Biomedical Informatics Commons^™

Large Language Models For Healthcare Data Augmentation: An Example On Patient-Trial Matching, Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, Xia Hu

Faculty, Staff and Student Publications

The process of matching patients with suitable clinical trials is essential for advancing medical research and providing optimal care. However, current approaches face challenges such as data standardization, ethical considerations, and a lack of interoperability between Electronic Health Records (EHRs) and clinical trial criteria. In this paper, we explore the potential of large language models (LLMs) to address these challenges by leveraging their advanced natural language generation capabilities to improve compatibility between EHRs and clinical trial descriptions. We propose an innovative privacy-aware data augmentation approach for LLM-based patient-trial matching (LLM-PTM), which balances the benefits of LLMs while ensuring the security …

Split Learning For Distributed Collaborative Training Of Deep Learning Models In Health Informatics, Zhuohang Li, Chao Yan, Xinmeng Zhang, Gharib Gharibi, Zhijun Yin, Xiaoqian Jiang, Bradley A Malin

Faculty, Staff and Student Publications

Deep learning continues to rapidly evolve and is now demonstrating remarkable potential for numerous medical prediction tasks. However, realizing deep learning models that generalize across healthcare organizations is challenging. This is due, in part, to the inherent siloed nature of these organizations and patient privacy requirements. To address this problem, we illustrate how split learning can enable collaborative training of deep learning models across disparate and privately maintained health datasets, while keeping the original records and model parameters private. We introduce a new privacy-preserving distributed learning framework that offers a higher level of privacy compared to conventional federated learning. We …

Local Contrastive Learning For Medical Image Recognition, Syed A Rizvi, Ruixiang Tang, Xiaoqian Jiang, Xiaotian Ma, Xia Hu

Faculty, Staff and Student Publications

The proliferation of Deep Learning (DL)-based methods for radiographic image analysis has created a great demand for expert-labeled radiology data. Recent self-supervised frameworks have alleviated the need for expert labeling by obtaining supervision from associated radiology reports. These frameworks, however, struggle to distinguish the subtle differences between different pathologies in medical images. Additionally, many of them do not provide interpretation between image regions and text, making it difficult for radiologists to assess model predictions. In this work, we propose Local Region Contrastive Learning (LRCLR), a flexible fine-tuning framework that adds layers for significant image region selection as well as cross-modality …

Immune Checkpoint Inhibitors In Advanced Cutaneous Squamous Cell Carcinoma: A Systemic Review And Meta-Analysis, Haoran Zhang, Ai Zhong, Junjie Chen

Faculty, Staff and Student Publications

BACKGROUND: To evaluate the immune checkpoint inhibitors (CPI) for the treatment of patients with advanced cutaneous squamous cell carcinoma (CSCC).

MATERIALS AND METHODS: A meta-analysis was conducted, and the efficacy and safety of CPI were assessed.

RESULTS: A total of 13 studies with 980 patients were included. The pooled objective response rate (ORR) and disease control rate were 47.2% and 64.4%, separately. In addition, patients with primary tumor located in head and neck (odds ratio [OR]: 0.374, 95% confidence interval [CI]: 0.219-0.640, p < 0.001) and positive expression of programmed death ligand 1 (OR: 0.364, 95% CI: 0.158-0.842, P = 0.018) had superior ORR during CPI treatment. The incidence of progression free survival at 6 and 12 months was 59.3% and 52.8%, and 80.6% and 76.4% for overall survival. As for safety, the overall incidence of adverse events with all grades and 3-4 grade was 76.9% and 20.2%.

CONCLUSIONS: Our systematic review confirmed the satisfying efficacy and acceptable toxicity of CPI for advanced CSCC.

Text Classification Of Cancer Clinical Trial Eligibility Criteria, Yumeng Yang, Soumya Jayaraj, Ethan Ludmir, Kirk Roberts

Faculty, Staff and Student Publications

Automatic identification of clinical trials for which a patient is eligible is complicated by the fact that trial eligibility are stated in natural language. A potential solution to this problem is to employ text classification methods for common types of eligibility criteria. In this study, we focus on seven common exclusion criteria in cancer trials: prior malignancy, human immunodeficiency virus, hepatitis B, hepatitis C, psychiatric illness, drug/substance abuse, and autoimmune illness. Our dataset consists of 764 phase III cancer trials with these exclusions annotated at the trial level. We experiment with common transformer models as well as a new pre-trained …

Optimization Of Mesh Generation For Geometric Accuracy, Robustness, And Efficiency Of Biomechanical-Model-Based Deformable Image Registration, Yulun He, Brian M Anderson, Guillaume Cazoulat, Bastien Rigaud, Lusmeralis Almodovar-Abreu, Julianne Pollard-Larkin, Peter Balter, Zhongxing Liao, Radhe Mohan, Bruno Odisio, Stina Svensson, Kristy K Brock

Faculty, Staff and Student Publications

BACKGROUND: Successful generation of biomechanical-model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor-intensive and hinder DIR efficiency and clinical workflow.

PURPOSE: To identify optimal parameters in surface mesh generation as boundary conditions for a BM-DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes.

METHODS: Contrast-enhanced CT images of 29 colorectal liver cancer patients and end-exhale four-dimensional CT images of 26 locally advanced non-small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality …

Transiently Impaired Endothelial Function During Thyroid Hormone Withdrawal In Differentiated Thyroid Cancer Patients, Li-Ying Hou, Xiao Li, Guo-Qiang Zhang, Chuang Xi, Chen-Tian Shen, Hong-Jun Song, Wen-Kun Bai, Zhong-Ling Qiu, Quan-Yong Luo

Faculty, Staff and Student Publications

PURPOSE: Endothelial dysfunction, which was associated with chronic hypothyroidism, was an early event in atherosclerosis. Whether short-term hypothyroidism following thyroxine withdrawal during radioiodine (RAI) therapy was associated with endothelial dysfunction in patients with differentiated thyroid cancer (DTC) was unclear. Aim of the study was to assess whether short-term hypothyroidism could impair endothelial function and the accompanied metabolic changes in the whole process of RAI therapy.

METHODS: We recruited fifty-one patients who underwent total thyroidectomy surgery and would accept RAI therapy for DTC. We analyzed thyroid function, endothelial function and serum lipids levels of the patients at three time points: the …

Extreme Temperatures And Sickness Absence In The Mediterranean Province Of Barcelona: An Occupational Health Issue, Mireia Utzet, Amaya Ayala-Garcia, Fernando G Benavides, Xavier Basagaña

Faculty, Staff and Student Publications

OBJECTIVES: This study aims to assess the association between daily temperature and sickness absence episodes in the Mediterranean province of Barcelona between 2012 and 2015, according to sociodemographic and occupational characteristics.

METHODS: Ecological study of a sample of salaried workers affiliated to the Spanish social security, resident in Barcelona province between 2012 and 2015. The association between daily mean temperature and risk of new sickness absence episodes was estimated with distributed lag non-linear models. The lag effect up to 1 week was considered. Analyses were repeated separately by sex, age groups, occupational category, economic sector and medical diagnosis groups of …

Workplace Aggression Against Healthcare Workers In A Spanish Healthcare Institution Between 2019 And 2021: The Impact Of The Covid-19 Pandemic, Aitor Díaz, Mireia Utzet, Joan Mirabent, Pilar Diaz, Jose Maria Ramada, Consol Serra, Fernando G Benavides

Faculty, Staff and Student Publications

OBJECTIVES: Describe the incidence of first aggressions among healthcare workers (HCWs) before and during the COVID-19 pandemic in a Spanish healthcare institution, according to workers' socio-occupational characteristics and analyze the impact of the pandemic on it.

METHODS: A cohort involving HCWs who worked in the institution for at least 1 week each year from 1 January 2019 to 31 December 2021. Adjusted relative risks (aRR) were estimated using generalized estimating equations and negative binomial models to calculate the differences in WPA between the different time periods. All analyses were stratified by gender.

RESULTS: Among women, the incidence was 6.8% (6.0; …

Anti-Inflammatory Effects Of Vagus Nerve Stimulation In Pediatric Patients With Epilepsy, Supender Kaur, Nathan R Selden, Alejandro Aballay

Faculty, Staff and Student Publications

INTRODUCTION: The neural control of the immune system by the nervous system is critical to maintaining immune homeostasis, whose disruption may be an underlying cause of several diseases, including cancer, multiple sclerosis, rheumatoid arthritis, and Alzheimer's disease.

METHODS: Here we studied the role of vagus nerve stimulation (VNS) on gene expression in peripheral blood mononuclear cells (PBMCs). Vagus nerve stimulation is widely used as an alternative treatment for drug-resistant epilepsy. Thus, we studied the impact that VNS treatment has on PBMCs isolated from a cohort of existing patients with medically refractory epilepsy. A comparison of genome-wide changes in gene expression …

A Gcn-Based Approach To Uncover Misaligned Synonymous Terms In The Umls Metathesaurus, Xubing Hao, Rashmie Abeysinghe, Jay Shi, Licong Cui

Faculty, Staff and Student Publications

The Unified Medical Language System (UMLS), a large repository of biomedical vocabularies, has been used for supporting various biomedical applications. Ensuring the quality of the UMLS is critical to maintain both the accuracy of its content and the reliability of downstream applications. In this work, we present a Graph Convolutional Network (GCN)-based approach to identify misaligned synonymous terms organized under different UMLS concepts. We used synonymous terms grouped under the same concept as positive samples and top lexically similar terms as negative samples to train the GCN model. We applied the model to a test set and suggested those negative …

Digital Solutions Observed In Clinical Trials: A Formative Feasibility Scoping Review, Taylor M Harrison, Sungrim Moon, Liwei Wang, Sunyang Fu, Hongfang Liu

Faculty, Staff and Student Publications

Growing digital access accelerates digital transformation of clinical trials where digital solutions (DSs) are increasingly and widely leveraged for improving trial efficiency, effectiveness, and accessibility. Many factors impact DS success including technology barriers, privacy concerns, or user engagement activities. It is unclear how those factors are considered or reported in the literature. Here, we perform a formative feasibility scoping review to identify gaps impacting DS quality and reproducibility in trials. Articles containing digital terms published in English from 2009 to 2022 were collected (n=4,167). 130 articles published between 2016 and 2022 were randomly selected for full-text review. Eligible articles (n=100) …

Contextual Variation Of Clinical Notes Induced By Ehr Migration, Kurt Miller, Sungrim Moon, Sunyang Fu, Hongfang Liu

Faculty, Staff and Student Publications

The structure and semantics of clinical notes vary considerably across different Electronic Health Record (EHR) systems, sites, and institutions. Such heterogeneity hampers the portability of natural language processing (NLP) models in extracting information from the text for clinical research or practice. In this study, we evaluate the contextual variation of clinical notes by measuring the semantic and syntactic similarity of the notes of two sets of physicians comprising four medical specialties across EHR migrations at two Mayo Clinic sites. We find significant semantic and syntactic variation imposed by the context of the EHR system and between medical specialties whereas only …

Oncology-Specific Radiation Dose And Image Noise Reference Levels In Adult Abdominal-Pelvic Ct, Moiz Ahmad, Xinming Liu, Ajaykumar C Morani, Dhakshinamoorthy Ganeshan, Marcus R Anderson, Ehsan Samei, Corey T Jensen

Faculty, Staff and Student Publications

OBJECTIVES: To provide our oncology-specific adult abdominal-pelvic CT reference levels for image noise and radiation dose from a high-volume, oncologic, tertiary referral center.

METHODS: The portal venous phase abdomen-pelvis acquisition was assessed for image noise and radiation dose in 13,320 contrast-enhanced CT examinations. Patient size (effective diameter) and radiation dose (CTDI

RESULTS: The noise reference level was 11.25 HU with a reference range of 10.25-12.25 HU. The dose reference level at a median effective diameter of 30.7 cm was 26.7 mGy with a reference range of 19.6-37.0 mGy. Dose increased with patient size; however, image noise remained approximately constant within …

Characterizing Performance Gaps Of A Code-Based Dementia Algorithm In A Population-Based Cohort Of Cognitive Aging, Maria Vassilaki, Sunyang Fu, Luke R Christenson, Muskan Garg, Ronald C Petersen, Jennifer St Sauver, Sunghwan Sohn

Faculty, Staff and Student Publications

BACKGROUND: Multiple algorithms with variable performance have been developed to identify dementia using combinations of billing codes and medication data that are widely available from electronic health records (EHR). If the characteristics of misclassified patients are clearly identified, modifying existing algorithms to improve performance may be possible.

OBJECTIVE: To examine the performance of a code-based algorithm to identify dementia cases in the population-based Mayo Clinic Study of Aging (MCSA) where dementia diagnosis (i.e., reference standard) is actively assessed through routine follow-up and describe the characteristics of persons incorrectly categorized.

METHODS: There were 5,316 participants (age at baseline (mean (SD)): 73.3 …

Segmentation Of Acute Stroke Infarct Core Using Image-Level Labels On Ct-Angiography, Luca Giancardo, Arash Niktabe, Laura Ocasio, Rania Abdelkhaleq, Sergio Salazar-Marioni, Sunil A Sheth

Faculty, Staff and Student Publications

Acute ischemic stroke is a leading cause of death and disability in the world. Treatment decisions, especially around emergent revascularization procedures, rely heavily on size and location of the infarct core. Currently, accurate assessment of this measure is challenging. While MRI-DWI is considered the gold standard, its availability is limited for most patients suffering from stroke. Another well-studied imaging modality is CT-Perfusion (CTP) which is much more common than MRI-DWI in acute stroke care, but not as precise as MRI-DWI, and it is still unavailable in many stroke hospitals. A method to determine infarct core using CT-Angiography (CTA), a much …

Keystroke-Dynamics For Parkinson's Disease Signs Detection In An At-Home Uncontrolled Population: A New Benchmark And Method, Shikha Tripathi, Teresa Arroyo-Gallego, Luca Giancardo

Faculty, Staff and Student Publications

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease disorder in the world. A prompt diagnosis would enable clinical trials for disease-modifying neuroprotective therapies. Recent research efforts have unveiled imaging and blood markers that have the potential to be used to identify PD patients promptly, however, the idiopathic nature of PD makes these tests very hard to scale to the general population. To this end, we need an easily deployable tool that would enable screening for PD signs in the general population. In this work, we propose a new set of features based on keystroke dynamics, i.e., the time …

Annotation And Information Extraction Of Consumer-Friendly Health Articles For Enhancing Laboratory Test Reporting, Zhe He, Shubo Tian, Arslan Erdengasileng, Karim Hanna, Yang Gong, Zhan Zhang, Xiao Luo, Mia Liza A Lustria

Faculty, Staff and Student Publications

Viewing laboratory test results is patients' most frequent activity when accessing patient portals, but lab results can be very confusing for patients. Previous research has explored various ways to present lab results, but few have attempted to provide tailored information support based on individual patient's medical context. In this study, we collected and annotated interpretations of textual lab result in 251 health articles about laboratory tests from AHealthyMe.com. Then we evaluated transformer-based language models including BioBERT, ClinicalBERT, RoBERTa, and PubMedBERT for recognizing key terms and their types. Using BioPortal's term search API, we mapped the annotated terms to concepts in …

The Current Status And Future Prospects For Conversion Therapy In The Treatment Of Hepatocellular Carcinoma, Jinfeng Bai, Ming Huang, Bohan Song, Wei Luo, Rong Ding

Faculty, Staff and Student Publications

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths worldwide. In China, most HCC patients are diagnosed with advanced disease and in these cases surgery is challenging. Conversion therapy can be used to change unresectable HCC into resectable disease and is a potential breakthrough treatment strategy. The resection rate for unresectable advanced HCC has recently improved as a growing number of patients have benefited from conversion therapy. While conversion therapy is at an early stage of development, progress in patient selection, optimum treatment methods, and the timing of surgery have the potential to deliver significant benefits. In …

The Health-Promoting Effects And The Mechanism Of Intermittent Fasting, Simin Liu, Min Zeng, Weixi Wan, Ming Huang, Xiang Li, Zixian Xie, Shang Wang, Yu Cai

Faculty, Staff and Student Publications

Intermittent fasting (IF) is an eating pattern in which individuals go extended periods with little or no energy intake after consuming regular food in intervening periods. IF has several health-promoting effects. It can effectively reduce weight, fasting insulin levels, and blood glucose levels. It can also increase the antitumor activity of medicines and cause improvement in the case of neurological diseases, such as memory deficit, to achieve enhanced metabolic function and prolonged longevity. Additionally, IF activates several biological pathways to induce autophagy, encourages cell renewal, prevents cancer cells from multiplying and spreading, and delays senescence. However, IF has specific adverse …

Emulate Randomized Clinical Trials Using Heterogeneous Treatment Effect Estimation For Personalized Treatments: Methodology Review And Benchmark, Yaobin Ling, Pulakesh Upadhyaya, Luyao Chen, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Big data and (deep) machine learning have been ambitious tools in digital medicine, but these tools focus mainly on association. Intervention in medicine is about the causal effects. The average treatment effect has long been studied as a measure of causal effect, assuming that all populations have the same effect size. However, no "one-size-fits-all" treatment seems to work in some complex diseases. Treatment effects may vary by patient. Estimating heterogeneous treatment effects (HTE) may have a high impact on developing personalized treatment. Lots of advanced machine learning models for estimating HTE have emerged in recent years, but there has been …

Advances In The Management Of Spinal Metastases: What The Radiologist Needs To Know, Sarah M Bahouth, Debra N Yeboa, Amol J Ghia, Claudio E Tatsui, Christopher A Alvarez-Breckenridge, Thomas H Beckham, Andrew J Bishop, Jing Li, Mary Frances Mcaleer, Robert Y North, Laurence D Rhines, Todd A Swanson, Wang Chenyang, Behrang Amini

Faculty, Staff and Student Publications

Spine is the most frequently involved site of osseous metastases. With improved disease-specific survival in patients with Stage IV cancer, durability of local disease control has become an important goal for treatment of spinal metastases. Herein, we review the multidisciplinary management of spine metastases, including conventional external beam radiation therapy, spine stereotactic radiosurgery, and minimally invasive and open surgical treatment options. We also present a simplified framework for management of spinal metastases used at The University of Texas MD Anderson Cancer Center, focusing on the important decision points where the radiologist can contribute.

Clinical Parameters Affecting Survival Outcomes In Patients With Low-Grade Serous Ovarian Carcinoma: An International Multicentre Analysis, Taymaa May, Marcus Bernardini, Stephanie Lheureux, Katja K H Aben, Elisa V Bandera, Matthias W Beckmann, Javier Benitez, Andrew Berchuck, Line Bjørge, Michael E Carney, Daniel W Cramer, Anna Defazio, Thilo Dörk, Diana M Eccles, Michael Friedlander, María Jose García, Ellen L Goode, Alexander Hein, Claus K Høgdall, Allan Jensen, Sharon Johnatty, Catherine J Kennedy, Lambertus A Kiemeney, Susanne K Kjær, Jolanta Kupryjańczyk, Keitaro Matsuo, Valerie Mcguire, Francesmary Modugno, Lisa E Paddock, Tanja Pejovic, Catherine M Phelan, Marjorie J Riggan, Cristina Rodriguez-Antona, Joseph H Rothstein, Weiva Sieh, Honglin Song, Kathryn L Terry, Anne M Van Altena, Adriaan Vanderstichele, Ignace Vergote, Liv Cecilie Vestrheim Thomsen, Penelope M Webb, Nicolas Wentzensen, Lynne R Wilkens, Argyrios Ziogas, Haiyan Jiang, Alicia Tone, Ovarian Cancer Association And The Australian Ovarian Cancer Study Group

Faculty, Staff and Student Publications

BACKGROUND: Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC.

METHODS: We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves.

RESULTS: Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of …

Selinexor In Combination With Weekly Paclitaxel In Patients With Metastatic Solid Tumors: Results Of An Open Label, Single-Center, Multi-Arm Phase 1b Study With Expansion Phase In Ovarian Cancer, Shannon N Westin, Siqing Fu, Apostolia Tsimberidou, Sarina Piha-Paul, Fechukwu Akhmedzhanov, Bulent Yilmaz, Lacey Mcquinn, Amanda L Brink, Jing Gong, Cheuk Hong Leung, Heather Lin, David S Hong, Shubham Pant, Brett Carter, Amir Jazaeri, David Gershenson, Anil K Sood, Robert L Coleman, Jatin Shah, Funda Meric-Bernstam, Aung Naing

Faculty, Staff and Student Publications

OBJECTIVE: Selinexor is a first-in-class, oral selective inhibitor of nuclear export (SINE) compound which blocks Exportin-1 (XPO1). Our objective was to determine maximum tolerated dose (MTD) and recommended phase II dose (RP2D) of selinexor and weekly paclitaxel.

METHODS: This was an open label, single-center, multi-arm phase 1b study utilizing a "3 + 3" design and a "basket-type" expansion in recurrent solid tumors. Selinexor (60 mg or 80 mg twice weekly orally) and weekly paclitaxel (80 mg IV 2 week on, 1 week off) were one of 13 parallel arms. Efficacy was evaluated using RECIST version 1.1.

RESULTS: All 35 patients …

Spatial Modelling Of The Tumor Microenvironment From Multiplex Immunofluorescence Images: Methods And Applications, Gayatri Kumar, Renganayaki Krishna Pandurengan, Edwin Roger Parra, Kasthuri Kannan, Cara Haymaker

Faculty, Staff and Student Publications

Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing …

Review Article: New Treatments For Advanced Differentiated Thyroid Cancers And Potential Mechanisms Of Drug Resistance, Sarah Hamidi, Marie-Claude Hofmann, Priyanka C Iyer, Maria E Cabanillas, Mimi I Hu, Naifa L Busaidy, Ramona Dadu

Faculty, Staff and Student Publications

The treatment of advanced, radioiodine refractory, differentiated thyroid cancers (RR-DTCs) has undergone major advancements in the last decade, causing a paradigm shift in the management and prognosis of these patients. Better understanding of the molecular drivers of tumorigenesis and access to next generation sequencing of tumors have led to the development and Food and Drug Administration (FDA)-approval of numerous targeted therapies for RR-DTCs, including antiangiogenic multikinase inhibitors, and more recently, fusion-specific kinase inhibitors such as RET inhibitors and NTRK inhibitors. BRAF + MEK inhibitors have also been approved for BRAF-mutated solid tumors and are routinely used in RR-DTCs in …

Understanding Fertility Behavior Of The Forcibly Displaced Myanmar Nationals In Bangladesh: A Qualitative Study, Md Anwer Hossain, Mohammad Bellal Hossain

Faculty, Staff and Student Publications

INTRODUCTION: Rohingya- the Forcibly Displaced Myanmar Nationals (FDMN)- are largely characterized by a high total fertility rate (TFR) and a low contraceptive prevalence rate. This study aimed to explore the reasons behind their high fertility behavior by utilizing the Theory of Planned Behavior.

DATA AND METHOD: We adopted a cross-sectional qualitative research approach. Fifteen semi-structured, face-to-face in-depth interviews were conducted with the Rohingya husbands, wives, and community leaders (Majhi and Imam/Khatib) living in Camps 1 and 2 of Ukhiya Refugee Camp, Cox's Bazar, Bangladesh. We analyzed the qualitative data using the thematic analysis approach.

RESULTS: The Muslim-majority FDMN predominantly constructed …

Trends And Correlates Of Low Hiv Knowledge Among Ever-Married Women Of Reproductive Age: Evidence From Cross-Sectional Bangladesh Demographic And Health Survey 1996–2014, Md Tariqujjaman, Md Mehedi Hasan, Mohammad Abdullah Heel Kafi, Md Alamgir Hossain, Saad A Khan, Nadia Sultana, Rashidul Azad, Md Arif Hossain, Mahfuzur Rahman, Mohammad Bellal Hossain

Faculty, Staff and Student Publications

BACKGROUND: The human immunodeficiency virus (HIV) burden has frequently been changing over time due to epidemiological and demographic transitions. To safeguard people, particularly women of reproductive age, who can be exposed to transmitting this burden to the next generation, knowledge regarding this life-threatening virus needs to be increased. This research intends to identify the trends and associated correlates of "low" HIV knowledge among ever-married women of reproductive age in Bangladesh from 1996 to 2014.

METHODS: We analyzed data derived from six surveys of Bangladesh Demographic and Health Surveys conducted in 1996, 1999, 2004, 2007, 2011, and 2014. Analyses were primarily …

Trem-1, Trem-2 And Their Association With Disease Severity In Patients With Covid-19, Ruyue Fan, Zuowang Cheng, Zhisheng Huang, Ying Yang, Na Sun, Bin Hu, Peibin Hou, Bo Liu, Chuanjun Huang, Shuai Liu

Faculty, Staff and Student Publications

BACKGROUND: Delayed diagnosis and inadequate treatment caused by limited biomarkers are associated with the outcomes of COVID-19 patients. It is necessary to identify other promising biomarkers and candidate targets for defining dysregulated inflammatory states.

METHODS: The triggering receptors expressed on myeloid cell (TREM)-1 and TREM-2 expression from hospitalized COVID-19 patients were characterized using ELISA and flow cytometry, respectively. Their correlation with disease severity and contrast with the main clinical indicators were evaluated.

RESULTS: Increased expression of soluble TREM-1 and TREM-2 in the plasma of COVID-19 patients was found compared to the control group. Moreover, membrane-bound TREM-1 and TREM-2 expression was …

Gibbs Process Distinguishes Survival And Reveals Contact-Inhibition Genes In Glioblastoma Multiforme, Afrooz Jahedi, Gayatri Kumar, Lavanya Kannan, Tarjani Agarwal, Jason Huse, Krishna Bhat, Kasthuri Kannan

Faculty, Staff and Student Publications

Tumor growth is a spatiotemporal birth-and-death process with loss of heterotypic contact-inhibition of locomotion (CIL) of tumor cells promoting invasion and metastasis. Therefore, representing tumor cells as two-dimensional points, we can expect the tumor tissues in histology slides to reflect realizations of spatial birth-and-death process which can be mathematically modeled to reveal molecular mechanisms of CIL, provided the mathematics models the inhibitory interactions. Gibbs process as an inhibitory point process is a natural choice since it is an equilibrium process of the spatial birth-and-death process. That is if the tumor cells maintain homotypic contact inhibition, the spatial distributions of tumor …