Reduction of the formaldehyde content in leathers treated with formaldehyde resins by means of plant polyphenols

Formaldehyde has applications in many industrial processes, including synthesis of resins and syntans to be used in the retanning process of leather. When resins are employed, they can hydrolyse, releasing formaldehyde. Due to the carcinogenicity of formaldehyde, its presence in leather should be avoided or kept below allowable limits. The aim of this study is to determine the effect of polyphenols contained in vegetable compounds (mimosa, quebracho and tara) in the reduction of the formaldehyde content in leathers treated with resins synthesized with formaldehyde (melamine-formaldehyde and dicyandiamide-formaldehyde). The formaldehyde content in leathers treated only with resin increases with time while the formaldehyde content in leathers treated additionally with vegetable compounds is reduced. The lower the formaldehyde content in the leather, the higher the ability of vegetable compounds to reduce such content. Mimosa shows the strongest ability to reduce the formaldehyde content, and this capacity increases with ageing. The addition of 4% (on shaved wet-blue weight) of mimosa gives rise to an 85% reduction in the formaldehyde content 140 days after leather processing of split hides treated with a formaldehyde resin of low formaldehyde content. However, this reduction is 68% in splits hides treated with a resin of high formaldehyde content. This is of great importance in baby’s leather articles, in which the formaldehyde content is low; therefore, the addition of a small amount (3%) of vegetable compounds (especially mimosa) guarantees that the formaldehyde content is below the allowed limits (16 mg/kg in the most restrictive regulation). Reducing the formaldehyde content using the polyphenols contained in vegetable compounds constitutes a good alternative not only in the leather sector but also in other industrial sectors (wood, textile, etc.) that use formaldehyde resins.Peer ReviewedPostprint (published version

An overlook on the current registries for rare and complex connective tissue diseases and the future scenario of TogethERN ReCONNET

European Reference Networks; Rare and complex connective tissue diseases; RegistriesRedes Europeas de Referencia; Enfermedades raras y complejas del tejido conjuntivo; RegistrosXarxes de referència europees; Malalties rares i complexes del teixit conjuntiu; RegistresBackground: Patient registries play a crucial role in supporting clinical practice, healthcare planning and medical research, offering a real-world picture on rare and complex connective tissue diseases (rCTDs). ERN ReCONNET launched the first European Registry Infrastructure with the aim to plan, upgrade and link registries for rCTDs, with the final goal to promote a harmonized data collection approach all over Europe for rCTDs. Methods: An online survey addressed to healthcare professionals and patients' representatives active in the field of rCTDs was integrated by an extensive database search in order to build a mapping of existing registries for rCTDs. Findings: A total of 140 registries were found, 38 of which include multiple diseases. No disease-specific registry was identified for relapsing polychondritis, mixed connective tissue disease and undifferentiated connective tissue disease. Discussion: This overview on the existing registries for rCTDs provides a useful starting point to identify the gaps and the strengths of registries on the coverage of rCTDs, and to develop a common data set and data collection approach for the establishment of the TogethERN ReCONNET Infrastructure.This work was funded by the European Union's Health Program (2014–2020). ERN ReCONNET is one of the 24 European Reference Networks (ERNs) approved by the ERN Board of Member States. The ERNs are co-funded by the EC (European Commission) (grant no. 947700)

Influenza Adverse Events in Patients with Rheumatoid Arthritis, Ulcerative Colitis, or Psoriatic Arthritis in the Tofacitinib Clinical Development Programs

Gripe; Artritis psoriásica; Colitis ulcerosaInfluenza; Psoriatic arthritis; Ulcerative colitisGrip; Artritis psoriàsica; Colitis ulcerosaIntroduction This post hoc analysis evaluated influenza adverse events (AEs) across rheumatoid arthritis (RA), ulcerative colitis (UC), and psoriatic arthritis (PsA) tofacitinib clinical programs. Methods Available data from phase 1, randomized phase 2/3/3b/4 clinical trials (completed by 2018), and long-term extension (LTE) studies (up to May 2019) in patients with RA, UC, and PsA were included [randomized or Overall (phase 1–3b/4 and LTE studies) tofacitinib cohorts]. Incidence rates (IRs; events per 100 patient-years) of combined influenza AEs (seasons 2004/2005 to 2018/2019) were analyzed, including by tofacitinib dose [5 or 10 mg twice daily (BID)] and age (< 65 versus ≥ 65 years). Logistic regression models evaluated risk factors for influenza AEs in the RA Overall tofacitinib cohort. Results In randomized cohorts, combined influenza AE IRs were generally similar across tofacitinib, adalimumab, methotrexate, and placebo groups, across indications. Among Overall tofacitinib cohorts, combined influenza AE IRs with tofacitinib 5/10 mg BID, respectively, were higher in the UC (3.66/5.09) versus RA (2.38/2.19) and PsA (1.74/1.29) cohorts. IRs were generally similar across tofacitinib dose and age groups. Most influenza AEs were nonserious and did not require changes to tofacitinib treatment. Significant risk factors for influenza AEs in patients with RA were geographic region, baseline oral corticosteroid and methotrexate use, and tofacitinib dose. Conclusions In the RA, UC, and PsA clinical programs, combined influenza AE IRs were highest in UC, while in each indication they were generally similar across tofacitinib, placebo, and comparator groups. Influenza AEs were predominantly nonserious and not associated with changes to tofacitinib treatment.This study was sponsored by Pfizer. Medical writing support was funded by Pfizer. The journal’s Rapid Service Fee for this article was also funded by Pfizer

Valorization of tannery wastes: Lipoamino acid surfactant mixtures from the protein fraction of process wastewater

The first stages of the transformation process of hides into leather (beamhouse process) generate an important waste in the tanning industry, since a considerable fraction of solubilized proteins ends up in waste water with the corresponding increase in contamination parameters, especially when the process is carried out without hair recovery (hair-pulping process). The objective of this work was the valorisation of this waste (the separated protein fraction) which conveniently hydrolyzed to amino acid level constituted the starting material for the production of biodegradable surfactants. The lipoamino acid surfactants were obtained by acylation of the amino acids from the protein hydrolysate. These surfactants were characterized and their physico-chemical and biological properties evaluated. They exhibit very low cmc values (about 40. mg/L). These surfactants are readily biodegradable and present an aquatic toxicity significantly lower than many common commercial surfactants derived whether from renewable or petrochemical feedstock. The mixtures of surfactants obtained are able to form oil/water emulsions that remain stable for at least 1. year. The results obtained in this work confirmed that it is possible the production of biodegradable and efficient lipoamino acid surfactant mixtures from the protein fraction present in beamhouse process wastewaters. This study constitutes a promising approach for the reduction of the pollution load from industrial tannery wastes and its valorisation as raw material for the production of surfactants with excellent environmental properties and good technical properties.The authors are grateful to the Spanish Ministry of Economy and Competitiveness for the financial support given through the CTQ2013-41514P, CTQ2013-43029P and MAT2012-38047-C02-02 Projects.Peer reviewe

Dyestuffs and formaldehyde content in split leather treated with formaldehyde resins

Formaldehyde resins are present in textile, leather and wood industries. Due to the harmful character of formaldehyde, different alternatives have been found to exclude or reduce its content on processed goods. However, the effect of dyestuffs on the formaldehyde content of goods containing formaldehyde-synthesized resins has not been studied up to date. The aim of this work is to check if the presence of free amino groups in the structure of dyestuffs exerts an influence on the formaldehyde content on leathers treated with formaldehyde-synthesized resins. Six dyes, belonging to three different families (acid dyes, direct dyes and basic dyes), have been taken as examples to evaluate how their structures affect the reaction with formaldehyde present in leather. The variation of the formaldehyde content in dyed leathers with respect to control samples (treated with resin only) and its evolution with time have been also considered. It has been found that the ability of dyes in reducing the formaldehyde content in leather depends on the amount of amino groups amenable to reaction with formaldehyde. Those amino groups that in their vicinity have other functionalities, with which to form relatively stable structures, have a reduced reactivity with formaldehyde. The reduction ability of dyes also depends on the formaldehyde content in leather. The lower the formaldehyde content is in the leather, the higher this reduction ability. Acid Black 234 dye caused a formaldehyde content reduction of approximately 84% in leathers treated with melamine-formaldehyde resin of low formaldehyde content in the analysis carried out after 90 days of leather processing whereas the reduction was approximately 20% when the resin was of high formaldehyde content. The highest reduction ability of basic dyes corresponded to the dye that has the greatest amount of amino residues amenable to reaction with formaldehyde (Basic Orange 2). Basic Orange 2 dye exhibited higher reduction ability (90% of reduction in leathers treated with resin of high formaldehyde content after 90 days of leather processing) than the Acid Black 234 dye (approximately 20%), both containing similar amount of free amino residues. Thin layer chromatography analysis revealed that the Basic Orange 2 dye is mainly a single major component, while the Acid Black dye 234 is a mixture of components that can have a reduced reactivity with formaldehyde. Further experiments are required to investigate if the surface leather dyeing (Basic Orange 2 dye) have a higher influence on formaldehyde content reduction than the through-dyeing (Acid Black 234 dye).Peer ReviewedPostprint (published version

Biomarcadores clínicos de Remisión en pacientes con Artritis Reumatoide tratados con Anti-TNFα

The way rheumatoid arthritis (RA) is treated has changed dramatically in the last decade, with the use of molecular targeted therapies. These durgs act in pathways associated with the inflammatory process, improving disease control with less development of adverse effects. However, there are a percentage of patients in whom these therapies are not effective. So far, no validated biomarkers that can be used as a predictor of response in clinical practice has ben detected. Being able to predict which patients will respond to a certain treatment will optimize treatment with these expensive drugs. Objectives: To identify biomarkers for anti-TNF therapy remission in patients with rheumatoid arthritis in a large cohort of patients. Materials and Methods: A total of 628 RA patients that have received theire first anti-TNFα therapy (n = 159 adalimumab, etanercept and infliximab n = 251 n = 218) were included in the present study. All patients were collected as part of the IMID consortium. A number of epidemiological variables (ie origin, toxic habits, physical activity, level of education, etc.) and a large number of variables related to the AR itself (ie age of onset, presence of autoantibodies, previous treatments, etc) were collected. Clinical remission was defined as a value of DAS28El estudio de la fisiopatología de la Artritis Reumatoide (AR) ha permitido el desarrollo de fármacos capaces de actuar de forma precisa en las vías relacionadas con el proceso inflamatorio, logrando un mejor control de la enfermedad con un menor desarrollo de efectos adversos. Sin embargo, existe un porcentaje de pacientes en los que estas terapias no son eficaces. Hasta el momento no existe ningún biomarcador validado que pueda ser utilizado como un predictor de respuesta en la práctica clínica y tampoco se conoce con exactitud el mecanismo biológico por el cual algunos pacientes no responden de forma adecuada a estos tratamientos. El poder predecir que pacientes responderán a un tratamiento determinado permitirá optimizar el tratamiento con estos agentes. Objetivo: Identificar biomarcadores de remisión no genéticos al tratamiento con terapias anti-TNFα en pacientes con artritis reumatoide en una gran cohorte de pacientes. Materiales y métodos: Se incluyó a los 628 pacientes con diagnóstico de AR del proyecto PSE IMID-Kit que iniciaban una terapia biológica (adalimumab n=159, etanercept n=251 e infliximab n=218). Se registraron una serie de variables epidemiológicas (i.e. procedencia, habitos tóxicos, actividad física, grado de estudios, etc) y un elevado número de variables relacionadas con la propia AR (i.e. edad de inicio, presencia de autoanticuerpos, tratamientos previos, etc). La remisión clínica fue definida como un valor del DAS2

An Eight-Gene Blood Expression Profile Predicts the Response to Infliximab in Rheumatoid Arthritis

BACKGROUND: TNF alpha blockade agents like infliximab are actually the treatment of choice for those rheumatoid arthritis (RA) patients who fail standard therapy. However, a considerable percentage of anti-TNF alpha treated patients do not show a significant clinical response. Given that new therapies for treatment of RA have been recently approved, there is a pressing need to find a system that reliably predicts treatment response. We hypothesized that the analysis of whole blood gene expression profiles of RA patients could be used to build a robust predictor to infliximab therapy. METHODS AND FINDINGS: We performed microarray gene expression analysis on whole blood RNA samples from RA patients starting infliximab therapy (n = 44). The clinical response to infliximab was determined at week 14 using the EULAR criteria. Blood cell populations were determined using flow cytometry at baseline, week 2 and week 14 of treatment. Using complete cross-validation and repeated random sampling we identified a robust 8-gene predictor model (96.6% Leave One Out prediction accuracy, P = 0.0001). Applying this model to an independent validation set of RA patients, we estimated an 85.7% prediction accuracy (75-100%, 95% CI). In parallel, we also observed a significantly higher number of CD4+CD25+ cells (i.e. regulatory T cells) in the responder group compared to the non responder group at baseline (P = 0.0009). CONCLUSIONS: The present 8-gene model obtained from whole blood expression efficiently predicts response to infliximab in RA patients. The application of the present system in the clinical setting could assist the clinician in the selection of the optimal treatment strategy in RA

scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases

Drug repurposing; Immune-mediated inflammatory disease; Single-cell RNA sequencingReutilización de medicamentos; Enfermedad inflamatoria inmunomediada; Secuenciación de ARN unicelularReutilització de medicaments; Malaltia inflamatòria immunomediada; Seqüenciació d'ARN unicel·lularBackground Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn’s disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn’s disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusions We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio’s potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package (https://github.com/SDTC-CPMed/scDrugPrio).Open access funding provided by Karolinska Institute. This work was supported by the DocTIS project, which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement N° 848028; Swedish Cancer Society CAN 2017/411; Cocozza Foundation; National Natural Science Foundation of China 82171791, US National Institutes of Health grants HL155107 and HL155096; American Heart Association grant 957729; European Union’s Horizon 2021 Research and Innovation Programme grant 101057619 and Mag-Tarmfonden (grant 1–23). The computations were partially enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at Linköping University partially funded by the Swedish Research Council through grant agreement no. 2018–05973