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Aim: The identification of the mechanisms determining spatial variation in biological diversity along elevational gradients is a central objective in ecology and biogeography. Here, we disentangle the direct and indirect effects of abiotic drivers (climatic conditions, and land use) and biotic drivers (vegetation structure and food resources) on functional diversity and composition of bird and bat assemblages along a tropical elevational gradient. Location: Southern slopes of Mt. Kilimanjaro, Tanzania, East Africa. Methods: We counted birds and recorded bat sonotypes on 58 plots distributed in near-natural and anthropogenically modified habitats from 700 to 4,600 m above sea level. For the recorded taxa, we compiled functional traits related to movement, foraging and body size from museum specimens and databases. Further, we recorded mean annual temperature, precipitation, vegetation complexity as well as the number of fruits, flowers, and insect biomass as measures of resource availability on each study site. Results: Using path analyses, we found similar responses of bird and bat functional diversity to the variation in abiotic and biotic drivers along the elevational gradient. In contrast, the functional composition of both taxa showed distinct responses to abiotic and biotic drivers. For both groups, direct temperature effects were most important, followed by resource availability, precipitation and vegetation complexity. Main Conclusions: Our findings indicate that physiological and metabolic constraints imposed by temperature and resource availability determine the functional diversity of bird and bat assemblages, whereas the composition of individual functional traits is driven by taxon-specific processes. Our study illustrates that distinct filtering mechanisms can result in similar patterns of functional diversity along broad environmental gradients. Such differences need to be taken into account when it comes to conserving the functional diversity of flying vertebrates on tropical mountains.
Objectives: An increasing number of treatment-determining biomarkers has been identified in non-small cell lung cancer (NSCLC) and molecular testing is recommended to enable optimal individualized treatment. However, data on implementation of these recommendations in the “real-world” setting are scarce. This study presents comprehensive details on the frequency, methodology and results of biomarker testing of advanced NSCLC in Germany.
Patients and methods: This analysis included 3,717 patients with advanced NSCLC (2,921 non-squamous; 796 squamous), recruited into the CRISP registry at start of systemic therapy by 150 German sites between December 2015 and June 2019. Evaluated were the molecular biomarkers EGFR, ALK, ROS1, BRAF, KRAS, MET, TP53, RET, HER2, as well as expression of PD-L1.
Results: In total, 90.5 % of the patients were tested for biomarkers. Testing rates were 92.2 % (non-squamous), 70.7 % (squamous) and increased from 83.2 % in 2015/16 to 94.2% in 2019. Overall testing rates for EGFR, ALK, ROS1, and BRAF were 72.5 %, 74.5 %, 66.1 %, and 53.0 %, respectively (non-squamous). Testing rates for PD-L1 expression were 64.5 % (non-squamous), and 58.5 % (squamous). The most common testing methods were immunohistochemistry (68.5 % non-squamous, 58.3 % squamous), and next-generation sequencing (38.7 % non-squamous, 14.4 % squamous). Reasons for not testing were insufficient tumor material or lack of guideline recommendations (squamous). No alteration was found in 37.8 % (non-squamous), and 57.9 % (squamous), respectively. Most common alterations in non-squamous tumors (all patients/all patients tested for the respective biomarker): KRAS (17.3 %/39.2 %), TP53 (14.1 %/51.4 %), and EGFR (11.0 %/15.1 %); in squamous tumors: TP53 (7.0 %/69.1 %), MET (1.5 %/11.1 %), and EGFR (1.1 %/4.4 %). Median PFS (non-squamous) was 8.7 months (95 % CI 7.4–10.4) with druggable EGFR mutation, and 8.0 months (95 % CI 3.9–9.2) with druggable ALK alterations.
Conclusion: Testing rates in Germany are high nationwide and acceptable in international comparison, but still leave out a significant portion of patients, who could potentially benefit. Thus, specific measures are needed to increase implementation.
Background and aims: Expression of carbonic anhydrase IX (CA9), an enzyme expressed in response to hypoxia, acidosis and oncogenic alterations, is reported to be a prognostic factor in HCC patients. Here we evaluated serum CA9 levels in HCC and cirrhosis patients.
Methods: HCC and cirrhosis patients were prospectively recruited and CA9 levels were determined. CA9 levels were compared to stages of cirrhosis and HCC stages. The association of the CA9 levels and overall survival (OS) was assessed. Furthermore, immunohistochemical CA9 expression in HCC and cirrhosis was evaluated.
Results: 215 patients with HCC were included. The median serum CA9 concentration in patients with HCC was 370 pg/ml and significantly higher than in a healthy cohort. Patients with advanced cancer stages (BCLC and ALBI score) had hid significant higher levels of CA9 in the serum. HCC patients with high serum CA9 concentrations (>400 pg/ml) had an increased mortality risk (hazard ratio (HR) 1.690, 95% confidence interval (CI) 1.017–2.809, P = 0.043). Serum CA9 concentration in cirrhotic patients did not differ significantly from HCC patients. Higher CA9 levels in cirrhotic patients correlated with portal hypertension and esophageal varices. Patients with ethanol induced cirrhosis had the highest CA9 levels in both cohorts. Levels of CA9 did not correlate with immunohistochemical expression.
Conclusions: We conclude that a high CA9 level is a possible prognostic indicator for a poor outcome in HCC patients. The high CA9 levels are probably mainly associated with portal hypertension. Ductular reactions might be a possible source of serum CA9.
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.
Nuclear transport models including density- and momentum-dependent mean-field effects are compared to intranuclear-cascade models and tested on recent data on inclusive p-like cross sections for 800A-MeV La+La. We find a remarkable agreement between most model calculations but a systematic disagreement with the measured yield at 20°, possibly indicating a need for modification of nuclear transport properties at high densities.
Background: MicroRNAs circulating in the blood, stabilized by complexation with proteins and/or additionally by encapsulation in lipid vesicles, are currently being evaluated as biomarkers. The consequences of their differential association with lipids/vesicles for their stability and use as biomarkers are largely unexplored and are subject of the present study.
Methods: The levels of a set of selected microRNAs were determined by quantitative reverse-transcription PCR after extraction from sera or vesicle- and non-vesicle fractions prepared from sera. The stability of these microRNAs after incubation with RNase A or RNase inhibitor, an inhibitor of RNase A family enzymes was studied.
Results: The levels of microRNA-1 and microRNA-122, but not those of microRNA-16, microRNA-21 and microRNA-142-3p, declined significantly during a 5-h incubation of the sera. RNase inhibitor prevented the loss of microRNAs in serum as well as the degradation of microRNA-122, a microRNA not expressed in blood cells, in whole blood. Stabilization of microRNA-122 was also achieved by hemolysis. Prolonged incubation of the sera led to enrichment of vesicle-associated relative to non-vesicle-associated microRNAs. Vesicle-associated microRNAs were more resistant to RNase A treatment than the respective microRNAs not associated with vesicles.
Conclusions: Serum microRNAs showed differential stability upon prolonged incubation. RNase inhibitor might be useful to robustly preserve the pattern of cell-free circulating microRNAs. In the case of microRNAs not expressed in blood cells this can also be achieved by hemolysis. Vesicle-associated microRNAs appeared to be more stable than those not associated with vesicles, which might be useful to disclose additional biomarker properties of miRNAs.
Ecological networks are more sensitive to plant than to animal extinction under climate change
(2016)
Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.
We demonstrate that momentum-dependent nuclear interactions (MDI) have a large effect on the dynamics and on the observables of high-energy heavy-ion collisions: A soft potential with MDI suppresses pion and kaon yields much more strongly than a local hard potential and results in transverse momenta intermediate between soft and hard local potentials. The collective-flow angles and the deuteron-to-proton ratios are rather insensitive to the MDI. Only simultaneous measurements of these observables can give clues on the nuclear equation of state at densities of interest for supernova collapse and neutron-star stability.
The quantum molecular dynamic method is used to study multifragmentation and fragment flow and their dependence on in-medium cross sections, momentum dependent interactions, and the nuclear equation of state, for collisions of 197Au+197Au and 93Nb+93Nb in the bombarding energy regime from 100 to 800A MeV. Time and impact parameter dependence of the fragment formation and their implications for the conjectured liquid-vapor phase transition are investigated. We find that the inclusive fragment mass distribution is independent of the equation of state and exhibits a power-law behavior Y(A)∼A-τ with an exponent τ≊-2.3. True multifragmentation events are found in central collisions for energies Elab∼30–200 MeV/nucleon. The associated light fragment (d,t,α) to proton ratios increase with the multiplicity of charged particles and decrease with energy, in agreement with recent experiments. The calculated absolute charged particle multiplicities, the multiplicities of intermediate mass (A>4) fragments, and their respective rapidity distributions do compare well with recent 4π data, but are quite insensitive to the equation of state. On the other hand, these quantities depend sensitively on the nucleon-nucleon scattering cross section, and can be used to determine σ experimentally. The transverse momentum flow of the complex fragments increases with the stiffness of the equation of state. Reduced (in-medium) n-n scattering cross sections reduce the fragment flow. Momentum dependent interactions increase the fragment flow. It is shown that the measured fragment flow at 200A MeV can be reproduced in the model. We find that also the increase of the px/A values with the fragment mass is in agreement with experiments. The calculated fragment flow is too small as compared to the plastic ball data, if a soft equation of state with in-medium corrections (momentum dependent interactions plus reduced cross sections) is employed. An alternative, most intriguing resolution of the puzzle about the stiffness of the equation of state could be an increase of the scattering cross sections due to precritical scattering in the vicinity of a phase transition.