Digital Commons Network^™

Host-Intrinsic Factors Determine Anti-Tumor Efficacy Of Exercise In Pancreatic Ductal Adenocarcinoma, Sumedha Pareek

Dissertations and Theses (Open Access)

Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths with a low 5-year relative survival rate of approximately 13.3% for all stages combined. We have previously shown that exercise can improve quality of life and enhance functional capacity among patients with PDAC. Exercise induces a variety of changes in the tumor microenvironment with beneficial effects in several tumor types. However, our understanding of the clinical effects of exercise and the mechanisms that mediate anti-tumor effects are limited in pancreatic cancer.

In this project, using C57BL/6 mice from Taconic Biosciences (Tac) and Jackson Laboratories (Jax), we established a …

Dual-Level Pattern Tree For Visual Field Improves Glaucoma Progression And Polygenic Risk Prediction, Luo Song, Lucy Q. Shen, Louis R. Pasquale, Michael V. Boland, Sarah R. Wellik, Carlos Gustavo De Moraes, Ayellet Segre, Janey L. Wiggs, Constance Turman, Jonathan S. Myers, Tobias Elze, Nazlee Zebardast, David S. Friedman, Jae H. Kang, Mengyu Wang

Wills Eye Hospital Papers

PURPOSE: To develop a dual-level pattern tree to characterize visual field (VF) loss subtypes that can be used to better predict glaucoma progression and glaucoma polygenic risk scores (PRSs).

METHODS: This study included 113,030 patients from three datasets, each used for a specific purpose: (1) model training, (2) progression forecasting, and (3) PRS correlations. We applied archetypal analysis to cluster 24-2 VFs into trunk patterns and their branch patterns. The Cox regression model was used to forecast VF progression using mean deviation (MD) slope, MD-fast slope, total deviation (TD) pointwise slope, and visual field index (VFI) slope. Multivariable regression analyses …

Embedding-Driven Dual-Branch Approach For Accurate Breast Tumor Cellularity Classification, Hossam Magdy Balaha, Ali Mahmoud, Khadiga M. Ali, Mohammed Ghazal, Norah Saleh Alghamdi, Ashraf Khalil, Ayman El-Baz

All Works

This study proposes a dual-branch framework for precise classification of breast tumor cellularity via histopathological images where it integrates two distinct branches: the Embedding Extraction Branch (embedding-driven) and the Vision Classification Branch (vision-based). The Embedding Extraction Branch uses the Virchow2 transformation to generate dense, structured embeddings, whereas the Vision Classification Branch employs Nomic AI Embedded Vision v1.5 to process image patches and produce classification logits. Both branches’ outputs are combined to form the final classification. The framework also suggests Knowledge Block with fully connected layers, batch normalization, and dropout to improve feature extraction and reduce overfitting. The proposed approach reports …

Wildfire Smoke And Public Health: Comparing 2023 Canadian Wildfire Events With Hospital Admissions In Douglas County, Nebraska, Jeremy Poell

Capstone Experience: Master of Public Health

Wildfires are becoming increasingly common in Canada and the United States. Smoke produced from these fires creates a multitude of air pollution constituents that can cause breathing and other health issues for humans, particularly those with asthma and other respiratory conditions. Of these pollutants, PM2.5 (particulate matter that is 2.5 microns or smaller) is particularly problematic as these particles are inhaled deep into lung tissue, where they create inflammation and oxidative stress. Poor air quality can also trigger asthma and respiratory issues, leading to an increase in emergency department admissions for breathing treatments. The goal of this study is to …

A Picture Tells A Thousand Words—, But Ecg Signals Have More To Say, Ashley N. Gomez

Theses and Dissertations

With the increasing adoption of deep learning classification models in the medical domain, a critical challenge remains: achieving high predictive accuracy while maintaining clinical Inter-pretability. This study examines how model architecture, dataset origin, and the use of full versus subset data affect both classification performance and Interpretability in Electrocardiogram (ECG) signal analysis. ResNet18 is evaluated using an open-source ECG Image Dataset, thus a custom dataset derived from digitized ECG images. Post-hoc explainability methods, such as Integrated Gradients, are applied to determine which time steps have the most significant influence on model decisions. The findings demonstrate that model architecture and dataset …

Definition Of The 3d Position And Motion Status Of The Moving Heart Based On 2d Projections, Lawrence D. Orijuela

Electronic Theses, Projects, and Dissertations

This thesis presents a novel application of deep learning to the estimation of pulmonary vein coordinates using X-ray image pairs from a FORBILD Thorax phantom derived motion dataset. A Siamese neural network was developed to predict the 3D coordinates of one pulmonary vein at a time, specifically the Right Superior Pulmonary Vein (RSPV), Left Superior Pulmonary Vein (LSPV), Left Inferior Pulmonary Vein (LIPV), or Right Inferior Pulmonary Vein (RIPV), based on two-dimensional projection images.

The input data consisted of over 1.6 million grayscale X-ray image pairs across 1331 virtual patients, each annotated with ground truth 3D coordinates. To manage memory …

Comparative Assessment Of Lower Limb Neuromusculoskeletal Activation And Joint Kinematics In Normal And Impaired Gait, Jack Ryan Schule

Theses and Dissertations

This thesis evaluates whether accessible and affordable technologies can provide clinically significant, quantifiable gait analysis comparable to traditional marker-based motion capture systems. Modern high-end systems offer excellent accuracy but remain financially and logistically inaccessible to many clinicians and researchers. To address this gap, a framework was developed using markerless pose estimation using the model, MediaPipe, inertial measurement units (IMUs) processed through an Extended Kalman Filter (EKF), and surface electromyography (sEMG) to measure joint kinematics and neuromuscular activity during gait. An experiment was performed where data was collected from participants with both normal gait and pathologies including: Osgood–Schlatter disease, Plica Band …

The "Woundosome" Concept And Its Impact On Procedural Outcomes In Patients With Chronic Limb-Threatening Ischemia, Lorenzo Patrone, Edoardo Pasqui, Michael S Conte, Alik Farber, Roberto Ferraresi, Matthew Menard, Joseph L Mills, John Rundback, Peter Schneider, August Ysa, Kumar Abhishek, George L Adams, Naseer Ahmad, Irfan Ahmed, Vlad A Alexandrescu, Max Amor, David Alper, Martin Andrassy, Christopher Attinger, Andy Baadh, Hashem Barakat, Lukla Biasi, Theodosios Bisdas, Zagum Bhatti, Erwin Blessing, Marc P Bonaca, Stefano Bonvini, Michel Bosiers, Andrew W Bradbury, Robert Beasley, Christian-Alexander Behrendt, Marianne Brodmann, Gonzalo Cabral, Roberto Cancellieri, Andrea Casini, Venita Chandra, Emiliano Chisci, Omar Chohan, Edward T C Choke, Patrick F S Chong, Giacomo Clerici, Raphael Coscas, Mary Costantino, Luca Dalla Paola, Sabeen Dand, Robert S M Davies, Mario D'Oria, Athanasios Diamantopoulos, Sebastian Debus, Koen Deloose, Costantino Del Giudice, Gianmarco De Donato, Brian De Rubertis, Jean Paul De Vries, Nuno V Dias, Larry Diaz-Sandoval, Florian Dick, Konstantinos Donas, Anahita Dua, Fabrizio Fanelli, Stefano Fazzini, Mazin Foteh, Roberto Gandini, Mauro Gargiulo, Luca Garriboli, Elizabeth A Genovese, Edward Gifford, Yann Goueffic, Peter Goverde, Prem Chand Gupta, Robert Hinchliffe, Andrew Holden, Kim C Houlind, Dominic Pj Howard, Bella Huasen, Giacomo Isernia, Konstantinos Katsanos, Barry Katzen, Philippe Kolh, Igor Koncar, Grigorios Korosoglou, Prakash Krishnan, Thomas Kroencke, Miltiadis Krokidis, Arun Kumarasamy, Paul Hayes, Osamu Iida, Enrique Alejandre Lafont, Ralf Langhoff, Alexandre Lecis, Mark Lessne, Hady Lichaa, Michael Lichtenberg, Marta Lobato, Alice Lopes, Giorgio Loreni, Pierleone Lucatelli, Sreekumar Madassery, Lieven Maene, Marco Manzi, Martin Maresch, Jay Santhosh Mathews, James Mccaslin, Antonio Micari, Stefano Michelagnoli, Bruno Migliara, Robert Morgan, Luis Morelli, Daniele Morosetti, Nicolas Mouawad, Paul Moxey, Stefan Müller-Hülsbeck, Jihad Mustapha, Tatsuya Nakama, Bahaa Nasr, Zola N'Dandu, Richard Neville, Elias Noory, Joakim Nordanstig, Katariina Noronen, Luis Mariano Palena, Gianbattista Parlani, Ashish S Patel, Parag Patel, Rafiuddin Patel, Sanjay Patel, Costantino Pena, Drazen Perkov, Mark Portou, Giovanni Pratesi, Christos Rammos, Jim Reekers, Vicente Riambau, Trisha Roy, Kenneth Rosenfield, Maria Antonella Ruffino, Fadi Saab, Athanasios Saratzis, Paolo Sbarzaglia, Andrej Schmidt, Eric Secemsky, Michael Siah, Henrik Sillesen, Gioele Simonte, Marc Sirvent, Jill Sommerset, Sabine Steiner, Ahmed Sakr, Dierk Scheinert, Mehdi Shishebor, Stavros Spiliopoulos, Alessio Spinelli, Konstantinos Stravoulakis, Gergana Taneva, Desarom Teso, Joerg Tessarek, Selva Theivacumar, Anish Thomas, Shannon Thomas, Narayan Thulasidasan, Giovanni Torsello, Ramesh Tripathi, Nicola Troisi, Srini Tummala, Venkat Tummala, Christopher Twine, Raman Uberoi, Alessandro Ucci, Domenico Valenti, Jos Van Den Berg, Daniel Van Den Heuvel, Isabelle Van Herzeele, Ramon Varcoe, Melina Vega De Ceniga, Frank J Veith, Maarit Venermo, Badri Vijaynagar, Sanjiv Virdee, Conrad Von Stempel, Michiel T Voûte, Kak Khee Yeung, Thomas Zeller, Hany Zayed, Miguel Montero Baker

Faculty, Staff and Student Publications

No abstract provided.

Short-Term Preeclampsia Prediction: Cutoff Variations For Sflt-1/Plgf In U.S. Patients With Or Without Hypertensive Disorders, Yaxin Li, Kristen Cagino, Jim Yee, Caroline Andy, Dajana Borova, Ayush Shah, Isla Racine, Tracy Grossman, Zhen Zhao

Student Papers, Posters & Projects

BACKGROUND: Preeclampsia (PE) is a complex disorder with significant maternal and fetal risks. The soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) ratio shows promise as a diagnostic tool, but its adoption in the U.S. remains limited due to the lack of accessible testing platforms, U.S.-based studies, and evidence-based implementation guidelines.

PATIENTS/MATERIALS AND METHODS: We conducted a cohort study to evaluate the sFlt-1/PlGF ratio for predicting PE within two weeks among pregnant individuals ≥18 years, ≥20 weeks gestation. Serum samples were obtained from routine prenatal visits or triage evaluations. sFlt-1/PlGF ratios were measured using Roche Elecsys assays, and …

Detection Of Phase-Binning And Interpolation Artifacts In 4-Dimensional Computed Tomography Imaging Using Deep Learning And Rule-Based Approaches, Jorge Cisneros, Nathan H. Feldt, Yevgeniy Vinogradskiy, Richard Castillo, Edward Castillo

Department of Radiation Oncology Faculty Papers

BACKGROUND: Four-dimensional computed tomography (4DCT) imaging is a crucial component to lung cancer radiotherapy planning and enables CT-ventilation-based functional avoidance planning to mitigate radiation toxicity. However, 4DCT scans are frequently impaired by acquisition artifacts that corrupt downstream analyses that depend on lung segmentation and deformable image registration, such as CT-ventilation and dose accumulation.

PURPOSE: This study develops 3D deep learning models to identify phase-binning artifacts at the voxel level and a heuristic, rule-based method to identify interpolation slices within 4DCT images.

METHODS: We introduce a generator that systematically inserts synthetic phase-binning and interpolation artifacts into any artifact-free breathing phase obtained …

Personalized Risk Prediction For Cancer Survivors: A Generalized Bayesian Semi-Parametric Model Of Recurrent Events With Competing Outcomes, Nam Hoai Nguyen, Seung Jun Shin, Elissa Dodd-Eaton, Jing Ning, Wenyi Wang

Faculty, Staff and Student Publications

Multiple primary cancers are increasingly more frequent due to improved survival of cancer patients. Characteristics of the first primary cancer largely impact the risk of developing subsequent primary cancers. Hence, model-based risk characterization of cancer survivors that captures patient-specific variables is needed for healthcare policy making. We propose a Bayesian semi-parametric framework, where the occurrence processes of the competing cancer types follow independent non-homogeneous Poisson processes and adjust for covariates including the type and age at diagnosis of the first primary. Applying this framework to a historically collected cohort with families presenting a highly enriched history of multiple primary tumors …

Forecasting Chemoradiation Response Midtreatment For High-Grade Gliomas Through Patient-Specific Biology-Based Modeling, David A Hormuth, Maguy Farhat, Bikash Panthi, Holly Langshaw, Mihir D Shanker, Wasif Talpur, Sara Thrower, Jodi Goldman, Sophia Ty, Calliope Custer, Jeanne Kowalski, Thomas E Yankeelov, Caroline Chung

Faculty, Staff and Student Publications

Purpose: The entire course of radiation therapy (RT) for high-grade glioma (HGG) is currently derived from pre-RT magnetic resonance imaging (MRI). Although it is possible to adapt RT during the course of treatment, it is often guided only by anatomical changes to the tumor. This study seeks to determine if a biology-based mathematical model, parameterized by patient-specific, multiparametric MRI (mpMRI) data, can accurately forecast HGG response during RT.

Methods and materials: Twenty one patients with HGG planned for 6 weeks of concurrent RT and chemotherapy were imaged weekly with mpMRI during RT and at 1, 2, and 3 months post-RT. …

Normalization Of Temperature Effects For Quality Assurance Of Quantitative Prostate Apparent Diffusion Coefficient Imaging Across Multiple Sites, Ken-Pin Hwang, Joshua Yung, R Jason Stafford, Caroline Chung, Aradhana M Venkatesan

Faculty, Staff and Student Publications

Background: Apparent Diffusion Coefficient (ADC) as measured by diffusion weighted imaging is known to negatively correlate with prostate tumor aggressiveness. Heterogeneity in system and protocol performance causes potential variability in ADC acquired across a large scanner network, prompting a need to evaluate quantitative ADC from a prostate-specific MR diffusion protocol as part of quality assurance (QA). Due to the temperature dependence of ADC, repeatability and reproducibility assessments typically require phantoms to maintain a temperature of 0°C, imposing a considerable burden when assessing large numbers of scanners.

Purpose: To develop a QA procedure at room temperature for assessing the reproducibility of …

Real-Time Estimated Sequential Organ Failure Assessment (Sofa) Score With Intervals: Improved Risk Monitoring With Estimated Uncertainty In Health Condition For Patients In Intensive Care Units, Yan He, Qian Luo, Hai Wang, Zhichao Zheng, Haidong Luo, Oon Cheong Ooi

Research Collection Lee Kong Chian School Of Business

Purpose: Real-time risk monitoring is critical but challenging in intensive care units (ICUs) due to the lack of real-time updates for most clinical variables. Although real-time predictions have been integrated into various risk-scoring systems to aid monitoring, existing systems do not address uncertainties in risk assessments. We developed an enhanced risk monitoring framework based on commonly used systems like the Sequential Organ Failure Assessment (SOFA) score by incorporating uncertainties to improve the effectiveness of real-time risk monitoring in ICUs.Methods: This study included 5,351 patients admitted to the Cardiothoracic ICU in the National University Hospital in Singapore. We developed machine learning …

Echoes Of The Modern Training Periodization Concepts In Russia Before The October 1917 Revolution, Sandro Bartolomei, Gulnara Mammadova, Renato Manno, Gregory G. Haff, Jay R. Hoffman, Franco Merni

Research outputs 2022 to 2026

Abstract – Bartolomei, S, Mammadova, G, Manno, R, Haff, GG, Hoffman, JR, and Merni, F. Echoes of the modern training periodization concepts in Russia before the October 1917 revolution. J Strength Cond Res 39(12): 1327–1330, 2025—The debate on the origins of the discipline of training periodization is still ongoing. The text “Olympic Sport, ” published by B. A. Kotov in 1916, was one of the first known books to focus on training methods and strategies for performance development. The book is also considered the first to deal with training organization and periodization. In addition, Kotov was the only author to …

From Standard To Stratified: Modeling Ntcp And Ear To Personalize Daily Mv-Cbct In Radiotherapy., Duong Thanh Tai, Luong Tien Phat, Tran Trung Kien, Duong Tuan Linh, Nguyen Ngoc Anh, Nguyen Quang Hung, Peter Sandwall, Parham Alaei, David Bradley, James C L Chow

Oncology Articles

PURPOSE: To evaluate the cumulative radiobiological impact of daily megavoltage cone-beam computed tomography (MV-CBCT) imaging dose based on normal tissue complication probability (NTCP) and excess absolute risk (EAR) of secondary malignancies among radiotherapy patients treated for breast, pelvic, and head & neck cancers. This study investigated whether MV-CBCT imaging dose warrants protocol personalization according to patient age, anatomical treatment site, and organ-specific radiosensitivity.

METHODS: This retrospective study included cohorts of breast (n = 30), pelvic (n = 17), and head & neck (n = 20) cancer patients undergoing radiotherapy with daily MV-CBCT. Imaging dose distributions employing two common MV-CBCT protocols …

Smags-Lasso: A Novel Feature Selection Method For Sensitivity Maximization In Early Cancer Detection, Hamid Khoshfekr Rudsari, Sara Khorami-Sarvestani, Johannes F Fahrmann, James P Long, Samir Hanash, Kim-Anh Do, Ehsan Irajizad

Faculty, Staff and Student Publications

Background: Sensitivity and specificity are foundational metrics for cancer detection tools. However, most machine learning algorithms prioritize overall accuracy during optimization, which fails to align with clinical priorities of early detection. We aim to develop a feature selection machine learning algorithm while maximizing sensitivity at a given specificity.

Methods: We developed SMAGS-LASSO, a machine learning algorithm that combines our developed Sensitivity Maximization at a Given Specificity (SMAGS) framework with L1 regularization for feature selection. This approach simultaneously optimizes sensitivity at user-defined specificity thresholds while performing feature selection. SMAGS-LASSO utilizes a custom loss function with L1 regularization and multiple parallel optimization …

Knowledge Mapping And Visualized Analysis Of Research Progress In Onconephrology: A Bibliometric Analysis, Yiwei Wang, Shuling Fan, Wei Wang

Faculty, Staff and Student Publications

Objectives: Onconephrology is an expanding subspecialty focused on the management of cancer patients with renal injury. This study used a comprehensive bibliometric analysis to emphasize the need for cooperation between oncologists and nephrologists, exploring current trends and future research areas in onconephrology.

Methods: Relevant literature on onconephrology published between 1 January 2000 and 27 April 2024 was retrieved from the Science Citation Index Expanded of the Web of Science Core Collection, followed by manual screening. Bibliometric analyses were performed using CiteSpace, VOSviewer, and Bibliometrix software.

Results: A total of 1,853 publications, including 1,647 articles and 206 reviews, by 11,606 authors …

Insecticide-Treated Net Use And Elimination Of Malaria In Sub-Saharan African Countries: Assessing The Global Technical Strategy Using An Evolutionary Game Approach, Laxmi, Tamer Oraby, Michael G. Tyshenko, Ina Danquah, Samit Bhattacharyya

School of Mathematical & Statistical Sciences Faculty Publications

Background: Malaria continues to be a major public health challenge in Sub-Saharan Africa (SSA), where the majority of the countries have not met the World Health Assembly's endorsed Global Technical Strategy (GTS) milestones in 2020 for malaria reduction. Insecticide-treated net (ITN) usage is a well-established and effective intervention, often outperforming other measures such as indoor residual spraying (IRS). However, multiple survey studies have reported improper use of ITNs across various SSA countries. This misuse likely poses an important barrier to the intervention's success, although it remains a largely untested hypothesis.

Methods: We developed a behaviour-incidence model and statistical analysis of …

Is Noise Exposure Associated With Impaired Extended High Frequency Hearing Despite A Normal Audiogram? A Systematic Review And Meta-Analysis, Sajana Aryal, Monica Trevino, Hansapani Rodrigo, Srikanta K. Mishra

School of Mathematical & Statistical Sciences Faculty Publications

Understanding the initial signature of noise-induced auditory damage remains a significant priority. Animal models suggest the cochlear base is particularly vulnerable to noise, raising the possibility that early-stage noise exposure could be linked to basal cochlear dysfunction, even when thresholds at 0.25-8 kHz are normal. To investigate this in humans, we conducted a meta-analysis following a systematic review, examining the association between noise exposure and hearing in frequencies from 9 to 20 kHz as a marker for basal cochlear dysfunction. Systematic review and meta-analysis followed PRISMA guidelines and the PICOS framework. Studies on noise exposure and hearing in the 9 …

Regional Variation And Epidemiological Insights In Malaria Underestimation In Cameroon, Sarafa A. Iyaniwura, Qing Han, Ngem Bede Yong, Ghislain Rutayisire, Agnes Adom-Konadu, Okwen Patrick Mbah, David Poumo Tchouassi, Kingsley Badu, Jude Dzevela Kong

All Peer-Reviewed Publications

Background: Despite significant global effort to control and eradicate malaria, many cases and deaths are still reported yearly. These efforts are hindered by several factors, including the severe underestimation of cases and deaths, especially in Africa. Methods: We used a mathematical model, incorporating the underestimation of cases and seasonality in mosquito biting rate, to study the malaria dynamics in Cameroon. Using a Bayesian inference framework, we calibrated our model to the monthly reported malaria cases in ten regions of Cameroon from 2019 to 2021 to quantify the underestimation of cases and estimate other important epidemiological parameters. We performed Hierarchical Clustering …

Building Rapport In Ethnoculturally Dissimilar Dyads: A Critical Grounded Theory Inquiry, Danielle E. Burton

LSU New Orleans Theses and Dissertations

Multiculturalism is not a new concept within the field of counseling. It is discussed in terms adjacent to competency, theory, and identity development. However, research indicates that students do not usually feel multiculturally-competent following their graduation from counseling programs, nor do they feel that they have adequate skills and techniques to engage diverse clientele. This critical grounded theory study examines counseling skills, dispositional factors, systemic factors, and other experiential factors used in pursuit of rapport within counseling dyads of ethnocultural dissimilarity. Semi-structured interview data was coded to reveal five themes to be used as a heuristic for further discovery. These …

Muc15 Ectodomain Architecture Regulates Integrin Clustering To Control Cancer Metastasis, Simei Zhang, Guy M Genin, Et Al.

2020-Current year OA Pubs

Cancer metastasis is governed by physical cues at the cell-matrix interface, with matrix stiffness, ligand density, and topography established as key determinants. Here, a fourth critical factor in cancer metastasis, the architecture of the cell-surface glycocalyx is identified. Using MUC15 as a representative small glycoprotein, mathematical modeling and domain truncation experiments are combined to show that glycoprotein size distribution governs integrin adhesion states and metastatic outcomes. MUC15 localizes to focal adhesions and interact with integrins, while larger glycoproteins such as MUC1 are sterically excluded. These physical effects, rather than intracellular signaling, dictate adhesion state transitions: removing MUC15's ectodomain eliminated its …

Does Health Insurance Coverage Improve Cardiometabolic Risk Factor Levels? Quasi-Experimental Evidence From India, Kavita Singh, Anubha Agarwal, Mark D Huffman, Et Al.

2020-Current year OA Pubs

BACKGROUND: Chronic conditions cause notable health and economic burdens. While health insurance enables access to healthcare, its effects on chronic care outcomes remain under-explored.

OBJECTIVE: To examine the association between health insurance coverage and cardiometabolic risk factors among people with chronic conditions in India.

METHODS: Data from the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) and Solan studies, including 2,926 adults with chronic conditions were analyzed using propensity score weighting to evaluate the associations between health insurance and cardiometabolic risk factors (HbA1c, low-density lipoprotein cholesterol [LDLc], and blood pressure [BP]) and self-reported health status (measured using European Quality …

Studies On Curcumin-Glucoside In The Prevention Of Alpha-Synuclein Aggregation, Lakshmi Sowmya Emani, Jayanth K. Rao, Jagadeesha Kumar Dasappa, Marisín Pecchio, Johant Lakey-Beitia, Hansapani Rodrigo, Jessica Cruz-Mora, Priya Narayan, Nikhilesh Anand, Bharathi Gadad

School of Medicine Publications

Background: α-synuclein (α-syn) deposition in the mid-brain region is one of the hallmark pathologies of Parkinson's disease (PD). The key steps involve the transformation of α-synuclein into a toxic oligomer and insoluble fibrillar aggregates.

Objective: To understand the role of curcumin-glucoside in the prevention of α-syn aggregation, a mechanistic approach.

Methods: In the present study, we synthesized a novel molecule, curcumin-glucoside (Curc-gluc), to improve the water solubility and partition coefficient, making the molecule with high bioavailability. The present study is focused on understanding the α-syn aggregation kinetics in the presence and absence of Curc-gluc, curcumin (Cur), copper (Cu), and iron …

Assessing Community Readiness And Benefits Of A Nursing Program: Implications For Healthcare And Education, Mary Anne Frances D. Reyes, Aaron A. Funa, Robert Jamisola, Ma. Joahna D. Perdigon, Jerica D. Latonero

Jurnal Keperawatan Indonesia

In response to recent policy shifts allowing the establishment of new nursing programs in the Philippines, this study assesses the perceived readiness of Sorsogon, a geographically underserved province, to implement a bachelor of science in nursing program. It also explores the anticipated benefits that such a program may offer to students and the local community. A cross-sectional survey of 375 stakeholders, selected through purposive sampling, was conducted using a validated instrument developed through expert consultation. Quantitative data were analyzed using descriptive statistics, while qualitative responses were examined through thematic analysis. The findings reveal widespread support for the proposed program, emphasizing …

Accuracy Of Student Career Choice: Analysis Of Interest And Personality Match In The Industry 4.0 Era, Nikon Aritonang, I Nyoman Sudana Degeng, M Ramli, Adi Atmoko

Buletin Konseling Inovatif

This study aims to clarify the high number of college students choosing unsuitable career choices. The impact of choosing an unsuitable career path can significantly hinder the development of Indonesian human resources in the context of the industry 4.0 era. This is caused by shifting paradigms in the recruitment process of most companies or institutions that no longer prioritize a diploma as the key factor in seeking new hires. Instead, there is greater emphasis on the employee's skills, interests, creativity, and innovation, followed by a diploma and achievement index. Descriptive-qualitative design was employed. Samples were collected from college students at …

Benchmarking Dna Foundation Models For Genomic And Genetic Tasks, Haonan Feng, Lang Wu, Bingxin Zhao, Chad Huff, Jianjun Zhang, Jia Wu, Lifeng Lin, Peng Wei, Chong Wu

School of Medicine Faculty Publications

The rapid evolution of DNA foundation models promises to revolutionize genomics, yet comprehensive evaluations are lacking. Here, we present a comprehensive, unbiased benchmark of five models (DNABERT-2, Nucleotide Transformer V2, HyenaDNA, Caduceus-Ph, and GROVER) across diverse genomic and genetic tasks including sequence classification, gene expression prediction, variant effect quantification, and topologically associating domain (TAD) region recognition, using zero-shot embeddings. Our analysis reveals that mean token embedding consistently and significantly improves sequence classification performance, outperforming other pooling strategies. Model performance varies among tasks and datasets; while general purpose DNA foundation models showed competitive performance in pathogenic variant identification, they were less …

Improving Glycemic Control Among Indonesian Urban Adults: A Digital And Behavioral Extension Of The Information–Motivation–Behavioral Skills Model, Imelda Appulembang

Kesmas

Management of type 2 diabetes mellitus (T2DM) in Indonesia continues to face challenges due to behavioral, informational, and technological gaps among patients. This study analyzed the influence of self-regulatory competence and information, motivation, family support, and digital health literacy on glycemic control behavior. A cross-sectional survey was conducted from February to April 2025 among 587 adults aged >30 years with T2DM enrolled in the Chronic Disease Management Program at primary health care in six major cities: Jakarta, Surabaya, Yogyakarta, Medan, Makassar, and Banjarmasin. Data were collected through structured questionnaires and analyzed using partial least squares structural equation modeling. The findings …

Transdisciplinary Perspectives On Ai: The Fourth Annual Conference Of The European Culture And Technology Laboratory, Connell Vaughan, Ioana Madalina Moldovan, Silivan Moldovan, Noel Fitzpatrick

Books/Book Chapters

The fourth annual conference of the ECT Lab+ was hosted by Technical University of Cluj-Napoca over two days in October 2024 at the Cluj Innovation Park. The conference brought together experts from the Arts, Humanities, Social Sciences, Technology, and other fields to discuss and reflect on the advent of Artificial Intelligence and how the associated technologies are transforming how we live, work and study. Under the title Transdisciplinary perspectives on AI: Alternative Histories, Current Practices and Possible Futures the conference moved beyond simplistic technophila and technophobia to consider whether we can co-evolve with these new technologies which combine machine learning …