4,025 research outputs found

    Identification of Small-Molecule Inhibitors against Meso-2, 6-Diaminopimelate Dehydrogenase from Porphyromonas gingivalis

    Get PDF
    Species-specific antimicrobial therapy has the potential to combat the increasing threat of antibiotic resistance and alteration of the human microbiome. We therefore set out to demonstrate the beginning of a pathogen-selective drug discovery method using the periodontal pathogen Porphyromonas gingivalis as a model. Through our knowledge of metabolic networks and essential genes we identified a “druggable” essential target, meso-diaminopimelate dehydrogenase, which is found in a limited number of species. We adopted a high-throughput virtual screen method on the ZINC chemical library to select a group of potential small-molecule inhibitors. Meso-diaminopimelate dehydrogenase from P. gingivaliswas first expressed and purified in Escherichia coli then characterized for enzymatic inhibitor screening studies. Several inhibitors with similar structural scaffolds containing a sulfonamide core and aromatic substituents showed dose-dependent inhibition. These compounds were further assayed showing reasonable whole-cell activity and the inhibition mechanism was determined. We conclude that the establishment of this target and screening strategy provides a model for the future development of new antimicrobials

    Human Activity Detection Based on the iBeacon Technology

    Get PDF
    Paper presents a new method of patient activity monitoring, by using modern ADL (Activities of Daily Living) techniques. Proposed method utilizes energy efficient Bluetooth iBeacon BLE (Bluetooth Low Energy) modules, developed by Apple. Main advantage of this technology is the ability to detect neighboring devices, which belong to the same device family. Proposed method is based on observing changes of received signal strength indicator (RSSI) in the time domain. The RSSI analysis is performed in order to asses a human activity. Such observation may be particularly useful for monitoring consciousness of elder people, where reaction time of emergency rescuers and appropriate rescue operations may save the human lives

    Leveraging Multi-level Dependency of Relational Sequences for Social Spammer Detection

    Full text link
    Much recent research has shed light on the development of the relation-dependent but content-independent framework for social spammer detection. This is largely because the relation among users is difficult to be altered when spammers attempt to conceal their malicious intents. Our study investigates the spammer detection problem in the context of multi-relation social networks, and makes an attempt to fully exploit the sequences of heterogeneous relations for enhancing the detection accuracy. Specifically, we present the Multi-level Dependency Model (MDM). The MDM is able to exploit user's long-term dependency hidden in their relational sequences along with short-term dependency. Moreover, MDM fully considers short-term relational sequences from the perspectives of individual-level and union-level, due to the fact that the type of short-term sequences is multi-folds. Experimental results on a real-world multi-relational social network demonstrate the effectiveness of our proposed MDM on multi-relational social spammer detection

    Online Self-Supervised Learning in Machine Learning Intrusion Detection for the Internet of Things

    Full text link
    This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which enables a fully online Machine Learning (ML) based Intrusion Detection System (IDS) that requires no human intervention or prior off-line learning. The proposed framework analyzes and labels incoming traffic packets based only on the decisions of the IDS itself using an Auto-Associative Deep Random Neural Network, and on an online estimate of its statistically measured trustworthiness. The SSID framework enables IDS to adapt rapidly to time-varying characteristics of the network traffic, and eliminates the need for offline data collection. This approach avoids human errors in data labeling, and human labor and computational costs of model training and data collection. The approach is experimentally evaluated on public datasets and compared with well-known ML models, showing that this SSID framework is very useful and advantageous as an accurate and online learning ML-based IDS for IoT systems

    Sex-specific disruption of murine midbrain astrocytic and dopaminergic developmental trajectories following antenatal GC treatment

    Get PDF
    The mammalian midbrain dopaminergic systems arising in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) are critical for coping behaviours and are implicated in neuropsychiatric disorders where early life challenges comprise significant risk factors. Here, we aimed to advance our hypothesis that glucocorticoids (GCs), recognised key players in neurobiological programming, target development within these systems, with a novel focus on the astrocytic population. Mice received antenatal GC treatment (AGT) by including the synthetic GC, dexamethasone, in the mothers' drinking water on gestational days 16-19; controls received normal drinking water. Analyses of regional shapes and volumes of the adult SNc and VTA demonstrated that AGT induced long-term, dose-dependent, structural changes that were accompanied by profound effects on astrocytes (doubling/tripling of numbers and/or density). Additionally, AGT induced long-term changes in the population size and distribution of SNc/VTA dopaminergic neurons, confirming and extending our previous observations made in rats. Furthermore, glial/neuronal structural remodelling was sexually dimorphic and depended on the AGT dose and sub-region of the SNc/VTA. Investigations within the neonatal brain revealed that these long-term organisational effects of AGT depend, at least in part, on targeting perinatal processes that determine astrocyte density and programmed cell death in dopaminergic neurons. Collectively, our characterisation of enduring, AGT-induced, sex-specific cytoarchitectural disturbances suggests novel mechanistic links for the strong association between early environmental challenge (inappropriate exposure to excess GCs) and vulnerability to developing aberrant behaviours in later life, with translational implications for dopamine-associated disorders (such as schizophrenia, ADHD, autism, depression), which typically show a sex bia

    The role of Gag in HIV-1 DNA synthesis and sensitivity to reverse transcriptase inhibitor drugs

    Get PDF
    We hypothesise that HIV-1 DNA synthesis occurs inside intact viral capsid (CA) cores. We propose that dNTPs are transported into the CA via an electrostatic channel, formed by six positively charged arginines in the centre of CA hexamers. Here, we consider whether reverse transcriptase inhibitor (RTI) sensitivity is altered when the nature of the channel is changed, either by Gag mutation or exchange with Gag from a non-pandemic HIV isolate with a different structure. There are two classes of RTIs: nucleoside/nucleotide based (NRTI) and non-nucleoside inhibitors (NNRTI). We hypothesised that negatively charged NRTIs would recruit to CA hexamers, to be transported into cores. However, NNRTIs are uncharged, yet potently inhibit DNA synthesis, suggesting that NNRTIs enter cores by diffusion or inhibit after uncoating. We tested HIV-1 vector sensitivity to RTIs, either bearing lab adapted M-group, transmitted founder, O-group or mutant Gag sequences. Viral inhibition was measured by comparing IC50 and IC90 values in a range of cell lines. Our data shows that some differences in Gag demonstrate a cell type-dependent effect on viral sensitivity to RTIs. We also tested the stage of RTI inhibition, measuring early and late–reverse transcription (RT) products of HIV-1 (M) and HIV-1 (O) virus in the presence of inhibitors. Our data show that both HIV-1 (M) and (O) vectors are inhibited after 2nd DNA strand transfer. We determined that a small number of vDNA strands are required to infect a U87 cell, which increases in the presence of RTIs or on R18G mutation. We conclude that differences in Gag have some small cell type-dependent effects on RTI sensitivity. We hypothesise this may be due to differences in the timing of CA uncoating between cell types, supported by our finding that all RTIs tested inhibit RT predominantly after 2nd strand transfer
    corecore