Mechanistic insights into the inhibition of prostate specific antigen by beta-lactam class compounds

Prostate Specific Antigen (PSA) is a biomarker used in the diagnosis of prostate cancer and to monitor therapeutic response. However, its precise role in prostate carcinogenesis and metastasis remains largely unknown. A number of studies arguing in the favor of an active role of PSA in prostate cancer development and progression have implicated this serine protease in the release and activation of growth factors such as insulin-like growth factor 1 (IGF1) through cleavage of insulin like growth factor binding protein 3 and Transforming Growth Factor beta (TGF-beta) through cleavage of Latent TGF-beta. In contrast, other studies suggest that PSA activity might hinder tumor development and progression. In light of these contradictory findings, efficient inhibitors of PSA are needed for exploring its biological role in tumor development and metastasis. Towards the goal of developing potent inhibitors of PSA, we have explored the molecular mechanism of a series of beta-lactam based compounds on binding to PSA using activity assays, matrix assisted laser desorption ionization with a time-of-flight mass spectrometry, and GOLD docking methodology. The mass spectrometry experiments and the activity assays confirmed the time-dependent and covalent nature of beta-lactam binding. To gain insights on the reaction intermediates at the molecular level, we docked beta-lactam inhibitors to a homology modeled PSA using the GOLD docking program in noncovalent and covalent binding modes. The docking studies elucidated the molecular details of the early noncovalent Michaelis complex, the acyl-enzyme covalent complex, and the nature of conformational reorganization required for the long term stability of the covalent complex. Additionally, the molecular basis for the effect of stereochemistry of the lactam ring on the inhibitory potency was elucidated through docking of beta-lactam enantiomers. As a validation of our docking methodology, two novel enantiomers were synthesized and evaluated for their inhibitory potency using fluorogenic substrate based activity assays. Additionally, cis enantiomers of eight beta-lactam compounds reported in a previous study were docked and their GOLD scores and binding modes were analyzed in order to assess the general applicability of our docking results. The close agreement of our docking results with the experimental data validates the mechanistic insights revealed through the docking studies and paves the way for the design and development of potent and specific inhibitors of PSA.     

非线性接触率和种群动力学对SI传染病模型的影响

本文研究了具有一般非线性接触率和易感类中具有Logistic增长的SI传染病模型的正不变集、平衡位置以及平衡位置的稳定性．     

Size and shape interspecific divergence patterns partly reflect phylogeny in an Onthophagus species‐complex (Coleoptera: Scarabaeidae)

Polyphenism has been suggested as an accelerator for morphological evolution and speciation. In the dung beetles of the genus Onthophagus, horn expression is polyphenic: large males develop horns whereas smaller males express greatly reduced or no horns. Horn static allometries seem to diverge rapidly amongst extant taxa, a process which might trigger changes in the male genital morphology, thus possibly promoting speciation as a by‐product. It can therefore be hypothesized that interspecific distances in allometries and, possibly, in other morphological traits mirror phylogenetic distances. In this study we first assessed the phylogenetic relationships amongst three closely related taxa belonging to the so‐called ‘Onthophagus fracticornis‐similis‐opacicollis’ species‐complex by sequencing the mitochondrial gene cytochrome oxidase subunit 1 (cox1). Biomolecular results indicated three independent lineages, the closest relationships being found between Onthophagus similis and Onthophagus opacicollis. Then we assessed the extent to which divergence pattern of horn static allometries and size and shape divergence patterns of one genital (paramere) and two nongenital (head and epipharynx) structures mirrored the phylogenetic relationships. Interspecific divergence patterns of horn static allometries, paramere, and head shape were found to be congruent with the evolutionary relationships inferred from biomolecular data. Nevertheless, paramere size and epipharynx shape showed patterns not consistent with the phylogeny. Furthermore, the relative size of nongenital structures showed little interspecific divergence compared to their shapes. Our results suggest that size and shape interspecific divergence mirror phylogeny only in part; they also indicate that distinct morphological traits may differ in their tendency to evolve in concert, and that size and shape of the same trait can evolve independently across species. © 2011 The Linnean Society of London, Zoological Journal of the Linnean Society, 2011, 162 , 482–498.     

A dynamic model of thoracic differentiation for the control of turning in the stick insect

Leg movements of stick insects (Carausius morosus) making turns towards visual targets are examined in detail, and a dynamic model of this behaviour is proposed. Initial results suggest that front legs shape most of the body trajectory, while the middle and hind legs just follow external forces (Rosano H, Webb B, in The control of turning in real and simulated stick insects, vol. 4095, pp 145–156, 2006). However, some limitations of this explanation and dissimilarities in the turning behaviour of the insect and the model were found. A second set of behavioural experiments was made by blocking front tarsi to further investigate the active role of the other legs for the control of turning. The results indicate that it is necessary to have different roles for each pair of legs to replicate insect behaviour. We demonstrate that the rear legs actively rotate the body while the middle legs move sideways tangentially to the hind inner leg. Furthermore, we show that on average the middle inner and hind outer leg contribute to turning while the middle outer leg and hind inner leg oppose body rotation. These behavioural results are incorporated into a 3D dynamic robot simulation. We show that the simulation can now replicate more precisely the turns made by the stick insect. This work was supported by CONACYT México and the European Commission under project FP6-2003-IST2-004690 SPARK.     

Detailed dosimetry calculation for in-vitro experiments and its impact on clinical BNCT

PurposeBoron Neutron Capture Therapy (BNCT) is a form of hadrontherapy based on the selective damage caused by the products of neutron capture in ¹⁰B to tumour cells. BNCT dosimetry strongly depends on the parameters of the dose calculation models derived from radiobiological experiments. This works aims at determining an adequate dosimetry for in-vitro experiments involving irradiation of monolayer-cultured cells with photons and BNCT and assessing its impact on clinical settings.M&MDose calculations for rat osteosarcoma UMR-106 and human metastatic melanoma Mel-J cell survival experiments were performed using MCNP, transporting uncharged particles for KERMA determinations, and secondary particles (electrons, protons, ¹⁴C, ⁴He and ⁷Li) to compute absorbed dose in cultures. Dose-survival curves were modified according to the dose correction factors determined from computational studies. New radiobiological parameters of the photon isoeffective dose models for osteosarcoma and metastatic melanoma tumours were obtained. Dosimetry implications considering cutaneous melanoma patients treated in Argentina with BNCT were assessed and discussed.ResultsKERMA values for the monolayer-cultured cells overestimate absorbed doses of radiation components of interest in BNCT. Detailed dose calculations for the osteosarcoma irradiation increased the relative biological effectiveness factor RBE_1% of the neutron component in more than 30%. The analysis based on melanoma cases reveals that the use of survival curves based on KERMA leads to an underestimation of the tumour doses delivered to patients.ConclusionsConsidering detailed dose calculation for in-vitro experiments significantly impact on the prediction of the tumor control in patients. Therefore, proposed methods are clinically relevant.     

Logistic regression when covariates are random effects from a non‐linear mixed model

In many studies, the association of longitudinal measurements of a continuous response and a binary outcome are often of interest. A convenient framework for this type of problems is the joint model, which is formulated to investigate the association between a binary outcome and features of longitudinal measurements through a common set of latent random effects. The joint model, which is the focus of this article, is a logistic regression model with covariates defined as the individual‐specific random effects in a non‐linear mixed‐effects model (NLMEM) for the longitudinal measurements. We discuss different estimation procedures, which include two‐stage, best linear unbiased predictors, and various numerical integration techniques. The proposed methods are illustrated using a real data set where the objective is to study the association between longitudinal hormone levels and the pregnancy outcome in a group of young women. The numerical performance of the estimating methods is also evaluated by means of simulation.     

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine‐scale models to evaluate environmental heterogeneity may help detecting adaptation to micro‐habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata. The two gene pools identified, experiencing limited gene flow along a 1‐km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine‐scale topography. Using a large panel of DEM‐derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high‐resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.