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Institute
Invasive coronary angiography (ICA) was the only method to image coronary arteries for a long time and is still the gold-standard. Technology of noninvasive imaging by coronary computed-tomography angiography (CCTA) has experienced remarkable progress during the last two decades. It is possible to visualize atherosclerotic lesions in the vessel wall in contrast to "lumenography" performed by ICA. Coronary artery disease can be ruled out by CCTA with excellent accuracy. The degree of stenoses is, however, often overestimated which impairs specificity. Atherosclerotic lesions can be characterized as calcified, non-calcified and partially calcified. Calcified plaques are usually quantified using the Agatston-Score. Higher scores are correlated with worse cardiovascular outcome and increased risk of cardiac events. For non-calcified or partially calcified plaques different angiographic findings like positive remodelling, a large necrotic core or spotty calcification more frequently lead to myocardial infarctions. CCTA is an important tool with increasing clinical value for ruling out coronary artery disease or relevant stenoses as well as for advanced risk stratification.
Background: While the incidence and aspects of pneumonia in ICU patients has been extensively discussed in the literature, studies on the occurrence of pneumonia in severely injured patients are rare. The aim of the present study is to elucidate factors associated with the occurrence of pneumonia in severely injured patients with thoracic trauma.
Setting: Level-I University Trauma Centres associated with the TraumaRegister DGU®.
Methods: A total of 1162 severely injured adult patients with thoracic trauma documented in the TraumaRegister DGU® (TR-DGU) were included in this study. Demographic data, injury severity, duration of mechanical ventilation (MV), duration of ICU stay, occurrence of pneumonia, bronchoalveolar lavage, aspiration, pathogen details, and incidences of mortality were evaluated. Statistical evaluation was performed using SPSS (Version 25.0, SPSS, Inc.) software.
Results: The overall incidence of pneumonia was 27.5%. Compared to patients without pneumonia, patients with pneumonia had sustained more severe injuries (mean ISS: 32.6 vs. 25.4), were older (mean age: 51.3 vs. 47.5) and spent longer periods under MV (mean: 368.9 h vs. 114.9 h). Age, sex (male), aspiration, and duration of MV were all independent predictors for pneumonia occurrence in a multivariate analysis. The cut-off point for duration of MV that best discriminated between patients who would and would not develop pneumonia during their hospital stay was 102 h. The extent of thoracic trauma (AISthorax), ISS, and presence of pulmonary comorbidities did not show significant associations to pneumonia incidence in our multivariate analysis. No significant difference in mortality between patients with and without pneumonia was observed.
Conclusions: Likelihood of pneumonia increases with age, aspiration, and duration of MV. These parameters were not found to be associated with differences in outcomes between patients with and without pneumonia. Future studies should focus on independent parameters to more clearly identify severely injured subgroups with a high risk of developing pneumonia.
Level of evidence: Level II - Retrospective medical record review.
Large-scale genetic census of an elusive carnivore, the European wildcat (Felis s. silvestris)
(2016)
The European wildcat, Felis silvestris silvestris, serves as a prominent target species for the reconnection of central European forest habitats. Monitoring of this species, however, appears difficult due to its elusive behaviour and the ease of confusion with domestic cats. Recently, evidence for multiple wildcat occurrences outside its known distribution has accumulated in several areas across Central Europe, questioning the validity of available distribution data for this species. Our aim was to assess the fine-scale distribution and genetic status of the wildcat in its central European distribution range. We compiled and analysed genetic samples from roadkills and hundreds of recent hair-trapping surveys and applied phylogenetic and genetic clustering methods to discriminate wild and domestic cats and identify population subdivision. 2220 individuals were confirmed as either wildcat (n = 1792) or domestic cat (n = 342), and the remaining 86 (3.9 %) were identified as hybrids between the two. Remarkably, genetic distinction of domestic cats, wildcats and their hybrids was only possible when taking into account the presence of two highly distinct genetic lineages of wildcats, with a suture zone in central Germany. 44 % of the individual wildcats where sampled outside the previously published distribution. Our analyses confirm a relatively continuous spatial presence of wildcats across large parts of the study area in contrast to previous analyses indicating a highly fragmented distribution. Our results suggest that wildcat conservation and management should take advantage of the higher than previously assumed dispersal potential of wildcats, which may use wildlife corridors very efficiently.
miR-142-3p expression is predictive for severe traumatic brain injury (TBI) in trauma patients
(2020)
Background: Predictive biomarkers in biofluids are the most commonly used diagnostic method, but established markers in trauma diagnostics lack accuracy. This study investigates promisingmicroRNAs(miRNA)releasedfromaffectedtissueafterseveretraumathathavepredictive values for the effects of the injury.
Methods: A retrospective analysis of prospectively collected data and blood samples of n = 33 trauma patients (ISS≥16) is provided. Levels of miR-9-5p, -124-3p, -142-3p, -219a-5p, -338-3pand-423-3p inseverelyinjuredpatients (PT)withouttraumatic braininjury (TBI) or with severe TBI (PT + TBI) and patients with isolated TBI (isTBI) were measured within 6 h after trauma.
Results: The highest miR-423-3p expression was detected in patients with severe isTBI, followed by patients with PT + TBI, and lowest levels were found in PT patients without TBI (2−∆∆Ct,p = 0.009). ApositivecorrelationbetweenmiR-423-3plevelandincreasingAIShead (p = 0.001) and risk of mortality (RISC II, p = 0.062) in trauma patients (n = 33) was found. ROC analysis of miR-423-3p levels revealed them as statistically significant to predict the severity of brain injury in trauma patients (p = 0.006). miR-124-3p was only found in patients with severe TBI, miR-338-3p was shown in all trauma groups. miR-9-5p, miR-142-3p and miR-219a-5p could not be detected in any of the four groups. Conclusion: miR-423-3p expression is significantly elevated after isolated traumatic braininjuryandpredictableforsevereTBIinthefirsthoursaftertrauma. miR-423-3pcouldrepresent a promising new biomarker to identify severe isolated TBI.
The inflammatory response plays an important role in the pathophysiology of multiple injuries. This study examines the effects of severe trauma and inflammatory response on markers of neuronal damage. A retrospective analysis of prospectively collected data in 445 trauma patients (Injury Severity Score (ISS) ≥ 16) is provided. Levels of neuronal biomarkers (calcium-binding Protein B (S100b), Enolase2 (NSE), glial fibrillary acidic protein (GFAP)) and Interleukins (IL-6, IL-10) in severely injured patients (with polytrauma (PT)) without traumatic brain injury (TBI) or with severe TBI (PT+TBI) and patients with isolated TBI (isTBI) were measured upon arrival until day 5. S100b, NSE, GFAP levels showed a time-dependent decrease in all cohorts. Their expression was higher after multiple injuries (p = 0.038) comparing isTBI. Positive correlation of marker level after concomitant TBI and isTBI (p = 0.001) was noted, while marker expression after PT appears to be independent. Highest levels of IL-6 and -10 were associated to PT und lowest to isTBI (p < 0.001). In all groups pro-inflammatory response (IL-6/-10 ratio) peaked on day 2 and at a lower level on day 4. Severe TBI modulates kinetic profile of inflammatory response by reducing interleukin expression following trauma. Potential markers for neuronal damage have a limited diagnostic value after severe trauma because undifferentiated increase.
Treatment response lowers tumor symptom burden in recurrent and/or metastatic head and neck cancer
(2020)
Background: Head and neck squamous cell cancer (HNSCC) frequently causes severe symptoms that may be reduced, when the tumor is successfully treated. The SOCCER trial studied the association of treatment response with patient reported tumor symptom burden in first line treatment of recurrent and/or metastatic HNSCC.
Methods: In this prospective, multi-center, non-interventional trial patients were treated either with platinum-based chemotherapy and cetuximab or radiotherapy and cetuximab. Tumor symptom burden was assessed every four weeks with a questionnaire containing ten visual analogue scales (VAS, range 0–100), which were summarized to the overall VAS score.
Results: Fourhundred seventy patients were registered in 97 German centers. A total of 315 patients with at least the baseline and one subsequent questionnaire were available for analysis. Changes in the VAS score were rated as absolute differences from baseline. Negative values indicate improvement of symptoms. The overall VAS score improved significantly at the first post-baseline assessment in responders (− 2.13 vs. non-responders + 1.15, p = 0.048), and even more for the best post-baseline assessment (− 7.82 vs. non-responders − 1.97, p = 0.0005). The VAS for pain (− 16.37 vs. non-responders − 8.89, p = 0.001) and swallowing of solid food (− 16.67 vs. non-responders − 5.06, p = 0.002) improved significantly more in responders (best post-baseline assessment). In the multivariable Cox regression analysis, worse overall VAS scores were associated with worse overall survival (hazard ratio for death 1.12 per 10 points increment on the overall VAS scale, 95% CI 1.05–1.20, p = 0.0009).
Conclusion: In unselected patients beyond randomized controlled trials, treatment response lowers tumor symptom burden in recurrent and/or metastatic HNSCC.
Trial registration: ClinicalTrials.gov, NCT00122460. Registered 22 Juli 2005,
Background: Chronic hepatitis C virus (HCV) infections are causally linked with metabolic comorbidities such as insulin resistance, hepatic steatosis, and dyslipidemia. However, the clinical impact of HCV eradication achieved by direct-acting antivirals (DAAs) on glucose and lipid homeostasis is still controversial. The study aimed to prospectively investigate whether antiviral therapy of HCV with DAAs alters glucose and lipid parameters. Methods: 50 patients with chronic HCV who were treated with DAAs were screened, and 49 were enrolled in the study. Biochemical and virological data, as well as noninvasive liver fibrosis parameters, were prospectively collected at baseline, at the end of treatment (EOT) and 12 and 24 weeks post-treatment. Results: 45 of 46 patients achieved sustained virologic response (SVR). The prevalence of insulin resistance (HOMA-IR) after HCV clearance was significantly lower, compared to baseline (5.3 ± 6.1 to 2.5 ± 1.9, p < 0.001), which is primarily attributable to a significant decrease of fasting insulin levels (18.9 ± 17.3 to 11.7 ± 8.7; p = 0.002). In contrast to that, HCV eradication resulted in a significant increase in cholesterol levels (total cholesterol, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein (HDL-C) levels) and Controlled Attenuated Score (CAP), although BMI did not significantly change over time (p = 0.95). Moreover, HOMA-IR correlated significantly with noninvasive liver fibrosis measurements at baseline und during follow-up (TE: r = 0.45; p = 0.003, pSWE: r = 0.35; p = 0.02, APRI: r = 0.44; p = 0.003, FIB-4: r = 0.41; p < 0.001). Conclusion: Viral eradication following DAA therapy may have beneficial effects on glucose homeostasis, whereas lipid profile seems to be worsened.
Molecular and cellular research modalities for the study of liver pathologies have been tremendously improved over the recent decades. Advanced technologies offer novel opportunities to establish cell isolation techniques with excellent purity, paving the path for 2D and 3D microscopy and high-throughput assays (e.g., bulk or single-cell RNA sequencing). The use of stem cell and organoid research will help to decipher the pathophysiology of liver diseases and the interaction between various parenchymal and non-parenchymal liver cells. Furthermore, sophisticated animal models of liver disease allow for the in vivo assessment of fibrogenesis, portal hypertension and hepatocellular carcinoma (HCC) and for the preclinical testing of therapeutic strategies. The purpose of this review is to portray in detail novel in vitro and in vivo methods for the study of liver cell biology that had been presented at the workshop of the 8th meeting of the European Club for Liver Cell Biology (ECLCB-8) in October of 2018 in Bonn, Germany.
Objectives: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance.
Purpose: Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a “watch and wait” strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging.
Experimental design: We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial.
Results: A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76).
Conclusion: The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a “watch and wait” strategy.
Translational relevance: Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for “watch and wait”.