Digital Commons Network^™

Real-World Data For Tisagenlecleucel In Patients With R/R B-All: Subgroup Analyses From The Cibmtr Registry., Samuel John, Kevin J. Curran, Erin Hall, Amy K. Keating, Susanne H C Baumeister, Sarah Nikiforow, Timothy Driscoll, Amy Moskop, Kevin O. Mcnerney, Christine L. Phillips, Michael A. Pulsipher, Emily M. Hsieh, Rayne H. Rouce, Marcelo C. Pasquini, Ranjan Tiwari, Jennifer Willert, Roberto Ramos, Joerg Krueger, Erin Guest, Stephan A. Grupp

Manuscripts, Articles, Book Chapters and Other Papers

Since the first approval of tisagenlecleucel in 2017, pediatric and young adult patients with relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL) may receive this CD19-directed chimeric antigen receptor T-cell therapy. We report real-world data from the Center for International Blood and Marrow Transplant Research (>2.5 years of follow-up). As of 4 May 2022, 768 patients with B-ALL had received tisagenlecleucel. Patients aged ≥18 and < 18 years of age (including those < 3 years) were treated during first relapse (26.6% and 26.7% [< 3 years, 44.8%], respectively) or primary refractory disease (12.4% and 12.1% [< 3 years, 15.5%], respectively) with 17.6% and 11.6% (< 3 years, 13.8%), respectively, having high disease burden (≥50% bone marrow [BM] blasts) and 20.2% and 20.2% (< 3 years, 13.8%), respectively, having low disease burden (>0 to < 5% BM blasts). Among patients with ≥12 months postinfusion follow-up (n = 578; median follow-up, 32.1 months), the best overall response of complete remission/complete remission with incomplete blood count recovery was 86.0%. The 12-month relapse-free survival (RFS) and overall survival (OS) were 61.8% and 79.4%, respectively, whereas the 24-month RFS and OS were 50.3% and 63.8%, respectively. Age (< 18 years) and disease burden (< 50% BM blasts) were associated with better outcomes. Previous inotuzumab therapy and KMT2A rearrangement were associated with worse outcomes. Older patients (≥18 years) experienced a higher rate of any-grade cytokine release syndrome (CRS) associated with higher disease burden before infusion. Any-grade CRS and neurotoxicity were lower in patients aged < 3 years. Extended follow-up continues to demonstrate high rates of RFS and favorable safety in this population.

How Does County Industry Mix Matter For Working-Age Mortality?, Xue Zhang, Iliya Gutin, Shannon M. Monnat, Jennifer Karas Montez

Population Health Research Brief Series

The types of industries that dominate employment in a county shape the health of the entire community, even for people who don't work in those sectors. This brief summarizes findings of a study that examined how five major employment sectors—agriculture, manufacturing, mining and construction, services, and professional services—were associated with overall county-level mortality rates and with mortality from drug overdoses, suicides, alcohol-related causes, and cardiometabolic disease among U.S. adults ages 25-64 from 2000 to 2022 Data are from the National Vital Statistics System and County Business Patterns. Findings show that the effects of local industries shift vary across time and …

Economic Growth In Mountain West Cities, 2019-2023, Anirudh Polagani, Isabelle G. Graham, Olivia K. Cheche, Kristian Thymianos, William E. Brown Jr.

Economic Development & Workforce

This fact sheet presents 2019-2023 data on economic growth indicators in 32 Mountain West cities across Arizona, Colorado, Nevada, New Mexico, and Utah. The CoworkingCafe report, “Rising Powerhouses: The Cities Making America’s Economic Future,” includes economic growth data for 269 cities across the United States. This fact sheet highlights data from select cities in each Mountain West state, categorized by population size: five large cities, eight mid-sized cities, and 19 small cities.

Unh Named To Princeton Review's Top 50 Green Colleges List, Unh Communications And Public Affairs

UNH Today Archive

No abstract provided.

Invisible Print? Reading Skill Predicts Children's Learning Of Novel Spoken Words, Taylor J. Bryant, Dawna Duff, Bethany Bell, Lisa Fitton, Suzanne M. Adlof

Faculty Publications

Research indicates that when literate children and adults hear a new word that they have never seen in print, they create an expectation for how the word may be spelled. However, studies have not yet examined the extent to which orthographic knowledge plays a role in children's spoken vocabulary learning when words are taught without print. The current study used structural equation modelling to examine the relation between children's word reading ability and their ability to learn novel words from spoken instruction. Children (N = 335; 7–9 years; 52% female; <  1% American Indian/Alaskan Native, 33% Black, 1% Multiracial, <  1% Native Hawaiian or Pacific Islander, 2% Other; 57% White; 6% did not report race; 2% Hispanic/Latino, 97% Not Hispanic/Latino; <  1% did not report ethnicity) completed norm-referenced language and reading assessments and experimental measures of spoken word learning. Word reading ability and vocabulary knowledge uniquely predicted spoken word learning with respective medium-small and medium-large effects after controlling for phonological memory, general language ability, and nonverbal cognition. Thus, orthographic skill has important effects on vocabulary learning, unaccounted for in previous research, that should be addressed in current theory and practice.

A New Scheme For Simple Asymmetric Bivariate Copulas And Applications, Rachid Bentoumi, Farid El Ktaibi, Christophe Chesneau

All Works

Bivariate copulas play a central role in modeling the dependence structure between two random variables and serve as a fundamental tool in various applied fields. In this article, we develop a new theoretical framework aimed at constructing simple asymmetric bivariate copulas of the form C(u, v) = uv [ϕ(v) + u(1 − ϕ(v))^], (u, v) ∈ [0, 1]². This framework relies on a tuning univariate function to achieve the desired asymmetry. We study this pioneering scheme, emphasizing its theoretical foundations, and illustrating it with several examples. More precisely, we establish important properties of the proposed copulas …

Center For Participatory Research Leads National Efforts In Community-Based Research, Dustin Roberto

HSC Newsroom

Nina Wallerstein, DrPH, is a Distinguished Professor of Public Health and director of the Center for Participatory Research at the University of New Mexico. She has spent more than four decades shifting health research toward community-based participatory research (CBPR). Her work emphasizes partnerships in which communities guide research priorities and retain ownership of findings.The center's work spans Indigenous health, including culturally centered family programs, CBPR, youth participatory action research and co-learning initiatives.

Understanding Film Tax Credits In Nevada And Nationally, Michael J. Brown, David F. Damore, William E. Brown Jr.

Policy Briefs and Reports

This policy primer provides an overview of Nevada’s transferable tax credit program for film and other productions and reviews articles, reports, audits, and studies of film tax credits as a tool for economic development in the United States. This review considers a significant body of work analyzing the use of film tax credits in support of economic development. Studies and state audits often show that because film tax credits do not create the number and quality of full-time jobs necessary to merit their costs and do little to stimulate other related industries, they are a poor financial choice for state …

Face Recognition Using Optimized Multi-Task Cascaded Cnn In Artificial Intelligence Systems, Sami Abduljabbar Rashid, Mustafa Maad Hamdi, Salah Ayad Jassim, Lukman Audah, Baraa Saad Abdulhakeem, Mohammed Salah Abood, Ahmed Adil Nafea

Baghdad Science Journal

Improving the accuracy level of face recognition system is still an open research area where it consists of certain limitations to attain maximum accuracy. In earlier days, several algorithms are developed using machine learning and deep learning models, but still, they need improvement in terms of accuracy. For that purpose, in this article a novel CNN model called the optimized multi cascaded CNN (OPT-MTC-CNN) in the artificial intelligence system is developed, which helps to overcome the accuracy issues in face recognition system. The algorithms that are incorporated in this model are Fully Convolutional Network (FCN), Convolutional Neural Network (CNN), and …

Microplastic Pollution In Marine Ecosystems: Sources, Impacts, Andstakeholder-Based Solutions, Seren Acarer Arat

Turkish Journal of Biology

Microplastics (MPs) are plastic particles of anthropogenic origin with a size range of 1–5000 μm. Marine MP pollution is increasingly recognized as a significant global environmental challenge. MPs, which enter marine ecosystems from land- and marine-based sources, pose physical, chemical, and biological risks due to the adsorption of various pollutants and the formation of biofilm layers. MPs are found in various organisms from lower to higher trophic levels of the marine food web. The negative effects of MPs on marine organisms depend on their abundance, their characteristics, and the exposure time of organisms to MPs. MPs can adversely affect various …

Application Of Biological And Green Nanomaterials In Wastewater Treatment: Techniques For The Effective Removal Of Dyes, Heavy Metals, And Organic Pollutants, Emi̇ne Sena Kazan Kaya, Zeynep Ci̇ğeroğlu, Tansel Kemerli̇ Kalbaran, Başak Temur Ergan, Zeynep Mi̇ne Şenol, Meral Yildirim Yalçin

Turkish Journal of Biology

Background/aim: Wastewater from industrial, agricultural, and residential sources poses significant environmental and public health risks due to the presence of dyes, heavy metals, and organic pollutants. Conventional treatment methods are often inadequate for the complete removal of these pollutants. Therefore, the development of sustainable, environmentally friendly, and highly efficient treatment techniques has become increasingly important. The aim of this review is to evaluate the application of biological and green nanomaterials in wastewater treatment and to compare their effectiveness against different types of pollutants (dyes, heavy metals, and organics).

Materials and methods: This review provides detailed information on the removal of …

A Review Of Deep Learning Architectures For Plant Disease Detection​, Yasi̇n Kaya, Ercan Gürsoy

Turkish Journal of Biology

Background/aim: The rapid advancement of deep learning (DL) has revolutionized plant disease detection by enabling highly accurate, image-based diagnostic solutions. This review provides a comprehensive synthesis of DL-based methodologies for plant disease detection, systematically structured around the key stages of the modeling pipeline, encompassing data acquisition, preprocessing, augmentation, classification, detection, segmentation, and deployment.

Materials and methods: The review focuses on evaluating convolutional neural network (CNN) architectures such as VGG, ResNet, EfficientNet, and DenseNet across diverse experimental contexts. Classification strategies are categorized according to their integration of visualization techniques (e.g., saliency maps, Grad-CAM) to enhance model interpretability, emphasizing the pivotal role …

Green Carbon Dots In The Era Of Ai: Sustainable Synthesis, Intelligent Drug Delivery, Advanced Diagnostics, And Bioimaging, Emi̇ne Sezer, Fulden Ulucan Karnak, Si̇nan Akgöl

Turkish Journal of Biology

Background/aim: Green carbon dots (GCDs) are a rapidly developing class of nanomaterials that are revolutionizing various scientific disciplines due to their unique optical properties, low toxicity, and sustainable synthesis. This review offers a comprehensive roadmap for the field, emphasizing the synergy between GCDs and artificial intelligence (AI).

Materials and methods: We begin by detailing the sustainable synthesis of GCDs, highlighting green chemistry principles and the transformative role of AI in optimizing their production. Subsequently, we explore the critical characterization of GCDs, including their structural, optical, and biocompatibility assessment. The core of this study explores the diverse biomedical applications of GCDs, …

Applications Of Transfer Learning In Sunflower Disease Detection: Advances, Challenges, And Future Directions, Yonis Gulzar

Turkish Journal of Biology

Background/aim: Sunflower (Helianthus annuus) is a crop of high economic and nutritional importance that continues to suffer significant yield losses due to foliar diseases. Traditional image-based and laboratory detection techniques remain limited by subjectivity, cost, and scalability. Transfer learning (TL) has recently emerged as an effective approach to overcoming these challenges involving the reuse of pretrained deep models for plant pathology tasks. Presented here is a systematic examination of recent TL-based studies on sunflower disease classification to identify prevailing trends, research gaps, and future opportunities.

Materials and methods: A structured Scopus query was employed to retrieve peer-reviewed articles published between …

Flavonoids And Phenolic Compounds: A Promising Avenue For Neurodegenerative Disease Therapy, Tesli̇me Özge Şahi̇n, Özge Cemali̇, Merve Özdemi̇r, Şeri̇fe Ayten, Duygu Ağagündüz

Turkish Journal of Biology

Background/aim: Neurodegenerative diseases such as Alzheimer’s, Parkinson’s, Huntington’s, and ALS are characterized by a progressive loss of nerve cells, for which no definitive cure currently exists. These conditions share common pathological mechanisms, including chronic neuroinflammation, oxidative stress, protein aggregation, and mitochondrial dysfunction. Flavonoids and other plant-derived phenolic compounds have recently attracted attention for the treatment of such conditions due to their antiinflammatory and antioxidant properties. This review explores the neuroprotective mechanisms of flavonoids and evaluates their potential for the prevention and treatment of neurodegenerative diseases.

Materials and methods: A literature search of the Web of Science, PubMed, and ScienceDirect databases …

Hsa_Circ_0001776 Regulates The Progression Of Acute Myeloid Leukemia Through The Mir-1269b/Pten Axis, Yaoyao Wang, Xiancong Yang, Simin Rong, Xiaoxu Lan, Chenhui Ti, Weimiao Sun, Baohui Yin, Youjie Li, Yunxiao Sun

Turkish Journal of Biology

Background/aim: Acute myeloid leukemia (AML) is a malignant neoplasm arising from bone marrow hematopoietic stem cells. It is a common subtype of childhood leukemia and remains challenging to cure. Emerging evidence suggests that circular RNAs (circRNAs), a class of noncoding RNAs, play key regulatory roles in tumor biology. Among their various functions, circRNAs often act as ‘sponges’ for microRNAs (miRNAs), modulating gene expression posttranscriptionally. This study investigates the functional role and clinical relevance of hsa_circ_0001776 in AML.

Materials and methods: Three AML cell lines and 22 peripheral blood samples were analyzed. Differential expression analysis of circRNAs in a GSE dataset …

The Effects Of The Combined Use Of Carbon Quantum Dots And Antibacterial Agents On Pathogenic Bacteria, Derya Doğanay, İbrahi̇m Serkan Avşar, Şevval Maral Özcan Aykol, Gamze Çamlik, Besa Bi̇lakaya, İsmai̇l Tuncer Deği̇m

Turkish Journal of Biology

Background/aim: This study evaluates the challenges associated with overcoming antimicrobial resistance and innovative approaches to combat multidrug-resistant (MDR) bacterial infections.

Materials and methods: Novel codoped carbon quantum dots (CCQDs) were synthesized using citric acid as the carbon source and L-cysteine as the nitrogen codoping atom. The formulation in which citric acid was retained was designated as CCQDs-1, whereas the purified version, from which citric acid was removed, was termed CCQDs-2. The antibacterial properties of CCQDs-1 and CCQDs-2 were compared using the agar well diffusion method. This study comprehensively characterizes these nanomaterials and evaluates their antibacterial potential, both alone and in …

Exploring Definitions And Frameworks Of Information Diplomacy: A Scoping Review Protocol, Bethany S. Mcgowan, Tuomas Harviainen

Libraries Faculty and Staff Scholarship and Research

Information diplomacy is an emerging concept that bridges information science, public diplomacy, and global communication. Although increasingly cited in scholarly and policy discourse, the term lacks definitional clarity and theoretical consensus. A systematic mapping of its explicit usage across disciplines is needed to support conceptual coherence and guide future applications.

This scoping review aims to identify, analyze, and synthesize existing definitions, frameworks, and applications of the term information diplomacy in scholarly and gray literature. The review will explore how the concept has been articulated across domains such as international relations, information policy, and communication, focusing exclusively on sources that explicitly …

Migration And U.S. Labor Market Effects Of The Mexican Drug War, Mark Borgschulte, Yuci Chen, Eduardo Medina-Cortina

Upjohn Institute Working Papers

We estimate the effect of the Mexican drug war on Mexico-to-U.S. migration and the resulting effects on population, employment, and wages in U.S. labor markets. Our empirical strategy compares U.S. counties differentially connected to Mexican municipalities through historical migration networks, using drug violence triggered by close municipal elections in 2007–2008 as a source of exogenous variation. Over the following decade, migrants fleeing the violence—the vast majority of whom are undocumented—cause native-born U.S. workers’ employment rates to increase and unemployment rates to fall, while wages do not change. Employment gains are largest for natives without a college degree. Employment effects fade …

Dramatic Biases In Terrestrial Nitrogen Fixation In Earth System Models Revealed By Natural Isotope Signatures, Maoyuan Fang, Shushi Peng, Philippe Ciais, Daniel S. Goll, Benjamin Z. Houlton, Ying-Ping Wang, Yilong Wang, Pan Liu, Joshua B. Fisher, Pierre Regnier

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Biological nitrogen fixation (BNF) is the primary input of new reactive nitrogen to natural terrestrial ecosystems. However, this flux is poorly constrained due to its unclear drivers and associated control mechanisms. Here, we extend the existing theory of nitrogen (N) isotope mass balance to estimate BNF rates and then use a Bayesian approach to constrain the BNF rates in natural terrestrial ecosystems by using measurements of natural N-isotope ratios (δ¹⁵N) in plants (δ_P) and soil (δ_S). Together with pairwise δ_P and δ_S measurements from 18 forest sites covering diverse climates and thousands …

Faculty Senate Executive Committee Minutes (10/28/2025), Csusb Faculty Senate

CSUSB Faculty Senate records

No abstract provided.

Complexity Measures For Self-Similar And Chemical Graphs Using Entropies And Generalized Fractal Dimensions, J. Bhuvaneswari, D. Easwaramoorthy

Baghdad Science Journal

Nonlinear analysis finds numerous applications in understanding the intricate characteristics of generalized Sierpinski graphs or chemical graphs. It aids in discerning the fractal patterns inherent in self-similar structures, deciphering the dynamic interactions within chemical bonds, and assessing the complexity of molecular arrangements. Furthermore, it plays a crucial role in unraveling the emergent behaviors of complex systems, offering insights applicable to diverse fields such as materials science, chemistry, biology, network theory, and beyond. In this paper, the complexity of generalized Sierpinski graphs and chemical graphs is analyzed using fractal-based nonlinear measures computed iteratively. Nonlinear measures assess intricate relationships within graphs by …

Lung Cancer Classification With High Accuracy Based On Enhanced K- Nearest Neighbor Algorithm, Ahmed Subhi Abdalkafor, Ali Azawii Abdul Lateef

Baghdad Science Journal

Lung diseases have newly increased, with lung cancer being the most serious, as a result of the widespread use of electronic cigarettes and the high demand for them among youth. Misdiagnosis of this disease has resulted in a high death rate around the world, which further complicates matters. So the researchers have tended to concentrate on and study this illness. After extracting the crucial characteristics for this cancer's classification, several studies implemented multiple artificial intelligence algorithms with different techniques, nonetheless, the primary difference between those studies persisted in the classification accuracy. In this paper, after selecting the methods of pre-processing …

Helping Families Thrive: The Impact Of A Health-Focused Parent Training On Family Outcomes, Mary Capili M.S.

Clinical Psychology Dissertations

Behavioral parent training (BPT) is a well-established intervention for children with ADHD and has been shown to reduce challenging behaviors in children and decrease caregiver stress. The Lifestyle Enhancement for ADHD Study (LEAP) is the only physical activity intervention that includes children with ADHD and their parents. To examine the relationships between child physical activity, caregiver physical activity, ADHD outcomes, and positive parenting. I hypothesized that H₁) caregiver physical activity will amplify the effect of child physical activity on reducing child ADHD symptoms, and H₂) caregiver strain will mediate the relationship caregiver physical activity and positive …

Adherence To Integrative Care, Oncology Healthcare Utilization, Opioid Use And Hospitalization, Eran Ben-Arye, Dan Greenberg, Noah Samuels, Ana Maria Lopez, Tzahit Simon-Tuval

Kimmel Cancer Center Faculty Papers

Research on the relationship between integrative oncology (IO) programs and dispensing of chemotherapy agents and supportive care drugs, and hospitalization rates is limited. The present study examined these outcomes in chemotherapy-treated patients with cancer, comparing patients highly adherent to integrative care (high-AIC) to those with low adherence (low-AIC). Data from patients with cancer treated with taxane and/or platinum-based agents participating in an ongoing prospective, controlled pragmatic trial were examined retrospectively. Patients were referred to an IO consultation and weekly treatments at 3 medical centers in Northern Israel, with high-AIC defined as attending ≥4 sessions at 6 weeks; low-AIC, 0-3 sessions. …

What Drives Advanced Practice Nurses To Stay In Rural America? Insights From The 2022 National Survey Of Registered Nurses, Esita Patel, Chris Gillette, Jan Ostermann Phd, Chris Everett, Dawn Caviness, Sarah Garvick

Faculty Publications

Purpose: Recruiting and retaining a robust rural health care workforce is critical to advancing health outcomes in rural communities. Although increasing the rural provider workforce has been a policy focus for decades, rural access continues to worsen. Using a strengths-based approach, we identify factors that influence the decisions of advanced practice registered nurses (APRNs) to leave or stay in their jobs.

Methods: Secondary analysis of data from the 2022 National Sample Survey of Registered Nurses. We describe rates of turnover, retention, intention to leave, and reasons for leaving and staying by job rurality. We compare reasons by rurality using Pearson …

A Deep Learning Approach: The Impact Of Sentiment Analysis Of Bangladeshi Workers Over The World, Md Raihanul Islam Tomal, Tanveer Kader, Kohbalan Moorthy, Mazlina Abdul Majid

Baghdad Science Journal

In today's globalized world, the pursuit of better opportunities has led to a significant increase in immigration and foreign labor. This trend is particularly evident in Bangladesh, where many workers migrate annually to destinations such as Malaysia, Qatar, Saudi Arabia, and the UAE. Understanding the sentiments and emotions of these workers is crucial to preventing crimes, suicides, political unrest, and other security issues in host countries. As maximum workers usually come from rural Bangladeshi communicate they use local dialect for conversations and very popular widely used local dialect known as Pabnaia. This study did not identify any prior research specifically …

Academic Senate - Agenda, 10/28/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

Revisiting The 64th: Assessing And Updating A Historical Collection With New Technologies, Elizabeth H. Holt

Library Faculty Publications

Background: In November 1940, the LSU Medical Center organized the 64th US Army General Hospital to serve in the Mediterranean from 1943 to 1945. In the 1970s, members of the unit donated approximately 3000 items to a faculty member, who then donated that collection to the LSU Health Libraries; it comprises photographs, newsletters, Army reports, interviews, and correspondences. In 2011, the Libraries faculty & staff undertook digitizing and describing the collection. In 2025, given the advances made in technology since the original project, it was decided to reassess both the physical and digital versions of the collection.

Description: This presentation …

Perioperative Benefits Of Dexmedetomidine As An Antiarrhythmic Agent In Noncardiac Surgical Patients: A Case Report, Sara Jaison, Kusuma Halemani

Sultan Qaboos University Medical Journal

Dexmedetomidine (DEX), a selective α2-adrenergic receptor agonist, has gained recognition for its sedative, anxiolytic, and sympatholytic properties, making it a valuable perioperative agent. This report describes the anaesthetic management of an elderly 75-year-old male patient with septic shock, multi-organ dysfunction, delirium and significant ventricular arrhythmias who presented in 2025 to a tertiary care teaching hospital in Oman and was scheduled for an emergency below-knee amputation. DEX was utilised for intraoperative sedation and its antiarrhythmic effects. Traditional sedatives often exacerbate delirium or pose cardiorespiratory risks; however, DEX provides effective sedation while preserving respiratory function and promoting haemodynamic stability. Notably, its …