Detection of organochlorine pesticides in infertile eggs of crocodylus acutus from sinaloa.

Environmental contaminants endanger human health and non-target organisms such as crocodiles (Crocodylus acutus) that live in aquatic bodies surrounding agricultural areas. Due to their intrinsic characteristics, these organisms could be bioaccumulating and transmitting organochlorine pesticides (OCs) to their eggs. The objectives of this study were to determine the OCs in infertile eggs of C. acutus from Sinaloa and their correlation with the morphometric characteristics (MC), and to perform a preliminary estimate of the ecological risk due to the presence of pesticides using the PERPEST model. In June 2022, 76 infertile eggs (Ie) were collected: 57 from wild areas (Wa) and 19 from a crocodile farm (CSMf). Determination of OC in Ie was performed according to the USEPA method 8081b, modified. The observed percentages of Ie in Wa were 31.48% and 21.33% in CSMf. Twenty OCs were detected in the Ie, where dieldrin recorded the highest average concentration in Wa (6542.6 ng/g), and endosulfan-II in the CSMf (2172.8 ng/g). Bad negative and positive correlations were observed between OCs and MC, standing out the correlations between endosulfan-II and %Ie (-0.688) in the Wa, Cedritos drain, and between endrin and the weight of Ie (0.786) of the CSMf. The evaluation of the ecological risks of the aquatic environment due to the presence of OCs follow the sequence cyclodienes > aromatic > alicyclic hydrocarbons. A potential risk to the endocrine health of the species C. acutus was observed. Crocodiles are excellent biological models for monitoring the effects of OCs.

A novel method for continuous measurements of clinical practice guideline adherence.

Introduction: Clinical practice guidelines (hereafter 'guidelines') are crucial in providing evidence-based recommendations for physicians and multidisciplinary teams to make informed decisions regarding diagnostics and treatment in various diseases, including cancer. While guideline implementation has been shown to reduce (unwanted) variability and improve outcome of care, monitoring of adherence to guidelines remains challenging. Real-world data collected from cancer registries can provide a continuous source for monitoring adherence levels. In this work, we describe a novel structured approach to guideline evaluation using real-world data that enables continuous monitoring. This method was applied to endometrial cancer patients in the Netherlands and implemented through a prototype web-based dashboard that enables interactive usage and supports various analyses. Method: The guideline under study was parsed into clinical decision trees (CDTs) and an information standard was drawn up. A dataset from the Netherlands Cancer Registry (NCR) was used and data items from both instruments were mapped. By comparing guideline recommendations with real-world data an adherence classification was determined. The developed prototype can be used to identify and prioritize potential topics for guideline updates. Results: CDTs revealed 68 data items for recording in an information standard. Thirty-two data items from the NCR were mapped onto information standard data items. Four CDTs could sufficiently be populated with NCR data. Conclusion: The developed methodology can evaluate a guideline to identify potential improvements in recommendations and the success of the implementation strategy. In addition, it is able to identify patient and disease characteristics that influence decision-making in clinical practice. The method supports a cyclical process of developing, implementing and evaluating guidelines and can be scaled to other diseases and settings. It contributes to a learning healthcare cycle that integrates real-world data with external knowledge.

Maternal transmission of bacterial microbiota during embryonic development in a viviparous lizard.

IMPORTANCE: We investigated the presence and diversity of bacteria in the embryos of the viviparous lizard Sceloporus grammicus and their amniotic environment. We compared this diversity to that found in the maternal intestine, mouth, and cloaca. We detected bacterial DNA in the embryos, albeit with a lower bacterial species diversity than found in maternal tissues. Most of the bacterial species detected in the embryos were also found in the mother, although not all of them. Interestingly, we detected a high similarity in the composition of bacterial species among embryos from different mothers. These findings suggest that there may be a mechanism controlling the transmission of bacteria from the mother to the embryo. Our results highlight the possibility that the interaction between maternal bacteria and the embryo may affect the development of the lizards.

DNA metabarcoding reveals seasonal changes in diet composition across four arthropod-eating lizard species (Phrynosomatidae: Sceloporus).

Diet composition and its ecological drivers are rarely investigated in coexisting closely related species. We used a molecular approach to characterize the seasonal variation in diet composition in four spiny lizard species inhabiting a mountainous ecosystem. DNA metabarcoding revealed that the lizards Sceloporus aeneus, S. bicanthalis, S. grammicus, and S. spinosus mostly consumed arthropods of the orders Hemiptera, Araneae, Hymenoptera, and Coleoptera. The terrestrial lizards S. aeneus and S. bicanthalis mostly predated ants and spiders, whereas the arboreal-saxicolous S. grammicus and saxicolous S. spinosus largely consumed grasshoppers and leafhoppers. The taxonomic and phylogenetic diversity of the prey was higher during the dry season than the rainy season, likely because reduced prey availability in the dry season forced lizards to diversify their diets to meet their nutritional demands. Dietary and phylogenetic composition varied seasonally depending on the species, but only dietary composition varied with altitude. Seasonal dietary turnover was greater in S. spinosus than in S. bicanthalis, suggesting site-specific seasonal variability in prey availability; no other differences among species were observed. S. bicanthalis, which lives at the highest altitude in our study site, displayed interseasonal variation in diet breadth. Dietary differences were correlated with the species' feeding strategies and elevational distribution, which likely contributed to the coexistence of these lizard species in the studied geographic area and beyond.

Measuring Motivation Using the Progressive Ratio Task in Adolescent Mice.

Alterations in reward seeking are a hallmark of multiple psychiatric disorders, including substance abuse and depression. One important aspect of reward seeking is 'wanting', which can be operationalized in both humans and rodents in tasks such as the progressive ratio, in which an increasing amount of work is required to earn a given reward. Importantly, many disorders with reward-seeking deficits are believed to have an important neurodevelopmental component, underscoring the importance of being able to study changes in motivation across the lifespan. Although this task has been adapted for both adult and adolescent rats, in mice it has predominantly been used to assay motivational changes in adults. Specific concerns in adapting this task from adult to adolescent mice include (1) optimizing a food restriction paradigm suitable for growing animals whose weights are naturally dynamically changing and (2) identifying task conditions that allow younger, smaller mice to perform the task while minimizing the length of the behavioral shaping required to measure motivation at specific developmental dates. Toward that end, we now report a protocol for appropriate weight management in developing animals that require food restriction, and a protocol for behavioral shaping and progressive ratio testing in adolescent mice, including an assessment of whether the animals perform better with lever presses or nose pokes as the required operant response. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Food restriction and weight management in the context of developing mice Alternate Protocol: Food restriction and weight management of developing mice without projected growth chart: Utilization of baseline mice Basic Protocol 2: Operant box design, progressive ratio training, testing, and data analysis in adolescent mice.

Mimotope discovery as a tool to design a vaccine against Zika and dengue viruses.

Vaccine development against dengue virus is challenging because of the antibody-dependent enhancement of infection (ADE), which causes severe disease. Consecutive infections by Zika (ZIKV) and/or dengue viruses (DENV), or vaccination can predispose to ADE. Current vaccines and vaccine candidates contain the complete envelope viral protein, with epitopes that can raise antibodies causing ADE. We used the envelope dimer epitope (EDE), which induces neutralizing antibodies that do not elicit ADE, to design a vaccine against both flaviviruses. However, EDE is a discontinuous quaternary epitope that cannot be isolated from the E protein without other epitopes. Utilizing phage display, we selected three peptides that mimic the EDE. Free mimotopes were disordered and did not elicit an immune response. After their display on adeno-associated virus (AAV) capsids (VLP), they recovered their structure and were recognized by an EDE-specific antibody. Characterization by cryo-EM and enzyme-linked immunosorbent assay confirmed the correct display of a mimotope on the surface of the AAV VLP and its recognition by the specific antibody. Immunization with the AAV VLP displaying one of the mimotopes induced antibodies that recognized ZIKV and DENV. This work provides the basis for developing a Zika and dengue virus vaccine candidate that will not induce ADE.

A federated approach to identify women with early-stage cervical cancer at low risk of lymph node metastases.

OBJECTIVE: Lymph node metastases (pN+) in presumed early-stage cervical cancer negatively impact prognosis. Using federated learning, we aimed to develop a tool to identify a group of women at low risk of pN+, to guide the shared decision-making process concerning the extent of lymph node dissection. METHODS: Women with cervical cancer between 2005 and 2020 were identified retrospectively from population-based registries: the Danish Gynaecological Cancer Database, Swedish Quality Registry for Gynaecologic Cancer and Netherlands Cancer Registry. Inclusion criteria were: squamous cell carcinoma, adenocarcinoma or adenosquamous carcinoma; The International Federation of Gynecology and Obstetrics 2009 IA2, IB1 and IIA1; treatment with radical hysterectomy and pelvic lymph node assessment. We applied privacy-preserving federated logistic regression to identify risk factors of pN+. Significant factors were used to stratify the risk of pN+. RESULTS: We included 3606 women (pN+ 11%). The most important risk factors of pN+ were lymphovascular space invasion (LVSI) (odds ratio [OR] 5.16, 95% confidence interval [CI], 4.59-5.79), tumour size 21-40 mm (OR 2.14, 95% CI, 1.89-2.43) and depth of invasion>10 mm (OR 1.81, 95% CI, 1.59-2.08). A group of 1469 women (41%)-with tumours without LVSI, tumour size ≤20 mm, and depth of invasion ≤10 mm-had a very low risk of pN+ (2.4%, 95% CI, 1.7-3.3%). CONCLUSION: Early-stage cervical cancer without LVSI, a tumour size ≤20 mm and depth of invasion ≤10 mm, confers a low risk of pN+. Based on an international privacy-preserving analysis, we developed a useful tool to guide the shared decision-making process regarding lymph node dissection.

First confirmation of importation and transmission in Spain of the newly identified SARS-CoV-2 B.1.1.7 variant.

INTRODUCTION: A newly identified SARS-CoV-2 variant, VOC202012/01 originating lineage B.1.1.7, recently emerged in the United Kingdom. The rapid spread in the UK of this new variant has caused other countries to be vigilant. MATERIAL AND METHODS: We based our initial screening of B.1.1.7 on the dropout of the S gene signal in the TaqPath assay, caused by the 69/70 deletion. Subsequently, we confirmed the B.1.1.7 candidates by whole genome sequencing. RESULTS: We describe the first three imported cases of this variant from London to Madrid, subsequent post-arrival household transmission to three relatives, and the two first cases without epidemiological links to UK. One case required hospitalization. In all cases, drop-out of gene S was correctly associated to the B.1.1.7 variant, as all the corresponding sequences carried the 17 lineage-marker mutations. CONCLUSION: The first identifications of the SARS-CoV-2 B.1.1.7 variant in Spain indicate the role of independent introductions from the UK coexisting with post-arrival transmission in the community, since the early steps of this new variant in our country.

Global Emergence of Resistance to Fluconazole and Voriconazole in Candida parapsilosis in Tertiary Hospitals in Spain During the COVID-19 Pandemic.

Background: Candida parapsilosis is a frequent cause of candidemia worldwide. Its incidence is associated with the use of medical implants, such as central venous catheters or parenteral nutrition. This species has reduced susceptibility to echinocandins, and it is susceptible to polyenes and azoles. Multiple outbreaks caused by fluconazole-nonsusceptible strains have been reported recently. A similar trend has been observed among the C. parapsilosis isolates received in the last 2 years at the Spanish Mycology Reference Laboratory. Methods: Yeast were identified by molecular biology, and antifungal susceptibility testing was performed using the European Committee on Antimicrobial Susceptibility Testing protocol. The ERG11 gene was sequenced to identify resistance mechanisms, and strain typing was carried out by microsatellite analysis. Results: We examined the susceptibility profile of 1315 C. parapsilosis isolates available at our reference laboratory between 2000 and 2021, noticing an increase in the number of isolates with acquired resistance to fluconazole, and voriconazole has increased in at least 8 different Spanish hospitals in 2020-2021. From 121 recorded clones, 3 were identified as the most prevalent in Spain (clone 10 in Catalonia and clone 96 in Castilla-Leon and Madrid, whereas clone 67 was found in 2 geographically unrelated regions, Cantabria and the Balearic Islands). Conclusions: Our data suggest that concurrently with the coronavirus disease 2019 pandemic, a selection of fluconazole-resistant C. parapsilosis isolates has occurred in Spain, and the expansion of specific clones has been noted across centers. Further research is needed to determine the factors that underlie the successful expansion of these clones and their potential genetic relatedness.

An Improved Infrastructure for Privacy-Preserving Analysis of Patient Data.

Incorporating healthcare data from different sources is crucial for a better understanding of patient (sub)populations. However, data centralization raises concerns about data privacy and governance. In this work, we present an improved infrastructure that allows privacy-preserving analysis of patient data: vantage6 v3. For this new version, we describe its architecture and upgraded functionality, which allows algorithms running at each party to communicate with one another through a virtual private network (while still being isolated from the public internet to reduce the risk of data leakage). This allows the execution of different types of algorithms (e.g., multi-party computation) that were practically infeasible before, as showcased by the included examples. The (continuous) development of this type of infrastructure is fundamental to meet the current and future demands of healthcare research with a strong emphasis on preserving the privacy of sensitive patient data.

Historical analysis of an imperiled fish species: environmental variables modeling, biotic interactions, extirpation, and current restricted-range.

BACKGROUND: Analyses of spatial and temporal patterns and interactions are important for determining the abiotic factors limiting populations and the impact from other species and different anthropogenic stressors that promote the extirpation of species. The fish Hubbsina turneri de Buen (1940) was studied as a model species in a historical context at varying locations. Originally distributed only in the Lerma-Chapala basin, the main lake complex in Mexico, this species has not been collected from Lake Cuitzeo (LC) and now is restricted to Lake Zacapu (LZ). At present, the Highland splitfin is classified as critically endangered. METHODS: Historical information of LC and historical and current information from LZ were explored by applying cluster analysis and generalized additive mixed model (GAMM) to describe the biotic interactions among fish species and the relationship between density and environmental variables, respectively. The two lakes' contrasting abiotic/biotic characteristics provided elements to describe some species distribution limits in chemical ion gradients. Extirpation calendar dates were estimated using an optimal linear estimation method. Finally, a bibliographic review was conducted on the causes that promoted the extirpation and restriction of H. turneri and the prognosis for its reestablishment and conservation. RESULTS: Clusters showed the fishes relationship according to their distribution along the lakes. GAMM indicated that high H. turneri density is related to low hardness/fecal coliforms, medium depth/suspended solids, and high oxygen concentration. Estimated extirpation dates were between the years 2013 and 2018. The extirpation was linked to an abrupt drop in the LC volume, water quality degradation, increased biotic interactions within macrophytes habitats with native and introduced species, and fisheries bycatches. The current restricted range of H. turneri resulted from the draining of the larger lake, forcing the remaining populations to small spring-fed remnants. Recent samplings in LZ resulted in a low number of individuals. CONCLUSIONS: The integration of ecological interactions derived from statistical models, extirpation dates from nonparametric tests, and the exhaustive analysis of historical information can be applied to define the current situation of imperiled, ecologically relevant species, in different aquatic ecosystems. We are confident that this general framework is important for determining (1) the requirements and limitations of populations regarding abiotic variables, (2) biotic interactions (trophic and spatial) with native and introduced species, and (3) different anthropogenic stressors within and around the ecosystem. This knowledge will also allow understanding those aspects that contribute to the extirpation of populations and could help the restoration of the habitat and the reintroduction of extirpated species.

Complete Genome Characterization of Reticuloendotheliosis Virus Detected in Chickens with Multiple Viral Coinfections.

Reticuloendotheliosis virus (REV) is a retroviral pathogen capable of infecting several avian hosts and is associated with immunosuppression, anemia, proventriculitis, neoplasia, and runting-stunting syndrome. Its genome contains the three major genes, gag, pol, and env, and two flanking long terminal repeat (LTR) regions. Complete genome sequences of REV are limited in terms of geographical origin. The aim of this study was to characterize the complete genome of REV detected in Brazilian chickens with multiple viral coinfections and analyze the polymorphisms in the deduced amino acids sequences corresponding to its encoded proteins. We tested the presence and completeness of REV as well as other viral pathogens in samples from Brazilian poultry farms by qPCR. The complete genomes of two REV strains were sequenced by overlapping fragments through the dideoxy method. Phylogenetic analysis, pairwise identity matrix, polymorphism identification and protein modeling were performed along the entire genome. We detected REV in 65% (26/40) of the tested samples. Concomitant viral infections were detected in 82.5% (33/40) of the samples and in 90% (9/10) of the farms. Multiple infections included up to seven viruses. Phylogenetic analysis classified both Brazilian strains into REV subtype 3, and the pairwise comparison indicated that strains from the USA and fowlpox virus (FWPV)-related strains were the most identical. The subdomain p18 in gag, the reverse transcriptase/ribonuclease H in pol, and the surface (SU) in the env protein were the most polymorphic in genomic comparisons. The relevant motifs for each protein were highly conserved, with fewer polymorphisms in the fusion peptide, immunosuppression domain, and disulfide bonds on the surface (SU) and transmembrane (TM) of env. This is the first study to include complete genomes of REV in Brazil and South America detected in farms with multiple viral coinfections. Our findings suggest an involvement of REV as an immunosuppressor and active agent in the emergence and progression of multiple infectious diseases. We also found a possible etiological relationship between Brazilian strains and the USA and FWPV recombinant strains. This information highlights the need for epidemiological vigilance regarding REV in association with another pathogens.

A case report of transmission and disease caused by Mycobacterium caprae and Mycobacterium bovis in Lima, Peru.

BACKGROUND: The Tuberculosis (TB) burden in Peru is significant with respect to both disease morbidity and mortality. Furthermore the recent diversification of farming enterprise to include a wide range of animal species has necessitated the consideration of members of the Mycobacterium Tuberculosis Complex (MTBC) with the potential for zoonotic transmission. M. bovis and M. caprae, a lesser known member of the MTBC exhibit an exceptionally wide host spectrum in animals and are capable of causing disease in humans. M. bovis has a predictable resistance profile which includes resistance to pyrazinamide. Thus, failure to identify M. bovis as the causative agent in reported TB cases leads to higher levels of treatment failure and contributes to the transmission of drug-resistant TB. CASE PRESENTATION: Reported here are the clinical presentations, investigations and treatment histories of two patients identified from a population level genotyping study in Lima, Peru that were at the time of treatment thought to be M. tuberculosis patients but in retrospect were spectated using whole genome sequencing as M. caprae and M. Bovis. CONCLUSIONS: The cases reported here constitute convincing evidence that M. caprae and M. bovis are causative agents of TB infection in humans in Peru and underscore the importance of species-level MTBC member identification to effectively control and treat zoonotic TB. Furthermore these cases highlight the challenges of using clinical risk factors to identify cases of zoonotic TB in humans as their clinical presentation and transmission history is often difficult to distinguish from anthroponotic TB.

Conversion of a High-Altitude Temperate Forest for Agriculture Reduced Alpha and Beta Diversity of the Soil Fungal Communities as Revealed by a Metabarcoding Analysis.

Land-use change is one of the most important drivers of change in biodiversity. Deforestation for grazing or agriculture has transformed large areas of temperate forest in the central highlands of Mexico, but its impact on soil fungal communities is still largely unknown. In this study, we determined how deforestation of a high-altitude temperate forest for cultivation of maize (Zea mays L.) or husbandry altered the taxonomic, phylogenetic, functional, and beta diversity of soil fungal communities using a 18S rRNA metabarcoding analysis. The true taxonomic and phylogenetic diversity at order q = 1, i.e., considering frequent operational taxonomic units, decreased significantly in the arable, but not in the pasture soil. The beta diversity decreased in the order forest > pasture > arable soil. The ordination analysis showed a clear effect of intensity of land-use as the forest soil clustered closer to pasture than to the arable soil. The most abundant fungal phyla in the studied soils were Ascomycota, Basidiomycota, and Mucoromycota. Deforestation more than halved the relative abundance of Basidiomycota; mostly Agaricomycetes, such as Lactarius and Inocybe. The relative abundance of Glomeromycota decreased in the order pasture > forest > arable soil. Symbiotrophs, especially ectomycorrhizal fungi, were negatively affected by deforestation while pathotrophs, especially animal pathogens, were enriched in the pasture and arable soil. Ectomycorrhizal fungi were more abundant in the forest soil as they are usually associated with conifers. Arbuscular mycorrhizal fungi were more abundant in the pasture than in the arable soil as the higher plant diversity provided more suitable hosts. Changes in fungal communities resulting from land-use change can provide important information for soil management and the assessment of the environmental impact of deforestation and conversion of vulnerable ecosystems such as high-altitude temperate forests.

Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival.

Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in oncology. Recently, several machine learning (ML) techniques have been adapted for this task. Although they have shown to yield results at least as good as classical methods, they are often disregarded because of their lack of transparency and little to no explainability, which are key for their adoption in clinical settings. In this paper, we used data from the Netherlands Cancer Registry of 36,658 non-metastatic breast cancer patients to compare the performance of CPH with ML techniques (Random Survival Forests, Survival Support Vector Machines, and Extreme Gradient Boosting [XGB]) in predicting survival using the [Formula: see text]-index. We demonstrated that in our dataset, ML-based models can perform at least as good as the classical CPH regression ([Formula: see text]-index [Formula: see text]), and in the case of XGB even better ([Formula: see text]-index [Formula: see text]). Furthermore, we used Shapley Additive Explanation (SHAP) values to explain the models' predictions. We concluded that the difference in performance can be attributed to XGB's ability to model nonlinearities and complex interactions. We also investigated the impact of specific features on the models' predictions as well as their corresponding insights. Lastly, we showed that explainable ML can generate explicit knowledge of how models make their predictions, which is crucial in increasing the trust and adoption of innovative ML techniques in oncology and healthcare overall.

First confirmation of importation and transmission in Spain of the newly identified SARS-CoV-2 B.1.1.7 variant.

INTRODUCTION: A newly identified SARS-CoV-2 variant, VOC202012/01 originating lineage B.1.1.7, recently emerged in the United Kingdom. The rapid spread in the UK of this new variant has caused other countries to be vigilant. MATERIAL AND METHODS: We based our initial screening of B.1.1.7 on the dropout of the S gene signal in the TaqPath assay, caused by the 69/70 deletion. Subsequently, we confirmed the B.1.1.7 candidates by whole genome sequencing. RESULTS: We describe the first three imported cases of this variant from London to Madrid, subsequent post-arrival household transmission to three relatives, and the two first cases without epidemiological links to UK. One case required hospitalization. In all cases, drop-out of gene S was correctly associated to the B.1.1.7 variant, as all the corresponding sequences carried the 17 lineage-marker mutations. CONCLUSION: The first identifications of the SARS-CoV-2 B.1.1.7 variant in Spain indicate the role of independent introductions from the UK coexisting with post-arrival transmission in the community, since the early steps of this new variant in our country.

Heterogeneity in Quality of Life of Long-Term Colon Cancer Survivors: A Latent Class Analysis of the Population-Based PROFILES Registry.

BACKGROUND: Long-term colon cancer survivors present heterogeneous health-related quality of life (HRQOL) outcomes. We determined unobserved subgroups (classes) of survivors with similar HRQOL patterns and investigated their stability over time and the association of clinical covariates with these classes. MATERIALS AND METHODS: Data from the population-based PROFILES registry were used. Included were survivors with nonmetastatic (TNM stage I-III) colon cancer (n = 1,489). HRQOL was assessed with the Dutch translation of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 version 3.0. Based on survivors' HRQOL, latent class analysis (LCA) was used to identify unobserved classes of survivors. Moreover, latent transition analysis (LTA) was used to investigate changes in class membership over time. Furthermore, the effect of covariates on class membership was assessed using multinomial logistic regression. RESULTS: LCA identified five classes at baseline: class 1, excellent HRQOL (n = 555, 37.3%); class 2, good HRQOL with prevalence of insomnia (n = 464, 31.2%); class 3, moderate HRQOL with prevalence of fatigue (n = 213, 14.3%); class 4, good HRQOL with physical limitations (n = 134, 9.0%); and class 5, poor HRQOL (n = 123, 8.3%). All classes were stable with high self-transition probabilities. Longer time since the diagnosis, no comorbid conditions, and male sex were associated with class 1, whereas older age was associated with class 4. Clinical covariates were not associated with class membership. CONCLUSION: The identified classes are characterized by distinct patterns of HRQOL and can support patient-centered care. LCA and LTA are powerful tools for investigating HRQOL in cancer survivors. IMPLICATIONS FOR PRACTICE: Long-term colon cancer survivors show great heterogeneity in their health-related quality of life. This study identified five distinct clusters of survivors with similar patterns of health-related quality of life and showed that these clusters remain stable over time. It was also shown that these clusters do not significantly differ in tumor characteristics or received treatment. Cluster membership of long-term survivors can be identified by sociodemographic characteristics but is not predetermined by diagnosis and treatment.

Evaluation of diagnostic accuracy of 10 serological assays for detection of SARS-CoV-2 antibodies.

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.

IL-6 serum levels predict severity and response to tocilizumab in COVID-19: An observational study.

BACKGROUND: Patients with coronavirus disaese 2019 (COVID-19) can develop a cytokine release syndrome that eventually leads to acute respiratory distress syndrome requiring invasive mechanical ventilation (IMV). Because IL-6 is a relevant cytokine in acute respiratory distress syndrome, the blockade of its receptor with tocilizumab (TCZ) could reduce mortality and/or morbidity in severe COVID-19. OBJECTIVE: We sought to determine whether baseline IL-6 serum levels can predict the need for IMV and the response to TCZ. METHODS: A retrospective observational study was performed in hospitalized patients diagnosed with COVID-19. Clinical information and laboratory findings, including IL-6 levels, were collected approximately 3 and 9 days after admission to be matched with preadministration and postadministration of TCZ. Multivariable logistic and linear regressions and survival analysis were performed depending on outcomes: need for IMV, evolution of arterial oxygen tension/fraction of inspired oxygen ratio, or mortality. RESULTS: One hundred forty-six patients were studied, predominantly males (66%); median age was 63 years. Forty-four patients (30%) required IMV, and 58 patients (40%) received treatment with TCZ. IL-6 levels greater than 30 pg/mL was the best predictor for IMV (odds ratio, 7.1; P < .001). Early administration of TCZ was associated with improvement in oxygenation (arterial oxygen tension/fraction of inspired oxygen ratio) in patients with high IL-6 (P = .048). Patients with high IL-6 not treated with TCZ showed high mortality (hazard ratio, 4.6; P = .003), as well as those with low IL-6 treated with TCZ (hazard ratio, 3.6; P = .016). No relevant serious adverse events were observed in TCZ-treated patients. CONCLUSIONS: Baseline IL-6 greater than 30 pg/mL predicts IMV requirement in patients with COVID-19 and contributes to establish an adequate indication for TCZ administration.

The Microbial Composition in Circumneutral Thermal Springs from Chignahuapan, Puebla, Mexico Reveals the Presence of Particular Sulfur-Oxidizing Bacterial and Viral Communities.

Terrestrial thermal springs are widely distributed globally, and these springs harbor a broad diversity of organisms of biotechnological interest. In Mexico, few studies exploring this kind of environment have been described. In this work, we explore the microbial community in Chignahuapan hot springs, which provides clues to understand these ecosystems' diversity. We assessed the diversity of the microorganism communities in a hot spring environment with a metagenomic shotgun approach. Besides identifying similarities and differences with other ecosystems, we achieved a systematic comparison against 11 metagenomic samples from diverse localities. The Chignahuapan hot springs show a particular prevalence of sulfur-oxidizing bacteria from the genera Rhodococcus, Thermomonas, Thiomonas, Acinetobacter, Sulfurovum, and Bacillus, highlighting those that are different from other recovered bacterial populations in circumneutral hot springs environments around the world. The co-occurrence analysis of the bacteria and viruses in these environments revealed that within the Rhodococcus, Thiomonas, Thermonas, and Bacillus genera, the Chignahuapan samples have specific species of bacteria with a particular abundance, such as Rhodococcus erytropholis. The viruses in the circumneutral hot springs present bacteriophages within the order Caudovirales (Siphoviridae, Myoviridae, and Podoviridae), but the family of Herelleviridae was the most abundant in Chignahuapan samples. Furthermore, viral auxiliary metabolic genes were identified, many of which contribute mainly to the metabolism of cofactors and vitamins as well as carbohydrate metabolism. Nevertheless, the viruses and bacteria present in the circumneutral environments contribute to the sulfur cycle. This work represents an exhaustive characterization of a community structure in samples collected from hot springs in Mexico and opens opportunities to identify organisms of biotechnological interest.