Thru-Hiking the Appalachian Trail

STEP Category: LeadershipMy STEP project focused on hiking the entirety of the 2,190.9-mile Appalachian Trail (A.T.) solo in the spring of 2018. The planning and preparation phases of the trip lasted two months, with the actual hiking portion of my experience contributing an additional four-and-a-half months to my project timeline. Hiking the A.T. was a goal of mine after completing Vermont’s 275 mile Long Trail before my freshman year of college, and I thought this trek would be a great way of demonstrating how valuable skills like persistence, resilience, and adaptability can be developed in unconventional settings. I expect these skills to transcend the trail and serve to enhance my personal and professional life.The Ohio State University Second-year Transformational Experience Program (STEP)Academic Major: Environment, Economy, Development, and Sustainabilit

Identifying Barriers to Linden Energy Saving Programs

Course Code: AEDECON 4567The goal of our project was to provide focus to the Community Energy Savers (CES) program being administered through AEP Ohio and Columbia Gas by identifying barriers to resident participation in the program. The CES program incentivizes energy efficiency through in-home energy audits and various rebate programs. Each time a resident participates in one of these programs they earn points for the community that go towards a goal set for the entire neighborhood. The CES program is currently being implemented in Linden, a low-income neighborhood in the Northeast area of Columbus. This report and research poster summarize key findings from our project and provide recommendations to improve resident participation in the Linden CES program.AEP OhioColumbia GasAcademic Major: Environment, Economy, Development, and Sustainabilit

Classification of bird species from video using appearance and motion features

The monitoring of bird populations can provide important information on the state of sensitive ecosystems; however, the manual collection of reliable population data is labour-intensive, time-consuming, and potentially error prone. Automated monitoring using computer vision is therefore an attractive proposition, which could facilitate the collection of detailed data on a much larger scale than is currently possible. A number of existing algorithms are able to classify bird species from individual high quality detailed images often using manual inputs (such as a priori parts labelling). However, deployment in the field necessitates fully automated in-flight classification, which remains an open challenge due to poor image quality, high and rapid variation in pose, and similar appearance of some species. We address this as a fine-grained classification problem, and have collected a video dataset of thirteen bird classes (ten species and another with three colour variants) for training and evaluation. We present our proposed algorithm, which selects effective features from a large pool of appearance and motion features. We compare our method to others which use appearance features only, including image classification using state-of-the-art Deep Convolutional Neural Networks (CNNs). Using our algorithm we achieved a 90% correct classification rate, and we also show that using effectively selected motion and appearance features together can produce results which outperform state-of-the-art single image classifiers. We also show that the most significant motion features improve correct classification rates by 7% compared to using appearance features alone

Aberrant DNA Methylation of Matrix Remodeling and Cell Adhesion Related Genes in Pterygium

10.1371/journal.pone.0014687PLoS ONE62

On the role of 4-hydroxynonenal in health and disease

AbstractPolyunsaturated fatty acids are susceptible to peroxidation and they yield various degradation products, including the main α,β-unsaturated hydroxyalkenal, 4-hydroxy-2,3-trans-nonenal (HNE) in oxidative stress. Due to its high reactivity, HNE interacts with various macromolecules of the cell, and this general toxicity clearly contributes to a wide variety of pathological conditions. In addition, growing evidence suggests a more specific function of HNE in electrophilic signaling as a second messenger of oxidative/electrophilic stress. It can induce antioxidant defense mechanisms to restrain its own production and to enhance the cellular protection against oxidative stress. Moreover, HNE-mediated signaling can largely influence the fate of the cell through modulating major cellular processes, such as autophagy, proliferation and apoptosis. This review focuses on the molecular mechanisms underlying the signaling and regulatory functions of HNE. The role of HNE in the pathophysiology of cancer, cardiovascular and neurodegenerative diseases is also discussed

Cohort Profile: Burden of Obstructive Lung Disease (BOLD) study

The Burden of Obstructive Lung Disease (BOLD) study was established to assess the prevalence of chronic airflow obstruction, a key characteristic of chronic obstructive pulmonary disease, and its risk factors in adults (≥40 years) from general populations across the world. The baseline study was conducted between 2003 and 2016, in 41 sites across Africa, Asia, Europe, North America, the Caribbean and Oceania, and collected high-quality pre- and post-bronchodilator spirometry from 28 828 participants. The follow-up study was conducted between 2019 and 2021, in 18 sites across Africa, Asia, Europe and the Caribbean. At baseline, there were in these sites 12 502 participants with high-quality spirometry. A total of 6452 were followed up, with 5936 completing the study core questionnaire. Of these, 4044 also provided high-quality pre- and post-bronchodilator spirometry. On both occasions, the core questionnaire covered information on respiratory symptoms, doctor diagnoses, health care use, medication use and ealth status, as well as potential risk factors. Information on occupation, environmental exposures and diet was also collected

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification