A proteomic and phosphoproteomic landscape of KRAS mutant cancers identifies combination therapies

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Ligh- and electron-microscopic immunocytochemistry of somatotropes in the anterior pituitary gland of European ferret,Mustela putorius furo

Light-microscopic immunocytochemistry of ferret anterior pituitary revealed the localization of somatotropes in the pars distalis, but no immunoreactive cells were detected in the pars tuberalis. Ultrastructural studies by superimposition immunocytochemistry and immuno-electron microscopy, clucidated the morphological heterogeneity of these somatotropic cells. They were classified into 2 subtypes on the basis of size of the secretory granules. Type-I cells with small granules (mean diameter, 192 nm), were considered to be the immature somatotrop, while Type-II cells, with comparatively larger secretory granules (mean diameter, 257 nm), were considered to be the matured form of Type-I cells and the typical somatotropic cell-type, and were much more predominant than the Type-I cells. The fact that Type-II cells had a distinct Golgi zone and many mitochondria, while in Type-I cells the intracellular organelles were generally less developed, supports this suggestion. In addition to these two extreme subtypes, several intermediate forms were also encountered that may represent different transitional phases during the conversion of Type I to Type II. Protein A-gold immuno-electron microscopy illustrated the specific localization of growth hormone over the granules, with no labelling over any other cytoplasmic organelles of the 2 somatotrope subtypes.     

Habitat ecological integrity and environmental impact assessment of anthropic activities: A GIS-based fuzzy logic model for sites of high biodiversity conservation interest

In literature, an effective method enabling the classification, based on a single indicator, of habitats that need a priority protection intervention has not been identified yet. Moreover, the excessive number of landscape metrics, used to quantify integrity of habitats, can cause confusion, often providing redundant and inconsistent results.The aim of this work is to develop a method for evaluating the ecological vulnerability of the habitats in sites of high biodiversity conservation interest. In the first phase, we selected and analyzed, by using principal component analysis (PCA) and fuzzy logic, the landscape metrics, in order to obtain the map of the intrinsic ecological vulnerability index. In the second step, the result of this intrinsic vulnerability was connected, through another fuzzy model, to anthropogenic impacts, obtaining the integrated ecological vulnerability index. We developed specific spatial indicators (landscape metrics), which can examine the mutual position and morphology of the habitats present, along with indicators of human pressure, related to the type and intensity of use of the anthropic territory, with reference to the habitat itself as well as to the areas immediately adjacent. The developed fuzzy models are innovative, compared to the current ecological studies, and examine landscape metrics as well as the impact of human activities.The case study is the “Val Basento-Ferrandina Scalo” Site of Community Importance, Ferrandina-SCI (Basilicata Region, Southern Italy). The results allowed us to build a rank of the habitats based on their intrinsic and integrated ecological vulnerability. Moreover, the results show that, in the Ferrandina-SCI, the most important source of concern is not human activities, but rather the inherent risk of ecological fragility caused by geographical and landscape features of the different patches of habitats themselves.This model aims to be a tool for decision support in sustainable landscape management. It is easy to use and to apply on other regions, although it should always be accompanied by a sensitivity analysis to reduce the subjectivity.     

Snap,crackle, and pop: Acoustic-based model estimation of snapping shrimp populations in healthy and degraded hard-bottom habitats

Human use of the ocean and its ecosystems continues to degrade coastal habitats around the world. Assessing anthropogenic impacts on these environments can be costly and manpower-intensive; thus, the development of rapid, remote techniques to assess habitat quality is important. We employed autonomous hydrophone receivers to record the soundscapes of healthy, sponge-rich hard-bottom habitat in Florida Bay, Florida (USA) and hard-bottom areas impacted by sponge die-offs. We also recorded sounds emanating from individual sponges of three species that were isolated in underwater sound booths, and then enumerated the invertebrates (mostly snapping shrimp) dwelling within the canals of each sponge. From these recordings, a modified cylindrical sound propagation model was used to estimate distances to individual snapping shrimp snaps. Using the program Distance, we estimated snapping shrimp population density and abundance within both habitat types. More snapping shrimp snaps per unit time were recorded in healthy hard-bottom areas as compared to degraded hard-bottom areas. In addition, the average distance to a snap source was greater within degraded hard-bottom areas than within healthy hard-bottom areas. As a consequence, the estimated density and abundance of snapping shrimp were one to two orders of magnitude greater within healthy habitat than within degraded habitat. This study demonstrates the feasibility of using acoustic sampling and modeling to rapidly assess populations of soniferous benthic indicator species, whose vocalizations may yield indirect estimates of habitat quality.     

Translating Cancer Molecular Variability into Personalized Information Using Bulk and Single Cell Approaches

Cancer research is striving toward new frontiers of assigning the correct personalized drug(s) to a given patient. However, extensive tumor heterogeneity poses a major obstacle. Tumors of the same type often respond differently to therapy, due to patient‐specific molecular aberrations and/or untargeted tumor subpopulations. It is frequently not possible to determine a priori which patients will respond to a certain therapy or how an efficient patient‐specific combined therapy should be designed. Large‐scale datasets have been growing at an accelerated pace and various technologies and analytical tools for single cell and bulk level analyses are being developed to extract significant individualized signals from such heterogeneous data. However, personalized therapies that dramatically alter the course of the disease remain scarce, and most tumors still respond poorly to medical care. In this review, the basic concepts of bulk and single cell approaches are discussed, as well as their emerging role in individualized designs of drug therapies, including the advantages and limitations of their applications in personalized medicine.     

Two human cases associated with forensic insects in Riyadh,Saudi Arabia

In Riyadh, Saudi Arabia, we are reporting two cases of natural death. The two bodies showed different types of habitat, insect colonization and decomposition stage. The first case was about the body of a 65-years-old male, with mummification of the clothed body was found in an outdoor habitat. Different life stages of Dermestes maculatus DeGeer (Coleoptera: Dermestidae were gathered from the cadaver, and due to the advanced degree of decomposition, the PMImin was estimated to be 3 months. The second body belonging to a 40-years-old male, was found in a semi-closed apartment (indoor habitat), and the body was at the end of the bloated decomposition stage. In this case, Musca domestica L. (Diptera: Muscidae) larvae were collected, and the PMImin was estimated to be 4 days. The limited insect activity for the two bodies caused by the advanced decomposition stage in the first case and indoor environment in the second. Average temperatures of (23.3 ± 1.6) °C for the first body and (27.5 ± 1.7) °C2 for the second body. Habitat was the key factor to attract insects to the two cadavers. This study stressed that, for accurate estimates of time since death, knowledge of the impact of different variables on insects found over and around the carrion is essential.     

Heterogeneity–diversity relationships in sessile organisms: a unified framework

The hypothesis that environmental heterogeneity promotes species richness by increasing opportunities for niche partitioning is a fundamental paradigm in ecology. However, recent studies suggest that heterogeneity–diversity relationships (HDR) are more complex than expected from this niche‐based perspective, and often show a decrease in richness at high levels of heterogeneity. These findings have motivated ecologists to propose new mechanisms that may explain such deviations. Here we provide an overview of currently recognised mechanisms affecting the shape of HDRs and present a conceptual model that integrates all previously proposed mechanisms within a unified framework. We also translate the proposed framework into an explicit community dynamic model and use the model as a tool for generating testable predictions concerning how landscape properties interact with species traits in determining the shape of HDRs. Our main finding is that, despite the enormous complexity of such interactions, the predicted HDRs are rather simple, ranging from positive to unimodal patterns in a highly consistent and predictable manner.     

Genetic variants and underlying mechanisms influencing variance heterogeneity in maize

Traditional genetic studies focus on identifying genetic variants associated with the mean difference in a quantitative trait. Because genetic variants also influence phenotypic variation via heterogeneity, we conducted a variance‐heterogeneity genome‐wide association study to examine the contribution of variance heterogeneity to oil‐related quantitative traits. We identified 79 unique variance‐controlling single nucleotide polymorphisms (vSNPs) from the sequences of 77 candidate variance‐heterogeneity genes for 21 oil‐related traits using the Levene test (P < 1.0 × 10^?5). About 30% of the candidate genes encode enzymes that work in lipid metabolic pathways, most of which define clear expression variance quantitative trait loci. Of the vSNPs specifically associated with the genetic variance heterogeneity of oil concentration, 89% can be explained by additional linked mean‐effects genetic variants. Furthermore, we demonstrated that gene × gene interactions play important roles in the formation of variance heterogeneity for fatty acid compositional traits. The interaction pattern was validated for one gene pair (GRMZM2G035341 and GRMZM2G152328) using yeast two‐hybrid and bimolecular fluorescent complementation analyses. Our findings have implications for uncovering the genetic basis of hidden additive genetic effects and epistatic interaction effects, and we indicate opportunities to stabilize efficient breeding and selection of high‐oil maize (Zea mays L.).