Browsing by Subject "Humans"

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3D Spheroids Derived from Human Lipedema ASCs Demonstrated Similar Adipogenic Differentiation Potential and ECM Remodeling to Non-Lipedema ASCs In Vitro
(MDPI, 2020-11-07) Al-Ghadban, Sara; Pursell, India A.; Diaz, Zaidmara T.; Herbst, Karen L.; Bunnell, Bruce A.
The growth and differentiation of adipose tissue-derived stem cells (ASCs) is stimulated and regulated by the adipose tissue (AT) microenvironment. In lipedema, both inflammation and hypoxia influence the expansion and differentiation of ASCs, resulting in hypertrophic adipocytes and deposition of collagen, a primary component of the extracellular matrix (ECM). The goal of this study was to characterize the adipogenic differentiation potential and assess the levels of expression of ECM-remodeling markers in 3D spheroids derived from ASCs isolated from both lipedema and healthy individuals. The data showed an increase in the expression of the adipogenic genes (ADIPOQ, LPL, PPAR-γ and Glut4), a decrease in matrix metalloproteinases (MMP2, 9 and 11), with no significant changes in the expression of ECM markers (collagen and fibronectin), or integrin A5 in 3D differentiated lipedema spheroids as compared to healthy spheroids. In addition, no statistically significant changes in the levels of expression of inflammatory genes were detected in any of the samples. However, immunofluorescence staining showed a decrease in fibronectin and increase in laminin and Collagen VI expression in the 3D differentiated spheroids in both groups. The use of 3D ASC spheroids provide a functional model to study the cellular and molecular characteristics of lipedema AT.
A bias correction method in meta-analysis of randomized clinical trials with no adjustments for zero-inflated outcomes
(John Wiley & Sons, Inc., 2021-09-03) Zhou, Zhengyang; Xie, Minge; Huh, David; Mun, Eun-Young
Many clinical endpoint measures, such as the number of standard drinks consumed per week or the number of days that patients stayed in the hospital, are count data with excessive zeros. However, the zero-inflated nature of such outcomes is sometimes ignored in analyses of clinical trials. This leads to biased estimates of study-level intervention effect and, consequently, a biased estimate of the overall intervention effect in a meta-analysis. The current study proposes a novel statistical approach, the Zero-inflation Bias Correction (ZIBC) method, that can account for the bias introduced when using the Poisson regression model, despite a high rate of inflated zeros in the outcome distribution of a randomized clinical trial. This correction method only requires summary information from individual studies to correct intervention effect estimates as if they were appropriately estimated using the zero-inflated Poisson regression model, thus it is attractive for meta-analysis when individual participant-level data are not available in some studies. Simulation studies and real data analyses showed that the ZIBC method performed well in correcting zero-inflation bias in most situations.
A Celebration of the Extraordinary Life of Late Professor Tatiana V. Serebrovskaya (Kyiv, Ukraine) in Advancing Hypoxia Science and Medicine
(Mary Ann Liebert, Inc., 2022-08-03) Swenson, Erik R.; Mallet, Robert T.; Xi, Lei; Manukhina, Eugenia B.; Downey, Fred; Burtscher, Johannes; Ehrenreich, Hannelore; Burtscher, Martin
A Collaborative Implementation Strategy to Increase Falls Prevention Training Using the Age-Friendly Health Systems Approach
(MDPI, 2022-05-12) Severance, Jennifer J.; Rivera, Solymar; Cho, Jinmyoung; Hartos, Jessica; Khan, Amal; Knebl, Janice
Falls in the home and in community environments are the leading cause of injuries and long-term disabilities for the aging population. The purpose of this study was to examine outcomes of a partnership among an academic institution, government agency, community organizations, and emergency management services to implement a falls prevention training program using an Age-Friendly Health Systems approach. In this prospective study, partners identified gaps in services and targeted and non-targeted delivery areas for implementation of an evidence-based falls prevention intervention addressing the 4Ms of Age-Friendly Health Systems-Mobility, Medications, Mentation, and What Matters. Descriptive statistics were calculated for program implementation and participant demographic variables, and paired t-test analysis compared scores for self-assessed general health and falls efficacy prior to and after program participation. Twenty-seven falls prevention classes were implemented, with over half (52%) in targeted areas. A total of 354 adults aged 50 and older participated, with N = 188 participants (53%) completing the program by attending at least five of eight sessions. Of completers, 35% resided in targeted areas. The results showed a statistically significant improvement in falls efficacy by program completers in targeted and non-targeted areas. However, there was no statistically significant difference in self-rated health. Overall, the findings of this study indicate that collaboration to deliver falls prevention training can be effective in reaching at-risk older adults. By mobilizing collaborative partnerships, limited resources can be allocated towards identifying at-risk older adults and improving community-based falls prevention education.
A Computational Modeling Study of COVID-19 in Bangladesh
(The American Society of Tropical Medicine and Hygiene, 2020-11-02) Khan, Irtesam Mahmud; Haque, Ubydul; Kaisar, Samiha; Rahman, Mohammad Sohel
The COVID-19 pandemic has spread globally. Only three cases in Bangladesh were reported on March 8, 2020. Here, we aim to predict the epidemic progression for 1 year under different scenarios in Bangladesh. We extracted the number of daily confirmed cases from March 8 to July 20, 2020. We considered the suspected-infected-removed (SIR) model and performed a maximum likelihood-based grid search to determine the removal rate (). The transmission was modeled as a stochastic random walk process, and sequential Monte Carlo simulation was run 100 times with bootstrap fits to infer the transmission rate (beta) and R t. According to the simulation, the (real) peak daily incidence of 3,600 would be followed by a steady decline, reaching below 1,000 in late January 2021. Thus, the model predicted that there would still be more than 300 cases/day even after a year. However, with proper interventions, a much steeper decline would be achieved following the peak. If we apply a combined (0.8beta, 1.2) intervention, there would be less than 100 cases by mid-October, only around five odd cases at the beginning of the year 2021, and zero cases in early March 2021. The predicted total number of deaths (in status quo) after 1 year would be 8,533 which would reduce to 3,577 if combined (0.8beta, 1.2) intervention is applied. We have also predicted the ideal number of tests that Bangladesh should perform and based on that redid the whole simulation. The outcome, though worse, would be manageable with interventions according to the simulation.
A Continuous Statistical Phasing Framework for the Analysis of Forensic Mitochondrial DNA Mixtures
(MDPI, 2021-01-20) Smart, Utpal; Cihlar, Jennifer Churchill; Mandape, Sammed N.; Muenzler, Melissa; King, Jonathan L.; Budowle, Bruce; Woerner, August E.
Despite the benefits of quantitative data generated by massively parallel sequencing, resolving mitotypes from mixtures occurring in certain ratios remains challenging. In this study, a bioinformatic mixture deconvolution method centered on population-based phasing was developed and validated. The method was first tested on 270 in silico two-person mixtures varying in mixture proportions. An assortment of external reference panels containing information on haplotypic variation (from similar and different haplogroups) was leveraged to assess the effect of panel composition on phasing accuracy. Building on these simulations, mitochondrial genomes from the Human Mitochondrial DataBase were sourced to populate the panels and key parameter values were identified by deconvolving an additional 7290 in silico two-person mixtures. Finally, employing an optimized reference panel and phasing parameters, the approach was validated with in vitro two-person mixtures with differing proportions. Deconvolution was most accurate when the haplotypes in the mixture were similar to haplotypes present in the reference panel and when the mixture ratios were neither highly imbalanced nor subequal (e.g., 4:1). Overall, errors in haplotype estimation were largely bounded by the accuracy of the mixture's genotype results. The proposed framework is the first available approach that automates the reconstruction of complete individual mitotypes from mixtures, even in ratios that have traditionally been considered problematic.
A cross-sectional study of latent tuberculosis infection, insurance coverage, and usual sources of health care among non-US-born persons in the United States
(Wolters Kluwer Health, Inc., 2021-02-19) Annan, Esther; Stockbridge, Erica L.; Katz, Dolly; Mun, Eun-Young; Miller, Thaddeus L.
ABSTRACT: More than 70% of tuberculosis (TB) cases diagnosed in the United States (US) occur in non-US-born persons, and this population has experienced less than half the recent incidence rate declines of US-born persons (1.5% vs 4.2%, respectively). The great majority of TB cases in non-US-born persons are attributable to reactivation of latent tuberculosis infection (LTBI). Strategies to expand LTBI-focused TB prevention may depend on LTBI positive non-US-born persons' access to, and ability to pay for, health care.To examine patterns of health insurance coverage and usual sources of health care among non-US-born persons with LTBI, and to estimate LTBI prevalence by insurance status and usual sources of health care.Self-reported health insurance and usual sources of care for non-US-born persons were analyzed in combination with markers for LTBI using 2011-2012 National Health and Nutrition Examination Survey (NHANES) data for 1793 sampled persons. A positive result on an interferon gamma release assay (IGRA), a blood test which measures immunological reactivity to Mycobacterium tuberculosis infection, was used as a proxy for LTBI. We calculated demographic category percentages by IGRA status, IGRA percentages by demographic category, and 95% confidence intervals for each percentage.Overall, 15.9% [95% confidence interval (CI) = 13.5, 18.7] of non-US-born persons were IGRA-positive. Of IGRA-positive non-US-born persons, 63.0% (95% CI = 55.4, 69.9) had insurance and 74.1% (95% CI = 69.2, 78.5) had a usual source of care. IGRA positivity was highest in persons with Medicare (29.1%; 95% CI: 20.9, 38.9).Our results suggest that targeted LTBI testing and treatment within the US private healthcare sector could reach a large majority of non-US-born individuals with LTBI. With non-US-born Medicare beneficiaries' high prevalence of LTBI and the high proportion of LTBI-positive non-US-born persons with private insurance, future TB prevention initiatives focused on these payer types are warranted.
A feed-forward regulation of endothelin receptors by c-Jun in human non-pigmented ciliary epithelial cells and retinal ganglion cells
(PLOS, 2017-09-22) Wang, Junming; Ma, Hai-Ying; Krishnamoorthy, Raghu R.; Yorio, Thomas; He, Shaoqing
c-Jun, c-Jun N-terminal kinase(JNK) and endothelin B (ETB) receptor have been shown to contribute to the pathogenesis of glaucoma. Previously, we reported that an increase of c-Jun and CCAAT/enhancer binding protein beta (C/EBPbeta) immunohistostaining is associated with upregulation of the ETB receptor within the ganglion cell layer of rats with elevated intraocular pressure (IOP). In addition, both transcription factors regulate the expression of the ETB receptor in human non-pigmented ciliary epithelial cells (HNPE). The current study addressed the mechanisms by which ET-1 produced upregulation of ET receptors in primary rat retinal ganglion cells (RGCs) and HNPE cells. Treatment of ET-1 and ET-3 increased the immunocytochemical staining of c-Jun and C/EBPbeta in primary rat RGCs and co-localization of both transcription factors was observed. A marked increase in DNA binding activity of AP-1 and C/EBPbeta as well as elevated protein levels of c-Jun and c-Jun-N-terminal kinase (JNK) were detected following ET-1 treatment in HNPE cells. Overexpression of ETA or ETB receptor promoted the upregulation of c-Jun and also elevated its promoter activity. In addition, upregulation of C/EBPbeta augmented DNA binding and mRNA expression of c-Jun, and furthermore, the interaction of c-Jun and C/EBPbeta was confirmed using co-immunoprecipitation. Apoptosis of HNPE cells was identified following ET-1 treatment, and overexpression of the ETA or ETB receptor produced enhanced apoptosis. ET-1 mediated upregulation of c-Jun and C/EBPbeta and their interaction may represent a novel mechanism contributing to the regulation of endothelin receptor expression. Reciprocally, c-Jun was also found to regulate the ET receptors and C/EBPbeta appeared to play a regulatory role in promoting expression of c-Jun. Taken together, the data suggests that ET-1 triggers the upregulation of c-Jun through both ETA and ETB receptors, and conversely c-Jun also upregulates endothelin receptor expression, thereby generating a positive feed-forward loop of endothelin receptor activation and expression. This feed-forward regulation may contribute to RGC death and astrocyte proliferation following ET-1 treatment.
A Machine Learning Approach to Identify Predictors of Potentially Inappropriate Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Use in Older Adults with Osteoarthritis
(MDPI, 2020-12-28) Patel, Jayeshkumar; Ladani, Amit; Sambamoorthi, Nethra; LeMasters, Traci; Dwibedi, Nilanjana; Sambamoorthi, Usha
Evidence from some studies suggest that osteoarthritis (OA) patients are often prescribed non-steroidal anti-inflammatory drugs (NSAIDs) that are not in accordance with their cardiovascular (CV) or gastrointestinal (GI) risk profiles. However, no such study has been carried out in the United States. Therefore, we sought to examine the prevalence and predictors of potentially inappropriate NSAIDs use in older adults (age > 65) with OA using machine learning with real-world data from Optum De-identified Clinformatics((R)) Data Mart. We identified a retrospective cohort of eligible individuals using data from 2015 (baseline) and 2016 (follow-up). Potentially inappropriate NSAIDs use was identified using the type (COX-2 selective vs. non-selective) and length of NSAIDs use and an individual's CV and GI risk. Predictors of potentially inappropriate NSAIDs use were identified using eXtreme Gradient Boosting. Our study cohort comprised of 44,990 individuals (mean age 75.9 years). We found that 12.8% individuals had potentially inappropriate NSAIDs use, but the rate was disproportionately higher (44.5%) in individuals at low CV/high GI risk. Longer duration of NSAIDs use during baseline (AOR 1.02; 95% CI:1.02-1.02 for both non-selective and selective NSAIDs) was associated with a higher risk of potentially inappropriate NSAIDs use. Additionally, individuals with low CV/high GI (AOR 1.34; 95% CI:1.20-1.50) and high CV/low GI risk (AOR 1.61; 95% CI:1.34-1.93) were also more likely to have potentially inappropriate NSAIDs use. Heightened surveillance of older adults with OA requiring NSAIDs is warranted.
A Multi-Level Analysis of Individual and Neighborhood Factors Associated with Patient Portal Use among Adult Emergency Department Patients with Multimorbidity
(MDPI, 2023-01-22) Wang, Hao; Shen, Chan; Barbaro, Michael; Ho, Amy F.; Pathak, Mona; Dunn, Cita; Sambamoorthi, Usha
BACKGROUND: Patient portals tethered to electronic health records (EHR) have become vital to patient engagement and better disease management, specifically among adults with multimorbidity. We determined individual and neighborhood factors associated with patient portal use (MyChart) among adult patients with multimorbidity seen in an Emergency Department (ED). METHODS: This study adopted a cross-sectional study design and used a linked database of EHR from a single ED site to patients' neighborhood characteristics (i.e., zip code level) from the American Community Survey. The study population included all adults (age > 18 years), with at least one visit to an ED and multimorbidity between 1 January 2019 to 31 December 2020 (N = 40,544). Patient and neighborhood characteristics were compared among patients with and without MyChart use. Random-intercept multi-level logistic regressions were used to analyze the associations of patient and neighborhood factors with MyChart use. RESULTS: Only 19% (N = 7757) of adults with multimorbidity used the patient portal. In the fully adjusted multi-level model, at the patient level, having a primary care physician (AOR = 5.55, 95% CI 5.07-6.07, p < 0.001) and health insurance coverage (AOR = 2.41, 95% CI 2.23-2.61, p < 0.001) were associated with MyChart use. At the neighborhood level, 4.73% of the variation in MyChart use was due to differences in neighborhood factors. However, significant heterogeneity existed in patient portal use when neighborhood characteristics were included in the model. CONCLUSIONS: Among ED patients with multimorbidity, one in five adults used patient portals. Patient-level factors, such as having primary care physicians and insurance, may promote patient portal use.
A nonparametric alternative to the Cochran-Armitage trend test in genetic case-control association studies: The Jonckheere-Terpstra trend test
(PLOS, 2023-02-03) Manning, Sydney E.; Ku, Hung-Chih; Dluzen, Douglas F.; Xing, Chao; Zhou, Zhengyang
Identifications of novel genetic signals conferring susceptibility to human complex diseases is pivotal to the disease diagnosis, prevention, and treatment. Genetic association study is a powerful tool to discover candidate genetic signals that contribute to diseases, through statistical tests for correlation between the disease status and genetic variations in study samples. In such studies with a case-control design, a standard practice is to perform the Cochran-Armitage (CA) trend test under an additive genetic model, which suffers from power loss when the model assumption is wrong. The Jonckheere-Terpstra (JT) trend test is an alternative method to evaluate association in a nonparametric way. This study compares the power of the JT trend test and the CA trend test in various scenarios, including different sample sizes (200-2000), minor allele frequencies (0.05-0.4), and underlying modes of inheritance (dominant genetic model to recessive genetic model). By simulation and real data analysis, it is shown that in general the JT trend test has higher, similar, and lower power than the CA trend test when the underlying mode of inheritance is dominant, additive, and recessive, respectively; when the sample size is small and the minor allele frequency is low, the JT trend test outperforms the CA trend test across the spectrum of genetic models. In sum, the JT trend test is a valuable alternative to the CA trend test under certain circumstances with higher statistical power, which could lead to better detection of genetic signals to human diseases and finer dissection of their genetic architecture.
A novel 3D culture model of fungal keratitis to explore host-pathogen interactions within the stromal environment
(Elsevier Ltd., 2021-04-15) Brown, Marina E.; Montgomery, Micaela L.; Kamath, Manali M.; Nicholas, Sarah; Liu, Yutao; Karamichos, Dimitrios; Fuller, Kevin K.
Fungal keratitis (FK) pathology is driven by both fungal growth and inflammation within the corneal stroma. Standard in vitro infection models involving co-culture of the pathogen and the corneal cells in tissue culture medium are sufficient to probe host responses to the fungus; however, they lack the physiological structure and nutrient composition of the stroma to accurately study fungal invasiveness and metabolic processes. We therefore sought to develop a culture model of FK that would allow for both host and fungal cell biology to be evaluated in parallel. Towards this end, we employed a previously described system in which primary human cornea fibroblasts (HCFs) are cultured on transwell membranes, whereupon they secrete a three-dimensional (3D) collagen matrix that resembles the human stroma. We demonstrated that two common mold agents of FK, Fusarium petroliphilum and Aspergillus fumigatus, penetrated into these constructs and caused a disruption of the collagen matrix that is characteristic of infection. HCF morphology appeared altered in the presence of fungus and electron microscopy revealed a clear internalization of fungal spores into these cells. Consistent with this apparent phagocyte-like activity of the HCFs, mRNA and protein levels for several pro-inflammatory cytokines/chemokines (including TNFalpha, IL-1beta, IL-6, and IL-8) were significantly upregulated compared to uninfected samples. We similarly found an upregulation of several HCF metalloproteases (MMPs), which are enzymes that breakdown collagen during wound healing and may further activate pro-inflammatory signaling molecules. Finally, several fungal collagenase genes were upregulated during growth in the constructs relative to growth in tissue culture media alone, suggesting a fungal metabolic shift towards protein catabolism. Taken together, our results indicate that this 3D-stromal model provides a physiologically relevant system to study host and fungal cell pathobiology during FK.
A novel ligand on astrocytes interacts with natural cytotoxicity receptor NKp44 regulating immune response mediated by NK cells
(PLOS, 2018-02-15) Bowen, Kelly E.; Mathew, Stephen O.; Borgmann, Kathleen; Ghorpade, Anuja; Mathew, Porunelloor A.
NK cells play important role in immunity against pathogens and cancer. NK cell functions are regulated by inhibitory and activating receptors binding corresponding ligands on the surface of target cells. NK cells were shown to be recruited to the CNS following several pathological conditions. NK cells could impact CNS physiology by killing glial cells and by secreting IFN-gamma. Astrocytes are intimately involved in immunological and inflammatory events occurring in the CNS and reactive astrogliosis is a key feature in HIV-associated neurocognitive disorders. There is little data on NK-astrocyte interactions and ligands expressed on astrocytes that could impact NK cell function. Natural cytotoxicity receptors (NCRs) play a critical role in the cytolytic function of NK cells. Among the NCRs, NKp44 is unique in expression and signal transduction. NKp44 is expressed only upon activation of NK cells and it can mediate both activating and inhibitory signals to NK cells. Here, we have studied the expression and function of natural cytotoxicity receptor NKp44 upon NK-astrocytes interactions in the presence or absence of an HIV peptide (HIV-3S peptide) shown to induce NK cell killing of CD4+ T cells during HIV-infection. Using a fusion protein consisting of the extracellular domain of NKp44 fused to Fc portion of human IgG, we determined the expression of a novel ligand for NKp44 (NKp44L) on astrocytes. Incubation of astrocytes with HIV-3S peptide downregulated NKp44L expression on astrocytes implicating protection from NK mediated killing. Thus, our study showed that NKp44 have a protective effect on astrocytes from NK cell mediated killing during HIV infection and impact astrocyte role in HAND.
A Novel Prodrug Approach for Central Nervous System-Selective Estrogen Therapy
(MDPI, 2019-11-19) Prokai-Tatrai, Katalin; Prokai, Laszlo
Beneficial effects of estrogens in the central nervous system (CNS) results from the synergistic combination of their well-orchestrated genomic and non-genomic actions, making them potential broad-spectrum neurotherapeutic agents. However, owing to unwanted peripheral hormonal burdens by any currently known non-invasive drug administrations, the development of estrogens as safe pharmacotherapeutic modalities cannot be realized until they are confined specifically and selectively to the site of action. We have developed small-molecule bioprecursor prodrugs carrying the para-quinol scaffold on the steroidal A-ring that are preferentially metabolized in the CNS to the corresponding estrogens. Here, we give an overview of our discovery of these prodrugs. Selected examples are shown to illustrate that, independently of the route of administrations and duration of treatments, these agents produce high concentration of estrogens only in the CNS without peripheral hormonal liability. 10beta,17beta-Dihydroxyestra-1,4-dien-3-one (DHED) has been the best-studied representative of this novel type of prodrugs for brain and retina health. Specific applications in preclinical animal models of centrally-regulated and estrogen-responsive human diseases, including neurodegeneration, menopausal symptoms, cognitive decline and depression, are discussed to demonstrate the translational potential of our prodrug approach for CNS-selective and gender-independent estrogen therapy with inherent therapeutic safety.
A Precision Medicine Approach to Treating Alzheimer's Disease Using Rosiglitazone Therapy: A Biomarker Analysis of the REFLECT Trials
(IOS Press, 2021-05-18) O'Bryant, Sid E.; Zhang, Fan; Petersen, Melissa E.; Johnson, Leigh A.; Hall, James R.; Rissman, Robert A.
Background: The REFLECT trials were conducted to examine the treatment of mild-to-moderate Alzheimer's disease utilizing a peroxisome proliferator-activated receptor gamma agonist. Objective: To generate a predictive biomarker indicative of positive treatment response using samples from the previously conducted REFLECT trials. Methods: Data were analyzed on 360 participants spanning multiple negative REFLECT trials, which included treatment with rosiglitazone and rosiglitazone XR. Support vector machine analyses were conducted to generate a predictive biomarker profile. Results: A pre-defined 6-protein predictive biomarker (IL6, IL10, CRP, TNFɑ, FABP-3, and PPY) correctly classified treatment response with 100% accuracy across study arms for REFLECT Phase II trial (AVA100193) and multiple Phase III trials (AVA105640, AV102672, and AVA102670). When the data was combined across all rosiglitazone trial arms, a global RSG-predictive biomarker with the same 6-protein predictive biomarker was able to accurately classify 98%of treatment responders. Conclusion: A predictive biomarker comprising of metabolic and inflammatory markers was highly accurate in identifying those patients most likely to experience positive treatment response across the REFLECT trials. This study provides additional proof-of-concept that a predictive biomarker can be utilized to help with screening and predicting treatment response, which holds tremendous benefit for clinical trials.
A prospective cost-benefit analysis for nylon 4N6FLOQSwabs(R): example of the process and potential benefits
(Springer Nature, 2022-09-04) Budowle, Bruce; Ge, Jianye; Sajantila, Antti
Laboratories and their criminal justice systems are confronted with challenges for implementing new technologies, practices, and policies even when there appears to be demonstrative benefits to operational performance. Impacting decisions are the often higher costs associated with, for example, new technologies, limited current budgets, and making hard decisions on what to sacrifice to take on the seemingly better approach. A prospective cost-benefit analysis (CBA) could help an agency better formulate its strategies and plans and more importantly delineate how a relatively small increase to take on, for example, a new technology can have large impact on the system (e.g., the agency, other agencies, victims and families, and taxpayers). To demonstrate the process and potential value a CBA was performed on the use of an alternate and more expensive swab with reported better DNA yield and being certified human DNA free (i.e., nylon 4N6FLOQSwabs(R)), versus the traditional less costly swab (i.e., cotton swab). Assumptions are described, potential underestimates and overestimates noted, different values applied (for low and modest to high), and potential benefits (monetary and qualitative) presented. The overall outcome is that the cost of using the more expensive technology pales compared with the potential tangible and intangible benefits. This approach could be a guide for laboratories (and associated criminal justice systems) worldwide to support increased funding, although the costs and benefits may vary locally and for different technologies, practices, and policies. With well-developed CBAs, goals of providing the best services to support the criminal justice system and society can be attained.
A review of musculoskeletal adaptations in individuals following major lower-limb amputation
(Hylonome Publications, 2022-06-01) Finco, M. G.; Kim, Suhhyun; Ngo, Wayne; Menegaz, Rachel A.
Structural musculoskeletal adaptations following amputation, such as bone mineral density (BMD) or muscle architecture, are often overlooked despite their established contributions to gait rehabilitation and the development of adverse secondary physical conditions. The purpose of this review is to provide a summary of the existing literature investigating musculoskeletal adaptations in individuals with major lower-limb amputations to inform clinical practice and provide directions for future research. Google Scholar, PubMed, and Scopus were searched for original peer-reviewed studies that included individuals with transtibial or transfemoral amputations. Summary data of twenty-seven articles indicated reduced BMD and increased muscle atrophy in amputees compared to controls, and in the amputated limb compared to intact and control limbs. Specifically, BMD was reduced in T-scores and Z-scores, femoral neck, and proximal tibia. Muscle atrophy was evidenced by decreased thigh cross-sectional area, decreased quadriceps thickness, and increased amounts of thigh fat. Overall, amputees have impaired musculoskeletal health. Future studies should include dysvascular etiologies to address their effects on musculoskeletal health and functional mobility. Moreover, clinicians can use these findings to screen increased risks of adverse sequelae such as fractures, osteopenia/porosis, and muscular atrophy, as well as target specific rehabilitation exercises to reduce these risks.
A Structural Equation Modeling Approach to Meta-analytic Mediation Analysis Using Individual Participant Data: Testing Protective Behavioral Strategies as a Mediator of Brief Motivational Intervention Effects on Alcohol-Related Problems
(Springer Nature, 2021-11-12) Huh, David; Li, Xiaoyin; Zhou, Zhengyang; Walters, Scott T.; Baldwin, Scott A.; Tan, Zhengqi; Larimer, Mary E.; Mun, Eun-Young
This paper introduces a meta-analytic mediation analysis approach for individual participant data (IPD) from multiple studies. Mediation analysis evaluates whether the effectiveness of an intervention on health outcomes occurs because of change in a key behavior targeted by the intervention. However, individual trials are often statistically underpowered to test mediation hypotheses. Existing approaches for evaluating mediation in the meta-analytic context are limited by their reliance on aggregate data; thus, findings may be confounded with study-level differences unrelated to the pathway of interest. To overcome the limitations of existing meta-analytic mediation approaches, we used a one-stage estimation approach using structural equation modeling (SEM) to combine IPD from multiple studies for mediation analysis. This approach (1) accounts for the clustering of participants within studies, (2) accommodates missing data via multiple imputation, and (3) allows valid inferences about the indirect (i.e., mediated) effects via bootstrapped confidence intervals. We used data (N = 3691 from 10 studies) from Project INTEGRATE (Mun et al. Psychology of Addictive Behaviors, 29, 34-48, 2015) to illustrate the SEM approach to meta-analytic mediation analysis by testing whether improvements in the use of protective behavioral strategies mediate the effectiveness of brief motivational interventions for alcohol-related problems among college students. To facilitate the application of the methodology, we provide annotated computer code in R and data for replication. At a substantive level, stand-alone personalized feedback interventions reduced alcohol-related problems via greater use of protective behavioral strategies; however, the net-mediated effect across strategies was small in size, on average.
A Tutorial on Cognitive Diagnosis Modeling for Characterizing Mental Health Symptom Profiles Using Existing Item Responses
(Springer Nature, 2022-02-04) Tan, Zhengqi; de la Torre, Jimmy; Ma, Wenchao; Huh, David; Larimer, Mary E.; Mun, Eun-Young
In research applications, mental health problems such as alcohol-related problems and depression are commonly assessed and evaluated using scale scores or latent trait scores derived from factor analysis or item response theory models. This tutorial paper demonstrates the use of cognitive diagnosis models (CDMs) as an alternative approach to characterizing mental health problems of young adults when item-level data are available. Existing measurement approaches focus on estimating the general severity of a given mental health problem at the scale level as a unidimensional construct without accounting for other symptoms of related mental health problems. The prevailing approaches may ignore clinically meaningful presentations of related symptoms at the item level. The current study illustrates CDMs using item-level data from college students (40 items from 719 respondents; 34.6% men, 83.9% White, and 16.3% first-year students). Specifically, we evaluated the constellation of four postulated domains (i.e., alcohol-related problems, anxiety, hostility, and depression) as a set of attribute profiles using CDMs. After accounting for the impact of each attribute (i.e., postulated domain) on the estimates of attribute profiles, the results demonstrated that when items or attributes have limited information, CDMs can utilize item-level information in the associated attributes to generate potentially meaningful estimates and profiles, compared to analyzing each attribute independently. We introduce a novel visual inspection aid, the lens plot, for quantifying this gain. CDMs may be a useful analytical tool to capture respondents' risk and resilience for prevention research.
Adipose Tissue-Derived Mesenchymal Stem Cells
(MDPI, 2021-12-06) Bunnell, Bruce A.
The long-held belief about adipose tissue was that it was relatively inert in terms of biological activity. It was believed that its primary role was energy storage; however, that was shattered with the discovery of adipokines. Scientists interested in regenerative medicine then reported that adipose tissue is rich in adult stromal/stem cells. Following these initial reports, adipose stem cells (ASCs) rapidly garnered interest for use as potential cellular therapies. The primary advantages of ASCs compared to other mesenchymal stem cells (MSCs) include the abundance of the tissue source for isolation, the ease of methodologies for tissue collection and cell isolation, and their therapeutic potential. Studies conducted both in vitro and in vivo have demonstrated that ASCs are multipotent, possessing the ability to differentiate into cells of mesodermal origins, including adipocytes, chondrocytes, osteoblast and others. Moreover, ASCs produce a broad array of cytokines, growth factors, nucleic acids (miRNAs), and other macromolecules into the surrounding milieu by secretion or in the context of microvesicles. The secretome of ASCs has been shown to alter tissue biology, stimulate tissue-resident stem cells, change immune cell activity, and mediate therapeutic outcomes. The quality of ASCs is subject to donor-to-donor variation driven by age, body mass index, disease status and possibly gender and ethnicity. This review discusses adipose stromal/stem cell action mechanisms and their potential utility as cellular therapeutics.