Beyond the surface: Exploring the temporally stable factors influencing injury severities in large-truck crashes using mixed logit models.

An analysis of crash data spanning four years (January 1, 2015, to December 31, 2018) from the State of Washington is conducted to investigate factors influencing injury severity outcomes in large truck-involved crashes. The study utilizes a mixed logit model that accounts for unobserved heterogeneity to capture the variation influenced by other variables. Transferability and temporal stability across the years are assessed using the likelihood ratio test. A wide range of attributes, including driver characteristics, vehicle features, crash-related attributes, roadway conditions, environmental factors, and temporal elements, are considered. Despite a significant temporal instability warranted by the likelihood ratio test across the years, twenty-one parameters consistently exhibit stable effects on injury severity over the years of which thirteen are new. The identified stable parameters included over speeding, following too closely, falling asleep, missing/ faulty airbags, head-on collisions, crashes involving two or more than three vehicles, rear-end collisions, lane width, low-light conditions, sag curves, New Jersey barriers, snowy weather, and morning hours. The temporally stable factors affecting injury severities in large truck crashes are crucial in developing the needed to address these crashes. The findings of this study offer valuable insights for researchers, stakeholders in the trucking industry, and policymakers, empowering them to develop targeted policies that not only improve traffic safety but also alleviate associated economic losses.

Core principles of Malakit intervention for transferability in other contexts.

To eliminate malaria, all populations must be included. For those who are not reached by the health care system, specific interventions must be tailor-made. An innovative Malakit strategy, based on the distribution of self-diagnosis and self-treatment kits, has been evaluated in the Suriname-French Guiana- Amapá (Brazil) region. The results showed effectiveness and good acceptability. The Malakit intervention is complex and has many components. Its transferability requires adaptation to other populations and regions, while retaining the main features of the intervention. This article provides the keys to adapting, implementing and evaluating it in other contexts facing residual malaria in hard-to-reach and/or mobile populations. The process of transferring this intervention includes: diagnosis of the situation (malaria epidemiology, characteristics of the population affected) to define the relevance of the strategy; determination of the stakeholders and the framework of the intervention (research project or public health intervention); adaptation modalities (adaptation of the kit, training, distribution strategy); the role of community health workers and their need for training and supervision. Finally, evaluation needs are specified in relation to prospects for geographical or temporal extension. Malaria elimination is likely to increasingly involve marginalized people due to climate change and displacement of populations. Evaluation of the transferability and effectiveness of the Malakit strategy in new contexts will be essential to increase and refine the evidence of its value, and to decide whether it could be an additional tool in the arsenal recommended in future WHO guidelines.

Rigorous Progress in Coarse-Graining.

Low-resolution coarse-grained (CG) models provide remarkable computational and conceptual advantages for simulating soft materials. In principle, bottom-up CG models can reproduce all structural and thermodynamic properties of atomically detailed models that can be observed at the resolution of the CG model. This review discusses recent progress in developing theory and computational methods for achieving this promise. We first briefly review variational approaches for parameterizing interaction potentials and their relationship to machine learning methods. We then discuss recent approaches for simultaneously improving both the transferability and thermodynamic properties of bottom-up models by rigorously addressing the density and temperature dependence of these potentials. We also briefly discuss exciting progress in modeling high-resolution observables with low-resolution CG models. More generally, we highlight the essential role of the bottom-up framework not only for fundamentally understanding the limitations of prior CG models but also for developing robust computational methods that resolve these limitations in practice.

Microfluidic capillary electrophoresis - mass spectrometry for rapid charge-variant and glycoform assessment of monoclonal antibody biosimilar candidates.

Early-stage cell line screening is a vital step in developing biosimilars of therapeutic monoclonal antibodies (mAbs). While the quality of the manufactured antibodies is commonly assessed by charge-based separation methods employing UV absorbance detection, these methods lack the ability to identify resolved mAb variants. We evaluated the performance of microfluidic capillary electrophoresis coupled to mass spectrometry (MCE-MS) as a rapid tool for profiling mAb biosimilar candidates from clonal cell lines. A representative originator sample was used to develop the MCE-MS method. The addition of dimethylsulfoxide (DMSO) to the background electrolyte yielded up to 60-fold enhancement of the protein MS signal. The resulting electropherograms consistently provided resolution of mAb charge variants within 10 min. Deconvoluted mass spectra facilitated the identification of basic variants such as C-terminal lysine and proline amidation, while the acidic variants could be assigned to deamidated forms. The MCE-MS method also allowed the identification of 18 different glycoforms in biosimilar samples. To mimic early-stage cell line selection, samples from five clonal cell lines that all expressed the same biosimilar candidate mAb were compared to their originator mAb. Based on the similarity observed in charge variants and glycoform profiles acquired by MCE-MS, the most promising candidate could be selected. The MCE-MS method demonstrated good overall reproducibility, as confirmed by a transferability study involving two separate laboratories. This study highlights the efficacy of the MCE-MS method for rapid proteoform screening of clonal cell line samples, underscoring its potential significance as an analytical tool in biosimilar process development.

FDAA: A feature distribution-aware transferable adversarial attack method.

In recent years, the research on transferable feature-level adversarial attack has become a hot spot due to attacking unknown deep neural networks successfully. But the following problems limit its transferability. Existing feature disruption methods often focus on computing feature weights precisely, while overlooking the noise influence of feature maps, which results in disturbing non-critical features. Meanwhile, geometric augmentation algorithms are used to enhance image diversity but compromise information integrity, which hamper models from capturing comprehensive features. Furthermore, current feature perturbation could not pay attention to the density distribution of object-relevant key features, which mainly concentrate in salient region and fewer in the most distributed background region, and get limited transferability. To tackle these challenges, a feature distribution-aware transferable adversarial attack method, called FDAA, is proposed to implement distinct strategies for different image regions in the paper. A novel Aggregated Feature Map Attack (AFMA) is presented to significantly denoise feature maps, and an input transformation strategy, called Smixup, is introduced to help feature disruption algorithms to capture comprehensive features. Extensive experiments demonstrate that scheme proposed achieves better transferability with an average success rate of 78.6% on adversarially trained models.

Transferability of the NHS low-calorie diet programme: A qualitative exploration of factors influencing the programme's transfer ahead of wide-scale adoption.

INTRODUCTION: Although behavioural interventions have been found to help control type 2 diabetes (T2D), it is important to understand how the delivery context can influence implementation and outcomes. The NHS committed to testing a low-calorie diet (LCD) programme designed to support people living with excess weight and T2D to lose weight and improve diabetes outcomes. Understanding what influenced implementation during the programme pilot is important in optimising rollout. This study explored the transferability of the NHS LCD Programme prior to wider adoption. METHODS: Twenty-five interviews were undertaken with stakeholders involved in implementing the LCD programme in pilot sites (health service leads, referring health professionals and programme deliverers). Interviews with programme participants (people living with T2D) were undertaken within a larger programme of work, exploring what worked, for whom and why, which is reported separately. The conceptual Population-Intervention-Environment-Transfer Model of Transferability (PIET-T) guided study design and data collection. Constructs of the model were also used as a deductive coding frame during data analysis. Key themes were identified which informed recommendations to optimise programme transfer. RESULTS: Population: Referral strategies in some areas lacked consideration of population characteristics. Many believed that offering a choice of delivery model would promote acceptability and accessibility of the eligible population. INTERVENTION: Overall, stakeholders had confidence in the LCD programme due to the robust evidence base along with anecdotal evidence, but some felt the complex referral process hindered engagement from GP practices. ENVIRONMENT: Stakeholders described barriers to accessing the programme, including language and learning difficulties. Transferability: Multidisciplinary working and effective communication supported successful implementation. CONCLUSION: Referral strategies to reach underrepresented groups should be considered during programme transfer, along with timely data from service providers on access and programme benefits. A choice of delivery models may optimise uptake. Knowledge sharing between sites on good working practices is encouraged, including increasing engagement with key stakeholders.

The effect of 3D printing speed and temperature on transferability of Staphylococcus aureus and Escherichia coli during 3D food printing.

The current study aimed to determine if the 3D-printing speed and temperature would impact the transferability of foodborne pathogens from the stainless-steel (SS) food cartridge to the 3D-printed food ink. Staphylococcus aureus and Escherichia coli were inoculated onto the interior surface of the SS food cartridges. Subsequently, a model food ink was extruded with a recommended macronutrient contribution of 55.8, 23.7, and 20.5% of carbohydrates, proteins, and fat, respectively. The impact of 3D-printing temperatures and speeds on transfer rates was analysed using a Two-Way ANOVA. S. aureus was transferred more from the cartridge to the food ink with a population of 3.39, 2.98, and 3.09 log CFU/g compared to 2.03, 2.06, and 2.00 log CFU/g for E. coli at 2000, 3000, and 4000 mm/s printing speed, respectively, at 25 °C. A Kruskal-Wallis Test was employed to investigate the effect of different speeds and temperatures on the transferability of S. aureus and E. coli. Speed was the main factor affecting S. aureus transferability, while temperature (25 and 50 °C) had the greatest impact on E. coli transferability. This research seeks to advance the understanding of 3D-printing parameters in pathogen transferability and help the food industry move towards this technology's quick and safe adoption.

Field assessment of active ingredient quantity in pharmaceutical tablets with limited calibration of near infrared spectra: An application to ciprofloxacin tablets.

Portable near-infrared (NIR) spectrophotometers have emerged as valuable tools for identifying substandard and falsified pharmaceuticals (SFPs). Integration of these devices with chemometric and machine learning models enhances their ability to provide quantitative chemical insights. However, different NIR spectrophotometer models vary in resolution, sensitivity, and responses to environmental factors such as temperature and humidity, necessitating instrument-specific libraries that hinder the wider adoption of NIR technology. This study addresses these challenges and seeks to establish a robust approach to promote the use of NIR technology in post-market pharmaceutical analysis. We developed support vector machine and partial least squares regression models based on binary mixtures of lab-made ciprofloxacin and microcrystalline cellulose, then applied the models to ciprofloxacin dosage forms that were assayed with high performance liquid chromatography (HPLC). A receiver operating characteristic (ROC) analysis was performed to set spectrophotometer independent NIR metrics to evaluate ciprofloxacin dosage forms as "meets standard," "needs HPLC assay," or "fails standard." Over 200 ciprofloxacin tablets representing 50 different brands were evaluated using spectra acquired from three types of NIR spectrophotometer with 85% of the prediction agreeing with HPLC testing. This study shows that non-brand-specific predictive models can be applied across multiple spectrophotometers for rapid screening of the conformity of pharmaceutical active ingredients to regulatory standard.

Transferability of Machine Learning Models for Geogenic Contaminated Groundwaters.

Machine learning models show promise in identifying geogenic contaminated groundwaters. Modeling in regions with no or limited samples is challenging due to the need for large training sets. One potential solution is transferring existing models to such regions. This study explores the transferability of high fluoride groundwater models between basins in the Shanxi Rift System, considering six factors, including modeling methods, predictor types, data size, sample/predictor ratio (SPR), predictor range, and data informing. Results show that transferability is achieved only when model predictors are based on hydrochemical parameters rather than surface parameters. Data informing, i.e., adding samples from challenging regions to the training set, further enhances the transferability. Stepwise regression shows that hydrochemical predictors and data informing significantly improve transferability, while data size, SPR, and predictor range have no significant effects. Additionally, despite their stronger nonlinear capabilities, random forests and artificial neural networks do not necessarily surpass logistic regression in transferability. Lastly, we utilize the t-SNE algorithm to generate low-dimensional representations of data from different basins and compare these representations to elucidate the critical role of predictor types in transferability.

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.

Enhancement of spectral model transferability in LIBS systems through LIBS-LIPAS fusion technique.

BACKGROUND: Laser-induced breakdown spectroscopy (LIBS) is extensively utilized a range of scientific and industrial detection applications owing to its capability for rapid, in-situ detection. However, conventional LIBS models are often tailored to specific LIBS systems, hindering their transferability between LIBS subsystems. Transfer algorithms can adapt spectral models to subsystems, but require access to the datasets of each subsystem beforehand, followed by making individual adjustments for the dataset of each subsystem. It is clear that a method to enhance the inherent transferability of spectral original models is urgently needed. RESULTS: We proposed an innovative fusion methodology, named laser-induced breakdown spectroscopy fusion laser-induced plasma acoustic spectroscopy (LIBS-LIPAS), to enhance the transferability of support vector machine (SVM) original models across LIBS systems with varying laser beams. The methodology was demonstrated using nickel-based high-temperature alloy samples. Here, the area-full width at half maximum (AFCEI) Composite Evaluation Index was proposed for extracting critical features from LIBS. Further enhancing the transferability of the model, the laser-induced plasma acoustic signal was transformed from the time domain to the frequency domain. Subsequently, the feature-level fusion method was employed to improve the classification accuracy of the transferred LIBS system to 97.8 %. A decision-level fusion approach (amalgamating LIBS, LIPAS, and feature-level fusion models) achieved an exemplary accuracy of 99 %. Finally, the adaptability of the method was demonstrated using titanium alloy samples. SIGNIFICANCE AND NOVELTY: In this work, based on plasma radiation models, we simultaneously captured LIBS and LIPAS, and proposed the fusion of these two distinct yet origin-consistent signals, significantly enhancing the transferability of the LIBS original model. The methodology proposed holds significant potential to advance LIBS technology and broaden its applicability in analytical chemistry research and industrial applications.

Supporting the applicability and transferability of the "Sortir Ensemble & Se Respecter" program in France / Accompagner l'applicabilité et la transférabilité du programme « Sortir Ensemble & Se Respecter ¼ en Frances

INTRODUCTION: The prevention of intimate partner violence (IPV) among young people is a major challenge for public policies. Nevertheless, there are a few prevention programs that have proven effective in France. "Sortir Ensemble & Se Respecter" (SE&SR) is a Swiss adaptation of "Safe Dates," an American intervention program that has reduced violent behavior by young perpetrators and victims of IPV alike. The aim of this article is to analyze the applicability and "potential transferability" of SE&SR in France. METHODS: We described the SE&SR intervention by explaining the intervention theory, the key functions (i.e., the "ingredients" allowing the SE&SR program to work), and we commented on its applicability from a perspective of adapting and transferring it to the French context. We used the ASTAIRE tool and the FIC (key functions, implementation, context) approach. RESULTS: The intervention theory highlighted various factors, acting at the individual level (i.e., beliefs/representations, knowledge, life skills) and at the level of the living environment (i.e., facilities welcoming young people; families; public policies; networks of actors), that can prevent IPV among young people. Ten key functions have been identified, revealing the "skeleton" of the Swiss intervention. We drew on these results to comment on the intervention's applicability, with a view to transferability, specifying the contextual elements to consider before implementing SE&SR in France. CONCLUSION: This study aims to make the process of evaluating applicability, with a view to transferring an evidence-based program to the French context, more accessible.

Introduction: La prévention des violences dans les relations amoureuses (VRA) chez les jeunes est un enjeu fort des politiques publiques. Néanmoins, il existe peu de programmes de prévention ayant fait la preuve de leur efficacité en France. « Sortir Ensemble & Se Respecter ¼ (SE&SR) est une adaptation suisse de « Safe Dates ¼, un programme d'intervention américain qui a montré des résultats en matière de réduction des comportements violents tant du côté des jeunes victimes que des auteurs. L'objectif de cet article est d'analyser l'applicabilité et la « potentielle transférabilité ¼ de SE&SR en France. Méthodes: L'approche adoptée consistait à décrire l'intervention SE&SR en explicitant la théorie d'intervention, les fonctions clés (soit les « ingrédients ¼ permettant que le programme SE&SR fonctionne) et en proposant des commentaires d'applicabilité en vue d'une transférabilité adaptée au contexte français. L'outil ASTAIRE et la démarche FIC ont été utilisés. Résultats: La théorie d'intervention a mis en évidence différents facteurs, agissant au niveau individuel (i.e. connaissances, croyances/représentations, compétences psychosociales) et au niveau des milieux de vie (i.e. structures accueillant les jeunes, familles, politiques publiques/réseaux d'acteurs), qui peuvent prévenir les VRA chez les jeunes. Dix fonctions clés ont été identifiées, dégageant le « squelette ¼ de l'intervention suisse. À la suite de ces résultats, des commentaires d'applicabilité en vue d'une transférabilité ont permis de préciser les éléments de contexte à prendre en compte avant la mise en œuvre de SE&SR en France. Conclusion: Cette étude souhaite rendre accessibles les process d'applicabilité en vue d'une transférabilité d'un programme probant en contexte français.

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.

Development of Genome-Wide Intron Length Polymorphism (ILP) Markers in Tea Plant (Camellia sinensis) and Related Applications for Genetics Research.

The market value of tea is largely dependent on the tea species and cultivar. Therefore, it is important to develop efficient molecular markers covering the entire tea genome that can be used for the identification of tea varieties, marker-assisted breeding, and mapping important quantitative trait loci for beneficial traits. In this study, genome-wide molecular markers based on intron length polymorphism (ILP) were developed for tea trees. A total of 479, 1393, and 1342 tea ILP markers were identified using the PCR method in silico from the 'Shuchazao' scaffold genome, the chromosome-level genome of 'Longjing 43', and the ancient tea DASZ chromosome-level genome, respectively. A total of 230 tea ILP markers were used to amplify six tea tree species. Among these, 213 pairs of primers successfully characterize products in all six species, with 112 primer pairs exhibiting polymorphism. The polymorphism rate of primer pairs increased with the improvement in reference genome assembly quality level. The cross-species transferability analysis of 35 primer pairs of tea ILP markers showed an average amplification rate of 85.17% through 11 species in 6 families, with high transferability in Camellia reticulata and tobacco. We also used 40 pairs of tea ILP primers to evaluate the genetic diversity and population structure of C. tetracocca with 176 plants from Puan County, Guizhou Province, China. These genome-wide markers will be a valuable resource for genetic diversity analysis, marker-assisted breeding, and variety identification in tea, providing important information for the tea industry.

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.

Validation activities for methods intended to be used to assess chemical safety have a cost but also bring substantial benefits when the validated methods are established as OECD Test Guidelines which results in mutual acceptance of data generated by the methods. The article discusses some of the challenges faced when method validation is underfunded and unattractive for researchers. Proposals are made to improve the current situation, gain efficiency and make validation a shared responsibility.

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.

Isolation and characterization of polymorphic microsatellite loci for the three Iberian vipers, Vipera aspis, V. Latastei and V. seoanei by Illumina MiSeq sequencing.

BACKGROUND: European vipers (genus Vipera) are a well-studied taxonomic group, but the low resolution of nuclear sanger-sequenced regions has precluded thorough studies at systematic, ecological, evolutionary and conservation levels. In this study, we developed novel microsatellite markers for the three Iberian vipers, Vipera aspis, V. latastei and V. seoanei, and assessed their polymorphism in north-central Iberian populations. METHODS AND RESULTS: Genomic libraries were developed for each species using an Illumina Miseq sequencing approach. From the 70 primer pairs initially tested, 48 amplified reliably and were polymorphic within species. Cross-species transferability was achieved for 31 microsatellites loci in the three target species and four additional loci that were transferable to one species only. The 48 loci amplified in average seven alleles, and detected average expected and observed heterozygosities of 0.7 and 0.55, in the three genotyped populations/species (26 V. aspis, 20 V. latastei and 10 V. seoanei). CONCLUSIONS: Our study provides a selection of 48 polymorphic microsatellite markers that will contribute significantly to current knowledge on genetic diversity, gene flow, population structure, demographic dynamics, systematics, reproduction and heritability in these species, and potentially in other congeneric taxa.

Enhancing adversarial attacks with resize-invariant and logical ensemble.

In black-box scenarios, most transfer-based attacks usually improve the transferability of adversarial examples by optimizing the gradient calculation of the input image. Unfortunately, since the gradient information is only calculated and optimized for each pixel point in the image individually, the generated adversarial examples tend to overfit the local model and have poor transferability to the target model. To tackle the issue, we propose a resize-invariant method (RIM) and a logical ensemble transformation method (LETM) to enhance the transferability of adversarial examples. Specifically, RIM is inspired by the resize-invariant property of Deep Neural Networks (DNNs). The range of resizable pixel is first divided into multiple intervals, and then the input image is randomly resized and padded within each interval. Finally, LETM performs logical ensemble of multiple images after RIM transformation to calculate the final gradient update direction. The proposed method adequately considers the information of each pixel in the image and the surrounding pixels. The probability of duplication of image transformations is minimized and the overfitting effect of adversarial examples is effectively mitigated. Numerous experiments on the ImageNet dataset show that our approach outperforms other advanced methods and is capable of generating more transferable adversarial examples.

Acquisition of a stable and transferable plasmid coharbouring hypervirulence and MDR genes with low fitness cost: Accelerating the dissemination of ST11-KL64 CR-HvKP.

OBJECTIVES: This study aimed to delineate the ability of a plasmid, pS130-4, which harboured both hypervirulence and multidrug resistance genes, to disseminate within Klebsiella pneumoniae, as well as its potential formation mechanism. METHODS: We employed whole-genome sequencing to decipher the genetic architecture of pS130-4. Its capability to conjugate and transfer was assessed through a series of experiments, including plasmid stability, competitive growth, and growth curve analysis. Its expression stability was further evaluated using drug sensitivity, larval survival, and biofilm formation tests. RESULTS: pS130-4 contained four intact modules typical of self-transmissible plasmids. BLAST analysis revealed a sequence identity exceeding 90% with other plasmids from a variety of hosts, suggesting its broad prevalence. Our findings indicated the plasmid's formation resulted from IS26-mediated recombination, leading us to propose a model detailing the creation of this conjugative fusion plasmid housing both blaKPC-2 and hypervirulence genes. Our conjugation experiments established that pS130-4, when present in the clinical strain S130, was self-transmissible with an estimated efficiency between 10-5 and 10-4. Remarkably, pS130-4 showcased a 90% retention rate and did not impede the growth of host bacteria. Galleria mellonella larval infection assay demonstrated that S130 had pronounced toxicity when juxtaposed with high-virulence control strain NTUH-K2044 and low-toxicity control strain ATCC700603. Furthermore, pS130-4's virulence remained intact postconjugation. CONCLUSION: A fusion plasmid, encompassing both hypervirulence and multidrug resistance genes, was viable within K. pneumoniae ST11-KL64 and incurred minimal fitness costs. These insights underscored the criticality of rigorous monitoring to pre-empt the escalation and distribution of this formidable super-plasmid.

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.