University of South Carolina

This commentary examines two recent papers featuring intriguing discoveries on the molecular processes and structural foundations involved in the activation and suppression of the N‐requirement gene 1 (NRG1) helper nucleotide‐binding leucine‐rich repeat receptor. image

INTRODUCTION Inflammasome activation is implicated in Alzheimer's disease (AD). We previously demonstrated that nucleoside reverse transcriptase inhibitors (NRTIs), drugs approved to treat human immunodeficiency virus (HIV) and hepatitis B, also inhibit inflammasome activation. METHODS We evaluated the association between NRTI exposure and subsequent development of AD in the United States Veterans Health Administration over a 24‐year period and in the MarketScan database over a 14‐year period using propensity score‐matched multivariate Cox hazards regression and Kaplan–Meier analyses. RESULTS We report that in humans, NRTI exposure was associated with a significantly lower incidence of AD in two of the largest health insurance databases in the United States. In contrast, exposure to non‐NRTIs, protease inhibitors (PIs), and integrase strand transfer inhibitors (INSTIs) was not associated with reducing AD incidence. DISCUSSION These findings support the concept that inflammasome inhibition could benefit AD and provide a rationale for prospective clinical testing of inflammasome inhibitors such as NRTIs in AD. Highlights Exposure to NRTIs, a class of anti‐retroviral drugs that also block inflammasome activation, was associated with a reduction in the risk of developing AD. The reduction in risk was observed in two large, diverse health insurance databases after correcting for numerous comorbidities known to be associated with AD. Other anti‐HIV therapies such as non‐NRTIs, protease inhibitors, and integrase strand transferase inhibitors were not associated with a reduction in the risk of developing AD. Our work provides a rationale for randomized clinical trials of inflammasome inhibitors in AD.

Emerging wildlife pathogens often display geographic variability due to landscape heterogeneity. Modeling approaches capable of learning complex, non-linear spatial dynamics of diseases are needed to rigorously assess and mitigate the effects of pathogens on wildlife health and biodiversity. We propose a novel machine learning (ML)-guided approach that leverages prior physical knowledge of ecological systems, using partial differential equations. We present our approach, taking advantage of the universal function approximation property of neural networks for flexible representation of the underlying dynamics of the geographic spread and growth of wildlife diseases. We demonstrate the benefits of our approach by comparing its forecasting power with commonly used methods and highlighting the obtained insights on disease dynamics. Additionally, we show the theoretical guarantees for the approximation error of our model. We illustrate the implementation of our ML-guided approach using data from white-nose syndrome (WNS) outbreaks in bat populations across the US. WNS is an infectious fungal disease responsible for significant declines in bat populations. Our results on WNS are useful for disease surveillance and bat conservation efforts. Our methods can be broadly used to assess the effects of environmental and anthropogenic drivers impacting wildlife health and biodiversity.

In response to the call for a research agenda to eliminate youth mental health disparities, this paper presents a purposive review of five areas of promise and concern for the amelioration of disparities in school settings: (1) mental health stigma, (2) behavioral health screening and referral disparities, (3) behavioral health treatment and outcome disparities, (4) socially and culturally responsive practices, and (5) alternatives to disparity‐reproducing school discipline and carceral behavioral health systems. Each topic is placed in context with current advances in the study of multitiered systems of support (MTSS) frameworks, particularly the Interconnected Systems Framework (ISF) for integrating behavioral health personnel, expertise, and practice in schools, emphasizing the enormous opportunity and importance of school‐based behavioral health systems research for youth mental health parity. Three approaches to research are highlighted with rationale for their likelihood to contribute to both youth mental health parity and to mutually beneficial research production, use, and participation in communities: Community‐partnered research (such as community‐based participatory research), research–practice partnerships, and research–policy partnerships. Recommendations are made for congruent research, training, and funding structures necessitated by these high impact approaches.

The availability of suitable niche space constrains where species can occur geographically. This tie between niche space and geographic space is crucial when estimating species geographic distributions in a changing climate. However, specific combinations of climatic conditions may be overrepresented in geographic space, highlighting the potential disconnect between climatic niche area and geographic range size. We develop a niche density estimator that accounts for the geographic availability of climatic niche space, relate this to traditional estimates of niche area and explore how these niche estimates are related to species geographic range size. To do this, we use data on over 230,000 species recorded in the Global Biodiversity Information Facility, providing a thorough test of the sensitivity of niche estimation technique on geographic range size–climatic niche scaling relationships, and clarifying the link between geographic space and environmental space by considering the density of available environments in environmental space. Niche density was more strongly related to species geographic range size than niche area, highlighting the role of the geographic availability of climatic niche space in biogeographic relationships. As species geographic ranges and environmental conditions change, understanding the ecological and evolutionary determinants of this positive scaling between geographic range size and niche size is an important research frontier.

The Tertiary Institutions Social Health Insurance Program (TISHIP) was created by the National Health Insurance Authority (NHIA) to enhance health insurance coverage among students in tertiary institutions in Nigeria. Despite being in existence for many years, a significant number of eligible students remain uncovered by the program. It is unclear whether the intended users are sufficiently aware of the program’s existence and benefits. Therefore, this study assessed the level of knowledge about the TISHIP program and related factors among students enrolled in selected tertiary institutions in Southwest Nigeria. Using a descriptive cross-sectional study design, 430 students were surveyed using a multi-stage random sampling technique from the University of Ibadan, Ibadan, Nigeria and the Federal College of Agriculture, Ibadan. Data were collected using a structured self-administered questionnaire of twenty-one questions using both a 4-point Likert scale questions and other questions not on a Likert scale to comprehensively assess the students’ knowledge and perceptions. Responses to the Likert scale were reversed, so that “Strongly disagree” had a score of “1”, and “Strongly agree” was assigned a score of “4”. Overall, six questions were used to determine the knowledge of TISHIP, and the highest score was therefore “24”. Persons with scores corresponding to the mean value and above (≥12 points) were categorized to have “Good knowledge of TISHIP”, while those with lower score (<12) were said to have “Poor knowledge of TISHIP”. One question “What is your view about TISHIP” was used to determine respondent’s perception of TISHIP. Responses were arranged as follows: “Good”, “Poor”, and “Not sure”. “Good” and “Not sure” were merged as “Poor”. Chi-square tests were conducted to determine the association between knowledge and utilization of TISHIP with sociodemographic characteristics of the respondents. The level of significance was set at p < 0.05. The mean age of the respondents was 21.2 ± 2.9 years. More than half of the respondents (52.1%) were males, and 76.0% were university students. Overall, 46.0% of the students had good knowledge of TISHIP, and 173 (73.0%) had a good perception of the program. Being male (Chi-square = 0.043, p = 0.836) was associated with having a good knowledge of TISHIP. University students were approximately 3 times more likely to have good knowledge of TISHIP compared to college students (AOR = 2.616, 95%CI = 1.209 – 5.658, p = 0.015). Postgraduate students were three times more likely to have a good perception of TISHIP (AOR = 3.257, 95%CI = 0.622 – 17.051, p = 0.162) than undergraduate students. Knowledge of TISHIP was low while perception of the program was promising among students in tertiary institutions. Increased efforts to effectively communicate existence and benefits of TISHIP will be critical to the success of the program.

Background The increasing prevalence of poor mental and physical health in adults is a global health concern. Given the scope of this problem, scalable and effective treatment interventions are needed. While podcasts (online digital audio files) are becoming more popular, the extent of podcast use in mental, physical, or combined health interventions has not been reviewed. Objective This scoping review primarily aims to summarize the available evidence regarding the use of podcasts in health promotion interventions. A series of 5 research questions was designed to systematically review and accurately represent podcast use in current research interventions. Methods We conducted a search of electronic databases (MEDLINE, PsycINFO, Embase, CINAHL, Scopus, and CENTRAL), gray literature articles, and relevant journals reported in the English language. Eligible studies targeted adults (aged ≥18 y), included a podcast in at least 1 intervention, and measured a mental or physical health outcome. Results Overall, 51 articles (published studies: n=26, 51% and gray literature articles: n=25, 49%) were deemed eligible. In total, 58% (15/26) of the included peer-reviewed studies were published in the last 5 years, suggesting that the use of podcasts as an intervention approach is increasing. On average, 85.6% (n=2104) of the participants included in these research studies were women. In total, 31% (8/26) of the studies contained a female-only sample. In contrast, no research studies contained a male-only sample. Most peer-reviewed published studies (19/26, 73%) and gray literature sources (22/25, 88%) of the podcasts were used within multicomponent interventions, with most targeting physical health outcomes (peer-reviewed publications: 14/26, 54% and gray literature sources: 13/25, 52%). Results pertaining to podcast design, sources, theoretical principles, and thorough process evaluation indicators were heterogeneous. Conclusions The versatility that podcasts can offer as a medium for reaching and engaging with participants and end users was evident in this scoping review. While research using podcasts is growing, many (18/26, 69%) studies included in this scoping review were conducted in the United States and sampled female participants, highlighting the need to diversify the field. As expected, there was a high level of variation across the included studies in relation to how podcasts were used and designed within interventions. To address this, a standardized approach would be valuable in guiding researchers and practitioners through both the development and reporting phases of future podcast research, including aspects such as theoretical framework, a description of podcast development (eg, co-design and end-user engagement), objective podcast use, and process evaluation data.

Purpose To examine whether various data structures, visualizations, and “nudges” impact police leader’s (lieutenant and above) strategic crime prevention decisions. Methods We utilized a multi-armed survey experiment in which police leaders (N = 1195) were randomly assigned various data visuals and “nudges” to investigate their impact on police leader’s decision-making intentions. Results When police leaders were presented process behavioral charts and hot spot street segment maps, they more accurately identified jurisdictional crime trends and high crime areas, respectively. However, when presented with kernel density maps compared to hot spot maps, police leaders were not influenced by data visuals and no more likely to respond to crime problems with empirically promising evidence-based practices. Conclusions This study highlights the value of data presentation and visualizations in how data is presented (e.g., charts, maps) influences police leaders’ decision-making. Data analysts should present refined (micro-unit) data visuals to avoid misappropriating police resources in areas where police resources may not be heavily needed. Further, process behavioral charts provide realistic variations in jurisdictional crime trends, which were clearly interpreted by police leaders. Police researchers should consistently keep police leaders apprised of “what works, what doesn’t, what’s promising,” while police leaders should engage with data/research and consider implementing evidence-based practices.

Suicide is a significant public health issue for young adults, especially for those living with intellectual and developmental disabilities (IDD). Our team explores the increasing concern of suicidality in young adults with IDD, emphasizing the importance of targeted suicide prevention and intervention strategies. Accordingly, we review relevant literature on the prevalence of suicidality among young adults with IDD and the factors contributing to their elevated risk. We also discuss the limitations of current suicide assessment and screening tools for individuals with IDD and the need for specialized adaptations to effectively address their unique needs. Drawing from two theoretical models, the Behavioral Pathway Model (BPM) and the Suicidal Barometer Model (SBM), we illustrate how these frameworks can be applied to assess suicide risk in young adults with IDD. In addition, a fictional case study is presented to highlight real-world applications of these models in suicide prevention. Finally, we provide recommendations for caregivers and helping professionals, focusing on strategies to improve suicide risk assessment, intervention planning, and training for those working with individuals with IDD. Considerations and implications for caregivers and helping professionals are included throughout our paper.

Parents living with HIV (PLWH) are often affected by co-occurring trauma, substance use, and mental health concerns. These complex challenges may contribute to intergenerational transmission of health risk, yet few studies have examined how these challenges affect family well-being in HIV-affected families. HIV care providers' insights can inform prevention efforts. Our study used qualitative focus group methods in two Southeast US cities to explore providers' perceptions of PLWH's challenges navigating parenting and HIV-related concerns and strengths supporting positive adaptation. Six themes emerged: PLWH's challenges; strengths; COVID-19 impacts; impact of trauma, mental health, and substance use; supports needed; and engagement strategies. Providers highlighted trade-offs between parents' self-care and parenting and that parents often draw strength from their children. Challenges identified were both common to parenting and unique to living with HIV. Results underscore the need for multilevel prevention, including addressing basic needs; integration of mental health and medical services; and increased family services.

Plain Language Summary Anthropogenic activities have significantly increased contaminant loads in (semi‐)confined aquifers, leading to elevated pollution levels in these groundwater systems. The contaminant migration from semi‐confined aquifers to coastal water threatens eco‐environmental security in marine systems, yet its dynamic mechanisms remain poorly understood. This study examines contaminant transport in a semi‐confined aquifer, which is separated from the overlying unconfined aquifer by an aquitard. Our study highlights the critical role of unconfined aquifers and saltwater wedges in deep‐layer contaminant transport. The upward leakages drive contaminants from semi‐confined to unconfined aquifers before discharge to the sea, albeit with less influence on saltwater‐density counterparts. During transport, these contaminants can mix with recirculating seawater in the underlying and overlying saltwater wedges, forming potential but long‐overlooked reactive zones. If the aquitard permeability is too low or too high, deep‐layer contaminants may migrate more quickly from the semi‐confined aquifer to the sea. These findings aid in predicting contaminant migration in semi‐confined aquifers and guiding groundwater management strategies to mitigate their adverse effects.

Plain Language Summary Satellite altimeters measure fluctuations in the ocean surface remotely, which can be used to observe major current systems like the Loop Current (LC) and roughly circular flow features called Loop Current Eddies and Loop Current Frontal Eddies (LCFEs). These circulation features significantly define upper ocean processes in the Gulf of Mexico (GoM). In December 2022, the Surface Water and Ocean Topography (SWOT) mission was launched, pioneering a new era of altimeters that resolve submesoscale surface ocean features. In August 2023, Hurricane Idalia formed in the Caribbean Sea and traversed northward through the northeastern GoM. Idalia ultimately grew to a major Category 4 hurricane that made landfall in Florida as a Category 3. SWOT identified more small‐scale features like LCFEs than conventional nadir altimeters due to its higher spatial resolution. The increased presence of LCFEs during the passage of Idalia could decrease the local sea surface temperatures due to their cold cores that correspond with regions of high chlorophyll‐a and low salinity, and could eventually contribute to a decrease in Idalia's intensity. Overall, SWOT was capable of sampling fine‐scale surface ocean features, thus proving its effectiveness for advancing the field of air‐sea interactions during extreme weather events like hurricanes.

Purpose Black women are 30% more likely to die of ovarian cancer than White women. Discrimination may affect cancer health disparities through pathways including socioeconomic disadvantage, chronic stress, and access to care. In this study, we evaluated associations of discrimination and trust in physicians with all-cause mortality among Black women with ovarian cancer. Methods Using data from the African American Cancer Epidemiology Study (AACES), we included 592 Black ovarian cancer patients who completed an interview. Discrimination and trust in physicians were measured using the Everyday Discrimination, Major Experiences of Discrimination, and Trust in Physicians scales, respectively. We used Cox proportional hazard models to compute multivariable-adjusted hazard ratios (HR) and 95% confidence intervals (CIs) associating everyday discrimination, major experiences of discrimination, and trust in physicians with all-cause mortality. Results Approximately 43% reported experiencing at least one major experience of discrimination, 16% reported high everyday experiences of discrimination, and the median trust in physician score was 35. The association between higher experiences of everyday discrimination was HR = 0.84 (95% CI: 0.63, 1.11), compared with low experiences of everyday discrimination. We observed that more major experiences of discrimination had 1.25-times the mortality rate compared with low experiences of major discrimination (95% CI: 0.84, 2.20). Higher trust in physicians was associated with slightly lower mortality rates (HR = 0.91, 95% CI: 0.74, 1.14). Conclusion We observed complexities in the relationships of everyday discrimination, major experiences of discrimination, and trust in physicians with mortality among Black women with ovarian cancer. Future work to understand the these relationships is likely warranted.

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. Here, we show that the collapse of aging flood control infrastructures, compounded by inadequate risk assessment and emergency preparedness, dramatically escalated the disaster’s impact. Our findings underscore the urgent need for systematic dam safety evaluations, enhanced flood forecasting, and adaptive risk management strategies that address climate extremes and infrastructure vulnerabilities.

Diversity education in the K‐12 years is a contentious issue in the contemporary US context. Given evidence that parental identity influences beliefs about and support for diversity education, we qualitatively explored cisgender‐heterosexual and LGBTQ+ parents’ ( N = 609) beliefs about the appropriateness of inclusive educational policies in K‐12 classrooms. We collected qualitative data on parental perceptions of inclusive signals in classrooms (e.g., displaying a rainbow flag) and on perceptions of inclusive curriculum (whether children should learn about diversity at school/from teachers or at home/from parents). Parents’ responses reflected variability in support for inclusive signals. Cisgender‐heterosexual parents were more likely to endorse that cues should not be allowed and were less likely to indicate holistic support of cues compared to LGBTQ+ parents. For inclusive curriculum, cisgender‐heterosexual parents were more likely than LGBTQ+ parents to endorse that diversity information should be discussed only at home with parents. We contextualize parents’ responses within contemporary political rhetoric (e.g., discussions of Parents’ Bills of Rights) and highlight implications for educators and policymakers.

There are over 35 million concrete crossties (sleepers) installed in track in North America, with approximately 750,000 to 1,500,000 additional new ones installed annually. These components have been the focus of much research over recent years, which is resulting in significant advancements in their design and use. New solutions are addressing rail seat deterioration, abrasion, splitting, and other issues that have been associated with past derailments or have required major intervention. Moreover, concrete crosstie design is moving toward a performance-based approach, which is more efficient than the traditional prescription-based methods with generous safety factors. Smart crossties are also emerging, which go far beyond the traditional concepts of crosstie application. This paper presents an overall picture of the state of the art of concrete crossties in North America, linking fundamentals, industry challenges, design approaches, recent developments, and trends for the future.

We introduce brain2print, a web-based application that converts T1-weighted MRI scans into 3D printable models. By leveraging artificial intelligence (AI), brain2print performs all computations directly on the user’s device, preserving privacy while removing the need for any software installation. This open-source tool enables users to convert voxel-based imaging into 3D meshes, thus facilitating broader access to 3D printing for educational, clinical, and research purposes. Prior methods for converting MRI scans into printable meshes were time-consuming and required multiple software tools, some of which are difficult to install and use. In contrast, brain2print provides a seamless and fast alternative. Users can drag and drop MRI scans onto the web page, select the desired AI segmentation models, and create a mesh that can be customized for complexity and structure, resulting in models ready for 3D printing. The zero-footprint design of brain2print ensures broad compatibility across devices, as it operates entirely in the browser. This approach not only simplifies the process but also safeguards user privacy by keeping all data on local hardware.

Introduction: Studies have evaluated the receipt of preventive care among children with Down syndrome, but barriers surrounding access to screenings and health care in general have not been well described among this population across the United States. This study describes parental perspectives on barriers to screenings and health care. Method: Twenty-four semistructured interviews with parents of children with Down syndrome were administered to families across South Carolina in 2022. Thematic analysis was used to identify salient themes related to barriers to care. Results: Barriers to preventive care identified by families included ineffective care coordination, insurance-related concerns, health care provider access shortages, and language barriers. Discussion: Findings can be used to address problems with major aspects of medical care and to make care more family-centered and accessible for children with Down syndrome.

Objective. Liver cancer has a high incidence rate, but experienced doctors are lacking in primary healthcare settings. The development of large models offers new possibilities for diagnosis. However, in liver cancer diagnosis, large models face certain limitations, such as insufficient understanding of specific medical images, inadequate consideration of liver vessel factors, and inaccuracies in reasoning logic. Therefore, this study proposes a diagnostic assistance tool specific to liver cancer to enhance the diagnostic capabilities of primary care doctors. Approach. A liver cancer diagnosis framework combining large and small models is proposed. A more accurate model for liver tumor segmentation and a more precise model for liver vessel segmentation are developed. The features extracted from the segmentation results of the small models are combined with the patient’s medical records and then provided to the large model. The large model employs chain of thought prompts to simulate expert diagnostic reasoning and uses Retrieval-Augmented Generation to provide reliable answers based on trusted medical knowledge and cases. Main results. In the small model part, the proposed liver tumor and liver vessel segmentation methods achieve improved performance. In the large model part, this approach receives higher evaluation scores from doctors when analyzing patient imaging and medical records. Significance. First, a diagnostic framework combining small models and large models is proposed to optimize the liver cancer diagnosis process. Second, two segmentation models are introduced to compensate for the large model’s shortcomings in extracting semantic information from images. Third, by simulating doctors’ reasoning and integrating trusted knowledge, the framework enhances the reliability and interpretability of the large model’s responses while reducing hallucination phenomena.