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How Team Science Is Documented and Described in Published Family Medicine Research
No full textPurpose: Increasingly emphasized by leaders in family medicine and primary care research, team science is an approach to research that requires clear documentation for replicability. Here, we report the approach to documenting team science in 2 US family medicine research journals.
Methods: Our interdisciplinary team, composed of MDs and PhDs from family medicine and other disciplines, established a definition of the "team science" construct, which included the utilization of interdisciplinary partnerships and/or collaboration with community-based organizations. Two team members reviewed every original research article published in 2023 in the Annals of Family Medicine (AFM) and the Journal of the American Board of Family Medicine (JABFM). Data extraction identified the use of the term "team science" or the presence of elements of the construct as defined by the team, as well as the funding source(s).
Results: Of the 107 articles reviewed, none explicitly mentioned the term "team science." However, 19 (17.8%) described interdisciplinary partnerships. Seventeen (15.9%) described the disciplines of the contributors, and 5 (4.7%) described community collaborators. Most articles (80.4%) were funded studies, with 70.9% supported by national governmental or nongovernmental entities.
Conclusions: In this sample of articles, team science was either not reported at all or it was described in a limited way. The authors recommend that editors encourage discussions of interdisciplinarity and team science research practices in manuscripts, including descriptions of the strengths each disciplinary representative brings to the team
Patient attitudes toward HPV self-sampling and community health worker-delivered cervical cancer screening services in an underserved area
No full textIntroduction: In Indiana, Black women had 12% higher cervical cancer incidence, and 21% higher mortality compared to White women during the years 2008-2017. Human Papillomavirus (HPV) self-sampling delivered by community health workers (CHW) has demonstrated potential to increase cervical cancer screening rates among at-risk populations. This study aims to understand patient attitudes toward HPV self-sampling and CHW-delivered screening.
Methods: We conducted a cross-sectional online survey among patients from three Planned Parenthood clinics in Lake County, IN, which has one of the highest cervical cancer mortality rates in Indiana. Patients' willingness to self-sample and to receive health education and services related to cervical cancer screening from CHWs was analyzed using logistic regression.
Results: In the final sample (N = 140), the largest proportions of respondents were below age 30 (54.3%), aware of cervical cancer (78.6%), up to date on cervical cancer screening (84.3%), had no prior self-sampling experience (53.6%) and were aware of CHWs (52.1%). Multivariable logistic regression analyses showed Black patients had higher odds of being willing to: self-sample at home (aOR = 3.749, 95% CI = 1.619-8.681), receive health education from CHWs (aOR = 4.952, 95% CI = 2.124-11.548), and receive health services from CHWs (aOR = 3.305, 95% CI = 1.479-7.388) compared to White patients.
Conclusion: Our results showed Black patients had higher willingness for HPV self-sampling and CHW delivery of cervical cancer screening services. Study findings can be used to inform future CHW-led interventions for outreach, education, and delivery of self-sampling interventions to increase cervical cancer screening rates among Black women in underserved areas
Multi‐Omics analysis identifies that different genetic perturbations affect various molecular mechanisms underlying Alzheimer's Disease (AD) in an age‐dependent manner
No full textBackground:
Alzheimer's disease (AD) is a complex, multifactorial pathology characterized by high heterogeneity in biological alterations. New genetic and genomic resources are identifying multiple genetic risk factors for late‐onset Alzheimer's disease (LOAD). However, our understanding of the cellular and molecular mechanisms linking disease risk variants to various phenotypes remains limited. Therefore, it is essential to integrate information from multiple data modalities to thoroughly explore endophenotype networks and biological interactions related to the disease, thereby accelerating our understanding of heterogeneity in Alzheimer's disease.
Method:
We obtained transcriptomics and proteomics data from whole hemibrain samples of mouse models harboring the genetic risk variants Abca7A1527G, Mthfr677C>T, and Plcg2 M28L. These mouse model already carrying humanized amyloid‐beta, APOE4, and Trem2 R47H alleles, all knocked into a C57BL/6J background. We included mouse models of multiple ages for both sexes. Using state‐of‐the‐art bioinformatics tools, we conducted multi‐omics analysis to identify molecular alterations in these mouse models. Furthermore, we systematically aligned the multimodal mouse data with relevant human study cohorts to determine the AD relevance of risk genes.
Result:
The effects of these genetic variants recapitulated a variety of human gene and protein expression patterns observed in the LOAD study cohort. The Abca7 variant exhibited extracellular matrix, neuroimmune, and oligodendrocyte‐related gene signatures at an early age, correlating with postmortem LOAD cases compared to controls. By 18 months of age, the Mthfr variant exhibited vasculature, myelination, and synapse‐related gene and protein signatures, also correlating with postmortem LOAD cases relative to controls. The Plcg2 variant exhibited neuroimmune, endolysosome, and synapse‐related gene signatures and altered cell‐ECM interaction processes at the protein level, correlating with postmortem LOAD cases compared to controls.
Conclusion:
We have characterized in vivo signatures of three genetic candidates for late‐onset Alzheimer's disease (LOAD), identifying alterations in specific LOAD‐related pathways for each variant. Our study highlights that assembling multi‐omics measurements reveals interrelated pathway alterations in Alzheimer's Disease (AD) and enables the identification of biomarker combinations that may inform clinical practice. Our approach provides a platform for further exploration into the causes and progression of AD by assessing animal models at different ages and/or with different combinations of LOAD risk variants
Looking into the Future of Language Learning and Technology with Carol A. Chapelle
No full textIn this reflective interview, Carol Chapelle traces her pioneering journey in language learning and technology (LLT), beginning in the late 1970s at the University of Illinois, where exposure to early computer-assisted language learning sparked her lifelong interest. Emphasizing that technology is an addition—not a replacement—for the human element in teaching, Chapelle discusses how evolving tools, including generative AI, both enhance and challenge pedagogical practice. She warns against misconceptions that students inherently know how to use technology for learning and that AI can replace educators. Instead, she advocates for equipping teachers with the expertise to guide students in leveraging technology productively. Chapelle highlights the importance of integrating LLT into teacher training and ongoing professional development. She also underscores the empowerment technology offers students, especially through access to cultural content and tools for linguistic analysis. For researchers, corpus linguistics exemplifies how technology transforms language study. Looking ahead, Chapelle foresees continued exploration of generative AI, acknowledging both its pedagogical potential and the uncertainty it introduces. Despite fears of AI replacing language education, she reaffirms the enduring human drive to learn language. This interview captures the evolving interplay between language, technology, and pedagogy from one of the field’s most influential voices
Pharmacotherapy research landscape and knowledge gaps of opioids in maternal and pediatric populations
No full textThe use and misuse of opioids has surged in the past decade, with nearly half of the users being female. Although opioid use is lower among pregnant women, trends mirror the general population. While pediatric exposures largely occur through prescriptions. This review presents a novel landscape analysis of pharmacology knowledge gaps in opioids in the maternal and pediatric populations. We queried PubMed for studies on 27 opioids, focusing on pharmacokinetics (PK), and pharmacoepidemiology (PE) or clinical trials (CT) in maternal and pediatric populations. English-language publications were included, and data were synthesized to identify gaps. Additionally, MarketScan claims data and United States Food and Drug Administration (FDA) drug labels were analyzed to compare scientific evidence, opioid prescriptions/orders, and FDA recommendations. Morphine, fentanyl, methadone, and buprenorphine are the most researched opioids in PK and PE/CT literature in both populations, but hydrocodone, oxycodone, and codeine are the most prescribed. Nine opioids lack FDA labels, and four of the 18 labeled drugs lack any human data. Hydrocodone, oxycodone, and codeine labels include lactation-focused PK information, with some pediatric clinical data for the latter two. Seven opioids lack PK and PE/CT studies in the maternal population, and PK research is absent for seven opioids, and PE/CT data is lacking for eight opioids in the pediatric population. PK studies often focus on labor, delivery, and lactation accompanied by neonatal data, whereas pregnancy research mainly occurs in PE studies. In pediatric populations, study types are evenly distributed among children, but PE studies focus more on adolescents. Drug concentration is the most reported parameter in PK studies, and neonatal opioid withdrawal syndrome (NOWS) is a key outcome in both PK and PE studies. NOWS is also researched more using real-world data, whereas neurodevelopmental outcomes are often captured in prospective observational studies. There is substantial disparity between the most commonly researched and prescribed opioids. In particular, the opioid pharmacology knowledge gaps are larger in pregnant women and for the highly prescribed opioids hydrocodone and oxycodone. The limited human data in FDA labels underscores the need for additional studies. Studies using real-world data can potentially help address these gaps
Comparison of mass spectrometry and fourier transform infrared spectroscopy of plasma samples in identification of patients with fracture-related infections
No full textObjectives: Fracture-related infections (FRIs) have significant impact on patient outcomes. Diagnosing FRIs is challenging due to lack of robust, minimally invasive diagnostic tests in the early stages of the disease. The objective of this study was to evaluate the ability of proteomic mass spectrometry (MS) (quantitative approach) and spectral pattern analysis based on fourier transform infrared (FTIR) spectroscopy of plasma samples (qualitative approach) in discriminating between FRI and controls.
Materials and methods: A prospective case-control study at a level 1 trauma center was conducted. Patients meeting confirmatory FRI criteria were matched with controls without infection based on age, time after surgery, and fracture region. Plasma samples were collected at the time of presentation for FRI and saved for batch analysis. Tandem mass tag liquid chromatography-mass spectrometry was used for proteomics, and FTIR spectroscopy of dried films was used to obtain mid-infrared spectra from samples. Mid-infrared spectra were preprocessed, and for MS data, protein abundance ratios of FRI and controls were compared. Multivariate analysis-based predictive models were developed separately for FTIR-based spectra and MS-based protein ratio data.
Results: Thirteen FRI and 13 controls were included in the study. The predictive models based on FTIR spectroscopy data had an average area under the receiver operating characteristic (AUROC) of ≈0.803, CI95(0.8, 0.81), the average sensitivity was ≈ 0. 0.755, CI95(0.75, 0.76), and the specificity was ≈ 0.677, CI95(0.672, 0.682). The MS-based predictive models from protein abundance ratio results had an average AUROC of ≈0.735, CI95(0.732, 0.737), the average sensitivity was ≈ 0.74, CI95 (0.739, 0.747), and the specificity was ≈ 0.653, CI95(0.649, 0.656).
Discussion and conclusions: Mass spectrometry and spectral pattern recognition based on FTIR spectroscopy can both be used to develop predictive models that can discriminate between FRI and control samples. There is potential for both analytical approaches as candidate diagnostic biomarkers in FRI patients that require further validation in future studies
Lymphedema Treatment Act: A Critical Step for Cancer Survivors, but Unresolved Equity Gaps Persist
No full text
Proceedings of the Alzheimer’s Diagnosis in Older Adults With Chronic Conditions Network Inaugural Annual Conference
No full textThe Alzheimer's Disease in Older Adults with Chronic Conditions (ADACC) Network is funded by the National Institute on Aging as a U24 cooperative agreement. ADACC is an inclusive, multidisciplinary group across multiple institutions that is charged with the task of developing evidence-based strategies for the use and implementation of Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) biomarkers among older adults with cognitive impairment and multiple chronic conditions (MCCs). This report summarizes highlights of the First Annual Symposium of ADACC, which was held in Winston-Salem, North Carolina, in April 2024. An overview of the ADACC Network and goals were initially described, followed by a state of the science integrating biomarkers, AD/ADRD, and MCCs. Multiple presentations on a variety of topics were featured, including the significance of MCCs in AD/ADRD, the effects of MCCs on Alzheimer's blood-based biomarkers, the incorporation of AD/ADRD biomarkers into cancer care, the need to address racial and biomarker disparities, clinician and patient perspectives on plasma AD/ADRD biomarker testing, and ethical considerations. ADACC emphasized the importance of supporting emerging researchers and fostering a collaborative environment
Case Report: Malignant perivascular epithelioid cell tumor with aggressive mediastinal invasion and pulmonary metastasis
No full textPerivascular epithelioid cell tumors (PEComas) are rare, typically benign soft tissue tumors that can develop at various anatomic sites. Malignant PEComas are rarer entities but may present aggressively with metastasis to the lungs or local recurrence years after initial presentation. In unresectable or metastatic cases, treatment options are limited due to the resistance of PEComas to chemotherapy and radiotherapy. The present case describes a 59-year-old man with a highly aggressive malignant PEComa, which ultimately invaded the mediastinum and replaced the right middle and lower lobes of the lung despite systemic therapy with oral sirolimus and definitive radiotherapy. As only three prior cases have described malignant PEComas invading the mediastinum, we highlight the clinical course of such an aggressive cancer and review current treatment paradigms