Positive False Discovery Rate Research Articles

Exact Integral Formulas for False Discovery Rate and the Variance of False Discovery Proportion.

Multiple hypothesis testing is an integral component of data analysis for large-scale technologies such as proteomics, transcriptomics, or metabolomics, for which the false discovery rate (FDR) and positive FDR (pFDR) have been accepted as error estimation and control measures. The pFDR is the expectation of false discovery proportion (FDP), which refers to the ratio of the number of null hypotheses to that of all rejected hypotheses. In practice, the expectation of ratio is approximated by the ratio of expectation; however, the conditions for transforming the former into the latter have not been investigated. This work derives exact integral expressions for the expectation (pFDR) and variance of FDP. The widely used approximation (ratio of expectations) is shown to be a particular case (in the limit of a large sample size) of the integral formula for pFDR. A recurrence formula is provided to compute the pFDR for a predefined number of null hypotheses. The variance of FDP was approximated for a practical application in peptide identification using forward and reversed protein sequences. The simulations demonstrate that the integral expression exhibits better accuracy than the approximate formula in the case of a small number of hypotheses. For large sample sizes, the pFDRs obtained by the integral expression and approximation do not differ substantially. Applications to proteomics data sets are included.

Does Behavior Evolve First? Correlated Responses to Selection for Voluntary Wheel-Running Behavior in House Mice.

AbstractHow traits at multiple levels of biological organization evolve in a correlated fashion in response to directional selection is poorly understood, but two popular models are the very general "behavior evolves first" (BEF) hypothesis and the more specific "morphology-performance-behavior-fitness" (MPBF) paradigm. Both acknowledge that selection often acts relatively directly on behavior and that when behavior evolves, other traits will as well but most with some lag. However, this proposition is exceedingly difficult to test in nature. Therefore, we studied correlated responses in the high-runner (HR) mouse selection experiment, in which four replicate lines have been bred for voluntary wheel-running behavior and compared with four nonselected control (C) lines. We analyzed a wide range of traits measured at generations 20-24 (with a focus on new data from generation 22), coinciding with the point at which all HR lines were reaching selection limits (plateaus). Significance levels (226 P values) were compared across trait types by ANOVA, and we used the positive false discovery rate to control for multiple comparisons. This meta-analysis showed that, surprisingly, the measures of performance (including maximal oxygen consumption during forced exercise) showed no evidence of having diverged between the HR and C lines, nor did any of the life history traits (e.g., litter size), whereas body mass had responded (decreased) at least as strongly as wheel running. Overall, results suggest that the HR lines of mice had evolved primarily by changes in motivation rather than performance ability at the time they were reaching selection limits. In addition, neither the BEF model nor the MPBF model of hierarchical evolution provides a particularly good fit to the HR mouse selection experiment.

Reduced Cortico-Cortical Resting-State Connectivity in Sensory Systems Related to Bodily Pain in Juvenile Fibromyalgia.

Juvenile-onset fibromyalgia (JFM) is a paradigmatic chronic pain condition for which the underlying neurobiological substrates are poorly understood. This study examined, for the first time, data-driven resting-state functional connectivity (rsFC) alterations in 37 female adolescents with JFM compared with 43 healthy female adolescents and identified associations with bodily pain. Whole-brain voxel-wise rsFC alterations were assessed using the intrinsic connectivity contrast, a measure of node centrality at each voxel, and seed-based analyses for interpretability. We studied the relationship between rsFC alterations in somatosensory systems and the location and extension of bodily pain. Adolescents with JFM had voxel-wise rsFC reductions in the paracentral lobule (PCL)/primary somatosensory cortex (S1) (T=4.89, family-wise error corrected p-value (pFWE)< 0.001) and left midcingulate cortex (T=4.67, pFWE=0.043). Post hoc analyses revealed reduced rsFC spanning major cortical sensory hubs (T > 4.4, pFWE < 0.030). Cortico-cortical rsFC reductions within PCL/S1 in JFM occurred in locations innervated by bodily areas where the pain was most frequent (F=3.15; positive false discovery rate=0.029) and predicted widespread pain (T > 4.4, pFWE < 0.045). Conversely, adolescents with JFM had increases in PCL/S1-thalamus (T=4.75, pFWE=0.046) and PCL/S1-anterior insula rsFC (T=5.13, pFWE=0.039). Reduced cortico-cortical sensory integration involving PCL/S1 and spanning the sensory systems may underly critical pain sensory features in youth with JFM. Reduced sensory integration is paralleled by augmented cross-talk between sensory and affective/salience-processing regions, potentially indicating a shift toward more affectively colored sensory experiences to the detriment of specific sensory discrimination.

Evidence of Ongoing Cerebral Microstructural Reorganization in Children With Persisting Symptoms Following Mild Traumatic Brain Injury: A NODDI DTI Analysis.

Approximately 300-550 children per 100,000 sustain a mild traumatic brain injury (mTBI) each year, of whom ∼25-30% have long-term cognitive problems. Following mTBI, free water (FW) accumulation occurs in white matter (WM) tracts. Diffusion tensor imaging (DTI) can be used to investigate structural integrity following mTBI. Compared with conventional DTI, neurite orientation dispersion and density imaging (NODDI) orientation dispersion index (ODI) and fraction of isolated free water (FISO) metrics may allow a more advanced insight into microstructural damage following pediatric mTBI. In this longitudinal study, we used NODDI to explore whole-brain and tract-specific differences in ODI and FISO in children with persistent symptoms after mTBI (n = 80) and in children displaying clinical recovery (n = 32) at 1 and 2-3 months post-mTBI compared with healthy controls (HCs) (n = 21). Two-way repeated measures analysis of variance (ANOVA) and voxelwise two-sample t tests were conducted to compare whole-brain and tract-specific diffusion across groups. All results were corrected at positive false discovery rate (pFDR) <0.05. We also examined the association between NODDI metrics and clinical outcomes, using logistical regression to investigate the value of NODDI metrics in predicting future recovery from mTBI. Whole-brain ODI was significantly increased in symptomatic participants compared with HCs at both 1 and 2 months post-injury, where the uncinate fasciculus (UF) and inferior fronto-occipital fasciculus (IFOF) were particularly implicated. Using region of interest (ROI) analysis in significant WM, bilateral IFOF and UF voxels, symptomatic participants had the highest ODI in all ROIs. ODI was lower in asymptomatic participants, and HCs had the lowest ODI in all ROIs. No changes in FISO were found across groups or over time. WM ODI was moderately correlated with a higher youth-reported post-concussion symptom inventory (PCSI) score. With 87% predictive power, ODI (1 month post-injury) and clinical predictors (age, sex, PCSI score, attention scores) were a more sensitive predictor of recovery at 2-3 months post-injury than fractional anisotropy (FA) and clinical predictors, or clinical predictors alone. FISO could not predict recovery at 2-3 months post-injury. Therefore, we found that ODI was significantly increased in symptomatic children following mTBI compared with HCs at 1 month post-injury, and progressively decreased over time alongside clinical recovery. We found no significant differences in FISO between groups or over time. WM ODI at 1 month was a more sensitive predictor of clinical recovery at 2-3 months post-injury than FA, FISO, or clinical measures alone. Our results show evidence of ongoing microstructural reorganization or neuroinflammation between 1 and 2-3 months post-injury, further supporting delayed return to play in children who remain symptomatic. We recommend future research examining the clinical utility of NODDI following mTBI to predict recovery or persistence of post-concussion symptoms and thereby inform management of mTBI.

Informativeness of the doppler twinkling artifact in the diagnosis of urinary tract calculi

The kidney stone disease (nephrolithiasis, urolithiasis) is a common urological problem that affects both adults and children and has a high recurrence rate. Early and reliable imaging diagnosis of urolithiasis is important for early pain relief and the avoidance of complications that require surgical intervention. Non-contrast computed tomography is considered the method of choice in the diagnosis of urolithiasis, however, this method is associated with exposure to ionizing radiation. Ultrasound diagnostics or sonography, in contrast, is considered as the method of early diagnosis of urolithiasis that is widely spread, highly accessible and does not use ionizing radiation. Recently, the attention of sonographers has been attracted by the so-called twinkling artifact or the artifact of the colored comet tail, which occurs in the Doppler color flow mapping behind a calculus in the urinary tract. The twinkling artifact is a phenomenon of a rapid change (twinkle) of red and blue behind the calculus. Among adult patients, the artifact shows high sensitivity in finding urinary stones, but at the same time a high level of false-positive results. However, the sensitivity of the artifact in children is higher than in adults, whereas the rate of false-positive findings is much lower. According to many authors, the sensitivity and specificity of the twinkling artifact as an independent diagnostic sign of urolithiasis are both very heterogeneous, especially compared to non-contrast computed tomography. Nevertheless, the artifact is known to increase the diagnostic efficiency in stone detection to more than 90%. We believe that the twinkling artifact in the Doppler color flow mapping should always be considered as an additional diagnostic tool, which is complementary to B-mode ultrasonography and increases its sensitivity and specificity.

Diagnostic performance of additional imaging tests for staging purposes in a bicentric German series of low-risk early breast cancer patients

PurposeLow-risk early breast cancer rarely leads to the development of metastatic disease, and in these patients, additional imaging test is controversial. The aim of our study was to evaluate the conventional staging procedures in a bicentric German series of low-risk breast carcinoma patients.MethodsRetrospective evaluation of all patients diagnosed with early, low-risk breast cancer at Saarland University Hospital and Freiburg University Hospital in 2017 was performed. Clinical patient characteristics, the number and type of additional imaging examinations, follow-up examinations, and results were evaluated. The detection rate of metastases and the rate of false-positive findings were analyzed.ResultsA total of 203 patients were included, with all patients received at least one additional imaging test. Initially, a total of 562 additional imaging examinations were performed: 166 chest X-rays, 169 upper abdominal ultrasounds, 199 bone scans, 27 computer tomographies (CT) chest and abdomen, and 1 CT abdomen. 6.8% of patients had abnormal findings reported, requiring 38 additional imaging examinations. One patient (0.5%) was found to have bone metastases. The rate of false-positive findings in the performed additional imaging procedures was 6.6%.ConclusionMetastatic disease was detected in one of 203 patients with low-risk early breast cancer. A total of 562 examinations and additional 38 follow-up examinations were performed without detection of metastasis (this corresponds to approximately 3 examinations/patient). The rate of false-positive findings was 6.6%. The performance of additional imaging procedures for detection of distant metastases should be critically reconsidered in patients with low-risk early breast cancer.

Adjusting for gene-specific covariates to improve RNA-seq analysis.

This paper suggests a novel positive false discovery rate (pFDR) controlling method for testing gene-specific hypotheses using a gene-specific covariate variable, such as gene length. We suppose the null probability depends on the covariate variable. In this context, we propose a rejection rule that accounts for heterogeneity among tests by employing two distinct types of null probabilities. We establish a pFDR estimator for a given rejection rule by following Storey's q-value framework. A condition on a type 1 error posterior probability is provided that equivalently characterizes our rejection rule. We also present a suitable procedure for selecting a tuning parameter through cross-validation that maximizes the expected number of hypotheses declared significant. A simulation study demonstrates that our method is comparable to or better than existing methods across realistic scenarios. In data analysis, we find support for our method's premise that the null probability varies with a gene-specific covariate variable. Online supplementary material includes proofs of theorems, results of additional simulation and data analysis.

Improved Workflow for Analysis of Vascular Myocyte Time-Series and Line-Scan Ca2+ Imaging Datasets.

Intracellular Ca2+ signals are key for the regulation of cellular processes ranging from myocyte contraction, hormonal secretion, neural transmission, cellular metabolism, transcriptional regulation, and cell proliferation. Measurement of cellular Ca2+ is routinely performed using fluorescence microscopy with biological indicators. Analysis of deterministic signals is reasonably straightforward as relevant data can be discriminated based on the timing of cellular responses. However, analysis of stochastic, slower oscillatory events, as well as rapid subcellular Ca2+ responses, takes considerable time and effort which often includes visual analysis by trained investigators, especially when studying signals arising from cells embedded in complex tissues. The purpose of the current study was to determine if full-frame time-series and line-scan image analysis workflow of Fluo-4 generated Ca2+ fluorescence data from vascular myocytes could be automated without introducing errors. This evaluation was addressed by re-analyzing a published "gold standard" full-frame time-series dataset through visual analysis of Ca2+ signals from recordings made in pulmonary arterial myocytes of en face arterial preparations. We applied a combination of data driven and statistical approaches with comparisons to our published data to assess the fidelity of the various approaches. Regions of interest with Ca2+ oscillations were detected automatically post hoc using the LCPro plug-in for ImageJ. Oscillatory signals were separated based on event durations between 4 and 40 s. These data were filtered based on cutoffs obtained from multiple methods and compared to the published manually curated "gold standard" dataset. Subcellular focal and rapid Ca2+ "spark" events from line-scan recordings were examined using SparkLab 5.8, which is a custom automated detection and analysis program. After filtering, the number of true positives, false positives, and false negatives were calculated through comparisons to visually derived "gold standard" datasets. Positive predictive value, sensitivity, and false discovery rates were calculated. There were very few significant differences between the automated and manually curated results with respect to quality of the oscillatory and Ca2+ spark events, and there were no systematic biases in the data curation or filtering techniques. The lack of statistical difference in event quality between manual data curation and statistically derived critical cutoff techniques leads us to believe that automated analysis techniques can be reliably used to analyze spatial and temporal aspects to Ca2+ imaging data, which will improve experiment workflow.

68Ga-FAPI-46 PET for cancer imaging: A prospective single-arm clinical trial.

3064 Background: Fibroblast activation protein (FAP) is expressed at high levels on tumor associated fibroblasts. FAP-directed radioligand positron-emission-tomography (FAP-PET) is a novel diagnostic tool for cancer. However, we currently do not understand the diagnostic performance of FAP-PET as compared to standard FDG-PET. Here we aim to compare tumor detection by FDG- vs. FAP-PET with independent validation of discrepant findings. Methods: Patients with (a) proven or suspected malignancy, (b) longest tumor diameter &gt;1 cm, (c) intended surgery or biopsy, and (d) no prior external beam radiation or systemic tumor therapy within 3 months underwent FDG- and FAP-PET for tumor localization on subsequent days. Clinical reads were analyzed prospectively on a per-patient and per-region basis (local, locoregional nodal, distant organ or soft tissue, bone). Discrepant findings were validated as true vs. false positive by histopathology or image follow-up. Tracer uptake in tumor tissue was assessed by SUVmax. Results: In total n=100 patients (median 62 years, male/female n=68/32) underwent FDG- and FAP-PET. Five most frequent tumor entities and respective median FDG vs FAP uptake were RCC (n=19; SUVmax 8.4 vs. 7.1), sarcoma (n=18; 10.3 vs. 10.9), NSCLC (n=10; 12.4 vs. 13.7), lymphoma (n=9; 18.3 vs. 10.9), and PDAC (n=8; 4.1 vs. 7.3). On a per-patient basis, FDG- vs FAP-PET localized malignancy in n=93/94 patients. FDG- vs FAP-PET was concordant for the assessment of 362/400 (91%) regions. n=16/400 (4%) regions were negative on FDG- and positive on FAP-PET (88% true, 12% false positive). n=22/400 (6%) regions were negative on FAP- and positive on FDG-PET (57% true, 43% false positive). Two false positive FDG-PET findings were due to tracer uptake in reactive lymph nodes. There were no PET-related adverse events. Conclusions: In patients with various tumor entities, standard FDG- and novel FAP-PET localized tumor equally well. Additionally, FAP-PET was associated with a lower rate of false positive findings, especially in lymph node assessments. Clinical trial information: NCT05160051 . [Table: see text]

An assessment of bioinformatics tools for the detection of human endogenous retroviral insertions in short-read genome sequencing data.

There is a growing interest in the study of human endogenous retroviruses (HERVs) given the substantial body of evidence that implicates them in many human diseases. Although their genomic characterization presents numerous technical challenges, next-generation sequencing (NGS) has shown potential to detect HERV insertions and their polymorphisms in humans. Currently, a number of computational tools to detect them in short-read NGS data exist. In order to design optimal analysis pipelines, an independent evaluation of the available tools is required. We evaluated the performance of a set of such tools using a variety of experimental designs and datasets. These included 50 human short-read whole-genome sequencing samples, matching long and short-read sequencing data, and simulated short-read NGS data. Our results highlight a great performance variability of the tools across the datasets and suggest that different tools might be suitable for different study designs. However, specialized tools designed to detect exclusively human endogenous retroviruses consistently outperformed generalist tools that detect a wider range of transposable elements. We suggest that, if sufficient computing resources are available, using multiple HERV detection tools to obtain a consensus set of insertion loci may be ideal. Furthermore, given that the false positive discovery rate of the tools varied between 8% and 55% across tools and datasets, we recommend the wet lab validation of predicted insertions if DNA samples are available.

Impact of Preoperative Extramammary Findings in Patients with Newly Diagnosed Breast Cancer.

Breast MRI has been associated with significant rates of false positive findings. We aimed to determine the frequency of extramammary findings (EMFs) in newly diagnosed breast cancer patients on breast MRI with contrast and assess the significance of these findings and need for additional imaging and follow-up. A retrospective review of patients diagnosed with breast cancer from October 2018 to October 2019 was performed. Clinicopathologic features were collected, including type of breast cancer, size, stage, and whether the patients had a breast MRI. Those who had MRI were included, and the MRI was reviewed to determine if EMFs were identified. Further imaging and follow-up were assessed and recorded. Of the 480 patients included in this cohort, 353 (74%) had invasive cancer, and the remainder had ductal carcinoma in situ. Two hundred ninety patients (60%) underwent MRI, and 53 of 290 (18%) had EMFs on MRI. Of these, 28 of 53 (53%) underwent additional imaging to further evaluate findings. Two invasive procedures were performed (fine needle aspiration and thymectomy), and 1 malignancy was identified in the thymus. No metastatic breast cancer was identified in any patient. MRIs are frequently obtained for newly diagnosed breast cancer patients, and additional findings, especially extramammary, can be stressful for patients, and potentially lead to treatment delay if further evaluation is warranted. Our results demonstrate that incidental EMFs discovered via breast MRI are common and often lead to additional imaging studies. However, no metastatic lesions were found, and only 1 separate malignancy was identified, which did not affect breast cancer management. In patients with early-stage breast cancer, EMFs yield a very low rate of malignancy, providing high levels of reassurance and supporting the option of proceeding with surgery or treatment without delay.

Inflated expectations: Rare-variant association analysis using public controls.

The use of publicly available sequencing datasets as controls (hereafter, "public controls") in studies of rare variant disease associations has great promise but can increase the risk of false-positive discovery. The specific factors that could contribute to inflated distribution of test statistics have not been systematically examined. Here, we leveraged both public controls, gnomAD v2.1 and several datasets sequenced in our laboratory to systematically investigate factors that could contribute to the false-positive discovery, as measured by λΔ95, a measure to quantify the degree of inflation in statistical significance. Analyses of datasets in this investigation found that 1) the significantly inflated distribution of test statistics decreased substantially when the same variant caller and filtering pipelines were employed, 2) differences in library prep kits and sequencers did not affect the false-positive discovery rate and, 3) joint vs. separate variant-calling of cases and controls did not contribute to the inflation of test statistics. Currently available methods do not adequately adjust for the high false-positive discovery. These results, especially if replicated, emphasize the risks of using public controls for rare-variant association tests in which individual-level data and the computational pipeline are not readily accessible, which prevents the use of the same variant-calling and filtering pipelines on both cases and controls. A plausible solution exists with the emergence of cloud-based computing, which can make it possible to bring containerized analytical pipelines to the data (rather than the data to the pipeline) and could avert or minimize these issues. It is suggested that future reports account for this issue and provide this as a limitation in reporting new findings based on studies that cannot practically analyze all data on a single pipeline.

Modulations of static and dynamic functional connectivity among brain networks by electroacupuncture in post-stroke aphasia.

Post-stroke aphasia (PSA) is a language disorder caused by left hemisphere stroke. Electroacupuncture (EA) is a minimally invasive therapeutic option for PSA treatment. Tongli (HT5) and Xuanzhong (GB39), two important language-associated acupoints, are frequently used in the rehabilitation of patients with PSA. Preliminary evidence indicated functional activation in distributed cortical areas upon HT5 and GB39 stimulation. However, research on the modulation of dynamic and static functional connectivity (FC) in the brain by EA in PSA is lacking. This study aimed to investigate the PSA-related effects of EA stimulation at HT5 and GB39 on neural processing. Thirty-five participants were recruited, including 19 patients with PSA and 16 healthy controls (HCs). The BOLD signal was analyzed by static independent component analysis, generalized psychophysiological interactions, and dynamic independent component analysis, considering variables such as age, sex, and years of education. The results revealed that PSA showed activated clusters in the left putamen, left postcentral gyrus (PostCG), and left angular gyrus in the salience network (SN) compared to the HC group. The interaction effect on temporal properties of networks showed higher variability of SN (F = 2.23, positive false discovery rate [pFDR] = 0.017). The interaction effect on static FC showed increased functional coupling between the right calcarine and right lingual gyrus (F = 3.16, pFDR = 0.043). For the dynamic FC, at the region level, the interaction effect showed lower variability and higher frequencies of circuit 3, with the strongest connections between the supramarginal gyrus and posterior cingulum (F = 5.42, pFDR = 0.03), middle cingulum and PostCG (F = 5.27, pFDR = 0.036), and triangle inferior frontal and lingual gyrus (F = 5.57, pFDR = 0.026). At the network level, the interaction effect showed higher variability in occipital network-language network (LN) and cerebellar network (CN) coupling, with stronger connections between the LN and CN (F = 4.29, pFDR = 0.042). Dynamic FC values between the triangle inferior frontal and lingual gyri were anticorrelated with transcribing, describing, and dictating scores in the Chinese Rehabilitation Research Center for Chinese Standard Aphasia Examination. These findings suggest that EA stimulation may improve language function, as it significantly modulated the nodes of regions/networks involved in the LN, SN, CN, occipital cortex, somatosensory regions, and cerebral limbic system.

It Is Time to Rethink Adult Glaucoma Screening Recommendations.

It Is Time to Rethink Adult Glaucoma Screening Recommendations.

Monitoring the Awake and Anesthetized Unconscious States Using Bispectral Index and Electroencephalographic Connectivity Measures.

Objective. Our objective was to compare three electroencephalography (EEG)-based methods with anesthesiologist clinical judgment of the awake and anesthetized unconscious states. Methods. EEG recorded from 25 channels and from four channel bilateral Bispectral index (BIS) electrodes were collected from 20 patients undergoing surgery with general anesthesia. To measure connectivity we applied Directed Transfer Function (DTF) in eight channels of the EEG, and extracted data from BIS over the same time segments. Shannon's entropy was applied to assess the complexity of the EEG signal. Discriminant analysis was used to evaluate the data in relation to clinical judgment. Results. Assessing anesthetic state relative clinical judgment, the bilateral BIS gave the highest accuracy (ACC) (95.4%) and lowest false positive discovery rate (FDR) (0.5%) . Equivalent DTF gave 94.5% for ACC and 2.6% for FDR. Combining all methods gave ACC = 94.9% and FDR = 1%. Generally, entropy scored lower on ACC and higher on FDR than the other methods (ACC 90.87% and FDR 4.6%). BIS showed at least a one minute delay in 18 of the 20 patients. Conclusions. Our results show that BIS and DTF both have a high ACC and low FDR. Because of time delays in BIS values, we recommend combining the two methods.

Use of high-resolution metabolomics to assess the biological perturbations associated with maternal exposure to Bisphenol A and Bisphenol F among pregnant African American women

BackgroundHuman and animal exposure to bisphenol A (BPA) has been associated with adverse developmental and reproductive effects. The molecular mechanisms by which BPA exposure exerts its effects are not well-understood, even less known about its analogues bisphenol F (BPF). To address these knowledge gaps, we conducted an untargeted metabolome-wide association study (MWAS) to identify metabolic perturbations associated with BPA/BPF exposures in a pregnant African American cohort. MethodsFrom a subset of study participants enrolled in the Atlanta African American Maternal-Child cohort, we collected both urine samples, for targeted exposure assessment of BPA (N = 230) and BPF (N = 48), and serum samples, for high-resolution metabolomics (HRM) profiling (N = 230), during early pregnancy (8–14 weeks’ gestation). Using an established untargeted HRM workflow consisting of MWAS modeling, pathway enrichment analysis, and chemical annotation and confirmation, we investigated the potential metabolic pathways and features associated with BPA/BPF exposures. ResultsThe geometric mean creatinine-adjusted concentrations of urinary BPA and BPF were 0.85 ± 2.58 and 0.70 ± 4.71 µg/g creatinine, respectively. After false positive discovery rate correction at 20 % level, 264 and 733 unique metabolic features were significantly associated with urinary BPA and BPF concentrations, representing 10 and 12 metabolic pathways, respectively. Three metabolic pathways, including steroid hormones biosynthesis, lysine and lipoate metabolism, were significantly associated with both BPA and BPF exposure. Using chemical standards, we have confirmed the chemical identity of 16 metabolites significantly associated with BPA or BPF exposure. ConclusionsOur findings support that exposure to BPA and BPF in pregnant women is associated with the perturbation of aromatic amino acid metabolism, xenobiotics metabolism, steroid biosynthesis, and other amino acid metabolism closely linked to stress responses, inflammation, neural development, reproduction, and weight regulation.

Cost-effectiveness of the implementation of [68Ga]Ga-PSMA-11 PET/CT at initial prostate cancer staging

BackgroundDespite its high specificity, PSMA PET/CT has a moderate to low sensitivity of 40–50% for pelvic lymph node detection, implicating that a negative PSMA PET/CT cannot rule out lymph node metastases. This study investigates a strategy of implementing PSMA PET/CT for initial prostate cancer staging and treatment planning compared to conventional diagnostics. In this PSMA PET/CT strategy, a bilateral extended pelvic lymph node dissection (ePLND) is only performed in case of a negative PSMA PET/CT; in case of a positive scan treatment planning is solely based on PSMA PET/CT results.MethodA decision table and lifetime state transition model were created. Quality-adjusted life years and health care costs were modelled over lifetime.ResultsThe PSMA PET/CT strategy of treatment planning based on initial staging with [68Ga]Ga-PSMA-11 PET/CT results in cost-savings of €674 and a small loss in quality of life (QoL), 0.011 QALY per patient. The positive effect of [68Ga]Ga-PSMA-11 PET/CT was caused by abandoning both an ePLND and unnecessary treatment in iM1 patients, saving costs and resulting in higher QoL. The negative effect was caused by lower QoL and high costs in the false palliative state, due to pN1lim patients (≤ 4 pelvic lymph node metastases) being falsely diagnosed as iN1ext (> 4 pelvic lymph node metastases). These patients received subsequently palliative treatment instead of potentially curative therapy.ConclusionInitial staging and treatment planning based on [68Ga]Ga-PSMA-11 PET/CT saves cost but results in small QALY loss due to the rate of false positive findings.

Stability selection for mixed effect models with large numbers of predictor variables: A simulation study

Covariate selection when the number of available variables is large relative to the number of observations is problematic in epidemiology and remains the focus of continued research. Whilst a variety of statistical methods have been developed to attempt to overcome this issue, at present very few methods are available for wide data that include a clustered outcome. The purpose of this research was to make an empirical evaluation of a new method for covariate selection in wide data settings when the dependent variable is clustered. We used 3300 simulated datasets with a variety of defined structures and known sets of true predictor variables to conduct an empirical evaluation of a mixed model stability selection procedure. Comparison was made with an alternative method based on regularisation using the least absolute shrinkage and selection operator (Lasso) penalty. Model performance was assessed using several metrics including the true positive rate (proportion of true covariates selected in a final model) and false discovery rate (proportion of variables selected in a final model that were non-true (false) variables). For stability selection, the false discovery rate was consistently low, generally remaining ≤ 0.02 indicating that on average fewer than 1 in 50 of the variables selected in a final model were false variables. This was in contrast to the Lasso-based method in which the false discovery rate was between 0.59 and 0.72, indicating that generally more than 60% of variables selected in a final model were false variables. In contrast however, the Lasso method attained higher true positive rates than stability selection, although both methods achieved good results. For the Lasso method, true positive rates remained ≥ 0.93 whereas for stability selection the true positive rate was 0.73–0.97. Our results suggest both methods may be of value for covariate selection with high dimensional data with a clustered outcome. When high specificity is needed for identification of true covariates, stability selection appeared to offer the better solution, although with a slight loss of sensitivity. Conversely when high sensitivity is needed, the Lasso approach may be useful, even if accompanied by a substantial loss of specificity. Overall, the results indicated the loss of sensitivity when employing stability selection is relatively small compared to the loss of specificity when using the Lasso and therefore stability selection may provide the better option for the analyst when evaluating data of this type.

Comparison of the performances of machine learning and deep learning in improving the quality of low dose lung cancer PET images.

To compare the performances of machine learning (ML) and deep learning (DL) in improving the quality of low dose (LD) lung cancer PET images and the minimum counts required. 33 standard dose (SD) PET images, were used to simulate LD PET images at seven-count levels of 0.25, 0.5, 1, 2, 5, 7.5 and 10 million (M) counts. Image quality transfer (IQT), a ML algorithm that uses decision tree and patch-sampling was compared to two DL networks-HighResNet (HRN) and deep-boosted regression (DBR). Supervised training was performed by training the ML and DL algorithms with matched-pair SD and LD images. Image quality evaluation and clinical lesion detection tasks were performed by three readers. Bias in 53 radiomic features, including mean SUV, was evaluated for all lesions. ML- and DL-estimated images showed higher signal and smaller error than LD images with optimal image quality recovery achieved using LD down to 5M counts. True positive rate and false discovery rate were fairly stable beyond 5M counts for the detection of small and large true lesions. Readers rated average or higher ratings to images estimated from LD images of count levels above 5M only, with higher confidence in detecting true lesions. LD images with a minimum of 5M counts (8.72MBq for 10min scan or 25MBq for 3min scan) are required for optimal clinical use of ML and DL, with slightly better but more varied performance shown by DL.

A phylogenetic approach to study the evolution of somatic mutational processes in cancer

Cancer cell genomes change continuously due to mutations, and mutational processes change over time in patients, leaving dynamic signatures in the accumulated genomic variation in tumors. Many computational methods detect the relative activities of known mutation signatures. However, these methods may produce erroneous signatures when applied to individual branches in cancer cell phylogenies. Here, we show that the inference of branch-specific mutational signatures can be improved through a joint analysis of the collections of mutations mapped on proximal branches of the cancer cell phylogeny. This approach reduces the false-positive discovery rate of branch-specific signatures and can sometimes detect faint signatures. An analysis of empirical data from 61 lung cancer patients supports trends based on computer-simulated datasets for which the correct signatures are known. In lung cancer somatic variation, we detect a decreasing trend of smoking-related mutational processes over time and an increasing influence of APOBEC mutational processes as the tumor evolution progresses. These analyses also reveal patterns of conservation and divergence of mutational processes in cell lineages within patients.