Life Sciences Commons^™

Tissue And Imaging Biomarkers Of Response To Neoadjuvant Nivolumab Or Nivolumab Plus Ipilimumab In Patients With Resectable Hepatocellular Carcinoma, Michael Lapelusa, Shadi Chamseddine, Hop Sanderson Tran Cao, Lianchun Xiao, Elshad Hasanov, Priya Bhosale, Hesham M Amin, Yehia I Mohamed, Betul Gok Yavuz, Yara Sakr, Li Xu, Ian Hu, Sunyoung S Lee, Divya Sakamuri, Sonali Jindal, Van Nguyen, Michael A Curran, Ryan Sun, Asif Rashid, Dan Gabriel Duda, Padmanee Sharma, Aliya Qayyum, Ahmed Omar Kaseb

Faculty, Staff and Student Publications

Introduction: Perioperative immunotherapy has shown promise in some patients with early-stage hepatocellular carcinoma (HCC). This study examined tissue and imaging biomarkers associated with pathologic response in a phase II clinical trial in patients with resectable HCC.

Methods: Analysis included 18 patients with biopsy-proven resectable HCC treated with neoadjuvant nivolumab plus ipilimumab or nivolumab alone in a phase II clinical trial at MD Anderson Cancer Center (NCT03222076). Liver MRE (to measure tissue fibrosis) and biopsies (to evaluate immune activation markers) were obtained serially pretreatment and after completing neoadjuvant immunotherapy. A major pathologic response (MPR) was defined as tumor necrosis …

Characterizing Spatial Immune Architecture In Metastatic Melanoma Using High-Dimensional Multiplex Imaging, Joel Eliason, Santhoshi Krishnan, Yasunari Fukuda, Matias A Bustos, Dan Winkowski, Sungnam Cho, Akshay Basi, Regan Baird, Elizabeth A Grimm, Michael A Davies, Dave S B Hoon, Arvind Rao, Jared K Burks, Suhendan Ekmekcioglu

Faculty, Staff and Student Publications

Introduction: Immune checkpoint inhibitors (ICIs) have significantly improved survival for patients with metastatic melanoma, yet many experienceresistance due to immunosuppressive mechanisms within the tumor immune microenvironment (TIME). Understanding how the spatial architecture of immune and inflammatory components changes across disease stages may reveal novel prognostic biomarkers and therapeutic targets.

Methods: We performed high-dimensional spatial profiling of two melanoma tissue microarrays (TMAs), representing Stage III (n = 157) and Stage IV (n = 248) metastatic tumors. Using imaging mass cytometry (IMC) and multiplex immunofluorescence (mIF), we characterized the phenotypic, functional, and spatial properties of the TIME. Cellular neighborhoods were …

Case Report: Durable Remission After Abscopal Effect Following Transcatheter Hepatic Arterial Embolization In A Patient With Mucosal Melanoma Refractory To Immunotherapy, Lynsey M Claus, Hannah E Kostan, Marshall E Hicks, Rony Avritscher, Michael A Davies

Faculty, Staff and Student Publications

Mucosal melanoma, a rare subtype of melanoma affecting mucosal surfaces, presents significant challenges in diagnosis and treatment, particularly due to its low programmed death-ligand 1 (PD-L1) expression and reduced response to immune checkpoint inhibitors (ICIs). This case report describes a 58-year-old woman with metastatic nasal mucosal melanoma initially resistant to neoadjuvant ipilimumab and nivolumab. After undergoing hepatic transcatheter arterial embolization, she experienced an unexpected abscopal effect, where distant metastases showed near-complete resolution despite prior lack of response to immunotherapy. The patient's disease initially progressed despite two cycles of ICI treatment, and further immunotherapy with nivolumab and relatimab did not improve …

Editorial: Molecular Mechanisms And Targeted Therapies For Colorectal Cancer Vol Ii, Alessandro Passardi, David Gibbons, Antonio Mario Scanu, Shilpa S Dhar

Faculty, Staff and Student Publications

No abstract provided.

The Impact Of Post-Remission Granulocyte Colony-Stimulating Factor Use In The Phase 3 Studies Of Venetoclax Combination Treatments In Patients With Newly Diagnosed Acute Myeloid Leukemia, Courtney D Dinardo, Keith W Pratz, Panayiotis Panayiotidis, Xudong Wei, Vladimir Vorobyev, Árpád Illés, Inho Kim, Vladimir Ivanov, Grace Ku, Catherine L Miller, Meng Zhang, Fernando Tatsch, Jalaja Potluri, Xenia Schmidt, Christian Récher

Faculty, Staff and Student Publications

No abstract provided.

Head And Neck Gross Tumor Volume Automatic Segmentation Using Pocketnet, Awj Twam, Adrian Celaya, Evan Lim, Khaled Elsayes, David Fuentes, Tucker Netherton

Faculty, Staff and Student Publications

Head and neck cancer (HNC) represents a significant global health burden, often requiring complex treatment strategies, including surgery, chemotherapy, and radiation therapy. Accurate delineation of tumor volumes is critical for effective treatment, particularly in MR-guided interventions, where soft tissue contrast enhances visualization of tumor boundaries. Manual segmentation of gross tumor volumes (GTV) is labor intensive, time-consuming and prone to variability, motivating the development of automated segmentation techniques. Convolutional neural networks (CNNs) have emerged as powerful tools in this task, offering significant improvements in speed and consistency. In this study, we participated as Team Pocket in Task 1 of the HNTS-MRG …

Meeting Highlights The 4th Marie Skłodowska-Curie Symposium On Cancer Research And Care: Mechanisms Of Support For Regional & International Collaborations, Pawel Kalinski, Kathleen M Kokolus, Indu Ahluwalia, Mihaela Balu, Łukasz Balwicki, Brygida Baran, Loretta Beine, Mikhail Berezin, Ioana Berindan-Neagoe, Andriy Beznosenko, Blanka Borowiec, Szabolcs Bozsányi, Jonathan Bramson, Brian Czerniecki, Rūta Everatt, Wojciech Fendler, Peter Forsyth, Jeffrey E Gershenwald, Maciej Goniewicz, Khurshid Guru, Andrew Hyland, Smitha James, Iva Kirac, Pawel Koczkodaj, Leszek Kotula, Maciej Łuba, Iwona Ługowska, Elizabeth Luke, Cristian Lungulescu, Sandro Matosevic, Kaushal Nanavati, Michael Nemeth, Karolina Nowak, Katia Noyes, Mark Parascandola, Waldemar Priebe, Piotr Rutkowski, Mukund Seshadri, Christine E Sheffer, Ioana-Miruna Stanciu, Joanna Stanson, Telisa Stewart, Edita Sužiedėlienė, Kęstutis Sužiedėlis, Iryna Tanasiichuk, Anda M Vlad, Wei-Zen Wei, Dylan Williams, Malgorzata Wojtowicz, Tomasz Zdrojewski

Faculty, Staff and Student Publications

The Marie Skłodowska-Curie Symposia on Cancer Research and Care (MSCS-CRC) promote collaborations between cancer researchers and care providers in the United States, Canada and Central and Eastern European Countries (CEEC) to accelerate the development of new cancer therapies, new strategies for early detection and prevention, and improve cancer care and the quality of life for patients and their families. The 4th MSCS-CRC (September 25-27, 2024, Buffalo, New York) brought together 147 participants from the US, Canada, Croatia, Czechia, Lithuania, Poland, Romania and Ukraine, and involved representatives of the US Centers for Disease Control and Prevention (CDC), National Cancer Institute (NCI) …

Comparison Of Deep Learning Schemes In Grading Non-Alcoholic Fatty Liver Disease Using B-Mode Ultrasound Hepatorenal Window Images With Liver Biopsy As The Gold Standard, Petros Drazinos, Ilias Gatos, Paraskevi F Katsakiori, Stavros Tsantis, Efstratios Syrmas, Stavros Spiliopoulos, Dimitris Karnabatidis, Ioannis Theotokas, Pavlos Zoumpoulis, John D Hazle, George C Kagadis

Faculty, Staff and Student Publications

Background/introduction: To evaluate the performance of pre-trained deep learning schemes (DLS) in hepatic steatosis (HS) grading of Non-Alcoholic Fatty Liver Disease (NAFLD) patients, using as input B-mode US images containing right kidney (RK) cortex and liver parenchyma (LP) areas indicated by an expert radiologist.

Methods: A total of 112 consecutively enrolled, biopsy-validated NAFLD patients underwent a regular abdominal B-mode US examination. For each patient, a radiologist obtained a B-mode US image containing RK cortex and LP and marked a point between the RK and LP, around which a window was automatically cropped. The cropped image dataset was augmented using up-sampling, …

Safety And Activity Of Ctx130, A Cd70-Targeted Allogeneic Crispr-Cas9-Engineered Car T-Cell Therapy, In Patients With Relapsed Or Refractory T-Cell Malignancies (Cobalt-Lym): A Single-Arm, Open-Label, Phase 1, Dose-Escalation Study, Swaminathan P Iyer, R Alejandro Sica, P Joy Ho, Anca Prica, Jasmine Zain, Francine M Foss, Boyu Hu, Amer Beitinjaneh, Wen-Kai Weng, Youn H Kim, Michael S Khodadoust, Auris O Huen, Leah M Williams, Anna Ma, Elaine Huang, Avanti Ganpule, Shashwat Deepali Nagar, Parin Sripakdeevong, Erika L Cullingford, Sushant Karnik, Mary-Lee Dequeant, Janki N Patel, Xinyi Shirley He, Ziliang Li, Qiuling Ally He, Joy H Mendonez, Alissa Keegan, Steven M Horwitz

Faculty, Staff and Student Publications

Background: Effective treatment options are scarce for relapsed or refractory T-cell lymphoma. This study assesses the safety and activity of CTX130 (volamcabtagene durzigedleucel), a CD70-directed, allogeneic chimeric antigen receptor (CAR) immunotherapy manufactured from healthy donor T cells, in patients with relapsed or refractory T-cell lymphoma.

Methods: This single-arm, open-label, phase 1 study was done at ten medical centres across the USA, Australia, and Canada in patients (aged ≥18 years) with relapsed or refractory peripheral T-cell lymphoma or cutaneous T-cell lymphoma, who had received at least one or at least two previous systemic therapy lines, respectively, and had an Eastern Cooperative …

Cord Blood-Derived Ink T Cells As A Platform For Allogeneic Car T Cell Therapy, Maison Grefe, Abel Trujillo-Ocampo, Jelita Clinton, Hong He, Ling Yu, Dan Li, Qing Ma, Elizabeth J Shpall, Jeffrey J Molldrem, Jin S Im

Faculty, Staff and Student Publications

CD1d-restricted invariant Natural Killer (iNK) T cells are a suitable candidate for allogeneic Chimeric Antigen Receptor (CAR) T cell therapy as they do not cause graft-versus-host disease (GvHD) due to the monomorphic nature of CD1d proteins. However, the phenotypic and functional heterogeneity of iNK T cells from adult donors (AD) may lead to the inconstant CAR-iNK T cell products. Cord blood-derived (CB) iNK T cells, in contrast, exhibit inter-donor homogeneity in phenotype including uniform CD4 expression and are enriched in memory iNK T cell populations. Thus, we evaluated the preclinical therapeutic potential of iNK T cells derived from cord blood …

Weighted Hypoxemia Index: An Adaptable Method For Quantifying Hypoxemia Severity, Diane C Lim, Cheng-Bang Chen, Ankita Paul, Yujie Wang, Jinyoung Kim, Soonhyun Yook, Emily Y Kim, Edison Q Kim, Anup Das, Medhi Wangpaichitr, Virend K Somers, Chi Hang Lee, Phyllis C Zee, Toshihiro Imamura, Hosung Kim

Faculty, Staff and Student Publications

Objective: To quantitate hypoxemia severity.

Methods: We developed the Weighted Hypoxemia Index to be adapted to different clinical settings by applying 5 steps to the oxygen saturation curve: (1) Identify desaturation/resaturation event [Formula: see text] by setting the upper threshold; (2) Exclude events as artifact by setting a lower threshold; (3) Calculate weighted area for each [Formula: see text] as [Formula: see text]; (4) Calculate a normalization factor [Formula: see text] for each subject; (5) Calculate the Weighted Hypoxemia Index as the summation of all weighted areas multiplied by [Formula: see text]. We assessed the Weighted Hypoxemia Index predictive value …

Stat3 Inhibition In Combination With Cd47 Blockade Inhibits Osteosarcoma Lung Metastasis, Pradeep Shrestha, Rejeena Shrestha, You Zhou, Rafal Zielinski, Waldemar Priebe, Eugenie S Kleinerman

Faculty, Staff and Student Publications

Background: New therapies are urgently needed for patients with osteosarcoma (OS). STAT3 and CD47 are potential therapeutic target in OS. Here we investigated the therapeutic activity of the orally bioavailable STAT3 inhibitor, WP1066, and anti-CD47 antibody using OS mouse models.

Methods: Cytotoxic effect of WP1066 against OS cell lines and its immunomodulatory effects were evaluated in vitro. Experimental metastasis and orthotopic syngeneic mouse models were used to investigate the therapeutic efficacy of WP1066 and anti-CD47 antibody. Further flow cytometric analysis was performed.

Results: STAT3 was constitutively activated in multiple human and mouse OS cell lines. WP1066 suppressed STAT3 activation …

Evaluation Of Quantum Contouring Algorithms For Treatment Planning On Mr Abdominal Images, Rachel Glenn, Tucker Netherton, Adrian Celaya, Mohamed Eltaher, Beatrice Riviere, Eugene J Koay, David Fuentes

Faculty, Staff and Student Publications

Introduction: Quantum computing is increasingly being investigated for integration into medical radiology and healthcare applications worldwide. Given its potential to enhance clinical care and medical research, there is growing interest in evaluating its practical applications in clinical workflows.

Methods: We developed an evaluation of quantum computing-based auto-contouring methods to introduce medical physicists to this emerging technology. We implemented existing quantum algorithms as prototypes tailored for specific quantum hardware, focusing on their application to auto-contouring in medical imaging. The evaluation was performed using a medical resonance imaging (MRI) abdominal dataset, comprising 102 patient scans.

Results: The quantum algorithms were applied to …

Predicting Sinonasal Inverted Papilloma Attachment Using Machine Learning: Current Lessons And Future Directions, Sean P Mckee, Xiaomin Liang, William C Yao, Brady Anderson, Jumah G Ahmad, David Z Allen, Salman Hasan, Andy J Chua, Chinmay Mokashi, Samia Islam, Amber U Luong, Martin J Citardi, Luca Giancardo

Faculty, Staff and Student Publications

Background: Hyperostosis is a common radiographic feature of inverted papilloma (IP) tumor origin on computed tomography (CT). Herein, we developed a machine learning (ML) model capable of analyzing CT images and identifying IP attachment sites.

Methods: A retrospective review of patients treated for IP at our institution was performed. The tumor attachment site was manually segmented on CT scans by the operating surgeon. We used a nnU-Net model, a state-of-the-art deep learning-based segmentation algorithm that automatically configures image preprocessing, network architecture, training, and post-processing to identify the IP attachment site. The model was trained and evaluated using a 5-fold cross …

2025 Standard-Sized Seedless Watermelon Cultivar Evaluation In Indiana, Wenjing Guan, Dennis Nowaskie, Cesar Escalante

Midwest Vegetable Trial Reports

Indiana ranked fifth in watermelon production in the United States. In 2024, Indiana growers planted approximately 8,100 acres of watermelons. Watermelon cultivar evaluation trials have been conducted annually at the Southwest Purdue Agricultural Center (SWPAC) in Vincennes, IN, for over 30 years. In 2025, 25 standard-sized seedless watermelons were evaluated, and yield and fruit quality parameters were assessed.

2025 Personal-Sized Seedless Watermelon Cultivar Evaluation In Indiana, Wenjing Guan, Dennis Nowaskie, Cesar Escalante

Midwest Vegetable Trial Reports

Indiana ranks fifth in the United States for watermelon production in 2024. Most of the state’s production consists of red-flesh seedless cultivars with fruit weighing 9 lbs and above. A small portion of watermelon production devoted to mini seedless types. Meanwhile, interest in watermelon production among small and diversified vegetable farms is increasing, where smaller-sized watermelons are likely fit better at these farms. In this report, we summarize the performance of 12 personal-sized watermelon cultivars evaluated at the Southwest Purdue Agricultural Center (SWPAC) in Vincennes, IN, during the 2025 season.

Colored Sweet Bell And Tapered Pepper Cultivar Evaluation For High Tunnel Production In West-Central Indiana, 2025, Petrus Langenhoven

Midwest Vegetable Trial Reports

Colored sweet bell-shaped and tapered peppers remain an important summer crop for small and medium-sized farming operations across Indiana. These crops can be produced in open-field systems or under protective structures, with high tunnels offering notable advantages for sweet pepper production. The moderated environment of a high tunnel allows planting 2–4 weeks earlier in the spring and extends harvest into the fall until the first hard freeze. Despite the crop’s regional importance, performance data for pepper varieties adapted to Indiana conditions have been limited. Our ongoing work aims to address this gap. To date, more than forty pepper cultivars have …

Eggplant Cultivar Demonstration Results For West-Central Indiana, 2025, Petrus Langenhoven, Alexandria Catherine Snabes

Midwest Vegetable Trial Reports

An eggplant cultivar demonstration at Purdue University's Meigs Horticulture Facility evaluated ten cultivars during the 2025 growing season to support evidence-based variety selection for Indiana growers. Eggplant production in Indiana totaled 34 acres in 2022, representing part of a national industry where 88.9% of 7,261 operations cultivate less than one acre. This demonstration provided performance data under Indiana conditions while offering hands-on learning for horticulture students. Results inform cultivar recommendations for small to medium-scale Midwest producers supplying diverse markets, including restaurants, farmers' markets, and ethnic food retailers seeking this Solanaceae crop for Asian, Mediterranean, and Middle Eastern cuisines.

Heterogeneous Clustering Of Multiomics Data For Breast Cancer Subgroup Classification And Detection, Joseph Pateras, Musaddiq Lodi, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

The rapid growth of diverse -omics datasets has made multiomics data integration crucial in cancer research. This study adapts the expectation–maximization routine for the joint latent variable modeling of multiomics patient profiles. By combining this approach with traditional biological feature selection methods, this study optimizes latent distribution, enabling efficient patient clustering from well-studied cancer types with reduced computational expense. The proposed optimization subroutines enhance survival analysis and improve runtime performance. This article presents a framework for distinguishing cancer subtypes and identifying potential biomarkers for breast cancer. Key insights into individual subtype expression and function were obtained through differentially expressed gene …

Foundation Models In Bioinformatics, Fei Guo, Renchu Guan, Yaohang Li, Qi Liu, Xiaowo Wang, Can Yang, Jianxin Wang

Computer Science Faculty Publications

With the adoption of foundation models (FMs), artificial intelligence (AI) has become increasingly significant in bioinformatics and has successfully addressed many historical challenges, such as pre-training frameworks, model evaluation and interpretability. FMs demonstrate notable proficiency in managing large-scale, unlabeled datasets, because experimental procedures are costly and labor intensive. In various downstream tasks, FMs have consistently achieved noteworthy results, demonstrating high levels of accuracy in representing biological entities. A new era in computational biology has been ushered in by the application of FMs, focusing on both general and specific biological issues. In this review, we introduce recent advancements in bioinformatics FMs …

A Data-Driven Sliding-Window Pairwise Comparative Approach For The Estimation Of Transmission Fitness Of Sars-Cov-2 Variants And The Construction Of The Evolution Fitness Landscape, Md Jubair Pantho, Richard Annan, Landen Alexander Bauder, Sophia Huang, Letu Qingge, Hong Qin

Computer Science Faculty Publications

Estimating the transmission fitness of SARS-CoV-2 variants and understanding their evolutionary fitness trends are important for epidemiological forecasting. Existing methods are often constrained by their parametric natures and do not satisfactorily align with the observations during COVID-19. Here, we introduce a sliding-window data-driven pairwise comparison method, the differential population growth rate (DPGR) that uses viral strains as internal controls to mitigate sampling biases. DPGR is applicable in time windows in which the logarithmic ratio of two variant subpopulations is approximately linear. We apply DPGR to genomic surveillance data and focus on variants of concern (VOCs) in multiple countries and regions. …

Gramseq-Dta: A Grammar-Based Drug-Target Affinity Prediction Approach Fusing Gene Expression Information, Kasul Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Drug–target affinity (DTA) prediction is a critical aspect of drug discovery. The meaningful representation of drugs and targets is crucial for accurate prediction. Using 1D string-based representations for drugs and targets is a common approach that has demonstrated good results in drug–target affinity prediction. However, these approach lacks information on the relative position of the atoms and bonds. To address this limitation, graph-based representations have been used to some extent. However, solely considering the structural aspect of drugs and targets may be insufficient for accurate DTA prediction. Integrating the functional aspect of these drugs at the genetic level can enhance …

Benchmarking Batch-Effect Correction Methods Towards The Construction Of A Triple-Negative Breast Cancer Cell Atlas, Peter Scheible, Amy H. Tang, Jing He, Jiangwen Sun

Computer Science Faculty Publications

Triple-negative breast cancer (TNBC) requires detailed cellular mapping given its aggressive nature, immense tumor heterogeneity and genetic diversity. We integrated 156,794 cells from six scRNA-seq datasets—including tumors, metastases, and cell lines—to build a TNBC scRNA cell atlas, focusing on batch effect mitigation while maintaining biological and molecular details. Preprocessing f ilters noise, normalizes data, and leverages PCA for integration readiness. We utilized scANVI, a semi-supervised tool, to align datasets, preserving TNBC’s complex tumor heterogeneity via marker annotations [1]. UMAPs demonstrate biological clustering in integrated data, contrasted with datasetdriven unintegrated patterns. Assessments verifying effective batch correction. This method aligns with NASA’s …

Cath-Ddg: Towards Robust Mutation Effect Prediction On Protein-Protein Interactions Out Of Cath Homologous Superfamily, Guanglei Yu, Xuehua Bi, Teng Ma, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Protein-protein interactions (PPIs) are fundamental aspects in understanding biological processes. Accurately predicting the effects of mutations on PPIs remains a critical requirement for drug design and disease mechanistic studies. Recently, deep learning models using protein 3D structures have become predominant for predicting mutation effects. However, significant challenges remain in practical applications, in part due to the considerable disparity in generalization capabilities between easy and hard mutations. Specifically, a hard mutation is defined as one with its maximum TM-score < 0.6 when compared to the training set. Additionally, compared to physics-based approaches, deep learning models may overestimate performance due to potential data leakage.

Results: We propose new training/test splits that mitigate data leakage according to the CATH homologous superfamily. Under the constraints of physical …

A Survey On Deep Learning For Drug-Target Binding Prediction: Models, Benchmarks, Evaluation, And Case Studies, Kusal Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Conventional drug discovery is expensive, time-consuming, and prone to failure. Artificial intelligence has become a potent substitute over the last decade, providing strong answers to challenging biological issues in this field. Among these difficulties, drug-target binding (DTB) is a key component of drug discovery techniques. In this context, drug-target affinity and drug–target interaction are complementary and essential frameworks that work together to improve our comprehension of DTB dynamics. In this work, we thoroughly analyze the most recent deep learning models, popular benchmark datasets, and assessment metrics for DTB prediction. We look at the paradigm shift in the development of drug …

Deepssetracer 2.0: Improved Deep Learning Model Performance For Protein Secondary Structure Segmentation From Cryo-Em Maps, Bryan Hawickhorst, Thu Nguyen, Willy Wriggers, Jiangwen Sun, Jing He

Computer Science Faculty Publications

DeepSSETracer is a method for segmenting protein secondary structure from medium-resolution (5-10Å) cryogenic electron microscopy (cryo-EM) density maps. We conducted experiments and ablation studies to examine the effects of normalization methods, max-pooling, activation functions, and loss calculation region on DeepSSETracer. By combining multiple technical improvements, the performance of the new version, DeepSSETracer 2.0, was significantly enhanced compared to DeepSSETracer 1.1. On a set of 77 test cases, the weighted average per-voxel F1 score increased from 62.1% to 70.3% for helix detection, and from 47.8% to 62.5% for β-sheet detection. While each of the five modifications in the network enhanced the …

Benchmarking And Improving Foundation Model Dietary Estimates From Meal Images, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Accurate quantifying dietary contents, such as calories, proteins, carbohydrates, and fats, from an image of a meal plate is vital for managing diabetes. Recently, Large Multimodal Models (LMMs) have excelled in complex vision-language tasks due to their use of very large, highly diverse data. This study benchmarked the use of seven LMMs that include full and lightweight models of GPT, Gemini, and Llama for nutrition estimation based on Google's Nutrition5k dataset and our own phone-collected DonateAndLearn dataset. We analyzed the performance of LMMs and the RGB-D fusion model, in which the RGB-D model was specifically trained using Nutrition5k data. On …

General Kernel Machine Methods For Multi-Omics Integration And Genome-Wide Association Testing With Related Individuals, Amarise Little, Ni Zhao, Anna Mikhaylova, Angela Zhang, Wodan Ling, Florian Thibord, Andrew D. Johnson, Laura M. Raffield, Joanne E. Curran, John Blangero

School of Medicine Publications

Integrating multi-omics data may help researchers understand the genetic underpinnings of complex traits and diseases. However, the best ways to integrate multi-omics data and use them to address pressing scientific questions remain a challenge. One important and topical problem is how to assess the aggregate effect of multiple genomic data types (e.g. genotypes and gene expression levels) on a phenotype, particularly while accommodating routine issues, such as having related subjects' data in analyses. In this paper, we extend an existing composite kernel machine regression model to integrate two multi-omics data types, while accommodating for general correlation structures amongst outcomes. Due …

Pattern Integration And Differentiation: Dual Process Model Of Episodic Memory, Hallvard Røe Evensmoen, Lars M. Rimol, Henning Stople Rise, Tor Ivar Hansen, Hamed Nili, Anderson M. Winkler, Asta K. Håberg

Human Genetics Publications

The role of precise timing in episodic memory remains obscure. We showed 139 participants episodes consisting of objects, and tested subsequent memory for the precise timing and order of the objects and episodes. Temporal compression of the episode enhanced memory for relative but not absolute timing of the objects’ presentation and their order. Conversely, temporal expansion between neighboring episodes was associated with successful memory for episode order. fMRI in 36 participants revealed that temporal compression of the episode was associated with more similar activation patterns within episodes in several brain regions including the posterior hippocampus. However, the activation pattern in …

Characterization Of An Acetogenin-Carrying Nanosuspension And Its Effect On Bacteria Of Interest In The Poultry Industry, Brandon A. Lopez-Romero, Gabriela Aguilar-Hernandez, Billy Hargis, Maria De Lourdes Garcia-Magana, Ulises M. Lopez-Garcia, Rosa I. Ortiz-Basurto, Adalberto Zamudio-Ojeda, Juan D. Latorre, Efigenia Montalvo-Gonzalez

Poultry Science Faculty Publications and Presentations

This work aimed to develop a nanosuspension (NSps) as an acetogenin (ACGs) carrier, using soy lecithin (SL) and hydroxypropyl-beta-cyclodextrin (beta CD) named NSps-beta CDSL-ACGs. It was characterized by various spectroscopic techniques (DLS, FTIR, UV-vis diffuse reflectance). Moreover, the NSps morphology was observed by transmission electron microscopy (TEM). Also, the antibacterial activity of NSps-beta CDSL-ACGs was evaluated against strains of interest in the poultry sector. NSps-beta CDSL-ACGs presented nanometric size (207-239 nm), acceptable polydispersity index (PDI) values (0.13-0.17) and a high Z potential value (-47.17-50.36 mV), demonstrating high stability. The presence of ACGs in NSps-beta CDSL-ACGs was confirmed by FTIR analysis. …