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Top-down approaches often fail to involve, collaborate with, and consider social actors in the process of planning, design, and maintenance of public spaces (PDMPS). This research addresses how social participation is included in PDMPS in the Mexican case, by identifying the actors, the level of communication achieved, and their authority and power in the PDMPS process. The paper employs a case study approach, informed by semi-structured interviews. We use a democracy diagram to uncover the diversity of involved actors and how they are involved in the process. We show how government could provide support for social participation to implement participatory processes in PDMPS. [ABSTRACT FROM AUTHOR]

Background: Rheumatoid arthritis (RA) in elderly population represents a challenge for physicians in terms of therapeutic management. Methotrexate (MTX) is the first-line treatment among conventional synthetic-disease-modifying anti-rheumatic drugs (cs-DMARDs); however, it is often associated with adverse events (AEs). Therefore, the objective of this study was to identify the incidence and risk factors of MTX discontinuation due to AEs in elderly patients with RA in a long-term retrospective cohort study. Methods: Clinical sheets from elderly RA patients taking MTX from an outpatient rheumatology consult in a university centre were reviewed. To assess MTX persistence, we used Kaplan–Meir curves and Cox regression models to identify the risk of withdrawing MTX due to adverse events. Results: In total, 198 elderly RA patients who reported using MTX were included. Of them, the rates of definitive suspension of MTX due to AEs were 23.0% at 5 years, 35.6% at 10 years and 51.7% at 15 years. The main organs and system involved were gastrointestinal (15.7%) and mucocutaneous (3.0%). Factors associated with withdrawing MTX due to AEs were MTX dose ≥ 15 mg/wk (adjusted HR: 2.46, 95% CI: 1.22–4.96, p = 0.012); instead, the folic acid supplementation was protective for withdrawal (adjusted HR: 0.28, 95% CI: 0.16–0.49, p < 0.001). Conclusions: Higher doses of MTX increase the risk of withdrawals in elderly RA, while folic acid supplementation reduces the risk. Therefore, physicians working in therapeutic management for elderly patients using MTX must focus on using lower MTX doses together with the concomitant prescription of folic acid. [ABSTRACT FROM AUTHOR]

Background and Objectives: According to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3), sepsis is defined as "life-threatening organ dysfunction caused by a dysregulated host response to infection". The increased presence of free radicals causes an increase in oxidative stress. Vitamin C is an essential water-soluble vitamin with antioxidant activity and immunoregulatory effects that plays a potential role in the treatment of bacterial infections. Our aim was to evaluate the effectiveness of adding vitamin C to the conventional treatment of sepsis to decrease its mortality rate. Materials and Methods: In a prospective cohort study, we included patients with a diagnosis of sepsis and a SOFA score ≥ 9 who were evaluated in an Intensive Care Unit at a secondary-care hospital. According to the intensive care specialist, they were treated using two different strategies: Group 1—patients with sepsis treated with conventional treatment without vitamin C; Group 2—patients with sepsis with the addition of vitamin C to conventional treatment. Results: We included 34 patients with sepsis. The incidence of mortality was 38%, and 47% of patients used vitamin C as an adjuvant to the basic treatment of sepsis. In the basal analyses, patients treated with use of vitamin C compared to patients treated without vitamin C required less use of glucocorticoids (75% vs. 100%, p = 0.039). At follow-up, patients treated without vitamin C had higher mortality than patients treated with vitamin C as an adjuvant for the treatment of sepsis (55.6% vs. 18.8%, p = 0.03). We observed that the use of vitamin C was a protective factor for mortality in patients with sepsis (RR: 0.54, 95% CI: 0.31–0.96, p = 0.03). Conclusions: The use of vitamin C as an adjuvant to treatment decreases the risk of mortality by 46% in patients with sepsis and SOFA ≥ 9 compared to patients treated without vitamin C as an adjuvant to sepsis. [ABSTRACT FROM AUTHOR]

The use of complementary therapies is highly prevalent among patients with rheumatoid arthritis (RA). Nevertheless, the use of complementary medicine could involve problems in the following of scientifically accepted treatments. To date, there is limited information regarding the association of nonconventional therapies with problems regarding compliance with the treatment. Therefore, the objective of this study was to identify whether the utilization of complementary therapies is associated with a high risk of problems regarding therapeutic adherence to conventional synthetic disease-modifying anti-rheumatic drugs (cs-DMARDs) in RA patients. A survey was performed with RA patients in an outpatient rheumatology clinic in a university hospital; the use of complementary therapies, as well as their type, was identified. To assess problems with therapeutic adherence, we used the four-item Morisky–Green scale. A comprehensive assessment of clinical and therapeutic characteristics was performed. Univariable and multivariable models were performed to identify the risk of problems with therapeutic adherence in users of complementary therapies. In total, 250 RA patients were included; 92% used complementary therapies. Of them, the most frequently used were herbal medicine (65%), homeopathy (64%), and cannabis and its derivatives (51%). In the univariable logistic regression analysis, the factors associated with problems in the therapeutic adherence to cs-DMARDs were age (p = 0.019), the presence of other comorbidities (p = 0.047), and the use of complementary therapies (p = 0.042). After controlling for potential confounders, the use of complementary therapies increased the risk of problems with therapeutic adherence to cs-DMARDs (adjusted OR = 2.84, 95% CI = 1.06–7.63, p = 0.037). We concluded that the use of complementary therapies increases the risk of problems with therapeutic adherence. Therefore, for physicians and healthcare professionals, the early identification of the use of nonconventional therapies in their RA patients is required, followed by a directed discussion with their patients about the risks and benefits to which they could be exposed to complementary therapies. [ABSTRACT FROM AUTHOR]

Rationale: Pregnant women are especially vulnerable to mental health problems, including stress, anxiety, and depression. This risk has been increased during the COVID-19 pandemic and differences in psychological symptoms in pregnancy and postpartum before and during COVID-19 exists. Mental health problems can have adverse effects on both the woman, and the neonate, including miscarriages, premature births, low birth weight, and higher rates of cesarean sections and instrument-assisted deliveries. Aim: To evaluate the prevalence of psychological symptoms of pregnant women before and during the COVID-19 pandemic. Method: A cross-sectional study was carried out to assess the psychological profile in a sample of pregnant women selected before the pandemic and a sample of women studied during the first wave of the pandemic. A total of 122 women were selected prior to the pandemic and 181 women during the COVID-19 outbreak. The Symptom Checklist-90 Revised (SCL-90-R) was used to assess depression and anxiety during pregnancy and in the postpartum period. Results: The prevalence of symptoms of depression and anxiety during pregnancy were higher in the sample of women studied during the pandemic (SCL-90-R: M = 54.6 vs. 42.6 and M = 62.6 vs. 51.7 respectively). In the postpartum the difference between both samples of women was even higher for depression and anxiety (SCL-90-R: M = 50.4 vs. 35.0 and M = 51.3 vs. 36.0 respectively). Being a pregnant woman at the COVID-19 outbreak was directly associated with a higher score of depression symptoms (aOR = 8.67, 95% CI [3.26, 23.02], p <.001). Anxiety during childbirth was more frequently reported by women before the pandemic (aOR = 5.13, 95% CI [2.53, 10.44], p <.001). The variable stage (before /during pandemic) was also associated with having a clinical SCL-90-R score above 70 (aOR = 7.61, 95% CI [2.7, 21.47], p <.001). Conclusion: During the pandemic, pregnancy and postpartum were associated with the presence of anxiety and depression. The main factor associated with postpartum depression was maternal age. These finding highlights the vulnerability of pregnant in front of the pandemic, in which psychological health and mental well-being are affected, not only during pregnancy, but also in the postpartum. [ABSTRACT FROM AUTHOR]

Recent research indicates that information and communication technologies (ICTs) can support social participation in the planning, design and maintenance of public spaces (PDMPS), specifically to create comprehensive knowledge among different stakeholders. However, critics point out that the use of ICTs by planners and decision-makers often ignores the needs of local residents. For this research, we inquired how ICTs can support social participation in PDMPS. Our case study combines a literature review and 21 semi-structured interviews with government officials, non-governmental organisations, academics and architecture/urban planning consultancy companies in Mexico to understand how different stakeholders use ICTs to improve the quality of public spaces. We developed an approach that facilitates the analysis of ICT aspects related to hardware and software supporting social participation in PDMPS. The findings show that Mexico has a base of digital tools requiring technical capacities and spatial literacy at various stages of PDMPS, and ICTs are seen as an opportunity to engage with residents. However, in practice, our interviewees mentioned that ICTs are rarely implemented to support participatory processes due to high costs, a lack of political support and the insufficient technical expertise of technical staff to engage with residents using ICTs. The paper closes with recommendations and suggestions for future research on how ICTs can better support participatory processes in PDMPS. [ABSTRACT FROM AUTHOR]

Low-speed drive is one of the challenges for modular multilevel converters (MMCs) due to large capacitor voltage fluctuation. In this article, a cascaded MMC and cycloconverter (CCV) based machine drive system is proposed to ensure stable operation of medium-voltage and low-speed machine. The MMC provides medium-frequency ac voltage for the CCV, and the CCV converts the medium-frequency ac input to low-frequency ac output required by the machine. Detailed analysis about MMC's operation frequency, device current stress, and submodule (SM) capacitance are given in this article. Proposed drive system can operate at zero/low frequency under rated load torque, while the SM capacitance is much smaller than that in existing methods. Simulation and experimental studies are conducted, and the results verify the effectiveness of the proposed system. [ABSTRACT FROM AUTHOR]

In this article, a low computational burden model predictive control (MPC) strategy without weighting factor is proposed for the single-phase cascaded H-bridge CHB converters. To reduce the switching state candidates, a hierarchy control algorithm is proposed. The grid current is controlled by selecting a subregion from the designed 2-D control plane, instead of the entire area. Two vectors are chosen in one sampling period for more accurate tracking. Then, the voltage balancing is achieved by selecting the optimal switching state from the subregion candidates to form the above two vectors. The cost function can be constructed of one variable: load voltage. Therefore, the weighting factor can be eliminated. No tuning or retuning processes are required in the proposed method. To reduce the computational time further, the principle of eliminating the switching state candidates operating the same voltage balancing performance is proposed. Conventional and proposed MPC methods are verified by experimental tests via a laboratory setup of a three-cell connected CHB converter. Steady-state and transient operations demonstrate that the proposed method guarantees less distortion grid current and shorter execution time (reduced from 15 to 3 $\mu s$). Fast response speed to variations in voltage reference and load resistance can be achieved t. [ABSTRACT FROM AUTHOR]

Nowadays the European Universities are worried about how to adapt higher education to the new European Higher Education Area, as proposed in the Bologna Magna Charta Universitatum of 1998, and signed by 32 European Education Ministers. One of the key points in this higher education reform was the introduction of new Master's level curricula. These Masters will look for the professional specialization and they will have to be adapted to the specific skills demanded by the society. This paper presents the results from a cooperation project--funded by the AECI (International Cooperation Spanish Agency) and developed between the University of Seville (Spain) and the Catholic University of Asuncion (Paraguay)--by about the planning of a new master's level curriculum in digital signal processing (DSP) area, taking into account the Bologna principles and the conclusions obtained by the Career Space Consortium. A scientific method from social science, known as concept mapping techniques, was used to perform this planning. Basically, the idea of concept mapping consists of compiling the opinion from actors belonging to different environments (lecturers, researchers, workers, businessmen, etc.) related to DSP applications. The compiled data were statistically computed to cluster the opinions of the different agents. The result will be a master's level curricula adapted to the environment requirements and the social settings.

The coronavirus SARS-CoV-2 generated an alert that became a state of emergency in health issues worldwide, a situation that affected the entire population, including pregnant women. The present study aims to understand the effect of the psychopathological profile of a sample of pregnant women at the time of the COVID-19 pandemic on themselves during childbirth (Phase 1) and after childbirth and the anthropometric measures of the neonate at birth (Phase 2). The total sample comprises 81 pregnant women aged 32.07 years (SD = 5.45) and their neonates. Sociodemographic and obstetric data of the sample were collected. During pregnancy, psychopathology was measured by means of the SCL-90, as well as other psychological measures on stress and social support. Cluster k-means techniques were used to uncover the heterogeneous profiles of psychopathology in Phase 1. Two main psychopathological profiles were found (Cluster 1: High psychopathological symptoms; Cluster 2: Low psychopathological symptoms). The clusters generated show significant differences in all the SCL-90-R subscales used and in the general index at Phase 1. After childbirth, high psychopathology profile membership was associated with a greater probability of having a non-eutocic delivery. On the other hand, the low psychopathological symptoms cluster shows higher levels of depressive symptoms, hostility, paranoid ideation, and psychotic symptoms in Phase 2. In conclusion, there seemed to exist two heterogeneous profiles of psychopathology in pregnant women during the pandemic; the stress related to the pandemic seemed uninfluential on the development of a profile of high psychopathological symptoms and the psychopathology profile may influence delivery and postpartum outcomes. [ABSTRACT FROM AUTHOR]

Promoting neglected and underutilized crop species is a possible solution to deal with the complex challenges of global food security. Chayote is a Neglected and Underutilized Cucurbit Species (NUCuS), which is recognized as a fruit vegetable in Latin America and is widely grown in Asia and Africa. However, basic biological knowledge about the crop is insufficient in scientific sources, especially outside of its center of origin. In this study, limited observations on reproductive characters were conducted, differentiating accessions from Mexico, Japan, and Myanmar. Cytological evaluation among Mexican and Japanese accessions showed that the relative nuclear DNA content is 1.55 ± 0.05 pg, the estimated genome size is 1511 at 2C/Mbp, and the observed mitotic chromosomal number is 2n = 28. The genetic diversity of 21 chayote accessions was also examined using six microsatellite markers. A global low genetic heterozygosity (Ho = 0.286 and He = 0.408) and three genetic groups were detected. The results established the basis to provide insights into chayote arrival history in Asia by looking at the crop's reproductive morphology, cytology, and genetic diversity status outside its origin center. This could help in developing sustainable utilization and conservation programs for chayote. [ABSTRACT FROM AUTHOR]

This article proposes a novel application method, inverse application of artificial intelligence (IAAI) for the control of power electronic converter systems. The proposed method can give the desired control coefficients/references in a simple way because, compared to conventional methods, IAAI only relies on a data-driven process with no need for an optimization process or substantial derivations. Noting that the IAAI approach uses artificial intelligence to provide feasible coefficients/references for the power converter control, rather than building a new controller. After illustrating the IAAI concept, a conventional application method of artificial neural network is discussed, an optimization-based design. Then, a two-source-converter microgrid case is studied to choose the best droop coefficients via the optimization-based approach. After that, the proposed IAAI method is employed for the same microgrid case to quickly find good droop coefficients. Furthermore, the IAAI method is applied to a modular multilevel converter (MMC) case, extending the MMC operation region under unbalanced grid faults. In the MMC case, both simulation and experimental online tests validate the operation, feasibility, and practicality of IAAI. [ABSTRACT FROM AUTHOR]

Introduction: Metabolic syndrome (MS) is associated with abnormalities in atrial mechanics, atrial remodeling, and an increased risk of heart rhythm disorders. One of the most commonly used approaches to the prevention of cardiac remodeling in arterial hypertension is the administration of renin--angiotensin system (RAS) inhibitors. Therefore, this study aimed to investigate the effects of RAS inhibitors on atrial mechanics parameters in patients with MS. Methods and materials: This longitudinal observational study included 55 patients with hypertension and MS, as defined by the ATP III criteria. The patients were evaluated at the start of antihypertensive treatment with an RAS inhibitor. The patients' clinical characteristics, chosen pharmacological treatment, and transthoracic echocardiography findings were recorded at baseline and 6 months thereafter. A student's dependent sample t-test was used for comparisons between groups. Pearson correlation was used to evaluate the relationships between variables. Results: Patients with MS had higher peak atrial longitudinal strain (PALS) values at 6 months than at baseline. Meanwhile, systolic strain and peak late strain rates were lower at follow-up than at baseline. The different antihypertensive treatments had comparable effects on the PALS changes during the follow-up period. Higher high-density lipoprotein levels at baseline were correlated with changes in PALS. Conclusion: The administration of RAS inhibitors improved atrial mechanics parameters in the early stages of antihypertensive management in MS. [ABSTRACT FROM AUTHOR]

In this article a finite control set model predictive control, is used to track a current reference in a power converter connected to an $RL$ load. An artificial intelligence approach is presented for real-time determination of the weighting factor that regulates the average switching frequency, independently of the operating point. The article focuses on the design, training, and digital implementation of an artificial neural network (ANN) that can be developed in a low-cost control platform. It is presented a sampling and offline ANN training procedure, together with a low-cost hardware implementation based on integer quantization of the ANN. The abovementioned approach provides a standalone application, serving as a framework for the development of ANN applications for power-converters. The main advantage of the presented approach is that the ANN inference is executed in real time. In this way, the weighting factor is automatically updated in real-time, allowing the system to quickly adapt to any reference step changes, and consequently provide the desired behavior. Executing the setup in laboratory prototype confirmed the theoretical analysis and successful tracking of the reference frequency. [ABSTRACT FROM AUTHOR]

Due to the high-performance requirements of power converters in industrial applications, sliding-mode control has drawn extensive research attention for its insensitivity against external disturbances. In order to ensure this advantage while suppressing the chattering problem caused by discontinuous switching functions, in this article, a fuzzy sliding-mode control (FSMC) strategy consisting of three control loops is proposed for three-phase three-level neutral-point-clamped active front-end rectifiers. In the power tracking loop, an improved super-twisting algorithm is proposed to enforce the tracking errors of active power and reactive power to bounded regions in finite time and guarantee the transient performance. Next, in the dc-link voltage regulation loop, the regulation error of dc-link voltage converges to a bounded region with a super-twisting extended state observer-based FSMC strategy. A simple but efficient proportional-integral controller is employed in dc-link voltage balancing loop to reduce the voltage difference between two dc-link capacitors. The proposed controller is characterized by attenuated chattering phenomenon and improved the dc-link voltage regulation performance, disturbance rejection ability, and power tracking performance. Experimental results are provided to verify the effectiveness and superiority of the proposed strategy. [ABSTRACT FROM AUTHOR]

Background Improving the identification of people who inject drugs (PWID) in electronic medical records can improve clinical decision making, risk assessment and mitigation, and health service research. Identification of PWID currently consists of heterogeneous, nonspecific International Classification of Diseases (ICD) codes as proxies. Natural language processing (NLP) and machine learning (ML) methods may have better diagnostic metrics than nonspecific ICD codes for identifying PWID. Methods We manually reviewed 1000 records of patients diagnosed with Staphylococcus aureus bacteremia admitted to Veterans Health Administration hospitals from 2003 through 2014. The manual review was the reference standard. We developed and trained NLP/ML algorithms with and without regular expression filters for negation (NegEx) and compared these with 11 proxy combinations of ICD codes to identify PWID. Data were split 70% for training and 30% for testing. We calculated diagnostic metrics and estimated 95% confidence intervals (CIs) by bootstrapping the hold-out test set. Best models were determined by best F-score, a summary of sensitivity and positive predictive value. Results Random forest with and without NegEx were the best-performing NLP/ML algorithms in the training set. Random forest with NegEx outperformed all ICD -based algorithms. F-score for the best NLP/ML algorithm was 0.905 (95% CI,.786–.967) and 0.592 (95% CI,.550–.632) for the best ICD -based algorithm. The NLP/ML algorithm had a sensitivity of 92.6% and specificity of 95.4%. Conclusions NLP/ML outperformed ICD -based coding algorithms at identifying PWID in electronic health records. NLP/ML models should be considered in identifying cohorts of PWID to improve clinical decision making, health services research, and administrative surveillance. [ABSTRACT FROM AUTHOR]

Finite control set model predictive control (FCS-MPC) strategies for power conversion devices benefit from extending the prediction horizon length. Solving this problem relies on the definition of the underlying integer least-squares problem. Sphere decoding algorithm (SDA) has been extensively used in previous works as an approach to solve this problem. In this article, a parallel and fully scalable K-best SDA hardware design is proposed as an alternative. The K-best SDA establishes a different breadth-first search strategy, which addresses some of the main drawbacks of the SDA. Through experimental tests based on an uninterruptible power supply, the K-best SDA performance for long prediction horizon FCS-MPC is assessed and verified. Results demonstrate key beneficial aspects through which the K-best SDA is capable of rendering an improved control performance when compared to the conventional SDA. [ABSTRACT FROM AUTHOR]

Recently, a multilevel cascaded converter fed with a single dc source has been presented. An analysis of the steady-state working limits of this type of converter is presented in this paper. Limits of the maximum output voltage and the minimum and maximum loading conditions for stable operation of the converter are addressed. In this paper, a way to achieve any dc voltage ratio (inside the stable operation area of the converter) between the H-bridges of the single-dc-source cascaded H-bridge converter is presented. The proposed dc-voltage-ratio control is based on a time-domain modulation strategy that avoids the use of inappropriate states to achieve the dc-voltage-ratio control. The proposed technique is a feedforward-modulation technique which takes into account the actual dc voltage of each H-bridge of the converter, leading to output waveforms with low distortion. In this way, the dc voltage of the floating H-bridge can be controlled while the output voltage has low distortion independently of the desired dc voltage ratio. Experimental results from a two-cell cascaded converter are presented in order to validate the proposed dc-voltage-ratio control strategy and the introduced concepts. Index Terms--Modulation, multilevel systems, voltage control.

The use of an inverter with an output LC filter allows for generation of output sinusoidal voltages with low harmonic distortion, suitable for uninterruptible power supply systems. However, the controller design becomes more difficult. This paper presents a new and simple control scheme using predictive control for a two-level converter. The controller uses the model of the system to predict, on each sampling interval, the behavior of the output voltage for each possible switching state. Then, a cost function is used as a criterion for selecting the switching state that will be applied during the next sampling interval. In addition, an observer is used for load-current estimation, enhancing the behavior of the proposed controller without increasing the number of current sensors. Experimental results under linear and nonlinear load conditions, with a 5.5-kW prototype, are presented, verifying the feasibility and good performance of the proposed control scheme. Index Terms--Power conversion, predictive control, uninterruptible power systems.

Modulation techniques for multilevel converters can create distorted output voltages and currents if the dc-link voltages are unbalanced. This situation can be avoided if the instantaneous dc voltage error is not taken into account in the modulation process. This paper proposes a feed-forward space vector modulation method for a single-phase multilevel cascade converter. Using this modulation technique, the modulated output voltage of the power converter always generates the reference determined by the controller, even in worst case voltage unbalance conditions. In addition, the possibility of optimizing the dc voltage ratio between the H-bridges of the power converter is introduced. Experimental results from a 5-kVA prototype are presented in order to validate the proposed modulation technique. Index Terms--Modulation, multilevel systems, voltage control.

Simplified space vector modulation (SVM) techniques for multilevel converters are being developed to improve factors such as the computational cost, number of commutations, and voltage distortion. The feedforward SVM presented in this paper takes into account the actual dc capacitor voltage unbalance of the multilevel power converter. The resulting technique is a low-cost generalized feedforward 3-D SVM method and is particularized for three-phase multilevel diode-clamped converters. This new modulation technique can be applied to topologies where the gamma component may not be zero. The computational cost of the proposed method is similar to those of comparable methods, and it is independent of the number of levels of the power converter. Experimental results using a three-level diode-clamped converter are presented to validate the proposed modulation technique. Index Terms--Modulation, multilevel systems, voltage control.

Background: Myostatin is a regulator of muscle size. To date, there have been no published studies focusing on the relation between myostin levels and myopenia in rheumatoid arthritis (RA).Objective: Evaluate the value of serum myostatin as a biomarker of cachexia and low skeletal muscle mass (LSMM) in RA patients, along with whether high serum myostatin is associated to these conditions after adjusting for potential confounders.Methods: This cross-sectional study included 161 female RA patients and 72 female controls. In the RA group, we assessed several potential risk factors for LSMM and rheumatoid cachexia. Dual-energy X-ray absorptiometry was used to quantify the skeletal muscle mass index (SMMI) (considering LSMM ≤ 5.5 kg/m2) and the presence of rheumatoid cachexia (a fat-free mass index ≤ 10 percentile and fat mass index ≥ 25 percentile of the reference population). Serum myostatin concentrations were determined by ELISA. To identify a cut-off for high serum myostatin levels, we performed ROC curve analysis. Multivariable logistic regression analysis was used to identify the risk factors for LSMM and rheumatoid cachexia. The risk was expressed as odds ratios (ORs) and their 95% confidence intervals (95% CIs).Results: Compared to the controls, the RA group had a higher proportion of LSMM and exhibited high serum myostatin levels (p < 0.001). ROC curve analysis showed that a myostatin level ≥ 17 ng/mL was the most efficient cut-off for identifying rheumatoid cachexia (sensitivity: 53%, specificity: 71%) and LSMM (sensitivity: 43%, specificity: 77%). In the multivariable logistic regression, RA with high myostatin levels (≥17 ng/mL) was found to increase the risk of cachexia (OR = 2.79, 95% CI: 1.24-6.29; p = 0.01) and LSMM (OR = 3.04, 95% CI: 1.17-7.89; p = 0.02).Conclusions: High serum myostatin levels increase the risk of LSMM and rheumatoid cachexia. We propose that high myostatin levels are useful biomarkers for the identification of patients in risk of rheumatoid cachexia and myopenia. [ABSTRACT FROM AUTHOR]

This work compares the performance of fixed and fluidized bed reactors in the SR of raw bio-oil with a NiAl2O4 spinel derived catalyst, which has high activity and selectivity of H2 in the raw bio-oil reforming. The SR runs have been carried out at 600 °C, steam/carbon molar ratio (S/C) of 3 and space time of 0.15 gcatalysth/gbio-oil. The results of the fluidized bed reactor evidences lower initial bio-oil conversion and H2 and CO2 yields, due to the less effective gas-solid contact, however its stability is higher. The characterization of deactivated catalysts by Temperature Programed Reduction (TPR), X-Ray Diffraction (XRD), N2 adsorption-desorption and Temperature Programed Oxidation (TPO) evidences that the main deactivation cause is coke deposition, that is noticeably higher in the fixed bed reactor (73 wt%) than in the fluidized bed (17 wt%). The TPO profiles for catalysts used in both reactors show two combustion domains, at low and high temperature. The reactor type does not affect the amount of coke that burns below 500 °C (coke I, amorphous), but notably affects both the amount and morphology of the coke burning at higher temperature (coke II, more graphitic). The use of fixed bed reactor leads to a noticeable higher formation of coke II, which contains heterogeneous carbon filaments and also carbon spheres, the latter not being formed in the fluidized bed. These differences in the amount and nature of the coke deposited explain the differences in stability of the catalyst in both reactors. [ABSTRACT FROM AUTHOR]