Retromer stabilization results in neuroprotection in a model of Amyotrophic Lateral Sclerosis.

Amyotrophic Lateral Sclerosis (ALS) is a fatal disease characterized by the degeneration of upper and lower motor neurons (MNs). We find a significant reduction of the retromer complex subunit VPS35 in iPSCs-derived MNs from ALS patients, in MNs from ALS post mortem explants and in MNs from SOD1G93A mice. Being the retromer involved in trafficking of hydrolases, a pathological hallmark in ALS, we design, synthesize and characterize an array of retromer stabilizers based on bis-guanylhydrazones connected by a 1,3-phenyl ring linker.

Zinc phthalocyanines as light harvesters for SnO-based solar cells: a case study.

SnO nanoparticles have been synthesized and used as electron transport material (ETM) in dye sensitized solar cells (DSSCs), featuring two peripherally substituted push-pull zinc phthalocyanines (ZnPcs) bearing electron donating diphenylamine substituents and carboxylic acid anchoring groups as light harvesters. These complexes were designed on the base of previous computational studies suggesting that the integration of secondary amines as donor groups in the structure of unsymmetrical ZnPcs might enhance photovoltaics performances of DSSCs. In the case of TiO-based devices, this hypothesis has been recently questioned by experimental results.

Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation.

DNA N4-methylcytosine (4mC) is an important genetic modification and plays crucial roles in differentiation between self and non-self DNA and in controlling DNA replication, cell cycle, and gene-expression levels. Accurate 4mC site identification is fundamental to improve the understanding of 4mC biological functions and mechanisms. Hence, it is necessary to develop in silico approaches for efficient and high-throughput 4mC site identification.

The selective disruption of presynaptic JNK2/STX1a interaction reduces NMDA receptor-dependent glutamate release.

The neuronal loss caused by excessive glutamate release, or 'excitotoxicity', leads to several pathological conditions, including cerebral ischemia, epilepsy, and neurodegenerative diseases. Over-stimulation of presynaptic N-methyl-D-aspartate (NMDA) receptors is known to trigger and support glutamate spillover, while postsynaptic NMDA receptors are responsible for the subsequent apoptotic cascade. Almost all molecules developed so far are unable to selectively block presynaptic or postsynaptic NMDA receptors, therefore a deeper knowledge about intracellular NMDA pathways is required to design more specific inhibitors.

mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation.

Motivation: Cardiovascular disease is the primary cause of death globally accounting for approximately 17.7 million deaths per year. One of the stakes linked with cardiovascular diseases and other complications is hypertension.

iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree.

A soluble carrier growth hormone binding protein (GHBP) that can selectively and non-covalently interact with growth hormone, thereby acting as a modulator or inhibitor of growth hormone signalling. Accurate identification of the GHBP from a given protein sequence also provides important clues for understanding cell growth and cellular mechanisms. In the postgenomic era, there has been an abundance of protein sequence data garnered, hence it is crucial to develop an automated computational method which enables fast and accurate identification of putative GHBPs within a vast number of candidate proteins.

Bidirectional Transcriptome Analysis of Rat Bone Marrow-Derived Mesenchymal Stem Cells and Activated Microglia in an Coculture System.

Microglia contribute to the regulation of neuroinflammation and play an important role in the pathogenesis of brain diseases. Thus, regulation of neuroinflammation triggered by activated microglia in brain diseases has become a promising curative strategy. Bone marrow-derived mesenchymal stem cells (BM-MSCs) have been shown to have therapeutic effects, resulting from the regulation of inflammatory conditions in the brain.

PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions.

Proinflammatory cytokines have the capacity to increase inflammatory reaction and play a central role in first line of defence against invading pathogens. Proinflammatory inducing peptides (PIPs) have been used as an antineoplastic agent, an antibacterial agent and a vaccine in immunization therapies. Due to the advancement in sequence technologies that resulted an avalanche of protein sequence data.

iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction.

Identification of B-cell epitopes (BCEs) is a fundamental step for epitope-based vaccine development, antibody production, and disease prevention and diagnosis. Due to the avalanche of protein sequence data discovered in postgenomic age, it is essential to develop an automated computational method to enable fast and accurate identification of novel BCEs within vast number of candidate proteins and peptides. Although several computational methods have been developed, their accuracy is unreliable.

Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy.

Cell-penetrating peptides (CPPs) can enter cells as a variety of biologically active conjugates and have various biomedical applications. To offset the cost and effort of designing novel CPPs in laboratories, computational methods are necessitated to identify candidate CPPs before in vitro experimental studies. We developed a two-layer prediction framework called machine-learning-based prediction of cell-penetrating peptides (MLCPPs).

AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest.

The use of therapeutic peptides in various inflammatory diseases and autoimmune disorders has received considerable attention; however, the identification of anti-inflammatory peptides (AIPs) through wet-lab experimentation is expensive and often time consuming. Therefore, the development of novel computational methods is needed to identify potential AIP candidates prior to experimentation. In this study, we proposed a random forest (RF)-based method for predicting AIPs, called AIPpred (AIP predictor in primary amino acid sequences), which was trained with 354 optimal features.

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine.

Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest.

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application.

Interfering with HuR-RNA Interaction: Design, Synthesis and Biological Characterization of Tanshinone Mimics as Novel, Effective HuR Inhibitors.

The human antigen R (HuR) is an RNA-binding protein known to modulate the expression of target mRNA coding for proteins involved in inflammation, tumorigenesis, and stress responses and is a valuable drug target. We previously found that dihydrotanshinone-I (DHTS, 1) prevents the association of HuR with its RNA substrate, thus imparing its function. Herein, inspired by DHTS structure, we designed and synthesized an array of ortho-quinones (tanshinone mimics) using a function-oriented synthetic approach.

Integration of metabolomics and transcriptomics in nanotoxicity studies.

Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule.

Dye-sensitized solar cells based on a push-pull zinc phthalocyanine bearing diphenylamine donor groups: computational predictions face experimental reality.

Computational studies have suggested that the integration of secondary amine as donor groups in the structure of unsymmetrical zinc phthalocyanine (ZnPc) should have positive effects on photovoltaic performance, once the molecule is integrated as light harvester in dye sensitized solar cells (DSSCs). Aiming at obtaining experimental confirmation, we synthesized a peripherally substituted push-pull ZnPc bearing three electron donating diphenylamine substituents and a carboxylic acid anchoring group and integrated it as sensitizer in TiO-based DSSCs. Detailed functional characterization of solar energy converting devices resulted in ruling out the original hypothesis.

MLACP: machine-learning-based prediction of anticancer peptides.

Cancer is the second leading cause of death globally, and use of therapeutic peptides to target and kill cancer cells has received considerable attention in recent years. Identification of anticancer peptides (ACPs) through wet-lab experimentation is expensive and often time consuming; therefore, development of an efficient computational method is essential to identify potential ACP candidates prior to experimentation. In this study, we developed support vector machine- and random forest-based machine-learning methods for the prediction of ACPs using the features calculated from the amino acid sequence, including amino acid composition, dipeptide composition, atomic composition, and physicochemical properties.

Diastereoselective protocols for the synthesis of 2,3-trans- and 2,3-cis-6-methoxy-morpholine-2-carboxylic acid derivatives.

Two diastereoselective and straightforward protocols for the high-yielding synthesis of 2,3-trans- and 2,3-cis-6-methoxy-3-substituted morpholine-2-carboxylic esters were realized in few steps, through the condensation between 5,6-diethoxy-5,6-dimethyl-1,4-dioxan-2-one and an appropriate imine, which is the key reaction to control the C2-C3 relative stereochemistry, followed by a methanolysis/ring-closure tandem reaction sequence. In particular, 2,3-trans-morpholines derive from the R*,S*-product of the acid condensation of N-functionalized alkylimines with the silylketene acetal of the above lactone, whereas 2,3-cis-morpholines derive from the R*,R*-product of basic condensation of an N-tosylimines with the lactone.

A Simple Mechanism Underlying the Effect of Protecting Osmolytes on Protein Folding.

Osmolytes are small organic compounds that confer to the cell an enhanced adaptability to external conditions. Many osmolytes not only protect the cell from osmotic stress but also stabilize the native structure of proteins. While simplified models able to predict changes to protein stability are available, a general physicochemical explanation of the underlying microscopic mechanism is still missing.

Resolving the structure of ligands bound to the surface of superparamagnetic iron oxide nanoparticles by high-resolution magic-angle spinning NMR spectroscopy.

A major challenge in magnetic nanoparticle synthesis and (bio)functionalization concerns the precise characterization of the nanoparticle surface ligands. We report the first analytical NMR investigation of organic ligands stably anchored on the surface of superparamagnetic nanoparticles (MNPs) through the development of a new experimental application of high-resolution magic-angle spinning (HRMAS). The conceptual advance here is that the HRMAS technique, already being used for MAS NMR analysis of gels and semisolid matrixes, enables the fine-structure-resolved characterization of even complex organic molecules bound to paramagnetic nanocrystals, such as nanosized iron oxides, by strongly decreasing the effects of paramagnetic disturbances.

Effects of gravity on proliferation and differentiation of adipose tissue-derived stem cells.

Recent studies have demonstrated that culturing stem cells under altered gravity conditions modulates their proliferation and differentiation. In the current study we focused on osteogenesis. In an attempt to induce high proliferation rates and low differentiation of adipose tissue-derived stem cells (AT-MSCs), we exposed them to simulated microgravity (sim-microg) and hypergravity.

A Re(CO)5 fragment bonded to a polyhedral oligomeric hydroxysilsesquioxane as a model which gives further evidence to the existence of an unexpected Re(CO)5 surface species.

Reaction of Re(CO)5O3SCF3 with (c-C6H11)7Si8O12O-Li+ at 273 K under a CO atmosphere affords the [Re(CO)5OR] (R = (c-C6H11)7Si8O12) derivative (1). 1 is the first example of a rhenium pentacarbonyl bearing an OR ligand (R = alkyl, aryl, or silyl) stable enough to be characterized, and it represents also the first molecular model of the surface [Re(CO)5OSi] species formed by reductive carbonylation of silica-supported [Re(CO)3OH]4. At room temperature, 1 loses one carbonyl ligand and dimerizes to afford {Re(CO)4[(mu-O)O12Si8(c-C6H11)7]}2 (2), which has been characterized by X-ray diffraction and is the first reported example of a rhenium tetracarbonyl mu-oxo-bridged dimer of the type [Re(CO)4(mu-OR)]2.

Novel nontoxic mitochondrial probe for confocal fluorescence microscopy.

We propose a 2,5-Bis[1-(4-N-methylpyridinium)ethen-2-yl)]-N-methylpyrrole ditriflate (PEPEP) as a novel nontoxic, nonpotentiometric mitochondrial probe for confocal fluorescence microscopy. PEPEP is a representative chromophore of a large family of heterocyclic fluorescent dyes that show fluorescence emission in aqueous media and great DNA affinity. We check its cytotoxicity and intracellular localization in mammalian and yeast cell cultures.

The introduction of the stilbene synthase gene enhances the natural antiradical activity of Lycopersicon esculentum mill.

Tomato (Lycopersicon esculentum) is a vegetable rich in antioxidants, such as lycopene, lutein, and zeaxanthin. Their presence is responsible for the characteristic ability of this product to inhibit the formation of reactive oxygen species, including singlet oxygen. The grapes and wines derived from grapes also contain powerful antioxidants.