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BackgroundCancer is the second-leading cause of death in the United States. Most studies have reported rural versus urban and Black versus White cancer disparities. However, few studies have investigated racial disparities in rural areas.ObjectiveWe conducted a literature review to explore the current state of knowledge on racial and ethnic disparities in cancer attitudes, knowledge, occurrence, and outcomes in rural United States.MethodsA systematic search of PubMed and Embase was performed. Peer-reviewed articles published in English from 2004-2023 were included. Three authors independently reviewed the articles and reached a consensus.ResultsAfter reviewing 993 articles, a total of 30 articles met the inclusion criteria and were included in the present review. Studies revealed that underrepresented racial and ethnic groups in rural areas were more likely to have low cancer-related knowledge, low screening, high incidence, less access to treatment, and high mortality compared to their White counterparts.ConclusionUnderrepresented racial and ethnic groups in rural areas experienced a high burden of cancer. Improving social determinants of health may help reduce cancer disparities and promote health.

Electronic waste (e-waste) or discarded electronic devices that are unwanted, not working, or have reached their end of life pose significant threats to human and environmental health. This is a major concern in Africa, where the majority of e-waste is discarded. In the year 2021, an estimated 57.4 million metric tons of e-waste were generated worldwide. Globally, COVID-19 lockdowns have contributed to increased e-waste generation. Although Africa generates the least of this waste, the continent has been the dumping ground for e-waste from the developed world. The flow of hazardous waste from the prosperous ‘Global North’ to the impoverished ‘Global South’ is termed “toxic colonialism”. Agbogbloshie, Ghana, an e-waste hub where about 39% of e-waste was treated, was listed among the top 10 most polluted places in the world. The discard of e-waste in Ghana presents an issue of environmental injustice, defined as the disproportionate exposure of communities of color and low-income communities to pollution, its associated health and environmental effects, and the unequal environmental protection provided through policies. Despite the economic benefits of e-waste, many civilians (low-income earners, settlers, children, and people with minimal education) are exposed to negative health effects due to poverty, lack of education, and weak regulations. We critically examine the existing literature to gather empirical information on e-waste and environmental injustice. Comprehensive policies and regulations are needed to manage e-waste locally and globally.

Abstract Objectives Listening2Faces (L2F) is a therapeutic, application-based training program designed to improve audiovisual speech perception for persons with communication disorders. The purpose of this research was to investigate the feasibility of using the L2F application with young adults with autism and complex communication needs. Methods Three young adults with autism and complex communication needs completed baseline assessments and participated in training sessions within the L2F application. Behavioral supports, including the use of cognitive picture rehearsal, were used to support engagement with the L2F application. Descriptive statistics were used to provide (1) an overview of the level of participation in L2F application with the use of behavioral supports and (2) general performance on L2F application for each participant. Results All three participants completed the initial auditory noise assessment (ANA) as well as 8 or more levels of the L2F application with varying accuracy levels. One participant completed the entire L2F program successfully. Several behavioral supports were used to facilitate participation; however, each individual demonstrated varied levels of engagement with the application. Conclusions The L2F application may be a viable intervention tool to support audiovisual speech perception in persons with complex communication needs within a school-based setting. A review of behavioral supports and possible beneficial modifications to the L2F application for persons with complex communication needs are discussed.

In 2019, there was no entity specifically dedicated to health promotion and education practitioners in Connecticut or New England. This made it difficult for health promotion practitioners and students to network, collaborate, and engage in professional development. The purpose of this article is to share our experiences developing the new Connecticut Chapter of the Society for Public Health Education (CT SOPHE), including how we leveraged student interns during the first two years to promote organizational growth. To build our membership, it was important to determine who would be interested in joining CT SOPHE and so we focused on three groups: the current workforce/professionals, future workforce/students, and future leaders/interns. Over the course of these two years, three interns were recruited to help with creating a needs assessment (MPH student) and program development (two BS students); the organization was established by an MPH student as her internship project. Three former interns share how their experience working with the CT SOPHE board has helped them develop crucial leadership skills early in their careers. Embedding student interns into the framework and operations of CT SOPHE demonstrates an intentional and strategic commitment to the sustainability of both the organization and the workforce.

The purpose of this chapter is twofold; we first review our approach to cultural discourse analysis and then explicate the role of “discursive hubs” within it. The six discursive hubs we discuss are A Hub of Being: How is identity expressed? Acting: How do we express what we are doing? Relating: How do we express that we are related to each other? Feeling: How do we express what we feel? Dwelling: How do we express where we are (place) in our natural world (or material environment)? Timing: How do we express the understanding of process or sequencing over time? Our chapter brings to the fore several features of the general construct, discursive hub. Each feature of a hub adds an essential aspect to studies of cultural discourses. The set of features offers a systematic guideline for the design and execution of cultural discourse analytic studies into discursive hubs. Specifically, the set of features includes (a) The research question each hub raises; (b) the specific bits of discourse each concept of “discourse hub” makes relevant; (c) the socio-cultural functions of each hub within discourses or what that hub does within a discourse and (d) symbolic instantiations of that hub (in language, images, sounds and other signs) in actual cases of cultural discourse. Our discussion of the discourse hubs then turns to the heuristic role they play in the conduct of cultural discourse analyses. We emphasise that the hubs often work deeply together and thus their interrelationships breathe social life into cultural discourses. © 2024 selection and editorial matter, Shi-xu; individual chapters, the contributors.

Currently, liquid biopsy method is mainly used for tumor detection based on genomic molecular alterations in vitro. Liquid biopsy is superior to traditional tissue biopsy techniques and its diagnosis time of disease and repeated diagnosis of liquid biopsy are new breakthroughs in clinical application. Liquid biopsy method can be used to detect most human disease based on genetic biomarkers from body fluids, among which, special biomarkers in blood and cerebrospinal fluid (CSF) samples are the main research objects, and have made good achievements in preliminary clinical applications. The application of optical spectroscopy in the field of liquid biopsy has aroused great interest among researchers and demonstrated the potential of its clinical application for oncology. The aim of this study is to reveal the optical spectroscopic characteristics of the main biochemical components of CSF of brain tumor using visible resonance Raman (VRR) spectroscopy ex vivo. Tumor-associated proteins, glucose, lactate and other metabolites released to CSF can be used as markers for liquid biopsy. We studied the VRR spectra of CSF samples from 7 types of brain tumor patients. The characteristic VRR modes that were found and may be used as a combination of multiple analyte biomarkers include amyloid-β and tau protein, excess neurotransmitters such as glutamic acid derived from the exchange with interstitial fluid (ISF), DNA, glucose, lactate, etc. for optical liquid biopsy analyses. Another interesting finding was that CSF of different types of tumors showed different images similar to the crystallization of water under the optical microscope. Considering our previous study, the current study on CSF provides another proof that the VRR system can provide a complete scan region of 200 - 4000cm-1 as a clinical tool for non-invasive diagnosis of brain disease. © 2024 SPIE.

The advancement in treating medical data grows significantly daily. An accurate data classification model can help determine patient disease and diagnose disease severity in the medical domain, thus easing doctors' treatment burdens. Nonetheless, medical data analysis presents challenges due to uncertainty, the correlations between various measurements, and the high dimensionality of the data. These challenges burden statistical classification models. Machine Learning (ML) and data mining approaches have proven effective in recent years in gaining a deeper understanding of the importance of these aspects. This research adopts a well-known supervised learning classification model named a Decision Tree (DT). DT is a typical tree structure consisting of a central node, connected branches, and internal and terminal nodes. In each node, we have a decision to be made, such as in a rule-based system. This type of model helps researchers and physicians better diagnose a disease. To reduce the complexity of the proposed DT, we explored using the Feature Selection (FS) method to design a simpler diagnosis model with fewer factors. This concept will help reduce the data collection stage. A comparative analysis has been conducted between the developed DT and other various ML models, such as Logistic Regression (LR), Support Vector Machine (SVM), and Gaussian Naive Bayes (GNB), to demonstrate the effectiveness of the developed model. The results of the DT model establish a notable accuracy of 93.78% and an ROC value of 0.94, which beats other compared algorithms. The developed DT model provided promising results and can help diagnose heart disease. © 2024, Zarka Private University. All rights reserved.

The search for selective anticholinergic agents stems from varying cholinesterase levels as Alzheimer’s Disease progresses from the mid to late stage. In this computational study, we probed the selectivity of FDA-approved and metabolite compounds against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) with molecular-docking-based virtual screening. The results were evaluated using locally developed codes for the statistical methods. The docking-predicted selectivity for AChE and BChE was predominantly the consequence of differences in the volume of the active site and the narrower entrance to the bottom of the active site gorge of AChE. © 2024 by the authors.

This final commentary, in comic format, frames this special issue using Graphic Medicine methodologies to explore broader themes and meanings related to the scientific study of gender and health. Comics can be seen as a way to introduce complex human narratives and as an exploratory tool to ask broader social-contextual and ethical questions about health and medicine. This piece is also constructed through the lens of queer scholarship, which, together with the comics format, provides opportunities to build more embodied, complicated narratives about gender, sexuality and health. Most importantly, comics are used as a modality to tell compelling narratives about how individuals, rather than populations, may be impacted by biomedical conceptualizations of gender and health. The commentary includes a series of graphic narratives containing hypothetical stories and cases: stories of how individuals may be harmed within healthcare systems by rigid framings of gender, sex and sexuality, and stories about how gender socialization may impact health in subtle ways. These narratives furthermore examine the inextricable link between gender and power, illustrating how overt and covert manifestations of power may shape a person's health over the life course. Finally, the piece explores how expansive views of gender may contribute to positive health care experiences. The intention of this piece is to nudge scientific researchers and clinicians alike to approach the topic of gender, sexuality and health with nuance and curiosity. © 2023 The Author(s)

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Designing and analyzing lesson plans is a ubiquitous practice in teacher education, and yet we know little about how preservice teachers (PSTs) notice elements of their lesson plans that afford opportunities for supporting equitable student sensemaking. We investigate how the use of a tool, a framework for supporting equitable sensemaking, guided 36 PSTs to notice four features of equitable sensemaking in their plans. Qualitative analysis of PSTs’ comments about their plans generated a coding rubric and three associated levels for noticing. These levels included (1) paying little to no attention to explicit strategies and making assumptions about the ways that traditional classroom practices might facilitate equitable sensemaking; (2) attending to some strategies but providing few details; and (3) attending to and making connections between specific moves and broader principles and practices of supporting equitable student sensemaking. Guided by the tool, PSTs were able to provide elaborate details about their plans to design instruction to engage students in authentic scientific work focused on investigating and explaining phenomenon (feature 4) and to position students as knowers (feature 2), but they struggled to discuss explicit ways to leverage students’ lived experiences in their science lessons (feature 3) and facilitate equitable engagement and participation (feature 1). This suggests that even with the use of a tool, it may be challenging for PSTs to attend to and describe in detail strategies for leveraging students’ out-of-school lives and interests for science learning and explicit classroom strategies for making learning accessible and engaging for all. © 2024 Association for Science Teacher Education.

We present an expanded and improved deep-learning (DL) methodology for determining centers of star images on Hubble Space Telescope/Wide-Field Planetary Camera 2 (WFPC2) exposures. Previously, we demonstrated that our DL model can eliminate the pixel-phase bias otherwise present in these undersampled images; however that analysis was limited to the central portion of each detector. In the current work we introduce the inclusion of global positions to account for the point-spread function (PSF) variation across the entire chip and instrumental magnitudes to account for nonlinear effects such as charge transfer efficiency. The DL model is trained using a unique series of WFPC2 observations of globular cluster 47 Tuc, data sets comprising over 600 dithered exposures taken in each of two filters—F555W and F814W. It is found that the PSF variations across each chip correspond to corrections of the order of ∼100 mpix, while magnitude effects are at a level of ∼10 mpix. Importantly, pixel-phase bias is eliminated with the DL model; whereas, with a classic centering algorithm, the amplitude of this bias can be up to ∼40 mpix. Our improved DL model yields star-image centers with uncertainties of 8-10 mpix across the full field of view of WFPC2. © 2024. The Astronomical Society of the Pacific. All rights reserved.