Effects of microgravity and hypergravity on early development stages of Xeonopus laevis

The aim of this work is to evaluate the development of X.l. in modified gravity conditions. The simulation of hyper and microgravity was performed utilizing: an hyperfuge, a Clinostat and later on a Random Positioning Machine (RPM, 3d Clinostat). The effect of hypergravity on embryos is significantly higher than that of microgravity; the exposure of embryos to 3xg for 3 days before and after hatch causes an activation of HSP-60 and HSP-70. Embryos exposed to 3xg during the first 3 days of development are very sensitive and show a retard of development, with a lower content of DNA, neutral glycolipids and gangliosides compared to controls.     

Identification of the human salivary cystatin complex by the coupling of high-performance liquid chromatography and ion-trap mass spectrometry

Human salivary cystatins, five major (S, S1, S2, SA, SN) and two minor (C and D), are multifunctional proteins playing a different role in the oral environment. Salivary cystatin SN is able to effectively inhibit lysosomal cathepsins B, C, H and L and cystatin SA inhibits cathepsins C and L in vitro. These activities suggest, particularly for cystatin SN, an important role in the control of proteolytic events in vivo. Differently, cystatins S are involved, together with statherin, in the mineral balance of the tooth. Due to their distinct role, a reliable method for identification and quantification of the different cystatins, as well as of possible truncated and derived forms, could be helpful for the assessment of the status of the oral cavity. To this purpose high-performance liquid chromatography electrospray ionization mass spectrometry (HPLC-ESI MS) was applied to the analysis of human saliva obtained from healthy subjects. All known salivary cystatins, with the exception of cystatin C, were detected. Strong evidence was also obtained for the presence in saliva of post-translational modified isoforms of cystatins, which may be related to donor habits. Cystatin SN and cystatins S, S1 and S2 were well separated by HPLC-ESI MS coupling from other components and thus this approach can be successfully applied to their quantification.     

The Guanine Nucleotide Exchange Factor ARNO mediates the activation of ARF and phospholipase D by insulin

Background  

Phospholipase D (PLD) is involved in many signaling pathways. In most systems, the activity of PLD is primarily regulated by the members of the ADP-Ribosylation Factor (ARF) family of GTPases, but the mechanism of activation of PLD and ARF by extracellular signals has not been fully established. Here we tested the hypothesis that ARF-guanine nucleotide exchange factors (ARF-GEFs) of the cytohesin/ARNO family mediate the activation of ARF and PLD by insulin.     

Collagen fibrils are differently organized in weight-bearing and not-weight-bearing regions of pig articular cartilage

The magnetic resonance (MR) appearance of the weight-bearing ("loaded") and not-weight-bearing ("unloaded") regions in T(2)-weighted images of pig articular cartilage is different. On the hypothesis that this difference may be ascribed, at least in part, to a different collagen fibre organization in the two regions, this organization was studied using biochemical, histological, and X-ray diffraction methods. While the mean concentrations of collagen and of its cross-links were the same in the two regions, a regular small angle X-ray diffraction pattern was observed only for the habitually "loaded" tissue. It was also seen by light microscopy that the four typical functional zones were well displayed in the "loaded" cartilage whereas they were not clearly depicted in the "unloaded" tissue. Collagen presented a high concentration of fibrils forming an intricate and dense meshwork at the surface of both "loaded" and "unloaded" cartilage. A second zone of high collagen concentration was present at the upper layer of the deep zone of "loaded" cartilage. By contrast, this lamina of highly concentrated fibrils was lacking in "unloaded" cartilage and collagen fibrils appear thinner. Our study proves that the organization of collagen fibres is different for the "loaded" and "unloaded" regions of articular cartilage. It also suggests that this different organization may influence the MR appearance of the tissue. J. Exp. Zool. 287:346-352, 2000.     

Design and synthesis of 4-[3,5-dioxo-11-oxa-4,9-diazatricyclo[5.3.1.02,6]undec-4-yl]-2-trifluoromethyl-benzonitriles as androgen receptor antagonists

A novel series of 4-[3,5-dioxo-11-oxa-4,9-diazatricyclo[5.3.1.0^2,6]undec-4-yl]-2-trifluoromethyl-benzonitriles has been synthesized. The ability of these compounds to act as antagonists of the androgen receptor was investigated and several were found to have potent activity in vitro and in vivo.     

Protectome Analysis: A New Selective Bioinformatics Tool for Bacterial Vaccine Candidate Discovery

New generation vaccines are in demand to include only the key antigens sufficient to confer protective immunity among the plethora of pathogen molecules. In the last decade, large-scale genomics-based technologies have emerged. Among them, the Reverse Vaccinology approach was successfully applied to the development of an innovative vaccine against Neisseria meningitidis serogroup B, now available on the market with the commercial name BEXSERO® (Novartis Vaccines). The limiting step of such approaches is the number of antigens to be tested in in vivo models. Several laboratories have been trying to refine the original approach in order to get to the identification of the relevant antigens straight from the genome. Here we report a new bioinformatics tool that moves a first step in this direction. The tool has been developed by identifying structural/functional features recurring in known bacterial protective antigens, the so called “Protectome space,” and using such “protective signatures” for protective antigen discovery. In particular, we applied this new approach to Staphylococcus aureus and Group B Streptococcus and we show that not only already known protective antigens were re-discovered, but also two new protective antigens were identified.Although vaccines based on attenuated pathogens as pioneered by Luis Pasteur have been shown to be extremely effective, safety and technical reasons recommend that new generation vaccines include few selected pathogen components which, in combination with immunostimulatory molecules, can induce long lasting protective responses. Such approach implies that the key antigens sufficient to confer protective immunity are singled out among the plethora of pathogen molecules. As it turns out, the search for such protective antigens can be extremely complicated.Genomic technologies have opened the way to new strategies in vaccine antigen discovery (1, 2, 3). Among them, Reverse Vaccinology (RV)¹ has proved to be highly effective, as demonstrated by the fact that a new Serogroup B Neisseria meningitidis (MenB) vaccine, incorporating antigens selected by RV, is now available to defeat meningococcal meningitis (4, 5). In essence, RV is based on the simple assumption that cloning all annotated proteins/genes and screening them against a robust and reliable surrogate-of-protection assay must lead to the identification of all protective antigens. Because most of the assays available for protective antigen selection involve animal immunization and challenge, the number of antigens to be tested represents a severe bottleneck of the entire process. For this reason, despite the fact that RV is a brute force, inclusive approach (“test-all-to-lose-nothing” type of approach) in their pioneered work of MenB vaccine discovery, Pizza and co-workers did not test the entire collection of MenB proteins but rather restricted their analysis to the ones predicted to be surface-localized. This was based on the evidence that for an anti-MenB vaccine to be protective bactericidal antibodies must be induced, a property that only surface-exposed antigens have. For the selection of surface antigens Pizza and co-workers mainly used PSORT and other available tools like MOTIFS and FINDPATTERNS to find proteins carrying localization-associated features such as transmembrane domains, leader peptides, and lipobox and outer membrane anchoring motifs. At the end, 570 proteins were selected and entered the still very labor intensive screening phase. Over the last few years, our laboratories have been trying to move to more selective strategies. Our ultimate goal, we like to refer to as the “Holy Grail of Vaccinology,” is to identify protective antigens by “simply” scanning the genome sequence of any given pathogen, thus avoiding time consuming “wet science” and “move straight from genome to the clinic” (6).With this objective in mind, we have developed a series of proteomics-based protocols that, in combination with bioinformatics tools, have substantially reduced the number of antigens to be tested in the surrogate-of-protection assays (7, 8). In particular, we have recently described a three-technology strategy that allows to narrow the number of antigens to be tested in the animal models down to less than ten (9). However, this strategy still requires high throughput experimental activities. Therefore, the availability of in silico tools that selectively and accurately single out relevant categories of antigens among the complexity of pathogen components would greatly facilitate the vaccine discovery process.In the present work, we describe a new bioinformatics approach that brings an additional contribution to our “from genome to clinic” goal. The approach has been developed on the basis of the assumption that protective antigens are protective in that they have specific structural/functional features (“protective signatures”) that distinguish them from immunologically irrelevant pathogen components. These features have been identified by using existing databases and prediction tools, such as PFam and SMART. Our approach focuses on protein biological role rather than its localization: it is completely protein localization unbiased, and lead to the identification of both surface-exposed and secreted antigens (which are the majority in extracellular bacteria) as well as cytoplasmic protective antigens (for instance, antigens that elicit interferon γ producing CD4+ T cells, thus potentiating the killing activity of phagocytic cells toward intracellular pathogens). Should these assumptions be valid, PS could be identified if: (1) all known protective antigens are compiled to create what we refer to as “the Protectome space,” and (2) Protectome is subjected to computer-assisted scrutiny using selected tools. Once signatures are identified, novel protective antigens of a pathogen of interest should be identifiable by scanning its genome sequence in search for proteins that carry one or more protective signatures. A similar attempt has been reported (10), where the discrimination of protective antigens versus nonprotective antigens was tried using statistical methods based on amino acid compositional analysis and auto cross-covariance. This model was implemented in a server for the prediction of vaccine candidates, that is, Vaxijen (www.darrenflower.info/Vaxijen); however, the selection criteria applied are still too general leading to a list of candidates that include ca. 30% of the total genome ORFs very similarly to the number of antigens predicted by classical RV based on the presence of localization signals.Here we show that Protectome analysis unravels specific signatures embedded in protective antigens, most of them related to the biological role/function of the proteins. These signatures narrow down the candidate list to ca. 3% of the total ORFs content and can be exploited for protective antigen discovery. Indeed, the strategy was validated by demonstrating that well characterized vaccine components could be identified by scanning the genome sequence of the corresponding pathogens for the presence of the PS. Furthermore, when the approach was applied to Staphylococcus aureus and Streptococcus agalactiae (Group B Streptococcus, GBS) not only already known protective antigens were rediscovered, but also two new protective antigens were identified.     

Independent Neuronal Origin of Seizures and Behavioral Comorbidities in an Animal Model of a Severe Childhood Genetic Epileptic Encephalopathy

The childhood epileptic encephalopathies (EE’s) are seizure disorders that broadly impact development including cognitive, sensory and motor progress with severe consequences and comorbidities. Recently, mutations in DNM1 (dynamin 1) have been implicated in two EE syndromes, Lennox-Gastaut Syndrome and Infantile Spasms. Dnm1 encodes dynamin 1, a large multimeric GTPase necessary for activity-dependent membrane recycling in neurons, including synaptic vesicle endocytosis. Dnm1^Ftfl or “fitful” mice carry a spontaneous mutation in the mouse ortholog of DNM1 and recapitulate many of the disease features associated with human DNM1 patients, providing a relevant disease model of human EE’s. In order to examine the cellular etiology of seizures and behavioral and neurological comorbidities, we engineered a conditional Dnm1^Ftfl mouse model of DNM1 EE. Observations of Dnm1 ^Ftfl/flox mice in combination with various neuronal subpopulation specific cre strains demonstrate unique seizure phenotypes and clear separation of major neurobehavioral comorbidities from severe seizures associated with the germline model. This demonstration of pleiotropy suggests that treating seizures per se may not prevent severe comorbidity observed in EE associated with dynamin-1 mutations, and is likely to have implications for other genetic forms of EE.     

A Multicenter,Randomized, Controlled Trial of Osteopathic Manipulative Treatment on Preterms

BackgroundDespite some preliminary evidence, it is still largely unknown whether osteopathic manipulative treatment improves preterm clinical outcomes.ResultsA total of 695 newborns were randomly assigned to either the study group (n= 352) or the control group (n=343). A statistical significant difference was observed between the two groups for the primary outcome (13.8 and 17.5 days for the study and control group respectively, p<0.001, effect size: 0.31). Multivariate analysis showed a reduction of the length of stay of 3.9 days (95% CI -5.5 to -2.3, p<0.001). Furthermore, there were significant reductions with treatment as compared to usual care in cost (difference between study and control group: 1,586.01€; 95% CI 1,087.18 to 6,277.28; p<0.001) but not in daily weight gain. There were no complications associated to the intervention.ConclusionsOsteopathic treatment reduced significantly the number of days of hospitalization and is cost-effective on a large cohort of preterm infants.     

The Changes of Lipid Metabolism in Advanced Renal Cell Carcinoma Patients Treated with Everolimus: A New Pharmacodynamic Marker?

Background

Everolimus is a mammalian target of rapamycin (mTOR) inhibitor approved for the treatment of metastatic renal cell carcinoma (mRCC). We aimed to assess the association between the baseline values and treatmentrelated modifications of total serum cholesterol (C), triglycerides (T), body mass index (BMI), fasting blood glucose level (FBG) and blood pressure (BP) levels and the outcome of patients treated with everolimus for mRCC.

Methods

177 patients were included in this retrospective analysis. Time to progression (TTP), clinical benefit (CB) and overall survival (OS) were evaluated.

Results

Basal BMI was significantly higher in patients who experienced a CB (p=0,0145). C,T and C+T raises were significantly associated with baseline BMI (p=0.0412, 0.0283 and 0.0001). Median TTP was significantly longer in patients with T raise compared to patients without T (10 vs 6, p=0.030), C (8 vs 5, p=0.042) and C+T raise (10.9 vs 5.0, p=0.003). At the multivariate analysis, only C+T increase was associated with improved TTP (p=0.005). T raise (21.0 vs 14.0, p=0.002) and C+T increase (21.0 vs 14.0, p=0.006) were correlated with improved OS but were not significant at multivariate analysis.

Conclusion

C+T raise is an early predictor for everolimus efficacy for patients with mRCC.     

Dietary Total Antioxidant Capacity and Colorectal Cancer in the Italian EPIC Cohort

Background

Colorectal cancer is the third most common cancer worldwide. Diet has been hypothesized as involved in colorectal cancer etiology, but few studies on the influence of total dietary antioxidant intake on colorectal cancer risk have been performed.

Methods

We investigated the association between colorectal cancer risk and the total antioxidant capacity (TAC) of the diet, and also of intake of selected antioxidants, in 45,194 persons enrolled in 5 centers (Florence, Naples, Ragusa, Turin and Varese) of the European Prospective Investigation into Cancer and Nutrition (EPIC) Italy study. TAC was estimated by the Trolox equivalent antioxidant capacity (TEAC) assay. Hazard ratios (HRs) for developing colorectal cancer, and colon and rectal cancers separately, adjusted for confounders, were estimated for tertiles of TAC by Cox modeling, stratifying by center.

Results

Four hundred thirty-six colorectal cancers were diagnosed over a mean follow-up of 11.28 years. No significant association between dietary TAC and colorectal cancer incidence was found. However for the highest category of TAC compared to the lowest, risk of developing colon cancer was lower (HR: 0.63; 95% CI: 0.44–0.89, P trend: 0.008). By contrast, increasing TAC intake was associated with significantly increasing risks of rectal cancer (2nd tertile HR: 2.09; 95%CI: 1.19–3.66; 3rd tertile 2.48 95%CI: 1.32–4.66; P trend 0.007). Intakes of vitamin C, vitamin E, and ß-carotene were not significantly associated with colorectal cancer risk.

Conclusions

Further prospective studies are needed to confirm the contrasting effects of high total antioxidant intake on risk of colon and rectal cancers.