Physicochemical and Theoretical Characterization of a New Small Non-Metal Schiff Base with a Differential Antimicrobial Effect against Gram-Positive Bacteria

Searching for adequate and effective compounds displaying antimicrobial activities, especially against Gram-positive bacteria, is an important research area due to the high hospitalization and mortality rates of these bacterial infections in both the human and veterinary fields. In this work, we explored (E)-4-amino-3-((3,5-di-tert-butyl-2-hydroxybenzylidene)amino) benzoic acid (SB-1, harboring an intramolecular hydrogen bond) and (E)-2-((4-nitrobenzilidene)amino)aniline (SB-2), two Schiff bases derivatives. Results demonstrated that SB-1 showed an antibacterial activity determined by the minimal inhibitory concentration (MIC) against Staphylococcus aureus, Enterococcus faecalis, and Bacillus cereus (Gram-positive bacteria involved in human and animal diseases such as skin infections, pneumonia, diarrheal syndrome, and urinary tract infections, among others), which was similar to that shown by the classical antibiotic chloramphenicol. By contrast, this compound showed no effect against Gram-negative bacteria (Klebsiella pneumoniae, Escherichia coli, and Salmonella enterica). Furthermore, we provide a comprehensive physicochemical and theoretical characterization of SB-1 (as well as several analyses for SB-2), including elemental analysis, ESMS, ¹H and ¹³C NMR (assigned by 1D and 2D techniques), DEPT, UV-Vis, FTIR, and cyclic voltammetry. We also performed a computational study through the DFT theory level, including geometry optimization, TD-DFT, NBO, and global and local reactivity analyses.     

NSAID-Based Coordination Compounds for Biomedical Applications: Recent Advances and Developments

After the serendipitous discovery of cisplatin, a platinum-based drug with chemotherapeutic effects, an incredible amount of research in the area of coordination chemistry has been produced. Other transition metal compounds were studied, and several new relevant metallodrugs have been synthetized in the past few years. This review is focused on coordination compounds with first-row transition metals, namely, copper, cobalt, nickel or manganese, or with zinc, which have potential or effective pharmacological properties. It is known that metal complexes, once bound to organic drugs, can enhance the drugs’ biological activities, such as anticancer, antimicrobial or anti-inflammatory ones. NSAIDs are a class of compounds with anti-inflammatory properties used to treat pain or fever. NSAIDs’ properties can be strongly improved when included in complexes using their compositional N and O donor atoms, which facilitate their coordination to metal ions. This review focuses on the research on this topic and on the promising or effective results that complexes of first-row transition metals and NSAIDs can exhibit.     

N-Aminierung von Isochinolinbasen

N-Amination of Isoquinoline Bases 3, 3-Pentamethylene oxaziridine 1 forms an N N-bond with secondary isoquinoline bases 2a – f to give the cyclohexylidene hydrazines 3a – f . In some cases nitrogen elimination yielding indane derivatives 13b, 13e competes with hydrazone formation. The cyclic Schiff'base 14 and the β-carboline derivative 16 can also be aminated.     

Zimbro (Juniperus communis L.) as a Promising Source of Bioactive Compounds and Biomedical Activities: A Review on Recent Trends

Plant-derived products and their extracted compounds have been used in folk medicine since early times. Zimbro or common juniper (Juniperus communis) is traditionally used to treat renal suppression, acute and chronic cystitis, bladder catarrh, albuminuria, leucorrhea, and amenorrhea. These uses are mainly attributed to its bioactive composition, which is very rich in phenolics, terpenoids, organic acids, alkaloids, and volatile compounds. In the last few years, several studies have analyzed the huge potential of this evergreen shrub, describing a wide range of activities with relevance in different biomedical discipline areas, namely antimicrobial potential against human pathogens and foodborne microorganisms, notorious antioxidant and anti-inflammatory activities, antidiabetic, antihypercholesterolemic and antihyperlipidemic effects, and neuroprotective action, as well as antiproliferative ability against cancer cells and the ability to activate inductive hepato-, renal- and gastroprotective mechanisms. Owing to these promising activities, extracts and bioactive compounds of juniper could be useful for the development of new pharmacological applications in the treatment of several acute and chronic human diseases.     

The Signaling Pathway of TNF Receptors: Linking Animal Models of Renal Disease to Human CKD

Chronic kidney disease (CKD) has been recognized as a global public health problem. Despite the current advances in medicine, CKD-associated morbidity and mortality remain unacceptably high. Several studies have highlighted the contribution of inflammation and inflammatory mediators to the development and/or progression of CKD, such as tumor necrosis factor (TNF)-related biomarkers. The inflammation pathway driven by TNF-α, through TNF receptors 1 (TNFR1) and 2 (TNFR2), involves important mediators in the pathogenesis of CKD. Circulating levels of TNFRs were associated with changes in other biomarkers of kidney function and injury, and were described as predictors of disease progression, cardiovascular morbidity, and mortality in several cohorts of patients. Experimental studies describe the possible downstream signaling pathways induced upon TNFR activation and the resulting biological responses. This review will focus on the available data on TNFR1 and TNFR2, and illustrates their contributions to the pathophysiology of kidney diseases, their cellular and molecular roles, as well as their potential as CKD biomarkers. The emerging evidence shows that TNF receptors could act as biomarkers of renal damage and as mediators of the disease. Furthermore, it has been suggested that these biomarkers could significantly improve the discrimination of clinical CKD prognostic models.     

ICA1L Is Associated with Small Vessel Disease: A Proteome-Wide Association Study in Small Vessel Stroke and Intracerebral Haemorrhage

Small vessel strokes (SVS) and intracerebral haemorrhages (ICH) are acute outcomes of cerebral small vessel disease (SVD). Genetic studies combining both phenotypes have identified three loci associated with both traits. However, the genetic cis-regulation at the protein level associated with SVD has not been studied before. We performed a proteome-wide association study (PWAS) using FUSION to integrate a genome-wide association study (GWAS) and brain proteomic data to discover the common mechanisms regulating both SVS and ICH. Dorsolateral prefrontal cortex (dPFC) brain proteomes from the ROS/MAP study (N = 376 subjects and 1443 proteins) and the summary statistics for the SVS GWAS from the MEGASTROKE study (N = 237,511) and multi-trait analysis of GWAS (MTAG)-ICH–SVS from Chung et al. (N = 240,269) were selected. We performed PWAS and then a co-localization analysis with COLOC. The significant and nominal results were validated using a replication dPFC proteome (N = 152). The replicated results (q-value < 0.05) were further investigated for the causality relationship using summary data-based Mendelian randomization (SMR). One protein (ICA1L) was significantly associated with SVS (z-score = −4.42 and p-value = 9.6 × 10⁻⁶) and non-lobar ICH (z-score = −4.8 and p-value = 1.58 × 10⁻⁶) in the discovery PWAS, with a high co-localization posterior probability of 4. In the validation PWAS, ICA1L remained significantly associated with both traits. The SMR results for ICA1L indicated a causal association of protein expression levels in the brain with SVS (p-value = 3.66 × 10⁻⁵) and non-lobar ICH (p-value = 1.81 × 10⁻⁵). Our results show that the association of ICA1L with SVS and non-lobar ICH is conditioned by the cis-regulation of its protein levels in the brain.     

An Experimental Model of Neuro–Immune Interactions in the Eye: Corneal Sensory Nerves and Resident Dendritic Cells

The cornea is an avascular connective tissue that is crucial, not only as the primary barrier of the eye but also as a proper transparent refractive structure. Corneal transparency is necessary for vision and is the result of several factors, including its highly organized structure, the physiology of its few cellular components, the lack of myelinated nerves (although it is extremely innervated), the tightly controlled hydration state, and the absence of blood and lymphatic vessels in healthy conditions, among others. The avascular, immune-privileged tissue of the cornea is an ideal model to study the interactions between its well-characterized and dense sensory nerves (easily accessible for both focal electrophysiological recording and morphological studies) and the low number of resident immune cell types, distinguished from those cells migrating from blood vessels. This paper presents an overview of the corneal structure and innervation, the resident dendritic cell (DC) subpopulations present in the cornea, their distribution in relation to corneal nerves, and their role in ocular inflammatory diseases. A mouse model in which sensory axons are constitutively labeled with tdTomato and DCs with green fluorescent protein (GFP) allows further analysis of the neuro-immune crosstalk under inflammatory and steady-state conditions of the eye.     

Parallel discovery of network motifs

Many natural structures can be naturally represented by complex networks. Discovering network motifs, which are overrepresented patterns of inter-connections, is a computationally hard task related to graph isomorphism. Sequential methods are hindered by an exponential execution time growth when we increase the size of motifs and networks. In this article we study the opportunities for parallelism in existing methods and propose new parallel strategies that adapt and extend one of the most efficient serial methods known from the Fanmod tool. We propose both a master–worker strategy and one with distributed control, in which we employ a randomized receiver initiated methodology capable of providing dynamic load balancing during the whole computation process. Our strategies are capable of dealing both with exact and approximate network motif discovery. We implement and apply our algorithms to a set of representative networks and examine their scalability up to 128 processing cores. We obtain almost linear speedups, showcasing the efficiency of our proposed approach and are able to reach motif sizes that were not previously achievable using conventional serial algorithms.     

Cooperative adaptive sampling of random fields with partially known covariance

This paper considers autonomous robotic sensor networks taking measurements of a physical process for predictive purposes. The physical process is modeled as a spatiotemporal random field. The network objective is to take samples at locations that maximize the information content of the data. The combination of information‐based optimization and distributed control presents difficult technical challenges as standard measures of information are not distributed in nature. Moreover, the lack of prior knowledge on the statistical structure of the field can make the problem arbitrarily difficult. Assuming the mean of the field is an unknown linear combination of known functions and its covariance structure is determined by a function known up to an unknown parameter, we provide a novel distributed method for performing sequential optimal design by a network comprised static and mobile devices. We characterize the correctness of the proposed algorithm and examine in detail the time, communication, and space complexities required for its implementation. Copyright © 2011 John Wiley & Sons, Ltd.     

The evaluation of scientific production: Towards a neutral impact factor

Measurement of research activity still remains a controversial question. The use of the impact factor from the Institute for Scientific Information (ISI) is quite widespread nowadays to carry out evaluations of all kinds; however, the calculation formula employed by ISI in order to construct its impact factors biases the results in favour of knowledge fields which are better represented in the sample, cite more in average and whose citations are concentrated in the early years of the articles. In the present work, we put forward a theoretical proposal regarding how aggregated normalization should be carried out with these biases, which allows comparing scientific production between fields, institutions and/or authors in a neutral manner. The technical complexity of such work, together with data limitations, lead us to propose some adjustments on the impact factor proposed by ISI which — although they do not completely solve the problem — reduce it and allow glimpsing the path towards more neutral evaluations. The proposal is empirically applied to three analysis levels: single journals, knowledge fields and the set of journals from the Journal Citation Report.