Concomitant history of cancer in acute pulmonary embolism is connected with poorer outcome

Purpose: Cancer increases the risk of venous thromboembolism (VTE) substantially. VTE is connected with poorer outcome in cancer patients. The aim of our study was to investigate the impact of cancer on the severity and short-term outcome of pulmonary embolism (PE). Methods: We retrospectively analyzed the data of 182 patients with confirmed PE. PE patients were subdivided in the group with concomitant active cancer disease or history of cancer or in the group without cancer. Groups were compared with Wilcoxon–Mann–Whitney Test. Logistic regression models were calculated to investigate the association between cancer and several parameters such as age and PE severity status as well as the association between in-hospital death and the parameters age, gender, PE severity status and cancer. Results: While 20.3% PE patients reported an active cancer disease or a history of cancer (64.9% female), 79.7% of the PE patients did not (60.7% female). PE patients with cancer were 5 years older (76.0 (65.5/81.0) vs. 71.0 (58.5/80.5) years, P=0.055) and revealed a higher PE severity status in mean (1.91±0.53 vs. 1.67±0.54, P=0.069). Univariate logistic regression models showed an association between cancer and age (OR 1.04, CI 95% (1.01–1.08), P=0.017) as well as cancer and the severity status (OR 2.38 (1.05–5.26), P=0.037). In-hospital death in the early course was strongly connected with the PE severity status (OR 36.60 (2.99–448.68), P=0.0049), but not with cancer (P=0.65). Conclusions: Concomitant history of cancer in acute PE was associated with higher PE severity status and therefore poorer outcome

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics

Framework and baseline examination of the German National Cohort (NAKO)

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10654-022-00890-5

Evaluation of Risk Stratification Markers and Models in Acute Pulmonary Embolism: Rationale and Design of the MARS-PE (Mainz Retrospective Study of Pulmonary Embolism) Study Programme

An acute pulmonary embolism (PE) is a crucial event in patients’ life and connected with serious morbidity and mortality. Regarding a high case-fatality rate, early and accurate risk-stratification is crucial. Risk for mortality and complications are closely related to hemodynamic stability and cardiac adaptations. The currently recommended risk-stratification approach is not overall simple to use and might delay the identification of those patients, who should be monitored more closely and may treated with more aggressive treatment strategies. Additionally, some risk-stratification criteria for the imaging procedures are still imprecise. Summarized, the search for the most effective risk-stratification tools is still ongoing and some diagnostic criteria might have to be refined. In the MAinz Retrospective Study of Pulmonary Embolism (MARS-PE), overall 182 consecutive patients with confirmed PE were retrospectively included over a 5-year period. Clinical, echocardiographic, functional and laboratory parameters were assessed. The study was designed to provide answers to some of the mentioned relevant questions

Enzymatic Dissociation Induces Transcriptional and Proteotype Bias in Brain Cell Populations

Different cell isolation techniques exist for transcriptomic and proteotype profiling of brain cells. Here, we provide a systematic investigation of the influence of different cell isolation protocols on transcriptional and proteotype profiles in mouse brain tissue by taking into account single-cell transcriptomics of brain cells, proteotypes of microglia and astrocytes, and flow cytometric analysis of microglia. We show that standard enzymatic digestion of brain tissue at 37 °C induces profound and consistent alterations in the transcriptome and proteotype of neuronal and glial cells, as compared to an optimized mechanical dissociation protocol at 4 °C. These findings emphasize the risk of introducing technical biases and biological artifacts when implementing enzymatic digestion-based isolation methods for brain cell analyses

Enzymatic dissociation induces transcriptional and proteotype bias in brain cell populations

Different cell isolation techniques exist for transcriptomic and proteotype profiling of brain cells. Here, we provide a systematic investigation of the influence of different cell isolation protocols on transcriptional and proteotype profiles in mouse brain tissue by taking into account single-cell transcriptomics of brain cells, proteotypes of microglia and astrocytes, and flow cytometric analysis of microglia. We show that standard enzymatic digestion of brain tissue at 37 °C induces profound and consistent alterations in the transcriptome and proteotype of neuronal and glial cells, as compared to an optimized mechanical dissociation protocol at 4 °C. These findings emphasize the risk of introducing technical biases and biological artifacts when implementing enzymatic digestion-based isolation methods for brain cell analyses. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.ISSN:1422-006

Multiplexed Quantification of Four Neuroblastoma DNA Targets in a Single Droplet Digital PCR Reaction

The detection and characterization of cell-free DNA (cfDNA) in peripheral blood from neuroblastoma patients may serve as a minimally invasive approach to liquid biopsy. Major challenges in the analysis of cfDNA purified from blood samples are small sample volumes and low cfDNA concentrations. Droplet digital PCR (ddPCR) is a technology suitable for analyzing low levels of cfDNA. Reported here are two quadruplexed ddPCR assay protocols that reliably quantify MYCN and ALK copy numbers in a single reaction together with the two reference genes, NAGK and AFF3, and accurately estimate ALK(F1174L) (exon 23 position 3522, C>A) and ALK(R1275Q) (exon 25 position 3824, G>A) mutant allele fractions using cfDNA as input. The separation of positive and negative droplets was optimized for detecting two targets in each ddPCR fluorescence channel by the adjustment of the probe and primer concentrations of each target molecule. The quadruplexed assays were validated using a panel of 10 neuroblastoma cell lines and paired blood plasma and primary neuroblastoma samples from nine patients. Accuracy and sensitivity thresholds in quadruplexed assays corresponded well with those from the respective duplexed assays. Presented are two robust quadruplexed ddPCR protocols applicable in the routine clinical setting and that require only minimal plasma volumes for the assessment of MYCN and ALK oncogene status