Biophysical mechanisms of endotoxin neutralization by cationic amphiphilic peptides

Bacterial endotoxins (lipopolysaccharides (LPS)) are strong elicitors of the human immune system by interacting with serum and membrane proteins such as lipopolysaccharide-binding protein (LBP) and CD14 with high specificity. At LPS concentrations as low as 0.3 ng/ml, such interactions may lead to severe pathophysiological effects, including sepsis and septic shock. One approach to inhibit an uncontrolled inflammatory reaction is the use of appropriate polycationic and amphiphilic antimicrobial peptides, here called synthetic anti-LPS peptides (SALPs). We designed various SALP structures and investigated their ability to inhibit LPS-induced cytokine secretion in vitro, their protective effect in a mouse model of sepsis, and their cytotoxicity in physiological human cells. Using a variety of biophysical techniques, we investigated selected SALPs with considerable differences in their biological responses to characterize and understand the mechanism of LPS inactivation by SALPs. Our investigations show that neutralization of LPS by peptides is associated with a fluidization of the LPS acyl chains, a strong exothermic Coulomb interaction between the two compounds, and a drastic change of the LPS aggregate type from cubic into multilamellar, with an increase in the aggregate sizes, inhibiting the binding of LBP and other mammalian proteins to the endotoxin. At the same time, peptide binding to phospholipids of human origin (e.g., phosphatidylcholine) does not cause essential structural changes, such as changes in membrane fluidity and bilayer structure. The absence of cytotoxicity is explained by the high specificity of the interaction of the peptides with LPS.     

Accounting for preferential sampling in species distribution models

Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a finite number of locations in order to predict where (and how much of) a species is likely to be present in unsampled locations. Standard geostatistical methodology assumes that the choice of sampling locations is independent of the values of the variable of interest. However, in natural environments, due to practical limitations related to time and financial constraints, this theoretical assumption is often violated. In fact, data commonly derive from opportunistic sampling (e.g., whale or bird watching), in which observers tend to look for a specific species in areas where they expect to find it. These are examples of what is referred to as preferential sampling, which can lead to biased predictions of the distribution of the species. The aim of this study is to discuss a SDM that addresses this problem and that it is more computationally efficient than existing MCMC methods. From a statistical point of view, we interpret the data as a marked point pattern, where the sampling locations form a point pattern and the measurements taken in those locations (i.e., species abundance or occurrence) are the associated marks. Inference and prediction of species distribution is performed using a Bayesian approach, and integrated nested Laplace approximation (INLA) methodology and software are used for model fitting to minimize the computational burden. We show that abundance is highly overestimated at low abundance locations when preferential sampling effects not accounted for, in both a simulated example and a practical application using fishery data. This highlights that ecologists should be aware of the potential bias resulting from preferential sampling and account for it in a model when a survey is based on non‐randomized and/or non‐systematic sampling.     

Fine needle aspiration appearance of extragastrointestinal stromal tumor. A case report

BACKGROUND: Gastrointestinal stromal tumors (GISTs) rarely develop outside the digestive tract and in the soft tissues of abdomen and retroperitoneum. Such tumors are designated extra-GISTs (EGISTs). Cytologic and immunocytochemical features of a case of EGIST are reported. CASE: A 54-year-old woman presented with a peritoneal mass, diameter 22 cm, adherent to the omentum and without a connection to the digestive tract. Fine needle aspiration biopsy (FNAB) of the excised tumor showed high cellularity in two patterns: monotonous spindle cells were intermingled with a mildly atypical epithelioid component. Immunocytochemistry performed on cytospins revealed reactivity for c-kit (CD117), CD34 and smooth muscle actin and negativity for S-100. The findings were concordant with a histologic diagnosis of EGIST. CONCLUSION: EGISTs are infrequent neoplasms and can be diagnosed in FNAB samples. The clinical/radiologic setting must be considered together with the cytologic features. Immunocytochemistry is a clue to the diagnosis when it detects c-kit reactivity.     

Short-term variations in the physiological state of phytoplankton [2pt] in a shallow temperate estuary

Short-term changes in the photosynthetic carbon metabolism and physiological state of phytoplankton were studied over a summer fortnight-long period in the Urdaibai estuary (Bay of Biscay) and related to observed environmental patterns. Day-to-day variability in the hydrographical and biological features of the estuary during the study period was due to changes in meteorological and tidal conditions. Phytoplankton biomass and primary production increased with the improvement of weather, i.e., light conditions, during neap tides. Thus a mixed bloom of cryptophyceans, Euglena sp., and the dinoflagellate Peridinium foliaceum developed in the middle and upper estuary. Photosynthetic responses of phytoplankton were related to the time-scale of changes in light regime. Allocation of photosynthate to major macromolecular classes (LMWM, lipid, polysaccharide, and protein), like phytoplankton biomass and primary production, showed strong spatio-temporal variability. High carbon fixation into low molecular weight metabolites was associated with growth limitation by low light. The relative incorporation of photosynthetic carbon into proteins increased at the beginning of the phytoplankton bloom but overall, it was rather constant. However, carbon allocation into storage products such us lipid or polysaccharide increased when carbon and energy produced under optimal growth conditions exceeded what could be assimilated into protein. These patterns are explained by both spatio-temporal changes in the environmental conditions and species-specific differences. In general, daily variability appeared to be more important than diurnal periodicity in the physiological responses of phytoplankton. Results from this study show that phytoplankton photosynthesis and carbon metabolism are simultaneously affected by biotic and abiotic factors, although short-term light fluctuations may have a major influence on the physiological state of phytoplankton in the Urdaibai estuary.