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Methotrexate successful therapy encounters various challenges in chemotherapy, such as poor oral bioavailability, low specificity, side effects and the development of drug resistances. In this study, it is proposed a dual-targeted nanocarrier comprising magnetite/chitosan nanoparticles for an efficient Methotrexate delivery. The formation of the particles was confirmed through morphological analysis using electron microscopy and elemental mappings via energy dispersive X-ray spectroscopy. These nanoparticles exhibited a size of ≈ 270 nm, a zeta potential of ≈ 24 mV, and magnetic responsiveness, as demonstrated by hysteresis cycle analysis and visual observations under a magnetic field. In addition, these particles displayed high stability, as evidenced by size and surface electric charge measurements, during storage at both 4 ºC and 25 ºC for at least 30 days. Electrophoretic properties were examined in relation to pH and ionic strength, confirming these core/shell nanostructure. The nanoparticles demonstrated a pH-responsive drug release as observed by a sustained Methotrexate release over the next 90 h under pH ≈ 7.4, while complete release occurred within 3 h under acidic conditions (pH ≈ 5.5). In the biocompatibility assessment, the magnetite/chitosan particles showed excellent hemocompatibility ex vivo and no cytotoxic effects on normal MCF-10 A and cancer MCF-7 cells. Furthermore, the Methotrexate-loaded nanoparticles significantly enhanced the antitumor activity reducing the half-maximal inhibitory concentration by ≈ 2.7-fold less compared to the free chemotherapeutic.

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Pseudomonas aeruginosa (P. aeruginosa) is a common nosocomial pathogen that can cause severe infections in critically ill patients. Due to its resistance to multiple drugs, it is challenging to treat, which can result in serious illness and death. Conventional treatments for infected wounds often involve the topical or systemic application of antibiotics, which can lead to systemic toxicity and the development of drug resistance. The combination of wound dressings that promote wound healing with nanoparticles (NPs) represents a revolutionary strategy for optimizing the safety and efficacy of antibiotics. This review assesses a systematic search to identify the latest approaches where the evaluation of wound dressings loaded with antibiotic NPs is conducted. The properties of NPs, the features of wound dressings, the antimicrobial activity and biocompatibility of the different strategies are analyzed. The results indicate that most research in this field is focused on dressings loaded with silver NPs (57.1%) or other inorganic materials (22.4%). Wound dressings loaded with polymeric NPs and carbon-based NPs represent 14.3% and 6.1% of the evaluated studies, respectively. Nevertheless, there are no clinical trials that have evaluated the efficacy of NPs-loaded wound dressings in patients. Further research is required to ensure the safety of these treatments and to translate the findings from the bench to the bedside.

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The effect of plant-based fillers on thermal resistance in highly filled biocomposites based on ethylene-vinyl acetate copolymer (EVA) was studied. Wood flour and microcrystalline cellulose were used as fillers. It was shown that the introduction of microcrystalline cellulose into EVA did not affect the thermal stability of the polymer matrix. In contrast, the introduction of wood flour into EVA led to a significant increase in the thermal stability of the entire biocomposite. Oxidation induction time increased from 0 (pure EVA) to 73 min (EVA + wood flour biocomposites). The low-molecular weight phenolic compounds contained in wood flour are likely able to diffuse into the polymer matrix, exerting a stabilizing effect. The discovered stabilizing effect is a positive development for expanding the possibilities of technological processing of biocomposites, including multiple processing.

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We previously reported that phenyl- and vinyl-silsesquioxanes (SQs), [RSiO1.5]8,10,12 (R = Ph or vinyl) functionalized with three or more conjugated moieties show red-shifted absorption- and emission features suggesting 3-D conjugation via a cage centered LUMOs. Corner missing [PhSiO1.5]7(OSiMe3)3 and edge opened, end capped [PhSiO1.5]8(OSiMe2)2 (double decker, DD) analogs also offer red shifted spectra again indicating 3-D conjugation and a cage centered LUMO. Copolymerization of DD [PhSiO1.5]8(OSiMevinyl)2 with multiple R-Ar-Br gives copolymers with emission red-shifts that change with degree of polymerization (DP), exhibit charge transfer to F4TNCQ and terpolymer averaged red-shifts suggesting through chain conjugation even with two (O-Si-O) end caps possibly via a cage centered LUMO. Surprisingly, ladder (LL) SQ, (vinylMeSiO2)[PhSiO1.5]4(O2SiMevinyl) copolymers offer emission red-shifts even greater for analogous copolymers requiring a different explanation. Here we assess the photophysical behavior of copolymers of a more extreme SQ form: the half cage [PhSiO1.5]4(OSiMe2Vinyl)4, Vy4HC SQs. We again see small red-shifted absorptions coupled with significant red-shifted emissions, even with just a half cage, thus further supporting the existence of pπ-dπ and/or σ*-π* conjugation through Si-O-Si bonds and contrary to most traditional views of Si-O-Si linked polymers. These same copolymers donate an electron to F4TCNQ generating the radical anion, F4TCNQ-. as further proof of conjugation. Column chromatographic separation of short from longer chain oligomers reveals a direct correlation between DP and emission λmax red-shifts as another indication of conjugation. Further, one- and two-photon absorption and emission spectroscopy reveals multiple excited fluorescence-emitting states in a violation of Kasha's rule wherein emission occurs only from the lowest excited state. Traditional modeling studies again find HOMO LUMO energy levels residing only on the aromatic co-monomers rather than through Si-O-Si bonds as recently found in related polymers.

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Acute lymphoblastic leukemia (ALL) is the most prevalent cancer in children, and despite considerable progress in treatment outcomes, relapses still pose significant risks of mortality and long-term complications. To address this challenge, we employed a supervised machine learning technique, specifically random survival forests, to predict the risk of relapse and mortality using array-based DNA methylation data from a cohort of 763 pediatric ALL patients treated in Nordic countries. The relapse risk predictor (RRP) was constructed based on 16 CpG sites, demonstrating c-indexes of 0.667 and 0.677 in the training and test sets, respectively. The mortality risk predictor (MRP), comprising 53 CpG sites, exhibited c-indexes of 0.751 and 0.754 in the training and test sets, respectively. To validate the prognostic value of the predictors, we further analyzed two independent cohorts of Canadian (n = 42) and Nordic (n = 384) ALL patients. The external validation confirmed our findings, with the RRP achieving a c-index of 0.667 in the Canadian cohort, and the RRP and MRP achieving c-indexes of 0.529 and 0.621, respectively, in an independent Nordic cohort. The precision of the RRP and MRP models improved when incorporating traditional risk group data, underscoring the potential for synergistic integration of clinical prognostic factors. The MRP model also enabled the definition of a risk group with high rates of relapse and mortality. Our results demonstrate the potential of DNA methylation as a prognostic factor and a tool to refine risk stratification in pediatric ALL. This may lead to personalized treatment strategies based on epigenetic profiling.

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Fatigue fractures in materials are the main cause of approximately 80% of all material failures, and it is believed that such failures can be predicted and mathematically calculated in a reliable manner. It is possible to establish prediction modalities in cases of fatigue fractures according to three fundamental variables in fatigue, such as volume, number of fracture cycles, as well as applied stress, with the integration of Weibull constants (length characteristic). In this investigation, mechanical fatigue tests were carried out on specimens smaller than 4 mm2, made of different industrial materials. Their subsequent analysis was performed through precision computed tomography, in search for microfractures. The measurement of these microfractures, along with their metrics and classifications, was recorded. A convolutional neural network trained with deep learning was used to achieve the detection of microfractures in image processing. The detection of microfractures in images with resolutions of 480 × 854 or 960 × 960 pixels is the primary objective of this network, and its accuracy is above 95%. Images that have microfractures and those without are classified using the network. Subsequently, by means of image processing, the microfracture is isolated. Finally, the images containing this feature are interpreted using image processing to obtain their area, perimeter, characteristic length, circularity, orientation, and microfracture-type metrics. All values are obtained in pixels and converted to metric units (µm) through a conversion factor based on image resolution. The growth of microfractures will be used to define trends in the development of fatigue fractures through the studies presented.

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Background: Chronic obstructive pulmonary disease (COPD) remains one of the most prevalent pathologies in the world and is among the leading causes of mortality and morbidity, partially due to underdiagnosis. The use of clinical questionnaires to identify high-risk individuals to take them to further diagnostic procedures has emerged as a strategy to address this problem. Objective: To compare the performance of the COULD IT BE COPD, CDQ, COPD-PS, LFQ, and PUMA questionnaires for COPD diagnosis. Methods: A cross-sectional study was carried out on subjects who underwent spirometry in the third-level center. Data were collected between January 2015 and March 2020. Bivariate analysis was performed between the study variables and the presence of COPD. The area under the receiver operating characteristics curve (AUC-ROC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) for each questionnaire were calculated. The AUC-ROCs were compared with the DeLong test, considering a p value <0.05 statistically significant. Results: 681 subjects met the inclusion criteria and were taken to the final analysis. The prevalence of COPD was 27.5% (187/681). The mean age of the subjects was 65.9 years (SD ± 11.79); 46.3% (315/681) were female, and 83.6% (569/681) reported respiratory symptoms. Statistically significant relationship was found for COPD diagnosis with male sex, older age, respiratory symptoms, and exposure to wood smoke (p value <0.05). The AUC-ROCs of the questionnaires were between 0.581 and 0.681. The COULD IT BE COPD questionnaire had a lower discriminatory capacity AUC-ROC of 0.581, concerning the other scores (DeLong test, p = 0.0002). Conclusion: The CDQ, COPD-PS, LFQ, PUMA, and COULD IT BE COPD questionnaires have acceptable performance for the diagnosis of COPD together with low sensitivity and specificity. Therefore, its use must be complemented with other diagnostic tests or techniques such as pulmonary function tests.

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OBJECTIVE: Reducing maternal morbidity and mortality has been a challenge for low and middle-income countries, especially in the setting of hypertensive disorders of pregnancy. Improved strategies for treating obstetric patients with resistant hypertension are needed. We sought to explore whether hemodynamic parameters may be used to identify patients that develop resistant hypertension in pregnancy. METHODS: Retrospective cohort study among pregnant patients with gestational hypertension or preeclampsia that experienced severe blood pressure elevations. Hemodynamic variables were evaluated, including cardiac output (CO), and total peripheral resistance (TPR). The primary endpoint was resistant hypertension. An exploratory logistic regression was performed to evaluate the association between the hemodynamic profile and the development of resistant hypertension. Adverse maternal and fetal outcomes were additionally described according to the presence of resistant hypertension. RESULTS: Fifty-seven patients with severe pregnancy hypertension were included, of whom 34 developed resistant hypertension (59.7%). The resistant hypertension group, in comparison to those without resistant hypertension, presented with a hypodynamic profile characterized by reduced CO < 5 L/min (41.2% vs. 8.7%, p: 0.007), and increased TPR > 1400 dyn-s/cm5 (64.7% vs. 39.1%, p: 0.057). Logistic regression analysis revealed an association between a hypodynamic profile and resistant hypertension (OR 3.252, 95% CI 1.079-9.804; p = 0.035). Newborns of the resistant hypertension group had more frequent low birth weight (<2500 g), low Apgar scores, ICU admissions, and acute respiratory distress syndrome. CONCLUSION: Patients experiencing hypertensive crisis during pregnancy and exhibiting a hypodynamic profile (TPR ≥1400 dyn·s/cm5 and CO ≤ 5 L/min) developed higher rates of resistant hypertension.

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[This corrects the article DOI: 10.3389/fonc.2022.968340.].

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The work environment is a factor that can significantly influence the composition and functionality of the gut microbiota of workers, in many cases leading to gut dysbiosis that will result in serious health problems. The aim of this paper was to provide a compilation of the different studies that have examined the influence of jobs with unconventional work schedules and environments on the gut microbiota of workers performing such work. As a possible solution, probiotic supplements, via modulation of the gut microbiota, can moderate the effects of sleep disturbance on the immune system, as well as restore the dysbiosis produced. Rotating shift work has been found to be associated with an increase in the risk of various metabolic diseases, such as obesity, metabolic syndrome, and type 2 diabetes. Sleep disturbance or lack of sleep due to night work is also associated with metabolic diseases. In addition, sleep disturbance induces a stress response, both physiologically and psychologically, and disrupts the healthy functioning of the gut microbiota, thus triggering an inflammatory state. Other workers, including military, healthcare, or metallurgy workers, as well as livestock farmers or long-travel seamen, work in environments and schedules that can significantly affect their gut microbiota.

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OBJECTIVE: To assess the impact of ambient temperature (AT) on the evolution of bodyweight in patients with heterogeneous types of cancer in advanced stages of the disease (stages III and IV) and anorexia- cachexia syndrome (ACS). METHODS: A prospective naturalistic multicenter study of patients undergoing oncological treatment at four hospitals during a three-year period (2017-2020) in the Autonomous Community of Extremadura in southwestern Spain with a continentalized Mediterranean climate of mild and relatively rainy winters, and particularly hot and sunny summers. Bodyweight changes were obtained from the medical records of 84 oncological patients (59 men and 25 women, age range 37-91 yrs). Mean monthly AT was used to examine the association of weight changes across cold and warm bimesters -BIMs (December and January, vs. July and August), Trimesters -TRIMs (July to September vs. December to February), and Semesters -SEMs (May to October vs. November to April). Weight changes between two consecutive weight measures were categorized as weight gain, weight loss, or no weight change. Differences across cold and warm seasons were analysed using parametric (ANOVA), and nonparametric statistics (Chi-square and binomial z tests). An alpha-rate of 0.05 was used for all analyses. RESULTS: A weight loss trend was observed during BIMs cold periods in comparison to warm ones (p 0.04). However, differences in average bodyweight were not significant. The negative impact of cold periods was more marked in men than in women, (p = 0.05; p = 0.03, for cold vs. warm BIMs and TRIMs, respectively). In contrast, significantly higher weight gain percentages were found in women during warm TRIMs and SEMs (p = 0.03, and p = 0.01, respectively). As for the number of patients dying during the study (N = 56; 39 men, 17 women), there were a significant interaction between temperature (cold/warm), and mean weight F (1, 499) = 6.06, p = 0.01, which revealed a pattern of weight loss in the cold semester as opposed to weight gain during the warm SEM months. CONCLUSIONS: AT temperature modulated body weight changes in patients with advanced oncological disease and ACS. Two main limitations of the study were the absence of information on diets as a moderating factor of weight loss/gain, and the lack of the patients' weight measurements closest to the date of diagnosis prior to admittance to the study. As for the practical implications, it remains to be seen whether an adjunctive heat supply will serve a buffering effect on weight loss during colder seasons for patients with advanced cancer and ACS.

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Chitosan-functionalized magnetite/poly(ε-caprolactone) nanoparticles were formulated by interfacial polymer disposition plus coacervation, and loaded with gemcitabine. That (core/shell)/shell nanostructure was confirmed by electron microscopy, elemental analysis, electrophoretic, and Fourier transform infrared characterizations. A short-term stability study proved the protection against particle aggregation provided by the chitosan shell. Superparamagnetic properties of the nanoparticles were characterized in vitro, while the definition of the longitudinal and transverse relaxivities was an initial indication of their capacity as T2 contrast agents. Safety of the particles was demonstrated in vitro on HFF-1 human fibroblasts, and ex vivo on SCID mice. The nanoparticles demonstrated in vitro pH- and heat-responsive gemcitabine release capabilities. In vivo magnetic resonance imaging studies and Prussian blue visualization of iron deposits in tissue samples defined the improvement in nanoparticle targeting into the tumor when using a magnetic field. This tri-stimuli (magnetite/poly(ε-caprolactone))/chitosan nanostructure could find theranostic applications (biomedical imaging & chemotherapy) against tumors.

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Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recurrence. We hypothesized that combining features from structured and unstructured sources would provide better prediction results for 5-year cancer recurrence than either source alone. We collected and preprocessed clinical data from a cohort of BC patients, resulting in 823 valid subjects for analysis. We derived three sets of features: structured information, features from free text, and a combination of both. We evaluated the performance of five ML algorithms to predict 5-year cancer recurrence and selected the best-performing to test our hypothesis. The XGB (eXtreme Gradient Boosting) model yielded the best performance among the five evaluated algorithms, with precision = 0.900, recall = 0.907, F1-score = 0.897, and area under the receiver operating characteristic AUROC = 0.807. The best prediction results were achieved with the structured dataset, followed by the unstructured dataset, while the combined dataset achieved the poorest performance. ML algorithms for BC recurrence prediction are valuable tools to improve patient risk stratification, help with post-cancer monitoring, and plan more effective follow-up. Structured data provides the best results when fed to ML algorithms. However, an approach based on natural language processing offers comparable results while potentially requiring less mapping effort.

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Diffuse Large B-cell Lymphoma (DLBCL) is the most common type of aggressive lymphoma. Approximately 60% of fit patients achieve curation with immunochemotherapy, but the remaining patients relapse or have refractory disease, which predicts a short survival. Traditionally, risk stratification in DLBCL has been based on scores that combine clinical variables. Other methodologies have been developed based on the identification of novel molecular features, such as mutational profiles and gene expression signatures. Recently, we developed the LymForest-25 profile, which provides a personalized survival risk prediction based on the integration of transcriptomic and clinical features using an artificial intelligence system. In the present report, we studied the relationship between the molecular variables included in LymForest-25 in the context of the data released by the REMoDL-B trial, which evaluated the addition of bortezomib to the standard treatment (R-CHOP) in the upfront setting of DLBCL. For this, we retrained the machine learning model of survival on the group of patients treated with R-CHOP (N=469) and then made survival predictions for those patients treated with bortezomib plus R-CHOP (N=459). According to these results, the RB-CHOP scheme achieved a 30% reduction in the risk of progression or death for the 50% of DLBCL patients at higher molecular risk (p-value 0.03), potentially expanding the effectiveness of this treatment to a wider patient population as compared with other previously defined risk groups.

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OBJECTIVES: Prostate health index (PHI) is a predictive biomarker of positive prostate biopsy. The majority of evidence refers to its use in the PSA gray zone (4-10 ng/mL) and negative digital rectal exam (DRE). We aim to evaluate and compare the predictive accuracy of PHI and PHI density (PHId) with PSA, percentage of free PSA and PSA density, in a wider range of patients for the detection of clinically significant prostate cancer (csPCa). METHODS: Multicenter prospective study that included patients suspicious of harboring prostate cancer. Non-probabilistic convenience sampling, where men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate and compare diagnostic accuracy AUC and decision curve analysis (DCA) were calculated. All these procedures were performed for the overall sample and the following subsamples: PSA < 4 ng/ml; PSA 4-10 ng/ml; PSA 4-10 ng/ml plus negative DRE and PSA > 10 ng/ml. RESULTS: Among the 559 men included, 194 (34.7%) were diagnosed of csPCa. PHI and PHId outperfomed PSA in all subgroups. PHI best diagnostic performance was found in PSA 4-10 ng/ml with negative DRE (sensitivity 93.33, NPV 96.04). Regarding AUC, significant differences were found between PHId and PSA in the subgroup of PSA 4-10 ng/ml, whatever DRE status. In DCA, PHI density shows the highest net benefit. CONCLUSIONS: PHI and PHId outperfom PSA in csPCa detection, not only in the PSA grey zone with negative DRE, but also in a wider range of PSA values. There is an urgent need of prospective studies to established a validated threshold and its incorporation in risk calculators.

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To evaluate associations between the domains of the ANCA-associated vasculitis patient-reported outcome (AAV-PRO) instrument and clinical variables. Patients with granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), eosinophilic granulomatosis with polyangiitis (EGPA), or renal-limited vasculitis (RLV) were recruited from a tertiary care center in Mexico City. Demographic, clinical, serological, and treatment-related data were retrieved. Disease activity, damage, patient and physician global assessments (PtGA and PhGA) were evaluated. All patients completed the AAV-PRO questionnaire, male patients also completed the International Index of Erectile Function (IIEF-5) questionnaire. Seventy patients (44 women and 26 men) were included, with a median age of 53.5 years (43-61), and a disease duration of 82 months (34-135). Moderate correlations were identified between the PtGA and the AAV-PRO domains: social and emotional impact, treatment side effects, organ-specific symptoms, and physical function. The PhGA correlated with the PtGA and prednisone doses. Subanalyses of the AAV-PRO domains according to sex, age, and disease duration showed significant differences in the treatment side effects domain, with higher scores in women, in patients < 50 years, and in patients with disease duration < 5 years. The domain of concerns about the future showed a higher score in patients with disease duration < 5 years. A total of 17/24 (70.8%) of men who completed the IIEF-5 questionnaire were classified as having some degree of erectile dysfunction. The domains of AAV-PRO correlated with other outcome measures, while differences were found between some of the domains according to sex, age, and disease duration.

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Licariaramiroi, a species endemic to western Mexico, is described and illustrated. The ascription of the new species to Licaria is analysed. It is classified in the subgen. Licaria and is most closely related to L.triandra and L.siphonantha from which it differs by its glabrous vegetative and floral structures, stamens mainly with free anthers and the inner wall of the receptacle sericeous. According to the IUCN criteria, the species is classified as critically endangered.

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Introducción: La fibromialgia (FM) es un trastorno complejo que genera impacto en la salud pública. Son escasos los estudios que determinan el sufrimiento en FM, pues el abordaje se enfoca en el dolor. Objetivo: Estimar la prevalencia de sufrimiento en los pacientes con FM y su asociación con el impacto en calidad de vida, malestar emocional, soledad, eventos vitales y aspectos clínicos y sociodemográficos en una institución de salud privada de Medellín (Colombia). Método: Se realizó un estudio transversal, en una institución especializada en manejo de dolor crónico. Se evaluó el grado de sufrimiento (PRISM), nivel de dolor (EVA), impacto de la FM (FIQR), soledad (UCLA), ansiedad y depresión (HADS), eventos vitales estresantes (CSV) y las características sociodemográficas y clínicas. Se planteó un modelo explicativo con una regresión logística. Resultados: El 55,5 % IC95 (50,0-61,1) presentó sufrimiento intenso. Se obtuvo un modelo explicativo, donde el impacto en la calidad de vida, la depresión y la toma de analgésicos fueron los factores más relevantes en el sufrimiento intenso. Discusión: Los pacientes con FM manifiestan un sufrimiento importante que debe ser atendido por el personal de salud. Si bien el dolor es un elemento relevante, existen otros factores a los que debe prestarse atención, como el impacto que causa la enfermedad en la persona y la depresión asociada.(AU)

Introduction: Fibromyalgia (FM) is a complex disorder with significant impact on public health. Few studies have explored suffering in FM, since its approach focuses on pain management. Objective: To estimate the prevalence of suffering in patients with FM and its association with impact on quality of life, emotional distress, loneliness, vital stress and clinical and sociodemographic factors in a private healthcare institution in Medellín (Colombia). Method: A cross-sectional study was conducted in an institution specialized in chronic pain management. The degree of suffering (PRISM), level of pain (EVA), impact of FM (FIQR), loneliness (UCLA), anxiety and depression (HADS), stressful life events (CSV) and sociodemographic and clinical characteristics were evaluated. An explanatory model was proposed using logistic regression. Results: 55.5 % IC95 (50,0-61,1) presented intense suffering. An explanatory model was obtained, where impact, depression and analgesic intake were the most relevant factors in intense suffering.Discussion: Patients with FM manifest an important suffering that should be attended by health personnel. Although pain is a relevant element, there are other factors to which attention should be paid, such as the impact of the disease on the person and the associated depression.(AU)

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BACKGROUND: Although there has developed an increased interest in the vaccines BNT1622b2 (Pfizer/BioNTech), mRNA-1273 (Moderna/NIAID), and ChAdOx1 nCoV-19 (AstraZeneca/University of Oxford), there are still few reports describing the immune response induced by different vaccine platforms in real-world settings of low-income countries. Here, we proposed to analyse the humoral immune response elicited by the primary vaccines used in Argentina from July-December 2021. METHODS: Anti-SARS-CoV-2-Spike-RBD IgG and neutralising antibodies were assayed by ELISA in a total of 871 serum samples obtained from 376 volunteers from an educational staff. The individuals were vaccinated with BBIBP-CorV (Sinopharm), ChAdOx1 nCoV-19 (AstraZeneca/University of Oxford, AZ), Gam-COVID-Vac (Sputnik V, SpV) or combined vaccines (mostly SpV and mRNA-1273, Moderna). The antibody response was analysed several days after the initial vaccination (20, 40, 120 and 180 days). RESULTS: After receiving at least one dose of the COVID-19 vaccine, we detected 93.34% of seroprevalence. Previously SARS-CoV-2 infected showed higher antibody concentrations compared with naïve vaccinees. Six months after the initial vaccination, combined vaccination induced higher anti-SARS-CoV-2 antibody levels than the other vaccines in naïve volunteers. However, we did not find differences in the neutralising responses after any vaccine from naïve vaccines or between the naïve and previously infected volunteers on day 120 after vaccination. CONCLUSIONS: Our long-term analysis of volunteers from the educational system provides data in a real-world context, showing the benefits of a boost dose still in previously infected volunteers, and suggesting the advantages of a heterologous prime-boost schedule.

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