Cyclotides derived from Viola dalatensis Gagnep: A novel approach for enrichment and evaluation of antimicrobial activity.

Cyclotides, plant-derived cysteine-rich peptides, exhibit a wide range of beneficial biological activities and possess exceptional structural stability. Cyclotides are commonly distributed throughout the Violaceae family. Viola dalatensis Gagnep, a Vietnamese species, has not been well studied, especially for cyclotides. This pioneering research explores cyclotides from V. dalatensis as antimicrobials. This study used a novel approach to enhance cyclotides after extraction. The approach combined 30% ammonium sulfate salt precipitation and RP-HPLC. A comprehensive analysis was performed to ascertain the overall protein content, flavonoids content, polyphenol content, and free radical scavenging capacity of compounds derived from V. dalatensis. Six known cyclotides were sequenced utilizing MS tandem. Semi-purified cyclotide mixtures (M1, M2, and M3) exhibited antibacterial efficacy against Bacillus subtilis (inhibitory diameters: 19.67-23.50 mm), Pseudomonas aeruginosa (22.17-23.50 mm), and Aspergillus flavus (14.67-21.33 mm). The enriched cyclotide precipitate from the stem extract demonstrated a minimum inhibitory concentration (MIC) of 0.08 mg/mL against P. aeruginosa, showcasing significant antibacterial effectiveness compared to the stem extract (MIC: 12.50 mg/mL). Considerable advancements have been achieved in the realm of cyclotides, specifically in their application as antimicrobial agents.

Atom-Based Machine Learning Model for Quantitative Property-Structure Relationship of Electronic Properties of Fusenes and Substituted Fusenes.

This study presents the development of machine-learning-based quantitative structure-property relationship (QSPR) models for predicting electron affinity, ionization potential, and band gap of fusenes from different chemical classes. Three variants of the atom-based Weisfeiler-Lehman (WL) graph kernel method and the machine learning model Gaussian process regressor (GPR) were used. The data pool comprises polycyclic aromatic hydrocarbons (PAHs), thienoacenes, cyano-substituted PAHs, and nitro-substituted PAHs computed with density functional theory (DFT) at the B3LYP-D3/6-31+G(d) level of theory. The results demonstrate that the GPR/WL kernel methods can accurately predict the electronic properties of PAHs and their derivatives with root-mean-square deviations of 0.15 eV. Additionally, we also demonstrate the effectiveness of the active learning protocol for the GPR/WL kernel methods pipeline, particularly for data sets with greater diversity. The interpretation of the model for contributions of individual atoms to the predicted electronic properties provides reasons for the success of our previous degree of π-orbital overlap model.

Mechanisms underlying reshuffling of visual responses by optogenetic stimulation in mice and monkeys.

The ability to optogenetically perturb neural circuits opens an unprecedented window into mechanisms governing circuit function. We analyzed and theoretically modeled neuronal responses to visual and optogenetic inputs in mouse and monkey V1. In both species, optogenetic stimulation of excitatory neurons strongly modulated the activity of single neurons yet had weak or no effects on the distribution of firing rates across the population. Thus, the optogenetic inputs reshuffled firing rates across the network. Key statistics of mouse and monkey responses lay on a continuum, with mice/monkeys occupying the low-/high-rate regions, respectively. We show that neuronal reshuffling emerges generically in randomly connected excitatory/inhibitory networks, provided the coupling strength (combination of recurrent coupling and external input) is sufficient that powerful inhibitory feedback cancels the mean optogenetic input. A more realistic model, distinguishing tuned visual vs. untuned optogenetic input in a structured network, reduces the coupling strength needed to explain reshuffling.

Machine Learning-Based Quantitative Structure-Property Relationships for the Electronic Properties of Cyano Polycyclic Aromatic Hydrocarbons.

In this study, quantitative structure-property relationships (QSPR) based on a machine learning (ML) methodology and the truncated degree of π-orbital overlap (DPO) to predict the electronic properties, namely, the bandgaps, electron affinities, and ionization potentials of the cyano polycyclic aromatic hydrocarbon (CN-PAH) chemical class were developed. The level of theory B3LYP/6-31+G(d) of density functional theory (DFT) was used to calculate a total of 926 data points for the development of the QSPR model. To include the substituents effects, a new descriptor was added to the DPO model. Consequently, the new ML-DPO model yields excellent linear correlations to predict the desired electronic properties with high accuracy to within 0.2 eV for all multi-CN-substituted PAHs and 0.1 eV for the mono-CN-substituted PAH subclass.

Gagones A-F: Six prenylated chalcones from the heartwood of Mansonia gagei.

Six undescribed prenylated chalcones gagones A-F were isolated from the acetone fraction of Mansonia gagei heartwood. Their structures were unambiguously established based on spectroscopic analysis (HRESIMS, 1D and 2D NMR), as well as comparison to literature data. Their absolute configurations were elucidated using DP4 and electronic circular dichroism calculations. Isolated compounds were evaluated for their inhibitory activity against α-glucosidase and DPPH assay. All of the tested compounds exhibited better activity than that of acarbose (IC50 93.6 ± 0.5 µM). Among them, gagone D exhibited the highest α-glucosidase inhibitory with the IC50 value of 3.6 ± 0.4 µM. For antioxidant activity, gagones A-C, and E showed more active than that of ascorbic acid (IC50 30.2 ± 0.5 µM) with the IC50 values of 13.2 ± 0.7, 20.1 ± 0.4, 19.3 ± 0.5 and 12.8 ± 0.2 µM, respectively.

Application of Machine Learning in Developing Quantitative Structure-Property Relationship for Electronic Properties of Polyaromatic Compounds.

The degree of π orbital overlap (DPO) model has been demonstrated to be an excellent quantitative structure-property relationship (QSPR) that can map two-dimensional structural information of polycyclic aromatic hydrocarbons (PAHs) and thienoacenes to their electronic properties, namely, band gaps, electron affinities, and ionization potentials. However, the model suffers from significant limitations that narrow its applications due to inefficient manual procedures in parameter optimization and descriptor formulation. In this work, we developed a machine learning (ML)-based method for efficiently optimizing DPO parameters and proposed a truncated DPO descriptor, which is simple enough that can be automatically extracted from simplified molecular-input line-entry system strings of PAHs and thienoacenes. Compared with the result from our previous studies, the ML-based methodology can optimize DPO parameters with four times fewer data, while it can achieve the same level of accuracy in predictions of the mentioned electronic properties to within 0.1 eV. The truncated DPO model also has similar accuracy to the full DPO model. Consequently, the ML-based DPO approach coupled with the truncated DPO model enables new possibilities for developing automatic pipelines for high-throughput screening and investigating new QSPR for new chemical classes.

Countering the future chemical weapons threat.

Shift focus from disarmament to preventing reemergence.

The impact of CD160 deficiency on alloreactive CD8 T cell responses and allograft rejection.

CD160 is a member of the immunoglobulin superfamily with a pattern of expression mainly restricted to cytotoxic cells. To assess the functional relevance of the HVEM/CD160 signaling pathway in allogeneic cytotoxic responses, exon 2 of the CD160 gene was targeted by CRISPR/Cas9 to generate CD160 deficient mice. Next, we evaluated the impact of CD160 deficiency in the course of an alloreactive response. To that aim, parental donor WT (wild-type) or CD160 KO (knock-out) T cells were adoptively transferred into non-irradiated semiallogeneic F1 recipients, in which donor alloreactive CD160 KO CD4 T cells and CD8 T cells clonally expanded less vigorously than in WT T cell counterparts. This differential proliferative response rate at the early phase of T cell expansion influenced the course of CD8 T cell differentiation and the composition of the effector T cell pool that led to a significant decreased of the memory precursor effector cells (MPECs) / short-lived effector cells (SLECs) ratio in CD160 KO CD8 T cells compared to WT CD8 T cells. Despite these differences in T cell proliferation and differentiation, allogeneic MHC class I mismatched (bm1) skin allograft survival in CD160 KO recipients was comparable to that of WT recipients. However, the administration of CTLA-4.Ig showed an enhanced survival trend of bm1 skin allografts in CD160 KO with respect to WT recipients. Finally, CD160 deficient NK cells were as proficient as CD160 WT NK cells in rejecting allogeneic cellular allografts or MHC class I deficient tumor cells. CD160 may represent a CD28 alternative costimulatory molecule for the modulation of allogeneic CD8 T cell responses either in combination with costimulation blockade or by direct targeting of alloreactive CD8 T cells that upregulate CD160 expression in response to alloantigen stimulation.

Development of a CNS-permeable reactivator for nerve agent exposure: an iterative, multi-disciplinary approach.

Nerve agents have experienced a resurgence in recent times with their use against civilian targets during the attacks in Syria (2012), the poisoning of Sergei and Yulia Skripal in the United Kingdom (2018) and Alexei Navalny in Russia (2020), strongly renewing the importance of antidote development against these lethal substances. The current standard treatment against their effects relies on the use of small molecule-based oximes that can efficiently restore acetylcholinesterase (AChE) activity. Despite their efficacy in reactivating AChE, the action of drugs like 2-pralidoxime (2-PAM) is primarily limited to the peripheral nervous system (PNS) and, thus, provides no significant protection to the central nervous system (CNS). This lack of action in the CNS stems from their ionic nature that, on one end makes them very powerful reactivators and on the other renders them ineffective at crossing the Blood Brain Barrier (BBB) to reach the CNS. In this report, we describe the use of an iterative approach composed of parallel chemical and in silico syntheses, computational modeling, and a battery of detailed in vitro and in vivo assays that resulted in the identification of a promising, novel CNS-permeable oxime reactivator. Additional experiments to determine acute and chronic toxicity are ongoing.

Cystathionine-gamma-lyase overexpression in T cells enhances antitumor effect independently of cysteine autonomy.

T cells could be engineered to overcome the aberrant metabolic milieu of solid tumors and tip the balance in favor of a long-lasting clinical response. Here, we explored the therapeutic potential of stably overexpressing cystathionine-gamma-lyase (CTH, CSE, or cystathionase), a pivotal enzyme of the transsulfuration pathway, in antitumor CD8+ T cells with the initial aim to boost intrinsic cysteine metabolism. Using a mouse model of adoptive cell transfer (ACT), we found that CTH-expressing T cells showed a superior control of tumor growth compared to control T cells. However, contrary to our hypothesis, this effect was not associated with increased T cell expansion in vivo or proliferation rescue in the absence of cysteine/cystine in vitro. Rather than impacting methionine or cysteine, ACT with CTH overexpression unexpectedly reduced glycine, serine, and proline concentration within the tumor interstitial fluid. Interestingly, in vitro tumor cell growth was mostly impacted by the combination of serine/proline or serine/glycine deprivation. These results suggest that metabolic gene engineering of T cells could be further investigated to locally modulate amino acid availability within the tumor environment while avoiding systemic toxicity.

Rotational thromboelastometry parameters as predicting factors for bleeding in immune thrombocytopenic purpura.

OBJECTIVE/BACKGROUND: Patients with immune thrombocytopenic purpura (ITP) often present with a severe reduction in platelet counts and suffer from an increased risk of bleeding. However, platelet counts do not accurately predict bleeding risk in these patients. METHODS: We thereby conducted a case series prospective study to compare the ability to predict hemorrhage in ITP patients between platelet counts and various rotational thromboelastometry (ROTEM) parameters. RESULTS: The inclusion criteria for patients diagnosed with acute, persistent, and chronic ITP were platelet counts of <30 × 109/L and no clinically significant bleeding (grade ≥ 2 according to the WHO Bleeding Scale) at the beginning of the study. After 24 hours of follow-up, of the 45 enrolled patients, 14 (31.1%) experienced clinically significant bleeding. The mean platelet counts of patients with and without clinically significant bleeding were not statistically different (p = .09). However, the mean EXTEM maximum clot firmness (MCF), EXTEM A10, EXTEM area under the curve (AUC), and platelet maximum clot elasticity (MCE) values of the two groups were statistically different (p < .05). There was also a significant difference in IPF values between these two groups (p < .05.) CONCLUSION: Results obtained from this preliminary study demonstrate that ROTEM parameters might be useful in predicting factors for hemorrhage in ITP patients. Future studies with a larger sample size is warranted to confirm our findings, which will allow prompt and effective bleeding management in ITP patients.

Suspected heparin-induced thrombocytopenia in a COVID-19 patient on extracorporeal membrane oxygenation support: a case report.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) support can be life-saving in critically ill COVID-19 patients. However, there are many complications associated with this procedure, including Heparin-induced thrombocytopenia (HIT.) Despite its rarity in ECMO cases, HIT can lead to devastating consequences and is difficult to manage. CASE PRESENTATION: In this report, we present a case of a COVID-19 patient on ECMO support who was diagnosed with HIT and required intensive treatment. Initially, HIT was only suspected due to newly-developed thrombocytopenia and oxygenator dysfunction, with thrombi observed later. Regarding his treatment, since there was no recommended replacement to heparin available to us at the time of diagnosis, we decided to use rivaroxaban temporarily. No adverse events were recorded during that period. The patient was able to make a full recovery. CONCLUSION: HIT may jeopardize patient's care during ECMO. As COVID-19 may bring about a surge in the number of patients requiring ECMO support, we need consented guidance to optimize treatment in this specific situation.

Quantum Mechanical-Based Quantitative Structure-Property Relationships for Electronic Properties of Two Large Classes of Organic Semiconductor Materials: Polycyclic Aromatic Hydrocarbons and Thienoacenes.

In this study, the degree of the π-orbital overlap (DPO) model proposed earlier for polycyclic aromatic hydrocarbons (PAH) was employed to develop quantitative structure-property relationships (QSPRs) for band gaps, ionization potentials, and electron affinities of thienoacenes. DPO is based on two-dimensional topological draw of aromatic molecules. The B3LYP/6-31+G(d) level of density functional theory (DFT) was used to provide chemical data for developing QSPRs. We found that the DPO model is able to capture the correct physics of electronic properties of aromatic molecules so that with only six nonzero topological parameters (four for PAH and additional two for thienoacenes), the DPO model yields the linear dependence of electronic properties of both the PAH and thienoacenes classes by a single set of QSPRs with the accuracy to within 0.1 eV of the DFT results. The results suggest that within the DPO framework, all aromatic molecules can share the same set of QSPRs.

Generation of Immunodeficient Rats With Rag1 and Il2rg Gene Deletions and Human Tissue Grafting Models.

BACKGROUND: Immunodeficient mice are invaluable tools to analyze the long-term effects of potentially immunogenic molecules in the absence of adaptive immune responses. Nevertheless, there are models and experimental situations that would beneficiate of larger immunodeficient recipients. Rats are ideally suited to perform experiments in which larger size is needed and are still a small animal model suitable for rodent facilities. Additionally, rats reproduce certain human diseases better than mice, such as ankylosing spondylitis and Duchenne disease, and these disease models would greatly benefit from immunodeficient rats to test different immunogenic treatments. METHODS: We describe the generation of Il2rg-deficient rats and their crossing with previously described Rag1-deficient rats to generate double-mutant RRG animals. RESULTS: As compared with Rag1-deficient rats, Il2rg-deficient rats were more immunodeficient because they partially lacked not only T and B cells but also NK cells. RRG animals showed a more profound immunossuppressed phenotype because they displayed undetectable levels of T, B, and NK cells. Similarly, all immunoglobulin isotypes in sera were decreased in Rag1- or Il2rg-deficient rats and undetectable in Rats Rag1 and Il2rg (RRG) animals. Rag1- or Il2rg-deficient rats rejected allogeneic skin transplants and human tumors, whereas animals not only accepted allogeneic rat skin but also xenogeneic human tumors, skin, and hepatocytes. Immune humanization of RRG animals was unsuccessful. CONCLUSIONS: Thus, immunodeficient RRG animals are useful recipients for long-term studies in which immune responses could be an obstacle, including tissue humanization of different tissues.

The biodistribution and pharmacokinetics of the oxime acetylcholinesterase reactivator RS194B in guinea pigs.

Organophosphorus-based (OP) nerve agents represent some of the most toxic substances known to mankind. The current standard of care for exposure has changed very little in the past decades, and relies on a combination of atropine to block receptor activity and oxime-type acetylcholinesterase (AChE) reactivators to reverse the OP binding to AChE. Although these oximes can block the effects of nerve agents, their overall efficacy is reduced by their limited capacity to cross the blood-brain barrier (BBB). RS194B, a new oxime developed by Radic et al. (J. Biol. Chem., 2012) has shown promise for enhanced ability to cross the BBB. To fully assess the potential of this compound as an effective treatment for nerve agent poisoning, a comprehensive evaluation of its pharmacokinetic (PK) and biodistribution profiles was performed using both intravenous and intramuscular exposure routes. The ultra-sensitive technique of accelerator mass spectrometry was used to quantify the compound's PK profile, tissue distribution, and brain/plasma ratio at four dose concentrations in guinea pigs. PK analysis revealed a rapid distribution of the oxime with a plasma t1/2 of ∼1 h. Kidney and liver had the highest concentrations per gram of tissue followed by lung, spleen, heart and brain for all dose concentrations tested. The Cmax in the brain ranged between 0.03 and 0.18% of the administered dose, and the brain-to-plasma ratio ranged from 0.04 at the 10 mg/kg dose to 0.18 at the 200 mg/kg dose demonstrating dose dependent differences in brain and plasma concentrations. In vitro studies show that both passive diffusion and active transport contribute little to RS194B traversal of the BBB. These results indicate that biodistribution is widespread, but very low quantities accumulate in the guinea pig brain, indicating this compound may not be suitable as a centrally active reactivator.

Predicting a Drug's Membrane Permeability: A Computational Model Validated With in Vitro Permeability Assay Data.

Membrane permeability is a key property to consider during the drug design process, and particularly vital when dealing with small molecules that have intracellular targets as their efficacy highly depends on their ability to cross the membrane. In this work, we describe the use of umbrella sampling molecular dynamics (MD) computational modeling to comprehensively assess the passive permeability profile of a range of compounds through a lipid bilayer. The model was initially calibrated through in vitro validation studies employing a parallel artificial membrane permeability assay (PAMPA). The model was subsequently evaluated for its quantitative prediction of permeability profiles for a series of custom synthesized and closely related compounds. The results exhibited substantially improved agreement with the PAMPA data, relative to alternative existing methods. Our work introduces a computational model that underwent progressive molding and fine-tuning as a result of its synergistic collaboration with numerous in vitro PAMPA permeability assays. The presented computational model introduces itself as a useful, predictive tool for permeability prediction.

Detection of ESKAPE Bacterial Pathogens at the Point of Care Using Isothermal DNA-Based Assays in a Portable Degas-Actuated Microfluidic Diagnostic Assay Platform.

An estimated 1.5 billion microbial infections occur globally each year and result in ∼4.6 million deaths. A technology gap associated with commercially available diagnostic tests in remote and underdeveloped regions prevents timely pathogen identification for effective antibiotic chemotherapies for infected patients. The result is a trial-and-error approach that is limited in effectiveness, increases risk for patients while contributing to antimicrobial drug resistance, and reduces the lifetime of antibiotics. This paper addresses this important diagnostic technology gap by describing a low-cost, portable, rapid, and easy-to-use microfluidic cartridge-based system for detecting the ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) bacterial pathogens that are most commonly associated with antibiotic resistance. The point-of-care molecular diagnostic system consists of a vacuum-degassed microfluidic cartridge preloaded with lyophilized recombinase polymerase amplification (RPA) assays and a small portable battery-powered electronic incubator/reader. The isothermal RPA assays detect the targeted ESKAPE pathogens with high sensitivity (e.g., a limit of detection of ∼10 nucleic acid molecules) that is comparable to that of current PCR-based assays, and they offer advantages in power consumption, engineering, and robustness, which are three critical elements required for the point-of-care setting. IMPORTANCE: This paper describes a portable system for rapidly identifying bacteria in resource-limited environments; we highlight the capabilities of the technology by detecting different pathogens within the ESKAPE collection, which cause nosocomial infections. The system is designed around isothermal DNA-based assays housed within an autonomous plastic cartridge that are designed with the end user in mind, who may have limited technological training. Displaying excellent sensitivity and specificity, the assay systems that we demonstrate may enable future diagnoses of bacterial infection to guide the development of effective chemotherapies and may have a role in areas beyond health where rapid detection is valuable, including in industrial processing and manufacturing, food security, agriculture, and water quality testing.

Homology-directed repair in rodent zygotes using Cas9 and TALEN engineered proteins.

The generation of genetically-modified organisms has been revolutionized by the development of new genome editing technologies based on the use of gene-specific nucleases, such as meganucleases, ZFNs, TALENs and CRISPRs-Cas9 systems. The most rapid and cost-effective way to generate genetically-modified animals is by microinjection of the nucleic acids encoding gene-specific nucleases into zygotes. However, the efficiency of the procedure can still be improved. In this work we aim to increase the efficiency of CRISPRs-Cas9 and TALENs homology-directed repair by using TALENs and Cas9 proteins, instead of mRNA, microinjected into rat and mouse zygotes along with long or short donor DNAs. We observed that Cas9 protein was more efficient at homology-directed repair than mRNA, while TALEN protein was less efficient than mRNA at inducing homology-directed repair. Our results indicate that the use of Cas9 protein could represent a simple and practical methodological alternative to Cas9 mRNA in the generation of genetically-modified rats and mice as well as probably some other mammals.