Antibacterial and Anti-Inflammatory Activities of Anacardium occidentale Leaves and Bark Extracts

Anacardium occidentale is a local medicinal plant used in ethno medicine for the treatment of diarrhea, constipation,pain and inflammation. The aqueous and ethanolic extracts of this plant parts were assessed for antiinflammatory and antibacterial activities using experimental animal model and agar disc diffusion methods respectively. Results show that the ethanolic extract of the plant were more efficacious than the aqueous extract in inhibiting the carrageenan induced paw oedema in rats in a non dose-dependent manner( P>0.05).No significant difference was found between the ethanolic extract of the leaves and bark (P>0.05). Also, the antibacterial activity was apparently higher in ethanolic extract than in aqueous extract for both leaves and barkwith the bark extract displaying a  significantly (P<0.05) higher activity compared to the leaves extract. The results of this study therefore justify the use of this plant in the treatment of  inflammation and bacterial infections.Keywords: Antibacterial, Anti inflammatory, Anacardium occidental

Molecular characterization and strain typing of fungal contaminants of Processed Manihot esculenta Crantz (“Garri”) in Ogun State, Nigeria

Background: The lack of standard biochemical tests, coupled with the limitation of the number of micro and macro morphology that can be scored for fungal diagnosis, makes the identification of fungal organisms using microbiological methods less reliable. Objective: To determine the fungal contaminants of processed Manihot esculenta Crantz (Garri) and provide information on their diversity. Methods: In this study, fungal contaminants of processed Manihot esculenta Crantz (Garri) were characterized by sequencing the hyper-variable 18S ribosomal RNA as well as type the isolated organisms using Random Amplified Polymorphic DNA markers. Results: The PCR amplification of the 18S ribosomal RNA gene of the isolated fungi from processed Manihot esculenta Crantz yielded a single fragment of an approximately between 600 and 700 bp. BLAST search using Genbank database showed that the isolate percentage similarity with GenBank accessions ranged between 98% and 100%. The molecular technique successfully identified all the isolated organisms resulting in 100% accurate diagnosis as against 79.3%accurate diagnosis made with the microbiological method. The forty isolated Aspergillus species were further resolved into 27 RAPD haplotypes with Simpson Index of Genetic Diversity approaching one for all the isolates. The mean genetic diversity within (GL) and among (GS) the isolated Aspergillus species were found to be 89% and 11% respectively. The total genetic diversity (HT) for these organisms was approximately 48%. These results connoted significant strain diversity in the sampled specimens as shown by differences in their electrophoretic patterns. Conclusion: The study revealed significant strain diversity in the sampled specimens as shown by differences in their electrophoretic patterns

Time of day is associated with paradoxical reductions in global signal fluctuation and functional connectivity.

The brain exhibits substantial diurnal variation in physiology and function, but neuroscience studies rarely report or consider the effects of time of day. Here, we examined variation in resting-state functional MRI (fMRI) in around 900 individuals scanned between 8 AM and 10 PM on two different days. Multiple studies across animals and humans have demonstrated that the brain's global signal (GS) amplitude (henceforth referred to as "fluctuation") increases with decreased arousal. Thus, in accord with known circadian variation in arousal, we hypothesised that GS fluctuation would be lowest in the morning, increase in the midafternoon, and dip in the early evening. Instead, we observed a cumulative decrease in GS fluctuation as the day progressed. Although respiratory variation also decreased with time of day, control analyses suggested that this did not account for the reduction in GS fluctuation. Finally, time of day was associated with marked decreases in resting-state functional connectivity across the whole brain. The magnitude of decrease was significantly stronger than associations between functional connectivity and behaviour (e.g., fluid intelligence). These findings reveal time of day effects on global brain activity that are not easily explained by expected arousal state or physiological artefacts. We conclude by discussing potential mechanisms for the observed diurnal variation in resting brain activity and the importance of accounting for time of day in future studies

Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters

Comparison between gradients and parcellations for functional connectivity prediction of behavior

Resting-state functional connectivity (RSFC) is widely used to predict behavioral measures. To predict behavioral measures, representing RSFC with parcellations and gradients are the two most popular approaches. Here, we compare parcellation and gradient approaches for RSFC-based prediction of a broad range of behavioral measures in the Human Connectome Project (HCP) and Adolescent Brain Cognitive Development (ABCD) datasets. Among the parcellation approaches, we consider group-average “hard” parcellations (Schaefer et al., 2018), individual-specific “hard” parcellations (Kong et al., 2021a), and an individual-specific “soft” parcellation (spatial independent component analysis with dual regression; Beckmann et al., 2009). For gradient approaches, we consider the well-known principal gradients (Margulies et al., 2016) and the local gradient approach that detects local RSFC changes (Laumann et al., 2015). Across two regression algorithms, individual-specific hard-parcellation performs the best in the HCP dataset, while the principal gradients, spatial independent component analysis and group-average “hard” parcellations exhibit similar performance. On the other hand, principal gradients and all parcellation approaches perform similarly in the ABCD dataset. Across both datasets, local gradients perform the worst. Finally, we find that the principal gradient approach requires at least 40 to 60 gradients to perform as well as parcellation approaches. While most principal gradient studies utilize a single gradient, our results suggest that incorporating higher order gradients can provide significant behaviorally relevant information. Future work will consider the inclusion of additional parcellation and gradient approaches for comparison

Modelling Realistic User Behaviour in Information Systems Simulations as Fuzzing Aspects

In this paper we contend that the engineering of information systems is hampered by a paucity of tools to tractably model, simulate and predict the impact of realistic user behaviours on the emergent properties of the wider socio-technical system, evidenced by the plethora of case studies of system failure in the literature. We address this gap by presenting a novel approach that models ideal user behaviour as workflows, and introduces irregularities in that behaviour as aspects which fuzz the model. We demonstrate the success of this approach through a case study of software development workflows, showing that the introduction of realistic user behaviour to idealised workflows better simulates outcomes reported in the empirical software engineering literature

A close halo of large transparent grains around extreme red giant stars

Intermediate-mass stars end their lives by ejecting the bulk of their envelope via a slow dense wind back into the interstellar medium, to form the next generation of stars and planets. Stellar pulsations are thought to elevate gas to an altitude cool enough for the condensation of dust, which is then accelerated by radiation pressure from starlight, entraining the gas and driving the wind. However accounting for the mass loss has been a problem due to the difficulty in observing tenuous gas and dust tens of milliarcseconds from the star, and there is accordingly no consensus on the way sufficient momentum is transferred from the starlight to the outflow. Here, we present spatially-resolved, multi-wavelength observations of circumstellar dust shells of three stars on the asymptotic giant branch of the HR diagram. When imaged in scattered light, dust shells were found at remarkably small radii (<~ 2 stellar radii) and with unexpectedly large grains (~300 nm radius). This proximity to the photosphere argues for dust species that are transparent to starlight and therefore resistant to sublimation by the intense radiation field. While transparency usually implies insufficient radiative pressure to drive a wind, the radiation field can accelerate these large grains via photon scattering rather than absorption - a plausible mass-loss mechanism for lower-amplitude pulsating stars.Comment: 13 pages, 1 table, 6 figure

Interleukin-6 gene (IL-6): a possible role in brain morphology in the healthy adult brain

Background: Cytokines such as interleukin 6 (IL-6) have been implicated in dual functions in neuropsychiatric disorders. Little is known about the genetic predisposition to neurodegenerative and neuroproliferative properties of cytokine genes. In this study the potential dual role of several IL-6 polymorphisms in brain morphology is investigated. Methodology: In a large sample of healthy individuals (N = 303), associations between genetic variants of IL-6 (rs1800795; rs1800796, rs2069833, rs2069840) and brain volume (gray matter volume) were analyzed using voxel-based morphometry (VBM). Selection of single nucleotide polymorphisms (SNPs) followed a tagging SNP approach (e.g., Stampa algorigthm), yielding a capture 97.08% of the variation in the IL-6 gene using four tagging SNPs. Principal findings/results: In a whole-brain analysis, the polymorphism rs1800795 (−174 C/G) showed a strong main effect of genotype (43 CC vs. 150 CG vs. 100 GG; x = 24, y = −10, z = −15; F(2,286) = 8.54, puncorrected = 0.0002; pAlphaSim-corrected = 0.002; cluster size k = 577) within the right hippocampus head. Homozygous carriers of the G-allele had significantly larger hippocampus gray matter volumes compared to heterozygous subjects. None of the other investigated SNPs showed a significant association with grey matter volume in whole-brain analyses. Conclusions/significance: These findings suggest a possible neuroprotective role of the G-allele of the SNP rs1800795 on hippocampal volumes. Studies on the role of this SNP in psychiatric populations and especially in those with an affected hippocampus (e.g., by maltreatment, stress) are warranted.Bernhard T Baune, Carsten Konrad, Dominik Grotegerd, Thomas Suslow, Eva Birosova, Patricia Ohrmann, Jochen Bauer, Volker Arolt, Walter Heindel, Katharina Domschke, Sonja Schöning, Astrid V Rauch, Christina Uhlmann, Harald Kugel and Udo Dannlowsk

Structure-guided design of purine-based probes for selective Nek2 inhibition

Nek2 (NIMA-related kinase 2) is a cell cycle-dependent serine/threonine protein kinase that regulates centrosome separation at the onset of mitosis. Overexpression of Nek2 is common in human cancers and suppression can restrict tumor cell growth and promote apoptosis. Nek2 inhibition with small molecules, therefore, offers the prospect of a new therapy for cancer. To achieve this goal, a better understanding of the requirements for selective-inhibition of Nek2 is required. 6-Alkoxypurines were identified as ATP-competitive inhibitors of Nek2 and CDK2. Comparison with CDK2-inhibitor structures indicated that judicious modification of the 6-alkoxy and 2-arylamino substituents could achieve discrimination between Nek2 and CDK2. In this study, a library of 6-cyclohexylmethoxy-2-arylaminopurines bearing carboxamide, sulfonamide and urea substituents on the 2-arylamino ring was synthesized. Few of these compounds were selective for Nek2 over CDK2, with the best result being obtained for 3-((6-(cyclohexylmethoxy)-9H-purin-2-yl)amino)-N,N-dimethylbenzamide (CDK2 IC50 = 7.0 μM; Nek2 IC50 = 0.62 μM) with >10-fold selectivity. Deletion of the 6-substituent abrogated activity against both Nek2 and CDK2. Nine compounds containing an (E)-dialkylaminovinyl substituent at C-6, all showed selectivity for Nek2, e.g. (E)-6-(2-(azepan-1-yl)vinyl)-N-phenyl-9H-purin-2-amine (CDK2 IC50 = 2.70 μM; Nek2 IC50 = 0.27 μM). Structural biology of selected compounds enabled a partial rationalization of the observed structure activity relationships and mechanism of Nek2 activation. This showed that carboxamide 11 is the first reported inhibitor of Nek2 in the DFG-in conformation

A general process for the development of peptide-based immunoassays for monoclonal antibodies

Monoclonal antibodies (mAb) are an important and growing class of cancer therapeutics, but pharmacokinetic analyses have in many cases been constrained by the lack of standard and robust pharmacologic assays. The goal of this project was to develop a general method for the production of immunoassays that can measure the levels of therapeutic monoclonal antibodies in biologic samples at relevant concentrations. Alemtuzumab and rituximab are monoclonal approved for the treatment of B-cell malignancies and were used as a model system. Phage-displayed peptide libraries were screened for peptide sequences recognized by alemtuzumab (anti-CD52) or rituximab (anti-CD20). Synthetic biotinylated peptides were used in enzyme-linked immunosorbent assays (ELISA). Peptides directly synthesized on polymer resin beads were used in an immunofluorescent-based assay. Peptide mimetope sequences were recovered for both mAb and confirmed by competitive staining and kinetic measurements. A peptide-based ELISA method was developed for each. The assay for rituximab had a limit of detection of 4 μg/ml, and the assay for alemtuzumab had a limit of detection of 1 μg/ml. Antibody-specific staining of peptide conjugated beads could be seen in a dose-dependent manner. Phage-displayed peptide libraries can be a source of highly specific mimetopes for therapeutic mAb. The biotinylated forms of those peptides are compatible with conventional ELISA methods with sensitivities comparable to other assay methods and sufficient for pharmacological studies of those mAb given at high dose. The process outlined here can be applied to any mAb to enable improved pharmacokinetic analysis during the development and clinical use of this class of therapies