6501 research outputs found
Sort by
The Neuroprotective Role of Lipoxin A4 in Reinstating Blood Brain Barrier Integrity in Neuroinflammatory Disease Processes
Get PDFBackground: The blood-brain barrier (BBB), formed by the vascular endothelium, astrocytic foot processes, pericytes, is a highly selective barrier that is responsible for maintaining brain homeostasis and ultimately proper neuronal function. Disruption of the BBB, leading to increased BBB permeability, has been reported in several neurodegenerative diseases, including Alzheimer’s disease (AD) and traumatic brain injury (TBI).1 Loss of BBB integrity leads to the proliferation of pro-inflammatory cytokines, including TNFɑ, IL-1β, and IL-6.2 Moderate inflammation has a beneficial response in the system following an acute injury. However, prolonged inflammation has been known to perturb homeostasis and have devastating neurodegenerative effects.4-7 Therefore, anti-inflammatory compounds are extensively tested for their potential therapeutic role in lowering these inflammatory changes. Lipoxins (LXs) are a class of arachidonate-derived eicosanoids, which are a class of specialized pro-resolving lipid mediators (SPMs).8 Hence, lipoxins are recognized as “breaking signals” in the inflammatory process. One form of lipoxin, Lipoxin A4 (LXA4), has been found to decreased production of proinflammatory mediators, inhibit neutrophils chemotaxis and infiltration to the site of injury, and promote the phagocytic clearance of debris by macrophages.4,12,13,14 This literature review aims at understanding the neuroprotective role of LXA4 in reducing BBB breakdown and reinstating BBB integrity.
Hypothesis: LXA4 treatment attenuates acute inflammation and reinstates the BBB integrity in acute BBB breakdown and inflammation.
Methods: A comprehensive literature search was performed using PubMed and EMBASE databases.
Conclusion: LXA4 serves a critical role in resolution of inflammatory process by regulating the activation of monocytes and modulating the generation of reactive oxygen species (ROS). LXA4 treatment has shown to reinstate the BBB integrity in acute BBB breakdown models
The Impact of Vitamin Supplementation (D, B12, B9) on Behaviors Associated with Autism Spectrum Disorder
Get PDFBackground: One in 36 children in the United States are diagnosed with Autism Spectrum Disorder (ASD). Although heritability of the condition ranges from 40 to 80%, other factors such as vitamin levels, may have a significant impact on the risk of development. These vitamins include D, B12, and B9.
Purpose: To assess the impact vitamin supplementation has on behaviors associated with ASD, and to determine which specific aspects of ASD may be improved with vitamin supplementation.
Methods: A literature review was performed. The search was utilized PubMed, JSTOR and Web of Science. Keyword strings included: “Vitamin D B12 B9 folate cobalamin supplementation brain autism spectrum disorder neurological development”, “Vitamin D B12 B9 folate cobalamin supplementation brain autism spectrum disorder neurological development”, and “Vitamin D B12 B9 folate cobalamin supplementation brain autism spectrum disorder neurological development”
Results: Supplementation with Vitamin D was associated with decreases in both irritability and hyperactivity. Vitamin B12 Supplementation showed improvements in several behaviors including hyperactivity, tantrumming and receptive language. Vitamin B9 Supplementation was associated with an improvement in verbal communication and may be indicated as an effective adjunct therapy to structured teaching programs.
Conclusions: Although each form of supplementation was associated with positive behavior changes, the research included contradicting outcomes and further research is warranted to strengthen existing conclusions
Waiting for a Cure: Factors Influencing Melanoma Treatment Delays
Get PDFMelanoma, with a five-year survival rate of 94% in early-stage diagnosis, drops significantly when diagnosed at later stages, making identifying barriers to timely treatment crucial. This literature review examines factors influencing melanoma treatment wait times and their impact on patient outcomes. Elderly, male, and Medicare patients, along with those with higher Breslow thickness and severe melanoma stages, experienced longer wait times. Patients receiving intervention within 30 days had better survival rates. Lack of knowledge and misconceptions about melanoma contribute to delayed care, particularly in communities with lower incidence rates. Black patients faced longer waits from diagnosis to surgery, indicating disparities. Socioeconomic factors also play a role, with lower-income neighborhoods experiencing longer wait times. Targeted interventions are needed to reduce these disparities. Enhancing public health education and addressing patient-based factors can improve outcomes. Further research is required to explore the impact of melanoma across racial groups and investigate factors like insurance coverage and access to care. Community education initiatives could lead to earlier interventions. Understanding these factors is essential for improving access to timely melanoma treatment and enhancing patient outcomes
Improved Cardiac Auscultation Competency Interweaving Visual, Auditory, and Tactile Stimuli: A Preliminary Study
Get PDFMETHODS: A pilot randomized controlled trial was conducted at our institution\u27s simulation center with 32 first year medical students from a single medical institution. Participants were randomly divided into two equal groups and completed an educational module on the identification and pathophysiology of five common cardiac sounds. The control group utilized traditional education methods, while the interventional group incorporated multisensory stimuli. Afterwards, participants listened to randomly selected cardiac sounds and competency data was collected through a multiple-choice post-assessment in both groups. Mann-Whitney U test was used to analyze the data.
Results: Data were analyzed using the Mann-Whitney U test. Diagnostic accuracy was significantly higher in the multisensory group (Mdn=100%) compared to the control group (Mdn=60%) on the post-assessment (U=73.5, p\u3c0.042). Likewise, knowledge acquisition was substantially better in the multisensory group (Mdn=80%) than in the control group (Mdn=50%) (U= 49, p\u3c0.031).
CONCLUSIONS: These findings suggest the incorporation of multisensory stimuli significantly improves cardiac auscultation competency. Given its cost-effectiveness and simplicity, this approach offers a viable alternative to more expensive simulation technologies like the Harvey simulator, particularly in settings with limited resources. Consequently, this teaching modality holds promise for global applicability, addressing the worldwide deterioration in cardiac auscultation skills and potentially leading to better patient outcomes. Future studies should broaden the sample size, span multiple institutions, and investigate long-term retention rates
Women’s comfort with mobile applications for menstrual cycle self-monitoring following the overturning of Roe v. Wade
Get PDFBackground: The overturning of Roe v. Wade in June 2022 has many implications for American women of reproductive age, as well as for researchers focused on women’s health in the United States (U.S.). Personal reproductive health data, such as information collected by menstrual cycle (MC) tracking applications (apps), can now be bought, sold, or accessed by law enforcement to enforce limits on abortion. American women have grown concerned about data privacy and have even deleted MC tracking apps following the overturning of Roe v. Wade. This concern is problematic as these apps may advance our understanding of women’s MC experiences by capturing time-sensitive data. The present study was designed to provide updated insight into women’s perceptions of these apps, including the response rate to a study of this nature and women’s willingness to self-report demographic information in this context, following the Supreme Court decision. Methods: A total of 206 women aged 18–60 years who were identified as pre- or perimenopausal completed an anonymous, cross-sectional survey between August and November 2022. Results: Most respondents had experience using a MC app at the time of reporting; 53.4% (n=110) were current users, and an additional 48 participants had used MC tracking apps in the past. Over one-third of participants (38.3%; n=75) indicated that they had reconsidered using such an app because of current events; 30.3% (n=59) preferred methods of MC tracking that did not involve app-based technology, and 34.2% (n=67) reported that they are not willing to participate in research that involves daily tracking of the MC. Conclusions: Overall, the feasibility of menstruation-related research that includes mobile apps is fairly low, given women’s current comfort with this technology compared to the Roe era, and there is a need to establish criteria and protections for use of mobile apps in women’s health research
Reconfigurable modular soft robots with modulating stiffness and versatile task capabilities
Get PDFSoft robots have revolutionized machine interactions with humans and the environment to enable safe operations. The fixed morphology of these soft robots dictates their mechanical performance, including strength and stiffness, which limits their task range and applications. Proposed here are modular, reconfigurable soft robots with the capabilities of changing their morphology and adjusting their stiffness to perform versatile object handling and planar or spatial operational tasks. The reconfiguration and tunable interconnectivity between the elemental soft, pneumatically driven actuation units is made possible through integrated permanent magnets with coils. The proposed concept of attaching/detaching actuators enables these robots to be easily rearranged in various configurations to change the morphology of the system. While the potential for these actuators allows for arbitrary reconfiguration through parallel or serial connection on their four sides, we demonstrate here a configuration called ManusBot. ManusBot is a hand-like structure with digits and palm capable of individual actuation. The capabilities of this system are demonstrated through specific examples of stiffness modulation, variable payload capacity, and structure forming for enhanced and versatile object manipulation and operations. The proposed modular, soft robotic system with interconnecting capabilities significantly expands the versatility of operational tasks as well as the adaptability of handling objects of various shapes, sizes, and weights using a single system
PERCEPTIONS OF PRIMARY GRADE TEACHERS ABOUT READING CURRICULUM AND EARLY LITERACY INTERVENTION
Get PDFThis thesis examines the perceptions of reading curriculum and early literacy intervention of primary grade teachers. The purpose of this study was to answer the following research questions: How do primary grade teachers view early literacy intervention? How do teachers perceive the basal reading program, Reading Wonders? While there are studies that focus on teacher perceptions, research is limited in the area of teachers’ perceptions of reading curriculum and early literacy intervention. Data was collected using a qualitative approach using a survey, interviews, and a focus group discussion. Findings reveal that teachers feel that they need to be prepared when providing early literacy intervention, while also needing to feel supported by the reading curriculum
UNLOCKING UNDERSTANDING: ENHANCING SCIENTIFIC LITERACY THROUGH INTERDISCIPLINARY READING STRATEGIES IN HIGH SCHOOL SCIENCE CLASSES
Get PDFThis study investigated the intersection of literacy instruction and high school science teaching in response to low proficiency levels in these areas and interest in pursuing STEM careers among U.S. high school students. Participants reported using close reading practices combined with inquiry-based science instruction to enhance students’ science literacy and reading proficiency. Data were from document analysis, one-on-one interviews, and focus group discussions. Five significant themes showed teachers\u27 journeys from recognizing a problem to implementing new instructional strategies while pursuing knowledge about how to continue growing their craft. The five themes included teacher awareness of students’ literacy struggles, the apprehension of high school science teachers to infuse literacy strategies in tandem with inquiry-based science instruction, how academic standards highlighted the connection between science and literacy, effective instructional practices implemented by the teachers, and the role of professional development in refining instructional practices. The findings suggest that interdisciplinary instructional practices like close reading empower high school science teachers to support their students in developing their ability to read and comprehend complex texts while enhancing their scientific knowledge
INTEGRATION OF MACHINE LEARNING IN STRUCTURAL HEALTH MONITORING FOR DAMAGE IDENTIFICATION AND RESPONSE PREDICTION IN BRIDGES
No full textMachine learning-based structural health monitoring (ML-SHM) plays a pivotal role in enhancing structural resilience. By recognizing potential hazards, implementing resistance measures, facilitating swift recovery, and continuously monitoring structural health, ML-SHM ensures proactive maintenance and minimizes recovery delays post-events. Leveraging machine learning algorithms and sensor data, ML-SHM enables early detection of anomalies, prediction of failures, and adaptive responses, enhancing the structure\u27s ability to withstand and recover from adverse conditions. This integrated approach not only improves the structure\u27s performance and adaptability but also contributes to overall safety and longevity. This thesis presents a comprehensive exploration of structural health monitoring (SHM) techniques for bridges, employing varied approaches to assess damages, predict responses, and enhance overall resilience. In this study, I encompassed four distinct applications, each harnessing innovative methodologies and machine learning models. In the first application, I developed a convolutional neural network (CNN)-based approach for detecting spalling of columns. Leveraging image data from a shaking table experiment on a quarter-scale two-span reinforced bridge, I employed diverse CNN models, including transfer learning and data augmentation. Notably, the ResNet50 model achieved exceptional accuracy, scoring 100% in training and 97% in testing. In the second application, I employed machine learning algorithms for detecting damage in reinforcing bars within columns, utilizing strain cycles. A hybrid model combining a Gaussian naive Bayes base estimator and “ada” boost classifier is implemented, achieving consistent high accuracy with a mean test accuracy of 95%. This study provides significant insights into machine learning integration for structural health monitoring. In the third application, the second application was innovated by addressing challenges in monitoring low-cycle fatigue, specifically rocking columns in bridges. Utilizing CNNs, I directly encoded strain time series data into images through the Markov transition field technique. This advancement bypasses the need for calculating strain cycles, achieving exceptional accuracy of 100% in training and 97.8% in testing. The project highlights the potential of CNNs in predicting reinforcing bar fractures due to low-cycle fatigue effects. In the fourth application, I focused on predicting response (accelerations) in rocking column bridges during seismic events. Employing gated recurrent unit (GRU) machine learning models, I evaluated lateral displacements and corresponding accelerations. The findings improve the accuracy of seismic response predictions achieving a test output of over 0.9 R2, offering important insights into the responses of rocking column bridges under various seismic conditions. Collectively, by conducting these applications, I demonstrated the effectiveness of advanced machine learning techniques, notably CNNs and GRUs, in comprehensive structural health monitoring for bridges. This research not only advances the understanding of damage detection and prediction but also offers practical applications to enhance critical infrastructure resilience and safety
Distinct Expression Patterns of Hedgehog Signaling Components in Mouse Gustatory System During Postnatal Tongue Development and Adult Homeostasis
Get PDFThe Hedgehog (HH) pathway regulates embryonic development of anterior tongue taste fungiform papilla (FP) and the posterior circumvallate (CVP) and foliate (FOP) taste papillae. HH signaling also mediates taste organ maintenance and regeneration in adults. However, there are knowledge gaps in HH pathway component expression during postnatal taste organ differentiation and maturation. Importantly, the HH transcriptional effectors GLI1, GLI2 and GLI3 have not been investigated in early postnatal stages; the HH receptors PTCH1, GAS1, CDON and HHIP, required to either drive HH pathway activation or antagonism, also remain unexplored. Using lacZ reporter mouse models, we mapped expression of the HH ligand SHH, HH receptors, and GLI transcription factors in FP, CVP and FOP in early and late postnatal and adult stages. In adults we also studied the soft palate, and the geniculate and trigeminal ganglia, which extend afferent fibers to the anterior tongue. Shh and Gas1 are the only components that were consistently expressed within taste buds of all three papillae and the soft palate. In the first postnatal week, we observed broad expression of HH signaling components in FP and adjacent, non-taste filiform (FILIF) papillae in epithelium or stroma and tongue muscles. Notably, we observed elimination of Gli1 in FILIF and Gas1 in muscles, and downregulation of Ptch1 in lingual epithelium and of Cdon, Gas1 and Hhip in stroma from late postnatal stages. Further, HH receptor expression patterns in CVP and FOP epithelium differed from anterior FP. Among all the components, only known positive regulators of HH signaling, SHH, Ptch1, Gli1 and Gli2, were expressed in the ganglia. Our studies emphasize differential regulation of HH signaling in distinct postnatal developmental periods and in anterior versus posterior taste organs, and lay the foundation for functional studies to understand the roles of numerous HH signaling components in postnatal tongue development