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Abstract Background Africa has some of the highest cervical cancer incidence and mortality rates globally. Burkina Faso launched a human papillomavirus (HPV) vaccination programme for 9-year-old girls in 2022 with support from Gavi, the Vaccine Alliance (Gavi). An economic evaluation of HPV vaccination is required to help sustain investment and inform decisions about optimal HPV vaccine choices. Methods We used a proportionate outcomes static cohort model to evaluate the potential impact and cost-effectiveness of HPV vaccination for 9-year-old girls over a ten-year period (2022–2031) in Burkina Faso. The primary outcome measure was the cost (2022 US$) per disability-adjusted life year (DALY) averted from a limited societal perspective (including all vaccine costs borne by the government and Gavi, radiation therapy costs borne by the government, and all other direct medical costs borne by patients and their families). We evaluated four vaccines (CERVARIX®, CECOLIN®, GARDASIL-4®, GARDASIL-9®), comparing each to no vaccination (and no change in existing cervical cancer screening and treatment strategies) and to each other. We combined local estimates of HPV type distribution, healthcare costs, vaccine coverage and costs with GLOBOCAN 2020 disease burden data and clinical trial efficacy data. We ran deterministic and probabilistic uncertainty analyses. Results HPV vaccination could prevent 37–72% of cervical cancer cases and deaths. CECOLIN® had the most favourable cost-effectiveness (cost per DALY averted

Nestboxes are commonly used to increase the number and quality of nest sites available to birds that usually use tree cavities and are considered an important conservation intervention. Although usually safer than natural cavities, birds nesting in simple, unmodified wooden nestboxes remain at risk of depredation. Accordingly, numerous design and placement modifications have been developed to ‘predator-proof’ nestboxes. These include: (1) adding metal plates around entrance holes to prevent enlargement; (2) affixing wire mesh to side panels; (3) deepening boxes to increase distance to nest cup; (4) creating external entrance ‘tunnels’ or internal wooden ledges; (5) using more robust construction materials; (6) developing photosensitive shutters to exclude nocturnal predators; (7) using baffles to block climbing mammals; and (8) regular replacement and relocation. However, the benefits and costs of these modifications are not always well understood. In this global review, we collate information on predator-proofing avian nestboxes designed for tree cavity-nesting birds to assess the efficacy of techniques for different predators (mammalian, avian, and reptilian) in different contexts. We critique the potential for modifications to have unintended consequences—including increasing nest building effort, altering microclimate, reducing provisioning rate, and elevating ectoparasite and microbial loads—to identify hidden costs. We conclude by highlighting remaining gaps in knowledge and providing guidance on optimal modifications in different contexts.

We herein report successful syntheses of both nickel cobalt sulfide (NCS) and its composite with zeolite (NCS@Z) using a solvothermal method. Techniques such as EDX analysis, SEM, and molar ratio determination were used for product characterization. The incorporation of NCS significantly changed the surface roughness and active sites of the zeolite, improving the efficiency of methylene blue degradation and its reusability, especially under UV irradiation. In comparing the pseudo-first order rates, the highest degradation efficiency of methylene blue was achieved with NCS-2@Z, having a degradation extent of 91.07% under UV irradiation. This environmentally friendly approach offers a promising solution for the remediation of methylene blue contamination in various industries.

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based "Translator" system capable of integrating existing biomedical data sets and "translating" those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system's architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems.

Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph-based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these "knowledge graphs" (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open-access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open-source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object-oriented classification and graph-oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

Limited studies examine how prenatal environmental and social exposures jointly impact perinatal health. Here we investigated relationships between a neighborhood-level combined exposure (CE) index assessed during pregnancy and perinatal outcomes, including birthweight, gestational age, and preterm birth. Across all participants, higher CE index scores were associated with small decreases in birthweight and gestational age. We also observed effect modification by race; infants born to Black pregnant people had a greater risk of preterm birth for higher CE values compared to White infants. Overall, our results suggest that neighborhood social and environmental exposures have a small but measurable joint effect on neonatal indicators of health.

There has been substantial progress in the development of regenerative medicine strategies for CNS disorders over the last decade, with progression to early clinical studies for some conditions. However, there are multiple challenges along the translational pipeline, many of which are common across diseases and pertinent to multiple donor cell types. These include defining the point at which the preclinical data are sufficiently compelling to permit progression to the first clinical studies; scaling-up, characterization, quality control and validation of the cell product; design, validation and approval of the surgical device; and operative procedures for safe and effective delivery of cell product to the brain. Furthermore, clinical trials that incorporate principles of efficient design and disease-specific outcomes are urgently needed (particularly for those undertaken in rare diseases, where relatively small cohorts are an additional limiting factor), and all processes must be adaptable in a dynamic regulatory environment. Here we set out the challenges associated with the clinical translation of cell therapy, using Huntington's disease as a specific example, and suggest potential strategies to address these challenges. Huntington's disease presents a clear unmet need, but, importantly, it is an autosomal dominant condition with a readily available gene test, full genetic penetrance and a wide range of associated animal models, which together mean that it is a powerful condition in which to develop principles and test experimental therapeutics. We propose that solving these challenges in Huntington's disease would provide a road map for many other neurological conditions. This white paper represents a consensus opinion emerging from a series of meetings of the international translational platforms Stem Cells for Huntington's Disease and the European Huntington's Disease Network Advanced Therapies Working Group, established to identify the challenges of cell therapy, share experience, develop guidance and highlight future directions, with the aim to expedite progress towards therapies for clinical benefit in Huntington's disease.

School closures and the move to remote learning during the COVID-19 pandemic transformed teaching and learning in Australian schools. Educators experienced personal and professional challenges as they rapidly responded to the needs of their school communities and managed their own emotional reactions. Eleven educators at two Victorian schools in areas of low socioeconomic status discussed in focus groups the impact of school closures and explored their perceptions of responses from leaders and colleagues who supported their wellbeing. While naming the significance of uncertainty, constant change and increased workloads, these educators acted creatively to ensure their students had access to specifically developed learning materials to suit their needs. Educators demonstrated that they could use existing reflective structures that fostered mutual support to sustain their wellbeing and create supportive environments for themselves and their wider school communities in times of crisis, as well as remain open to sometimes-surprising learning opportunities.

Objective: This study aims to: (1) examine gender differences for weight conscious drinking among college students accounting for the broader phenomenon (e.g. including the Alcohol Effects dimension); and (2) longitudinally examine the effect of weight conscious drinking behaviors on body mass index (BMI). Participants: United States freshmen students from eight participating universities (N= 1,149). Methods: Structural equation modeling was used to model the effect of gender on weight conscious drinking dimensions at 7-month follow-up. Results: Findings suggest a significant effect of gender on Alcohol Effects ([beta] = -0.15, SE = 0.05, p = 0.005) at 7-month follow-up among college freshmen. Weight conscious drinking dimensions predicted no significant change in BMI at 7-month follow-up among college freshmen. Conclusion: Findings contribute to weight conscious drinking theory and provide campus weight conscious drinking prevention initiatives with evidence to tailor their programming to address female tendencies to engage in compensatory strategies to enhance the psychoactive effects of alcohol.

K-12 students need to become familiar with engineering because 21st-century careers integrate engineering practices across all science, technology, engineering, and mathematics (STEM) fields. While the Next Generation Science Standards (NGSS) emphasize learning real science and engineering practices, further work is needed to authenticate engineering for K-12 education. The NGSS are presented in a way that merges a single general practice with a core disciplinary idea and cross-cutting concept. Based on this framing and underlying epistemology, NGSS engineering practices are often implemented as overgeneralized, isolated, and largely context-neutral. Yet, in the STEM workplace, practices are rarely done in isolation from one another. Research is needed to better understand the integrated use of NGSS practices in STEM workplaces in order to make these practices more visible and accessible for use in K-12 classrooms. We conducted semi-structured interviews with 22 entry-level employees and managers in STEM-intensive workplaces. Using emergent and a priori coding, we identified how NGSS practices and contextual features are situated and connected in the STEM workplace. Our findings suggest that by adding rich contextual features, practices become more interconnected and reflective of authentic engineering in the STEM workplace. This process will enable educators to interpret K-12 engineering standards in an authentic way that supports deep engagement in learning engineering.

Purpose: Clinical education is a key component of speech-language pathology university curriculum, whereby students have the opportunity to apply theoretical knowledge and practical skills learned in the classroom into a real workplace. However, more recently the availability of high quality, consistent clinical placements and learning experiences across the range of practice areas in the discipline is reducing. Therefore, alternative clinical learning opportunities that enable students to develop skills and competencies are being explored. Recently, replacing clinical time with a simulated learning program has been shown to achieve equivalent levels of clinical competency in speech pathology. However, it is unknown how simulation impacts on student learning in traditional clinical placements. Therefore, this research explored clinical educators' perceptions of students undertaking clinical placements in their workplace immediately following a five-day simulation-based learning program related to the same area of practice. Method: Thirty-five clinical educators who supervised students in the workplace immediately after they completed the simulation program participated in semi-structured interviews. All interviews were transcribed verbatim and analyzed using qualitative methods described by Graneheim and Lundman (2004). Result: The analysis identified four key themes related to the impact of students in the workplace, simulation priming students for learning, the importance of the transition from simulation-based learning to the workplace, and the role of simulation in clinical education programs. Conclusion: The use of simulation to support student learning and develop clinical skills and competencies in adult speech pathology practice is supported by workplace clinical educators. However, results of this study suggest that the simulation program needs to be embedded within the curriculum and clinical education program to enhance transition between learning experiences and maximize benefits of learning experiences in real workplace contexts.

Political Ritual and Practice in Capetian France: Studies in Honour of Elizabeth A. R. Brown. Edited by M. Cecilia Gaposchkin and Jay Rubenstein. (Turnhout: Brepols, 2021. Pp. 457. ISBN: 9782503593029.) [...]