Control of Weekly Time Trend in Time-Stratified Case-Crossover Design

Case-crossover designs have become widespread in biomedical investigations of transient associations. However, the most popular reference-selection strategy - the time-stratified scheme - may not be an optimum solution to control systematic bias in case-crossover studies. To prove this, we conducted a time series decomposition for daily ozone records and examined the capability of the time-stratified scheme to control for yearly, monthly, and weekly time trends; and observed its failure on the control for the weekly time trend. To solve this issue, we proposed a new logistic regression approach in which we suggest the adjustment for the weekly time trend. We compared the performance of the proposed with that of the traditional method by simulation. We further conducted an empirical study to explore the performance of the new logistic regression approach in examining potential associations between ambient air pollutants and acute myocardial infarction hospitalizations. The time-stratified scheme provides effective control for yearly and monthly time trends but not of the weekly time trend. Uncontrolled weekly time trends could be the dominant source of systematic bias in time-stratified case-crossover studies. In contrast, the proposed logistic regression approach can effectively minimize systematic bias in a case-crossover study.

Explaining Deep Neural Network Models with Adversarial Gradient Integration

Deep neural networks (DNNs) have became one of the most high performing tools in a broad range of machine learning areas. However, the multilayer non-linearity of the network architectures prevent us from gaining a better understanding of the models’ predictions. Gradient based attribution methods (e.g., Integrated Gradient (IG)) that decipher input features’ contribution to the prediction task have been shown to be highly effective yet requiring a reference input as the anchor for explaining model’s output. The performance of DNN model interpretation can be quite inconsistent with regard to the choice of references. Here we propose an Adversarial Gradient Integration (AGI) method that integrates the gradients from adversarial examples to the target example along the curve of steepest ascent to calculate the resulting contributions from all input features. Our method doesn’t rely on the choice of references, hence can avoid the ambiguity and inconsistency sourced from the reference selection. We demonstrate the performance of our AGI method and compare with competing methods in explaining image classification results. Code is available from https://github.com/pd90506/AGI.

Suitable reference genes selection for reliable normalization of gene expression in melanoma: implementation of an innovative GenExpA software

Melanoma is characterized by a high mutation rate and the proper reference selection is a serious problem. The algorithms commonly used to select the best stable reference gene or pair of genes in RT-qPCR data analysis have their limitations which affects the interpretation of the results and drawing conclusions. For reliable assessment of the B4GALT genes expression changes in melanoma and comparing them to their expression levels in melanocytes, we implemented an innovative GenExpA software. We proposed selection of the best reference by combining the NormFinder algorithm with progressive removal of the least stable gene from the candidate genes in a given experimental model and the set of daughter models assigned to it. The reliability of references is validated by normalizing of target gene expression level through all models and is described by the coherence score. The software performs statistical analyses and generates results in the form of ready-to-use graphs and tables. GenExpA is a promising tool for basic research; it produces analyses of target gene expression in a manner independent of the experimental model and the normalizer. GenExpA and its manual is freely available at https://drive.google.com/drive/folders/1FcpBtEc_bKPvEnM5GcPZerBb_Tw_fCkt?usp=sharing or https://www.sciencemarket.pl/baza-programow-open-source#oferty. Supplemental materials are deposited under DOI number: 10.5281/zenodo.4544296.

TRACE

The deployment of vehicle location services generates increasingly massive vehicle trajectory data, which incurs high storage and transmission costs. A range of studies target offline compression to reduce the storage cost. However, to enable online services such as real-time traffic monitoring, it is attractive to also reduce transmission costs by being able to compress streaming trajectories in real-time. Hence, we propose a framework called TRACE that enables compression, transmission, and querying of network-constrained streaming trajectories in a fully online fashion. We propose a compact two-stage representation of streaming trajectories: a speed-based representation removes redundant information, and a multiple-references based referential representation exploits subtrajectory similarities. In addition, the online referential representation is extended with reference selection, deletion and rewriting functions that further improve the compression performance. An efficient data transmission scheme is provided for achieving low transmission overhead. Finally, indexing and filtering techniques support efficient real-time range queries over compressed trajectories. Extensive experiments with real-life and synthetic datasets evaluate the different parts of TRACE, offering evidence that it is able to outperform the existing representative methods in terms of both compression ratio and transmission cost.

Comparative efficacy and side-effect profile of ketamine and esketamine in the treatment of unipolar and bipolar depression: protocol for a systematic review and network meta-analysis

IntroductionDespite a range of antidepressant drugs and therapies, approximately one-third of patients fail to achieve meaningful recovery, prompting the urgent need for more effective treatment for depression. Several open-label studies randomised controlled trials (RCTs) and meta-analyses have been conducted to confirm the therapeutic efficacy and side effects of ketamine and esketamine. Esketamine is (S)- enantiomer of ketamine; however, there is limited evidence comparing esketamine and ketamine in treating unipolar and bipolar depression have been published so far.Methods and analysisWe will include all double-blind RCTs comparing efficacy and side-effect profile of ketamine and esketamine in the treatment of unipolar and bipolar depression. Our primary outcomes will be study-defined response at endpoint assessment; dropouts due to adverse events and other adverse drug reactions. Published studies will be retrieved through relevant database searches. Reference selection and data extraction will be independently completed by two investigators, resolving inconsistencies by consensus or a discussion with the third investigator. For each outcome, we will undertake a network meta-analysis to synthesise all evidence. Local and global methods will be used to evaluate consistency. We will assess the quality of evidence contributing to network estimates with the Confidence in Network Meta-Analysis web application.Ethics and disseminationThis work does not require ethics approval as it will be based on published studies. This review will be published in peer-reviewed journals.PROSPERO registration numberCRD42020201559.

Acting hot or not? Testing the citing to show-off hypothesis

PurposeCitation analysis as a method for studying scientific communication is frequently criticized for being based on biased citation practices. Questionable motives for the reference selection have been suggested including the claim that authors tend to cite hot papers in order to show-off. In this study, the authors investigate the claim that authors tend to cite the recent literature in order to show-off.Design/methodology/approachFollowing Moed and Garfield (2004), the authors investigate the claim by analyzing the proportion of recent references as a function of the length of the reference lists of citing papers. The authors analyze reference lists of citing papers in the fields of biomedical engineering, economics, medicine, psychology and library and information science between 2010 and 2019. From each of these fields, a number of journals are included in the analysis to represent the field. In total, 42 journals are included in the analyses comprising a selection of almost 65,000 journal articles. The proportion of recent references is calculated using two citation windows. The proportion of recent references as a function of the length of the reference lists is calculated through simple linear regressions to predict the share of recent references based on the number of references.FindingsThe results of the linear regressions indicate that in most cases, there are a statistically significant relationship between the share of recent references and the number of references. This study’s results show that when authors display selective referencing behavior, references to the recent literature tend to be only marginally increased, and some results even display the opposite tendency (marginally overciting the older literature).Originality/valueThis study of the claim that authors tend to cite the recent literature in order to show-off does not confirm the hypothesis.

Selection of internal references for transcriptomics and RT-qPCR assays in Neurofibromatosis type 1 (NF1) related Schwann cell lines

Transcriptomics has been widely applied in uncovering disease mechanisms and screening potential biomarkers. Internal reference selection determines the accuracy and reproducibility of data analyses. The aim of this study was to identify the most qualified reference genes for the relative quantitation analysis of transcriptomics and real-time quantitative reverse-transcription PCR in fourteen NF1 related cell lines, including non-tumor, benign and malignant Schwann cell lines. The expression characteristics of eleven candidate reference genes (RPS18, ACTB, B2M, GAPDH, PPIA, HPRT1, TBP, UBC, RPLP0, TFRC and RPL32) were screened and analyzed by four software programs: geNorm, NormFinder, BestKeeper and RefFinder. Results showed that GAPDH, the most used internal reference gene, was significantly unstable. The combinational use of two reference genes (PPIA and TBP) was optimal in malignant Schwann cell lines and the use of single reference genes (PPIA or PRLP0) alone or in combination was optimal in benign Schwann cell lines. Our recommended internal reference genes may improve the accuracy and reproducibility of the results of transcriptomics and real-time quantitative reverse-transcription PCR in further gene expression analyses of NF1 related tumors.