A class of pyrrole derivatives endowed with analgesic/anti-inflammatory activity

We report the synthesis and bio-pharmacological evaluation of a class of pyrrole derivatives featuring a small appendage fragment (carbaldehyde, oxime, nitrile) on the central core. Compound 1c proved to be extremely effective in vivo, showing an interesting anti-nociceptic profile that is comparable to reference compounds already marketed, hence representing a great stimulus for a further improvement of this class of molecules.     

The key role of “Moscato bianco” and “Malvasia aromatica di Parma” in the parentage of traditional aromatic grape varieties

A great number of flavored grape varieties, of significant oenological potential, are traditionally cultivated in north-western Italy, besides the renowned “Moscato bianco” (syn. “Muscat à petits grains blancs”). Understanding their origin, besides its historical and scientific interest, would help to increase market appeal and consequently facilitate the commercial exploitation of these products. Twenty-four aromatic genotypes were investigated for their identity, kinship relations, and genetic origins through molecular markers (SSR and SNPs) supported by plant morphology and historical information. Flavored grape genotypes from other regions, possible ancestors, and reference cultivars of known pedigree were also included in the analysis. Kinship analysis used a likelihood-based approach (IBS, IBD, relatedness coefficients, and likelihood ratios) to achieve strong statistical support. The analyses revealed two possible leading genitors, in turn closely related by a parent/offspring relationship: “Moscato bianco” and “Malvasia aromatica di Parma,” a female grape cultivar that is today almost extinct. The outlined molecular and statistical approach could be applied for the investigation on the origin of ancient traditional cultivars of other vegetative propagated species.     

Shape-Related Toxicity of Titanium Dioxide Nanofibres

Titanium dioxide (TiO₂) nanofibres are a novel fibrous nanomaterial with increasing applications in a variety of fields. While the biological effects of TiO₂ nanoparticles have been extensively studied, the toxicological characterization of TiO₂ nanofibres is far from being complete. In this study, we evaluated the toxicity of commercially available anatase TiO₂ nanofibres using TiO₂ nanoparticles (NP) and crocidolite asbestos as non-fibrous or fibrous benchmark materials. The evaluated endpoints were cell viability, haemolysis, macrophage activation, trans-epithelial electrical resistance (an indicator of the epithelial barrier competence), ROS production and oxidative stress as well as the morphology of exposed cells. The results showed that TiO₂ nanofibres caused a cell-specific, dose-dependent decrease of cell viability, with larger effects on alveolar epithelial cells than on macrophages. The observed effects were comparable to those of crocidolite, while TiO₂ NP did not decrease cell viability. TiO₂ nanofibres were also found endowed with a marked haemolytic activity, at levels significantly higher than those observed with TiO₂ nanoparticles or crocidolite. Moreover, TiO₂ nanofibres and crocidolite, but not TiO₂ nanoparticles, caused a significant decrease of the trans-epithelial electrical resistance of airway cell monolayers. SEM images demonstrated that the interaction with nanofibres and crocidolite caused cell shape perturbation with the longest fibres incompletely or not phagocytosed. The expression of several pro-inflammatory markers, such as NO production and the induction of Nos2 and Ptgs2, was significantly increased by TiO₂ nanofibres, as well as by TiO₂ nanoparticles and crocidolite. This study indicates that TiO₂ nanofibres had significant toxic effects and, for most endpoints with the exception of pro-inflammatory changes, are more bio-active than TiO₂ nanoparticles, showing the relevance of shape in determining the toxicity of nanomaterials. Given that several toxic effects of TiO₂ nanofibres appear comparable to those observed with crocidolite, the possibility that they exert length dependent toxicity in vivo seems worthy of further investigation.     

Skewed Differentiation of Circulating Vγ9Vδ2 T Lymphocytes in Melanoma and Impact on Clinical Outcome

Objective

The aim of this study was to evaluate over time circulating γδ T lymphocytes in melanoma patients in terms of frequency, effector functions, and relationship with clinical stage and evolution, by comparing preoperative values to those obtained at a mean follow-up of 36 months or in the event of recurrence or disease progression, and to those of healthy controls. Also, we correlated the presence of tumor-infiltrating γδ T lymphocytes with clinical evolution of melanoma.

Results

Mean frequencies of circulating γδ T cells before and after melanoma removal were very similar and comparable to healthy subjects, but patients who progressed to stage III or IV showed a significantly decreased frequency of circulating Vγ9Vδ2 T cells. The distribution of Vγ9Vδ2 memory and effector subsets was similar in healthy subjects and melanoma patients at diagnosis, but circulating γδ T cells of patients after melanoma removal had a skewed terminally-differentiated effector memory phenotype. Highly suggestive of progressive differentiation toward a cytotoxic phenotype, Vγ9Vδ2T cells from patients at follow up had increased cytotoxic potential and limited cytokine production capability, while the opposite pattern was detected in Vγ9Vδ2T cells from patients before melanoma removal.

Conclusions

Follow-up data also showed that tumor infiltrating γδ T cells were significantly associated with lower mortality and relapse rates, suggesting that they may serve as a prognostic biomarker, for human melanoma.     

Analysis of physical pore space characteristics of two pyrolytic biochars and potential as microhabitat

Plant and Soil - Biochar amendment to soil is a promising practice of enhancing productivity of agricultural systems. The positive effects on crop are often attributed to a promotion of beneficial...     

Pyrazolo[1,5-a]quinazoline scaffold as 5-deaza analogue of pyrazolo[5,1-c][1,2,4]benzotriazine system: synthesis of new derivatives,biological activity on GABAA receptor subtype and molecular dynamic study

To investigate the binding affinity of GABA_A receptor subtype, new pyrazolo [1,5-a]quinazolines were designed, synthesized, and in vitro evaluated. These compounds, 5-deaza analogues of pyrazolo[5,1-c][1,2,4]benzotriazine derivatives which were already studied in our research group, permit us to evaluate the relevance of the nitrogen or the oxygen atom at 5-position of the tricyclic scaffold. Molecular dynamic study was done on a set of the new and known ligands to rationalize and to explain the lack of affinity on the 4- or 5-substituted new derivative. In fact, from biological results, it can be found that the only 5-unsubstituted new derivative, compound 15, has receptor recognition (K_i?=?834.7?nM).     

Precise periodic components estimation for chronobiological signals through Bayesian Inference with sparsity enforcing prior

The toxicity and efficacy of more than 30 anticancer agents present very high variations, depending on the dosing time. Therefore, the biologists studying the circadian rhythm require a very precise method for estimating the periodic component (PC) vector of chronobiological signals. Moreover, in recent developments, not only the dominant period or the PC vector present a crucial interest but also their stability or variability. In cancer treatment experiments, the recorded signals corresponding to different phases of treatment are short, from 7 days for the synchronization segment to 2 or 3 days for the after-treatment segment. When studying the stability of the dominant period, we have to consider very short length signals relative to the prior knowledge of the dominant period, placed in the circadian domain. The classical approaches, based on Fourier transform (FT) methods are inefficient (i.e., lack of precision) considering the particularities of the data (i.e., the short length). Another particularity of the signals considered in such experiments is the level of noise: such signals are very noisy and establishing the periodic components that are associated with the biological phenomena and distinguishing them from the ones associated with the noise are difficult tasks. In this paper, we propose a new method for the estimation of the PC vector of biomedical signals, using the biological prior informations and considering a model that accounts for the noise. The experiments developed in cancer treatment context are recording signals expressing a limited number of periods. This is a prior information that can be translated as the sparsity of the PC vector. The proposed method considers the PC vector estimation as an Inverse Problem (IP) using the general Bayesian inference in order to infer the unknown of our model, i.e. the PC vector but also the hyperparameters (i.e the variances). The sparsity prior information is modeled using a sparsity enforcing prior law. In this paper, we propose a Student’s t distribution, viewed as the marginal distribution of a bivariate normal-inverse gamma distribution. We build a general infinite Gaussian scale mixture (IGSM) hierarchical model where we assign prior distributions also for the hyperparameters. The expression of the joint posterior law of the unknown PC vector and hyperparameters is obtained via Bayes rule, and then, the unknowns are estimated via joint maximum a posteriori (JMAP) or posterior mean (PM). For the PM estimator, the expression of the posterior distribution is approximated by a separable one, via variational Bayesian approximation (VBA), using the Kullback-Leibler (KL) divergence. For the PM estimation, two possibilities are considered: an approximation with a partially separable distribution and an approximation with a fully separable one. Both resulting algorithms corresponding to the PM estimation and the one corresponding to the JMAP estimation are iterative algorithms. The algorithms are presented in detail and are compared with the ones corresponding to the Gaussian model. We examine the convergency of the algorithms and give simulation results to compare their performances. Finally, we show simulation results on synthetic and real data in cancer treatment applications. The real data considered in this paper examines the rest-activity patterns of KI/KI Per2::luc mouse, aged 10 weeks, singly housed in RealTime Biolumicorder (RT-BIO).