The potential role of fatigue in difficult-to-treat rheumatoid arthritis.

OBJECTIVES: A subset of patients with rheumatoid arthritis (RA) who remains symptomatic after failing to multiple drugs are deemed to have "difficult-to-treat RA" (D2T RA). Fatigue is a burdensome symptom for RA patients, hindering their improvement. Our purpose was to evaluate the role of fatigue in D2T RA. METHODS: This cross-sectional study included rheumatoid arthritis (RA) patients between 2018 and 2022, treated with biological agents or targeted synthetic disease-modifying antirheumatic drugs. D2T RA was defined attending EULAR criteria. Independent variable was fatigue (dimensions and impact) assessed by the Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire and Numerical Rating Scales. Covariables: sociodemographic, clinical and treatment. To identify factors independently associated to D2T RA, multivariable logistic regression was run. RESULTS: The study included 145 patients and 38 (26.21%) developed D2T RA. D2T RA group were older, with more comorbidity and disability. D2T RA patients scored higher for global fatigue (p = 0.003), and almost for all their dimensions except for cognitive fatigue (p = 0.06) and fatigue coping (p = 0.07). Females with D2T RA showed more fatigue than those with non-D2T RA. In the adjusted models, all fatigue dimensions were associated with D2T RA: global fatigue RA (OR: 1.03; p = 0.007), physical (OR: 1.09; p = 0.008), living (OR: 1.09; p = 0.016), cognitive (OR: 1.1; p = 0.046) and emotional (OR: 1.18; p = 0.012). CONCLUSIONS: Despite the absence of an explicit mention of fatigue in the definition of D2T RA, it appears to be associated to this outcome. Fatigue should be evaluated in a multidimensional perspective, and gender-specific differences should be considered.

Sitetack: A deep learning model that improves PTM prediction by using known PTMs.

MOTIVATION: Post-translational modifications (PTMs) increase the diversity of the proteome and are vital to organismal life and therapeutic strategies. Deep learning has been used to predict PTM locations. Still, limitations in datasets and their analyses compromise success. RESULTS: We evaluated the use of known PTM sites in prediction via sequence-based deep learning algorithms. For each PTM, known locations of that PTM were encoded as a separate amino acid before sequences were encoded via word embedding and passed into a convolutional neural network that predicts the probability of that PTM at a given site. Without labeling known PTMs, our models are on par with others. With labeling, however, we improved significantly upon extant models. Moreover, knowing PTM locations can increase the predictability of a different PTM. Our findings highlight the importance of PTMs for the installation of additional PTMs. We anticipate that including known PTM locations will enhance the performance of other proteomic machine learning algorithms. AVAILABILITY AND IMPLEMENTATION: Sitetack is available as a web tool at https://sitetack.net; the source code, representative datasets, instructions for local use, and select models are available at https://github.com/clair-gutierrez/sitetack. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Osteochondral Tissue-On-a-Chip: A Novel Model for Osteoarthritis Research.

The existing in vitro and in vivo models for studying osteoarthritis have significant limitations in replicating the complexity of joint tissues. This research aims to validate a Tissue-On-a-Chip system for osteoarthritis research. Osteochondral tissues obtained from knee replacement surgeries of patients with osteoarthritis were cultured in an Organ-On-a-Chip system. This system was designed to supply oxygen and glucose to the cartilage from the bone. The distribution of oxygen and glucose was evaluated by fluorescence using Image-iT Green Hypoxia and 2-NBDG, respectively. Cytotoxicity was measured using lactate dehydrogenase (LDH) levels in chip cultures compared to plate cultures (12 tissues per method). Glycosaminoglycans (GAGs), alkaline phosphatase (ALP), Coll2-1, and procollagen type II N-terminal propeptide (PIINP) were measured in the perfused medium of the Tissue-On-a-Chip over a period of 70 days. Fluorescence of Image-iT Green Hypoxia was observed only in the cartilage area, while 2-NBDG was distributed throughout the tissue. An increase in LDH levels was noted in the plate cultures on day 24 and in the Tissue-On-a-Chip cultures on day 63. Compared to the start of the culture, GAG content increased on day 52, while ALP showed variations. A notable increase in GAG, ALP, and Coll2-1 levels was observed on day 59. PIINP levels remained stable throughout the experiment. The validated osteochondral Tissue-On-a-Chip system can replicate the joint microenvironment, with hypoxic conditions in cartilage and normoxic conditions in bone. Tissue survival and component stability were maintained for approximately two months. This platform is a useful tool for evaluating new drugs and represents a viable alternative to animal models.

Switching related to inefficacy in biologics and targeted synthetic therapies for psoriatic arthritis: a comparative real-life study.

Background: Switching between therapies is a recommended strategy for psoriatic arthritis (PsA) patients who experience treatment failure; however, studies including real-life data are scarce. Objectives: To assess the incidence rate (IR) of switching between biologics and targeted synthetic disease-modifying anti-rheumatic drugs (b/tsDMARDs) due to inefficacy in PsA, and to compare the risk of switching due to inefficacy across different b/tsDMARDs groups. Design: A longitudinal retrospective study, spanning from 2007 to 2022, was conducted on patients with PsA treated with b/tsDMARDs at an outpatient rheumatology clinic. Methods: The primary outcome was switching between b/tsDMARDs due to inefficacy. The independent variable was the exposure to b/tsDMARDs during follow-up. As covariates, clinical, treatment-related, and sociodemographic variables were considered. Survival techniques were run to estimate the IR of switching due to inefficacy per 100 patients*year and confidence interval at 95% (95% CI). Cox multivariate regression analyses were run to assess the risk of b/tsDMARDs switching due to inefficacy, expressed as hazard ratio (HR) and 95% CI. Results: In all, 141 patients were included, with 893.09 patients*year follow-ups. 52.48% of them were females in their fifties. In total, 262 courses of treatment were recorded. During the study period, 56 patients presented 121 switches and 103 related to inefficacy (IR: 11.53 (9.51-13.98)). Tumor necrosis factor-alpha inhibitors (TNFi) showed the lowest IR. In the bivariate analysis, all b/tsDMARDs had more risk of switching compared to TNFi (HR: anti-lL-17 vs TNFi: 2.26 (1.17-4.36); others vs TNFi: 3.21 (1.59-6.45)); however, this statistical significance was no longer present in the multivariate analysis once adjustments were made for the covariates. Still, the final model achieved statistical significance in the following variables: gender, clinical symptoms, prescription year, therapy courses, glucocorticoids, and sulfasalazine. Conclusion: In this study, we did not find differences in the rate of switching due to inefficacy among different groups of b/tsDMARDs. Other concomitant treatments, sociodemographic, and clinical variables were identified as risk factors for switching due to inefficacy.

METHODS: We included patients from 2007 to 2022 in which their consultant rheumatologist had decided to commence them on biologic therapy. We studied the changes due to drug failure, we also included sociodemographic, clinical and treatments information. RESULTS: The study comprised 141 patients. 52% were women in their fifties. We found that 56 patients change drugs 121 times, with 103 of those changes due to failure drug. This means about 11 out of every 100 patients change their biologic therapy each year. There was no difference in the risk of change between the different studied biologic therapies. Women, those with inflammatory back pain, and those who had tried many different drugs were more likely to change due to drug failure. Using additional therapies like glucocorticoids and sulfasalazine also increased the probability of biologic therapy change. CONCLUSION: Our work did not find differences in the risk of change due to drug failure among different biologic therapies.

Changes due to drug failure between biologic therapies: a real-life study in psoriatic arthritis patients Introduction: We wanted to evaluate how often patients with psoriatic arthritis change between different drugs because the drugs weren't working well enough. Additionally, we evaluated which factors could influence the change due to drug failure. The studied drugs are biological therapies that are arthritis-modifying drugs designed early in the last decade to prevent or reduce inflammation caused by the disease.

Sitetack: A Deep Learning Model that Improves PTM Prediction by Using Known PTMs.

Post-translational modifications (PTMs) increase the diversity of the proteome and are vital to organismal life and therapeutic strategies. Deep learning has been used to predict PTM locations. Still, limitations in datasets and their analyses compromise success. Here we evaluate the use of known PTM sites in prediction via sequence-based deep learning algorithms. Specifically, PTM locations were encoded as a separate amino acid before sequences were encoded via word embedding and passed into a convolutional neural network that predicts the probability of a modification at a given site. Without labeling known PTMs, our model is on par with others. With labeling, however, we improved significantly upon extant models. Moreover, knowing PTM locations can increase the predictability of a different PTM. Our findings highlight the importance of PTMs for the installation of additional PTMs. We anticipate that including known PTM locations will enhance the performance of other proteomic machine learning algorithms.

Genomic Evolution Strategy in SARS-CoV-2 Lineage B: Coevolution of Cis Elements.

In the SARS-CoV-2 lineage, RNA elements essential for its viral life cycle, including genome replication and gene expression, have been identified. Still, the precise structures and functions of these RNA regions in coronaviruses remain poorly understood. This lack of knowledge points out the need for further research to better understand these crucial aspects of viral biology and, in time, prepare for future outbreaks. In this research, the in silico analysis of the cis RNA structures that act in the alpha-, beta-, gamma-, and deltacoronavirus genera has provided a detailed view of the presence and adaptation of the structures of these elements in coronaviruses. The results emphasize the importance of these cis elements in viral biology and their variability between different viral variants. Some coronavirus variants in some groups, depending on the cis element (stem-loop1 and -2; pseudoknot stem-loop1 and -2, and s2m), exhibited functional adaptation. Additionally, the conformation flexibility of the s2m element in the SARS variants was determined, suggesting a coevolution of this element in this viral group. The variability in secondary structures suggests genomic adaptations that may be related to replication processes, genetic regulation, as well as the specific pathogenicity of each variant. The results suggest that RNA structures in coronaviruses can adapt and evolve toward different viral variants, which has important implications for viral adaptation, pathogenicity, and future therapeutic strategies.

Dysregulation of Glypicans and Notum in Osteoarthritis: Plasma Levels, Bone Marrow Mesenchymal Stromal Cells and Osteoblasts.

In this study of the alterations of Glypicans 1 to 6 (GPCs) and Notum in plasma, bone marrow mesenchymal stromal cells (BM-MSCs) and osteoblasts in Osteoarthritis (OA), the levels of GPCs and Notum in the plasma of 25 patients and 24 healthy subjects were measured. In addition, BM-MSCs from eight OA patients and eight healthy donors were cultured over a period of 21 days using both a culture medium and an osteogenic medium. Protein and gene expression levels of GPCs and Notum were determined using ELISA and qPCR at 0, 7, 14 and 21 days. GPC5 and Notum levels decreased in the plasma of OA patients, while the BM-MSCs of OA patients showed downexpression of GPC6 and upregulation of Notum. A decrease in GPC5 and Notum proteins and an increase in GPC3 were found. During osteogenic differentiation, elevated GPCs 2, 4, 5, 6 and Notum mRNA levels and decreased GPC3 were observed in patients with OA. Furthermore, the protein levels of GPC2, GPC5 and Notum decreased, while the levels of GPC3 increased. Glypicans and Notum were altered in BM-MSCs and during osteogenic differentiation from patients with OA. The alterations found point to GPC5 and Notum as new candidate biomarkers of OA pathology.

Effect of combined treatment with prednisone and methotrexate versus prednisone alone over laboratory parameters in giant cell arteritis.

OBJECTIVE: To compare the effect of combined treatment with prednisone and methotrexate (MTX) versus prednisone alone over laboratory parameters in giant cell arteritis (GCA). PATIENTS AND METHODS: We performed a double-blind, placebo-controlled, randomized clinical trial about usefulness of treatment with prednisone and MTX versus prednisone and placebo in GCA (Ann Intern Med 2001;134:106-114). As a part of follow-up of patients (n=42), we performed laboratory analysis in 20 time points during the two-year period of follow-up. To analyze differences, we calculated the area under the curve (AUC) for erythrocyte sedimentation rate (ESR), hemoglobin, and platelets, and compared the results in both groups adjusting by time of follow-up, existence of relapses and dose of prednisone. RESULTS: A total of 724 laboratory measurements were done. Median value of ESR was 33 [18-56] in patients with placebo and 26 [15-44] in patients with MTX (P=0.0002). No significant differences were observed in ESR during relapses. The mean ESR value followed a parallel course in both groups, but was lower in the group with MTX than in the group with placebo in 18 of 20 time points of follow-up. The AUC of ESR by time of follow-up was 28,461.7±12,326 in the group with placebo and 19,598.4±8,117 in the group with MTX (mean difference 8,863, 95% CI 1.542-16.184; P=0.019). The course of other laboratory parameters paralleled, without statistical significance, those observed for ESR. CONCLUSIONS: These data, along with clinical data, suggest that MTX might play a role as a disease-modifying agent in the treatment of GCA.

Editing VvDXS1 for the creation of muscat flavour in Vitis vinifera cv. Scarlet Royal.

Muscat flavour represents a group of unique aromatic attributes in some grape varieties. Biochemically, grape berries with muscat flavour produce high levels of monoterpenes. Monoterpene biosynthesis is mainly through the DOXP/MEP pathway, and VvDXS1 encodes the first enzyme in this plastidial pathway of terpene biosynthesis in grapevine. A single-point mutation resulting in the substitution of a lysine with an asparagine at position 284 in the VvDXS1 protein has previously been identified as the major cause for producing muscat flavour in grapes. In this study, the same substitution in the VvDXS1 protein was successfully created through prime editing in the table grape Vitis vinifera cv. 'Scarlet Royal'. The targeted point mutation was detected in most of the transgenic vines, with varying editing efficiencies. No unintended mutations were detected in the edited alleles, either by PCR Sanger sequencing or by amplicon sequencing. More than a dozen edited vines were identified with an editing efficiency of more than 50%, indicating that these vines were likely derived from single cells in which one allele was edited. These vines had much higher levels of monoterpenes in their leaves than the control, similar to what was found in leaf samples between field-grown muscat and non-muscat grapes.

Emerging trends in nurse-led programs of care for management of patients with established rheumatoid arthritis: Systematic literature review.

INTRODUCTION: In patients with rheumatoid arthritis (RA), nurses are considered as essential, not only to ensure pharmacological safety, but also in the promotion in self-care and decision-making, favouring the empowerment of patients. This systematic review aimed to summarize the available literature on the health education by the nurse in patients with RA. MATERIAL AND METHODS: Following Cochrane Collaboration procedures, the PRISMA statement and PRISMA checklist, relevant quantitative studies published were retrieved from the CINAHL, Scopus, PubMed and Medic databases and then systematically reviewed. The search ended in August 2021. Nineteen studies were retained for inclusion and evaluated with the Scottish Intercollegiate Guidelines Network for Systematic Reviews. RESULTS: We found statistically significant improvement in self-care (five studies), disease activity (three studies), quality of life (two studies), satisfaction (five studies) and adherence (one study) with the nursing-led management of patients with established rheumatoid arthritis. DISCUSSION: Although there is solid evidence of improvement in satisfaction and self-care, there seems to be a trend also to improve other outcomes, such as DAS28, from the EULAR recommendations, the expansion of the therapeutic arsenal for rheumatoid arthritis and shared decision-making. In addition, recently and due to the implementation of new technologies, the role of the nurse has been evaluated through virtual consultations. The results of recent studies have shown that this an effective and well-accepted novel approach for the management of patients with stable rheumatoid arthritis. CONCLUSION: Our study suggests that nurse-led health education, in addition of improvement in satisfaction and self-care, improve activity disease scores in RA patients.

Harnessing ChatGPT and GPT-4 for evaluating the rheumatology questions of the Spanish access exam to specialized medical training.

The emergence of large language models (LLM) with remarkable performance such as ChatGPT and GPT-4, has led to an unprecedented uptake in the population. One of their most promising and studied applications concerns education due to their ability to understand and generate human-like text, creating a multitude of opportunities for enhancing educational practices and outcomes. The objective of this study is twofold: to assess the accuracy of ChatGPT/GPT-4 in answering rheumatology questions from the access exam to specialized medical training in Spain (MIR), and to evaluate the medical reasoning followed by these LLM to answer those questions. A dataset, RheumaMIR, of 145 rheumatology-related questions, extracted from the exams held between 2010 and 2023, was created for that purpose, used as a prompt for the LLM, and was publicly distributed. Six rheumatologists with clinical and teaching experience evaluated the clinical reasoning of the chatbots using a 5-point Likert scale and their degree of agreement was analyzed. The association between variables that could influence the models' accuracy (i.e., year of the exam question, disease addressed, type of question and genre) was studied. ChatGPT demonstrated a high level of performance in both accuracy, 66.43%, and clinical reasoning, median (Q1-Q3), 4.5 (2.33-4.67). However, GPT-4 showed better performance with an accuracy score of 93.71% and a median clinical reasoning value of 4.67 (4.5-4.83). These findings suggest that LLM may serve as valuable tools in rheumatology education, aiding in exam preparation and supplementing traditional teaching methods.

Optimization of In Vitro Embryo Rescue and Development of a Kompetitive Allele-Specific PCR (KASP) Marker Related to Stenospermocarpic Seedlessness in Grape (Vitis vinifera L.).

Seedlessness is one of the highest valued agronomic traits in grapes. Embryo rescue in combination with marker-assisted selection have been widely applied in seedless grape breeding due to the advantages of increasing the ratio of seedless progenies and shortening the breeding cycle. However, the large number of deformed seedlings produced during embryo rescue and the lack of fast, efficient, and low-cost markers severely inhibit the process of seedless grape breeding. In this study, a total of eighty-three grape cultivars (51 seedless and 32 seeded) with diverse genetic backgrounds and two populations derived from embryo rescue, including 113 F1 hybrid individuals (60 seedless and 53 seeded), were utilized. We screened suitable media for converting malformed seedlings into normal seedlings, analyzed the association between the SNP in VviAGL11 and seeded/seedless phenotype, and developed a KASP marker related to stenospermocarpic seedlessness. Our results indicated that the transformation rate of 37.8% was obtained with MS medium supplemented with 2.0 mg·L-1 of 6-BA and 0.5 mg·L-1 of IBA. The presence of an A nucleotide allele at position chr18:26889437 was further confirmed to be fully associated with the stenospermocarpic seedlessness phenotype. The developed KASP marker, based on the verified SNP locus in VviAGL11, successfully distinguished the seedless and seeded genotypes with high precision and throughput. The results will contribute to enhancing the efficiency of embryo rescue and facilitate parent selection and early selection of seedless offspring with molecular markers, thereby accelerating the breeding process in seedless table grapes.

Ultrafast mode-locked laser in nanophotonic lithium niobate.

Mode-locked lasers (MLLs) generate ultrashort pulses with peak powers substantially exceeding their average powers. However, integrated MLLs that drive ultrafast nanophotonic circuits have remained elusive because of their typically low peak powers, lack of controllability, and challenges when integrating with nanophotonic platforms. In this work, we demonstrate an electrically pumped actively MLL in nanophotonic lithium niobate based on its hybrid integration with a III-V semiconductor optical amplifier. Our MLL generates [Formula: see text]4.8-ps optical pulses around 1065 nm at a repetition rate of ∼10 GHz, with energies exceeding 2.6 pJ and peak powers beyond 0.5 W. The repetition rate and the carrier-envelope offset frequency of the output can be controlled in a wide range by using the driving frequency and the pump current, providing a route for fully stabilized on-chip frequency combs.

Specific Cellular and Humoral Response after the Third Dose of Anti-SARS-CoV-2 RNA Vaccine in Patients with Immune-Mediated Rheumatic Diseases on Immunosuppressive Therapy.

OBJECTIVE: Data on cellular and humoral immunogenicity after the third dose of anti-SARS-CoV-2 vaccines in patients with immune-mediated rheumatic diseases (IMRDs) are scarce. Herein, we evaluated the adaptive immune response in IMRD patients treated with different immunosuppressive therapies (conventional synthetic disease-modifying antirheumatic drugs [csDMARDs], biological disease-modifying antirheumatic drugs [bDMARDs], and targeted synthetic disease-modifying antirheumatic drugs [tsDMARDs]) after the booster of the anti-SARS-CoV-2 vaccine to determine whether any drug reduced the vaccine's response. METHODS: A single-center prospective study was conducted, including patients presenting with IMRD and healthy controls (HC). Specific anti-SARS-CoV-2 interferon-gamma (IFN-γ) production was evaluated between 8-12 weeks after the third dose of the SARS-CoV-2 vaccine. In addition, anti-Spike IgG antibody titers were also measured. RESULTS: Samples were obtained from 79 IMRD patients (51 women, 28 men; mean age 57 ± 11.3 years old): 43 rheumatoid arthritis, 10 psoriatic arthritis, 14 ankylosing spondylitis, 10 undifferentiated spondyloarthritis, and 2 inflammatory bowel disease-associated spondyloarthritis (IBD-SpA). In total, 31 HC (mean age 50.9 ± 13.1 years old, 67.7% women) were included in the study. Post-vaccine results displayed positive T-cell immune responses in 68 out of 79 (86.1%) IMRD patients (82.3% of those without prior COVID-19). All HC and IMRDs patients had an antibody response against the SARS-CoV-2 receptor-binding domain; however, the HC response was significantly higher (median of 18,048 AU/mL) than in IMRDs patients (median of 6590.3 AU/mL, p < 0.001). MTX and leflunomide were associated with lower titers of IgG and IFN-γ responses. Among bDMARDs, adalimumab, etanercept, and guselkumab are associated with reduced cellular responses. CONCLUSION: Our preliminary data show that the majority of our IMRD patients develop cellular and humoral responses after the SARS-CoV-2 booster vaccination, emphasizing the relevance of vaccination in this group. However, the magnitude of specific responses was dependent on the immunosuppressive therapy administered. Specific vaccination protocols and personalized decisions about boosters are essential for these patients.

Non-Structural Proteins (Nsp): A Marker for Detection of Human Coronavirus Families.

SARS-CoV-2 was the cause of the global pandemic that caused a total of 14.9 million deaths during the years 2020 and 2021, according to the WHO. The virus presents a mutation rate between 10-5 and 10-3 substitutions per nucleotide site per cell infection (s/n/c). Due to this, studies aimed at knowing the evolution of this virus could help us to foresee (through the future development of new detection strategies and vaccines that prevent the infection of this virus in human hosts) that a pandemic caused by this virus will be generated again. In this research, we performed a functional annotation and identification of changes in Nsp (non-structural proteins) domains in the coronavirus genome. The comparison of the 13 selected coronavirus pangenomes demonstrated a total of 69 protein families and 57 functions associated with the structural domain's differentials between genomes. A marked evolutionary conservation of non-structural proteins was observed. This allowed us to identify and classify highly pathogenic human coronaviruses into alpha, beta, gamma, and delta groups. The designed Nsp cluster provides insight into the trajectory of SARS-CoV-2, demonstrating that it continues to evolve rapidly. An evolutionary marker allows us to discriminate between phylogenetically divergent groups, viral genotypes, and variants between the alpha and betacoronavirus genera. These types of evolutionary studies provide a window of opportunity to use these Nsp as targets of viral therapies.

Regulation Transcriptional of Antibiotic Resistance Genes (ARGs) in Bacteria Isolated from WWTP.

The incidence of antibiotics and transcriptional regulation of ARGs in isolated bacteria from wastewater needs to be explored. By HPLC, in samples of untreated wastewater, ampicillin (49.74 ± 5.70 µg/mL), chloramphenicol (0.60 ± 0.03 µg/mL), tylosin (72.95 ± 2.03 µg/mL), and oxytetracycline (0.22 ± 0.01 µg/mL) was determined. Through metagenomic analysis identified 58 bacterial species belonging to 9 phyla and at least 14 species have shown resistance to a variety of antibiotics. Twenty-two bacterial isolates were proved to be resistant to fifteen antibiotics of new generation and used in medical research to combat infectious diseases. Fourteen strains were shown to harbor plasmids in size ranges of 2-5 Kb, 6-10 Kb and plasmids with size greater than 10 Kb. By quantitative PCR it was possible to identify genes sul, qnr, cat1, aadA1, and sat-1 gene were shown to be present in gDNA samples from treated and untreated samples of wastewater and by relative expression analysis, differential expression of cat1, ermB, act, and tetA genes was demonstrated in strains that showed identity with Escherichia coli, Bacteroides fragilis, and Salmonella thyphi, and that were stressed with different concentrations of antibiotics. The presence of ARGs in untreated water samples, as well as in bacterial isolates, was indicative that in these habitats there are microorganisms that can resist ß-lactams, aminoglycosides, tetracyclines, sulfonamides, and quinolones.

Understanding the role and adoption of artificial intelligence techniques in rheumatology research: An in-depth review of the literature.

The major and upward trend in the number of published research related to rheumatic and musculoskeletal diseases, in which artificial intelligence plays a key role, has exhibited the interest of rheumatology researchers in using these techniques to answer their research questions. In this review, we analyse the original research articles that combine both worlds in a five- year period (2017-2021). In contrast to other published papers on the same topic, we first studied the review and recommendation articles that were published during that period, including up to October 2022, as well as the publication trends. Secondly, we review the published research articles and classify them into one of the following categories: disease identification and prediction, disease classification, patient stratification and disease subtype identification, disease progression and activity, treatment response, and predictors of outcomes. Thirdly, we provide a table with illustrative studies in which artificial intelligence techniques have played a central role in more than twenty rheumatic and musculoskeletal diseases. Finally, the findings of the research articles, in terms of disease and/or data science techniques employed, are highlighted in a discussion. Therefore, the present review aims to characterise how researchers are applying data science techniques in the rheumatology medical field. The most immediate conclusions that can be drawn from this work are: multiple and novel data science techniques have been used in a wide range of rheumatic and musculoskeletal diseases including rare diseases; the sample size and the data type used are heterogeneous, and new technical approaches are expected to arrive in the short-middle term.

Long-Term Benefit of Perlingual Polybacterial Vaccines in Patients with Systemic Autoimmune Diseases and Active Immunosuppression.

INTRODUCTION: We have previously shown that trained-immunity-based vaccines, namely TIbV, significantly reduce the rate of recurrent infections, both of the respiratory tract (RRTI) and urinary tract infections (RUTI) in SAD patients on disease-modifying drugs (DMARDs). OBJECTIVE: We evaluated the frequency of RRTI and RUTI from 2018 to 2021 in those SAD patients that received TIbV until 2018. Secondarily, we evaluated the incidence and clinical course of COVID-19 in this cohort. METHODS: A retrospective observational study was conducted in a cohort of SAD patients under active immunosuppression immunized with TIbV (MV130 for RRTI and MV140 for RUTI, respectively). RESULTS: Forty-one SAD patients on active immunosuppression that were given TIbV up to 2018 were studied for RRTI and RUTI during the 2018-2021 period. Approximately half of the patients had no infections during 2018-2021 (51.2% no RUTI and 43.5% no RRTI at all). When we compared the 3-year period with the 1-year pre-TIbV, RRTI (1.61 ± 2.26 vs. 2.76 ± 2.57; p = 0.002) and RUTI (1.56 ± 2.12 vs. 2.69 ± 3.07; p = 0.010) episodes were still significantly lower. Six SAD patients (four RA; one SLE; one MCTD) with RNA-based vaccines were infected with SARS-CoV-2, with mild disease. CONCLUSIONS: Even though the beneficial protective effects against infections of TIbV progressively decreased, they remained low for up to 3 years, with significantly reduced infections compared to the year prior to vaccination, further supporting a long-term benefit of TIbV in this setting. Moreover, an absence of infections was observed in almost half of patients.

Difficult-to-treat rheumatoid arthritis (D2T RA): clinical issues at early stages of disease.

OBJECTIVES: Most studies on difficult-to-treat rheumatoid arthritis (D2T RA) have focused on established RA. Here, we analyse whether disease activity in the early stages of RA could influence progression to a D2T RA under real-life conditions. Other clinical and treatment-related factors were also analysed. METHODS: A longitudinal multicentre study of patients with RA was conducted from 2009 to 2018. Patients were followed up until January 2021. D2T RA was defined based on EULAR criteria (treatment failure, signs suggestive of currently active/progressive disease and management being perceived as problematic by the rheumatologist and/or patient). The main variable was disease activity in the early stages. The covariates were sociodemographic, clinical and treatment-related factors. We ran a multivariable logistic regression analysis to investigate risk factors associated with progression to D2T RA. RESULTS: The study population comprised 631 patients and 35 (5.87%) developed D2T RA. At the time of diagnosis, the D2T RA group were younger, with a higher disability, 28-joint Disease Activity Score (DAS28) score, tender joint count and pain scores. In our final model, DAS28 was not statistically significantly associated with D2T RA. No differences were found between groups for therapy. Disability was independently associated with D2T RA (OR: 1.89; p=0.01). CONCLUSIONS: In this cohort of patients newly diagnosed with RA, our results do not allow us to prove the influence of active disease according to DAS28. However, we did find that younger patients and those with elevated initial disability scores are more likely to develop D2T RA regardless of other factors.