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Variable Selection and Prediction Using Machine Learning Models in High-Dimensional Data
No full textThe early detection of complex diseases is essential for improving patient outcomes, particularly for conditions that remain asymptomatic until advanced stages. Biomarkers serve as key indicators of disease presence and progression, but selecting an optimal subset remains a challenge due to the high dimensionality of modern biological datasets. While advances in omics technologies have identified numerous candidate biomarkers, their effective utilization requires robust selection methods to ensure interpretability, cost-effectiveness, and predictive reliability in both cross-sectional and longitudinal settings. To address these challenges, we propose two novel approaches: Stability Selection Ensemble Learning (STABEL) for cross-sectional data and Longitudinal Stability Selection Ensemble Learning (LSTABEL) for longitudinal data. These methods integrate stability selection with ensemble learning to improve biomarker selection and predictive accuracy while mitigating overfitting. Stability selection enhances traditional variable selection by producing a stable subset of significant variables. Additionally, ensemble learning enhances generalization capabilities by combining the predictions of multiple models in order to mitigate the limitations of individual models. Simulation studies demonstrate the superiority of STABEL and LSTABEL over traditional methods in selecting truly relevant biomarkers and enhancing prediction performance. These methodologies are particularly valuable in applications where early detection is crucial. We illustrate their effectiveness in two case studies: ovarian cancer, where selecting a concise biomarker panel can enhance early diagnosis and treatment strategies, and Alzheimer’s disease, where robust biomarker discovery can improve the prediction of disease progression and cognitive decline. We also developed an R package, stabel, for the STABEL method
Gallium β-Cyclodextrin Nanoparticles Containing both Gallium Protoporphyrin and Gallium Nitrate Exhibit Antimicrobial Activity against Nontuberculous Mycobacteria in Vitro and in Vivo
No full textEffective and safe antibiotics active against pathogenic mycobacterial species are needed. Iron is an essential element for bacterial survival. Ga(NO3)3 (GN) and Ga protoporphyrin (GP) as iron mimetics have each been shown to inhibit the iron metabolism and growth of various mycobacterial species. In this study, the dual cyclodextrin nanoparticle (CDGPGN) is prepared that carries GP and GN using a sonication homogenization technique to increase the efficacy of the combination therapy. CDGPGN shows a long-acting antimicrobial activity against Mycobacteroides abscessus residing in monocyte-derived macrophages (MDM). A murine pulmonary study showed that the CDGPGN also inhibited the growth of M. abscessus and M. avium complex (MAC) in the lungs. GP induced mycobacterial superoxide dismutase (SOD) activity and reduced catalase activity. GN neither reduces nor increases SOD and catalase activities in mycobacteria. This study confirms that dual CDGPGN nanoparticles containing both GN and GP have potential for development as antimycobacterial agents against M. abscessus
Improving Safety in Magnetic Resonance Imaging: A Grounded Theory Approach to Exploring the Perceptions of Technologists and Magnetic Resonance Safety Officers in Pediatric Settings
No full textThe purpose of this study was to explore how efforts to reduce adverse events related to Magnetic Resonance Imaging (MR) exams have influenced safety from the perspective of Magnetic Resonance (MR) technologists and certified Magnetic Resonance Imaging Safety Officers (MRSOs) in pediatric facilities. This study also sought information regarding common causes of MR related adverse events, how the American College of Radiology’s (ACR) guidance on MR safe practices has influenced safety in the scanning environment, and how patient and staff safety may be improved from the perspective of technologists performing these exams. The American College of Radiology (ACR) is the premiere professional organization for radiology in the United States and has driven industry-wide change with its formal guidance on the topic of MR safety. These guidelines have been the impetus behind immeasurable positive safety reform in the industry for everything from facility design and the establishment of MR related roles, to safely scanning implants, and proper patient screening, all of which is critically important to safely scanning patients, pediatric or otherwise. The literature revealed a gap exploring MR safety from the perspective of technologists, driving the need to perform this research as this population of healthcare workers was identified as critical in the prevention of safety events. Key findings in this study revealed that participants felt the ACR’s safety guidance is robust and has been effective, yet there are enhancements that could be made, perhaps at the organizational level, to further optimize the work environment. Participants in the study expressed the need for more time in exam execution, stronger support for a culture of safety, more organization-wide MR safety education, and enhanced communication mechanisms. The implications for practice indicate a need to further explore how organizations can enhance their culture of safety to optimize work environments
Utilization of TRICARE’s Childbirth and Breastfeeding Support Demonstration: Access to Lactation Services Among Military Families
No full textIn January 2022, the Department of Defense launched a five-year pilot program called the TRICARE Childbirth and Breastfeeding Support Demonstration. This demonstration aimed to cover lactation services for Tricare beneficiaries. This project included an electronic survey and was created and completed by 577 participants. Eligible participants needed to have given birth in the last 24 months and have TRICARE as their primary insurance. Participants completed this survey to help understand if they were aware of lactation benefits, if they utilized the service, and if it improved their breastfeeding experience.
Out of the 577 participants, 485 were eligible for the project. Eligible participants needed to have given birth in the last 24 months and have TRICARE as their primary insurance. The survey responses were analyzed to determine the percentages for each response.
After the results were analyzed, we learned that 54.75% of participants utilized their lactation benefits, and 45.25% did not. Out of those who did not utilize this benefit, 33.26% were unaware that this service was available to them. Many participants expressed a disconnect between their providers and understanding TRICARE benefits.
Encouraging providers to have a better understanding of TRICARE benefits available to families through the Childbirth and Breastfeeding Support Demonstration could increase referrals and usage of the benefit, positively impacting breastfeeding initiation and duration
Evaluating Joint Control Teaching Procedures for Teaching Yes-No Responding with Tact and Intraverbal Questions for Children with Autism
No full textResponding to yes and no questions is a general language skill that allows individuals to efficiently interact with their verbal community. Few behavior analytic studies have sought teaching this skill in general, with even fewer studies seeking to teach this skill when it pertains to a tact or intraverbal context. All behavior analytic studies to date seeking to teach this skill have used direct prompting and reinforcement of the yes and no responses, but there is little guidance for what can be done if this teaching strategy is not producing desired acquisition. The current experiments examined a teaching procedure informed by joint control conceptualizations to teach yes-no responding across tact and intraverbal operants after direct prompting and reinforcement failed to result in acceptable levels of responding and acquisition of this skill. Experiment 1 showed that standard teaching procedures resulted in mastery levels for four of nine data sets. Experiment 2 showed that joint control teaching procedures resulted in mastery levels for one data set. Overall, this preliminary investigation did not support joint control teaching procedures for teaching yes-no. Implications, potential pre-requisites, and future research are discussed
Analgesic Safety and Efficacy of Intrathecal Morphine in Elective Posterior Lumbar Fusion: A Systematic Review With Meta-Analyses
No full textBackground. We evaluated perioperative intrathecal morphine (ITM) compared with placebo or standard postoperative pain strategies in adults undergoing elective posterior lumbar fusion.
Methods. A systematic search of EMBASE, MEDLINE, the Cochrane Library, and Google Scholar (December 12, 2023) identified studies involving ITM in posterior lumbar fusion. Eligible patients were ≥18 years. Two reviewers extracted outcomes and assessed non-randomized studies with the Newcastle- Ottawa scale. Odds ratios (OR) and mean differences (MD) with 95% confidence intervals (CI) were calculated using fixed- and random-effects models.
Results. Eleven studies met the inclusion criteria. ITM significantly lowered opioid requirements within 24 hours (MD -0.72, 95% CI [-1.30, -0.14], I² = 91.08%, p = 0.015) and pain scores at 24 hours (MD -0.57, 95% CI [-1.01, -0.13], I² = 73.17%, p = 0.010). Reductions were also seen in pain scores at 48 hours (MD -0.63, 95% CI [-1.55, 0.29], p = 0.178), hospital stay (MD -0.71, 95% CI [-1.77, 0.36], p = 0.191), sedation (OR -0.18, p = 0.594), and respiratory depression (OR -0.08, p = 0.782), though these were not statistically significant. ITM increased the incidence of pruritus (OR 1.04, 95% CI [0.45, 1.64], I² = 43.55%, p \u3c 0.001), with non-significant rises in urinary retention (OR 0.45, p = 0.070) and nausea/vomiting (OR 0.03, p = 0.847).
Conclusion. Although based on relatively small and methodologically heterogeneous studies, these analyses suggest that perioperative ITM enhances analgesia and maintains an acceptable safety profile following posterior lumbar fusion
Differential Plasma Carotenoid Profiles in Hypertensive Disorders of Pregnancy
No full textBackground: Hypertensive disorders of pregnancy (HDP) affect one in six pregnancies globally. The etiology of HDP remains unclear but is known to involve oxidative stress. While the body produces endogenous antioxidants, antioxidative nutrients, like carotenoids, remain critical in modulating oxidative stress. The statuses of several carotenoids have been linked to hypertension in both pregnant and non-pregnant populations. However, their associations with the spectrum of HDP, including gestational hypertension (GH), chronic hypertension (CH), and preeclampsia (PE), remains unclear. Our objective was to quantify and compare carotenoid intake and plasma levels among HDP. Methods: We conducted a prospective cohort study of patients presenting for delivery at a Midwestern academic medical center between 2015 and 2023. Women ≥ 19 years old delivering at least one infant were eligible for inclusion. Mothers with diseases affecting nutrient metabolism or birthing newborn wards of the state were excluded. Subjects were recruited at delivery for Harvard Food Frequency Questionnaire and plasma sample collection. Plasma carotenoids were analyzed by HPLC-MS. Results: A total of 488 patients, including 270 normotensive (NT), 61 CH, 102 GH, and 55 PE, were recruited. Plasma carotenoid analyses were available for 225 subjects. Plasma total, cis-, and trans-β-carotene were significantly lower in PE (73 mcg/L) compared to NT (170 mcg/L), CH (194 mcg/L), and GH (190 mcg/L) groups. Lutein + zeaxanthin and β-cryptoxanthin were also reduced in PE (142 mcg/L and 81 mcg/L) compared to NT (209 mcg/L and 123 mcg/L) but only β-cryptoxanthin was lower in PE compared to GH (126 mcg/L). Levels of α-carotene were lower in PE (18 mcg/L) compared to both CH (43 mcg/L) and GH (48 mcg/L). Conclusions: These results demonstrate that plasma carotenoid levels differ among HDP and may suggest that oxidative stress in PE depletes circulating carotenoids, differentiating it from other HDP
Presence and Performance: A Cross-Campus Analysis of Academic Performance and Course Evaluations Through the Lens of the Community of Inquiry
No full textSocial, teaching, and cognitive presences have been shown to have promising outcomes for student perceptions and distance education; however, little is known about the relationships between these domains and academic performance. This quantitative, cross-sectional observational study examined the academic performance and perceptions of Physician Assistant students across two campuses—Primary and Distance, which utilized synchronized live content delivery. Using the Community of Inquiry (CoI) framework, the study aimed to (1) evaluate academic performance differences between campuses, (2) assess the relationship between CoI domains and student GPA, and (3) explore the association between CoI and course evaluations.
Findings revealed no statistically significant differences in GPA between campuses or cohort years, suggesting that the program’s use of standardized curricula, synchronous instructional technologies, and consistent faculty engagement effectively supports comparable academic outcomes across geographically distinct cohorts. Although correlations between GPA and CoI domains were positive, they were weak and statistically non-significant, indicating that CoI may be more predictive of affective outcomes than cognitive achievement alone. A strong positive correlation was found between overall CoI scores and course evaluations, reinforcing the theoretical proposition that students who perceive a richer learning environment tend to rate their courses more favorably.
Physician Assistant education is rigorous, requiring students to acquire extensive knowledge and skills to provide high-quality healthcare services to their patients and communities upon graduation. The study’s findings and theoretical implications affirm the relevance of CoI in professional graduate medical education. Practically, the findings suggest that enhancing teaching presence through clear instructional design and timely feedback, promoting social presence via collaborative learning, and strengthening cognitive presence through reflective and problem-based activities can improve student satisfaction and potentially influence retention. Faculty development programs should incorporate CoI principles to support effective online instruction and foster inclusive learning environments.
Recommendations for future research include conducting longitudinal studies to assess the long-term impact of the curriculum and examining correlations with board certification outcomes. Mixed-method approaches and course-specific evaluations may also yield deeper insights into the relationship between instructional design, student perceptions, and academic performance
Species-Specific Discrimination of Bacterial Biofilms Using a Ratiometric Fluorescence Sensor Array and Machine Learning
No full textBiofilms are intricate bacterial communities encased in a self-produced extracellular matrix (ECM) of DNA, lipids, proteins, and polysaccharides. The diverse ECM composition across bacterial species significantly influences the progression of biofilm-associated infections, making precise identification crucial for effective treatment. Traditional methods such as biochemical assays, MALDI-TOF mass spectrometry, DNA sequencing and culturing provide valuable insights but have notable drawbacks, including time-consuming procedures, high costs, and the need for specialized equipment and trained personnel. These limitations hinder the rapid and widespread adoption of biofilm identification in clinical settings, underscoring the need for more streamlined, accurate, and accessible methods. In this study, we employed a paper-based ratiometric sensor array with fluorescent dyes (3-hydroxyflavone derivatives) pre-adsorbed onto paper microzone plates to identify bacterial biofilms. The fluorescence signals from the sensor upon interaction with biofilms were analyzed using linear discriminant analysis and different machine learning algorithms, including neural networks, support vector machines, and naïve Bayes classifiers. Our results show that the sensor array accurately distinguishes between biofilms of eight species with 97.5% classification accuracy. It effectively identifies individual bacteria at OD600 as low as 0.002 o.u. Additionally, using neural networks, the sensor array achieves more than 95% accuracy in distinguishing planktonic bacteria from biofilms and shows over 85% accuracy in identifying clinical bacterial species and biofilms. These findings highlight the sensor\u27s potential for high-precision biofilm identification in laboratory and clinical settings, offering a valuable tool for advancing biofilm research and enhancing clinical diagnostics