Topics in analyzing longitudinal data

We propose methods for analyzing longitudinal data, obtained in clinical trials and other applications with repeated measures of responses taken over time. Common characteristics of longitudinal studies are correlated responses and observations taken at unequal points in time. The first part of this dissertation examines the justification of a block bootstrap procedure for the repeated measurement designs, which takes into account the dependence structure of the data by resampling blocks of adjacent observations rather than individual data points. In the case of dependent stationary data, under regular conditions, the approximately studentized or standardized block bootstrap possesses a higher order of accuracy. With longitudinal data, the second part of this dissertation shows that the diagonal optimal weights for unbalanced designs can be made to improve the efficiency of the estimators in terms of mean squared error criterion. Simulation study is conducted for each of the longitudinal designs. We will also analyze repeated measurement data set concerning nursing home residents with multiple sclerosis, which is obtained from a large database termed the minimum data set (MDS)

Context-Preserving Two-Stage Video Domain Translation for Portrait Stylization

Portrait stylization, which translates a real human face image into an artistically stylized image, has attracted considerable interest and many prior works have shown impressive quality in recent years. However, despite their remarkable performances in the image-level translation tasks, prior methods show unsatisfactory results when they are applied to the video domain. To address the issue, we propose a novel two-stage video translation framework with an objective function which enforces a model to generate a temporally coherent stylized video while preserving context in the source video. Furthermore, our model runs in real-time with the latency of 0.011 seconds per frame and requires only 5.6M parameters, and thus is widely applicable to practical real-world applications.Comment: 5 pages, 3 figures, CVPR 2023 Workshop on AI for Content Creatio

The socio-spatial neighborhood estimation method: An approach to operationalizing the neighborhood concept

The literature on neighborhoods and health highlights the difficulty of operationalizing "neighborhood" in a conceptually and empirically valid manner. Most studies, however, continue to define neighborhoods using less theoretically relevant boundaries, risking erroneous inferences from poor measurement. We review an innovative methodology to address this problem, called the socio-spatial neighborhood estimation method (SNEM). To estimate neighborhood boundaries, researchers used a theoretically informed combination of qualitative GIS and on-the-ground observations in Texas City, Texas. Using data from a large sample, we assessed the SNEM-generated neighborhood units by comparing intra-class correlation coefficients (ICCs) and multi-level model parameter estimates of SNEM-based measures against those for census block groups and regular grid cells. ICCs and criterion-related validity evidence using SF-36 outcome measures indicate that the SNEM approach to operationalization could improve inferences based on neighborhoods and health research

Problem Drinking among Mexican-Americans: The Influence of Nativity and Neighborhood Context?

We examined the influence of nativity and community context (Hispanic neighborhood concentration) on two measures of problem drinking among Mexican-Americans

Paricalcitol Pretreatment Attenuates Renal Ischemia-Reperfusion Injury via Prostaglandin E 2

The protective mechanism of paricalcitol remains unclear in renal ischemia-reperfusion (IR) injury. We investigated the renoprotective effects of paricalcitol in IR injury through the prostaglandin E2 (PGE2) receptor EP4. Paricalcitol was injected into IR-exposed HK-2 cells and mice subjected to bilateral kidney ischemia for 23 min and reperfusion for 24 hr. Paricalcitol prevented IR-induced cell death and EP4 antagonist cotreatment offset these protective effects. Paricalcitol increased phosphorylation of Akt and cyclic AMP responsive element binding protein (CREB) and suppressed nuclear factor-κB (NF-κB) in IR-exposed cells and cotreatment of EP4 antagonist or EP4 small interfering RNA blunted these signals. In vivo studies showed that paricalcitol improved renal dysfunction and tubular necrosis after IR injury and cotreatment with EP4 antagonist inhibited the protective effects of paricalcitol. Phosphorylation of Akt was increased and nuclear translocation of p65 NF-κB was decreased in paricalcitol-treated mice with IR injury, which was reversed by EP4 blockade. Paricalcitol decreased oxidative stress and apoptosis in renal IR injury. Paricalcitol also attenuated the infiltration of inflammatory cells and production of proinflammatory cytokines after IR injury. EP4 antagonist abolished these antioxidant, anti-inflammatory, and antiapoptotic effects. The EP4 plays a pivotal role in the protective effects of paricalcitol in renal IR injury

Elevated IFNA1 and suppressed IL12p40 associated with persistent hyperinflammation in COVID-19 pneumonia

IntroductionDespite of massive endeavors to characterize inflammation in COVID-19 patients, the core network of inflammatory mediators responsible for severe pneumonia stillremain remains elusive. MethodsHere, we performed quantitative and kinetic analysis of 191 inflammatory factors in 955 plasma samples from 80 normal controls (sample n = 80) and 347 confirmed COVID-19 pneumonia patients (sample n = 875), including 8 deceased patients. ResultsDifferential expression analysis showed that 76% of plasmaproteins (145 factors) were upregulated in severe COVID-19 patients comparedwith moderate patients, confirming overt inflammatory responses in severe COVID-19 pneumonia patients. Global correlation analysis of the plasma factorsrevealed two core inflammatory modules, core I and II, comprising mainly myeloid cell and lymphoid cell compartments, respectively, with enhanced impact in a severity-dependent manner. We observed elevated IFNA1 and suppressed IL12p40, presenting a robust inverse correlation in severe patients, which was strongly associated with persistent hyperinflammation in 8.3% of moderate pneumonia patients and 59.4% of severe patients. DiscussionAberrant persistence of pulmonary and systemic inflammation might be associated with long COVID-19 sequelae. Our comprehensive analysis of inflammatory mediators in plasmarevealed the complexity of pneumonic inflammation in COVID-19 patients anddefined critical modules responsible for severe pneumonic progression