imputation

BACKGROUND AND OBJECTIVES: The cognitive reserve hypothesis posits that cognitively stimulating work delays the onset of mild cognitive impairment (MCI) and dementia. However, the effect of occupational cognitive demands across midlife on the risk of these conditions is unclear. METHODS: Using a cohort study design, we evaluated the association between registry-based trajectories of occupational cognitive demands from ages 30-65 years and clinically diagnosed MCI and dementia in participants in the HUNT4 70+ Study (2017-19)...

Modern spatial temporal data are often collected from sensor networks. Missing data problems are common to this kind of data. Making accurate imputation is important for many applications. In the unsupervised setting, one technique is to minimize the rank of a tensor or matrix. If we add related covariates, can we get more accurate imputation results? To address this, we transform the original sensor×time measurements to high order tensors by adding additional temporal dimensions and then integrate tensor regression with tensor completion using nuclear norm penalty...

Spatial transcriptomics (ST) has become a powerful tool for exploring the spatial organization of gene expression in tissues. Imaging-based methods, though offering superior spatial resolutions at the single-cell level, are limited in either the number of imaged genes or the sensitivity of gene detection. Existing approaches for enhancing ST rely on the similarity between ST cells and reference single-cell RNA sequencing (scRNA-seq) cells. In contrast, we introduce stDiff, which leverages relationships between gene expression abundance in scRNA-seq data to enhance ST...

Comprehensive expression quantitative trait loci studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein quantitative trait loci in brain, cerebrospinal fluid, and plasma. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high quality imputed genetic variants (8...

BACKGROUND: Phenome-wide association studies (PheWASs) have been conducted on Asian populations, including Koreans, but many were based on chip or exome genotyping data. Such studies have limitations regarding whole genome-wide association analysis, making it crucial to have genome-to-phenome association information with the largest possible whole genome and matched phenome data to conduct further population-genome studies and develop health care services based on population genomics...

The time-varying effective reproduction number Rt is a widely used indicator of transmission dynamics during infectious disease outbreaks. Timely estimates of Rt can be obtained from reported cases counted by their date of symptom onset, which is generally closer to the time of infection than the date of report. Case counts by date of symptom onset are typically obtained from line list data, however these data can have missing information and are subject to right truncation. Previous methods have addressed these problems independently by first imputing missing onset dates, then adjusting truncated case counts, and finally estimating the effective reproduction number...

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are widely detected in pregnant women and associated with adverse outcomes related to impaired placental function. Human chorionic gonadotropin (hCG) is a dimeric glycoprotein hormone that can indicate placental toxicity. OBJECTIVES: Our aim was to quantify the association of serum PFAS with placental hCG, measured as an intact molecule (hCG), as free alpha-(<mml:math xmlns:mml="https://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mtext>hCG</mml:mtext><mml:mi>α</mml:mi></mml:mrow></mml:math>) and beta-subunits (<mml:math xmlns:mml="https://www...

Missing data is a common challenge when analyzing epidemiological data, and imputation is often used to address this issue. Here, we investigate the scenario where a covariate used in an analysis has missingness and will be imputed. There are recommendations to include the outcome from the analysis model in the imputation model for missing covariates, but it is not necessarily clear if this recommendation always holds and why this is sometimes true. We examine deterministic imputation (i.e. single imputation with fixed values) and stochastic imputation (i...

In this study, we explored spatial-temporal dependencies and their impact on the tactile perception of moving objects. Building on previous research linking visual perception and human movement, we examined if an imputed motion mechanism operates within the tactile modality. We focused on how biological coherence between space and time, characteristic of human movement, influences tactile perception. An experiment was designed wherein participants were stimulated on their right palm with tactile patterns, either ambiguous (incongruent conditions) or non-ambiguous (congruent conditions) relative to a biological motion law (two-thirds power law) and asked to report perceived shape and associated confidence...

Purpose This study delves into the epidemiology of high-risk human papillomavirus (HR-HPV) infection and its link to precancerous lesions among perimenopausal (40-59 years) and elderly (60-65 years) women in a Chinese county with a notably high incidence of cervical cancer. By uniquely focusing on these age groups in underdeveloped regions, the research aims to offer novel strategies for the management and prevention of cervical cancer. It seeks to inform targeted interventions and public health policies that could significantly benefit women at heightened risk for HPV, addressing a critical gap in current prevention efforts in economically disadvantaged communities...

BACKGROUND: Valoctocogene roxaparvovec transfers a human factor VIII (FVIII) coding sequence into hepatocytes of people with severe hemophilia A to provide bleeding protection. OBJECTIVE: Present 3-year efficacy and safety in the multicenter, open-label, single-arm, phase 3 GENEr8-1 trial. METHODS: GENEr8-1 enrolled 134 adult males with severe hemophilia A who were receiving FVIII prophylaxis. Efficacy endpoints included annualized bleeding rate (ABR), annualized FVIII utilization (AFU), FVIII activity (chromogenic substrate assay; imputed as 1 IU/dL at baseline and 0 IU/dL after discontinuation), and the Haemophilia-Specific Quality of Life Questionnaire for Adults (Haemo-QOL-A)...

OBJECTIVES: Prognostication for cerebral venous thrombosis (CVT) remains difficult. We sought to validate the SI2 NCAL2 C score in an international cohort. MATERIALS AND METHODS: The SI2 NCAL2 C score was originally developed to predict poor outcome (modified Rankin Scale (mRS) 3-6) at 6 months, and mortality at 30 days and 1 year using data from the International CVT Consortium. The SI2 NCAL2 C score uses 9 variables: the absence of any female-sex-specific risk factors, intracerebral hemorrhage, central nervous system infection, focal neurological deficits, coma, age, lower level of hemoglobin, higher level of glucose, and cancer...

Previous research has indicated an association between the presence of the vitamin D receptor (VDR) in breast cancer tissue and a favorable prognosis. This study aimed to further evaluate the prognostic potential of VDR located in the nuclear membrane or nucleus (liganded). The VDR protein levels were analyzed using immunohistochemistry in tumor samples from 878 breast cancer patients from Lund, Sweden, included in the Breast Cancer and Blood Study (BCBlood) from October 2002 to June 2012. The follow-up for breast cancer events and overall survival was recorded until 30 June 2019...

Congestive heart failure (CHF) is one of the primary sources of mortality and morbidity among the global population. Over 26 million individuals globally are affected by heart disease, and its prevalence is rising by 2% yearly. With advances in healthcare technologies, if we predict CHF in the early stages, one of the leading global mortality factors can be reduced. Therefore, the main objective of this study is to use machine learning applications to enhance the diagnosis of CHF and to reduce the cost of diagnosis by employing minimum features to forecast the possibility of a CHF occurring...

OBJECTIVE: We attempted to identify abnormal immune cell components and signaling pathways in lupus nephritis (LN) and to identify potential therapeutic targets. METHODS: Differentially expressed genes (DEGs) between LN and normal kidney tissues were identified from bulk transcriptome data, and functional annotation was performed. The phenotypic changes in macrophages and aberrant intercellular signaling communications within immune cells were imputed from LN scRNA-seq data using trajectory analysis and verified using immunofluorescence staining...

BACKGROUND: The observed increase in the incidence of complicated diverticulitis may lead to the performance of more emergency surgeries. This study aimed to assess the rate and risk factors of emergency surgery for sigmoid diverticulitis. METHOD: The primary outcomes were the rate of emergency surgery for sigmoid diverticulitis and its associated risk factors. The urgent or elective nature of the surgical intervention was provided by the surgeon and in accordance with the indication for surgical treatment...

Tackling the impact of missing data in water management is crucial to ensure the reliability of scientific research that informs decision-making processes in public health. The goal of this study is to ascertain the root causes associated with cyanobacteria proliferation under major missing data scenarios. For this purpose, a dynamic missing data management methodology is proposed using Bayesian Machine Learning for accurate surface water quality prediction of a river from Limia basin (Spain). The methodology used entails a sequence of analytical steps, starting with data pre-processing, followed by the selection of a reliable dynamic Bayesian missing value prediction system, leading finally to a supervised analysis of the behavioral patterns exhibited by cyanobacteria...

The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models, despite their potential, lack comprehensive genetic data. This inadequacy fuels our research focus-integrating specific genetic information, such as pathway scores, into clinical data. Our aim is to refine machine learning models for more precise relapse prediction in early-stage non-small cell lung cancer...

By generating massive gene transcriptome data and analyzing transcriptomic variations at the cell level, single-cell RNA-sequencing (scRNA-seq) technology has provided new way to explore cellular heterogeneity and functionality. Clustering scRNA-seq data could discover the hidden diversity and complexity of cell populations, which can aid to the identification of the disease mechanisms and biomarkers. In this paper, a novel method (DSINMF) is presented for single cell RNA sequencing data by using deep matrix factorization...

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis...