FAMetA: a mass isotopologue-based tool for the comprehensive analysis of fatty acid metabolism.

The use of stable isotope tracers and mass spectrometry (MS) is the gold standard method for the analysis of fatty acid (FA) metabolism. Yet, current state-of-the-art tools provide limited and difficult-to-interpret information about FA biosynthetic routes. Here we present FAMetA, an R package and a web-based application (www.fameta.es) that uses 13C mass isotopologue profiles to estimate FA import, de novo lipogenesis, elongation and desaturation in a user-friendly platform. The FAMetA workflow covers the required functionalities needed for MS data analyses. To illustrate its utility, different in vitro and in vivo experimental settings are used in which FA metabolism is modified. Thanks to the comprehensive characterization of FA biosynthesis and the easy-to-interpret graphical representations compared to previous tools, FAMetA discloses unnoticed insights into how cells reprogram their FA metabolism and, when combined with FASN, SCD1 and FADS2 inhibitors, it enables the identification of new FAs by the metabolic reconstruction of their synthesis route.

Ecotoxicity characterization assisted performance assessment of electro-bioremediation reactors for nitrate and arsenite elimination.

The performance of combined reduction of nitrate (NO3 - ) to dinitrogen gas (N2 ) and oxidation of arsenite (As[III]) to arsenate (As[V]) by a bioelectrochemical system was assessed, supported by ecotoxicity characterization. For the comprehensive toxicity characterization of the untreated model groundwater and the treated reactor effluents, a problem-specific ecotoxicity test battery was established. The performance of the applied technology in terms of toxicity and target pollutant elimination was compared and analyzed. The highest toxicity attenuation was achieved under continuous flow mode with hydraulic retention time (HRT) = 7.5 h, with 95%, nitrate removal rate and complete oxidation of arsenite to arsenate. Daphnia magna proved to be the most sensitive test organism. The results of the D. magna lethality test supported the choice of the ideal operational conditions based on chemical data analysis. The outcomes of the study demonstrated that the applied technology was able to improve the groundwater quality in terms of both chemical and ecotoxicological characteristics. The importance of ecotoxicity evaluation was also highlighted, given that significant target contaminant elimination did not necessarily lower the environmental impact of the initial, untreated medium, in addition, anomalies might occur during the technology operational process which in some instances, could result in elevated toxicity levels.

Real-world evaluation of a QCM-based biosensor for exhaled air.

The biosensor, named "virusmeter" in this study, integrates quartz crystal microbalance technology with an immune-functionalized chip to distinguish between symptomatic patients with respiratory diseases and healthy individuals by analyzing exhaled air samples. Renowned for its compact design, rapidity, and noninvasive nature, this device yields results within a 5-min timeframe. Evaluated under controlled conditions with 54 hospitalized symptomatic COVID-19 patients and 128 control subjects, the biosensor demonstrated good overall sensitivity (98.15%, 95% CI 90.1-100.0) and specificity (96.87%, 95% CI 92.2-99.1). This proof-of-concept presents an innovative approach with significant potential for leveraging piezoelectric sensors to diagnose respiratory diseases.

LipidMS 3.0: an R-package and a web-based tool for LC-MS/MS data processing and lipid annotation.

MOTIVATION: LipidMS was initially envisioned to use fragmentation rules and data-independent acquisition (DIA) for lipid annotation. However, data-dependent acquisition (DDA) remains the most widespread acquisition mode for untargeted LC-MS/MS-based lipidomics. Here, we present LipidMS 3.0, an R package that not only adds DDA and new lipid classes to its pipeline but also the required functionalities to cover the whole data analysis workflow from pre-processing (i.e. peak-peaking, alignment and grouping) to lipid annotation. RESULTS: We applied the new workflow in the data analysis of a commercial human serum pool spiked with 68 representative lipid standards acquired in full scan, DDA and DIA modes. When focusing on the detected lipid standard features and total identified lipids, LipidMS 3.0 data pre-processing performance is similar to XCMS, whereas it complements the annotations returned by MS-DIAL, providing a higher level of structural information and a lower number of incorrect annotations. To extend and facilitate LipidMS 3.0 usage among less experienced R-programming users, the workflow is also implemented as a web-based application. AVAILABILITY AND IMPLEMENTATION: The LipidMS R-package is freely available at https://CRAN.R-project.org/package=LipidMS and as a website at http://www.lipidms.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Starkeya nomas sp. nov., a prosthecate and budding bacterium isolated from an immunocompromized patient.

Strain HF14-78462T is an environmental bacterium found in clinical samples from an immunocompromized patient in 2014 at Hospital Universitari i Politècnic La Fe (Valencia, Spain). Phenotypically, strain HF14-78462T cells were Gram-stain-negative, aerobic, non-spore forming and non-motile small rods which formed mucous and whitish-translucent colonies when incubated at 20-36 °C. Phylogenetic analyses based on the 16S rRNA genes and the whole genomes of closest sequenced relatives confirmed that strain HF14-78462T is affiliated with the genus Starkeya. The strain was oxidase, catalase and urease positive; but indole, lysine decarboxylase, ornithine decarboxylase and DNase negative, did not produce H2S and was able to utilize a wide variety of carbon sources including acetamide, adonitol, amygdalin, l-arabinose, citric acid, glucose, mannitol and melibiose. Unlike Starkeya novella and Starkeya koreensis, strain HF14-78462T failed to grow in thiosulphate-oxidizing media and had a narrower temperature growth range. Its genome was characterized by a size of 4.83 Mbp and a C+G content of 67.75 mol%. Major fatty acids were C18:1 ω7c, cyclo C19 : 0 and C16 : 0, its polar acids were diphosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol and an aminophospholipid; while the ubiquinones were Q9 (1.8 %) and Q10 (98.2 %). Digital DNA-DNA hybridization values were 41 and 41.4 against S. novella and S. koreensis, respectively, while average nucleotide identity values were around 84 %. Phenotypic, average nucleotide identity and phylogenomic comparative studies suggest that strain HF14-78462T is a new representative of the genus Starkeya and the name Starkeya nomas sp. nov. is proposed. The type strain is HF14-78462T (=CECT 30124T=LMG 31874T).

Enhanced Channel Calibration for the Image Sensor of the TuMag Instrument.

The Sunrise missions consist of observing the magnetic field of the sun continuously for a few days from the stratosphere. In these missions, a balloon supporting a telescope and associated instrumentation, including a Tunable Magnetograph (TuMag), is lifted into the stratosphere. In the camera of this instrument, the image sensor sends its data to a Field Programmable Gate Array (FPGA) using eight transmission channels. These channels must be previously calibrated for a correct delivery of the image. For this mission, the FPGA has been exchanged for a newer and larger one, so the firmware has been adapted to the new device. In addition, the calibration algorithm has been parallelized as the main innovation of this work, taking advantage of the increase in logic resources of the new FPGA, in order to minimize the calibration time of the channels. The algorithm has been implemented specifically for this instrument without using the Input Serial Deserializer (ISERDES) Intellectual Property (IP), since this IP does not support the deserialization of the data sent by the image sensor to the FPGA.

tuxnet: a simple interface to process RNA sequencing data and infer gene regulatory networks.

Predicting gene regulatory networks (GRNs) from expression profiles is a common approach for identifying important biological regulators. Despite the increased use of inference methods, existing computational approaches often do not integrate RNA-sequencing data analysis, are not automated or are restricted to users with bioinformatics backgrounds. To address these limitations, we developed tuxnet, a user-friendly platform that can process raw RNA-sequencing data from any organism with an existing reference genome using a modified tuxedo pipeline (hisat 2 + cufflinks package) and infer GRNs from these processed data. tuxnet is implemented as a graphical user interface and can mine gene regulations, either by applying a dynamic Bayesian network (DBN) inference algorithm, genist, or a regression tree-based pipeline, rtp-star. We obtained time-course expression data of a PERIANTHIA (PAN) inducible line and inferred a GRN using genist to illustrate the use of tuxnet while gaining insight into the regulations downstream of the Arabidopsis root stem cell regulator PAN. Using rtp-star, we inferred the network of ATHB13, a downstream gene of PAN, for which we obtained wild-type and mutant expression profiles. Additionally, we generated two networks using temporal data from developmental leaf data and spatial data from root cell-type data to highlight the use of tuxnet to form new testable hypotheses from previously explored data. Our case studies feature the versatility of tuxnet when using different types of gene expression data to infer networks and its accessibility as a pipeline for non-bioinformaticians to analyze transcriptome data, predict causal regulations, assess network topology and identify key regulators.

Characterizing the involvement of FaMADS9 in the regulation of strawberry fruit receptacle development.

FaMADS9 is the strawberry (Fragaria x ananassa) gene that exhibits the highest homology to the tomato (Solanum lycopersicum) RIN gene. Transgenic lines were obtained in which FaMADS9 was silenced. The fruits of these lines did not show differences in basic parameters, such as fruit firmness or colour, but exhibited lower Brix values in three of the four independent lines. The gene ontology MapMan category that was most enriched among the differentially expressed genes in the receptacles at the white stage corresponded to the regulation of transcription, including a high percentage of transcription factors and regulatory proteins associated with auxin action. In contrast, the most enriched categories at the red stage were transport, lipid metabolism and cell wall. Metabolomic analysis of the receptacles of the transformed fruits identified significant changes in the content of maltose, galactonic acid-1,4-lactone, proanthocyanidins and flavonols at the green/white stage, while isomaltose, anthocyanins and cuticular wax metabolism were the most affected at the red stage. Among the regulatory genes that were differentially expressed in the transgenic receptacles were several genes previously linked to flavonoid metabolism, such as MYB10, DIV, ZFN1, ZFN2, GT2, and GT5, or associated with the action of hormones, such as abscisic acid, SHP, ASR, GTE7 and SnRK2.7. The inference of a gene regulatory network, based on a dynamic Bayesian approach, among the genes differentially expressed in the transgenic receptacles at the white and red stages, identified the genes KAN1, DIV, ZFN2 and GTE7 as putative targets of FaMADS9. A MADS9-specific CArG box was identified in the promoters of these genes.

Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells.

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells.

LipidMS: An R Package for Lipid Annotation in Untargeted Liquid Chromatography-Data Independent Acquisition-Mass Spectrometry Lipidomics.

High resolution LC-MS untargeted lipidomics using data independent acquisition (DIA) has the potential to increase lipidome coverage, as it enables the continuous and unbiased acquisition of all eluting ions. However, the loss of the link between the precursor and the product ions combined with the high dimensionality of DIA data sets hinder accurate feature annotation. Here, we present LipidMS, an R package aimed to confidently identify lipid species in untargeted LC-DIA-MS. To this end, LipidMS combines a coelution score, which links precursor and fragment ions with fragmentation and intensity rules. Depending on the MS evidence reached by the identification function survey, LipidMS provides three levels of structural annotations: (i) "subclass level", e.g., PG(34:1); (ii) "fatty acyl level", e.g., PG(16:0_18:1); and (iii) "fatty acyl position level", e.g., PG(16:0/18:1). The comparison of LipidMS with freely available data dependent acquisition (DDA) and DIA identification tools showed that LipidMS provides significantly more accurate and structural informative lipid identifications. Finally, to exemplify the utility of LipidMS, we investigated the lipidomic serum profile of patients diagnosed with nonalcoholic steatohepatitis (NASH), which is the progressive form of nonalcoholic fatty liver disease, a disorder underlying a strong lipid dysregulation. As previously published, a significant decrease in lysophosphatidylcholines, phosphatidylcholines and cholesterol esters and an increase in phosphatidylethanolamines were observed in NASH patients. Remarkably, LipidMS allowed the identification of a new set of lipids that may be used for NASH diagnosis. Altogether, LipidMS has been validated as a tool to assist lipid identification in the LC-DIA-MS untargeted analysis of complex biological samples.

Genetic Architecture and Molecular Networks Underlying Leaf Thickness in Desert-Adapted Tomato Solanum pennellii.

Thicker leaves allow plants to grow in water-limited conditions. However, our understanding of the genetic underpinnings of this highly functional leaf shape trait is poor. We used a custom-built confocal profilometer to directly measure leaf thickness in a set of introgression lines (ILs) derived from the desert tomato Solanum pennellii and identified quantitative trait loci. We report evidence of a complex genetic architecture of this trait and roles for both genetic and environmental factors. Several ILs with thick leaves have dramatically elongated palisade mesophyll cells and, in some cases, increased leaf ploidy. We characterized the thick IL2-5 and IL4-3 in detail and found increased mesophyll cell size and leaf ploidy levels, suggesting that endoreduplication underpins leaf thickness in tomato. Next, we queried the transcriptomes and inferred dynamic Bayesian networks of gene expression across early leaf ontogeny in these lines to compare the molecular networks that pattern leaf thickness. We show that thick ILs share S. pennellii-like expression profiles for putative regulators of cell shape and meristem determinacy as well as a general signature of cell cycle-related gene expression. However, our network data suggest that leaf thickness in these two lines is patterned at least partially by distinct mechanisms. Consistent with this hypothesis, double homozygote lines combining introgression segments from these two ILs show additive phenotypes, including thick leaves, higher ploidy levels, and larger palisade mesophyll cells. Collectively, these data establish a framework of genetic, anatomical, and molecular mechanisms that pattern leaf thickness in desert-adapted tomato.

Multi-sample Arabidopsis Growth and Imaging Chamber (MAGIC) for long term imaging in the ZEISS Lightsheet Z.1.

Time-course imaging experiments on live organisms are critical for understanding the dynamics of growth and development. Light-sheet microscopy has advanced the field of long-term imaging of live specimens by significantly reducing photo-toxicity and allowing fast acquisition of three-dimensional data over time. However, current light-sheet technology does not allow the imaging of multiple plant specimens in parallel. To achieve higher throughput, we have developed a Multi-sample Arabidopsis Growth and Imaging Chamber (MAGIC) that provides near-physiological imaging conditions and allows high-throughput time-course imaging experiments in the ZEISS Lightsheet Z.1. Here, we illustrate MAGIC's imaging capabilities by following cell divisions, as an indicator of plant growth and development, over prolonged time periods. To automatically quantify the number of cell divisions in long-term experiments, we present a FIJI-based image processing pipeline. We demonstrate that plants imaged with our chamber undergo cell divisions for >16 times longer than those with the glass capillary system supplied by the ZEISS Z1.

RpeakChrom: Novel R package for the automated characterization and optimization of column efficiency in high-performance liquid chromatography analysis.

Characterization of chromatographic columns using the traditional van Deemter method is limited by the necessity of calculating extra-column variance, issue particularly relevant when modeling asymmetrical peaks eluted from monolithic columns. A novel R package that implements Parabolic Variance Modified Gaussian approach for accurate peak modeling, van Deemter equation and two alternatives approaches, based on van Deemter, has been developed to calculate the height equivalent to a theoretical plate (HETP). To assess package capabilities conventional packed reverse-phase and monolithic HPLC columns were characterized. Peaks eluted from the monolithic column showed a high value of factor asymmetry due, in part, to the contribution of extra-column factors. Such deviation can be circumvented by the two alternatives approaches implemented in the R-package. Furthermore, increased values of eddy diffusion and mass transfer kinetics terms in HETP were observed for the packed column, while accuracy was below 9% in all cases. These results showed the usefulness of the R-package for both modeling chromatographic peaks and assessing column efficiency. The RpeakChrom package could become a helpful tool for testing new stationary phases during column development and to evaluate column during its lifetime. This R tool is freely available from CRAN (https://CRAN.R-project.org/package=RpeakChrom).

On the Edge of Research and Technological Application: A Critical Review of Electromethanogenesis.

The conversion of electrical current into methane (electromethanogenesis) by microbes represents one of the most promising applications of bioelectrochemical systems (BES). Electromethanogenesis provides a novel approach to waste treatment, carbon dioxide fixation and renewable energy storage into a chemically stable compound, such as methane. This has become an important area of research since it was first described, attracting different research groups worldwide. Basics of the process such as microorganisms involved and main reactions are now much better understood, and recent advances in BES configuration and electrode materials in lab-scale enhance the interest in this technology. However, there are still some gaps that need to be filled to move towards its application. Side reactions or scaling-up issues are clearly among the main challenges that need to be overcome to its further development. This review summarizes the recent advances made in the field of electromethanogenesis to address the main future challenges and opportunities of this novel process. In addition, the present fundamental knowledge is critically reviewed and some insights are provided to identify potential niche applications and help researchers to overcome current technological boundaries.

Co2MnO4/Ce0.8Tb0.2O2-δ Dual-Phase Membrane Material with High CO2 Stability and Enhanced Oxygen Transport for Oxycombustion Processes.

Oxygen transport membranes (OTMs) are a promising oxygen production technology with high energy efficiency due to the potential for thermal integration. However, conventional perovskite materials of OTMs are unstable in CO2 atmospheres, which limits their applicability in oxycombustion processes. On the other hand, some dual-phase membranes are stable in CO2 and SO2 without permanent degradation. However, oxygen permeation is still insufficient; therefore, intensive research focuses on boosting oxygen permeation. Here, we present a novel dual-phase membrane composed of an ion-conducting fluorite phase (Ce0.8Tb0.2O2-δ, CTO) and an electronic-conducting spinel phase (Co2MnO4, CMO). CMO spinel exhibits high electronic conductivity (60 S·cm-1 at 800 °C) compared to other spinels used in dual-phase membranes, i.e., 230 times higher than that of NiFe2O4 (NFO). This higher conductivity ameliorates gas-solid surface exchange and bulk diffusion mechanisms. By activating the bulk membrane with a CMO/CTO porous catalytic layer, it was possible to achieve an oxygen flux of 0.25 mL·min-1·cm-2 for the 40CMO/60CTO (%vol), 680 µm-thick membrane at 850 °C even under CO2-rich environments. This dual-phase membrane shows excellent potential as an oxygen transport membrane or oxygen electrode under high CO2 and oxycombustion operation.

Dubbing language-therapy CINEma-based in aphasia post-stroke (DULCINEA): A feasibility randomized crossover controlled trial.

Background: Helping people recover from aphasia is among the top 10 research priorities relating to life after stroke. Objective: We aimed to evaluate the feasibility of dubbing techniques (using newly developed software) for post-stroke aphasia therapy and explore its potential efficacy. Methods: Randomised, crossover, interventional, feasibility trial that included patients with chronic post-stroke non-fluent aphasia. The intervention consisted of an individualised programme (16 sessions; 8 weeks) based on dubbing words and sentences progressively adapted to the severity of the aphasia. Patients were allocated to groups that underwent therapy within the first 3 months, or between 3 and 6 months from inclusion, each group serving as the control during the non-therapy periods. Outcomes were the pre-post differences in the Communicative Activity Log, the Boston Diagnostic Aphasia Examination, the General Health Questionnaire-12, the Stroke Aphasia Quality of Life Scale, and the Western Aphasia Battery Revised, administered by psychologists blinded to the patients' allocation. Results: Recruitment was limited due to COVID-19 and prematurely stopped because of funding coming to an end. A total of 23 patients were randomised, 20 of whom completed the study (1 withdrew consent, and 2 dropped out). The adherence rate to the allocated group was 95.3%. No statistically significant differences were found in any of the outcomes; however, 17 (85%) patients reported subjective improvements in communication skills. Conclusions: This trial shows the feasibility of dubbing therapy (using dedicated software) for patients with post-stroke non-fluent aphasia. Although it lacks statistical power, certain effects on language and communication cannot be ignored.

Energetics of formation and stability in high pressure steam of barium lanthanide cobaltite double perovskites.

This study concerns energetics of formation and the stability in high water partial pressure of BaLnCo2O6-δ, (Ln = La, Pr, Nd, and Gd) (BLnC) and BaGd1-xLaxCo2O6-δ, where x = 0.2, 0.5, and 0.7 (BGLC) double perovskite cobaltites. Those materials are extensively studied due to their potential applications as a positrode in electrochemical devices. Therefore, their stability under such conditions is a key issue. All investigated materials are thermodynamically stable relative to binary oxides and exhibit strongly exothermic enthalpies of formation. Moreover, BaGd0.3La0.7Co2O6-δ and BaGd0.8La0.2Co2O6-δ remain the main perovskite structure up to 3 bars of water vapor at 400 °C. At higher steam pressure, reaching 10 bar at 300 °C, the partial decomposition to constituent oxides and hydroxides was observed. The BGLC compounds exhibit higher negative formation enthalpies in comparison to single-Ln compositions, which does not translate into higher chemical stability under high steam pressures since the BLnC series retained the main perovskite structure at higher temperatures as well as in higher water vapor pressures.

Evaluation of Er Doped CeO2-δ as Oxygen Transport Membrane.

Ceria based materials are robust candidates for a range of applications involving redox reactions and high oxygen activity. The substitution of erbium in the ceria lattice introduces extrinsic oxygen vacancies. Further addition of Co introduces electronic carriers. We have studied the structural and redox behavior of Ce1-xErxO2-δ (x = 0.1 and 0.2) and the influence of adding 2 mol% of Co in the electrochemical properties. A limitation in the solubility of Er cation is found. Diffusion and surface exchange coefficients have been obtained by electrical conductivity relaxation and the DC-conductivity and O2 permeation measurements show the importance of the electronic component in the transport properties, obtaining an oxygen permeation flux of 0.07 mL·min-1·cm-2 at 1000 °C, for a 769 µm thick membrane.

Structural properties of mixed conductor Ba1-xGd1-yLax+yCo2O6-δ.

Ba1-xGd1-yLax+yCo2O6-δ (BGLC) compositions with large compositional ranges of Ba, Gd, and La have been characterised with respect to phase compositions, structure, and thermal and chemical expansion. The results show a system with large compositional flexibility, enabling tuning of functional properties and thermal and chemical expansion. We show anisotropic chemical expansion and detailed refinements of emerging phases as La is substituted for Ba and Gd. The dominating phase is the double perovskite structure Pmmm, which is A-site ordered along the c-axes and with O vacancy ordering along the b-axis in the Ln-layer. Phases emerging when substituting La for Ba are orthorhombic Ba-deficient Pbnm and cubic LaCoO3-based R3̄c. When La is almost completely substituted for Gd, the material can be stabilised in Pmmm, or cubic Pm3̄m, depending on thermal and atmospheric history. We list thermal expansion coefficients for x = 0-0.3, y = 0.2.

[Post-vaccination antibodies against SARS-CoV-2 in a cohort of workers of a general hospital]. / Anticuerpos postvacunales frente a SARS-CoV-2 en una cohorte de trabajadores de un hospital general.

INTRODUCTION: The aim was to estimate the evolution of the levels of anti-SARS-CoV-2 antibodies, the associated factors, and the incidence of new infections during the follow-up period.  Method: Prospective cohort study of a representative sample of workers at the General University Hospital of Castellon 8 months after receiving the second dose of Pfizer-BioNTech vaccine against SARS-CoV-2, by determining IgG-S, IgG-NP, follow-up and response to a questionnaire. The results were compared with those at the start of the cohort in February 2021. Multivariate linear regression and Poisson regression were used.  Results: A total of 253 workers participated out of the 275 in the start of the cohort. All had detectable levels of IgG-S, median 691% AU/ml, decreasing by 93.3% compared with the first study. The decline of IgG-S increased with age and obesity; and decreased with a COVID-19 previous history, regular exercise, and in smokers. IgG-NP was positively associated with a history of COVID-19, taking vitamin D, and decreased from 4.4% to 1.2%. There were 4 new cases of COVID-19 in the cohort, with and incidence rate of 1.7%. One death occurred in a participant with immunosuppressive treatment, only one case was asymptomatic and no reinfections occurred. CONCLUSIONS: A general decrease of IgG-S and IgG-NP antibodies after the second dose of Pfizer-BioNTech vaccine was observed in the cohort, as well as with new SARS-CoV-2 infections. Booster doses, maintaining protective measures and further determination of the protection threshold of vaccination are recommended.

Introducción: Estimar la evolución de los niveles de anticuerpos anti-SARS-CoV-2 y los factores asociados, así como la incidencia de nuevas infecciones. Método: Estudio de cohorte prospectivo de una muestra representativa de trabajadores del Hospital General Universitario de Castellón a los 8 meses de recibir la 2ª dosis de la vacuna Pfizer-BioNTech contra el SARS-CoV-2, mediante la determinación de anticuerpos IgG-S y IgG-NP, y la cumplimentación de un cuestionario. Se compararon los resultados con los del inicio de la cohorte en febrero de 2021. Se usó regresión lineal múltiple y regresión de Poisson.  Resultados: Participaron 253 trabajadores de los 275 reclutados al inicio de la cohorte (92%). Todos mantenían niveles detectables de IgG-S, mediana de 691,5 UA/ml, disminuyendo un 93,3% con respecto al inicio. Los descensos de IgG-S fueron mayores con la edad y la obesidad, y menores en aquellos con historia de COVID-19, IgG-S elevada inicial, practicar ejercicio habitual y ser fumador. Tener IgG-NP se asoció positivamente con historia de COVID-19, tomar vitamina D, y disminuyeron del 4,4% al 1,2%. Se produjeron 4 casos de COVID-19 en la cohorte, con una tasa de incidencia del 1,7%, con un fallecimiento en un participante con tratamiento inmunosupresor, solo un caso fue asintomático y no hubo reinfecciones.  Conclusiones: Se produce un descenso general de los anticuerpos IgG-S e IgG-NP después de la segunda dosis de vacuna Pfizer-BioNTech, así como nuevas infecciones por SARS-CoV-2. Se recomienda dosis de recuerdo, mantener medidas protectoras y determinar el umbral de anticuerpos protectores de la vacunación.