Current Topics in Medicinal Chemistry - Volume 20, Issue 9, 2020

Background: Due to the rapid development of microbial resistance, finding new molecules became urgent to counteract this problem. Objective: The objective of this work is to access 1,2,3-triazene-1,3-disubstituted, a class of molecule with high therapeutic potential. Methods: Here we describe the access to 17 new triazene including six with an imidazole-1,2,3-triazene moiety and eleven with an alkyl-1,2,3-triazene moiety and their evaluation against five strains: two gram (-): Escherichia coli ATCC 25921 and Pseudomonas aeruginosa ATCC 27253; two gram (+) : Staphylococcus aureus ATCC 38213 and Enterococcus faecalis ATCC 29212; and one fungi: Candida albicans ATCC 24433. Results: All strains were sensitive and the best MIC, 0.28 μM, is observed for 4c against Escherichia coli ATCC 25921. Compound 9, 3-isopropynyltriazene, appears to be the most interesting since it is active on the five evaluated strains with satisfactory MIC 0.32 μM against Escherichia coli and Pseudomonas aeruginosa and 0.64 μM against Enterococcus faecalis and Pseudomonas aeruginosa. Conclusion: Comparing the structure activity relationship, electron withdrawing groups appear to increase antimicrobial activity.

Aims: Computational modelling may help us to detect the more important factors governing this process in order to optimize it. Background: The generation of hazardous organic waste in teaching and research laboratories poses a big problem that universities have to manage. Methods: In this work, we report on the experimental measurement of waste generation on the chemical education laboratories within our department. We measured the waste generated in the teaching laboratories of the Organic Chemistry Department II (UPV/EHU), in the second semester of the 2017/2018 academic year. Likewise, to know the anthropogenic and social factors related to the generation of waste, a questionnaire has been utilized. We focused on all students of Experimentation in Organic Chemistry (EOC) and Organic Chemistry II (OC2) subjects. It helped us to know their prior knowledge about waste, awareness of the problem of separate organic waste and the correct use of the containers. These results, together with the volumetric data, have been analyzed with statistical analysis software. We obtained two Perturbation-Theory Machine Learning (PTML) models including chemical, operational, and academic factors. The dataset analyzed included 6050 cases of laboratory practices vs. practices of reference. Results: These models predict the values of acetone waste with R2 = 0.88 and non-halogenated waste with R2 = 0.91. Conclusion: This work opens a new gate to the implementation of more sustainable techniques and a circular economy with the aim of improving the quality of university education processes.

Background: Dryopteris cycadina has diverse traditional uses in the treatment of various human disorders which are supported by pharmacological studies. Similarly, the phytochemical studies of this plant led to the isolation of numerous compounds. Methodology: The present study deals with α-glucosidase inhibition of various kaempferol derivates including kaempferol-3, 4/-di-O-α- L-rhamnopyranoside 1, kaempferol-3, 5-di-O-α-L-rhamnoside 2 and kaempferol-3,7-di-O-α- L-rhamnopyranoside 3. Results: The results showed marked concentration-dependent inhibition of the enzyme when assayed at different concentrations and the IC50 values of compounds 1-3 were 137±9.01, 110±7.33, and 136±1.10 mM, respectively far better than standard compound, acarbose 290±0.54 mM. The computational studies revealed strong docking scores of these compounds and augmented the in vitro assay. Conclusion: In conclusion, the isolated kaempferol derivatives 1-3 from D. cycadina exhibited potent α- glucosidase inhibition.

Aims: The present study aims to determine the phototoxic and haemolytic activity of organophosphorus. The use of alternative in vitro assays with human erythrocytes is suggested to predict the polluting effect of these products on health. Methodology: Human erythrocytes from Toluca Blood Bank were used. Sodium dodecyl sulfate was employed as a positive control. Additionally, the haemolysis percentage of three organophosphate (Acetate, Chlorpyrifos, Malathion, Methamidophos, Methyl Parathion) induced photo haemolysis formulated with surfactants on a concentration of 2 x 109 erythrocytes were evaluated. Finally, the products were classified as irritant or phototoxic. Results: Results showed that the HC50 red blood cells were similar for each organophosphate (Malathion and Methamidophos) indicating very irritant action with ratio classification (L/D) of 0.041 and 0.053, respectively. On the other hand, Chlorpyrifos was classified as an irritant with L/D= 0.14. On the other hand, the HC50 obtained photo hemolysis assays irradiated red blood cells was similar for each organophosphate (Acetate, Chlorpyrifos, Malathion, Methamidophos, Methyl Parathion) indicating no phototoxic action. Conclusion: As a conclusion, it can be said that the parameters of haemolysis and denaturation of proteins are good indicators to classify organophosphorus formulated with surfactants as irritating or phototoxic.

Background: In schizophrenia, pathway-genotypes may be constructed by combining interrelated immune biomarkers with changes in specific neurocognitive functions that represent aberrations in brain neuronal circuits. These constructs provide an insight on the phenome of schizophrenia and show how pathway-phenotypes mediate the effects of genome X environmentome interactions on the symptomatology/phenomenology of schizophrenia. Nevertheless, there is a lack of knowledge how to construct pathway-phenotypes using Partial Least Squares (PLS) path modeling and Soft Independent Modeling of Class Analogy (SIMCA). Aims: This paper aims to provide a step-by-step utilization guide for the construction of pathwayphenotypes that reflect aberrations in the neuroimmune - brain circuit axis (NIBCA) in deficit schizophrenia. Methods and Results: This NIBCA index is constructed using immune biomarkers (CCL-2, CCL-11, IL-1β, sIL-1RA, TNF-α, sTNFR1, sTNFR2) and neurocognitive tests (Brief Assessment of Cognition in Schizophrenia) predicting overall severity of schizophrenia (OSOS) in 120 deficit SCZ and 54 healthy participants. Using SmartPLS path analysis, a latent vector is extracted from those biomarkers and cognitive tests, which shows good construct reliability (Cronbach alpha and composite reliability) and replicability and which is reflectively measured through its NIBCA manifestations. This NIBCA pathwayphenotype explains 75.0% of the variance in PHEMN (psychotic, hostility, excitation, mannerism and negative) symptoms. Using SIMCA, we constructed a NIBCA pathway-class that defines deficit schizophrenia as a qualitatively distinct nosological entity, which allows patients with deficit schizophrenia to be authenticated as belonging to the deficit schizophrenia class. Conclusion: In conclusion, our nomothetic approach to develop a nomological network combining neuro-immune and neurocognitive phenome markers to predict OSOS and cross-validate a diagnostic class generated replicable models reflecting the key phenome of the illness, which may mediate the effects of genome X environmentome interactions on the final outcome phenome features, namely symptomatology and phenomenology.

Mood disorders and Major Depressive Disorder, in particular, appear to be some of the most common psychiatric disorders with a high rate of comorbidity most frequently of anxiety or substance abuse disorders (alcohol use disorder). In both cases – MDD and AUD, a number of immunological disturbances are observed, such as chronic mild inflammation response, increased level of cytokines, hypercortisolaemia, which lead to specific changes in brain neurotransmitter functions. Some of the contemporary brain imaging techniques are functional magnetic resonance imaging (fMRI) and magnetic spectroscopy which are most commonly used to assess the brain metabolism and functional connectivity changes such as altered responses to emotional stimuli in MDD or overactivation of ventromedial prefrontal areas during delayed and underactivation of dorsolateral prefrontal regions during impulsive reward decisions in AUD and dysfunction of gamma-aminobutyric acid (GABA) and/or glutamate neurotransmitter systems, low NAA and myo-Inositol in both MDD and AUD.

Alzheimer’s disease (AD) is the most prevalent and severe neurodegenerative disease affecting more than 0.024 billion people globally, more common in women as compared to men. Senile plaques and amyloid deposition are among the main causes of AD. Amyloid deposition is considered as a central event which induces the link between the production of β amyloid and vascular changes. Presence of numerous biomarkers such as cerebral amyloid angiopathy, microvascular changes, senile plaques, changes in white matter, granulovascular degeneration specifies the manifestation of AD while an aggregation of tau protein is considered as a primary marker of AD. Likewise, microvascular changes, activation of microglia (immune defense system of CNS), amyloid-beta aggregation, senile plaque and many more biomarkers are nearly found in all Alzheimer’s patients. It was seen that 70% of Alzheimer’s cases occur due to genetic factors. It has been reported in various studies that apolipoprotein E(APOE) mainly APOE4 is one of the major risk factors for the later onset of AD. Several pathological changes also occur in the white matter which include dilation of the perivascular space, loss of axons, reactive astrocytosis, oligodendrocytes and failure to drain interstitial fluid. In this review, we aim to highlight the various biological signatures associated with the AD which may further help in discovering multitargeting drug therapy.

The multifaceted nature of Alzheimer’s disease (AD) and Mild cognitive impairment (MCI) can lead to wide inter-individual differences in disease manifestation in terms of brain pathology and cognition. The lack of understanding of phenotypic diversity in AD arises from a difficulty in understanding the integration of different levels of network organization (i.e. genes, neurons, synapses, anatomical regions, functions) and in inclusion of other information such as neuropsychiatric characteristics, personal history, information regarding general health or subjective cognitive complaints in a coherent model. Non-cognitive factors, such as personality traits and behavioral and psychiatric symptoms, can be informative markers of early disease stage. It is known that personality can affect cognition and behavioral symptoms. The aim of the paper is to review the different types of interactions existing between personality, depression/anxiety, and cognition and cognitive disorders at behavioral and brain/genetic levels.

Objectives: Ischemic stroke affects language production and/or comprehension and leads to devastating long-term consequences for patients and their families. Previous studies have shown that neuroimaging can increase our knowledge of the basic mechanisms of language recovery. Currently, models for predicting patients’ outcomes have limited use in the clinic for the evaluation and optimization of rehabilitative strategies mostly because that are often based on high-resolution magnetic resonance imaging (MRI) data, which are not always possible to carry out in the clinical routine. Here, we investigate the use of Voxel-Based Morphometry (VBM), multivariate modelling and native Computed Tomography (nCT) scans routinely acquired in the acute stage of stroke for identifying biological signatures that explicate the relationships between brain anatomy and types of impairments. Methods: 80 stroke patients and 30 controls were included. nCT-scans were acquired in the acute ischemia stage and bedside clinical assessment from board-certified neurologist based on the NIH stroke scale. We use a multivariate Principal Component Analyses (PCA) to identify the brain signatures group the patients according to the presence or absence of impairment and identify the association between local Grey Matter (GM) and White Matter (WM) nCT values with the presence or absence of the impairment. Results: Individual patient’s nCT scans were compared to a group of controls’ with no radiological signs of stroke to provide an automated delineation of the lesion. Consistently across the whole group the regions that presented significant difference GM and WM values overlap with known areas that support language processing. Conclusion: In summary, the method applied to nCT scans performed in the acute stage of stroke provided robust and accurate information about brain lesions’ location and size, as well as quantitative values. We found that nCT and VBQ analyses are effective for identifying neural signatures of concomitant language impairments at the individual level, and neuroanatomical maps of aphasia at the population level. The signatures explicate the neurophysiological mechanisms underlying aetiology of the stroke. Ultimately, similar analyses with larger cohorts could lead to a more integrated multimodal model of behaviour and brain anatomy in the early stage of ischemic stroke.

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.