Antisense oligonucleotide-based therapies for the treatment of osteoarthritis: Opportunities and roadblocks

Osteoarthritis (OA) is a debilitating disease with no approved disease-modifying therapies. Among the challenges for developing treatment is achieving targeted drug delivery to affected joints. This has contributed to the failure of several drug candidates for the treatment of OA. Over the past 20 years, significant advances have been made in antisense oligonucleotide (ASO) technology for achieving targeted delivery to tissues and cells both in vitro and in vivo. Since ASOs are able to bind specific gene regions and regulate protein translation, they are useful for correcting aberrant endogenous mechanisms associated with certain diseases. ASOs can be delivered locally through intra-articular injection, and can enter cells through natural cellular uptake mechanisms. Despite this, ASOs have yet to be successfully tested in clinical trials for the treatment of OA. Recent chemical modification to ASOs have further improved cellular uptake and reduced toxicity. Among these are locked nucleic acid (LNA)-based ASOs, which have shown promising results in clinical trials for diseases such as hepatitis and dyslipidemia. Recently, LNA-based ASOs have been tested both in vitro and in vivo for their therapeutic potential in OA, and some have shown promising joint-protective effects in preclinical OA animal models. In order to accelerate the testing of ASO therapies in a clinical trial setting for OA, further investigation into delivery mechanisms is required. In this review article, we discuss opportunities for viral-, particle-, biomaterial-, and chemical modification-based therapies, which are currently in preclinical testing. We also address potential roadblocks in the clinical translation of ASO-based therapies for the treatment of OA, such as the limitations associated with OA animal models and the challenges with drug toxicity. Taken together, we review what is known and what would be useful to accelerate translation of ASO-based therapies for the treatment of OA

A bioinformatics approach to microRNA-sequencing analysis

The rapid expansion of Next Generation Sequencing (NGS) data availability has made exploration of appropriate bioinformatics analysis pipelines a timely issue. Since there are multiple tools and combinations thereof to analyze any dataset, there can be uncertainty in how to best perform an analysis in a robust and reproducible manner. This is especially true for newer omics applications, such as miRNomics, or microRNA-sequencing (miRNA-sequencing). As compared to transcriptomics, there have been far fewer miRNA-sequencing studies performed to date, and those that are reported seldom provide detailed description of the bioinformatics analysis, including aspects such as Unique Molecular Identifiers (UMIs). In this article, we attempt to fill the gap and help researchers understand their miRNA-sequencing data and its analysis. This article will specifically discuss a customizable miRNA bioinformatics pipeline that was developed using miRNA-sequencing datasets generated from human osteoarthritis plasma samples. We describe quality assessment of raw sequencing data files, reference-based alignment, counts generation for miRNA expression levels, and novel miRNA discovery. This report is expected to improve clarity and reproducibility of the bioinformatics portion of miRNA-sequencing analysis, applicable across any sample type, to promote sharing of detailed protocols in the NGS field

Inhibition of iNOS induction and nf-κΒ activation by taste compounds from the edible mushroom tricholoma caligatum (Viv.) ricken

© 2019 ACG Publications. All rights reserved. Tricholoma caligatum (Viv.) Ricken is an edible mushroom that belongs to matsutake group. The first chemical investigation of the three different extracts of Tricholoma caligatum resulted in two new compounds, 8-demethoxylascivol (1) and 8-epi-lascivol (2) and six known compounds, lascivol (3), trametenolic acid (4), ergosterol (5), ergosterol peroxide (6), 5α, 6α-epoxyergosterol (7), and cerebroside B (8). Their structures were elucidated by spectroscopic analyses including 1D and 2D NMR data. The biological activities of all the compounds were evaluated toward multiple targets related to inflammation and metabolic disorder such as NF-κΒ, iNOS and ROS. The findings of this study reveal that the edible mushroom Tricholoma caligatum could be a potential source for anti-inflammatory bioactive metabolites

Can genetics guide exercise prescriptions in osteoarthritis?

Osteoarthritis (OA) is the most common form of arthritis and has a multifactorial etiology. Current management for OA focuses on minimizing pain and functional loss, typically involving pharmacological, physical, psychosocial, and mind-body interventions. However, there remain challenges in determining which patients will benefit most from which interventions. Although exercise-based interventions are recommended as first-line treatments and are known to be beneficial for managing both the disease and illness of OA, the optimal exercise prescription is unknown, due in part to our limited understanding of the precise mechanisms underlying its action. Here we present our perspective on the potential role of genetics in guiding exercise prescription for persons with OA. We describe key publications in the areas of exercise and OA, genetics and OA, and exercise and genetics, and point to a paucity of knowledge at the intersection of exercise, genetics, and OA. We suggest there is emerging evidence to support the use of genetics and epigenetics to explain the beneficial effects of exercise for OA. We identify missing links in the existing research relating to exercise, genetics, and OA, and highlight epigenetics as a promising mechanism through which environmental exposures such as exercise may impact OA outcomes. We anticipate future studies will improve our understanding of how genetic and epigenetic factors mediate exercise-based interventions to support implementation and ultimately improve OA patient care

Neo-clerodanes from Teucrium divaricatum and their potential antiinflammatory and antimicrobial activities

Corresponding author (NCNPR): Fadime Aydoğan, [email protected]://egrove.olemiss.edu/pharm_annual_posters_2022/1000/thumbnail.jp

Chemical Analysis and Biological Activities of Salvia lavandulifolia Vahl. Essential Oil

Genus Salvia is one of important genera belonging to family lamiaceae. Most of reported biological activities of Salvia usually attributed to its volatile oil. The chemical composition of essential oil from Salvia lavandulifolia was analyzed by GC/MS. A total of sixty seven components were identified in the oil of S. lavandulifolia representing 95.78% of the total oil. β-caryophyllene (11.87%), spathulenol (8.13%), neomenthol (7.75%), pulegone (6.97%), hexadecanoic acid (6.85%), germacrene-D (5.70%), bicyclogermacrene (4.53%), caryophyllene oxide (3.97%) and humulene (3.29%) were found to be the major constituents. The oil showed no antimicrobial and antileishmanial activities in a concentration up to 200 and20 µg/mL, respectively. It displayed a weak antimalarial activity (47 % inhibition) against P. flaciparium.The oil exhibited anti-inflammatory activity adopting iNOS inhibition assay with IC50of 30 µg/mL, but there is no cytotoxicity demonstrated by the oil at tested concentration of 100 µg/mL. Keywords: S. lavandulifolia, essential oil, antimalaria, antimicrobial, antiinflammtory, anticancer

Biological and Phytochemical Studies on Six Astragalus Taxa from Anatolia

Corresponding author (NCNPR): Fadime Aydoğan, [email protected]://egrove.olemiss.edu/pharm_annual_posters_2022/1001/thumbnail.jp

Characterization of miR-335-5p and miR-335-3p in human osteoarthritic tissues

OBJECTIVE: We aimed to characterize the expression patterns, gene targets, and functional effects of miR-335-5p and miR-335-3p among seven primary human knee and hip osteoarthritic tissue types. METHODS: We collected synovial fluid, subchondral bone, articular cartilage, synovium, meniscus/labrum, infrapatellar/acetabular fat, anterior cruciate ligament/ligamentum teres, and vastus medialis oblique/quadratus femoris muscle (n = 7-20) from surgical patients with early- or late-stage osteoarthritis (OA) and quantified miR-335-5p and miR-335-3p expression by real-time PCR. Predicted gene targets were measured in knee OA infrapatellar fat following miRNA inhibitor transfection (n = 3), and prioritized gene targets were validated following miRNA inhibitor and mimic transfection (n = 6). Following pathway analyses, we performed Oil-Red-O staining to assess changes in total lipid content in infrapatellar fat. RESULTS: Showing a 227-fold increase in knee OA infrapatellar fat (the highest expressing tissue) versus meniscus (the lowest expressing tissue), miR-335-5p was more abundant than miR-335-3p (92-fold increase). MiR-335-5p showed higher expression across knee tissues versus hip tissues, and in late-stage versus early-stage knee OA fat. Exploring candidate genes, VCAM1 and MMP13 were identified as putative direct targets of miR-335-5p and miR-335-3p, respectively, showing downregulation with miRNA mimic transfection. Exploring candidate pathways, predicted miR-335-5p gene targets were enriched in a canonical adipogenesis network (p = 2.1e - 5). Modulation of miR-335-5p in late-stage knee OA fat showed an inverse relationship to total lipid content. CONCLUSION: Our data suggest both miR-335-5p and miR-335-3p regulate gene targets in late-stage knee OA infrapatellar fat, though miR-335-5p appears to be more prominent, with tissue-, joint-, and stage-specific effects

Cantharidin Poisoning due to Blister Beetle Ingestion in Children : Two case reports and a review of clinical presentations

Cantharidin is an intoxicant found in beetles in the Meloidae (Coleoptera) family. Ingestion may result in haematemesis, impaired level of consciousness, electrolyte disturbance, haematurea and renal impairment. Here, we report two paediatric cases of meloid beetle ingestion resulting in cantharidin poisoning and the clinical presentation of the ensuing intoxication

Identification of the ubiquitin–proteasome pathway domain by hyperparameter optimization based on a 2D convolutional neural network

The major mechanism of proteolysis in the cytosol and nucleus is the ubiquitin–proteasome pathway (UPP). The highly controlled UPP has an effect on a wide range of cellular processes and substrates, and flaws in the system can lead to the pathogenesis of a number of serious human diseases. Knowledge about UPPs provide useful hints to understand the cellular process and drug discovery. The exponential growth in next-generation sequencing wet lab approaches have accelerated the accumulation of unannotated data in online databases, making the UPP characterization/analysis task more challenging. Thus, computational methods are used as an alternative for fast and accurate identification of UPPs. Aiming this, we develop a novel deep learning-based predictor named “2DCNN-UPP” for identifying UPPs with low error rate. In the proposed method, we used proposed algorithm with a two-dimensional convolutional neural network with dipeptide deviation features. To avoid the over fitting problem, genetic algorithm is employed to select the optimal features. Finally, the optimized attribute set are fed as input to the 2D-CNN learning engine for building the model. Empirical evidence or outcomes demonstrates that the proposed predictor achieved an overall accuracy and AUC (ROC) value using 10-fold cross validation test. Superior performance compared to other state-of-the art methods for discrimination the relations UPPs classification. Both on and independent test respectively was trained on 10-fold cross validation method and then evaluated through independent test. In the case where experimentally validated ubiquitination sites emerged, we must devise a proteomics-based predictor of ubiquitination. Meanwhile, we also evaluated the generalization power of our trained modal via independent test, and obtained remarkable performance in term of 0.862 accuracy, 0.921 sensitivity, 0.803 specificity 0.803, and 0.730 Matthews correlation coefficient (MCC) respectively. Four approaches were used in the sequences, and the physical properties were calculated combined. When used a 10-fold cross-validation, 2D-CNN-UPP obtained an AUC (ROC) value of 0.862 predicted score. We analyzed the relationship between UPP protein and non-UPP protein predicted score. Last but not least, this research could effectively analyze the large scale relationship between UPP proteins and non-UPP proteins in particular and other protein problems in general and our research work might improve computational biological research. Therefore, we could utilize the latest features in our model framework and Dipeptide Deviation from Expected Mean (DDE) -based protein structure features for the prediction of protein structure, functions, and different molecules, such as DNA and RNA