Digital Commons Network^™

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 M. 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-β-cyclodextrin (βCD) named NSps-βCDSL-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-βCDSL-ACGs was evaluated against strains of interest in the poultry sector. NSps-βCDSL-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-βCDSL-ACGs was confirmed by FTIR analysis. The nanoparticles had a spherical …

Gc-Ms Analysis And Evaluation Of Antioxidant, Anticancer, Cytotoxicity, And Hypoglycemic Properties Of The Libyan Moringa Oleifera Leaf Extract On Alloxan-Induced Diabetes In Mice, Osama Abdel-Hafeez Mohammed Al-Bedak, Ahlam Rashed, Seham T.M. Oskandali, Nouri Kushlaf, Amal Eishebani, Samira A. Alacrouk, Fadia T.M. Oshkandale, Manal Eisheli, Zahur R. Almesai, Ameerah Shaeroun, Steven L. Stephenson, Fuad Ameen

Biological Sciences Faculty Publications and Presentations

Libyan Moringa oleifera leaves were extracted using methanol, and the bioactive components' antibacterial, antioxidant, anti-inflammatory, and anticancer characteristics were assessed using gas chromatography mass spectrometry analysis (GC-MS). Moringa oleifera exhibited antioxidant activity, with an IC50 of 11.53 µg/mL. Wi38 cell line's viability decreased with increasing M. oleifera extract concentration, while its cytotoxicity increased with an IC50 of 393.41±7.77 μg/mL. Alloxan-induced diabetes model in Swiss albino mice was implemented. Three different doses (100, 200, or 300 mg/kg of mice body weight) of M. oleifera’s extract were evaluated for their effects on blood sugar concentration and the histology of the pancreatic islets. …

Dehydrin Client Proteins Identified Using Phage Display Affinity Selected Libraries Processed With Paired-End Phage Sequencing, Sandra Helena Unêda-Trevisoli, Lynnette M.A. Dirk, Francisco Elder Carlos Bezerra Pereira, Manohar Chakrabarti, Guijie Hao, James M. Campbell, Sai Deepshikha Bassetti Nayakwadi, Ashley Morrison, Sanjay Joshi, Sharyn E. Perry

School of Integrative Biological & Chemical Sciences Faculty Publications

The late embryogenesis abundant proteins (LEAPs) are a class of noncatalytic, intrinsically disordered proteins with a malleable structure. Some LEAPs exhibit a protein and/or membrane binding capacity and LEAP binding to various targets has been positively correlated with abiotic stress tolerance. Regarding the LEAPs’ presumptive role in protein protection, identifying client proteins (CtPs) to which LEAPs bind is one practicable means of revealing the mechanism by which they exert their function. To this end, we used phage display affinity selection to screen libraries derived from Arabidopsis thaliana seed mRNA with recombinant orthologous LEAPs from Arabidopsis and soybean (Glycine max …

Variation In Sorghum Aphid (Melanaphis Sorghi) 1 Populations Translates Into Life History Traits On Sorghum-Sudangrass (Sorghum´ Drummondii), Neetu Khanal, Christopher J. Vitek, Rupesh R. Kariyat

School of Integrative Biological & Chemical Sciences Faculty Publications

Sorghum aphid (Melanaphis sorghi; SA) (Theobald) is a new invasive pest of sorghum first reported in the USA in 2013. Since then, the use of synthetic pesticides and resistant cultivars have increased, which has caused levels of differences in the populations of SAs and led to the potential emergence of new biotype(s) of SA. However, most research has concentrated on comparing SA fed on sorghum, sugarcane, and other hosts, which may have obscured any population differences that may exist within sorghum. To understand this, we collected three populations of SA that fed on sorghum from three different locations around …

Reducing Dna Extraction Costs Through Factorial Design For The Dnadvance Kit, Carson J. Neal, Zachery D. Zbinden, Michael E. Douglas, Marlis R. Douglas

Biological Sciences Faculty Publications and Presentations

Objective

Extracting DNA is essential in wildlife genetic studies, and numerous methods are available. However, the process is costly and time-consuming for non-model organisms, including most wildlife species. Therefore, we optimized a cost-efficient protocol to extract DNA from the muscle tissue of White-tailed Deer using the DNAdvance kit (Beckman Coulter), a magnetic-bead-based approach. We devised a 3 × 3 factorial design using combinations of tissue mass (10 mg, 50 mg, or 100 mg) and reaction volume (25%, 33%, and 50% of the manufacturer's recommended volumes). DNA was extracted for N = 81 tissue sub-samples (9 replicates/treatment).

Results

Our target yield …

Biosense: An Automated Sensing Node For Organismal And Environmental Biology, Andrea Contina, Eric Abelson, Brendan Allison, Brian Stokes, Kenedy F. Sanchez, Henry M. Hernandez, Anna M. Kepple, Quynhmai Tran, Isabella Kazen

School of Integrative Biological & Chemical Sciences Faculty Publications

Automated remote sensing has revolutionized the fields of wildlife ecology and environmental science. Yet, a cost-effective and flexible approach for large scale monitoring has not been fully developed, resulting in a limited collection of high-resolution data. Here, we describe BioSense, a low-cost and fully programmable automated sensing platform for applications in bioacoustics and environmental studies. Our design offers customization and flexibility to address a broad array of research goals and field conditions. Each BioSense is programmed through an integrated Raspberry Pi computer board and designed to collect and analyze avian vocalizations while simultaneously collecting temperature, humidity, and soil moisture data. …

Decoding Fgf/Fgfr Signaling: Insights Into Biological Functions And Disease Relevance, Oshadi Edirisinghe, Gaetane Ternier, Zeina Alraawi, Thallapuranam Krishnaswamy Suresh Kumar

Chemistry & Biochemistry Faculty Publications and Presentations

Fibroblast Growth Factors (FGFs) and their cognate receptors, FGFRs, play pivotal roles in a plethora of biological processes, including cell proliferation, differentiation, tissue repair, and metabolic homeostasis. This review provides a comprehensive overview of FGF-FGFR signaling pathways while highlighting their complex regulatory mechanisms and interconnections with other signaling networks. Further, we briefly discuss the FGFs involvement in developmental, metabolic, and housekeeping functions. By complementing current knowledge and emerging research, this review aims to enhance the understanding of FGF-FGFR-mediated signaling and its implications for health and disease, which will be crucial for therapeutic development against FGF-related pathological conditions.

Tumor Expression Of Cd83 Reduces Glioma Progression And Is Associated With Reduced Immunosuppression, Malcolm F Mcdonald, Rachel Naomi Curry, Isabella O'Reilly, Brittney Lozzi, Alexis Cervantes, Zhung-Fu Lee, Anna Rosenbaum, Peihao He, Carrie Mohila, Arif O Harmanci, Akdes Serin Harmanci, Benjamin Deneen, Ganesh Rao

Faculty, Staff and Student Publications

Immunosuppression in malignant glioma remains a barrier to therapeutic development. CD83 overexpression in human and mouse glioma increases survival. CD83+ tumor cells promote signatures related to cytotoxic T cells, enhanced activation of CD8+ T cells, and increased proinflammatory cytokines. These findings suggest that tumor-expressed CD83 could mediate tumor-immune communications.

Piloting A Novel Computational Framework For Identifying Prosthesis-Specific Contributions To Gait Deviations, Jacques Ezechiel N'Guessan, Muhammad Hassaan Ahmed, Matthew Leineweber, Sachin Goyal

Faculty Research, Scholarly, and Creative Activity

This paper introduces a novel computational framework for evaluating above-knee prostheses, addressing a major challenge in gait deviation studies: distinguishing between prosthesis-specific and patient-specific contributions to gait deviations. This innovative approach utilizes three separate computational models to quantify the changes in gait dynamics necessary to achieve a set of ideal gait kinematics across different prosthesis designs. The pilot study presented here employs a simple two-dimensional swing-phase model to conceptually demonstrate how the outcomes of this three-model framework can assess the extent to which prosthesis design impacts a user's ability to replicate the dynamics of able-bodied gait. Furthermore, this framework offers …

Enhancing Medical Cybersecurity: A Machine Learning Solution For Intrusion Detection In Iomt Devices, Afra Yaqoob

Theses

In the past few decades, the healthcare sector has undergone major technological advancements, which have included the adoption of Internet of Medical Things (IoMT), and networked medical devices. These advancements have changed the manner in which patient care is provisioned, enabling for more accurate diagnosis, personalized treatment plans, among other benefits. However, as healthcare providers are growing more reliant on interconnected systems, they have also been exposed to critical cybersecurity vulnerabilities. Medical devices have now become targets for cyberattacks, threatening patient data and its security and endangering patient's health and safety. This thesis examines the affects that inadequate cybersecurity measures, …

Artificial Neurovascular Networks To Simulate Energy Distribution To Spiking Neural Networks, William Bottom

Theses

Biological neurons are known to be much more energy efficient than modern computers, with the human brain only consuming about 20 Watts. An Artificial Neural Network can take hours or days to train on high-performance and energy-consuming GPUs, so networks that can achieve similar performance at a fraction of the energy cost are very sought after. Spiking Neural Networks, which mimic biological neurons more closely than Artificial Neural Networks (ANNs), are a potential option for the energy problem in Neural Networks. By converting an ANN to an SNN and applying energy-saving methods/architectures, the equivalent SNN network can achieve similar performance …

Small Angle X-Ray Scattering And Form Factor Modeling Of Β Crystallins - A Physiologically Significant Eye Lens Cytoplasm Protein, Srijan Banerjee

Theses

This thesis provides in depth analysis of small angle x-ray scattering (SAXS) experiments conducted on the beta-high crystallin eye lens cytoplasm protein. In particular, radius of gyration and molecular weight measurements are extracted and compared to measurements from existing work. Furthermore, an approach to math ematically modeling the scattering ”form-factor”, which describes the size and shape of individual particles, is also developed and applied to the SAXS data. The model acheived in the thesis appears to agree closely with scattering data at the low q range. Several obstacles which impede the resulting modeling from perfectly characterizing the data at higher …

Robust And Efficient Active Inference For Perception, Action, And Learning, Zhizhuo Yang

Theses

Active Inference (AIF) is an emerging framework rooted in neuroscience aimed at elucidating human perception, action, and cognitive processes. Recent advances in machine learning have facilitated the non-invasive study of human cognition through the lens of this framework. This dissertation expands upon this theoretical foundation to address practical challenges in robotic control and human cognitive behavior analysis. We initiate our exploration with a review of the eye-tracking studies that underpin the motivation for AIF research. This provides a background for understanding how AIF can model cognitive processes. First, we present a minimal AIF model within a discrete state space, framed …

Deep Subseafloor Sediments In Guaymas Basin Harbor Cosmopolitan Microbiota And Traces Of Hydrothermal Populations, Paraskevi Mara, David Beaudoin, Ivano Aiello, Yuki Morono, David Geller-Mcgrath, Virginia P. Edgcomb, Andreas Teske

Faculty Research, Scholarly, and Creative Activity

Environmental factors shape subsurface microbial ecosystems, and well-characterized sites are ideal for determining how environmental parameters shape sediment communities. Sediments from eight geologically and thermally distinct sites were drilled during International Ocean Discovery Program Expedition 385 in Guaymas Basin, an expedition focused on the hydrothermal deep biosphere. Using high-throughput 16S ribosomal nucleic acid sequencing, cell counts, phylogenetics, metatranscriptomics, and mineralogical/elemental X-ray spectroscopy, we examine linkages and feedbacks between mineral composition, temperature, geochemistry, and microbial populations. We show subsurface life is dominated by heterotrophic, cosmopolitan prokaryotes that thrive within a range of sediments and temperature conditions across Guaymas Basin. Hydrothermally-affiliated lineages …

Private Landowner Interest In Prescribed Fire In California: Findings From Workshops In The Sierra Nevada, Kate M. Wilkin, Amanda M. Stasiewicz, Susan D. Kocher

Faculty Research, Scholarly, and Creative Activity

Background: Globally, prescribed fire political interest and practice has been rekindled following recent devastating wildfire seasons. This phenomenon was especially acute in areas with dual wildfire and forest health crises, like California. Previous research has investigated prescribed fire on public lands or on private lands in other regions, but little is known about prescribed fire practice or interest on private lands in California. Therefore, we sought to understand private land managers’ perceptions of prescribed fire compared to other land management techniques, treatment pathways, motivations, and barriers to complete these treatments in California. Results: Before workshops on prescribed fire for private …

A Multiscale Approach To Understanding The Shared Blue-Orange Flower Color Polymorphism In Two Lysimachia Species, Mercedes Sánchez-Cabrera, Eduardo Narbona, Montserrat Arista, Pedro L. Ortiz, Francisco J. Jiménez-López, Amelia Fuller, Benjamin Carter, Justen B. Whittall

Faculty Research, Scholarly, and Creative Activity

Background: Polymorphisms are common in nature, but they are rarely shared among closely related species. Polymorphisms could originate through convergence, ancestral polymorphism, or introgression. Although shared neutral genomic variation across species is commonplace, few examples of shared functional traits exist. The blue-orange petal color polymorphisms in two closely related species, Lysimachia monelli and L. arvensis were investigated with UV-vis reflectance spectra, flavonoid biochemistry, and transcriptome comparisons followed by climate niche analysis. Results: Similar color morphs between species have nearly identical reflectance spectra, flavonoid biochemistry, and ABP gene expression patterns. Transcriptome comparisons reveal two orange-specific genes directly involved in both blue-orange …

Beyond Boundaries: Governance Considerations For Climate-Driven Habitat Shifts Of Highly Migratory Marine Species Across Jurisdictions, Bianca S. Santos, Elliott L. Hazen, Heather Welch, Nerea Lezama-Ochoa, Barbara A. Block, Daniel P. Costa, Scott A. Shaffer, Larry B. Crowder

Faculty Research, Scholarly, and Creative Activity

The mobile nature of migratory marine animals across jurisdictional boundaries can challenge the management of biodiversity, particularly under global environmental change. While projections of climate-driven habitat change can reveal whether marine species are predicted to gain or lose habitat in the future, geopolitical boundaries and differing governance regimes may influence animals’ abilities to thrive in new areas. Broad geographic movements and diverse governance approaches elicit the need for strong international collaboration to holistically manage and conserve these shared migratory species. In this study, we use data from the Tagging of Pacific Predators program to demonstrate the feasibility of using climate-driven …

Aars Online: A Collaborative Database On The Structure, Function, And Evolution Of The Aminoacyl-Trna Synthetases, Jordan Douglas, Haissi Cui, John J. Perona, Oscar Vargas-Rodriguez, Henna Tyynismaa, Claudia Alvarez Carreno, Jiqiang Ling, Lluis Ribas De Pouplana, Xiang-Lei Yang, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

The aminoacyl-tRNA synthetases (aaRS) are a large group of enzymes that implement the genetic code in all known biological systems. They attach amino acids to their cognate tRNAs, moonlight in various translational and non-translational activities beyond aminoacylation, and are linked to many genetic disorders. The aaRS have a subtle ontology characterized by structural and functional idiosyncrasies that vary from organism to organism, and protein to protein. Across the tree of life, the 22 coded amino acids are handled by 16 evolutionary families of Class I aaRS and 21 families of Class II aaRS. We introduce AARS Online, an interactive Wikipedia-like …

Nuclear Expression Of Dynamin 2 Is Associated With Tumor Aggressiveness In Bladder Cancer Patients: A Bioinformatics And Experimental Approach, Mahdieh Razmi, Leili Saeednejad Zanjani, Mandana Rahimi, Roya Sajed, Sadegh Safaei, Zahra Madjd, Roya Ghods

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

BACKGROUND: Dynamin 2 (DNM2) is aberrantly expressed in different malignancies and exerts a function in tumor progression.

AIMS: This study, for the first time, aimed to evaluate the clinical and prognostic value of DNM2 in the pathophysiology of bladder cancer using bioinformatics analysis and experimental evaluation.

METHODS AND RESULTS: We analyzed gene expression of DNM2 in bladder tumor by GEPIA2 and GENT2 platforms. Cluster subnetworks were recognized from the protein-protein interaction (PPI) network using the MCODE plugin to screen the key genes. Subsequently, the pathway enrichment analysis was evaluated. Then, the immunohistochemical examination was conducted on 209 paraffin-embedded bladder cancer …

Facilitated Forest Restoration Using Pioneer Seed Dispersers In Madagascar: The Example Of Microcebus Spp., Joerg U. Ganzhorn, Jean-Basile Andriambeloson, Sylvia Atsalis, Lis M. Behrendt, Marina B. Blanco, An Bollen, Stephanie M. Carriere, Lounes Chikhi, Melanie Dammhahn, Giuseppe Donati, Timothy M. Eppley, Multiple Additional Authors

Anthropology Faculty Publications and Presentations

The concept of “facilitated restoration” aims at native biodiversity reinstatement with the help of animal seed dispersers attracted by fruiting trees. Yet, large-crowned trees will have to develop in the early stages of restoration; therefore, seed dispersal provided by small generalist mammals and birds that use rapidly growing herbs, shrubs, and small trees at early stages of forest succession would accelerate biodiversity restoration. Due to the elusive lifestyle of these small animals, it is unclear what species can contribute to the early stages of this process. Using the primate genus Microcebus (adult body mass about 60 g) as an example, …

Predicting Newborn Low Birth Weight: A Machine Learning Approach Using Maternal Health And Demographic Data, Rayan Elsayed

Theses

Low birth weight (LBW), defined by the World Health Organization as a birth weight under 2500 grams, remains a major global health challenge due to its association with increased risks for adverse neonatal and long-term health outcomes. This study aims to identify maternal health factors that contribute to LBW and to develop predictive models to support early identification of at-risk pregnancies. Two machine learning models, Logistic Regression (LR) and Random Forest (RF), were developed to analyze the relationship between maternal factors and LBW outcomes. The RF model achieved an accuracy of 96.36%, demonstrating robust predictive performance across metrics, making it …

Evaluation Of Industrial Hemp Cultivar And Biochar Rate To Remediate Heavy-Metal-Contaminated Soil From The Tar Creek Superfund Site, Usa, Dietrich V. Thurston, Kristofor R. Brye, David M. Miller, Philip A. Moore Jr., Donald M. Johnson, Mike Richardson

Crop, Soil and Environmental Sciences Faculty Publications and Presentations

Soil contamination by cadmium (Cd), lead (Pb), and zinc (Zn) at the Tar Creek superfund site in northeast Oklahoma, United States, remains a threat to the environment and local ecosystem. Phytoremediation with industrial hemp (Cannabis sativa L.) and the use of biochar (BC) have been independently shown to be effective methods to remediate heavy-metal-contaminated soils. The objective of this greenhouse study was to evaluate the effects of industrial hemp cultivar (‘Carmagnola’ and ‘Jinma’), biochar rate (0, 2, 5, and 10% by volume), soil contamination level (low, medium, and high), and their interactions on above- (AG) and belowground dry matter …

Rice Response To Struvite And Other Phosphorus Fertilizers In A Phosphorus-Deficient Soil Under Simulated Furrow-Irrigation, Jonathan B. Brye, Diego Della Lunga, Kristofor R. Brye

Crop, Soil and Environmental Sciences Faculty Publications and Presentations

Wastewater-recovered phosphorus (P), in the form of the mineral struvite (MgNH₄PO₄⋅6H₂O), may provide a sustainable alternative to decreasing rock-phosphate reserves. Struvite can be generated via precipitation methods, potentially reducing the amount of P runoff to aquatic ecosystems. The objective of this greenhouse tub study was to evaluate the effects of chemically- and electrochemically precipitated struvite (CPST and ECST, respectively) on above- and belowground plant response in a hybrid rice (Oryza sativa) cultivar grown using furrow-irrigation compared to other common fertilizer-P sources [i.e., triple super phosphate (TSP) and diammonium phosphate (DAP)]. Rice was …

Interpreting The Spatial Distribution Of Soil Properties With A Physically-Based Distributed Hydrological Model, Zamir Libohova, Marcelo Mancini, Hans Edwin Winzeler, Quentin D. Read, Ning Sun, Dylan Beaudette, Candiss Williams, Joshua Michael Blackstock, Sergio H.G. Silva, Nilton Curi, Kabindra Adhikari, Amanda Ashworth, Joshua O. Minai, Phillip R. Owens

Crop, Soil and Environmental Sciences Faculty Publications and Presentations

Digital soil maps are commonly data-driven as the development of physically-based models for soil mapping is difficult due to the complexity of soils. However, physically-based hydrologic models have been successful in simulating water dynamics. Since water movement is a major driver of pedogenesis, the physical rules that govern water movement might help explain and predict the spatial variation of soil properties. Here, we demonstrate the novel use of a physically-based, distributed hydrologic model to inform the spatial distribution of soil properties. The Distributed Hydrology Soil Vegetation Model (DHSVM) was utilized to simulate soil moisture content (SM) and water table …

Artificial Intelligence And Cracks In The Foundation Of Intellectual Property, Robin Feldman

UC Law Journal

Our implicit image of progress and the standards we use to calibrate human contribution to progress are quietly at risk from the onslaught of artificial intelligence (AI). AI has the potential to significantly shrink the pool of creative work that is protectable by intellectual property (IP) law and the range of information that is protectable, as well as shrinking the value proposition of IP regimes themselves.

As society faces this changing landscape, we must tread carefully to distinguish fears about AI from the task of defining the boundaries of intellectual property, whose theoretic concepts aren’t designed to bear such weighty …

Development And Evaluation Of A Training Curriculum To Engage Researchers On Accessing And Analyzing The All Of Us Data, Julie R Coleman, Jasmine N Baker, Shamika Ketkar, Ashley M Butler, Laterrica Williams, Latanya Hammonds-Odie, Elizabeth G Atkinson, Debra D Murray, Brendan Lee, Kim C Worley

Faculty, Staff and Students Publications

OBJECTIVE: The All of Us Evenings with Genetics (EwG) Research Program at Baylor College of Medicine (BCM), funded to engage research scholars to work with the All of Us data, developed a training curriculum for the Researcher Workbench, the platform to access and analyze All of Us data. All of Us EwG developed the curriculum so that it could teach scholars regardless of their skills and background in programming languages and cloud computing. All of Us EwG delivered this curriculum at the first annual All of Us EwG Faculty Summit in May 2022. The curriculum was evaluated both during and …

Hands-On Training About Data Clustering With Orange Data Mining Toolbox, Janez Demšar, Blaž Zupan

Faculty, Staff and Students Publications

Data clustering is a core data science approach widely used and referenced in the scientific literature. Its algorithms are often intuitive and can lead to exciting, insightful results that are easy to interpret. For these reasons, data clustering techniques could be the first method encountered in data science training. This paper proposes a hands-on approach to data clustering training suitable for introductory courses. The education approach features problem-based training that starts with the data and gradually introduces various data processing and analysis methods, illustrating them through visual representations of data and models. The proposed training is suitable for a general …

Lenvatinib Plus Ifosfamide And Etoposide In Children And Young Adults With Relapsed Osteosarcoma: A Phase 2 Randomized Clinical Trial, Nathalie Gaspar, Giun-Yi Hung, Sandra J Strauss, Quentin Campbell-Hewson, Filemon S Dela Cruz, Julia L Glade Bender, Kyung-Nam Koh, Sarah B Whittle, Godfrey Chi-Fung Chan, Nicolas U Gerber, Sauli Palmu, Daniel A Morgenstern, Alessandra Longhi, Fredrik Baecklund, Jun Ah Lee, Franco Locatelli, Catalina Márquez Vega, Katherine A Janeway, Geoffrey Mccowage, Martin G Mccabe, Behzad Bidadi, Jie Huang, Jodi Mckenzie, Chinyere E Okpara, Francisco Bautista, Olie Study Investigators

Faculty, Staff and Students Publications

IMPORTANCE: The combination of ifosfamide and etoposide (IE) is commonly used to treat relapsed or refractory osteosarcoma; however, second-line treatment recommendations vary across guidelines.

OBJECTIVE: To evaluate whether the addition of lenvatinib to IE (LEN-IE) improves outcomes in children and young adults with relapsed or refractory osteosarcoma.

DESIGN, SETTING, AND PARTICIPANTS: The OLIE phase II, open-label, randomized clinical trial was conducted globally across Europe, Asia and the Pacific, and North America. From March 22, 2020, through November 11, 2021, the trial enrolled patients aged 2 to 25 years with high-grade osteosarcoma, measurable or evaluable disease per Response Evaluation Criteria in …

10 Practical Priorities To Prevent And Manage Serious Allergic Reactions: Ga2len Anacare And Efa Anaphylaxis Manifesto, Antonella Muraro, Debra De Silva, Marcia Podesta, Aikaterini Anagnostou, Victoria Cardona, Susanne Halken, Pete Smith, Luciana Kase Tanno, Paul Turner, Margitta Worm, Montserrat Alvaro-Lozano, Stefania Arasi, Anna Asarnoj, Simona Barni, Kirsten Beyer, Lucy A Bilaver, Andrew Bird, Roberta Bonaguro, Helen A Brough, R Sharon Chinthrajah, Emma E Cook, Céline Demoulin, Antoine Deschildre, Timothy E Dribin, Motohiro Ebisawa, Montserrat Fernandez-Rivas, Alessandro Fiocchi, David M Fleischer, Eleanor Garrow, Jennifer Gerdts, Mattia Giovannini, Kirsi M Järvinen, Mary Kelly, Edward F Knol, Gideon Lack, Francesca Lazzarotto, Thuy-My Le, Stephanie Leonard, Jay Lieberman, Michael Makris, Lianne Mandelbaum, Mary Jane Marchisotto, Gustavo Andres Marino, Francesca Mori, Caroline Nilsson, Anna Nowak-Wegrzyn, Mikaela Odemyr, H N G Oude Elberink, Kati Palosuo, Nandinee Patel, Jennifer Pier, Sung Poblete, Rima Rachid, Pablo Rodríguez Del Río, Maria Said, Hugh A Sampson, Angel Sánchez Sanz, Sabine Schnadt, Fallon Schultz, Alice Toniolo, Julia E M Upton, Carina Venter, Brian P Vickery, Berber Vlieg-Boerstra, Julie Wang, Graham Roberts, Torsten Zuberbier, Ga2len Anacare Centres And Efa

Faculty, Staff and Students Publications

This Anaphylaxis Manifesto calls on communities to prioritise 10 practical actions to improve the lives of people at risk of serious allergic reactions. The Global Allergy and Asthma European Network and the European Federation of Allergy and Airways Diseases Patients' Associations (EFA) compiled patient-centric priorities. We used qualitative consensus methods, research evidence and feedback from over 200 patient groups, stakeholder organisations and healthcare professionals. We encourage healthcare, education and food organisations to collaborate with people at risk of serious allergic reactions to tackle safety, anxiety and financial burdens for individuals and societies. Key priorities for prevention include awareness-raising campaigns for …

Machine Learning-Based Prediction Model For Icu Mortality After Continuous Renal Replacement Therapy Initiation In Children, Sameer Thadani, Tzu-Chun Wu, Danny T Y Wu, Aadil Kakajiwala, Danielle E Soranno, Gerard Cortina, Rachana Srivastava, Katja M Gist, Shina Menon, Worldwide Exploration Of Renal Replacement Outcomes Collaborative In Kidney Diseases (We-Rock) Collaborators

Faculty, Staff and Students Publications

BACKGROUND: Continuous renal replacement therapy (CRRT) is the favored renal replacement therapy in critically ill patients. Predicting clinical outcomes for CRRT patients is difficult due to population heterogeneity, varying clinical practices, and limited sample sizes.

OBJECTIVE: We aimed to predict survival to ICUs and hospital discharge in children and young adults receiving CRRT using machine learning (ML) techniques.

DERIVATION COHORT: Patients less than 25 years of age receiving CRRT for acute kidney injury and/or volume overload from 2015 to 2021 (80%).

VALIDATION COHORT: Internal validation occurred in a testing group of patients from the dataset (20%).

PREDICTION MODEL: Retrospective international …