Challenges in the Evaluation of Observational Data Trustworthiness From a Data Producers Viewpoint (FAIR+)

Recent discussions in many scientific disciplines stress the necessity of “FAIR” data. FAIR data, however, does not necessarily include information on data trustworthiness, where trustworthiness comprises reliability, validity and provenience/provenance. This opens up the risk of misinterpreting scientific data, even though all criteria of “FAIR” are fulfilled. Especially applications such as secondary data processing, data blending, and joint interpretation or visualization efforts are affected. This paper intends to start a discussion in the scientific community about how to evaluate, describe, and implement trustworthiness in a standardized data evaluation approach and in its metadata description following the FAIR principles. It discusses exemplarily different assessment tools regarding soil moisture measurements, data processing and visualization and elaborates on which additional (metadata) information is required to increase the trustworthiness of data for secondary usage. Taking into account the perspectives of data collectors, providers and users, the authors identify three aspects of data trustworthiness that promote efficient data sharing: 1) trustworthiness of the measurement 2) trustworthiness of the data processing and 3) trustworthiness of the data integration and visualization. The paper should be seen as the basis for a community discussion on data trustworthiness for a scientifically correct secondary use of the data. We do not have the intention to replace existing procedures and do not claim completeness of reliable tools and approaches described. Our intention is to discuss several important aspects to assess data trustworthiness based on the data life cycle of soil moisture data as an example

First detection of porcine respirovirus 1 in Germany and the Netherlands

Porcine respirovirus 1, also referred to as porcine parainfluenza virus 1 (PPIV-1), was first detected in deceased pigs from Hong Kong in 2013. It has since then been found in the USA, Chile and most recently in Hungary. Information on the pathogenicity and global spread is sparse. However, it has been speculated to play a role in the porcine respiratory disease complex. To investigate the porcine virome, we screened 53 pig samples from 26 farms within the Dutch-German border region using shotgun metagenomics sequencing (SMg). After detecting PPIV-1 in five farms through SMg, a real-time reverse transcriptase PCR (RT-qPCR) assay was designed, which not only confirmed the presence of the virus in 1 of the 5 farms but found an additional 6 positive farms. Phylogenetic analysis found the closest match to be the first detected PPIV-1 strain in Hong Kong. The Dutch-German region represents a significant area of pig farming within Europe and could provide important information on the characterization and circulation of porcine viruses, such as PPIV-1. With its recent detection in Hungary, these findings suggest widespread circulation of PPIV-1 in Central Europe, highlighting the need for further research on persistence, pathogenicity and transmission in Europe

Assessment of Viral Targeted Sequence Capture Using Nanopore Sequencing Directly from Clinical Samples

Shotgun metagenomic sequencing (SMg) enables the simultaneous detection and characterization of viruses in human, animal and environmental samples. However, lack of sensitivity still poses a challenge and may lead to poor detection and data acquisition for detailed analysis. To improve sensitivity, we assessed a broad scope targeted sequence capture (TSC) panel (ViroCap) in both human and animal samples. Moreover, we adjusted TSC for the Oxford Nanopore MinION and compared the performance to an SMg approach. TSC on the Illumina NextSeq served as the gold standard. Overall, TSC increased the viral read count significantly in challenging human samples, with the highest genome coverage achieved using the TSC on the MinION. TSC also improved the genome coverage and sequencing depth in clinically relevant viruses in the animal samples, such as influenza A virus. However, SMg was shown to be adequate for characterizing a highly diverse animal virome. TSC on the MinION was comparable to the NextSeq and can provide a valuable alternative, offering longer reads, portability and lower initial cost. Developing new viral enrichment approaches to detect and characterize significant human and animal viruses is essential for the One Health Initiative

Alcohol consumption and mortality in individuals with diabetes mellitus

Studies have suggested that moderate alcohol consumption is associated with a reduced risk of CVD and premature mortality in individuals with diabetes mellitus. However, history of alcohol consumption has hardly been taken into account. We investigated the association between current alcohol consumption and mortality in men and women with diabetes mellitus accounting for past alcohol consumption. Within the European Prospective Investigation into Cancer and Nutrition (EPIC), a cohort was defined of 4797 participants with a confirmed diagnosis of diabetes mellitus. Men and women were assigned to categories of baseline and past alcohol consumption. Hazard ratios (HR) and 95% CI for total mortality were estimated with multivariable Cox regression models, using light alcohol consumption (>0-6 g/d) as the reference category. Compared with light alcohol consumption, no relationship was observed between consumption of 6 g/d or more and total mortality. HR for >6.12 g/d was 0.89(95% CI 0.61, 1.30) in men and 0.86(95% CI 0.46, 1.60) in women. Adjustment for past alcohol consumption did not change the estimates substantially. In individuals who at baseline reported abstaining from alcohol, mortality rates were increased relative to light consumers: HR was 1.52 (95% CI 0.99, 2.35) in men and 1.81 (95% CI 1.04, 3.17) in women. The present study in diabetic individuals showed no association between current alcohol consumption >6 g/d and mortality risk compared with light consumption. The increased mortality risk among non-consumers appeared to be affected by their past alcohol consumption rather than their current abstinence

Selinexor in Advanced, Metastatic Dedifferentiated Liposarcoma: A Multinational, Randomized, Double-Blind, Placebo-Controlled Trial

PURPOSE Antitumor activity in preclinical models and a phase I study of patients with dedifferentiated liposarcoma (DD-LPS) was observed with selinexor. We evaluated the clinical benefit of selinexor in patients with previously treated DD-LPS whose sarcoma progressed on approved agents. METHODS SEAL was a phase II-III, multicenter, randomized, double-blind, placebo-controlled study. Patients age 12 years or older with advanced DD-LPS who had received two-five lines of therapy were randomly assigned (2:1) to selinexor (60 mg) or placebo twice weekly in 6-week cycles (crossover permitted). The primary end point was progression-free survival (PFS). Patients who received at least one dose of study treatment were included for safety analysis (ClinicalTrials.gov identifier: ). RESULTS Two hundred eighty-five patients were enrolled (selinexor, n = 188; placebo, n = 97). PFS was significantly longer with selinexor versus placebo: hazard ratio (HR) 0.70 (95% CI, 0.52 to 0.95; one-sided P = .011; medians 2.8 v 2.1 months), as was time to next treatment: HR 0.50 (95% CI, 0.37 to 0.66; one-sided P < .0001; medians 5.8 v 3.2 months). With crossover, no difference was observed in overall survival. The most common treatment-emergent adverse events of any grade versus grade 3 or 4 with selinexor were nausea (151 [80.7%] v 11 [5.9]), decreased appetite (113 [60.4%] v 14 [7.5%]), and fatigue (96 [51.3%] v 12 [6.4%]). Four (2.1%) and three (3.1%) patients died in the selinexor and placebo arms, respectively. Exploratory RNA sequencing analysis identified that the absence of CALB1 expression was associated with longer PFS with selinexor compared with placebo (median 6.9 v 2.2 months; HR, 0.19; P = .001). CONCLUSION Patients with advanced, refractory DD-LPS showed improved PFS and time to next treatment with selinexor compared with placebo. Supportive care and dose reductions mitigated side effects of selinexor. Prospective validation of CALB1 expression as a predictive biomarker for selinexor in DD-LPS is warranted. (C) 2022 by American Society of Clinical Oncolog

Reproductive Factors and Exogenous Hormone Use in Relation to Risk of Glioma and Meningioma in a Large European Cohort Study

Background: The etiologies of glioma and meningioma tumors are largely unknown. Although reproductive hormones are thought to influence the risk of these tumors, epidemiologic data are not supportive of this hypothesis; however, few cohort studies have published on this topic. We examined the relation between reproductive factors and the risk of glioma and meningioma among women in the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: After a mean of 8.4 years of follow-up, 193 glioma and 194 meningioma cases were identified among 276,212 women. Information on reproductive factors and hormone use was collected at baseline. Cox proportional hazard regression was used to determine hazard ratios (HR) and 95% confidence intervals (95% CI). Results: No associations were observed between glioma or meningioma risk and reproductive factors, including age at menarche, parity, age at first birth, menopausal status, and age at menopause. A higher risk of meningioma was observed among postmenopausal women who were current users of hormone replacement therapy (HR, 1.79; 95% CI, 1.18-2.71) compared with never users. Similarly, current users of oral contraceptives were at higher risk of meningioma than never users (HR, 3.61; 95% CI, 1.75-7.46). Conclusion: Our results do not support a role for estrogens and glioma risk. Use of exogenous hormones, especially current use, seems to increase meningioma risk. However, these findings could be due to diagnostic bias and require confirmation. Impact: Elucidating the role of hormones in brain tumor development has important implications and needs to be further examined using biological measurements. Cancer Epidemiol Biomarkers Prev; 19(10); 2562-9. (C) 2010 AACR