed the information are acceptable. Finally, we explored the impact of different parameters on the algorithm with the potential of our steganography algorithm through parameter selection experiments. We also verify the effectiveness of our validation model to select the best steganographic images. The experiments show that our algorithm can achieve a 100% information embedding rate and more than 95% steganography success rate under the set condition of 3 samples per group. In addition, our embedded information can be hardly detected by other OCR models.

Three-dimensional multiple object tracking improves young adult cognitive abilities associated with driving: evidence for transfer to the useful field of view

OBJECTIVES

3-dimensional multiple object tracking (3D-MOT) and the useful field of view (UFOV) both claim to measure and train cognitive abilities, such as selective and divided attention implicated in driving safety. 3D-MOT is claimed to improve even young adult cognitive ability. If true, one would expect to observe the transfer of 3D-MOT training to UFOV performance mediated by way of shared underlying cognitive mechanisms.

METHODS

We test this notion by assessing whether ten 30-min sessions of 3D-MOT training spread across 5 weeks improves UFOV performance relative to an active control group trained on a visual task and a challenging puzzle game (participants aged between 23 and 33 years old).

RESULTS

The 3D-MOT training group exhibited significantly improved UFOV performance whereas the active control group exhibited only a small, statistically nonsignificant improvement in the task.

CONCLUSIONS

This suggests that 3D-MOT and UFOV performance are likely dependent on overlapping cognitive abilities and helps support the assertion that these abilities can be trained and measured even in young adults. Such training could have implications for improving driver safety in both young and older adults.

Full-length transcriptome sequencing analysis and characterization, development and validation of microsatellite markers in Kengyilia melanthera

As a typical psammophyte of the Triticeae, Kengyilia melanthera possesses high feeding potential and great utilization values in desertification control in the Qinghai-Tibet Plateau. However, few gene function and genetic studies have been performed in K. melanthera. In this study, single-molecule real-time sequencing technology was used to obtain the full-length transcriptome sequence of K. melanthera, following the functional annotation of transcripts and prediction of coding sequences (CDSs), transcription factors (TFs), and long noncoding RNA (lncRNA) sequences. Meanwhile, a total of 42,433 SSR loci were detected, with 5'-UTRs having the most SSR loci and trinucleotide being the most abundant type. In total, 108,399 SSR markers were designed, and 300 SSR markers were randomly selected for diversity verification of K. melanthera. A total of 49 polymorphic SSR markers were used to construct the genetic relationships of 56 K. melanthera accessions, among which 21 SSR markers showed good cross-species transferability among the related species. In conclusion, the full-length transcriptome sequence of the K. melanthera will assist gene prediction and promote molecular biology and genomics research, and the polymorphic SSR markers will promote molecular-assisted breeding and related research of K. melanthera and its relatives.

Priority setting and cross-country learning: the relevance of TO-REACH for primary care

Aim:

To inform the primary care community about priorities for research in primary care as came up from the European project TO-REACH and to discuss transferability of service and policy innovations between countries.

Background:

TO-REACH stands for Transfer of Organizational innovations for Resilient, Effective, equitable, Accessible, sustainable and Comprehensive Health services and systems. This EU-funded project has put health systems and services research higher on the European agenda and has led to the current development of a European ‘Partnership Transforming Health and Care Systems’.

Methods:

To identify research priorities, both qualitative and quantitative approaches were used. Policy documents and strategic roadmaps were searched, and priorities were mapped. Stakeholders were involved through national roundtable consultations and online consultations. Regarding transferability, we carried out a review of the literature, guided by a conceptual framework, and using a snowballing approach.

Findings:

Primary care emerged as an important priority from the inventory, as are areas that are conducive to strengthening primary care, such as workforce policies. The large variation in service organisation and policy around primary care in Europe is a huge potential for cross-country learning. However, the simple transfer of primary care service and policy arrangements from one health system to another has a big chance to fail, unless known conditions for successful transfer are taken into account and gaps in our knowledge about transfer are resolved.

What you see is what you breathe? Estimating air pollution spatial variation using street level imagery

High spatial resolution information on urban air pollution levels is unavailable in many areas globally, partially due to high input data needs of existing estimation approaches. Here we introduce a computer vision method to estimate annual means for air pollution levels from street level images. We used annual mean estimates of NO2 and PM2.5 concentrations from locally calibrated models as labels from London, New York, and Vancouver to allow for compilation of a sufficiently large dataset (~250k images for each city). Our experimental setup is designed to quantify intra and intercity transferability of image-based model estimates. Performances were high and comparable to traditional land-use regression (LUR) and dispersion models when training and testing on images from the same city (R2 values between 0.51 and 0.95 when validated on data from ground monitoring stations). Like LUR models, transferability of models between cities in different geographies is more difficult. Specifically, transferability between the three cities i.e., London, New York, and Vancouver, which have similar pollution source profiles were moderately successful (R2 values between zero and 0.67). Comparatively, performances when transferring models trained on these cities with very different source profiles i.e., Accra in Ghana and Hong Kong were lower (R2 between zero and 0.21) suggesting the need for local calibration with local calibration using additional measurement data from cities that share similar source profiles.

Case management for people with dementia living at home and their informal caregivers: A scoping review

Case management is a complex intervention aimed at addressing a variety of health needs of people in their social environment. Case management for people with dementia is often poorly defined and insufficiently described. The crucial process steps are often not well understood. We aim to map and compare the key components, processes and contextual factors of case management programmes for dementia and to explore aspects of the interventions' generalisability. Our search covered the databases PubMed, CINAHL, Cochrane and GeroLit, as well as policy papers from international organisations. We included qualitative, quantitative and mixed-methods studies in the English or German language that was published between 1999 and 2020. The programmes were analysed according to programme characteristics, case management intervention and the structural and processing conditions. We identified 67 studies dealing with 25 programmes. Approximately half of the programmes were investigated in randomised controlled trials, two programmes used a mixed-methods design and the remaining were the subject of pre-post cohort studies. Participants in the studies were predominantly dyads of people with dementia and their informal caregivers. About half of the programmes reported a theoretical framework. All the programmes were derived from case management approaches or referred to such approaches. Despite huge differences in implementation, all the programmes covered the case management steps. In 14 out of 25 programmes, case management was carried out without additional intervention, the other programmes provided mainly education and training for informal caregivers. Costs of the case management interventions were stated in more than half of the programmes.The effectiveness and generalisability of dementia-specific case management interventions could be enhanced if the framework introduced in the review was used in the future by policy, practice and research.

Characterization of Microsatellites in the Akebia trifoliata Genome and Their Transferability and Development of a Whole Set of Effective, Polymorphic, and Physically Mapped Simple Sequence Repeat Markers

Akebia trifoliata is a perennial climbing woody liana plant with a high potential for commercial exploitation and theoretical research. Similarly, microsatellites (simple sequence repeats, SSRs) also have dual roles: as critical markers and as essential elements of the eukaryotic genome. To characterize the profile of SSRs and develop molecular markers, the high-quality assembled genome of A. trifoliata was used. Additionally, to determine the potential transferability of SSR loci, the genomes of Amborella trichopoda, Oryza sativa, Vitis vinifera, Arabidopsis thaliana, Papaver somniferum, and Aquilegia coerulea were also used. We identified 434,293 SSRs with abundant short repeats, such as 290,868 (66.98%) single-nucleotide repeats (SNRs) and 113,299 (26.09%) dinucleotide repeats (DNRs) in the A. trifoliata genome. 398,728 (91.81%) SSRs on 344,283 loci were physically mapped on the chromosomes, and a positive correlation (r = 0.98) was found between the number of SSRs and chromosomal length. Additionally, 342,916 (99.60%) potential SSR markers could be designed from the 344,283 physically mapped loci, while only 36,160 could be viewed as high-polymorphism-potential (HPP) markers, findings that were validated by PCR. Finally, SSR loci exhibited broad potential transferability, particularly DNRs such as the "AT/AT" and "AG/CT" loci, among all angiosperms, a finding that was not related to the genetic divergence distance. Practically, we developed a whole set of effective, polymorphic, and physically anchored molecular markers and found that, evolutionarily, DNRs could be responsible for microsatellite origin and protecting gene function.

Fragmentation and transferability in Hirshfeld atom refinement

Hirshfeld atom refinement (HAR) is one of the most effective methods for obtaining accurate structural parameters for hydrogen atoms from X-ray diffraction data. Unfortunately, it is also relatively computationally expensive, especially for larger molecules due to wavefunction calculations. Here, a fragmentation approach has been tested as a remedy for this problem. It gives an order of magnitude improvement in computation time for larger organic systems and is a few times faster for metal-organic systems at the cost of only minor differences in the calculated structural parameters when compared with the original HAR calculations. Fragmentation was also applied to polymeric and disordered systems where it provides a natural solution to problems that arise when HAR is applied. The concept of fragmentation is closely related to the transferable aspherical atom model (TAAM) and allows insight into possible ways to improve TAAM. Hybrid approaches combining fragmentation with the transfer of atomic densities between chemically similar atoms have been tested. An efficient handling of intermolecular interactions was also introduced for calculations involving fragmentation. When applied in fragHAR (a fragmentation approach for polypeptides) as a replacement for the original approach, it allowed for more efficient calculations. All of the calculations were performed with a locally modified version of Olex2 combined with a development version of discamb2tsc and ORCA. Care was taken to efficiently use the power of multicore processors by simple implementation of load-balancing, which was found to be very important for lowering computational time.

Toward universal substituent constants: Transferability of group descriptors from the quantum theory of atoms in molecules

Traditionally, substituents are described not by their intrinsic properties, but by their effect elsewhere in a molecule. However, the quantum theory of atoms in molecules (QTAIM) provides a route to intrinsic substituent descriptors. Ideally, these descriptors would exhibit minimal change as the local environment changes, and hence be considered transferable. Whether this is true is an open question. Here, we evaluated the transferability of QTAIM functional group descriptors for 117 functional groups in a series of 17 substrates to determine whether descriptors obtained using hydrogen as substrate are transferable. The functional group volume has a strong, consistent, linear relationship throughout. All other hydrogen-based group descriptors exhibit a relatively strong linear relationship with those in carbon-based substrates and a reasonable linear relationship with those in non-carbon-based substrates. Outliers are readily interpretable in terms of substrate induced functional group geometry changes. As expected, directional descriptors lying along the substituent-substrate axis are the least conserved.

Transferability of tigecycline resistance: Characterization of the expanding Tet(X) family

Tetracycline and its derivative tigecycline are clinical options against Gram-negative bacterial infections. The emergence of mobile Tet(X) enzymes that destruct tetracycline-type antibiotics is posing a big challenge to antibacterial therapy and food/environmental securities. Here, we present an update on a growing number of Tet(X) variants. We describe structure and action of Tet(X) enzyme, and discuss the evolutional origin. In addition, potential Tet(X) inhibitors are given. This mini-review might benefit better understanding of Tet(X)-mediated tigecycline resistance. This article is categorized under: Infectious Diseases > Genetics/Genomics/Epigenetics Infectious Diseases > Environmental Factors Infectious Diseases > Molecular and Cellular Physiology.

A Principal Component Informed Approach to Address Polygenic Risk Score Transferability Across European Cohorts

One important confounder in genome-wide association studies (GWASs) is population genetic structure, which may generate spurious associations if not properly accounted for. This may ultimately result in a biased polygenic risk score (PRS) prediction, especially when applied to another population. To explore this matter, we focused on principal component analysis (PCA) and asked whether a population genetics informed strategy focused on PCs derived from an external reference population helps in mitigating this PRS transferability issue. Throughout the study, we used two complex model traits, height and body mass index, and samples from UK and Estonian Biobanks. We aimed to investigate 1) whether using a reference population (1000G) for computation of the PCs adjusted for in the discovery cohort improves the resulting PRS performance in a target set from another population and 2) whether adjusting the validation model for PCs is required at all. Our results showed that any other set of PCs performed worse than the one computed on samples from the same population as the discovery dataset. Furthermore, we show that PC correction in GWAS cannot prevent residual population structure information in the PRS, also for non-structured traits. Therefore, we confirm the utility of PC correction in the validation model when the investigated trait shows an actual correlation with population genetic structure, to account for the residual confounding effect when evaluating the predictive value of PRS.

Improving the Transferability of Adversarial Examples With a Noise Data Enhancement Framework and Random Erasing

Deep neural networks (DNNs) are proven vulnerable to attack against adversarial examples. Black-box transfer attacks pose a massive threat to AI applications without accessing target models. At present, the most effective black-box attack methods mainly adopt data enhancement methods, such as input transformation. Previous data enhancement frameworks only work on input transformations that satisfy accuracy or loss invariance. However, it does not work for other transformations that do not meet the above conditions, such as the transformation which will lose information. To solve this problem, we propose a new noise data enhancement framework (NDEF), which only transforms adversarial perturbation to avoid the above issues effectively. In addition, we introduce random erasing under this framework to prevent the over-fitting of adversarial examples. Experimental results show that the black-box attack success rate of our method Random Erasing Iterative Fast Gradient Sign Method (REI-FGSM) is 4.2% higher than DI-FGSM in six models on average and 6.6% higher than DI-FGSM in three defense models. REI-FGSM can combine with other methods to achieve excellent performance. The attack performance of SI-FGSM can be improved by 22.9% on average when combined with REI-FGSM. Besides, our combined version with DI-TI-MI-FGSM, i.e., DI-TI-MI-REI-FGSM can achieve an average attack success rate of 97.0% against three ensemble adversarial training models, which is greater than the current gradient iterative attack method. We also introduce Gaussian blur to prove the compatibility of our framework.

Development and Application of EST-SSR Markers in Cephalotaxus oliveri From Transcriptome Sequences

Cephalotaxus oliveri is an endemic conifer of China, which has medicinal and ornamental value. However, the limited molecular markers and genetic information are insufficient for further genetic studies of this species. In this study, we characterized and developed the EST-SSRs from transcriptome sequences for the first time. The results showed that a total of 5089 SSRs were identified from 36446 unigenes with a density of one SSR per 11.1 kb. The most common type was trinucleotide repeats, excluding mononucleotide repeats, followed by dinucleotide repeats. AAG/CTT and AT/AT exhibited the highest frequency in the trinucleotide and dinucleotide repeats, respectively. Of the identified SSRs, 671, 1125, and 1958 SSRs were located in CDS, 3′UTR, and 5′UTR, respectively. Functional annotation showed that the SSR-containing unigenes were involved in growth and development with various biological functions. Among successfully designed primer pairs, 238 primer pairs were randomly selected for amplification and validation of EST-SSR markers and 47 primer pairs were identified as polymorphic. Finally, 28 high-polymorphic primers were used for genetic analysis and revealed a moderate level of genetic diversity. Seven natural C. oliveri sampling sites were divided into two genetic groups. Furthermore, the 28 EST-SSRs had 96.43, 71.43, and 78.57% of transferability rate in Cephalotaxus fortune, Ametotaxus argotaenia, and Pseudotaxus chienii, respectively. These markers developed in this study lay the foundation for further genetic and adaptive evolution studies in C. oliveri and related species.

Mechanisms and context in the San Patrignano drug recovery community, Italy: a qualitative study to inform transfer to Scotland

The San Patrignano drug recovery community, Italy, is regarded as one of the most successful in the world. However, if this model is to be transferred to other countries, it is necessary to clarify its underlying mechanisms and how far their success is context dependent. This qualitative study investigated these features of the San Patrignano model. Data collection included semi-structured interviews with six key stakeholders and 10 days’ observational field notes. Data were synthesised using frameworks and analysis was informed by realist principles. Individual level mechanisms include: commitment to change, removal from former social environment, communal living, peer mentor with lived experience and meaningful work. These operate in the context of a free of charge, long term (3–4 year) residential community. Organisational level mechanisms are: visionary leadership, staff dedication, social enterprise and adaptable learning. Organisational contextual factors include: a gap in suitable provision for drug recovery and the region’s high level of social capital. Articulating the programme theory of the recovery model and its contextual dependency helps clarify which elements should be transferred and how far they need to be adapted for different socio-cultural settings. The recognition of context is crucial when considering transfer of effective complex interventions across countries.

Transferability of neural network clinical deidentification systems

OBJECTIVE

Neural network deidentification studies have focused on individual datasets. These studies assume the availability of a sufficient amount of human-annotated data to train models that can generalize to corresponding test data. In real-world situations, however, researchers often have limited or no in-house training data. Existing systems and external data can help jump-start deidentification on in-house data; however, the most efficient way of utilizing existing systems and external data is unclear. This article investigates the transferability of a state-of-the-art neural clinical deidentification system, NeuroNER, across a variety of datasets, when it is modified architecturally for domain generalization and when it is trained strategically for domain transfer.

MATERIALS AND METHODS

We conducted a comparative study of the transferability of NeuroNER using 4 clinical note corpora with multiple note types from 2 institutions. We modified NeuroNER architecturally to integrate 2 types of domain generalization approaches. We evaluated each architecture using 3 training strategies. We measured transferability from external sources; transferability across note types; the contribution of external source data when in-domain training data are available; and transferability across institutions.

RESULTS AND CONCLUSIONS

Transferability from a single external source gave inconsistent results. Using additional external sources consistently yielded an F1-score of approximately 80%. Fine-tuning emerged as a dominant transfer strategy, with or without domain generalization. We also found that external sources were useful even in cases where in-domain training data were available. Transferability across institutions differed by note type and annotation label but resulted in improved performance.

Rapid Screening of Metal-Organic Frameworks for Propane/Propylene Separation by Synergizing Molecular Simulation and Machine Learning

At present, 100 000+ metal-organic frameworks (MOFs) have been synthesized, and it is challenging to identity the best candidate for a specific application. In this study, MOFs are rapidly screened via a hierarchical approach for propane/propylene (C₃H₈/C₃H₆) separation. First, the adsorption capacity and selectivity of C₃H₈/C₃H₆ mixture in "Computation-Ready, Experimental" (CoRE) MOFs are predicted via a molecular simulation (MS) method. The relationships between separation metrics and structural factors are established, and top-performing CoRE MOFs are identified. Then, machine learning (ML) models are trained and developed upon the CoRE MOFs using pore size, pore geometry, and framework chemistry as feature descriptors. By introducing binned pore size distributions and geometric descriptors, the accuracy of ML models is substantially improved. The feature importance of the descriptors is physically interpreted by the Gini impurities and Shapley Additive Explanations. Subsequently, the ML models are used to rapidly screen experimental "Cambridge Structural Database" (CSD) MOFs and hypothetical MOFs for C₃H₈/C₃H₆ separation. In the CSD MOFs, the out-of-sample predictions are found to agree well with simulation results, demonstrating the excellent transferability of the ML models from the CoRE to CSD MOFs. Moreover, nine CSD MOFs are identified to possess separation performance superior to top-performing CoRE MOFs. Finally, the similarity and diversity among experimental and hypothetical MOFs are visualized and compared by the t-Distributed Stochastic Neighbor Embedding (t-SNE) feature projections. Remarkably, the CoRE and CSD MOFs are revealed to share a close similarity in both chemical and geometric feature spaces. By synergizing MS and ML, the hierarchical approach developed in this study would advance the rapid screening of MOFs across different databases toward industrially important separation processes.

Assessing the Transferability of Physical Activity Type Detection Models: Influence of Age Group Is Underappreciated

Increasing the amount of physical activity (PA) in older adults that have shifted to a sedentary lifestyle is a determining factor in decreasing health and social costs. It is, therefore, imperative to develop objective methods that accurately detect daily PA types and provide detailed PA guidance for healthy aging. Most of the existing techniques have been applied in the younger generation or validated in the laboratory. To what extent, these methods are transferable to real-life and older adults are a question that this paper aims to answer. Sixty-three participants, including 33 younger and 30 older healthy adults, participated in our study. Each participant wore five devices mounted on the left and right hips, right knee, chest, and left pocket and collected accelerometer and GPS data in both semi-structured and real-life environments. Using this dataset, we developed machine-learning models to detect PA types walking, non-level walking, jogging/running, sitting, standing, and lying. Besides, we examined the accuracy of the models within-and between-age groups applying different scenarios and validation approaches. The within-age models showed convincing classification results. The findings indicate that due to age-related behavioral differences, there are more confusion errors between walking, non-level walking, and running in older adults’ results. Using semi-structured training data, the younger adults’ models outperformed older adults’ models. However, using real-life training data alone or in combination with semi-structured data generated better results for older adults who had high real-life data quality. Assessing the transferability of the models to older adults showed that the models trained with younger adults’ data were only weakly transferable. However, training the models with a combined dataset of both age groups led to reliable transferability of results to the data of the older subgroup. We show that age-related behavioral differences can alter the PA classification performance. We demonstrate that PA type detection models that rely on combined datasets of young and older adults are strongly transferable to real-life and older adults’ data. Our results yield significant time and cost savings for future PA studies by reducing the overall volume of training data required.

Dissection of Highly Prevalent qnrS1-Carrying IncX Plasmid Types in Commensal Escherichia coli from German Food and Livestock

Plasmids are mobile genetic elements, contributing to the spread of resistance determinants by horizontal gene transfer. Plasmid-mediated quinolone resistances (PMQRs) are important determinants able to decrease the antimicrobial susceptibility of bacteria against fluoroquinolones and quinolones. The PMQR gene qnrS1, especially, is broadly present in the livestock and food sector. Thus, it is of interest to understand the characteristics of plasmids able to carry and disseminate this determinant and therewith contribute to the resistance development against this class of high-priority, critically important antimicrobials. Therefore, we investigated all commensal Escherichia (E.) coli isolates, with reduced susceptibility to quinolones, recovered during the annual zoonosis monitoring 2017 in the pork and beef production chain in Germany (n = 2799). Through short-read whole-genome sequencing and bioinformatics analysis, the composition of the plasmids and factors involved in their occurrence were determined. We analysed the presence and structures of predominant plasmids carrying the PMQR qnrS1. This gene was most frequently located on IncX plasmids. Although the E. coli harbouring these IncX plasmids were highly diverse in their sequence types as well as their phenotypic resistance profiles, the IncX plasmids-carrying the qnrS1 gene were rather conserved. Thus, we only detected three distinct IncX plasmids carrying qnrS1 in the investigated isolates. The IncX plasmids were assigned either to IncX1 or to IncX3. All qnrS1-carrying IncX plasmids further harboured a β-lactamase gene (bla). In addition, all investigated IncX plasmids were transmissible. Overall, we found highly heterogenic E. coli harbouring conserved IncX plasmids as vehicles for the most prevalent qnr gene qnrS1. These IncX plasmids may play an important role in the dissemination of those two resistance determinants and their presence, transfer and co-selection properties require a deeper understanding for a thorough risk assessment.

Applicability of organ-on-chip systems in toxicology and pharmacology

Organ-on-chip (OoC) systems are microfabricated cell culture devices designed to model functional units of human organs by harboring an in vitro generated organ surrogate. In the present study, we reviewed issues and opportunities related to the application of OoC in the safety and efficacy assessment of chemicals and pharmaceuticals, as well as the steps needed to achieve this goal. The relative complexity of OoC over simple in vitro assays provides advantages and disadvantages in the context of compound testing. The broader biological domain of OoC potentially enhances their predictive value, whereas their complexity present issues with throughput, standardization and transferability. Using OoCs for regulatory purposes requires detailed and standardized protocols, providing reproducible results in an interlaboratory setting. The extent to which interlaboratory standardization of OoC is feasible and necessary for regulatory application is a matter of debate. The focus of applying OoCs in safety assessment is currently directed to characterization (the biology represented in the test) and qualification (the performance of the test). To this aim, OoCs are evaluated on a limited scale, especially in the pharmaceutical industry, with restricted sets of reference substances. Given the low throughput of OoC, it is questionable whether formal validation, in which many reference substances are extensively tested in different laboratories, is feasible for OoCs. Rather, initiatives such as open technology platforms, and collaboration between OoC developers and risk assessors may prove an expedient strategy to build confidence in OoCs for application in safety and efficacy assessment.

The Effect of Forward Testing as a Function of Test Occasions and Study Material

It has long been known that one of the most effective study techniques is to be tested on the to-be-remembered material, a phenomenon known as the testing effect. Recent research has also shown that testing of previous materials promotes the learning of new materials, a phenomenon known as the forward testing effect. In this paper, as of yet unexplored aspects of the forward testing effect related to face-name learning are examined; continuous and initial testing are compared to restudying, the effects of an initial test on subsequent learning, and whether an initial change of domain (change from one topic to another) regarding study material affects the robustness of the effect. An experiment (N = 94) was performed according to a 2 (Material: word pairs/face-name pairs in Block 1) × 3 (Test occasions: Blocks 1–4/Blocks 1 and 4/Block 4) complex between-groups design. The results showed that no difference between testing and repetition could be observed regarding the recall of faces and names. The restudy groups incorrectly recalled more names from previous lists in the last interim test compared to the tested groups, which supports the theory that interim tests reduce proactive interference. The results also suggest that the number of test occasions correlates with the number of incorrect recalls from previous lists. These results, in contrast to previous studies, highlight a potential uncertainty about the forward testing effect linked to the robustness of the phenomenon, the specificity in execution, and generalizability.

Multiple Health Behavior Programs in School Settings: Strategies to Promote Transfer-of-Learning Through Life Skills Education

Typically, schools implement health promotion programs that focus on a single behavioral domain. Multiple related health topics may be addressed using separate interventions, potentially producing overlap in program content. However, integrative approaches in health promotion have the potential to produce interventions capable of improving multiple health behaviors. In particular, more research is needed to identify the conditions and the factors that can promote the transfer of learning to broaden the target outcomes of health promotion programs. The present study aims to identify the characteristics of an evidence-based life skills education program that can facilitate the transfer of learning to different health behaviors not initially targeted by the program, and the strategies for achieving successful transfer. A two round Delphi method was used with a diverse group of 21 experts in health promotion, life skills education, and methods of pedagogy for early adolescent students. Questionnaires with open and closed-ended questions were administered on-line. Content qualitative analysis was run, integrating codes, subcategories, and categories of the two rounds of the study. Results showed strong consensus among experts about the potential for promoting the transfer of skills from one health domain to another. Many elements were identified as important factors that facilitate the transfer of learning. Strategies for successful transfer were related to teaching methods, educational approaches, and consistency with the broader school curriculum. Findings suggest that the successful transfer of learning to a new health domain requires that educators recognize its importance and explicitly designate it as an educational aim.

Determinants of habitat suitability models transferability across geographically disjunct populations: Insights from Vipera ursinii urs inii

Transferability of habitat suitability models (HSMs), essential to accurately predict outside calibration conditions, has been seldom investigated at intraspecific level. We targeted Vipera ursinii ursinii, a meadow viper from southeastern France and central Italy, to assess determinants of transferability among geographically disjunct populations. We fitted HSMs upon occurrences of the Italian and French populations separately, as well as on the combined occurrence dataset. Internal transferability of HSMs, on spatially independent test data drawn from the calibration region, and their external transferability on the geographically disjunct populations were evaluated according to (a) use of full or spatially rarefied presence datasets; (b) ecology-driven or statistics-driven filtering of predictors; (c) modeling algorithm, testing generalized additive models and gradient boosting models; and (d) multivariate environmental novelty within test data. Niche overlap between French and Italian populations was also tested. Niche overlap was low, but niche divergence between the two populations' clusters was not corroborated. Nonetheless, wider niche breadth and heterogeneity of background environmental conditions characterizing the French populations led to low intercluster transferability. Although models fitted on the combined datasets did not attain consistently higher internal transferability than those separately fitted for the French and Italian populations, ensemble projection from the HSMs fitted on the joint occurrences produced more consistent suitability predictions across the full range of V. u. ursinii. Spatial thinning of occurrences ameliorated internal transferability but did not affect external transferability. The two approaches to predictors filtering did not differ in transferability of the respective HSMs but led to discrepant estimated environment-occurrence relationships and spatial predictions, while the two algorithms attained different relative rankings depending on the considered prediction task. Multivariate novelty of projection sites was negatively correlated to both internal transferability and external transferability. Our findings clarify issues researchers should keep in mind when using HSMs to get predictions across geographically disjunct populations.

Genome-Wide Identification and Development of LTR Retrotransposon-Based Molecular Markers for the Melilotus Genus

Melilotus is an important genus of legumes with industrial and medicinal value, partly due to the production of coumarin. To explore the genetic diversity and population structure of Melilotus, 40 accessions were analyzed using long terminal repeat (LTR) retrotransposon-based markers. A total of 585,894,349 bp of LTR retrotransposon sequences, accounting for 55.28% of the Melilotus genome, were identified using bioinformatics tools. A total of 181,040 LTR retrotransposons were identified and classified as Gypsy, Copia, or another type. A total of 350 pairs of primers were designed for assessing polymorphisms in 15 Melilotus albus accessions. Overall, 47 polymorphic primer pairs were screened for their availability and transferability in 18 Melilotus species. All the primer pairs were transferable, and 292 alleles were detected at 47 LTR retrotransposon loci. The average polymorphism information content (PIC) value was 0.66, which indicated that these markers were highly informative. Based on unweighted pair group method with arithmetic mean (UPGMA) dendrogram cluster analysis, the 18 Melilotus species were classified into three clusters. This study provides important data for future breeding programs and for implementing genetic improvements in the Melilotus genus.

Coping strategies: Seeking personalized care in relapsing-remitting multiple sclerosis. A patient reported measure-coping responses inventory

Coping is defined as a set of cognitive and behavioral efforts made to master stressful specific demands. Adaptation to chronic diseases, such as Multiple Sclerosis (MS), depends on the effectiveness of coping.

Objective: To assess the psychometric properties of the Coping Responses Inventory (CRI-A) in persons with MS (PwMS), verifying the transferability of the measure, already validated in the Argentine general population, and to describe the types of coping strategies available for PwMS.

Methods: 90 PwMS were included.

Outcome measures: CRI-A Inventory, Expanded Disability Status Scale (EDSS), Beck Depression Inventory, Fatigue Severity Scale and MS International Quality of Life questionnaire.

Results: Descriptive data is as follows: mean age (years): 40.97 ± 12.85; years of education: 13.46 ± 3.93; EDSS: 2.48 ± 1.79; disease evolution (years): 10.76 ± 9.72; depression: 13.92 ± 10.45; fatigue 3.77 ± 1.72. The psychometric properties of the CRI-A Inventory observed in the Argentine general population are present in the MS sample as well, with adequate validity and reliability. The respondents most frequently utilized a problem-focused coping style.

Conclusions: Results showed the CRI-A has good transferability properties from the Argentine general population to the MS population.

Improved prediction of Canada lynx distribution through regional model transferability and data efficiency

The application of species distribution models (SDMs) to areas outside of where a model was created allows informed decisions across large spatial scales, yet transferability remains a challenge in ecological modeling. We examined how regional variation in animal-environment relationships influenced model transferability for Canada lynx (Lynx canadensis), with an additional conservation aim of modeling lynx habitat across the northwestern United States. Simultaneously, we explored the effect of sample size from GPS data on SDM model performance and transferability. We used data from three geographically distinct Canada lynx populations in Washington (n = 17 individuals), Montana (n = 66), and Wyoming (n = 10) from 1996 to 2015. We assessed regional variation in lynx-environment relationships between these three populations using principal components analysis (PCA). We used ensemble modeling to develop SDMs for each population and all populations combined and assessed model prediction and transferability for each model scenario using withheld data and an extensive independent dataset (n = 650). Finally, we examined GPS data efficiency by testing models created with sample sizes of 5%-100% of the original datasets. PCA results indicated some differences in environmental characteristics between populations; models created from individual populations showed differential transferability based on the populations' similarity in PCA space. Despite population differences, a single model created from all populations performed as well, or better, than each individual population. Model performance was mostly insensitive to GPS sample size, with a plateau in predictive ability reached at ~30% of the total GPS dataset when initial sample size was large. Based on these results, we generated well-validated spatial predictions of Canada lynx distribution across a large portion of the species' southern range, with precipitation and temperature the primary environmental predictors in the model. We also demonstrated substantial redundancy in our large GPS dataset, with predictive performance insensitive to sample sizes above 30% of the original.