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The clinical application of sparingly soluble drugs is hampered by the wide range of problems associated to their delivery. Herein we present a new physical hydrogel as a delivery system for these drugs. The strategy behind the design of this delivery system involved the incorporation of the protein albumin into the hydrogel with the aim of exploiting its intrinsic capacity to bind small hydrophobic molecules. Prednisolone and ketoconazole were used as model drug molecules. A combination of the saturation transfer difference (STD) spectra and a novel double titration assay followed by NMR was applied to study all of the possible binding modes between albumin and each drug. Finally, the ability of the hydrogel system to release the two model drugs was corroborated. The results of the release studies were in agreement with the drug binding capacities derived from the NMR studies, thus confirming that the potential of the NMR approach as a predictive technique could be useful in evaluating the designs of new drug delivery systems., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Two of the main types of nanotubular architectures are the single-walled carbon nanotubes (SWCNTs) and the self-assembling cyclic peptide nanotubes (SCPNs). We here report the preparation of the dual composite resulting from the ordered combination of both tubular motifs. In the resulting architecture, the SWCNTs can act as templates for the assembly of SCPNs that engage the carbon nanotubes noncovalently via pyrene "paddles", each member of the resulting hybrid stabilizing the other in aqueous solution. The particular hybrids obtained in the present study formed highly ordered oriented arrays and display complementary properties such as electrical conductivity. Furthermore, a self-sorting of the cyclic peptides toward semiconducting rather than metallic SWCNTs is also observed in the aqueous dispersions. It is envisaged that a broad range of exploitable properties may be achieved and/or controlled by varying the cyclic peptide components of similar SWCNT/SCPN hybrids.

Iron oxide nanoparticles (ION), with different coatings and sizes, have attracted extensive interest in the last years to be applied in drug delivery, cancer therapy and as contrast agents in imagiologic techniques such as magnetic resonance imaging. However, the safety of these nanoparticles is still not completely established, particularly to host defense systems that are usually recruited for their clearance from the body. In this paper, given the importance of neutrophils in the immune response of the organism to nanoparticles, the effect of polyacrylic acid (PAA)-coated and non-coated ION on human neutrophils was evaluated in vitro, namely their capacity to activate the oxidative burst and to modify their lifespan. The obtained results showed that the studied PAA-coated and non-coated ION triggered neutrophils' oxidative burst in a NADPH oxidase dependent manner, and that PAA-coated ION increased - while non-coated ION prevented - apoptotic signaling and apoptosis. These effects may have important clinical implications in biomedical applications of ION., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

The traditional lack of techniques suitable for in vivo imaging has induced a great interest in molecular imaging for preclinical research. Nevertheless, its use spreads slowly due to the difficulties in justifying the high cost of the current dedicated preclinical scanners. An alternative for lowering the costs is to repurpose old clinical gamma cameras to be used for preclinical imaging. In this paper we assess the performance of a portable device, that is, working coupled to a single-head clinical gamma camera, and we present our preliminary experience in several small animal applications. Our findings, based on phantom experiments and animal studies, provided an image quality, in terms of contrast-noise trade-off, comparable to dedicated preclinical pinhole-based scanners. We feel that our portable device offers an opportunity for recycling the widespread availability of clinical gamma cameras in nuclear medicine departments to be used in small animal SPECT imaging and we hope that it can contribute to spreading the use of preclinical imaging within institutions on tight budgets.

Perturbation methods add variation terms to a known experimental solution of one problem to approach a solution for a related problem without known exact solution. One problem of this type in immunology is the prediction of the possible action of epitope of one peptide after a perturbation or variation in the structure of a known peptide and/or other boundary conditions (host organism, biological process, and experimental assay). However, to the best of our knowledge, there are no reports of general-purpose perturbation models to solve this problem. In a recent work, we introduced a new quantitative structure-property relationship theory for the study of perturbations in complex biomolecular systems. In this work, we developed the first model able to classify more than 200,000 cases of perturbations with accuracy, sensitivity, and specificity >90% both in training and validation series. The perturbations include structural changes in >50000 peptides determined in experimental assays with boundary conditions involving >500 source organisms, >50 host organisms, >10 biological process, and >30 experimental techniques. The model may be useful for the prediction of new epitopes or the optimization of known peptides towards computational vaccine design.

Here we report the development of polymeric nanoparticles, made of poly(lactide-co-glycolide) (PLGA) chemically modified with mannosamine (MN), intended to specifically interact with the intestinal mucosa and facilitate the intestinal transport of proteins. PLGA-MN nanoparticles displayed nanometric size and a negative zeta potential, which was lower than that of the PLGA nanoparticles. This correlate well with the preferential location of the MN group on the nanoparticles surface obtained by X-ray photoelectron spectroscope (XPS). The presence of MN groups in the polymer chain led to a different surface morphology noted by SEM, an increase of the encapsulation of model proteins, and to help stabilizing the nanoparticles in simulated intestinal fluids. Furthermore, the MN modification significantly enhanced the nanoparticle's interaction with the epithelial cells in human intestinal follicle-associated epithelium cell culture model. Overall, the MN modification significantly modifies the properties of PLGA nanoparticles making them more suitable as nanocarriers for oral protein delivery.

In this paper, we show the effect of crambescidin-816, -800, and -830 on Saccharomyces cerevisiae viability. We determined that, of the three molecules tested, crambescidin-816 was the most potent. Based on this result, we continued by determining the effect of crambescidin-816 on the cell cycle of this yeast. The compound induced cell cycle arrest in G2/M followed by an increase in cell DNA content and size. When the type of cell death was analyzed, we observed that crambescidin-816 induced apoptosis. The antifungal effect indicates that crambescidins, and mostly crambescidin-816, could serve as a lead compound to fight fungal infections.

The disappointing results obtained in recent clinical trials renew the interest in experimental/computational techniques for the discovery of neuroprotective drugs. In this context, multitarget or multiplexing QSAR models (mt-QSAR/mx-QSAR) may help to predict neurotoxicity/neuroprotective effects of drugs in multiple assays, on drug targets, and in model organisms. In this work, we study a data set downloaded from CHEMBL; each data point (>8000) contains the values of one out of 37 possible measures of activity, 493 assays, 169 molecular or cellular targets, and 11 different organisms (including human) for a given compound. In this work, we introduce the first mx-QSAR model for neurotoxicity/neuroprotective effects of drugs based on the MARCH-INSIDE (MI) method. First, we used MI to calculate the stochastic spectral moments (structural descriptors) of all compounds. Next, we found a model that classified correctly 2955 out of 3548 total cases in the training and validation series with Accuracy, Sensitivity, and Specificity values>80%. The model also showed excellent results in Computational-Chemistry simulations of High-Throughput Screening (CCHTS) experiments, with accuracy=90.6% for 4671 positive cases. Next, we reported the synthesis, characterization, and experimental assays of new rasagiline derivatives. We carried out three different experimental tests: assay (1) in the absence of neurotoxic agents, assay (2) in the presence of glutamate, and assay (3) in the presence of H2O2. Compounds 11 with 27.4%, 8 with 11.6%, and 9 with 15.4% showed the highest neuroprotective effects in assays (1), (2), and (3), respectively. After that, we used the mx-QSAR model to carry out a CCHTS of the new compounds in >400 unique pharmacological tests not carried out experimentally. Consequently, this model may become a promising auxiliary tool for the discovery of new drugs for the treatment of neurodegenerative diseases.

Endogen polyamines are known to be molecules of high biological value. Herein, a new generation of physical hydrogels was developed through the mild ionotropic gelantion technique, using the endogen polyamine spermidine as a physical cross-linker. The main negatively charged polymer of the hydrogel is the natural polysaccharide gellan gum. Optionally, interesting endogen molecules, such as chondroitin sulfate and albumin, can be included as part of the formulation. These new hydrogels were characterized and the influence of the different components on their final properties was carefully analyzed, ultimately demonstrating the possibility to modulate these properties as well as the system's versatility in terms of composition. On the contrary, in vitro cell studies showed the absence of cytotoxicity of these hydrogels. Finally, the in vitro-release profiles obtained for different model molecules evidenced the potential of these systems as novel drug delivery platforms., (Copyright © 2013 Wiley Periodicals, Inc.)

Thermal annealing was used for the bottom-up fabrication of morphologically controlled gold-block-copolymer (Au-BC) nanocomposites. Three different blends formed by polystyrene (PS) homopolymer and PS-coated gold nanoparticles (PSSH@Au) were used as modifiers of asymmetric polystyrene-b-polymethylmethacrylate (PS-b-PMMA): PS26/PS26SH@Au, PS75/PS75SH@Au and PS167/PS167SH@Au (where the subscripts refer to the number of styrene monomeric units).The results indicated that all three blends used as modifiers (PSn/PSnSH@Au) were successfully located in the PS phase during thermally induced BC self-assembly for a composition range from 5 to 43 wt% without macro-phase separation. The PSnSH@Au moiety experienced molecular desorption, nanocrystal core coalescence and partial molecular re-encapsulation processes during thermal annealing, leading to sphere-like gold NPs with a larger average size (without exceeding an interdomain distance). Ligand chain length regulated the degree of coalescence and re-encapsulation, defining ultimate core size. Furthermore, proper combination of chain length and composition enabled tuning of NP partitioning and arrangement on different length scales through thermally activated cooperative assembly processes. These results have not only significant impact for establishing thermal processing as a useful tool for the precise control of NP size and distribution, but also much broader implications for many nanoparticle-based technologies.

The purpose of this study was to evaluate the performance of a semiautomatic segmentation method for the anatomical and functional assessment of both ventricles from cardiac cine magnetic resonance (MR) examinations, reducing user interaction to a "mouse-click". Fifty-two patients with cardiovascular diseases were examined using a 1.5-T MR imaging unit. Several parameters of both ventricles, such as end-diastolic volume (EDV), end-systolic volume (ESV) and ejection fraction (EF), were quantified by an experienced operator using the conventional method based on manually-defined contours, as the standard of reference; and a novel semiautomatic segmentation method based on edge detection, iterative thresholding and region growing techniques, for evaluation purposes. No statistically significant differences were found between the two measurement values obtained for each parameter (p > 0.05). Correlation to estimate right ventricular function was good (r > 0.8) and turned out to be excellent (r > 0.9) for the left ventricle (LV). Bland-Altman plots revealed acceptable limits of agreement between the two methods (95%). Our study findings indicate that the proposed technique allows a fast and accurate assessment of both ventricles. However, further improvements are needed to equal results achieved for the right ventricle (RV) using the conventional methodology.

Embryonic, adult, artificially reprogrammed, and cancer…- there are various types of cells associated with stemness. Do they have something fundamental in common? Are we applying a common name to very different entities? In this review, we will revisit the characteristics that define 'pluripotency', the main property of stem cells (SCs). For each main type of physiological (embryonic and adult) or synthetic (induced pluripotent) SCs, markers and functional behavior in vitro and in vivo will be described. We will review the pioneering work that has led to obtaining human SC lines, together with the problems that have arisen, both in a biological context (DNA alterations, heterogeneity, tumors, and immunogenicity) and with regard to ethical concerns. Such problems have led to proposals for new operative procedures for growing human SCs of sufficiently high quality for use as models of disease and in human therapy. Finally, we will review the data from the first clinical trials to use various types of SCs.

Somatotrophs produce growth hormone (GH) and are the most abundant secretory cells of the pituitary. Somatotrophs express the transcription factor Pit-1 and the dependence receptor RET, its co-receptor GFRa1 and ligand GDNF. Pit-1 is a transcription factor essential for somatotroph proliferation and differentiation and for GH expression. GDNF represses excess Pit-1 expression preventing excess GH. In the absence of GDNF, RET behaves as a dependence receptor, becomes intracellularly processed and induces strong Pit-1 expression leading to p53 accumulation and apoptosis. How accumulation of Pit-1 leads to p53 expression is unknown. We have unveiled the relationship of Pit-1 with the p19Arf gene. There is a parallel correlation of RET processing, Pit-1 increase and ARF protein and mRNA expression. Interfering the pathway with RET, Pit-1 or p19Arf siRNA blocked apoptosis. We have found a Pit-1 DNA-binding element within the ARF promoter. Pit-1 directly regulates the CDKN2A locus and binds to the p19Arft promoter inducing p19Arf gene expression. The Pit-1-binding element is conserved in rodents and humans. RET/Pit-1 induces p19Arf/p53 and apoptosis not only in a somatotroph cell line but also in primary cultures of pituitary somatotrophs, where ARF siRNA interference also blocks p53 and apoptosis. Analyses of the somatotrophs in whole pituitaries supported the above findings. Thus Pit-1, a differentiation factor, activates the oncogene-induced apoptosis (OIA) pathway as oncogenes exerting a tight control in somatotrophs to prevent the disease due to excess of GH (insulin-resistance, metabolic disease, acromegaly).

Vaccination has become one of the most important health interventions of our times, revolutionizing health care, and improving the quality of life and life expectancy of millions all over the world. In spite of this, vaccine research remains a vast field for innovation and improvement. Indeed, the shift towards the use of sub-unit antigens, much safer but less immunogenic, and the recognized need to facilitate the access to vaccines in the global framework is currently stimulating the search for safe and efficient adjuvants and delivery technologies. Within this context, nanocarriers have gained particular attention over the last years and appear as one of the most promising strategies for antigen delivery. A number of biomaterials and technologies can be used to design nanovaccines that fulfill the requirements of new vaccination approaches, such as single-dose and transmucosal immunization, critical for achieving a widespread coverage while reducing the overall costs in relation to traditional forms of vaccination. Here we present an overview of the current state of nanocarriers for antigen delivery, developed with the perspective of contributing to the global vaccination goal., (© Société de Biologie, 2013.)

Context: Adult stem cells maintain some markers expressed by embryonic stem cells and express other specific markers depending on the organ where they reside. Recently, stem/progenitor cells in the rodent and human pituitary have been characterized as expressing GFRA2/RET, PROP1, and stem cell markers such as SOX2 and OCT4 (GPS cells)., Objective: Our objective was to detect other specific markers of the pituitary stem cells and to investigate whether craniopharyngiomas (CRF), a tumor potentially derived from Rathke's pouch remnants, express similar markers as normal pituitary stem cells., Design: We conducted mRNA and Western blot studies in pituitary extracts, and immunohistochemistry and immunofluorescence on sections from normal rat and human pituitaries and 20 CRF (18 adamantinomatous and two papillary)., Results: Normal pituitary GPS stem cells localized in the marginal zone (MZ) express three key embryonic stem cell markers, SOX2, OCT4, and KLF4, in addition to SOX9 and PROP1 and β-catenin overexpression. They express the RET receptor and its GFRA2 coreceptor but also express the coreceptor GFRA3 that could be detected in the MZ of paraffin pituitary sections. CRF maintain the expression of SOX2, OCT4, KLF4, SOX9, and β-catenin. However, RET and GFRA3 expression was altered in CRF. In 25% (five of 20), both RET and GFRA3 were detected but not colocalized in the same cells. The other 75% (15 of 20) lose the expression of RET, GFRA3, or both proteins simultaneously., Conclusions: Human pituitary adult stem/progenitor cells (GPS) located in the MZ are characterized by expression of embryonic stem cell markers SOX2, OCT4, and KLF4 plus the specific pituitary embryonic factor PROP1 and the RET system. Redundancy in RET coreceptor expression (GFRA2 and GFRA3) suggest an important systematic function in their physiological behavior. CRF share the stem cell markers suggesting a common origin with GPS. However, the lack of expression of the RET/GFRA system could be related to the cell mislocation and deregulated growth of CRF.

Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models have been largely used for different kind of problems in Medicinal Chemistry and other Biosciences as well. Nevertheless, the applications of QSAR models have been restricted to the study of small molecules in the past. In this context, many authors use molecular graphs, atoms (nodes) connected by chemical bonds (links) to represent and numerically characterize the molecular structure. On the other hand, Complex Networks are useful in solving problems in drug research and industry, developing mathematical representations of different systems. These systems move in a wide range from relatively simple graph representations of drug molecular structures (molecular graphs used in classic QSAR) to large systems. We can cite for instance, drug-target interaction networks, protein structure networks, protein interaction networks (PINs), or drug treatment in large geographical disease spreading networks. In any case, all complex networks have essentially the same components: nodes (atoms, drugs, proteins, microorganisms and/or parasites, geographical areas, drug policy legislations, etc.) and links (chemical bonds, drug-target interactions, drug-parasite treatment, drug use, etc.). Consequently, we can use the same type of numeric parameters called Topological Indices (TIs) to describe the connectivity patterns in all these kinds of Complex Networks irrespective the nature of the object they represent and use these TIs to develop QSAR/QSPR models beyond the classic frontiers of drugs small-sized molecules. The goal of this work, in first instance, is to offer a common background to all the manuscripts presented in this special issue. In so doing, we make a review of the most used software and databases, common types of QSAR/QSPR models, and complex networks involving drugs or their targets. In addition, we review both classic TIs that have been used to describe the molecular structure of drugs and/or larger complex networks. In second instance, we use for the first time a Markov chain model to generalize Spectral moments to higher order analogues coined here as the Stochastic Spectral Moments TIs of order k (πk). Lastly, we report for the first time different QSAR/QSPR models for different classes of networks found in drug research, nature, technology, and social-legal sciences using πk values. This work updates our previous reviews Gonzalez-Diaz et al. Curr Top Med Chem. 2007; 7(10): 1015-29 and Gonzalez-Diaz et al. Curr Top Med Chem. 2008; 8(18):1676-90. It has been prepared in response to the kind invitation of the editor Prof. AB Reitz in commemoration of the 10th anniversary of this journal in 2010.

The number of neurodegenerative diseases has been increasing in recent years. Many of the drug candidates to be used in the treatment of neurodegenerative diseases present specific 3D structural features. An important protein in this sense is the acetylcholinesterase (AChE), which is the target of many Alzheimer's dementia drugs. Consequently, the prediction of Drug-Protein Interactions (DPIs/nDPIs) between new drug candidates and specific 3D structure and targets is of major importance. To this end, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out a rational DPIs prediction. Unfortunately, many previous QSAR models developed to predict DPIs take into consideration only 2D structural information and codify the activity against only one target. To solve this problem we can develop some 3D multi-target QSAR (3D mt-QSAR) models. In this study, using the 3D MI-DRAGON technique, we have introduced a new predictor for DPIs based on two different well-known software. We have used the MARCH-INSIDE (MI) and DRAGON software to calculate 3D structural parameters for drugs and targets respectively. Both classes of 3D parameters were used as input to train Artificial Neuronal Network (ANN) algorithms using as benchmark dataset the complex network (CN) made up of all DPIs between US FDA approved drugs and their targets. The entire dataset was downloaded from the DrugBank database. The best 3D mt-QSAR predictor found was an ANN of Multi-Layer Perceptron-type (MLP) with profile MLP 37:37-24-1:1. This MLP classifies correctly 274 out of 321 DPIs (Sensitivity = 85.35%) and 1041 out of 1190 nDPIs (Specificity = 87.48%), corresponding to training Accuracy = 87.03%. We have validated the model with external predicting series with Sensitivity = 84.16% (542/644 DPIs; Specificity = 87.51% (2039/2330 nDPIs) and Accuracy = 86.78%. The new CNs of DPIs reconstructed from US FDA can be used to explore large DPI databases in order to discover both new drugs and/or targets. We have carried out some theoretical-experimental studies to illustrate the practical use of 3D MI-DRAGON. First, we have reported the prediction and pharmacological assay of 22 different rasagiline derivatives with possible AChE inhibitory activity. In this work, we have reviewed different computational studies on Drug- Protein models. First, we have reviewed 10 studies on DP computational models. Next, we have reviewed 2D QSAR, 3D QSAR, CoMFA, CoMSIA and Docking with different compounds to find Drug-Protein QSAR models. Last, we have developped a 3D multi-target QSAR (3D mt-QSAR) models for the prediction of the activity of new compounds against different targets or the discovery of new targets.

A Shiga-toxin-producing Escherichia coli (STEC) strain belonging to serotype O104:H4, phylogenetic group B1 and sequence type ST678, with virulence features common to the enteroaggregative E. coli (EAEC) pathotype, was reported as the cause of the recent 2011 outbreak in Germany. The outbreak strain was determined to carry several virulence factors of extraintestinal pathogenic E. coli (ExPEC) and to be resistant to a wide range of antibiotics. There are only a few reports of serotype O104:H4, which is very rare in humans and has never been detected in animals or food. Several research groups obtained the complete genome sequence of isolates of the German outbreak strain as well as the genome sequences of EAEC of serotype O104:H4 strains from Africa. Those findings suggested that horizontal genetic transfer allowed the emergence of the highly virulent Shiga-toxin-producing enteroaggregative E. coli (STEAEC) O104:H4 strain responsible for the outbreak in Germany. Epidemiologic investigations supported a linkage between the outbreaks in Germany and France and traced their origin to fenugreek seeds imported from Africa. However, there has been no isolation of the causative strain O104:H4 from any of the samples of fenugreek seeds analyzed. Following the German outbreak, we conducted a large sampling to analyze the presence of STEC, EAEC, and other types of diarrheagenic E. coli strains in Spanish vegetables. During June and July 2011, 200 vegetable samples from different origins were analyzed. All were negative for the virulent serotype O104:H4 and only one lettuce sample (0.6%) was positive for a STEC strain of serotype O146:H21 (stx1, stx2), considered of low virulence. Despite the single positive case, the hygienic and sanitary quality of Spanish vegetables proved to be quite good. In 195 of the 200 samples (98%), <10 colony-forming units (cfu) of E. coli per gram were detected, and the microbiological levels of all samples were satisfactory (<100 cfu/g). The samples were also negative for other pathotypes of diarrheagenic E. coli (EAEC, ETEC, tEPEC, and EIEC). Consistent with data from other countries, STEC belonging to serotype O157:H7 and other serotypes have been isolated from beef, milk, cheese, and domestic (cattle, sheep, goats) and wild (deer, boar, fox) animals in Spain. Nevertheless, STEC outbreaks in Spain are rare.

There are many protein ligands and/or drugs described with very different affinity to a large number of target proteins or receptors. In this work, we selected Ligands or Drug-target pairs (DTPs/nDTPs) of drugs with high affinity/non-affinity for different targets. Quantitative Structure-Activity Relationships (QSAR) models become a very useful tool in this context to substantially reduce time and resources consuming experiments. Unfortunately most QSAR models predict activity against only one protein target and/or have not been implemented in the form of public web server freely accessible online to the scientific community. To solve this problem, we developed here a multi-target QSAR (mt-QSAR) classifier using the MARCH-INSIDE technique to calculate structural parameters of drug and target plus one Artificial Neuronal Network (ANN) to seek the model. The best ANN model found is a Multi-Layer Perceptron (MLP) with profile MLP 20:20-15-1:1. This MLP classifies correctly 611 out of 678 DTPs (sensitivity=90.12%) and 3083 out of 3408 nDTPs (specificity=90.46%), corresponding to training accuracy=90.41%. The validation of the model was carried out by means of external predicting series. The model classifies correctly 310 out of 338 DTPs (sensitivity=91.72%) and 1527 out of 1674 nDTP (specificity=91.22%) in validation series, corresponding to total accuracy=91.30% for validation series (predictability). This model favorably compares with other ANN models developed in this work and Machine Learning classifiers published before to address the same problem in different aspects. We implemented the present model at web portal Bio-AIMS in the form of an online server called: Non-Linear MARCH-INSIDE Nested Drug-Bank Exploration & Screening Tool (NL MIND-BEST), which is located at URL: http://miaja.tic.udc.es/Bio-AIMS/NL-MIND-BEST.php. This online tool is based on PHP/HTML/Python and MARCH-INSIDE routines. Finally we illustrated two practical uses of this server with two different experiments. In experiment 1, we report by first time Quantum QSAR study, synthesis, characterization, and experimental assay of antiplasmodial and cytotoxic activities of oxoisoaporphine alkaloids derivatives as well as NL MIND-BEST prediction of potential target proteins. In experiment 2, we report sampling, parasite culture, sample preparation, 2-DE, MALDI-TOF, and -TOF/TOF MS, MASCOT search, MM/MD 3D structure modeling, and NL MIND-BEST prediction for different peptides a new protein of the found in the proteome of the human parasite Giardia lamblia, which is promising for anti-parasite drug-targets discovery., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Recently, it has been shown that commercial human thyroid lines were in fact derived from colon, mammary carcinoma, or melanoma. Others have demonstrated the absence of a common pattern of gene expression between available thyroid cancer cell lines and tumors from patients. Thus, it is important to use several primary cells with a common pathological origin to achieve reproducible results, and it is necessary to find common methods for manipulation of protein expression in such various cultures. We have standardized a transfection method for efficient expression of exogenous proteins in human primary thyroid cultures. We compared lipid-based techniques with three electroporation systems (Electroporator PulseAgile [PA]-4000, Microporator MP-100, and Nucleofector II). Nucleofection was unquestionably the most efficient even for promoter regulation studies, and it was effective in cultures from different origins as normal thyroid, papillary carcinoma, or lymphoid node metastasis. We also standardized, through lentiviral infection, the short hairpin RNA downregulation of protein expression generating human thyrocytes with low levels of p27KIP1 as a model system., (Copyright 2010 Elsevier Inc. All rights reserved.)

In this communication we carry out an in-depth review of a very versatile QSPR-like method. The method name is MARCH-INSIDE (MARkov CHains Ivariants for Network Selection and DEsign) and is a simple but efficient computational approach to the study of QSPR-like problems in biomedical sciences. The method uses the theory of Markov Chains to generate parameters that numerically describe the structure of a system. This approach generates two principal types of parameters Stochastic Topological Indices (sto-TIs). The use of these parameters allows the rapid collection, annotation, retrieval, comparison and mining structures of molecular, macromolecular, supramolecular, and non-molecular systems within large databases. Here, we review and comment by the first time on the several applications of MARCH-INSIDE to predict drugs ADMET, Activity, Metabolizing Enzymes, and Toxico-Proteomics biomarkers discovery. The MARCH-INSIDE models reviewed are: a) drug-tissue distribution profiles, b) assembling drug-tissue complex networks, c) multi-target models for anti-parasite/anti-microbial activity, c) assembling drug-target networks, d) drug toxicity and side effects, e) web-server for drug metabolizing enzymes, f) models in drugs toxico-proteomics. We close the review with some legal remarks related to the use of this class of QSPR-like models.

In the previous work, we reported a multitarget Quantitative Structure-Activity Relationship (mt-QSAR) model to predict drug activity against different fungal species. This mt-QSAR allowed us to construct a drug-drug multispecies Complex Network (msCN) to investigate drug-drug similarity (González-Díaz and Prado-Prado, J Comput Chem 2008, 29, 656). However, important methodological points remained unclear, such as follows: (1) the accuracy of the methods when applied to other problems; (2) the effect of the distance type used to construct the msCN; (3) how to perform the inverse procedure to study species-species similarity with multidrug resistance CNs (mdrCN); and (4) the implications and necessary steps to perform a substructural Triadic Census Analysis (TCA) of the msCN. To continue the present series with other important problem, we developed here a mt-QSAR model for more than 700 drugs tested in the literature against different parasites (predicting antiparasitic drugs). The data were processed by Linear Discriminate Analysis (LDA) and the model classifies correctly 93.62% (1160 out of 1239 cases) in training. The model validation was carried out by means of external predicting series; the model classified 573 out of 607, that is, 94.4% of cases. Next, we carried out the first comparative study of the topology of six different drug-drug msCNs based on six different distances such as Euclidean, Chebychev, Manhattan, etc. Furthermore, we compared the selected drug-drug msCN and species-species mdsCN with random networks. We also introduced here the inverse methodology to construct species-species msCN based on a mt-QSAR model. Last, we reported the first substructural analysis of drug-drug msCN using Triadic Census Analysis (TCA) algorithm., (Copyright 2009 Wiley Periodicals, Inc.)

Several graph representations have been introduced for different data in theoretical biology. For instance, complex networks based on Graph theory are used to represent the structure and/or dynamics of different large biological systems such as protein-protein interaction networks. In addition, Randic, Liao, Nandy, Basak, and many others developed some special types of graph-based representations. This special type of graph includes geometrical constrains to node positioning in space and adopts final geometrical shapes that resemble lattice-like patterns. Lattice networks have been used to visually depict DNA and protein sequences but they are very flexible. However, despite the proved efficacy of new lattice-like graph/networks to represent diverse systems, most works focus on only one specific type of biological data. This work proposes a generalized type of lattice and illustrates how to use it in order to represent and compare biological data from different sources. We exemplify the following cases: protein sequence; mass spectra (MS) of protein peptide mass fingerprints (PMF); molecular dynamic trajectory (MDTs) from structural studies; mRNA microarray data; single nucleotide polymorphisms (SNPs); 1D or 2D-Electrophoresis study of protein polymorphisms and protein-research patent and/or copyright information. We used data available from public sources for some examples but for other, we used experimental results reported herein for the first time. This work may break new ground for the application of Graph theory in theoretical biology and other areas of biomedical sciences.

Amylin (islet amyloid polypeptide) and vaspin (visceral adipose tissue specific serpin) are gut and adipocyte hormones involved in the regulation of body weight homeostasis. The aim of this study was to examine whether amylin and vaspin are expressed in human and rat placenta, as well as their regulation by nutritional status. Our results demonstrate that amylin and vaspin are localized in both human and rat placenta. In the rat term placenta vaspin was demonstrated in the trophoblast of the fetal villi, the labyrinth. Vaspin immunostaining in human placenta was localized in cytotrophoblast and syncytiotrophoblast in the first trimester placentas while in the third trimester vaspin was localized in the syncytiotrophoblast. Regarding amylin, rat placenta of 16 days of gestational age showed an intense immunostaining, mainly localized in the labyrinth. On the other hand, in the human third trimester placenta amylin immunoreactivity was intense in the syncytiotrophoblast of the chorionic villi and in decidual cells. Furthermore, placental amylin and vaspin showed an opposite pattern of expression during pregnancy, with vaspin showing the highest expression level at the end and amylin at the beginning of pregnancy. Finally, food restriction also has contrary effects on their expression, increasing vaspin but decreasing amylin placental mRNA and protein levels. Taken together, our results demonstrate that vaspin and amylin are modulated by energy status in the placenta, which suggests that these proteins may be involved in the regulation of placental metabolic functions.

A review of the most important original studies describing the natural course of bipolar disorder (manic-depressive psychosis) published in the pre-drug era - before 1950 - is conducted. Discrepancies among studies are detected, most of which are likely explained by methodological differences. However, some conclusions from these old studies remain perfectly valid nowadays: mania is a chronic brain disorder, inherited in most cases, decompensation being more frequent between March and August. It is more common in males, and in some cases, is secondary to other somatic problems. Mixed states are more frequent in the elderly. The review of this type of historical studies is aimed at underscoring the importance that should be attached to the careful study of psychopathology and its recording, both in clinical practice and in psychiatry research.

Purpose: This study aimed to evaluate the effects of lyophilization and cryopreservation on human amniotic membrane (HAM) in terms of histological characteristics and growth factor levels., Methods: Non-preserved, lyophilized and cryopreserved HAM samples from 13 placentas were investigated. The morphological characteristics of HAM were evaluated using light and electron microscopy. Immunohistochemical methods were also applied to assess the distribution of collagen IV in the basement membrane. Total protein amounts were measured in extracts of intact amniotic membrane from non-preserved, lyophilized and cryopreserved samples. An enzyme-linked immunosorbent assay (ELISA) was used to assay growth factor protein levels for epidermal growth factor, fibroblast growth factor basic, hepatocyte growth factor, keratinocyte growth factor, transforming growth factor-beta1 and nerve growth factor., Results: Histological examination of lyophilized and cryopreserved human amniotic membrane showed similar results. Immunohistochemistry showed presence of collagen IV throughout the basement membrane, both in cryopreserved and lyophilized samples. Total protein amount was higher in cryopreserved samples, without statistical significance. Growth factors ELISA did not show statistically significant differences except for fibroblast growth factor basic, with higher levels in cryopreserved amniotic membrane., Conclusions: Lyophilization maintains the histological structure of HAM, but seems to cause greater reductions in total protein amount and growth factor concentration than cryopreservation.

In marine mollusks, many physiologic functions are regulated seasonally depending on such factors as the reproductive cycle or the presence of food. The synthesis of nitric oxide by hemocytes of Mytilus galloprovincialis is among the multiple physiologic actions in the immune response, and it is also affected by season. The maximal basal production of NO by hemocytes of M. galloprovincialis was detected in summer, whereas the minimum values were detected in winter. In winter, the presence of IL-2 induced an increase in NO production that was not detected in summer. Three months after the Prestige oil spill (November 2002), basal NO production by the hemocytes of mussels in the Galician coast showed a progressive decrease and stopping, both in summer and in winter. The characteristic increase of NO synthesis induced by IL-2 in winter also disappeared all through 2003 and 2004. The two different nitric oxide synthases previously identified by immunoblotting between 1999 and 2002 were undetectable in both 2003 and 2004. When comparing the data obtained during 2003 and 2004 to those obtained in previous years, an increase in the proportion of SH cells was detected. Also, these cells showed a higher sensitivity to apoptosis- and necrosis-inducing agents than in earlier years.

Purpose: We have previously shown that high molecular weight (MW > 100 kDa) chitosan nanocapsules are efficient vehicles for improving the oral absorption of salmon calcitonin (sCT). In the present work, our objectives were, first, to investigate the influence of some formulation parameters on the efficacy of chitosan nanocapsules as carriers for the oral administration of sCT and, second, to elucidate the mechanism of interaction of chitosan nanocapsules with intestinal model cell lines., Methods: sCT-loaded chitosan nanocapsules were prepared by the solvent displacement technique. They were characterized for their size, zeta potential, and sCT loading. The ability of chitosan nanocapsules to enhance the oral absorption of sCT was investigated in rats by monitoring the serum calcium levels. Finally, the mechanism of interaction of chitosan nanocapsules with the Caco-2 cell model or in the coculture of Caco-2 with HT29-M6 cells was investigated by confocal fluorescence microscopy., Results: Chitosan nanocapsules presented a particle size in nanometer range, a positive surface charge, and an efficient encapsulation of sCT. Following oral administration to rats, all formulations of nanocapsules exhibited the ability to reduce calcemia levels; however, the intensity of the response varied depending on the formulation conditions. With regard to the mechanism of interaction of chitosan nanocapsules with cell culture, the xz images evidenced that chitosan nanocapsules interact and remain associated to the apical side of both model cell cultures. In addition, chitosan nanocapsules showed a preferable association to the mucus-secreting cells (HT29-M6)., Conclusions: Chitosan nanocapsules are able to enhance and prolong the intestinal absorption of sCT and this effect could be mainly ascribed to their mucoadhesive character and intimate interaction with the intestinal barrier.

Mucosal surfaces are the most common and convenient routes for delivering drugs to the body. However, macromolecular drugs such as peptides and proteins are unable to overcome the mucosal barriers and/or are degraded before reaching the blood stream. Among the approaches explored so far in order to optimize the transport of these macromolecules across mucosal barriers, the use of nanoparticulate carriers represents a challenging but promising strategy. The present paper aims to compare the characteristics and potential of nanostructures based on the mucoadhesive polysaccharide chitosan (CS). These are CS nanoparticles, CS-coated oil nanodroplets (nanocapsules) and CS-coated lipid nanoparticles. The characteristics and behavior of CS nanoparticles and CS-coated lipid nanoparticles already reported [A. Vila, A. Sanchez, M. Tobio, P. Calvo, M.J. Alonso, Design of biodegradable particles for protein delivery, J. Control. Rel. 78 (2002) 15-24; R. Fernandez-Urrusuno, P. Calvo, C. Remunan-Lopez, J.L. Vila-Jato, M.J. Alonso, Enhancement of nasal absorption of insulin using chitosan nanoparticles, Pharm. Res. 16 (1999) 1576-1581; M. Garcia-Fuentes, D. Torres, M.J. Alonso, New surface-modified lipid nanoparticles as delivery vehicles for salmon calcitonin (submitted for publication).] are compared with those of CS nanocapsules originally reported here. The three types of systems have a size in the nanometer range and a positive zeta potential that was attributed to the presence of CS on their surface. They showed an important capacity for the association of peptides such as insulin, salmon calcitonin and proteins, such as tetanus toxoid. Their mechanism of interaction with epithelia was investigated using the Caco-2 model cell line. The results showed that CS-coated systems caused a concentration-dependent reduction in the transepithelial resistance of the cell monolayer. Moreover, within the range of concentrations investigated, these systems were internalized in the monolayer in a concentration-dependent manner. This uptake was slightly enhanced by the presence of the CS coating but, as compared with previously published results [M. Garcia-Fuentes, C. Prego, D. Torres, M.J. Alonso, Triglyceride-chitosan nanostructures for oral calcitonin delivery: evaluation in the Caco-2 cell model and in vivo (submitted for publication)], highly dependent on the nature of the lipid core. Nevertheless, these differences in the uptake of the CS-coated systems (solid lipid core or oily core) by the Caco-2 cells did not have a consequence in the in vivo behaviour. Indeed, both CS-coated systems (nanocapsules and CS-coated nanoparticles) showed an important capacity to enhance the intestinal absorption of the model peptide, salmon calcitonin, as shown by the important and long-lasting decrease in the calcemia levels observed in rats.