Benedictine University

Pancreatic cancer (PC) is a malignant tumor of the digestive system that has a bad prognosis. N6-methyladenosine (m6A) is involved in a wide variety of biological activities due to the fact that it is the most common form of mRNA modification in mammals. Numerous research has accumulated evidence suggesting that a malfunction in the regulation of m6A RNA modification is associated with various illnesses, including cancers. However, its implications in PC remain poorly characterized. The methylation data, level 3 RNA sequencing data, and clinical information of PC patients were all retrieved from the TCGA datasets. Genes associated with m6A RNA methylation were compiled from the existing body of research and made available for download from the m6Avar database. The LASSO Cox regression method was used to construct a 4-gene methylation signature, which was then used to classify all PC patients included in the TCGA dataset into either a low- or high-risk group. In this study, based on the set criteria of cor>0.4 and p value < 0.05. A total of 3507 gene methylation were identified to be regulated by m6A regulators. Based on the univariate Cox regression analysis and identified 3507 gene methylation, 858 gene methylation was significantly associated with the patient’s prognosis. The multivariate Cox regression analysis identified four gene methylation (PCSK6, HSP90AA1, TPM3, and TTLL6) to construct a prognosis model. Survival assays indicated that the patients in the high-risk group tend to have a worse prognosis. ROC curves showed that our prognosis signature had a good prediction ability on patient survival. Immune assays suggested a different immune infiltration pattern in patients with high- and low-risk scores. Moreover, we found that two immune-related genes, CTLA4 and TIGIT, were downregulated in high-risk patients. We generated a unique methylation signature that is related to m6A regulators and is capable of accurately predicting the prognosis for patients with PC. The findings might prove useful for therapeutic customization and the process of making medical decisions.

Objectives: Overeating interventions and research often focus on single determinants and use subjective or nonpersonalized measures. We aim to (1) identify automatically detectable features that predict overeating and (2) build clusters of eating episodes that identify theoretically meaningful and clinically known problematic overeating behaviors (e.g., stress eating), as well as new phenotypes based on social and psychological features. Method: Up to 60 adults with obesity in the Chicagoland area will be recruited for a 14-day free-living observational study. Participants will complete ecological momentary assessments and wear 3 sensors designed to capture features of overeating episodes (e.g., chews) that can be visually confirmed. Participants will also complete daily dietitian-administered 24-hour recalls of all food and beverages consumed. Analysis: Overeating is defined as caloric consumption exceeding 1 standard deviation of an individual's mean consumption per eating episode. To identify features that predict overeating, we will apply 2 complementary machine learning methods: correlation-based feature selection and wrapper-based feature selection. We will then generate clusters of overeating types and assess how they align with clinically meaningful overeating phenotypes. Conclusions: This study will be the first to assess characteristics of eating episodes in situ over a multiweek period with visual confirmation of eating behaviors. An additional strength of this study is the assessment of predictors of problematic eating during periods when individuals are not on a structured diet and/or engaged in a weight loss intervention. Our assessment of overeating episodes in real-world settings is likely to yield new insights regarding determinants of overeating that may translate into novel interventions.

Cancer is among the leading causes of mortality worldwide. While considerable attention has been given to genetic and epigenetic sources of cancer-specific cellular activities, the role of alternative mRNA splicing has only recently received attention as a major contributor to cancer initiation and progression. The distribution of alternate mRNA splicing variants in cancer cells is different from their non-cancer counterparts, and cancer cells are more sensitive than non-cancer cells to drugs that target components of the splicing regulatory network. While many of the alternatively spliced mRNAs in cancer cells may represent “noise” from splicing dysregulation, certain recurring splicing variants have been shown to contribute to tumor progression. Some pathogenic splicing disruption events result from mutations in cis-acting splicing regulatory sequences in disease-associated genes, while others may result from shifts in balance among naturally occurring alternate splicing variants among mRNAs that participate in cell cycle progression and the regulation of apoptosis. This review provides examples of cancer-related alternate splicing events resulting from each step of mRNA processing and the promising therapies that may be used to address them.

Declining reptilian populations has been a growing concern over the last couple of decades. One such declining species of concern, the Blanding's turtle Emydoidea blandingii, occurs as isolated populations in North American prairie‐wetlands and is at risk of extirpation due to habitat loss and fragmentation, and increased predator (e.g. racoons, coyotes) populations due to supplemented resources in urban environments. To help mitigate declining populations, wildlife managers have invested in the conservation of this species through head‐starting (i.e. reared in ex situ) and juvenile release programs to augment wild Blanding's turtle populations. However, much of their spatial and winter/thermal ecology is understudied, and data for juveniles, and juveniles reared ex situ is especially scarce, yet this information is imperative to understanding shortfalls and improving head‐starting efforts in the future. In spring 2016 (RR2016) and 2017 (RR2017) we released a cohort (n = 12 each year) of head‐started juvenile Blanding's turtles equipped with radio transmitters and temperature dataloggers into a prairie‐wetland in the greater Chicago region, North America. Using ground‐based radio telemetry, we determined seasonal movement areas (SMAs; spring, summer and fall) and annual home ranges (AHRs) for both RR2016 and RR2017 cohorts via kernel density (KD) estimates. We also investigated the thermal characteristics of overwintering for both juvenile cohorts. We found that SMAs for the RR2016 cohort, but not for the RR2017 cohort, significantly differed across seasons for most SMA estimators. We also found that juveniles in both cohorts not only survived overwintering, but also displayed similar overwintering phenology (i.e. initiation: October–November; termination: April) and temperature variation as Blanding's turtles adults in other studies. Overall, our results indicate that head‐started juvenile Blanding's turtles may be able to acclimatize quickly to their natural environment post‐release. Our study provides evidence to the efficacy of well‐developed head‐starting programs that aim to augment and preserve imperiled turtle populations.

We present the results of a field study examining the effect of losses disguised as wins (LDWs) on subsequent slot machine gambler betting behavior. An LDW occurs when the amount won is less than the amount bet. Using non-experimental, individual transaction gambling data, we examine post LDW betting behavior in a panel of 42,669 gamblers and 17 million slot machine plays. The primary empirical findings include: (1) streaks of three LDWs greater than 75% of the original amount bet lead slot gamblers to increase the amount bet on the next spin; (2) streaks of three LDWs less than 25% of the original amount bet results in gamblers decreasing their bet size on the next spin; (3) slot machine gamblers play faster following streaks of three LDWs compared to losses. We interpret these behavioral findings of differing outcomes associated with small versus large LDWs as consistent with a cognitive dissonance effect (Festinger, 1957). Specifically, the disconnect between the amount “won” (actually lost) and the audio and video stimulus produced by the slot machine highlighting the LDW, produces a dissonance-related arousal that players seek to avoid or reduce leading to changes in betting behavior. Our results complement the experimental findings on LDWs and suggest that the size of the LDW matters in examining the impact on gambling behavior.

Purpose: This study explores whether nativity differences in health care and sociodemographic factors help to account for nativity differences in low birth weight (LBW) when comparing US-born Black women (USBW) to Black Immigrant women (BIW). Methods: Bivariate analyses and multinomial nested logit (MNL) models were performed using the National Survey of Family Growth (NSFG) dataset. Results: Statistically significant nativity differences between USBW and BIW were found across variables of LBW (p = .009), marital status (p < .001), education level (p < .001), receiving public assistance (p < .001), health care coverage (p < .001), age (p < .001), and poverty level income (p < .001). Results from the MNL models indicated that BIW were 91% less likely to have a LBW baby (p < .001). When accounting for other sociodemographic and health care related variables differing by nativity, although a statistically significant, narrowing gap between BIW and USBW was observed (OR = .12, p < .001), BIW were still less likely to have a LBW baby. Conclusions: Differences between USBW and BIW across sociodemographic variables and health care related factors related to adverse pregnancy outcomes were observed in this study. Controlling for the factors attenuated nativity differences but did not eliminate the differences on LBW. Future research should continue to explore this relationship.

The title character of the early twelfth-century Persian Kushnāmeh (Epic of Kush), written by Irānshāh ebn Abu al-Khayr, is an anti-hero—the monstrous Kush, a warrior-king with elephantine ears and tusks. The Kushnāmeh has a two-layered frame tale, which emphasises the epic’s dependence on potentially unreliable sources. I argue that the frame tales, Kush’s monstrous qualities, and other features of the text—including some apparent seams and inconsistencies in the narrative—may be understood as intentional, interpretable features of the text that contribute to its parodic and fictional qualities. The figure of Kush is a parodic inversion of the legendary king Jamshid, who in the Shāhnāmeh (Epic of Kings) represents the preservation of life and social hierarchy, as well as Iranian communal identity. The epic thus challenges the authority and authenticity of received narratives, especially that of the monumental Shāhnāmeh, and legitimises the author’s rewriting of texts that were among the most important literary monuments of kingship in Islamicate culture.

Background: Female sexual activity and, accordingly, birth rates, tend to decline in times of stress, such as a pandemic. Additionally, when resources are scarce or exogenous conditions are threatening, some women may engage in sexual activity primarily to maintain socioeconomic security. Having unwanted sex may indicate sexual activity in exchange for economic security. Objective: To describe patterns and correlates of unwanted sex, defined as having sex more frequently than desired, among U.S. women early in the COVID-19 pandemic. Study design: The National U.S. Women's Health COVID-19 Study was conducted in April 2020, using a nested quota sample design to enroll 3,200 English-speaking women (88% cooperation rate) ages 18-90 years recruited from a research panel. The quota strata ensured sufficient sample sizes in sociodemographic groups of interest, namely racial and ethnic sub-groups. Patterns of sexual activity, including unwanted sex early in the pandemic, were described. To further elucidate the experiences of women reporting unwanted sex, open-ended responses to an item querying "how the coronavirus pandemic is affecting your sex life" were assessed using conventional content analysis. Logistic regression analyses - adjusting for sociodemographic characteristics, self-reported health and pre-pandemic health-related socioeconomic risk factors (HRSRs), including food insecurity, housing instability, utilities and transportation difficulties and interpersonal violence - were used to model the odds of unwanted sex by pandemic-related change in HRSRs. Results: The proportion of women who were sexually active early in the pandemic (51%) was about the same as in the 12 months pre-pandemic (52%), although 7% became active and 7% became inactive. Eleven percent of sexually active women were having unwanted sex in the early pandemic. Rates of anxiety, depression, traumatic stress symptoms and each of the five HRSRs assessed were about 2 times higher among women having unwanted sex compared to others (p-values <0.001). Women having unwanted sex were also 5 times more likely than others to report increased frequency of sex since the pandemic (65% vs 13%, p<0.001) and 6 times more likely to be using emergency contraception (18% vs 3%, p<0.001). Women reporting unwanted sex commonly described decreased libido or interest in sex related to mood changes since the pandemic, having "more sex," fear or worry about transmission of the virus due to sex, and having sex to meet the partner's needs. Among sexually active women, odds of unwanted sex (adjusting for demographic, reproductive and health factors) were higher among women with one (aOR 2.0, 95% CI 1.1, 3.8) and two or more pre-pandemic HRSRs (aOR 6.0, 95% CI 3.4, 10.6). Among sexually active women with any pre-pandemic HRSRs, those with new or worsening transportation difficulties early in the pandemic were particularly vulnerable to unwanted sex (aOR 2.7, 95% CI 1.7, 4.3). Conclusions: More than one in ten sexually active U.S. women was having unwanted sex early in the COVID-19 pandemic. Socioeconomically vulnerable women, especially those with new or worsening transportation problems due to the pandemic, were more likely than others to engage in unwanted sex. Pandemic response and recovery efforts should seek to mitigate unwanted sexual activity and related health and social risks among women.

Financial support (capital) and technological improvement are the crucial factors in any industry, and they are also the major factors of marine economics. However, the government has supplied a great deal of capital and the marine economy has been deeply explored and researched using advanced technology. The marine industry is still not the mainstay industry in Chinese industry. Considering this, the issues of how to address financial support, technical improvement and marine economics are common foci within the government and society, especially regarding the economic growth of China. It is necessary to develop the marine economy. However, many scholars only pay attention to the aspects of marine financial support, marine technology and marine economic development separately, and no scholars have studied the relationship between the three at present. Therefore, this article establishes a model to conduct empirical tests regarding the relationship between financial support, technological improvement and marine economic development using panel data from 11 coastal regions in China. The results show that financial support has a negative impact on technological improvement, but it has a positive impact on marine economic efficiency. Technological improvement has a positive impact on financial support and marine economic efficiency. However, marine economic efficiency has a negative impact on financial support, and it has a positive impact on technological improvement. Through impulse response analysis, there is a significant correlation between them. This article calculates marine economic efficiency with the SBM-DEA model and analyzes relationships with the BVAR model, which is proposed to improve the development and efficiency of the marine economy. Financial support should be used in the rather important parts of the marine economy so that the marine economy can achieve returns in the short-term and attract more circulating funds to enter the marine economy, which impacts the long-term stable and sustainable growth of the marine economy. Moreover, financial support, financial liberalization, technological research and technological creation in the progress of marine economic construction should focus on effectively using circulating funds, which provides geo-advantages and aids in building a new marine economic ecological circle.

A biologically-inspired method to access 2-formylpyrrole structures is reported using an Achmatowicz reaction and condensation sequence. This robust synthetic process has been used to access a variety of 2-formylpyrrole structures related to naturally isolated and bioactive compounds. Several families of pyrrole-based natural products have recently been isolated, and these structurally related compounds have been shown to demonstrate interesting bioactive properties. Synthesis targets include the natural products sinopyrine C and pyrrolezanthine.

Higher education has been in a financially precarious position for many years – facing either a total transformation or elimination. Tuition increases and fewer college-age students from shifting demographics are primary reasons for the financial distress. Alternative financial stability models have assumed linear variable relationships and improperly calculate the probability of default. Stakeholders have historically relied upon models such as those developed by Edmit and the Department of Education which are inadequate at separating financially sound from unsound universities. We used an Automated Machine Learning approach utilizing multiple models to explain the relationship between metrics and the probability of default/closure allowing for more informed managerial decisions. This research, although applied to the homogeneous group of small liberal arts universities, can be applied to online and state universities and will allow the opportunity to take preventive steps to mitigate the likelihood of closing due to financial distress.

We are facing both a short-term emergency cooling crisis and a long-term greenhouse gas (GHG) draw down planetary ecological crisis. We must address both. The first requires emergency direct cooling, or temporary “triage” or a “tourniquet, for our bleeding planet.” The second requires rapid GHG emissions reductions and draw down and natural planetary regeneration that realistically will take at least a few decades and may take a century or more. Conflating the challenge and opportunity of the second crisis with a response to the first crisis will not produce a rapid and credible global response to the second crisis because of structural economic inequity and fossil fuel dependency that is deeply embedded in the current global economy. Realistically, we need emergency direct climate cooling to address the first crisis and a long-term binding global cap and trade emissions trading system to address the second. The Florin proposal that conditions Stratospheric Aerosol Injection (SAI) direct climate cooling on credible GHG emissions and draw down is a step in the right direction, but omits other direct climate cooling methods and effectively makes the deployment of SAI contingent on a global emissions trading system (ETS) that may not be possible before the deployment of SAI becomes necessary. Rather than conflating our two climate crises, or conditioning the solution of the first on a solution to the second, we need to address both on an emergency basis by putting all options on the table as called for in the Healthy Planet Action Coalition (HPAC) proposal. JEL Classification: Q54, Q55, Q56, Q57, Q58

Many authors have noted the apparent ‘decoupling’ of the taxonomic and ecological severity of mass extinction events, with no widely accepted mechanistic explanation for this pattern having been offered. Here, we test between two key factors that potentially influence ecological severity: biosphere entropy (a measure of functional redundancy), and the degree of functional selectivity (in terms of deviation from a pattern of random extinction with respect to functional entities). While theoretical simulations suggest that the Shannon entropy of a given community prior to an extinction event determines the expected outcome following a perturbation of a given magnitude, actual variation in Shannon entropy between major extinction intervals is insufficient to explain the observed variation in ecological severity. Within this information-theoretic framework, we show that it is the degree of functional selectivity that is expected to primarily determine the ecological impact of a given perturbation when levels of functional redundancy are not substantially different.

This paper explores racial differences in maternal risk factors associated with adverse pregnancy outcomes across urban and rural geographies using 2019 data from the Behavioral Risk Factor Surveillance System. Bivariate chi-square tests and logistic regression were performed which showed statistically significant geographical differences among Non-Hispanic (NH) Black pregnant women across income levels (p = .016) and perceived health status (p = .003). Regression analyses indicated an increased racial gap between NH White pregnant women and other racial/ethnic groups. The findings support that there are statistically significant racial differences in maternal risk factors across urban and rural geographies for NH Black and Hispanic pregnant women.

Currently, there is a lack of a holistic framework that ensures Industry 4.0 systems include Internet of Things (IOT) devices and computer systems designed to be fail-safe during cyber-attacks. The silo view of treating industrial risk, IT risk, and software quality as separate fields are leading to exploitable and hackable systems as documented by recent events. A stable system requires the collaboration and integration of engineering experts in quality, software design, and reliability along with quality managers and auditors to focus on the intersection of technology and safety/reliability. The field of Cybernetics was originally created as an interdisciplinary field to understand and control complex systems. A multi-faceted and cross-disciplinary approach will be required to design fail-safe systems that can withstand cyberattacks in Industry 4.0. The integration of roles and responsibilities cannot succeed without a similarly aligned cross-functional approach, including a RAIC framework.

Objective: Sleep and eating behaviors are disturbed during the premenstrual phase of the menstrual cycle in a significant number of reproductive-age women. Despite their impact on the development and control of chronic health conditions, these behaviors are poorly understood. In the present study, we sought to identify affective and psychological factors which associate with premenstrual changes in sleeping and eating behaviors and assess how they impact functionality. Methods: Fifty-seven women provided daily ratings of premenstrual symptomatology and functionality across two-three menstrual cycles (156 cycles total). For each participant and symptom, we subtracted the mean day +5 to +10 ("post-menstruum") ratings from mean day -6 to -1 ("pre-menstruum") ratings and divided this value by participant- and symptom-specific variance. We completed the statistical analysis using multivariate linear regression. Results: Low interest was associated with a premenstrual increase in insomnia (p ≤ 0.05) and appetite/eating (p ≤ 0.05). Furthermore, insomnia was associated with occupational (p ≤ 0.001), recreational (p ≤ 0.001), and relational (p ≤ 0.01) impairment. Conclusions: Results of the present analysis highlight the importance of apathy (i.e., low interest) on the expression of behavioral symptomatology, as well as premenstrual insomnia on impairment. These findings can inform treatment approaches, thereby improving care for patients suffering from premenstrual symptomatology linked to chronic disease conditions.

We offer a framework for developing the collaborative workplace, developed through a case study of a subsystem of Intuit Canada, a knowledge-based product development firm known for strong collaboration. Grounded in interviews, observations, informal conversations, and archival data, our framework reveals a series of factors that shape work, relationships, and behaviors to promote collaboration widely. Beyond factors, we uncover what it is about them, the underlying properties that created the conditions for employees to work, relate and contribute collectively. We show how the factors interrelate to create two collaborative subsystems; one fostering widespread alignment around strategic goals and the other fostering locally led interactivity to operationalize those goals. We illustrate how the duality works in practice and conclude with implications for future research and practice.

Objectives Certain aspects of nutrition assessment within the Nutrition Care Process (NCP) are sex-specific, meaning they require nutrition professionals to select a male or female sex (i.e., growth charts, body fat percentage, and the normal ranges for certain biochemical markers). This presents a unique question for nutrition professionals working with transgender and gender diverse (TGGD) patients who may be medically transitioning or identify as non-binary. Methods LB is a 17 year-old, white individual who was assigned male at birth, identifies as non-binary, and uses they/their pronouns. They wear both masculine and feminine clothing and are not interested in pursuing medical interventions. LB is 5’5” and weighs 120 lbs. Which growth chart would be appropriate to assess LB's weight status? JY is a 50 year-old African American individual who assigned female at birth, identifies as transgender male, and uses he/his or they/their pronouns. JY's past medical history indicates he medically transitioned in his mid-20s, has been on masculinizing HT for the past 25 years, and is amenorrheic. Given JY's past medical history, which reference values would be most appropriate to assess hemoglobin and hematocrit? Hemoglobin - 12 g/dl Hematocrit - 37% RBCs - 5.0 ml Platelet count - 250,000 WBC - 6,000 cells/ml MR is a 30 year-old, Hispanic individual who was assigned male at birth, identifies as transgender female, and uses she/her pronouns. She started feminizing HT one month ago, is 5’8” tall and weighs 180 lbs; she would prefer a smaller physique and expressed that she would like to lose about 30 lbs. MR walks her dog for 30 minutes daily. Using the Estimated Energy Requirement (EER) equation, what are MR's energy needs to maintain her current weight? What energy requirement would support MR's weight loss goal? Results The cases of LB, JY and MR illustrate the potential strategies that nutrition professionals can utilize. 1. Use reference values consistent with sex assigned at birth for patients who have not medically transitioned (LB). 2. Individualize nutrition assessment to align with the client's medical transition (JY). 3. Express data as a range between the female-male reference values (MR). Conclusions Nutrition professionals can apply specific strategies and clinical reasoning to address sex-specific aspects of nutrition assessment when caring for TGGD patients. Funding Sources None.

Objectives Previous studies have investigated if meal timing is associated with energy and macronutrient intake. However, few focus on the combination of food intake and meal timing and their association with diet quality. We use machine learning to examine how day-level meal patterns (food group intake, meal timing) predict diet quality among adults. Methods We analyzed diet data from interviewer-administered 24-hour recalls from the NHANES 2015–2016 and 2017–2018 cycles (N = 9761). Fifteen food groups were examined: fruit, fruit juice, vegetables, whole grains, meats (red, cured, poultry, seafood), eggs, plant protein, dairy, oils, solid fats, added sugar, and alcohol. Proportion of intake for each food group per participant - relative to that participant's total daily intake of that food group - was included as input parameters for each meal (breakfast, lunch, dinner). Diet quality was computed using the Healthy Eating Index 2015 (HEI-2015); higher scores represented better diet quality. Cutoff threshold for a higher vs. lower quality diet was defined by the 75th percentile of HEI-2015 for the dataset (cutoff = 59.24). Decision tree modeling identified the inputs that contributed to the highest information gain and the optimal classification threshold for each input. Results On average, participants consumed 0.4 ± 0.8 cup equivalents of fruits and 0.6 ± 1.2 ounce equivalents of whole grains. These two food groups contributed most to the diet quality prediction model, which had a 78% classification accuracy for the dataset. Lower quality diets were associated with: a) < 2% of both total fruit and whole grain intake at breakfast; b) >2% of total fruit but < 2% of total whole grain intake at breakfast; or c) >2% of total whole grain intake at breakfast but < 2% of total fruit intake at breakfast and lunch. Higher quality diets were associated with: a) >2% of both total fruit and whole grain intake at breakfast or b) < 2% of total fruit intake at breakfast but > 2% of both total whole grain intake at breakfast and fruit intake at lunch. Food group intake at dinner was not a top predictor in the preliminary model. Conclusions Preliminary analyses revealed that the timing of fruit and whole grain consumption are important predictors of diet quality. Future studies should test the preliminary model on additional datasets and should include snacking episodes in the analyses. Funding Sources None.