Hydroxyurea reduces infections in children with sickle cell anemia in Uganda.

ABSTRACT: After starting hydroxyurea treatment, Ugandan children with sickle cell anemia had 60% fewer severe or invasive infections, including malaria, bacteremia, respiratory tract infections, and gastroenteritis, than before starting hydroxyurea treatment (incidence rate ratio, 0.40 [95% confidence interval, 0.29-0.54]; P < .001).

An integrative latent class model of heterogeneous data modalities for diagnosing kidney obstruction.

Radionuclide imaging plays a critical role in the diagnosis and management of kidney obstruction. However, most practicing radiologists in US hospitals have insufficient time and resources to acquire training and experience needed to interpret radionuclide images, leading to increased diagnostic errors. To tackle this problem, Emory University embarked on a study that aims to develop a computer-assisted diagnostic (CAD) tool for kidney obstruction by mining and analyzing patient data comprised of renogram curves, ordinal expert ratings on the obstruction status, pharmacokinetic variables, and demographic information. The major challenges here are the heterogeneity in data modes and the lack of gold standard for determining kidney obstruction. In this article, we develop a statistically principled CAD tool based on an integrative latent class model that leverages heterogeneous data modalities available for each patient to provide accurate prediction of kidney obstruction. Our integrative model consists of three sub-models (multilevel functional latent factor regression model, probit scalar-on-function regression model, and Gaussian mixture model), each of which is tailored to the specific data mode and depends on the unknown obstruction status (latent class). An efficient MCMC algorithm is developed to train the model and predict kidney obstruction with associated uncertainty. Extensive simulations are conducted to evaluate the performance of the proposed method. An application to an Emory renal study demonstrates the usefulness of our model as a CAD tool for kidney obstruction.

Diagnostic evaluation of pharmacokinetic features of functional markers.

The dynamicity of functional (curve) markers from modern clinical studies offers deeper insights into complex disease physiology. A frequent clinical practice is to examine various 'pharmacokinetic features' of functional markers (definite integral, maximum value, time to maximum, etc.) that reflect important physiological underpinnings. For instance, the current diagnostic procedure for kidney obstruction is to examine several pharmacokinetic features of renogram curves characterizing renal function. Motivated by such clinical practices, we develop a statistical framework for evaluating diagnostic accuracy of pharmacokinetic features using area under the receiver operating characteristic curve (AUC). The major challenge is that functional markers are observed at discrete time points with measurement error. To address this challenge, we develop a two-stage non-parametric AUC estimator based on summary functionals providing unified representation of various pharmacokinetic features and study its asymptotic properties. We also propose a sensible adaptation of a semiparametric regression model that can describe heterogeneity of AUC across different subpopulations, while appropriately handling discreteness and noise in observed functional markers. Here, a novel data-driven approach that balances between bias and efficiency of the regression coefficient estimates is introduced. Finally, the framework is applied to rigorously evaluate pharmacokinetic features of renogram curves potentially useful for detecting kidney obstruction.

The Effect of In-Person Primary and Secondary School Instruction on County-Level Severe Acute Respiratory Syndrome Coronavirus 2 Spread in Indiana.

BACKGROUND: Our goal was to determine the county-level effect of in-person primary and secondary school reopening on daily cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Indiana. METHODS: In this county-level, population-based study, we used a panel data regression analysis of the proportion of in-person learning to evaluate an association with community-wide daily new SARS-CoV-2 cases. The study period was 12 July 2020-6 October 2020. We included 73 of 92 (79.3%) Indiana counties in the analysis, accounting for 85.7% of school corporations and 90.6% of student enrollment statewide. The primary exposure was the proportion of students returning to in-person instruction. The primary outcome was the daily new SARS-CoV-2 cases per 100 000 residents at the county level. RESULTS: There is a statistically significant relationship between the proportion of students attending K-12 schools in-person and the county level daily cases of SARS-CoV-2 28 days later. For all ages, the coefficient of interest (ß) is estimated at 3.36 (95% confidence interval, 1.91 to 4.81; P < .001). This coefficient represents the effect of a change in the proportion of students attending in-person on new daily cases 28 days later. For example, a 10 percentage point increase in K-12 students attending school in-person is associated with a daily increase in SARS-CoV-2 cases in the county equal to 0.336 cases/100 000 residents of all ages. CONCLUSIONS: In-person primary and secondary school is associated with a statistically significant but proportionally small increase in the spread of SARS-CoV-2 cases.

Examination of Social Inferencing Skills in Men and Women After Traumatic Brain Injury.

OBJECTIVE: To examine sex differences in social inferencing deficits after traumatic brain injury (TBI) and to examine the odds of men and women being impaired while controlling for potential confounders. DESIGN: Cross-sectional survey. SETTING: Two TBI rehabilitation hospitals. PARTICIPANTS: One hundred five participants with TBI (60 men, 45 women) and 105 controls without TBI (57 men, 48 women) (N=210). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The Awareness of Social Inference Test (TASIT), which includes (1) Emotion Evaluation Test (EET), (2) Social Inference-Minimal (SI-M) test, and (3) Social Inference-Enriched (SI-E) test. RESULTS: Within the control sample, men and women performed similarly on all 3 TASIT subtests. Within the group with TBI, men had significantly lower scores than women on EET (P=.03), SI-M (P=.01), and SI-E (P=.04). Using impairment cutoffs derived from the sample without TBI, we found significantly more men with TBI (30%) were impaired on the EET than women (16.7%); impairment was similar between men and women on SI-M and SI-E. When adjusting for executive functioning and education, the odds of being impaired on the EET did not significantly differ for men and women (odds ratio, 0.47; 95% CI, 0.16-1.40; P=.18). CONCLUSIONS: Although more men with TBI have emotion perception deficits than women, the difference appears to be driven by education and executive functioning. Research is needed in larger samples with more definitive norms to better understand social inferencing impairments in men and women with TBI as well as translation to interpersonal behaviors.

Stabilization of C/EBPß through direct interaction with STAT3 in H-Ras transformed human mammary epithelial cells.

Signal transducer and activator of transcription 3 (STAT3) plays important roles in cancer-associated inflammation by controlling expression of proinflammatory cytokines and chemokines. Recent studies suggest that C/EBPß (CCAAT-enhancer binding protein beta) and STAT3 synergistically stimulate cancer cell proliferation and epithelial-mesenchymal transition. C/EBPß is a leucine-zipper transcription factor that regulates expression of a variety of inflammatory cytokines or chemokines, such as IL-8, G-CSF (granulocyte colony stimulating factor), and GM-CSF (granulocyte macrophage colony stimulating factor) which induce neutrophil infiltration and differentiation. However, molecular mechanisms by which STAT3 and C/EBPß cooperatively interact had not been fully elucidated. In this study, we found that the level of C/EBPß protein, but not that of its mRNA transcript, was decreased in the absence of STAT3 in H-Ras transformed human mammary epithelial (H-Ras MCF10A) cells. In addition, silencing STAT3 dramatically induced ubiquitination of C/EBPß for proteasomal degradation. Furthermore, direct interaction between STAT3 and C/EBPß was confirmed by immunoprecipitation and proximity ligation assays. Taken together, these results suggest that STAT3 stabilizes C/EBPß, thereby promoting cancer-associated inflammation.

Principal component analysis of hybrid functional and vector data.

We propose a practical principal component analysis (PCA) framework that provides a nonparametric means of simultaneously reducing the dimensions of and modeling functional and vector (multivariate) data. We first introduce a Hilbert space that combines functional and vector objects as a single hybrid object. The framework, termed a PCA of hybrid functional and vector data (HFV-PCA), is then based on the eigen-decomposition of a covariance operator that captures simultaneous variations of functional and vector data in the new space. This approach leads to interpretable principal components that have the same structure as each observation and a single set of scores that serves well as a low-dimensional proxy for hybrid functional and vector data. To support practical application of HFV-PCA, the explicit relationship between the hybrid PC decomposition and the functional and vector PC decompositions is established, leading to a simple and robust estimation scheme where components of HFV-PCA are calculated using the components estimated from the existing functional and classical PCA methods. This estimation strategy allows flexible incorporation of sparse and irregular functional data as well as multivariate functional data. We derive the consistency results and asymptotic convergence rates for the proposed estimators. We demonstrate the efficacy of the method through simulations and analysis of renal imaging data.

A Bayesian multiple imputation approach to bivariate functional data with missing components.

Existing missing data methods for functional data mainly focus on reconstructing missing measurements along a single function-a univariate functional data setting. Motivated by a renal study, we focus on a bivariate functional data setting, where each sampling unit is a collection of two distinct component functions, one of which may be missing. Specifically, we propose a Bayesian multiple imputation approach based on a bivariate functional latent factor model that exploits the joint changing patterns of the component functions to allow accurate and stable imputation of one component given the other. We further extend the framework to address multilevel bivariate functional data with missing components by modeling and exploiting inter-component and intra-subject correlations. We develop a Gibbs sampling algorithm that simultaneously generates multiple imputations of missing component functions and posterior samples of model parameters. For multilevel bivariate functional data, a partially collapsed Gibbs sampler is implemented to improve computational efficiency. Our simulation study demonstrates that our methods outperform other competing methods for imputing missing components of bivariate functional data under various designs and missingness rates. The motivating renal study aims to investigate the distribution and pharmacokinetic properties of baseline and post-furosemide renogram curves that provide further insights into the underlying mechanism of renal obstruction, with post-furosemide renogram curves missing for some subjects. We apply the proposed methods to impute missing post-furosemide renogram curves and obtain more refined insights.

Evaluating Negative Attributions in Persons With Brain Injury: A Comparison of 2 Measures.

OBJECTIVES: To compare construct and predictive validity, readability, and time-to-administer of 2 negative attribution measures in participants with traumatic brain injury (TBI). SETTING: Two TBI rehabilitation hospitals. PARTICIPANTS: Eighty-five adults with complicated mild to severe TBI. MAIN MEASURES: Negative attributions (intent, hostility, and blame) and anger responses to hypothetical scenarios were measured with the Epps scenarios and the Ambiguous Intention Hostility Questionnaire (AIHQ). Trait aggression was measured with the Buss-Perry Aggression Questionnaire (BPAQ). RESULTS: Associations between attributions and anger responses (ie, construct validity) within each measure were significant (Epps: r = 0.61-0.74; AIHQ: r = 0.39-0.71); however, associations were stronger for Epps (Ps < .001). Receiver operating characteristics (ROC) revealed attributions from both measures predicted BPAQ scores (area under the ROC curves = 0.6-0.8); predictive validity did not statistically differ between the 2 measures. Both had comparable readability (fifth- to sixth-grade levels), but Epps required longer administration times. CONCLUSION: Negative attributions affect anger and aggression after TBI, making it important to identify suitable assessments for the TBI population. While psychometric properties of the AIHQ and Epps scenarios should be further explored, this study offers early support for the use of either instrument in persons with TBI. Advantages and disadvantages of the AIHQ and Epps scenarios are highlighted.

Stepwise Regression and Latent Profile Analyses of Locomotor Outcomes Poststroke.

BACKGROUND AND PURPOSE: Previous data suggest patient demographics and clinical presentation are primary predictors of motor recovery poststroke, with minimal contributions of physical interventions. Other studies indicate consistent associations between the amount and intensity of stepping practice with locomotor outcomes. The goal of this study was to determine the relative contributions of these combined variables to locomotor outcomes poststroke across a range of patient demographics and baseline function. METHODS: Data were pooled from 3 separate trials evaluating the efficacy of high-intensity training, low-intensity training, and conventional interventions. Demographics, clinical characteristics, and training activities from 144 participants >1-month poststroke were included in stepwise regression analyses to determine their relative contributions to locomotor outcomes. Subsequent latent profile analyses evaluated differences in classes of participants based on their responses to interventions. RESULTS: Stepwise regressions indicate primary contributions of stepping activity on locomotor outcomes, with additional influences of age, duration poststroke, and baseline function. Latent profile analyses revealed 2 main classes of outcomes, with the largest gains in those who received high-intensity training and achieved the greatest amounts of stepping practice. Regression and latent profile analyses of only high-intensity training participants indicated age, baseline function, and training activities were primary determinants of locomotor gains. Participants with the smallest gains were older (≈60 years), presented with slower gait speeds (<0.40 m/s), and performed 600 to 1000 less steps/session. CONCLUSIONS: Regression and cluster analyses reveal primary contributions of training interventions on mobility outcomes in patients >1-month poststroke. Age, duration poststroke, and baseline impairments were secondary predictors. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02507466 and NCT01789853.

Fibroblast growth factor-2, derived from cancer-associated fibroblasts, stimulates growth and progression of human breast cancer cells via FGFR1 signaling.

Cancer-associated fibroblasts (CAFs) constitute a major compartment of the tumor microenvironment. In the present study, we investigated the role for CAFs in breast cancer progression and underlying molecular mechanisms. Human breast cancer MDA-MB-231 cells treated with the CAF-conditioned media manifested a more proliferative phenotype, as evidenced by enhanced messenger RNA (mRNA) expression of Cyclin D1, c-Myc, and proliferating cell nuclear antigen. Analysis of data from The Cancer Genome Atlas revealed that fibroblast growth factor-2 (FGF2) expression was well correlated with the presence of CAFs. We noticed that the mRNA level of FGF2 in CAFs was higher than that in normal fibroblasts. FGF2 exerts its biological effects through interaction with FGF receptor 1 (FGFR1). In the breast cancer tissue array, 42% estrogen receptor-negative patients coexpressed FGF2 and FGFR1, whereas only 19% estrogen receptor-positive patients exhibited coexpression. CAF-stimulated MDA-MB-231 cell migration and invasiveness were abolished when FGF2-neutralizing antibody was added to the conditioned media of CAFs. In a xenograft mouse model, coinjection of MDA-MB-231 cells with activated fibroblasts expressing FGF2 dramatically enhanced tumor growth, and this was abrogated by silencing of FGFR1 in cancer cells. In addition, treatment of MDA-MB-231 cells with FGF2 enhanced expression of Cyclin D1, a key molecule involved in cell cycle progression. FGF2-induced cell migration and upregulation of Cyclin D1 were abolished by siRNA-mediated FGFR1 silencing. Taken together, the above findings suggest that CAFs promote growth, migration and invasion of MDA-MB-231 cells via the paracrine FGF2-FGFR1 loop in the breast tumor microenvironment.

Resveratrol suppresses gastric cancer cell proliferation and survival through inhibition of PIM-1 kinase activity.

The proviral integration site for Moloney murine leukemia virus (PIM) family of serine/threonine-specific kinases consist of three isoforms, that regulate proliferation, apoptosis, metabolism, invasion, and metastasis of cancer cells. Among these, abnormally elevated kinase activity of PIM-1 contributes to the progression of gastric cancer and predicts poor prognosis and a low survival rate in gastric cancer patients. In the present study, we found that resveratrol, one of the representative chemopreventive and anticarcinogenic phytochemicals, directly binds to PIM-1 and thereby inhibits its catalytic activity in human gastric cancer SNU-601 cells. This resulted in suppression of phosphorylation of the proapoptotic Bad, a known substrate of PIM-1. Resveratrol, by inactivating PIM-1, also inhibited anchorage-independent growth and proliferation of SNU-601 cells. To understand the molecular interaction between resveratrol and PIM-1, we conducted docking simulation and found that resveratrol directly binds to the PIM-1 at the ATP-binding pocket. In conclusion, the proapototic and anti-proliferative effects of resveratrol in gastric cancer cells are likely to be mediated through suppression of PIM-1 kinase activity, which may represent a novel mechanism underlying its chemopreventive and anticarcinogenic actions.

Assessing alignment between functional markers and ordinal outcomes based on broad sense agreement.

Functional markers and their quantitative features (eg, maximum value, time to maximum, area under the curve [AUC], etc) are increasingly being used in clinical studies to diagnose diseases. It is thus of interest to assess the diagnostic utility of functional markers by assessing alignment between their quantitative features and an ordinal gold standard test that reflects the severity of disease. The concept of broad sense agreement (BSA) has recently been introduced for studying the relationship between continuous and ordinal measurements, and provides a promising tool to address such a question. Our strategy is to adopt a general class of summary functionals (SFs), each of which flexibly captures a different quantitative feature of a functional marker, and study its alignment according to an ordinal outcome via BSA. We further illustrate the proposed framework using three special classes of SFs (AUC-type, magnitude-specific, and time-specific) that are widely used in clinical settings. The proposed BSA estimator is proven to be consistent and asymptotically normal given a consistent estimator for the SF. We further provide an inferential framework for comparing a pair of candidate SFs in terms of their importance on the ordinal outcome. Our simulation results demonstrate satisfactory finite-sample performance of the proposed framework. We demonstrate the application of our methods using a renal study.

Role of heme oxygenase-1 in potentiation of phagocytic activity of macrophages by taurine chloramine: Implications for the resolution of zymosan A-induced murine peritonitis.

Phagocytosis of pathogens by macrophages is crucial for the successful resolution of inflammation induced by microbial infection. Taurine chloramine (TauCl), an endogenous anti-inflammatory and antioxidative substance, is produced by reaction between taurine and hypochlorous acid by myeloperoxidase activity in neutrophils under inflammatory conditions. In the present study, we investigated the effect of TauCl on resolution of acute inflammation caused by fungal infection using a zymosan A-induced murine peritonitis model. TauCl administration reduced the number of the total peritoneal leukocytes, while it increased the number of peritoneal monocytes. Furthermore, TauCl promoted clearance of pathogens remaining in the inflammatory environment by macrophages. When the macrophages isolated from thioglycollate-treated mice were treated with TauCl, their phagocytic capability was enhanced. In the murine macrophage-like RAW264.7 cells treated with TauCl, the proportion of macrophages clearing the zymosan A particles was also increased. TauCl administration resulted in elevated expression of heme oxygenase-1 (HO-1) in the peritoneal macrophages. Pharmacologic inhibition of HO-1 activity or knockdown of HO-1 in the murine macrophage RAW264.7 cells abolished the TauCl-induced phagocytosis, whereas the overexpression of HO-1 augmented the phagocytic ability of macrophages. Moreover, peritoneal macrophages isolated from HO-1 null mice failed to mediate TauCl-induced phagocytosis. Our results suggest that TauCl potentiates phagocytic activity of macrophages through upregulation of HO-1 expression.

Overall indices for assessing agreement among multiple raters.

The need to assess agreement exists in various clinical studies where quantifying inter-rater reliability is of great importance. Use of unscaled agreement indices, such as total deviation index and coverage probability (CP), is recommended for two main reasons: (i) they are intuitive in a sense that interpretations are tied to the original measurement unit; (ii) practitioners can readily determine whether the agreement is satisfactory by directly comparing the value of the index to a prespecified tolerable CP or absolute difference. However, the unscaled indices were only defined in the context of comparing two raters or multiple raters that assume homogeneity of variances across raters. In this paper, we introduce a set of overall indices based on the root mean square of pairwise differences that are unscaled and can be used to evaluate agreement among multiple raters that often exhibit heterogeneous measurement processes in practice. Furthermore, we propose another overall agreement index based on the root mean square of pairwise differences that is scaled and extends the concept of the recently proposed relative area under CP curve in the presence of multiple raters. We present the definitions of overall indices and propose inference procedures in which bootstrap methods are used for the estimation of standard errors. We assess the performance of the proposed approach and demonstrate its superiority over the existing methods when raters exhibit heterogeneous measurement processes using simulation studies. Finally, we demonstrate the application of our methods using a renal study.

Aschantin targeting on the kinase domain of mammalian target of rapamycin suppresses epidermal growth factor-induced neoplastic cell transformation.

Mammalian target of rapamycin (mTOR), a serine/threonine protein kinase, forms two different complexes, complex 1 and 2, and plays a key role in the regulation of Akt signaling-mediated cell proliferation and transformation. This study reveals aschantin, a natural compound abundantly found in Magnolia flos, as a novel mTOR kinase inhibitor. Aschantin directly targeted the active pocket of mTOR kinase domain by competing with adenosine triphosphate (ATP), but not PI3K and PDK1. Aschantin inhibited epidermal growth factor (EGF)-induced full activation of Akt by phosphorylation at Ser473/Thr308, resulting in inhibition of the mTORC2/Akt and Akt/mTORC1/p70S6K signaling pathways and activation of GSK3ß by abrogation of Akt-mediated GSK3ß phosphorylation at Ser9. The activated GSK3ß inhibited cell proliferation by c-Jun phosphorylation at Ser243, which facilitated destabilization and degradation of c-Jun through the ubiquitination-mediated proteasomal degradation pathway. Notably, aschantin treatment decreased c-Jun stability through inhibition of the mTORC2-Akt signaling pathway, which suppressed EGF-induced anchorage-independent cell transformation in non-malignant JB6 Cl41 and HaCaT cells and colony growth of LNCaP and MIAPaCa-2 cancer cells in soft agar. Altogether, the results show that aschantin targets mTOR kinase and destabilizes c-Jun, which implicate aschantin as a potential chemopreventive or therapeutic agent.

Magnolin inhibits cell migration and invasion by targeting the ERKs/RSK2 signaling pathway.

BACKGROUND: Magnolin is a natural compound abundantly found in Magnolia flos, which has been traditionally used in oriental medicine to treat headaches, nasal congestion and anti-inflammatory reactions. Our recent results have demonstrated that magnolin targets the active pockets of ERK1 and ERK2, which are important signaling molecules in cancer cell metastasis. The aim of this study is to evaluate the effects of magnolin on cell migration and to further explore the molecular mechanisms involved. METHODS: Magnolin-mediated signaling inhibition was confirmed by Western blotting using RSK2(+/+) and RSK2(-/-) MEFs, A549 and NCI-H1975 lung cancer cells, and by NF-κB and Cox-2 promoter luciferase reporter assays. Inhibition of cell migration by magnolin was examined by wound healing and/or Boyden Chamber assays using JB6 Cl41 and A549 human lung cancer cells. The molecular mechanisms involved in cell migration and epithelial-to-mesenchymal transition were determined by zymography, Western blotting, real-time PCR and immunocytofluorescence. RESULTS: Magnolin inhibited NF-κB transactivation activity by suppressing the ERKs/RSK2 signaling pathway. Moreover, magnolin abrogated the increase in EGF-induced COX-2 protein levels and wound healing. In human lung cancer cells such as A549 and NCI-H1975, which harbor constitutive active Ras and EGFR mutants, respectively, magnolin suppressed wound healing and cell invasion as seen by a Boyden chamber assay. In addition, it was observed that magnolin inhibited MMP-2 and -9 gene expression and activity. The knockdown or knockout of RSK2 in A549 lung cancer cells or MEFs revealed that magnolin targeting ERKs/RSK2 signaling suppressed epithelial-to-mesenchymal transition by modulating EMT marker proteins such as N-cadherin, E-cadherin, Snail, Vimentin and MMPs. CONCLUSIONS: These results demonstrate that magnolin inhibits cell migration and invasion by targeting the ERKs/RSK2 signaling pathway.

Assessing Trends in Hospitalizations for Breast Cancer among Women in Korea: A Utilization of the Korea National Hospital Discharge In-depth Injury Survey (2006-2020).

OBJECTIVE: Breast cancer poses a significant health threat globally and particularly in Korea, where mortality rates have risen notably. In this study, we analyzed the characteristics of breast cancer patients discharged in Korea over the past 15 years and explored the association between comorbidities and treatment outcomes to propose effective strategies for managing cancer patients. Understanding these dynamics is vital for informing tailored management strategies and optimizing healthcare system sustainability. METHODS: This study utilized cross-sectional data from the Korea National Hospital Discharge In-depth Injury Survey from 2006 to 2020. Each year, among patients discharged from hospital with 100 beds or more, those identified with breast cancer patients were based on their primary diagnosis code (C50) according to the ICD-10, as recorded in their medical records. RESULTS: Between 2006 and 2020, an estimated 499,281 breast cancer patients were discharged, with an average annual percent change (AAPC) of 5.2% (95% CI 4.2-6.2, p <.05). A notable increase in AAPC was particularly evident among those aged 60 years and old. Across all age groups, there was a consistent increasing trend in the risk of mortality as the CCI score increased (p <.05). The risk of comorbidity was more pronounced in younger age groups compared to older age groups. CONCLUSIONS: The increasing life expectancy is expected to lead to a continued rise in the number of elderly breast cancer patients. Countermeasures are needed to address this trend through appropriate diagnosis and treatment planning. Particularly, considering comorbidities in breast cancer treatment plans is necessary to promote positive treatment outcomes, especially in younger breast cancer patients.

Assessing intra- and inter-method agreement of functional data.

Modern medical devices are increasingly producing complex data that could offer deeper insights into physiological mechanisms of underlying diseases. One type of complex data that arises frequently in medical imaging studies is functional data, whose sampling unit is a smooth continuous function. In this work, with the goal of establishing the scientific validity of experiments involving modern medical imaging devices, we focus on the problem of evaluating reliability and reproducibility of multiple functional data that are measured on the same subjects by different methods (i.e. different technologies or raters). Specifically, we develop a series of intraclass correlation coefficient and concordance correlation coefficient indices that can assess intra-method, inter-method, and total (intra + inter) agreement based on multivariate multilevel functional data consisting of replicated functional data measurements produced by each of the different methods. For efficient estimation, the proposed indices are expressed using variance components of a multivariate multilevel functional mixed effect model, which can be smoothly estimated by functional principal component analysis. Extensive simulation studies are performed to assess the finite-sample properties of the estimators. The proposed method is applied to evaluate the reliability and reproducibility of renogram curves produced by a high-tech radionuclide image scan used to non-invasively detect kidney obstruction.

Domperidone, a Dopamine Receptor D2 Antagonist, Induces Apoptosis by Inhibiting the ERK/STAT3-Mediated Pathway in Human Colon Cancer HCT116 Cells.

Colorectal cancer (CRC) continues to demonstrate high incidence and mortality rates, emphasizing that implementing strategic measures for prevention and treatment is crucial. Recently, the dopamine receptor D2 (DRD2), a G protein-coupled receptor, has been reported to play multiple roles in growth of tumor cells. This study investigated the anticancer potential of domperidone, a dopamine receptor D2 antagonist, in HCT116 human CRC cells. Domperidone demonstrated concentration- and time-dependent reductions in cell viability, thereby inducing apoptosis. The molecular mechanism revealed that domperidone modulated the mitochondrial pathway, decreasing mitochondrial Bcl-2 levels, elevating cytosolic cytochrome C expression, and triggering caspase- 3, -7, and -9 cleavage. Domperidone decreased in formation of ß-arrestin2/MEK complex, which contributing to inhibition of ERK activation. Additionally, treatment with domperidone diminished JAK2 and STAT3 activation. Treatment of U0126, the MEK inhibitor, resulted in reduced phosphorylation of MEK, ERK, and STAT3 without alteration of JAK2 activation, indicating that domperidone targeted both MEK-ERK-STAT3 and JAK2-STAT3 signaling pathways, respectively. Immunoblot analysis revealed that domperidone also downregulated DRD2 expression. Domperidone-induced reactive oxygen species (ROS) generation and N-acetylcysteine treatment mitigated ROS levels and restored cell viability. An in vivo xenograft study verified the significant antitumor effects of domperidone. These results emphasize the multifaceted anticancer effects of domperidone, highlighting its potential as a promising therapeutic agent for human CRC.