176 research outputs found
Modeling reactivity to biological macromolecules with a deep multitask network
Most
small-molecule drug candidates fail before entering the market,
frequently because of unexpected toxicity. Often, toxicity is detected
only late in drug development, because many types of toxicities, especially
idiosyncratic adverse drug reactions (IADRs), are particularly hard
to predict and detect. Moreover, drug-induced liver injury (DILI)
is the most frequent reason drugs are withdrawn from the market and
causes 50% of acute liver failure cases in the United States. A common
mechanism often underlies many types of drug toxicities, including
both DILI and IADRs. Drugs are bioactivated by drug-metabolizing enzymes
into reactive metabolites, which then conjugate to sites in proteins
or DNA to form adducts. DNA adducts are often mutagenic and may alter
the reading and copying of genes and their regulatory elements, causing
gene dysregulation and even triggering cancer. Similarly, protein
adducts can disrupt their normal biological functions and induce harmful
immune responses. Unfortunately, reactive metabolites are not reliably
detected by experiments, and it is also expensive to test drug candidates
for potential to form DNA or protein adducts during the early stages
of drug development. In contrast, computational methods have the potential
to quickly screen for covalent binding potential, thereby flagging
problematic molecules and reducing the total number of necessary experiments.
Here, we train a deep convolution neural networkî—¸the XenoSite
reactivity modelî—¸using literature data to accurately predict
both sites and probability of reactivity for molecules with glutathione,
cyanide, protein, and DNA. On the site level, cross-validated predictions
had area under the curve (AUC) performances of 89.8% for DNA and 94.4%
for protein. Furthermore, the model separated molecules electrophilically
reactive with DNA and protein from nonreactive molecules with cross-validated
AUC performances of 78.7% and 79.8%, respectively. On both the site-
and molecule-level, the model’s performances significantly
outperformed reactivity indices derived from quantum simulations that
are reported in the literature. Moreover, we developed and applied
a selectivity score to assess preferential reactions with the macromolecules
as opposed to the common screening traps. For the entire data set
of 2803 molecules, this approach yielded totals of 257 (9.2%) and
227 (8.1%) molecules predicted to be reactive only with DNA and protein,
respectively, and hence those that would be missed by standard reactivity
screening experiments. Site of reactivity data is an underutilized
resource that can be used to not only predict if molecules are reactive,
but also show where they might be modified to reduce toxicity while
retaining efficacy. The XenoSite reactivity model is available at http://swami.wustl.edu/xenosite/p/reactivity
Open source drug discovery with the Malaria Box compound collection for neglected diseases and beyond
Formalizing Chemical Physics using the Lean Theorem Prover
Chemical theory can be made more rigorous using the Lean theorem prover, an
interactive theorem prover for complex mathematics. We formalize the Langmuir
and BET theories of adsorption, making each scientific premise clear and every
step of the derivations explicit. Lean's math library, mathlib, provides
formally verified theorems for infinite geometries series, which are central to
BET theory. While writing these proofs, Lean prompts us to include mathematical
constraints that were not originally reported. We also illustrate how Lean
flexibly enables the reuse of proofs that build on more complex theories
through the use of functions, definitions, and structures. Finally, we
construct scientific frameworks for interoperable proofs, by creating
structures for classical thermodynamics and kinematics, using them to formalize
gas law relationships like Boyle's Law and equations of motion underlying
Newtonian mechanics, respectively. This approach can be extended to other
fields, enabling the formalization of rich and complex theories in science and
engineering
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An In Vitro Pipeline for Screening and Selection of Citrus-Associated Microbiota with Potential Anti-"Candidatus Liberibacter asiaticus" Properties.
Huanglongbing (HLB) is a destructive citrus disease that is lethal to all commercial citrus plants, making it the most serious citrus disease and one of the most serious plant diseases. Because of the severity of HLB and the paucity of effective control measures, we structured this study to encompass the entirety of the citrus microbiome and the chemistries associated with that microbial community. We describe the spatial niche diversity of bacteria and fungi associated with citrus roots, stems, and leaves using traditional microbial culturing integrated with culture-independent methods. Using the culturable sector of the citrus microbiome, we created a microbial repository using a high-throughput bulk culturing and microbial identification pipeline. We integrated an in vitro agar diffusion inhibition bioassay into our culturing pipeline that queried the repository for antimicrobial activity against Liberibacter crescens, a culturable surrogate for the nonculturable "Candidatus Liberibacter asiaticus" bacterium associated with HLB. We identified microbes with robust inhibitory activity against L. crescens that include the fungi Cladosporium cladosporioides and Epicoccum nigrum and bacterial species of Pantoea, Bacillus, and Curtobacterium Purified bioactive natural products with anti-"Ca. Liberibacter asiaticus" activity were identified from the fungus C. cladosporioides Bioassay-guided fractionation of an organic extract of C. cladosporioides yielded the natural products cladosporols A, C, and D as the active agents against L. crescens This work serves as a foundation for unraveling the complex chemistries associated with the citrus microbiome to begin to understand the functional roles of members of the microbiome, with the long-term goal of developing anti-"Ca Liberibacter asiaticus" bioinoculants that thrive in the citrus holosystem.IMPORTANCE Globally, citrus is threatened by huanglongbing (HLB), and the lack of effective control measures is a major concern of farmers, markets, and consumers. There is compelling evidence that plant health is a function of the activities of the plant's associated microbiome. Using Liberibacter crescens, a culturable surrogate for the unculturable HLB-associated bacterium "Candidatus Liberibacter asiaticus," we tested the hypothesis that members of the citrus microbiome produce potential anti-"Ca Liberibacter asiaticus" natural products with potential anti-"Ca Liberibacter asiaticus" activity. A subset of isolates obtained from the microbiome inhibited L. crescens growth in an agar diffusion inhibition assay. Further fractionation experiments linked the inhibitory activity of the fungus Cladosporium cladosporioides to the fungus-produced natural products cladosporols A, C, and D, demonstrating dose-dependent antagonism to L. crescens
IGVC drive by wire project: Critical design report
Investigate and develop a Drive-By-Wire (DBW) system, its computer interface, and user interface for a Polaris Gem e2. The vehicle is planned to participate in the IGVC 2023 autonomous vehicle competition. The DBW system includes automatic control of brakes, throttle, steering, and potentially other components, such as lights. The final solution included hydraulic autonomous brakes, a cabled emergency brake, and numerous custom controller boards. The boards interface via a research CAN bus, include hardware based ESTOP handling, and a interface with the vehicle through a system of relays designed to fully disconnect the boards during manual control
Gene Alterations of Ovarian Cancer Cells Expressing Estrogen Receptors by Estrogen and Bisphenol A Using Microarray Analysis
Since endocrine disrupting chemicals (EDCs) may interfere with the endocrine system(s) of our body and have an estrogenicity, we evaluated the effect(s) of bisphenol A (BPA) on the transcriptional levels of altered genes in estrogen receptor (ER)-positive BG-1 ovarian cancer cells by microarray and real-time polymerase-chain reaction. In this study, treatment with 17β-estradiol (E2) or BPA increased mRNA levels of E2-responsive genes related to apoptosis, cancer and cell cycle, signal transduction and nucleic acid binding etc. In parallel with their microarray data, the mRNA levels of some altered genes including RAB31_MEMBER RAS ONCOGENE FAMILY (U59877), CYCLIN D1 (X59798), CYCLIN-DEPENDENT KINASE 4 (U37022), IGF-BINDING PROTEIN 4 (U20982), and ANTI-MULLERIAN HORMONE (NM_000479) were significantly induced by E2 or BPA in this cell model. These results indicate that BPA in parallel with E2 induced the transcriptional levels of E2-responsive genes in an estrogen receptor (ER)-positive BG-1 cells. In conclusion, these microarray and real-time polymerase-chain reaction results indicate that BPA, a potential weak estrogen, may have estrogenic effect by regulating E2-responsive genes in ER-positive BG-1 cells and BG-1 cells would be the best in vitro model to detect these estrogenic EDCs
Mixed Chamber Ensembles
Kennesaw State University School of Music presents Mixed Chamber Ensembles, 4:00 performance.https://digitalcommons.kennesaw.edu/musicprograms/1428/thumbnail.jp
Why are we not flooded by involuntary thoughts about the past and future? Testing the cognitive inhibition dependency hypothesis
© The Author(s) 2018In everyday life, involuntary thoughts about future plans and events occur as often as involuntary thoughts about the past. However, compared to involuntary autobiographical memories (IAMs), such episodic involuntary future thoughts (IFTs) have become a focus of study only recently. The aim of the present investigation was to examine why we are not constantly flooded by IFTs and IAMs given that they are often triggered by incidental cues while performing undemanding activities. One possibility is that activated thoughts are suppressed by the inhibitory control mechanism, and therefore depleting inhibitory control should enhance the frequency of both IFTs and IAMs. We report an experiment with a between-subjects design, in which participants in the depleted inhibition condition performed a 60-min high-conflict Stroop task before completing a laboratory vigilance task measuring the frequency of IFTs and IAMs. Participants in the intact inhibition condition performed a version of the Stroop task that did not deplete inhibitory control. To control for physical and mental fatigue resulting from performing the 60-min Stroop tasks in experimental conditions, participants in the control condition completed only the vigilance task. Contrary to predictions, the number of IFTs and IAMs reported during the vigilance task, using the probe-caught method, did not differ across conditions. However, manipulation checks showed that participants’ inhibitory resources were reduced in the depleted inhibition condition, and participants were more tired in the experimental than in the control conditions. These initial findings suggest that neither inhibitory control nor physical and mental fatigue affect the frequency of IFTs and IAMs.Peer reviewedFinal Published versio
Mixed Chamber Ensembles
KSU School of Music presents Mixed Chamber Ensembles.https://digitalcommons.kennesaw.edu/musicprograms/1312/thumbnail.jp
Hepatic transcriptional responses to copper in the three-spined stickleback are affected by their pollution exposure history
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Some fish populations inhabiting contaminated environments show evidence of increased chemical tolerance, however the mechanisms contributing to this tolerance, and whether this is heritable, are poorly understood. We investigated the responses of two populations of wild three-spined stickleback (Gasterosteus aculeatus) with different histories of contaminant exposure to an oestrogen and copper, two widespread aquatic pollutants. Male stickleback originating from two sites, the River Aire, with a history of complex pollution discharges, and Siblyback Lake, with a history of metal contamination, were depurated and then exposed to copper (46ÎĽg/L) and the synthetic oestrogen ethinyloestradiol (22ng/L). The hepatic transcriptomic response was compared between the two populations and to a reference population with no known history of exposure (Houghton Springs, Dorset). Gene responses included those typical for both copper and oestrogen, with no discernable difference in response to oestrogen between populations. There was, however, some difference in the magnitude of response to copper between populations. Siblyback fish showed an elevated baseline transcription of genes encoding metallothioneins and a lower level of metallothionein induction following copper exposure, compared to those from the River Aire. Similarly, a further experiment with an F1 generation of Siblyback fish bred in the laboratory found evidence for elevated transcription of genes encoding metallothioneins in unexposed fish, together with an altered transcriptional response to 125ÎĽg/L copper, compared with F1 fish originating from the clean reference population exposed to the same copper concentration. These data suggest that the stickleback from Siblyback Lake have a differential response to copper, which is inherited by the F1 generation in laboratory conditions, and for which the underlying mechanism may include an elevation of baseline transcription of genes encoding metallothioneins. The genetic and/or epigenetic mechanisms contributing to this inherited alteration of metallothionein transcription have yet to be established.This work was funded by the UK NERC postgenomic and proteomic programme grant NE/C507661/1 and by a Fisheries Society of the British Isles research grant to EMS. Birmingham functional genomics facilities were funded by BBSRC grant 6/JIF13209. We thank R.E. Godfrey, S. Jondhale, A. Jones, and L. Klovrza for technical assistance, J.K. Chipman for help and support, and the Environment Agency for provision of water chemistry data
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