Outcome measures of disease activity in inflammatory arthritis

The most common types of chronic inflammatory arthritis are rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis. In order to assess the activity of these diseases and tailor therapy, several outcome measures have been developed. They include composite scores based on clinical findings, biochemical markers and patient questionnaires. This article discusses the most commonly used outcome measures and looks at their limitations in quantifying the complex clinical features of different types of inflammatory arthritis, focusing in particular on rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis

Climate, COVID-19 and conflict threaten health, food security and nutrition

September 2021 saw the United Nations Food Systems Summit (UNFSS) take place in New York. It focused on the “three Cs” that are driving disruption to food systems and threatening recent progress in mitigating hunger, malnutrition, and undernutrition: global environmental climate change, covid-19 disease, and conflict. Summit delegates from 183 countries agreed that business as usual would not lead to the change necessary to achieve the sustainable development goals. Summit participants called for urgent action at scale. The three Cs interact on five mediators (“five Fs”) upon which food systems depend: the geopolitics of our global food, fertilizer, finance, fodder, and fuel systems (fig 1). Our global food supply system is fragile and vulnerable to the impacts of each driver or mediator. However, all can interact to amplify the downstream effects on people, their health, and diets. For example, decreased food availability has financial impacts (and vice versa). In a vicious feedback loop, undernutrition affects the ability to produce food, and lack of food availability can lead to conflict (and vice versa), while environmental climate change can cause both. Key messages • Global environmental climate change can lead to challenges related to health, food security, and nutrition • Environmental climate change interacts with covid-19 and conflict, and drives food insecurity and malnutrition • Every public policy choice has opportunities, threats, and trade-offs that can affect health, food security, and nutrition for communities directly and indirectly through supply and market challenges, conflict, and geopolitic

Cleavage Requirements for Activation of Factor V by Factor Xa

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65728/1/j.1432-1033.1997.00012.x.pd

Screen for Genetic Modifiers of stbm Reveals that Photoreceptor Fate and Rotation Can Be Genetically Uncoupled in the Drosophila Eye

BACKGROUND: Polarity of the Drosophila compound eye arises primarily as a consequence of two events that are tightly linked in time and space: fate specification of two photoreceptor cells, R3 and R4, and the subsequent directional movement of the unit eyes of the compound eye, or ommatidia. While it is thought that these fates dictate the direction of ommatidial rotation, the phenotype of mutants in the genes that set up this polarity led to the hypothesis that these two events could be uncoupled. METHODOLOGY/PRINCIPAL FINDINGS: To definitively demonstrate these events are genetically separable, we conducted a dominant modifier screen to determine if genes, when misexpressed, could selectively enhance subclasses of mutant ommatidia in which the direction of rotation does not follow the R3/R4 cell fates, yet not affect the number of ommatidia in which rotation follows the R3/R4 cell fates. We identified a subset of P element lines that exhibit this selective enhancement. We also identified lines that behave in the opposite manner: They enhance the number of ommatidia that rotate in the right direction, but do not alter the number of ommatidia that rotate incorrectly with respect to the R3/R4 fates. CONCLUSIONS/SIGNIFICANCE: These results indicate that fate and direction of rotation can be genetically separated, and that there are genes that act between R3/R4 fate specification and direction of ommatidial rotation. These data affirm what has been a long-standing assumption about the genetic control of ommatidial polarity

The relationship between the time of cerebral desaturation episodes and outcome in aneurysmal subarachnoid haemorrhage: a preliminary study.

In this preliminary study we investigated the relationship between the time of cerebral desaturation episodes (CDEs), the severity of the haemorrhage, and the short-term outcome in patients with aneurysmal subarachnoid haemorrhage (aSAH). Thirty eight patents diagnosed with aneurysmal subarachnoid haemorrhage were analysed in this study. Regional cerebral oxygenation (rSO2) was assessed using near infrared spectroscopy (NIRS). A CDE was defined as rSO2 < 60% with a duration of at least 30 min. The severity of the aSAH was assessed using the Hunt and Hess scale and the short-term outcome was evaluated utilizing the Glasgow Outcome Scale. CDEs were found in 44% of the group. The total time of the CDEs and the time of the longest CDE on the contralateral side were longer in patients with severe versus moderate aSAH [h:min]: 8:15 (6:26-8:55) versus 1:24 (1:18-4:18), p = 0.038 and 2:05 (2:00-5:19) versus 0:48 (0:44-2:12), p = 0.038. The time of the longest CDE on the ipsilateral side was longer in patients with poor versus good short-term outcome [h:min]: 5:43 (3:05-9:36) versus 1:47 (0:42-2:10), p = 0.018. The logistic regression model for poor short-term outcome included median ABP, the extent of the haemorrhage in the Fisher scale and the time of the longest CDE. We have demonstrated that the time of a CDE is associated with the severity of haemorrhage and short-term outcome in aSAH patients. A NIRS measurement may provide valuable predictive information and could be considered as additional method of neuromonitoring of patients with aSAH

Water in Cavity−Ligand Recognition

We use explicit solvent molecular dynamics simulations to estimate free energy, enthalpy, and entropy changes along the cavity-ligand association coordinate for a set of seven model systems with varying physicochemical properties. Owing to the simplicity of the considered systems we can directly investigate the role of water thermodynamics in molecular recognition. A broad range of thermodynamic signatures is found in which water (rather than cavity or ligand) enthalpic or entropic contributions appear to drive cavity-ligand binding or rejection. The unprecedented, nanoscale picture of hydration thermodynamics can help the interpretation and design of protein-ligand binding experiments. Our study opens appealing perspectives to tackle the challenge of solvent entropy estimation in complex systems and for improving molecular simulation models

Cooperative Regulation of the Activity of Factor Xa within Prothrombinase by Discrete Amino Acid Regions from Factor Va Heavy Chain†

ABSTRACT: The prothrombinase complex catalyzes the activation of prothrombin to R-thrombin. We have repetitively shown that amino acid region 695DYDY698 from the COOH terminus of the heavy chain of factor Va regulates the rate of cleavage of prothrombin at Arg271 by prothrombinase. We have also recently demonstrated that amino acid region 334DY335 is required for the optimal activity of prothrombinase. To assess the effect of these six amino acid residues on cofactor activity, we created recombinant factor Va molecules combining mutations at amino acid regions 334–335 an

Staying active under restrictions: Changes in type of physical exercise during the initial COVID-19 lockdown

Copyright: © 2021 by the authors. The COVID-19 pandemic and the associated governmental restrictions suddenly changed everyday life and potentially affected exercise behavior. The aim of this study was to explore whether individuals changed their preference for certain types of physical exercise during the pandemic and to identify risk factors for inactivity. An international online survey with 13,881 adult participants from 18 countries/regions was conducted during the initial COVID-19 related lock-down (between April and May 2020). Data on types of exercise performed during and before the initial COVID-19 lockdown were collected, translated, and categorized (free-text input). Sankey charts were used to investigate these changes, and a mixed-effects logistic regression model was used to analyze risks for inactivity. Many participants managed to continue exercising but switched from playing games (e.g., football, tennis) to running, for example. In our sample, the most popular exercise types during the initial COVID-19 lockdown included endurance, muscular strength, and multimodal exercise. Regarding risk factors, higher education, living in rural areas, and physical activity before the COVID-19 lockdown reduced the risk for inactivity during the lockdown. In this relatively active multinational sample of adults, most participants were able to continue their preferred type of exercise despite restrictions, or changed to endurance type activities. Very few became physically inactive. It seems people can adapt quickly and that the constraints imposed by social distancing may even turn into an opportunity to start exercising for some. These findings may be helpful to identify individuals at risk and optimize interventions following a major context change that can disrupt the exercise routine

Abatacept in individuals at high risk of rheumatoid arthritis (APIPPRA): a randomised, double-blind, multicentre, parallel, placebo-controlled, phase 2b clinical trial

\ua9 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Background: Individuals with serum antibodies to citrullinated protein antigens (ACPA), rheumatoid factor, and symptoms, such as inflammatory joint pain, are at high risk of developing rheumatoid arthritis. In the arthritis prevention in the pre-clinical phase of rheumatoid arthritis with abatacept (APIPPRA) trial, we aimed to evaluate the feasibility, efficacy, and acceptability of treating high risk individuals with the T-cell co-stimulation modulator abatacept. Methods: The APIPPRA study was a randomised, double-blind, multicentre, parallel, placebo-controlled, phase 2b clinical trial done in 28 hospital-based early arthritis clinics in the UK and three in the Netherlands. Participants (aged ≥18 years) at risk of rheumatoid arthritis positive for ACPA and rheumatoid factor with inflammatory joint pain were recruited. Exclusion criteria included previous episodes of clinical synovitis and previous use of corticosteroids or disease-modifying antirheumatic drugs. Participants were randomly assigned (1:1) using a computer-generated permuted block randomisation (block sizes of 2 and 4) stratified by sex, smoking, and country, to 125 mg abatacept subcutaneous injections weekly or placebo for 12 months, and then followed up for 12 months. Masking was achieved by providing four kits (identical in appearance and packaging) with pre-filled syringes with coded labels of abatacept or placebo every 3 months. The primary endpoint was the time to development of clinical synovitis in three or more joints or rheumatoid arthritis according to American College of Rheumatology and European Alliance of Associations for Rheumatology 2010 criteria, whichever was met first. Synovitis was confirmed by ultrasonography. Follow-up was completed on Jan 13, 2021. All participants meeting the intention-to-treat principle were included in the analysis. This trial was registered with EudraCT (2013–003413–18). Findings: Between Dec 22, 2014, and Jan 14, 2019, 280 individuals were evaluated for eligibility and, of 213 participants, 110 were randomly assigned to abatacept and 103 to placebo. During the treatment period, seven (6%) of 110 participants in the abatacept group and 30 (29%) of 103 participants in the placebo group met the primary endpoint. At 24 months, 27 (25%) of 110 participants in the abatacept group had progressed to rheumatoid arthritis, compared with 38 (37%) of 103 in the placebo group. The estimated proportion of participants remaining arthritis-free at 12 months was 92\ub78% (SE 2\ub76) in the abatacept group and 69\ub72% (4\ub77) in the placebo group. Kaplan–Meier arthritis-free survival plots over 24 months favoured abatacept (log-rank test p=0\ub7044). The difference in restricted mean survival time between groups was 53 days (95% CI 28–78; p&lt;0\ub70001) at 12 months and 99 days (95% CI 38–161; p=0\ub70016) at 24 months in favour of abatacept. During treatment, abatacept was associated with improvements in pain scores, functional wellbeing, and quality-of-life measurements, as well as low scores of subclinical synovitis by ultrasonography, compared with placebo. However, the effects were not sustained at 24 months. Seven serious adverse events occurred in the abatacept group and 11 in the placebo group, including one death in each group deemed unrelated to treatment. Interpretation: Therapeutic intervention during the at-risk phase of rheumatoid arthritis is feasible, with acceptable safety profiles. T-cell co-stimulation modulation with abatacept for 12 months reduces progression to rheumatoid arthritis, with evidence of sustained efficacy beyond the treatment period, and with no new safety signals. Funding: Bristol Myers Squibb

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues