Studies on the structure and function of some enzyme inhibitors from plants

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Paradoxical Psoriatic Arthritis with the Initiation of Brodalumab and Guselkumab

Paradoxical plaque psoriasis reactions have been reported with the usage of biologics, primarily with the use of anti-TNF agents. Brodalumab, a human monoclonal antibody against interleukin-17 receptor A (IL17RA), and, guselkumab, an interleukin-23 blocker, are biologic agents that have been proven to be effective against psoriasis and psoriatic arthritis. We report a case of a 47 year old white male with a long standing history of psoriatic arthritis with worsening plaque psoriasis who was placed on brodalumab and guselkumab, separately, for control of his cutaneous manifestations. He experienced an unusual severe worsening of arthritis in a longstanding psoriasis and psoriatic arthritis within days of starting brodalumab, and subsequently within days of starting guselkumab despite a significant clearing of plaque psoriasis. Both reactions subsided after cessation of the offending agent. Paradoxical reactions caused by these newer biologics are unusual. Psoriatic arthropathy has been reported as an insignificant adverse effect in the literature for brodalumab but has not been reported for guselkumab. Additionally, paradoxical psoriatic arthritis flares usually occur de novo rather than a worsening of previous disease, as seen in our patient. In summary, this case highlights previously undescribed adverse reaction associated with the initiation of both brodalumab and guselkumab that one should be aware of.https://scholarlycommons.henryford.com/merf2020caserpt/1066/thumbnail.jp

Effects of Ginger Supplementation on Inflammation in Individuals

Background. Ginger is a widely used ingredient in Southeast Asian countries and has gained increasing popularity in the Western diet due to its purported health benefits. Ginger has high antioxidant power because of its rich phytochemistry profile that contributes to its anti- inflammatory properties. While there have been animal studies, the research of ginger’s effects in humans is limited. Objective. We sought to understand ginger’s effects on commonly assayed inflammatory biomarkers—C-Reactive Protein (CRP), Interleukin-6 (IL-6), and Tumor Necrosis Factor-Alpha (TNF- α)—in individuals with varying levels of physical activity. We propose that ginger may lower levels of these biomarkers due to its inherent anti-inflammatory characteristics. Design. We designed an eight-week cohort study. Blood draw measurements were taken at three timepoints: the start of study, at week four, and upon completion of study. Participants/setting. The study was conducted at Loma Linda University, where we enrolled twelve participants with a mean age of 42.4 ± 11.4 years who exercised at least once/week, did not take any anti-inflammatory medications, and who were free of any chronic inflammatory conditions. Intervention. Participants were instructed to take three grams of ginger supplement mixed with lemonade powder to improve palatability daily. Participants also completed a pre- and post- intervention Short Form Health questionnaire (SF-36) to evaluate quality of life. Main outcome measures. Inflammation was measured using three blood biomarkers: CRP, TNF-α, and IL-6. Quality of life was measured using the SF-36 questionnaire. Statistical analyses performed. The three inflammatory biomarkers were analyzed using the Friedman non-parametric test and the Wilcoxon test where appropriate. The SF-36 questionnaire was analyzed using a paired t-test. Results. Results of our study indicated a statistically significant reduction in TNF- α (p = .04) and a clinically significant reduction of greater than 15% in IL-6. There was a significant improvement in the domain of emotional well-being on the SF-36 after the ginger supplementation (p = .05). Conclusions. Ginger may potentially be used as an adjuvant intervention in the prevention and management of chronic inflammatory diseases such as cardiovascular disease, diabetes, and obesity

Rational polynomial representation of ribonucleotide reductase activity

BACKGROUND: Recent data suggest that ribonucleotide reductase (RNR) exists not only as a heterodimer R1(2)R2(2 )of R1(2 )and R2(2 )homodimers, but also as tetramers R1(4)R2(4 )and hexamers R1(6)R2(6). Recent data also suggest that ATP binds the R1 subunit at a previously undescribed hexamerization site, in addition to its binding to previously described dimerization and tetramerization sites. Thus, the current view is that R1 has four NDP substrate binding possibilities, four dimerization site binding possibilities (dATP, ATP, dGTP, or dTTP), two tetramerization site binding possibilities (dATP or ATP), and one hexamerization site binding possibility (ATP), in addition to possibilities of unbound site states. This large number of internal R1 states implies an even larger number of quaternary states. A mathematical model of RNR activity which explicitly represents the states of R1 currently exists, but it is complicated in several ways: (1) it includes up to six-fold nested sums; (2) it uses different mathematical structures under different substrate-modulator conditions; and (3) it requires root solutions of high order polynomials to determine R1 proportions in mono-, di-, tetra- and hexamer states and thus RNR activity as a function of modulator and total R1 concentrations. RESULTS: We present four (one for each NDP) rational polynomial models of RNR activity as a function of substrate and reaction rate modifier concentrations. The new models avoid the complications of the earlier model without compromising curve fits to recent data. CONCLUSION: Compared to the earlier model of recent data, the new rational polynomial models are simpler, adequately fitting, and likely better suited for biochemical network simulations

Human neural stem cell transplantation into the corpus callosum of Alzheimer’s mice

The hippocampus has been the target of stem cell transplantations in preclinical studies focused on Alzheimer’s disease, with results showing improvements in histological and behavioral outcomes. The corpus callosum is another structure that is affected early in Alzheimer’s disease. Therefore, we hypothesize that this structure is a novel target for human neural stem cell transplantation in transgenic Alzheimer’s disease mouse models. This study demonstrates the feasibility of targeting the corpus callosum and identifies an effective immunosuppression regimen for transplanted neural stem cell survival. These results support further preclinical development of the corpus callosum as a therapeutic target in Alzheimer’s disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138852/1/acn3443_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138852/2/acn3443.pd

A genetically encoded tool for reconstituting synthetic modulatory neurotransmission and reconnect neural circuits in vivo

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hawk, J. D., Wisdom, E. M., Sengupta, T., Kashlan, Z. D., & Colon-Ramos, D. A. A genetically encoded tool for reconstituting synthetic modulatory neurotransmission and reconnect neural circuits in vivo. Nature Communications, 12(1), (2021): 4795, https://doi.org/10.1038/s41467-021-24690-9.Chemogenetic and optogenetic tools have transformed the field of neuroscience by facilitating the examination and manipulation of existing circuits. Yet, the field lacks tools that enable rational rewiring of circuits via the creation or modification of synaptic relationships. Here we report the development of HySyn, a system designed to reconnect neural circuits in vivo by reconstituting synthetic modulatory neurotransmission. We demonstrate that genetically targeted expression of the two HySyn components, a Hydra-derived neuropeptide and its receptor, creates de novo neuromodulatory transmission in a mammalian neuronal tissue culture model and functionally rewires a behavioral circuit in vivo in the nematode Caenorhabditis elegans. HySyn can interface with existing optogenetic, chemogenetic and pharmacological approaches to functionally probe synaptic transmission, dissect neuropeptide signaling, or achieve targeted modulation of specific neural circuits and behaviors.This work was initiated in the Grass Laboratory at the Marine Biological Laboratories (MBL) with funding through a Grass Fellowship awarded to J.D.H. Thanks to Richard Goodman (OHSU) for encouragement during the conceptualization of the fellowship application, and the 2019 Grass Fellows, Mel Coleman (Grass Director), and Christophe Dupré (Associate Director) for advice and support during the summer fellowship. We thank the MBL Division of Education and participants in the Vendor Equipment Loan Program. Special thanks to Sutter Instruments, who generously provided all electrophysiology equipment and substantial on-site assistance, and Zeiss, who provided on-site assistance at MBL. We thank Zhao-Wen Wang and Ping Liu (UConn) for guidance and training in patch-clamp electrophysiology, as well as providing Neuro2a cells. We thank Rob Steele (UCI) for supplying Hydra, as well as advice and inspiration on Hydra biology. We thank members of the Colón-Ramos lab and Hari Shroff (NIH) for thoughtful comments on the manuscript. We thank Michael Koelle and Andrew Olson (Yale University) for advice and reagents regarding serotonin rewiring experiments. We also thank Steve Flavell (MIT) for ideas and reagents regarding the experiments associated with del-7. We thank Life Science Editors for editing assistance. D.A.C.-R. is an MBL Fellow. Research in the D.A.C.-R. lab was supported by NIH R01NS076558, DP1NS111778, and by an HHMI Scholar Award

Equilibrium model selection: dTTP induced R1 dimerization

<p>Abstract</p> <p>Background</p> <p>Biochemical equilibria are usually modeled iteratively: given one or a few fitted models, if there is a lack of fit or over fitting, a new model with additional or fewer parameters is then fitted, and the process is repeated. The problem with this approach is that different analysts can propose and select different models and thus extract different binding parameter estimates from the same data. An alternative is to first generate a comprehensive standardized list of plausible models, and to then fit them exhaustively, or semi-exhaustively.</p> <p>Results</p> <p>A framework is presented in which equilibriums are modeled as pairs (<it>g</it>, <it>h</it>) where <it>g </it>= 0 maps total reactant concentrations (system inputs) into free reactant concentrations (system states) which <it>h </it>then maps into expected values of measurements (system outputs). By letting dissociation constants <it>K</it>_{<it>d </it>}be either freely estimated, infinity, zero, or equal to other <it>K</it>_<it>d</it>, and by letting undamaged protein fractions be either freely estimated or 1, many <it>g </it>models are formed. A standard space of <it>g </it>models for ligand-induced protein dimerization equilibria is given. Coupled to an <it>h </it>model, the resulting (<it>g</it>, <it>h</it>) were fitted to dTTP induced R1 dimerization data (R1 is the large subunit of ribonucleotide reductase). Models with the fewest parameters were fitted first. Thereafter, upon fitting a batch, the next batch of models (with one more parameter) was fitted only if the current batch yielded a model that was better (based on the Akaike Information Criterion) than the best model in the previous batch (with one less parameter). Within batches models were fitted in parallel. This semi-exhaustive approach yielded the same best models as an exhaustive model space fit, but in approximately one-fifth the time.</p> <p>Conclusion</p> <p>Comprehensive model space based biochemical equilibrium model selection methods are realizable. Their significance to systems biology as mappings of data into mathematical models warrants their development.</p

Regulatory Considerations in the Design and Manufacturing of Implantable 3D‐Printed Medical Devices

Three‐dimensional (3D) printing, or additive manufacturing, technology has rapidly penetrated the medical device industry over the past several years, and innovative groups have harnessed it to create devices with unique composition, structure, and customizability. These distinctive capabilities afforded by 3D printing have introduced new regulatory challenges. The customizability of 3D‐printed devices introduces new complexities when drafting a design control model for FDA consideration of market approval. The customizability and unique build processes of 3D‐printed medical devices pose unique challenges in meeting regulatory standards related to the manufacturing quality assurance. Consistent material powder properties and optimal printing parameters such as build orientation and laser power must be addressed and communicated to the FDA to ensure a quality build. Postprinting considerations unique to 3D‐printed devices, such as cleaning, finishing and sterilization are also discussed. In this manuscript we illustrate how such regulatory hurdles can be navigated by discussing our experience with our group's 3D‐printed bioresorbable implantable device.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115990/1/cts12315.pd