Different expression of [béta] subunits of the KCa1.1 channel by invasive and non-invasive human fibroblast-like synoviocytes

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Мультидисциплінарний підхід до хірургічного лікування феохромоцитоми наднирників

Мета. Оцінити результати застосування мультидисциплінарного підходу в лікуванні феохромоцитоми наднирників. Матеріали і методи. Для аналізу ефективності схеми періопераційного лікування проспективно та ретроспективно досліджено результати лапароскопічної адреналектомії (ЛА), виконаної з приводу феохромоцитоми у 31 хворого за період з 2015 по 2017 р. Пацієнтів розподілили на дві групи: 1-ша - 15 хворих, яким періопераційне лікування проводили із застосуванням мультидисциплінарного підходу, 2-га - 16 пацієнтів, яким виконали тільки ЛА. Аналізували середню тривалість оперативного втручання, середній об’єм інтраопераційної крововтрати, геодинамічні показники та ускладнення. Результати. Середній об’єм інтраопераційної крововтрати у 1-й групі становив (48,7 ± 9,1) мл, у 2-й - (231,3 ± 113,8) мл (р < 0,05), середній рівень метанефрину в сечі до адреналектомії - відповідно (290,9 ± 71,8) та (991,2 ± 703,0) мкг/добу (р < 0,05). Середня тривалість оперативного втручання у пацієнтів 1-ї групи становила (117,7 ± 52,1) хв і була несуттєво меншою порівняно з пацієнтами 2-ї групи - (164,7 ± 57,5) хв (р = 0,133). Гемодинамічну нестабільність спостерігали лише у 5 пацієнтів 2-ї групи. Середні строки лікування після операції пацієнтів 1-ї групи становили (5,9 ± 2,2) дня, 2-ї - (11,3 ± 5,4) дня (p < 0,05). Ускладнення виникли у 2 (12,5%) пацієнтів 2-ї групи. Ніхто із пацієнтів обох груп не помер. Висновки. У пацієнтів з феохромоцитомою наднирника періопераційне лікування із застосуванням мультидисциплінарного підходу є більш безпечним й ефективним та менш тривалим у порівнянні з виконанням тільки ЛА

Role of mitochondria-bound HK2 in rheumatoid arthritis fibroblast-like synoviocytes

BackgroundGlucose metabolism, specifically, hexokinase 2 (HK2), has a critical role in rheumatoid arthritis (RA) fibroblast-like synoviocyte (FLS) phenotype. HK2 localizes not only in the cytosol but also in the mitochondria, where it protects mitochondria against stress. We hypothesize that mitochondria-bound HK2 is a key regulator of RA FLS phenotype.MethodsHK2 localization was evaluated by confocal microscopy after FLS stimulation. RA FLSs were infected with Green fluorescent protein (GFP), full-length (FL)-HK2, or HK2 lacking its mitochondrial binding motif (HK2ΔN) expressing adenovirus (Ad). RA FLS was also incubated with methyl jasmonate (MJ; 2.5 mM), tofacitinib (1 µM), or methotrexate (1 µM). RA FLS was tested for migration and invasion and gene expression. Gene associations with HK2 expression were identified by examining single-cell RNA sequencing (scRNA-seq) data from murine models of arthritis. Mice were injected with K/BxN serum and given MJ. Ad-FLHK2 or Ad-HK2ΔN was injected into the knee of wild-type mice.ResultsCobalt chloride (CoCl2) and platelet-derived growth factor (PDGF) stimulation induced HK2 mitochondrial translocation. Overexpression of the HK2 mutant and MJ incubation reversed the invasive and migrative phenotype induced by FL-HK2 after PDGF stimulation, and MJ also decreased the expression of C-X-C Motif Chemokine Ligand 1 (CXCL1) and Collagen Type I Alpha 1 Chain (COL1A1). Of interest, tofacitinib but not methotrexate had an effect on HK2 dissociation from the mitochondria. In murine models, MJ treatment significantly decreased arthritis severity, whereas HK2FL was able to induce synovial hypertrophy as opposed to HK2ΔN.ConclusionOur results suggest that mitochondrial HK2 regulates the aggressive phenotype of RA FLS. New therapeutic approaches to dissociate HK2 from mitochondria offer a safer approach than global glycolysis inhibition

A Crowdsourcing Approach to Develop Machine Learning Models to Quantify Radiographic Joint Damage in Rheumatoid Arthritis

IMPORTANCE An automated, accurate method is needed for unbiased assessment quantifying accrual of joint space narrowing and erosions on radiographic images of the hands and wrists, and feet for clinical trials, monitoring of joint damage over time, assisting rheumatologists with treatment decisions. Such a method has the potential to be directly integrated into electronic health records.OBJECTIVES To design and implement an international crowdsourcing competition to catalyze the development of machine learning methods to quantify radiographic damage in rheumatoid arthritis (RA).DESIGN, SETTING, AND PARTICIPANTS This diagnostic/prognostic study describes the Rheumatoid Arthritis 2-Dialogue for Reverse Engineering Assessment and Methods (RA2-DREAM Challenge), which used existing radiographic images and expert-curated Sharp-van der Heijde (SvH) scores from 2 clinical studies (674 radiographic sets from 562 patients) for training (367 sets), leaderboard (119 sets), and final evaluation (188 sets). Challenge participants were tasked with developing methods to automatically quantify overall damage (subchallenge 1), joint space narrowing (subchallenge 2), and erosions (subchallenge 3). The challenge was finished on June 30, 2020.MAIN OUTCOMES AND MEASURES Scores derived from submitted algorithms were compared with the expert-curated SvH scores, and a baseline model was created for benchmark comparison. Performances were ranked using weighted root mean square error (RMSE). The performance and reproductivity of each algorithm was assessed using Bayes factor from bootstrapped data, and further evaluated with a postchallenge independent validation data set.RESULTS The RA2-DREAM Challenge received a total of 173 submissions from 26 participants or teams in 7 countries for the leaderboard round, and 13 submissions were included in the final evaluation. The weighted RMSEs metric showed that the winning algorithms produced scores that were very close to the expert-curated SvH scores. Top teams included Team Shirin for subchallenge 1 (weighted RMSE, 0.44), HYL-YFG (Hongyang Li and Yuanfang Guan) subchallenge 2 (weighted RMSE, 0.38), and Gold Therapy for subchallenge 3 (weighted RMSE, 0.43). Bootstrapping/Bayes factor approach and the postchallenge independent validation confirmed the reproducibility and the estimation concordance indices between final evaluation and postchallenge independent validation data set were 0.71 for subchallenge 1, 0.78 for subchallenge 2, and 0.82 for subchallenge 3.CONCLUSIONS AND RELEVANCE The RA2-DREAM Challenge resulted in the development of algorithms that provide feasible, quick, and accurate methods to quantify joint damage in RA. Ultimately, these methods could help research studies on RA joint damage and may be integrated into electronic health records to help clinicians serve patients better by providing timely, reliable, and quantitative information for making treatment decisions to prevent further damage

Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints

BACKGROUND: We are interested in the problem of predicting secondary structure for small sets of homologous RNAs, by incorporating limited comparative sequence information into an RNA folding model. The Sankoff algorithm for simultaneous RNA folding and alignment is a basis for approaches to this problem. There are two open problems in applying a Sankoff algorithm: development of a good unified scoring system for alignment and folding and development of practical heuristics for dealing with the computational complexity of the algorithm. RESULTS: We use probabilistic models (pair stochastic context-free grammars, pairSCFGs) as a unifying framework for scoring pairwise alignment and folding. A constrained version of the pairSCFG structural alignment algorithm was developed which assumes knowledge of a few confidently aligned positions (pins). These pins are selected based on the posterior probabilities of a probabilistic pairwise sequence alignment. CONCLUSION: Pairwise RNA structural alignment improves on structure prediction accuracy relative to single sequence folding. Constraining on alignment is a straightforward method of reducing the runtime and memory requirements of the algorithm. Five practical implementations of the pairwise Sankoff algorithm – this work (Consan), David Mathews' Dynalign, Ian Holmes' Stemloc, Ivo Hofacker's PMcomp, and Jan Gorodkin's FOLDALIGN – have comparable overall performance with different strengths and weaknesses

Six priorities to advance the science and practice of coral reef restoration worldwide

Coral reef restoration is a rapidly growing movement galvanized by the accelerating degradation of the world's tropical coral reefs. The need for concerted and collaborative action focused on the recovery of coral reef ecosystems coalesced in the creation of the Coral Restoration Consortium (CRC) in 2017. In March 2020, the CRC leadership team met for a biennial review of international coral reef restoration efforts and a discussion of perceived knowledge and implementation bottlenecks that may impair scalability and efficacy. Herein we present six priorities wherein the CRC will foster scientific advancement and collaboration to: (1) increase restoration efficiency, focusing on scale and cost-effectiveness of deployment; (2) scale up larval-based coral restoration efforts, emphasizing recruit health, growth, and survival; (3) ensure restoration of threatened coral species proceeds within a population-genetics management context; (4) support a holistic approach to coral reef ecosystem restoration; (5) develop and promote the use of standardized terms and metrics for coral reef restoration; and (6) support coral reef restoration practitioners working in diverse geographic locations. These priorities are not exhaustive nor do we imply that accomplishing these tasks alone will be sufficient to restore coral reefs globally; rather these are topics where we feel the CRC community of practice can make timely and significant contributions to facilitate the growth of coral reef restoration as a practical conservation strategy. The goal for these collective actions is to provide tangible, local-scale advancements in reef condition that offset declines resulting from local and global stressors including climate change

Financialization in Commodity Markets: Disentangling the Crisis from the Style Effect

In this paper, we show that large inflows into commodity investments, a recent phenomenon known as financialization, has changed the behavior and dependence structure between commodities and the general stock market. The common perception is that the increase in comovements is the result of distressed investors selling both assets during the 2007-2009 financial crisis. We show that financial distress alone cannot explain the size and persistence of comovements. Instead, we argue that commodities have become an investment style for institutional investors. Given that institutional investors continue to target funds into commodities, we predict spillovers between commodities and the stock market to remain high in the future

Incorporating phylogenetic-based covarying mutations into RNAalifold for RNA consensus structure prediction

BACKGROUND: RNAalifold, a popular computational method for RNA consensus structure prediction, incorporates covarying mutations into a thermodynamic model to fold the aligned RNA sequences. When quantifying covariance, it evaluates conserved signals of two aligned columns with base-pairing rules. This scoring scheme performs better than some other approaches, such as mutual information. However it ignores the phylogenetic history of the aligned sequences, which is an important criterion to evaluate the level of sequence covariance. RESULTS: In this article, in order to improve the accuracy of consensus structure folding, we propose a novel approach named PhyloRNAalifold. It incorporates the number of covarying mutations on the phylogenetic tree of the aligned sequences into the covariance scoring of RNAalifold. The benchmarking results show that the new scoring scheme of PhyloRNAalifold can improve the consensus structure detection of RNAalifold. CONCLUSION: Incorporating additional phylogenetic information of aligned sequences into the covariance scoring of RNAalifold can improve its performance of consensus structures folding. This improvement is correlated with alignment characteristics, such as pair-wise identity and the number of sequences in the alignment