Mixed Data Research Articles

The estimation of pubertal growth spurt parameters using the superimposition by translation and rotation model in Korean children and adolescents: a longitudinal cohort study.

Understanding the characteristics of the pubertal growth spurt in Korean children and adolescents can serve as crucial foundational data for researching puberty and growth-related disorders. This study aims to estimate the key parameters of pubertal growth, specifically the age and magnitude of the pubertal growth spurt, utilizing longitudinal data from a cohort of Korean children and adolescents. This study used mixed longitudinal height data from a cohort of Korean elementary, middle, and high school students aged 7-18 years. The Superimposition by Translation and Rotation (SITAR) model, a shape-invariant growth curve model, was utilized to estimate a reference height velocity curve for the entire dataset and individual curves via random effects to evaluate pubertal growth parameters. Altogether, 3,339 height measurements (1,519 for boys and 1,820 for girls) from 270 individuals (123 boys and 147 girls) were analyzed. The average age of growth spurt onset in Korean boys was 10.17 ± 0.61 years (mean ± SE), with peak height velocity occurring at 12.46 ± 0.69 years of age (9.61 ± 1.26 cm/year). Korean girls, contrarily, experience their growth spurt at an earlier age (8.57 ± 0.68 years), with peak height velocity occurring at 10.99 ± 0.74 years of age (8.32 ± 1.09 cm/year). An earlier onset of puberty in both sexes is associated with a shorter growth spurt duration (0.63 years for boys and 0.58 years for girls) and a higher peak height velocity (1.82 cm/year for boys and 1.39 cm/year for girls). These associations were statistically significant for both sexes (all p < 0.0001). This study is the first to use the height velocity curve from the SITAR model to examine the pubertal growth spurt of Korean children and adolescents. The estimated timing and magnitude of the pubertal growth spurt, and their relationships can be useful data for clinicians and researchers.

A Digital Intervention for Capturing the Real-Time Health Data Needed for Epilepsy Seizure Forecasting: Protocol for a Formative Co-Design and Usability Study (The ATMOSPHERE Study).

Epilepsy is a chronic neurological disorder affecting individuals globally, marked by recurrent and apparently unpredictable seizures that pose significant challenges, including increased mortality, injuries, and diminished quality of life. Despite advancements in treatments, a significant proportion of people with epilepsy continue to experience uncontrolled seizures. The apparent unpredictability of these events has been identified as a major concern for people with epilepsy, highlighting the need for innovative seizure forecasting technologies. The ATMOSPHERE study aimed to develop and evaluate a digital intervention, using wearable technology and data science, that provides real-time, individualized seizure forecasting for individuals living with epilepsy. This paper reports the protocol for one of the workstreams focusing on the design and testing of a prototype to capture real-time input data needed for predictive modeling. The first aim was to collaboratively design the prototype (work completed). The second aim is to conduct an "in-the-wild" study to assess usability and refine the prototype (planned research). This study uses a person-based approach to design and test the usability of a prototype for real-time seizure precipitant data capture. Phase 1 (work completed) involved co-design with individuals living with epilepsy and health care professionals. Sessions explored users' requirements for the prototype, followed by iterative design of low-fidelity, static prototypes. Phase 2 (planned research) will be an "in-the-wild" usability study involving the deployment of a mid-fidelity, functional prototype for 4 weeks, with the collection of mixed methods usability data to assess the prototype's real-world application, feasibility, acceptability, and engagement. This phase involves primary participants (adults diagnosed with epilepsy) and, optionally, their nominated significant other. The usability study will run in 3 rounds of deployment and data collection, aiming to recruit 5 participants per round, with prototype refinement between rounds. The phase-1 co-design study engaged 22 individuals, resulting in the development of a mid-fidelity, functional prototype based on identified requirements, including the tracking of evidence-based and personalized seizure precipitants. The upcoming phase-2 usability study is expected to provide insights into the prototype's real-world usability, identify areas for improvement, and refine the technology for future development. The estimated completion date of phase 2 is the last quarter of 2024. The ATMOSPHERE study aims to make a significant step forward in epilepsy management, focusing on the development of a user-centered, noninvasive wearable device for seizure forecasting. Through a collaborative design process and comprehensive usability testing, this research aims to address the critical need for predictive seizure forecasting technologies, offering a promising approach to improving the lives of individuals with epilepsy. By leveraging predictive analytics and personalized machine learning models, this technology seeks to offer a novel approach to managing epilepsy, potentially improving clinical outcomes, including quality of life, through increased predictability and seizure management. DERR1-10.2196/60129.

EFL STUDENTS’ PERCEPTIONS OF GOOGLE CLASSROOM IN JUNIOR HIGH SCHOOL ENGLISH LEARNING

This study is aimed at investigating EFL students’ perceptions on the use of Google Classroom for English language learning in a junior high school. The study used a mixed method design, combining quantitative and qualitative data. The context of the study was EFL students from one of state junior high schools in Jakarta, Indonesia. Through a survey of 146 students and some selected students for interviews, the study examines various aspects of their experiences with the platform, including motivation, effectiveness, communication, and access to learning materials. The findings reveal a positive attitude among EFL students towards Google Classroom, with their acknowledging its benefits in enhancing motivation, facilitating interaction, and providing convenient access to resources. The study highlights the potential of digital tools like Google Classroom to address challenges in language education. Thus, this study suggests implications for English teachers seeking to optimize technology-enhanced learning environments, mainly in English learning in junior high schools.

Should end-users take their clothes off inside on a cold winter's day? Sustainability pressures on district heating professionals in Denmark

This research explores how district heating (DH) sector professionals /employees experience the low-carbon energy transitions-related change processes in the Danish heat supply sector. Enquiry draws upon mixed data collected among DH employees from 148 utilities. Geels’ triple embeddedness framework conceptualizes the connections between regime-level actor experiences of niche- and landscape-level pressures, sustainability imperatives, and the associated change processes. This neo-institutionalist perspective finds that the historically stable DH regime-level institutions are being destabilised. It also reveals the tensions and change inertia associated with, for example, sunk costs, infrastructural path dependencies, and professional culture. For the DH professionals, and regime-level actors, these destabilization processes challenge what were previously core regime-level professional practices, skills and taken-for-granted standards for a job well done. Indeed, professional identity and pride may be at stake. Paradoxically, the identified DH sector norms for stable, affordable, and invisible heat supply service provision may not necessarily motivate DH end-users /customers towards more sustainable heat-use behaviours: DH end-users in Denmark have come to expect these DH community heat supply provision as taken-for-granted societal goods, and the topics of space heating and thermal comfort are increasingly dissociated from consumption-related debates within public, and political realms. This DH case study shows how landscape, regime, and actor-level socio-technical trajectories interact, and it exemplifies actor-structure relationships in situations of regime stress. Perhaps it proves an exemplary case for exploring the lock-in mechanisms, inertia, restraints, and potentials of change-processes within also other societal domains and institutional realms.

A mixed methods analysis of a yearlong intercultural competence curriculum strand

ABSTRACT Background: In a published 2016 report, it was estimated that approximately 80% of public-school teachers identified as White (United States Department of Education 2016). The duality of the issue is that the diversity of the teacher workforce has improved since 1990 but lags in comparison to the increasing diversity of the student population [Gumber, C., and J. Beckhusen. 2022. “U.S. Teachers More Diverse but Still Lag Student Racial, Ethnic Makeup”. United States Census Bureau, January 5. Accessed August 12, 2022. https://www.census.gov/library/stories/2022/01/nations-teachers-more-diverse-but-still-lag-racial-ethnic-makeup-of-students.html.]. The discrepancy that exists in racial or ethnic diversity between teachers and students has been termed a cultural gap [Muschell, L. H., and H. M. Roberts. 2011. “Bridging the Cultural Gap: One Teacher Education Program’s Response to Preparing Culturally Responsive Teachers.” Childhood Education 87 (5): 337–340. https://doi.org/10.1080/00094056.2011.10523209]. The value proposition for a teacher workforce that mirrors society is hard to dispute. In the broadest sense, members of the education sector must coordinate efforts to recruit and retain culturally diverse teachers. While these efforts are critical, progress will likely be carried out over a longer period of time. Thus, adequately preparing current and future teachers to bridge the cultural gap is essential. Purpose: Intercultural competence (ICC) is an increasingly relevant topic for teacher preparation programs. To date, there remains a relative dearth of research on strategies that physical education teacher education (PETE) programs can use to promote ICC among teacher candidates (TCs). This study aimed to explore a yearlong curriculum strand’s impact on promoting ICC development in TCs. Methods: A mixed methods research design involving quantitative and qualitative data collection was employed. The quantitative measure was the Intercultural Development Inventory®. Qualitative measures consisted of journal entries and semi-structured interviews. Datasets were then merged to generate mixed-data narratives. Participants included 29 TCs enrolled at a mid-Atlantic University. Findings: Analyses revealed that the curriculum strand did not promote significant change in teacher candidates’ ICC levels quantitatively. Researchers used the constant comparison method to interpret the mixed data narratives. Analyses of the mixed data narratives revealed four emergent themes: (a) experience with cultural diversity; (b) confidence to teach culturally diverse students; (c) making sense of ICC; and (d) reflection on action. Conclusions: Participant data suggests that ICC is a topic that TCs value but may be lacking in their practical, applied understanding of working across cultural differences. Implications and future research on promoting ICC among physical education TCs are discussed. To our knowledge, this study will be the first application of the IDI® to explore change following physical education TCs’ participation in a yearlong curriculum strand focused on promoting ICC.

Events as a Strategy to Enhance Destination’s Brand: Millennium Estoril Open Case Study

This research, based on a case study, aims to examine the contributions of the Millennium Estoril Open, a tennis event (ATP 250), to enhance and promote the Cascais destination brand. To such end, an empirical study was conducted in the 2019 edition, using a mixed data collection methodology through the application of questionnaires to spectators, interviews with stakeholders, and direct observation at the event. Results suggest that this event contributes to enhancing the destination brand, despite the identification of some limitations. The contribution of this sport event to the enhancement of the destination’s image cannot be dissociated from the portfolio of events promoted by the region and from its consistency and regularity.

Degrade for upgrade: Learning degradation representations for real-world low-light image enhancement

Most existing low-light image enhancement approaches predominantly focus on directly modeling the mapping between low-light images and normal-light images, but models trained on the single fixed data set often fail to achieve satisfactory results in complex real-world scenes. To address the limitations posed by limited data, this paper proposes a joint framework to learn spatially adaptive degradation and enhancement representations of bright-to-dark images and dark-to-bright images. Firstly, we design an illumination degradation model based on cycle consistent loss to learn how to degrade normal-light images into low-light reference images. The degradation model can synthesize a large number of normal/degraded-light pairs, which is beneficial for the training of the second-stage enhancement model. Subsequently, leveraging the self-luminance information of images, we construct a self-attention-based light enhancement model. The enhancement model is trained on mixed data, which combines both real normal/low-light image pairs and synthetic normal/degraded-light image pairs. In this way, the enhancement model can learn more features from a diverse set of images, enhancing its robustness. Extensive experiments on low-light image enhancement, low-light object detection, and nighttime image segmentation have demonstrated that our proposed method outperforms existing supervised and unsupervised methods across a variety of real-world scenes.

Examining intra-host genetic variation of RSV by short read high-throughput sequencing.

Every viral infection entails an evolving population of viral genomes. High-throughput sequencing technologies can be used to characterize such populations, but to date there are few published examples of such work. In addition, mixed sequencing data are sometimes used to infer properties of infecting genomes without discriminating between genome-derived reads and reads from the much more abundant, in the case of a typical active viral infection, transcripts. Here we apply capture probe-based short read high-throughput sequencing to nasal wash samples taken from a previously described group of adult hematopoietic cell transplant (HCT) recipients naturally infected with respiratory syncytial virus (RSV). We separately analyzed reads from genomes and transcripts for the levels and distribution of genetic variation by calculating per position Shannon entropies. Our analysis reveals a low level of genetic variation within the RSV infections analyzed here, but with interesting differences between genomes and transcripts in 1) average per sample Shannon entropies; 2) the genomic distribution of variation 'hotspots'; and 3) the genomic distribution of hotspots encoding alternative amino acids. In all, our results suggest the importance of separately analyzing reads from genomes and transcripts when interpreting high-throughput sequencing data for insight into intra-host viral genome replication, expression, and evolution.

Effect of stationary factors on the yield and chemical composition of essential oils of Tetraclinis articulata (Vahl) Masters from Sdama Chergui massif’s (Tiaret, North-West Algeria)

This paper aims to study the influence of exposure, altitude, and soil pH on the yield and chemical composition of essential oils (EOs) from the leaves of Tetraclinis articulata (Vahl) Masters, developed in the Sdama Chergui massif in northwestern Algeria. These EOs were obtained by hydrodistillation, resulting in average yields of 0.33±0.13 %, 0.29±0.07 %, 0.24±0.07 %, and 0.2±0.03 %, recorded at the south, west, north, and east exposures, respectively. Upon analyzing the obtained EOs by gas chromatography coupled with mass spectrometry (GC/MS), a total of chemical molecules grouped into 22 families were identified. The predominant compounds were Bornyl acetate (9.14 %, 7.95 %, 11.20 %, and 9.78 %), Limonene (5.03 %, 7.18 %, 5.76 %, and 5.41 %), α-Pinene (4.97 %, 5.26 %, 5.09 %, and 4.79 %), Camphor (7.53 %, 3.69 %, 3.01 %, and 5.91 %), and Borneol (5.20 %, 6.26 %, 4.93 %, and 5.11 %). Additionally, the analysis of these molecules by Factorial Analysis of Mixed Data (PCAmix) revealed that exposure, altitude, and soil pH have little effect on the yield and chemical composition of the essential oils of Tetraclinis articulata. Finally, careful attention to stationary parameters is crucial for obtaining essential oils of high quality and optimal quantity.

Parental Contributions to Enhance Sustainable School Feeding Programme in Public Primary Schools in Gairo District Council, Tanzania

This study aimed to find out the parental contributions to enhance sustainable school feeding programmes (SFP) at public primary schools in Gairo District Council, Tanzania. It is guided by the two objectives; identify the kind of parental contributions in enhancing sustainable SFP and highlight the parents' perceptions in supporting sustainable school feeding programme (SFP). The study had a sample of 177 respondents who were selected using simple random, snowball and purposive sampling techniques. The study sample involved 98 students, 18 teachers, 60 parents, and 1 District Primary Education Officer. The study employed the mixed method approach and data was collected through a questionnaire, interview, FGD, observation and documentary review. The quantitative data was analysed by using SPSS version 25.0 and the qualitative data was analysed thematically according to the two research objectives. The findings of the study showed the existence of SFP in all 6 schools and the parents had positive perceptions as revealed through contributing food crops, cash money and physical labour to the SFP for constant supply of students' meals. The study recommended the policymakers, government and the community to act on their part for the success and sustainability of SFP

Analysis of Public Satisfaction Levels in Gelora Bung Karno (GBK) City Forest Based on Socio-Cultural Functions

The Jakarta City Government, along with the central government, has implemented various measures to address the issue of air pollution that has become a serious problem for the city. One of the efforts undertaken is to increase the provision of urban green spaces and restore the function of the GBK City Forest as a public green open space (GOS). However, there has been no research showing the public's perspective and satisfaction with the utilization of the GBK City Forest. This study aims to determine the level of public satisfaction with the GBK City Forest based on social-cultural functions. The assessment indicators used to measure public satisfaction in this study are based on the theory of cultural ecosystem services developed by Shijie Gai et al. The data used in this study were obtained using mixed methods data collection techniques through questionnaires (quantitative) as well as in-depth interviews and literature studies (qualitative). Based on the results of the study, it can be concluded that the majority of the public is highly satisfied with the utilization of the social-cultural functions of the GBK City Forest. However, some people still complain about the lack of supporting facilities for recreational activities and the disturbances from external parties that make them feel uncomfortable when engaging in activities at the GBK City Forest. Therefore, it is important for the government and the GBK City Forest management to consider public feedback and improve the quality and safety of the existing facilities.

Surrogate method for partial association between mixed data with application to well-being survey analysis

Surrogate method for partial association between mixed data with application to well-being survey analysis

The Voices on Vax Campaign: Lessons Learned from Engaging Youth to Promote COVID Vaccination

Abstract: Background: The Voices on Vax campaign was a collaborative effort that engaged youth to create an interactive website and social media presence to increase COVID vaccine confidence and uptake among African American families in Baltimore, Maryland. Objectives: To describe lessons learned and offer recommendations for future health communication campaigns involving youth ambassadors and virtual platforms. Methods: We collected website analytics and limited data from pop-up surveys on the Voices on Vax website, as well as reflections from the youth ambassadors about their experiences. Lessons Learned: Challenges included difficulties engaging the priority population and methodological limitations of our campaign’s impact evaluation. Successes included our focus on youth and adaptive engagement strategies. Conclusions: We recommend using techniques to maximize engagement by the priority population, conducting in-person outreach, incorporating mixed methods data collection, and providing a mix of structured training and creative freedom to youth ambassadors.

Toward a dynamic national transportation noise map: Modeling temporal variability of spectral traffic noise emission levels.

The National Transportation Noise Map predicts time-averaged road traffic noise across the continental United States (CONUS) based on annual average daily traffic counts. However, traffic noise can vary greatly with time. This paper outlines a method for predicting nationwide hourly varying source traffic sound emissions called the Vehicular Reduced-Order Observation-based Model (VROOM). The method incorporates three models that predict temporal variability of traffic volume, predict temporal variability of different traffic classes, and use Traffic Noise Model (TNM) 3.0 equations to give traffic noise emission levels based on vehicle numbers and class mix. Location-specific features are used to predict average class mix across CONUS. VROOM then incorporates dynamic traffic class mix data to obtain dynamic traffic class mix. TNM 3.0 equations then give estimated equivalent sound level emission spectra near roads with up to hourly resolution. Important temporal traffic noise characteristics are modeled, including diurnal traffic patterns, rush hours in urban locations, and weekly and yearly variation. Examples of the temporal variability are depicted and possible types of uncertainties are identified. Altogether, VROOM can be used to map national transportation noise with temporal and spectral variability.

Multiple Inputs and Mixed Data for Alzheimer’s Disease Classification Based on 3D Vision Transformer

The current methods for diagnosing Alzheimer’s Disease using Magnetic Resonance Imaging (MRI) have significant limitations. Many previous studies used 2D Transformers to analyze individual brain slices independently, potentially losing critical 3D contextual information. Region of interest-based models often focus on only a few brain regions despite Alzheimer’s affecting multiple areas. Additionally, most classification models rely on a single test, whereas diagnosing Alzheimer’s requires a multifaceted approach integrating diverse data sources for a more accurate assessment. This study introduces a novel methodology called the Multiple Inputs and Mixed Data 3D Vision Transformer (MIMD-3DVT). This method processes consecutive slices together to capture the feature dimensions and spatial information, fuses multiple 3D ROI imaging data inputs, and integrates mixed data from demographic factors, cognitive assessments, and brain imaging. The proposed methodology was experimentally evaluated using a combined dataset that included the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Australian Imaging, Biomarker, and Lifestyle Flagship Study of Ageing (AIBL), and the Open Access Series of Imaging Studies (OASIS). Our MIMD-3DVT, utilizing single or multiple ROIs, achieved an accuracy of 97.14%, outperforming the state-of-the-art methods in distinguishing between Normal Cognition and Alzheimer’s Disease.

Reconstructing SARS-CoV-2 lineages from mixed wastewater sequencing data

Wastewater surveillance of SARS-CoV-2 has emerged as a critical tool for tracking the spread of COVID-19. In addition to estimating the relative case numbers using quantitative PCR, SARS-CoV-2 genomic RNA can be extracted from wastewater and sequenced. There are many existing techniques for using the sequenced RNA to determine the relative abundance of known lineages in a sample. However, it is very challenging to predict novel lineages from wastewater data due to its mixed composition and unreliable genomic coverage. In this work, we present a novel technique based on non-negative matrix factorization which is able to reconstruct lineage definitions by analyzing data from across different samples. We test the method both on synthetic and real wastewater sequencing data. We show that the technique is able to determine major lineages such as Omicron and Delta as well as sub-lineages such as BA.5.2.1. We provide a method for determining emerging lineages in wastewater without the need for genomic data from clinical samples. This could be used for routine monitoring of SARS-CoV-2 as well as other emerging viral pathogens in wastewater. Additionally, it may be used to determine more full-genome sequences for viruses with fewer available genomes.

Observation of the Reconstitution Process and Factors that Influence the Final Condition of Chemotherapy Patients in Private Hospitals

 Handling of cytostatic preparations is the aseptic handling of cancer drugs in ready-to-use packaging according to patient needs by trained pharmacists with control of environmental safety, officers, and drug preparations from toxic effects and contamination, using personal protective equipment. Resistant to handling cytostatics preparations, including preparation, mixing, handling of spills, and cytostatics waste management. The purpose of this study was to determine the suitability of the handling of cytostatic preparations and the description of the use of chemotherapy drugs in cancer patients. This research was conducted by descriptive analytic observation, data on the handling of cytostatics preparations was obtained by observing directly in the chemotherapy drug mixing room and data on the use of chemotherapy drugs were obtained retrospectively by looking at medical records and service sheets of mixing cytostatics preparations. The results obtained in the process of handling cytostatic preparations in the preparation, mixing and labeling stages are 100% to the guidelines, while the labeling stage is 86% appropriate. Evaluation of the type of use of chemotherapy drugs is known that the taxane drug class is the most widely used by 91,7%. The appropriate evaluation of chemotherapy drugs in breast cancer patients is 92%, lung cancer is 100% and uterine cancer is 0%. Evaluation of the correct dose of chemotherapy drugs obtained results of 0%. The results of the Chi Square statistical test found that there was a relationship between the last cycle of chemotherapy and the patient's final condition p = &lt;0.001

Unlocking Learning: The Impact of an Educational Escape Room on Energy Transition

Since the first escape room opened in 2007, the industry has grown to attract people from all over the world and is expected to continue to grow. This trend of rising social and recreational interest has, in turn, being introduced in the education sector in many countries. The use of escape rooms for educational purposes has become increasingly popular across different levels of education, including higher education institutions. This innovative and ludic approach involves students in their learning environment, encourages the use of numerous soft skills (creativity, problem solving, teamwork, etc.), and provides opportunity to escape the ‘routine’ of traditional and less student-centered learning methods. Although Educational Escape Rooms (EER) are becoming more prevalent in formal education, initiatives related to the topic of energy transition are scarce. As a result, there is limited information on the impact of these strategies to promote youth motivation and learning towards the energy transition. Exploring this issue is particularly relevant as young people have the potential to play an active and important role in achieving a sustainable future. This case study employs a quasi-experimental pretest-posttest design with mixed data. The sample consist of 32 students playing an EER, designed by higher education students, on energy transition. The study aims to assess the quality of the resource design and its impact on students’ knowledge, motivation to learn, soft skills utilization, and engagement. The study results show a noteworthy improvement in self-perceived knowledge regarding the energy transition after playing the EER. This increase is associated with new knowledge gained by the players about energy consumption, production and transformation. The results indicate that the EER is ineffective in increasing or decreasing motivation to learn among players. Engagement is perceived as positive with respect to the experience of playing the EER. However, there is no correlation between motivation to learn and engagement. The study also suggests that the EER has the potential to improve various soft skills, especially teamwork, communication, and problem-solving. Finally, the EER was generally praised by the players for its engagement, on both quantitative and qualitative data in the study. On the other hand, the thematic analysis revealed some design issues that may have affected the players' experience and learning outcomes. These included excessive difficulty in some puzzles, lack of guidance, and insufficient time to complete. These issues need to be addressed in order to improve the overall impact of the EER, despite players' generally positive perceptions of it. In relation to the four puzzles that compose the EER (which relate to energy consumption, production, storage and transformation), they were generally positively rated by the participants, with the energy consumption puzzle being the highest rated for its practical application.

Implementation and Impact of Intimate Partner Violence Screening Expansion in the Veterans Health Administration: Protocol for a Mixed Methods Evaluation.

Intimate partner violence (IPV) is a significant public health problem with far-reaching consequences. The health care system plays an integral role in the detection of and response to IPV. Historically, the majority of IPV screening initiatives have targeted women of reproductive age, with little known about men's IPV screening experiences or the impact of screening on men's health care. The Veterans Health Administration (VHA) has called for an expansion of IPV screening, providing a unique opportunity for a large-scale evaluation of IPV screening and response across all patient populations. In this protocol paper, we describe the recently funded Partnered Evaluation of Relationship Health Innovations and Services through Mixed Methods (PRISM) initiative, aiming to evaluate the implementation and impact of the VHA's IPV screening and response expansion, with a particular focus on identifying potential gender differences. The PRISM Initiative is guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and Consolidated Framework for Implementation Research (CFIR 2.0) frameworks. We will use mixed methods data from 139 VHA facilities to evaluate the IPV screening expansion, including electronic health record data and qualitative interviews with patients, clinicians, and national IPV program leadership. Quantitative data will be analyzed using a longitudinal observational design with repeated measurement periods at baseline (T0), year 1 (T1), and year 2 (T2). Qualitative interviews will focus on identifying multilevel factors, including potential implementation barriers and facilitators critical to IPV screening and response expansion, and examining the impact of screening on patients and clinicians. The PRISM initiative was funded in October 2023. We have developed the qualitative interview guides, obtained institutional review board approval, extracted quantitative data for baseline analyses, and began recruitment for qualitative interviews. Reports of progress and results will be made available to evaluation partners and funders through quarterly and end-of-year reports. All data collection and analyses across time points are expected to be completed in June 2026. Findings from this mixed methods evaluation will provide a comprehensive understanding of IPV screening expansion at the VHA, including the implementation and impact of screening and the scope of IPV detected in the VHA patient population. Moreover, data generated by this initiative have critical policy and clinical practice implications in a national health care system. PRR1-10.2196/59918.

Rhizobium etli CFN42 and Sinorhizobium meliloti 1021 bioinformatic transcriptional regulatory networks from culture and symbiosis.

Rhizobium etli CFN42 proteome-transcriptome mixed data of exponential growth and nitrogen-fixing bacteroids, as well as Sinorhizobium meliloti 1021 transcriptome data of growth and nitrogen-fixing bacteroids, were integrated into transcriptional regulatory networks (TRNs). The one-step construction network consisted of a matrix-clustering analysis of matrices of the gene profile and all matrices of the transcription factors (TFs) of their genome. The networks were constructed with the prediction of regulatory network application of the RhizoBindingSites database (http://rhizobindingsites.ccg.unam.mx/). The deduced free-living Rhizobium etli network contained 1,146 genes, including 380TFs and 12 sigma factors. In addition, the bacteroid R. etli CFN42 network contained 884 genes, where 364 were TFs, and 12 were sigma factors, whereas the deduced free-living Sinorhizobium meliloti 1021 network contained 643 genes, where 259 were TFs and seven were sigma factors, and the bacteroid Sinorhizobium meliloti 1021 network contained 357 genes, where 210 were TFs and six were sigma factors. The similarity of these deduced condition-dependent networks and the biological E. coli and B. subtilis independent condition networks segregates from the random Erdös-Rényi networks. Deduced networks showed a low average clustering coefficient. They were not scale-free, showing a gradually diminishing hierarchy of TFs in contrast to the hierarchy role of the sigma factor rpoD in the E. coli K12 network. For rhizobia networks, partitioning the genome in the chromosome, chromids, and plasmids, where essential genes are distributed, and the symbiotic ability that is mostly coded in plasmids, may alter the structure of these deduced condition-dependent networks. It provides potential TF gen-target relationship data for constructing regulons, which are the basic units of a TRN.