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Antibody detection is essential to establish exposure, infection, and immunity to SARS-CoV-2, as well as to perform epidemiological studies. The worldwide urge for new diagnostic tools to control the pandemic has led to a quick incorporation in clinical practice of the recently developed serological assays. However, as only few comparative studies have been published, there is a lack of data about the diagnostic accuracy of currently available assays. We evaluated the diagnostic accuracy to detect Ig G, Ig M+A, and/or IgA anti SARS-CoV-2 of 10 different assays: lateral flow card immunoassays, 4 enzyme-linked immunosorbent assay (ELISA), and 3 chemiluminescent particle immunoassays (CMIA). Using reverse transcriptase polymerase chain reaction (RT-PCR) for COVID-19 as gold standard, sensitivity, specificity, PPV, and NPV were determined. Each assay was tested in 2 groups, namely, positive control, formed by 50 sera from 50 patients with SARS-CoV-2 pneumonia with positive RT-PCR; and negative control, formed by 50 sera from 50 patients with respiratory infection non-COVID-19. Sensitivity range of the 10 assays evaluated for patients with positive COVID-19 RT-PCR was 40–77% (65–81% considering IgG plus IgM). Specificity ranged 83–100%. VPP and VPN were respectively 81–100% and 61.6–81%. Among the lateral flow immunoassays, the highest sensitivity and specificity results were found in Wondfo® SARS-CoV-2 Antibody Test. ELISA IgG and IgA from EUROIMMUN® were the most sensitive ELISA. However, poor results were obtained for isolated detection of IgG. We found similar sensitivity for IgG with SARS-CoV-2 for Architect by Abbott® and ELISA by Vircell®. Results obtained varied widely among the assays evaluated. Due to a better specificity, overall diagnostic accuracy of the assays evaluated was higher in case of positive result. On the other side, lack of antibody detection should be taken with care because of the low sensitivity described. Highest diagnostic accuracy was obtained with ELISA and CMIAs, but they last much longer.

Mycobacterium abscessus (MABS) is an emerging pathogen causing severe infections, particularly in cystic fibrosis (CF) patients. A prospective multicentre study included CF patients from four hospitals in Madrid between January 2022 and January 2024. Respiratory samples were collected, and MABS isolates were analysed to determine their antibiotic resistance profiles, growth dynamics, infection kinetics, intracellular behaviour, and pathogenicity. Intracellular bacterial growth and macrophage viability were evaluated through THP-1 cell infection experiments, with and without amikacin. Phenotypic susceptibility testing and genotypic susceptibility testing were also conducted. Among 148 patients, 28 MABS isolates were detected from 16 patients (10.8%), and the first isolate from each patient was analysed. Isolation was more prevalent in younger individuals (median age 24.4 vs. 28.4 years, p = 0.049), and most isolates (81.25%) were identified as M. abscessus subsp. abscessus (MABSa) . MABS isolates exhibited high resistance rates (>85%) to doxycycline, tobramycin, ciprofloxacin, moxifloxacin (75%) and cotrimoxazole (56.3%). Amikacin resistance (18.8%) was higher than expected, and inducible (10/16 isolates) or acquired (1/16 isolate) macrolide resistance was found in 68.8% of strains. Phenotypic and genotypic testing results were fully concordant. Tigecycline demonstrated strong in vitro activity, and resistance to imipenem, linezolid, and cefoxitin remained low. Rough strains displayed lower optical density values in later growth stages, probably due to their increased aggregation. In THP-1 cell infection experiments, rough strains showed higher intracellular bacterial loads with statistically significant differences observed at 2 hours (both with and without amikacin) and at 72 hours (with amikacin) post infection. Notably, rough strains also exhibited a higher internalisation index and greater impact on THP-1 cell viability, especially in the absence of amikacin.

Mycobacterium abscessus is an opportunistic, extensively drug-resistant non-tuberculous mycobacterium. Few genomic studies consider its diversity in persistent infections. Our aim was to characterize microevolution/reinfection events in persistent infections. Fifty-three sequential isolates from 14 patients were sequenced to determine SNV-based distances, assign resistance mutations and characterize plasmids. Genomic analysis revealed 12 persistent cases (0-13 differential SNVs), one reinfection (15,956 SNVs) and one very complex case (23 sequential isolates over 192 months), in which a first period of persistence (58 months) involving the same genotype 1 was followed by identification of a genotype 2 (76 SNVs) in 6 additional alternating isolates; additionally, ten transient genotypes (88-243 SNVs) were found. A macrolide resistance mutation was identified from the second isolate. Despite high diversity, the genotypes shared a common phylogenetic ancestor and some coexisted in the same specimens. Genomic analysis is required to access the true intra-patient complexity behind persistent infections involving M. abscessus . Mycobacterium abscessus is considered an emerging pathogen, given its prevalence in patients with pulmonary diseases, such as cystic fibrosis. Here, authors perform a genomic analysis on sequential isolates obtained from patients with persistent infections of M. abscessus .

Chimeric antigen receptor (CAR) T-cell therapy has shown significant success in treating diffuse large B-cell lymphoma (DLBCL). The initial step involves collecting autologous CD3 + lymphocytes through apheresis, in which obtaining an adequate CD3 + cell yield is essential for therapeutic efficacy. Despite prior research, the factors influencing CD3 + cell apheresis remain poorly understood. Traditional statistical analyses offer limited insights, but machine learning (ML) approaches enable precision modeling of clinical predictors owing to their advanced pattern-recognition capabilities. In this study, we employed three ML algorithms, random forest classifier (RF), logistic regression (LR), and extreme gradient boosting (XGBoost) to analyze a homogeneous cohort of 98 DLBCL patients who underwent mononuclear cell (MNC) apheresis. The LR model, which achieved an area under the curve (AUC) of 0.824, identified four key predictive features: CD3 + cell absolute count, NK cell percentage, total blood volume, and CD3 + cell percentage. Among these, NK cell percentage and CD3 + cell absolute count showed the most significant negative impact on CD3 + cell apheresis yield. This study underscores the potential of ML approaches as a complementary analytical approach for identifying key factors that impact CD3 + cell apheresis efficiency, offering valuable insights for optimizing CAR-T therapy outcomes in patients with DLBCL.

Background Plasmodium vivax malaria is characterized by the presence of dormant liver-stage parasites, called hypnozoites, which can cause malaria relapses after an initial attack. Primaquine, which targets liver hypnozoites, must be used in combination with a schizonticidal agent to get the radical cure. However, relapses can sometimes occur in spite of correct treatment, due to different factors such as a diminished metabolization of primaquine. Case presentation In January 2019, a 21 years old woman with residence in Madrid, returning from a trip to Venezuela with clinical symptoms compatible with malaria infection, was diagnosed with vivax malaria. Chloroquine for 3 days plus primaquine for 14 days was the elected treatment. Two months later and after a second trip to Venezuela, the patient presented a second P. vivax infection, which was treated as the previous one. A third P. vivax malaria episode was diagnosed 2 months later, after returning from a trip to Morocco, receiving chloroquine for 3 days but increasing to 28 days the primaquine regimen, and with no more relapses after 6 months of follow up. The genotyping of P. vivax in the three malaria episodes revealed that the same strain was present in the different relapses. Upon confirmation of correct adherence to the treatment, non-description of resistance in the infection area and the highly unlikely re-infection on subsequent trips or stays in Spain, a possible metabolic failure was considered. CYP2D6 encodes the human cytochrome P450 isoenzyme 2D6 (CYP2D6), responsible for primaquine activation. The patient was found to have a CYP2D6* 4/*1 genotype, which turns out in an intermediate metabolizer phenotype, which has been related to P. vivax relapses. Conclusions The impairment in CYP2D6 enzyme could be the most likely cause of P. vivax relapses in this patient. This highlights the importance of considering the analysis of CYP2D6 gene polymorphisms in cases of P. vivax relapses after a correct treatment and, especially, it should be considered in any study of dosage and duration of primaquine treatment.

Positron emission tomography (PET) imaging of Aβ plaques, is recognized as a tool for the diagnosis of Alzheimer’s disease. As a contribution to the development of new strategies for early diagnosis of the disease, using PET medical imaging technique, a new copper complex, the [Cu(TE1PA-ONO)] + was synthesized in ten steps. The key step of our strategy is the coupling of a monopicolinate-N-alkylated cyclam-based ligand with a moiety capable of recognizing Aβ plaques via a successful and challenging Buchwald-Hartwig coupling reaction. To our knowledge, it is the first time that such a strategy is used to functionalize polyazamacrocyclic derivatives. The thermodynamic stability constants determined in MeOH/H 2 O solvent indicate that the attachment of this moiety does not weaken the chelating properties of TE1PA-ONO ligand in relation to parent HTE1PA. The novel complex described here is able to recognize amyloid plaques in brain sections from Alzheimer's disease patients and shows low toxicity to human neuronal cells. Graphical abstract

The characteristics of the host are crucial in the final outcome of COVID-19. Herein, the influence of genetic and clinical variants in COVID-19 severity was investigated in a total of 1350 patients. Twenty-one single nucleotide polymorphisms of genes involved in SARS-CoV-2 sensing as Toll-like-Receptor 7, antiviral immunity as the type I interferon signalling pathway ( TYK2, STAT1, STAT4, OAS1, SOCS ) and the vasoactive intestinal peptide and its receptors ( VIP/VIPR1,2 ) were studied. To analyse the association between polymorphisms and severity, a model adjusted by age, sex and different comorbidities was generated by ordinal logistic regression. The genotypes rs8108236-AA (OR 0.12 [95% CI 0.02–0.53]; p  = 0.007) and rs280519-AG (OR 0.74 [95% CI 0.56–0.99]; p  = 0.03) in TYK2 , and rs688136-CC (OR 0.7 [95% CI 0.5–0.99]; p  = 0.046) in VIP, were associated with lower severity; in contrast, rs3853839-GG in TLR7 (OR 1.44 [95% CI 1.07–1.94]; p  = 0.016), rs280500-AG (OR 1.33 [95% CI 0.97–1.82]; p  = 0.078) in TYK2 and rs1131454-AA in OAS1 (OR 1.29 [95% CI 0.95–1.75]; p  = 0.110) were associated with higher severity. Therefore, these variants could influence the risk of severe COVID-19.

Mycobacterium abscessus (MABS) is an emerging pathogen causing severe infections, particularly in cystic fibrosis (CF) patients. A prospective multicentre study included CF patients from four hospitals in Madrid between January 2022 and January 2024. Respiratory samples were collected, and MABS isolates were analysed to determine their antibiotic resistance profiles, growth dynamics, infection kinetics, intracellular behaviour, and pathogenicity. Intracellular bacterial growth and macrophage viability were evaluated through THP-1 cell infection experiments, with and without amikacin. Phenotypic susceptibility testing and genotypic susceptibility testing were also conducted. Among 148 patients, 28 MABS isolates were detected from 16 patients (10.8%), and the first isolate from each patient was analysed. Isolation was more prevalent in younger individuals (median age 24.4 vs. 28.4 years, p = 0.049), and most isolates (81.25%) were identified as M. abscessus subsp. abscessus (MABSa). MABS isolates exhibited high resistance rates (>85%) to doxycycline, tobramycin, ciprofloxacin, moxifloxacin (75%) and cotrimoxazole (56.3%). Amikacin resistance (18.8%) was higher than expected, and inducible (10/16 isolates) or acquired (1/16 isolate) macrolide resistance was found in 68.8% of strains. Phenotypic and genotypic testing results were fully concordant. Tigecycline demonstrated strong in vitro activity, and resistance to imipenem, linezolid, and cefoxitin remained low. Rough strains displayed lower optical density values in later growth stages, probably due to their increased aggregation. In THP-1 cell infection experiments, rough strains showed higher intracellular bacterial loads with statistically significant differences observed at 2 hours (both with and without amikacin) and at 72 hours (with amikacin) post infection. Notably, rough strains also exhibited a higher internalisation index and greater impact on THP-1 cell viability, especially in the absence of amikacin.

Abstract Background Staphylococcus aureus is the leading cause of prosthetic joint infection (PJI). Beyond the antibiogram, little attention has been paid to the influence of deep microbiological characteristics on patient prognosis. Our aim was to investigate whether microbiological genotypic and phenotypic features have a significant influence on infection pathogenesis and patient outcome. Methods A prospective multicenter study was performed, including all S. aureus PJIs (2016–2017). Clinical data and phenotypic (agr functionality, β-hemolysis, biofilm formation) and genotypic characteristics of the strains were collected. Biofilm susceptibility to antimicrobials was investigated (minimal biofilm eradication concentration [MBEC] assay). Results Eighty-eight patients (39.8% men, age 74.7 ± 14.1 years) were included. Forty-five had early postoperative infections (EPIs), 21 had chronic infections (CPIs), and 19 had hematogenous infections (HIs). Twenty (22.7%) were caused by methicillin-resistant S. aureus. High genotypic diversity was observed, including 16 clonal complexes (CCs), with CC5 being the most frequent (30.7%). agr activity was greater in EPI than CPI (55.6% vs 28.6%; P = .041). Strains causing EPI were phenotypically and genotypically similar, regardless of symptom duration. Treatment failure (36.5%) occurred less frequently among cases treated with implant removal. In cases treated with debridement and implant retention, there were fewer failures among those who received combination therapy with rifampin. No genotypic or phenotypic characteristics predicted failure, except vancomycin minimal inhibitory concentration ≥1.5 mg/L (23.1% failure vs 3.4%; P = .044). MBEC50 was >128 mg/L for all antibiotics tested and showed no association with prognosis. Conclusions S. aureus with different genotypic backgrounds is capable of causing PJI, showing slight differences in clinical presentation and pathogenesis. No major microbiological characteristics were observed to influence the outcome, including MBEC.

COVID-19 has overloaded national health services worldwide. Thus, early identification of patients at risk of poor outcomes is critical. Our objective was to analyse SARS-CoV-2 RNA detection in serum as a severity biomarker in COVID-19. Retrospective observational study including 193 patients admitted for COVID-19. Detection of SARS-CoV-2 RNA in serum (viremia) was performed with samples collected at 48–72 h of admission by two techniques from Roche and Thermo Fischer Scientific (TFS). Main outcome variables were mortality and need for ICU admission during hospitalization for COVID-19. Viremia was detected in 50–60% of patients depending on technique. The correlation of Ct in serum between both techniques was good (intraclass correlation coefficient: 0.612; p < 0.001). Patients with viremia were older (p = 0.006), had poorer baseline oxygenation (PaO 2 /FiO 2 ; p < 0.001), more severe lymphopenia (p < 0.001) and higher LDH (p < 0.001), IL-6 (p = 0.021), C-reactive protein (CRP; p = 0.022) and procalcitonin (p = 0.002) serum levels. We defined \"relevant viremia\" when detection Ct was < 34 with Roche and < 31 for TFS. These thresholds had 95% sensitivity and 35% specificity. Relevant viremia predicted death during hospitalization (OR 9.2 [3.8–22.6] for Roche, OR 10.3 [3.6–29.3] for TFS; p < 0.001). Cox regression models, adjusted by age, sex and Charlson index, identified increased LDH serum levels and relevant viremia (HR = 9.87 [4.13–23.57] for TFS viremia and HR = 7.09 [3.3–14.82] for Roche viremia) as the best markers to predict mortality. Viremia assessment at admission is the most useful biomarker for predicting mortality in COVID-19 patients. Viremia is highly reproducible with two different techniques (TFS and Roche), has a good consistency with other severity biomarkers for COVID-19 and better predictive accuracy.