University of North Dakota

Cell-free DNAs (cfDNAs) are DNA fragments found in blood. In healthy individuals, cfDNAs are primarily derived from immune cells, while in cancer patients, a significant fraction of cfDNAs originates from cancerous cells. These cancer-derived cfDNAs contain specific mutations, making cfDNA analysis a promising diagnostic biomarker. Recent studies have revealed that epigenetic information, such as DNA methylation and nucleosome positioning, is retained in cfDNAs, enhancing the accuracy of cell-of-origin predictions. This study aims to characterize the chromatin architecture preserved in cfDNAs by looking at nucleosomal DNA enrichment. Nucleosome fragments from both breast and pancreatic cancer patients are significantly enriched in open chromatin regions. A differential enrichment was observed between healthy donors and cancer patients at cell type-specific ATAC-seq peaks. Leveraging this pattern of open chromatin enrichment, we enhanced the prediction accuracy for identifying breast cancer-derived cfDNA through machine learning. Our analysis pipeline provides an interpretable machine learning platform that effectively detects cancer-specific nucleosome enrichment in cfDNAs.

Trade‐offs between food acquisition and predator avoidance shape the landscape‐scale movements of herbivores. These movements create landscape features, such as game trails, which are paths that animals use repeatedly to traverse the landscape. As such, these trails integrate behavioral trade‐offs over space and time. Here, we used remotely sensed imagery to analyze the density of game trails with spatial environmental variables to understand landscape‐scale patterns of herbivore habitat use in an African savanna. Woody plant cover was the best predictor of game trail density, with the highest densities correlating with intermediate woody plant cover. We also explored how patterns of game trail density compared to two known measures of herbivore habitat use (i.e., dung counts and maximum entropy modeling) and found strong quantitative fits. To understand the patterns revealed by the density of game trails, we explored the trade‐off between food acquisition and perceived predation risk across a woody plant cover gradient. Using behavioral observations, we found that the relationship between woody plant cover and the distribution of game trails was likely driven by the risk and reward trade‐off, with less vigilance and more feeding occurring in areas with a high density of game trails and intermediate woody cover. Ultimately, we show that game trails are a novel data source that can be used to identify broadly‐occurring patterns of herbivore habitat use over large spatial scales.

Background Agitation is one of the most challenging behaviors exhibited by people with cognitive decline, causing distress in caregivers, earlier placement into long‐term care and faster disease progression. In order to better manage agitated behaviors in people with cognitive decline, it is important to identify associated factors. The MODERATE (Monitoring Dementia‐Related Agitation Using Technology Evaluation) study aims to characterize agitation using technology and identify precipitants (behavioral or environmental) of agitation. Method People living in the greater Portland, Oregon, USA area were recruited into the study. The inclusion criteria were a diagnosis of mild cognitive impairment or dementia, currently residing with a family caregiver within their own home, and caregiver endorsement of symptom(s) of agitation, irritability/lability, motor disturbance, nighttime behaviors and/or disinhibition in the Neuropsychiatric Inventory‐Questionnaire (NPI‐Q). Bed pressure mats (Emfit) were deployed as part of the ORCATECH platform in their homes, which measure participants' sleep behaviors and their physiological signals through ballistocardiography. The weekly agitation levels of the participants were reported by their family caregivers through modified Cohen‐Mansfield Agitation Inventory‐Short Form questionnaires as part of weekly online surveys. Result Data from the first 8 participants (mean age(SD) = 70 (10)) with bed pressure mats were analyzed. A subset of bed pressure mat outputs was selected to provide a holistic picture of participants' sleep behaviors and their physiology while avoiding multicollinearity. Monitoring period was for a mean (SD) of 315 (190) nights. An individual mixed linear model was built with each included bed pressure mat output and week as the predictors and total agitation level as the model output. After false discovery rate correction, higher duration of wake after sleep onset was a significant predictor of their weekly total level of agitation. The caveats of these results include small sample and varied follow‐up time ranging from 4‐85 weeks of observations per participant. Conclusion Disrupted sleep (measured objectively by bed pressure mat) are positively associated with participants' weekly level of agitation. Future work with larger sample sizes is needed to confirm findings. Unobtrusive identification of behavioral factors associated with agitation can potentially help manage this challenging behavioral symptom.

Background Current tools to assess caregiver burden in individuals caring for people living with dementia commonly involve the use of questionnaires administered at infrequent intervals. Caregiver burden can vary significantly between individuals and at different time points throughout the progression of the disease. There has been research investigating the determinants of caregiver burden, but less is known about what represents a clinically‐meaningful amount of intra‐individual change in caregiver burden. The objective of this preliminary analysis is to present data showing change in caregiver burden over time in a cohort with frequent collection of burden level. Method Data were derived from longitudinal studies involving the ORCATECH technology platform, consisting of ambient, wearable and other sensors deployed in participants’ homes collecting continuous data on daily activities. Participants were individuals with mild cognitive impairment (MCI) or dementia living with a caregiver (one dyad per home). Caregivers completed the Zarit Burden Interview Short Version (ZBI‐12, range 0‐48) weekly through the duration of their participation. ZBI‐12 scores and their distribution were analyzed. Result Data are presented from 47 dyads. Caregivers completed a total of 2949 weekly ZBI‐12 questionnaires (range 2‐118). Caregivers had a mean age of 71.3 and 68% were female. The mean ZBI‐12 score was 15.5 (SD 9.5, range 0‐44). The modal distribution of ZBI‐12 scores demonstrated peaks at 2‐4, 11‐12, and 22‐24, at low, moderate and high levels of burden. The variability in ZBI‐12 scores (standard deviation) increased with the total mean ZBI‐12 score (r² = 0.23) per participant. Conclusion Caregiver burden ranged from very low to high and fluctuated week‐to‐week in the majority of caregivers of individuals with MCI and dementia. Caregivers who had a higher average level of burden also had more variability in their ZBI‐12 scores. More frequent assessments of caregiver burden could help to provide a more complete picture of the dementia care situation. Novel approaches, such as continuous monitoring using home sensors, may provide a method to assess variability in burden level. Future work will evaluate changes in ZBI‐12 scores that represent clinically meaningful differences in caregiver burden and sensor outcome measures that predict higher levels of burden.

Background With the advent of anti‐amyloid therapies, identifying those with underlying amyloid burdens and detecting subsequent clinical effects of this AD pathology is critical. The DETECT‐AD study (ClinicalTrials.gov, NCT05385913) is a simulated secondary prevention anti‐amyloid clinical trial testing digital biomarkers as more sensitive and meaningful primary outcome measures. Clinically prodromal AD patients with estimable rates of AD progression based on Aβ PET status are enrolled as Aβ “positive” (higher amyloid burden) patients who predictably progress (as if receiving placebo) and Aβ “negative” patients progressing more slowly (representing the treatment group). Typical of current trials, participants are screened at entry to determine those with critical CNS amyloid burdens. Given the effort and cost of establishing AD phenotypes, efficient means for this screening are needed. Here we report to date the results of examining the screening process using blood‐based amyloid determinations for identifying florbetapir PET imaging‐based, amyloid status leading to enrollment of prodromal AD trial participants. Method Participants were initially screened by telephone using inclusion/exclusion criteria questionnaires. If passing this phase, participants underwent in‐person cognitive and neurological examinations and clinical blood tests; if passing this phase, an MRI/amyloid PET scan was performed; if passing this last step, the digital technologies were deployed in‐homes. The first 47 participants used this protocol. The subsequent 140 participants underwent a blood amyloid test (plasma Aβ42:40) first, and then the remaining procedures if intermediate or high risk for CNS amyloid (Aβ42:40 < 0.170). Result A Consort Diagram shows the study results (Figure). As of 1/3/2024, 85/100 have been enrolled with mean(SD): follow‐up=59.4(21.3) weeks; age=78.2(6.5); 65% women; MoCA=25.0(2.5); PET SUVR=1.14(0.23), range: 0.806‐2.18. Without blood amyloid pre‐screening, 26% of participants were PET amyloid positive (SUVR≧1.11). With the blood amyloid screening, 52% were PET amyloid positive. Conclusion A simple telephone screen and blood amyloid test significantly improved the yield of amyloid PET positive participants in a simulated clinical trial, which can reduce costs, personnel effort, and participant burden and risk. Follow‐up will suggest how additional simple clinical, digital, and blood‐based biomarkers may further aid in identifying well‐defined target populations for clinical trials.

Background Accumulating evidence suggests that spirituality and religiosity may be associated with improved health outcomes. However, few studies have examined maternal religiosity as a protective factor for perinatal outcomes. We explored the association between maternal religious attendance and pregnancy loss. Methods Data were drawn from the Future Families & Child Wellbeing Study’s first and second waves and medical records (n = 1874). Religious attendance was a self-reported response to the question “About how often do you attend religious services?” Pregnancy loss was measured from responses to the second wave survey question, “Since focal child’s birth, have you had any miscarriages/abortions/stillbirths?” Logistic regression estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between maternal religious attendance frequency and pregnancy loss. Models were adjusted for sampling weights, religious preference, socioeconomic and behavioral factors. Results 8% (n = 164) of mothers reported having a pregnancy loss. Of those with a pregnancy loss, 28% (n = 46) attended services hardly ever and 20% (n = 20) attended services once a week or more. Women who attended services more frequently had 58% increased odds of not experiencing a pregnancy loss (OR:1.58;95%CI:1.01,2.48) after adjusting for potential confounding. A post hoc analysis found no difference in pregnancy loss type or subsequent reproductive history based on attendance level. Conclusions Results suggest that higher maternal religious attendance frequency may be a protective factor for pregnancy loss. Further research is needed to understand the association between maternal religious attendance and mechanisms for pregnancy loss.

The Ordinary Least Squares (OLS) method is widely adopted in studies estimating net profit generation among farmers, despite its strong tendency to produce misleading estimates, particularly when one or more fundamental assumptions are violated. This study examined the determinants of farm income among smallholder cassava farmers in Osun State, Nigeria correcting for various assumptions violations of the classical regression model. Aside from the usual OLS estimator, we employed robust estimators such as Maximum Likelihood-type estimator (M-estimator), Monotone M-estimator (MM-estimator), and Scale estimator (S-estimator) to account for outliers. One hundred and one smallholder farmers in Osun state were randomly selected for the study. Analyses revealed that the major socioeconomic factors affecting farming household profit were access to credit, farm size, years spent in farmers’ associations, years of experience, and distance to the nearest market, which are the major determinants of net farm profit among the cassava-based farming households in the study area. On average, the return on investment (ROI) among cassava-based farming households was found to be ₦1.32 per naira invested. The research findings indicated that cassava cultivation is a profitable venture within the investigated area and recommended robust methodology for effectiveness and accurate information in future analysis.

This paper proposes and develops inexact proximal methods for finding stationary points of the sum of a smooth function and a nonsmooth weakly convex one, where an error is present in the calculation of the proximal mapping of the nonsmooth term. A general framework for finding zeros of a continuous mapping is derived from our previous paper on this subject to establish convergence properties of the inexact proximal point method when the smooth term is vanished and of the inexact proximal gradient method when the smooth term satisfies a descent condition. The inexact proximal point method achieves global convergence with constructive convergence rates when the Moreau envelope of the objective function satisfies the Kurdyka–Łojasiewicz (KL) property. Meanwhile, when the smooth term is twice continuously differentiable with a Lipschitz continuous gradient and a differentiable approximation of the objective function satisfies the KL property, the inexact proximal gradient method achieves the global convergence of iterates with constructive convergence rates.

The purpose of this study was to examine the impact of interpersonal justice perceptions on employee engagement in the three factors of time banditry (classical, technology, and social). In addition, the moderating role of work ethic on the interpersonal justice to time banditry relationship was investigated. Social exchange theory was used to explain why employees might engage in time banditry activities as a result of their interpersonal justice perceptions. A Qualtrics panel was used to collect data via a self-report survey questionnaire using established scales. The sample consisted of 172 individuals employed full-time in hourly paid positions across various industries. An empirical analysis was performed using SPSS Process. Findings of this study confirm the previously proposed negative relationship between interpersonal justice and the three individual factors of time banditry. However, work ethic was only found to moderate the interpersonal justice to classical time banditry relationship. Based on these results, this study suggests that organizations should consider investing in new policy development and/or supervisor training programs on topics such as civility training or conflict resolution to try and prevent and/or manage employee perceptions of interpersonal justice. Additionally, we discuss theoretical and practical implications, limitations, and suggest potential future research.

Background Agitation is one of the most challenging behaviors exhibited by people with cognitive decline, causing distress in caregivers, earlier placement into long‐term care and faster disease progression. In order to better manage agitated behaviors in people with cognitive decline, it is important to identify associated factors. The MODERATE (Monitoring Dementia‐Related Agitation Using Technology Evaluation) study aims to characterize agitation using technology and identify precipitants (behavioral or environmental) of agitation. Method People living in the greater Portland, Oregon, USA area were recruited into the study. The inclusion criteria were a diagnosis of mild cognitive impairment or dementia, currently residing with a family caregiver within their own home, and caregiver endorsement of symptom(s) of agitation, irritability/lability, motor disturbance, nighttime behaviors and/or disinhibition in the Neuropsychiatric Inventory‐Questionnaire (NPI‐Q). Bed pressure mats (Emfit) were deployed as part of the ORCATECH platform in their homes, which measure participants’ sleep behaviors and their physiological signals through ballistocardiography. The weekly agitation levels of the participants were reported by their family caregivers through modified Cohen‐Mansfield Agitation Inventory‐Short Form questionnaires as part of weekly online surveys. Result Data from the first 8 participants (mean age(SD) = 70 (10)) with bed pressure mats were analyzed. A subset of bed pressure mat outputs was selected to provide a holistic picture of participants’ sleep behaviors and their physiology while avoiding multicollinearity. Monitoring period was for a mean (SD) of 315 (190) nights. An individual mixed linear model was built with each included bed pressure mat output and week as the predictors and total agitation level as the model output. After false discovery rate correction, higher duration of wake after sleep onset was a significant predictor of their weekly total level of agitation. The caveats of these results include small sample and varied follow‐up time ranging from 4‐85 weeks of observations per participant. Conclusion Disrupted sleep (measured objectively by bed pressure mat) are positively associated with participants’ weekly level of agitation. Future work with larger sample sizes is needed to confirm findings. Unobtrusive identification of behavioral factors associated with agitation can potentially help manage this challenging behavioral symptom.

Background Inhibitory interneurons normally regulate neural networks underlying memory and cognition, but are disrupted in Alzheimer’s disease. Proper interneuron activity reduces amyloid‐beta, whereas hyperexcitability elevates amyloid levels. Still, the underlying pathologic processes mediating interneuron dysfunction remain unknown. Therefore, we employed a spatial transcriptomics approach to map transcriptomic profiles of interneurons in a temporal and spatial manner. Method Coronal hemibrain sections from early stage (12 wks) and late stage (30 wks) male mice (5XFAD) underwent fluorescence in situ hybridization to identify interneuron subtypes (parvalbumin‐expressing, PV+, or somatostatin‐expressing, SST+). Slides were submitted for GeoMx DSP spatial transcriptomics (2 duplicate slides per timepoint, n = 2 5XFAD and n = 2 WT per slide). Regions of interest (ROIs) were defined in hippocampal and cortical regions (Figure 1). UV‐liberated barcodes from each ROI, restricted to PV+ or SST+ interneurons, were collected by microcapillary and sequenced by the NanoString Max/Flex nCounter system. Differentially expressed genes (DEGs) were assessed by linear mixed‐effect model and the GeoMx analysis suite, and attribution to respective time points, cell type, and anatomic region were sequentially parsed. Result In early‐stage disease, 1,562 DEGs were uniquely expressed by PV+ interneurons and 2,284 DEGs were uniquely expressed by SST+ interneurons. Similarly, at late‐stage disease, 2,790 DEGs were expressed by PV+ interneurons and 2,346 DEGs were uniquely expressed by SST+ interneurons (Figure 2). Focusing on the CA1 region, previously implicated as having a central role in hippocampal dysfunction, interneurons again showed unique alterations. Early‐stage PV+ interneurons in CA1 uniquely expressed 310 DEGs, with “metabolic pathways” having the most DEGs (Figure 3). By contrast, early‐stage SST+ interneurons in CA1 uniquely expressed 422 DEGs, enriched in pathways canonically linked to “amyotrophic lateral sclerosis” and “Alzheimer disease.” Conclusion The most significant altered pathways within AD interneurons at the earliest stages of disease included neurodegeneration and metabolism pathways. Zero or few DEGs overlapped across all regions or neuronal subtypes. Thus, interneurons display distinct profiles and transcriptional changes by brain area at early‐ and late‐stage disease. These findings will inform future mechanistic experimentation, and suggest investigation into neural circuit dysfunction in AD will require consideration of anatomic subregion specificity.

Background Alzheimer’s disease (AD) is an age‐related neurodegenerative disorder affecting nearly 50 million individuals worldwide. Besides aging, various comorbidities can increase the risk of AD, such as asthma. However, the molecular mechanism(s) underlying this asthma‐associated AD exacerbation is unknown. This study was designed to explore the effects of house dust mite‐induced asthma on AD‐related brain changes using the AppNL‐G‐F transgenic mouse model. Method Male and female C57BL/6 wild type and AppNL‐G‐F mice (8‐9 months old) were exposed to either saline or house dust mite (dose: 833µg/kg in saline) every alternate day for 16 weeks. Mice were sacrificed at the end of the experiment and broncho‐alveolar lavage fluid (BALF), lungs, blood, and brains were collected. BALF was analyzed for immune cell markers, inflammatory mediators, and LDH activity. Lung sections were stained with Alcian blue and Masson’s Trichrome to examine mucus and collagen production, respectively. The serum was analyzed for cytokine levels. Brain sections were immunostained for Aβ, GFAP, and collagen‐4. Finally, frozen hippocampi and cortices were used to perform Aβ ELISAs and cytokine arrays, respectively. Result Dust‐mite exposure increased inflammatory cells, cytokine levels, and LDH activity in the BALF and increased the mucus and collagen production in the lungs from both sexes and genotypes, suggesting induction of a severe asthma‐like condition. This correlated with increased levels of serum cytokines in all dust‐mite‐exposed groups. In agreement with this peripheral change, hippocampi from asthma‐induced male and female AppNL‐G‐F mice demonstrated elevated Aβ plaque load and increased soluble Aβ 1‐40/42 and insoluble Aβ 1‐40 levels. Dust‐mite exposure also increased astrogliosis in both sexes of AppNL‐G‐F mice, as indicated by GFAP immunoreactivity. Additionally, dust‐mite exposure‐induced asthma elevated cortical levels of several cytokines in both sexes and genotypes. Finally, dust‐mite exposed groups also showed a disturbed BBB integrity in the hippocampus of AppNL‐G‐F mice, as indicated by decreased collagen‐4 immunoreactivity. Conclusion Dust‐mite exposure induced a severe asthma‐like condition that exacerbated Aβ pathology, astrogliosis, cytokine changes, and disturbed BBB integrity in the brains of male and female AppNL‐G‐F mice. Defining the mechanisms of secondary effects of asthma on the brain may provide a novel therapeutic approach for both asthma and AD.

Students in the course take part in a semester long simulation of a country “Marashia” that has just come out of a decade long civil war. This course is a “long-form” simulation playing out over the course of a semester. This course is designed to meet one of my university’s goals for diversity as this course provides essentials studies (general education) credit for “analyzing worldview.”

Background Marriage promotes breastfeeding duration through economic and social supports. The COVID-19 pandemic disproportionately affected marginalized communities and impacted women’s employment and interpersonal dynamics. This study examined how marriage affects breastfeeding duration across socioeconomic and racially minoritized groups during COVID-19, aiming to inform social support strategies for vulnerable families in public health crises. Methods For this cross-sectional study, data were drawn from the 2017–2021 North Dakota Pregnancy Risk Assessment Monitoring System (weighted n = 41433). Breastfeeding duration was self-reported, and 2-, 4-, and 6-month duration variables were calculated. Marital status(married, not married) and education (< high school education, ≥high school education) were drawn from birth certificates. Income (≤ US$48,000, > US$48,000) and race/ethnicity (White, American Indian, Other) were self-reported. Infant birth date was used to identify pre-COVID (2017–2019) and COVID (2020–2021) births. Logistic regression estimated odds ratios and 95% confidence intervals for the association between marital status and breastfeeding duration outcomes. Models were fit overall, by COVID-19 era and by demographic factors. Lastly, demographic-specific models were further stratified by COVID era. Models were adjusted for maternal health and sociodemographic factors. Results Overall, married women consistently had 2-fold higher odds of breastfeeding across all durations during both pre-COVID and COVID eras. Pre-COVID, marriage was a stronger predictor for all breastfeeding durations in low-income women (4-month duration OR 4.07, 95%CI 2.52, 6.58) than for high-income women (4-month duration OR 1.76, 95%CI 1.06, 2.91). Conversely, during COVID, marriage was a stronger predictor of breastfeeding duration for high-income women (4-month duration OR 2.89, 95%CI 1.47, 5.68) than low-income women (4-month duration OR 1.59, 95%CI 0.80, 3.15). Findings were similar among American Indian women and those with less than high school education, in that both groups lost the benefit of marriage on breastfeeding duration during the COVID-19 pandemic. Conclusion Marriage promotes breastfeeding duration, yet the observed benefit was reduced for low-socioeconomic and racially minoritized populations during the COVID-19 pandemic. These observations highlight the disproportionate impacts low-socioeconomic and racially minoritized populations face during public health crises. Continued research examining how major societal disruptions intersect with social determinants to shape breastfeeding outcomes can inform more equitable systems of care.

Ultralow compressible materials, which have high bulk modulus (K), are invaluable in extreme conditions due to their ability to undergo significant compression without structural failure. As large number of borides can be found with high K, this study develop a computational framework to scan the vast chemical space to identify the ultralow compressible borides. Transformer-based networks are helpful to generate new chemical compositions due to their self-attention mechanism, scalability, and ability to capture long-range dependencies. First, we developed a transformer-based network to generate new binary and ternary boride compositions based on the known boride compositions. Next, we trained a hybrid model based on AdaBoost and Gradient Boosting algorithms with mean absolute error (MAE) of 14.1 GPa to scan the high K borides. The CALYPSO code was used to find the possible structures for those materials. After predicting K for broad chemical domain, we found that Re-B and W-B systems are promising ultralow compressible materials. We then performed density functional theory (DFT) calculations to investigate the stability of high K materials. Our computations suggest that Re3B2, Re2B3, W5VB4, and Re5CrB4 materials exhibit K > 300 GPa with negative formation energy and energy-above-hull less than 40 meV. Those materials are mechanically and dynamically stable based on the elastic constant calculations and the phonon dispersion.

This article offers a concise exploration of the profound impact of asynchronous learning on modern education. Delving into its core characteristics and benefits, the authors reveal how asynchronous learning offers flexibility, structured guidance, tailored content delivery, and opportunities for learner autonomy. Reflective practices and boundary-breaking interactions are key elements that enhance engagement and understanding. Real-world examples underscore its effectiveness.

By employing a Ventajas/Assets y Conocimientos/Knowledge framework (Rendón et al., Ventajas/Assets y Conocimientos/Knowledge: Leveraging Latin@ strengths to foster student success. Center for Research and Policy in Education, The University of Texas at San Antonio, 2014), this chapter critiques the superficial recognition of Hispanic Heritage Month at Research 1 Institutions with an HSI designation (R1-HSIs), advocating for an HSI cultural wealth paradigm (HCWP) that genuinely recognizes racial intersectionality within HSIs. Additionally, the chapter expands on HCWP consciousness as a form “servingness” (Garcia et al., Review of Educational Research, 89(5), 745–784, 2019) and student success.