Application of ecotoxicological tools to evaluate the quality status of mangroves under restoration in the Yucatán Peninsula, Mexico.

Ecotoxicological tools, namely biomarkers and bioassays, may provide insights on the ecological quality status of mangroves under restoration. We investigated how 1) physicochemical parameters and water bioassays using Artemia franciscana; and 2) quantification of sublethal (osmoregulatory capacity, biochemical, and oxidative stress) and individual biomarkers (density, length-weight relationship [LWR], parasitic prevalence) in the sentinel fiddler crab Minuca rapax, can improve restoration indicators in mangroves from the Yucatán Peninsula, Southern Gulf of Mexico. We showed that water quality was improved with restoration, but still presented toxicity. Regarding sublethal biomarkers, M rapax from restored areas lower osmotic regulatory capacity, higher oxidative stress, and showed lipid peroxidation. As to the individual biomarkers, the density, LWR, and the prevalence of parasites in M. rapax was higher in restored areas. The use of bioassays/biomarkers were useful as early warning indicators to better assess the health of mangroves under restoration.

Exploring Gluten Assessment in Marketed Products through a Sandwich ELISA Methodology Based on Novel Recombinant Antibodies.

This study presents the development of a sandwich ELISA method for gluten detection in foods, using recombinant Fab antibody fragments against gliadin. The Fabs were chemically biotinylated and immobilized on streptavidin-coated plates as capture antibodies, while alkaline phosphatase-conjugated Fabs were used as detection antibodies. Four different gliadin-binding Fabs were tested and the Fab pair Fab8E-4 and Fab-C showed the best compatibility. An indirect sandwich immunoassay, using unmodified Fab8E-4 for capture and Fab-C as the detection antibody, achieved a detection limit of 26 ng/mL of gliadin, corresponding to 10 mg/kg of gluten in foods. No cross-reactivity was observed against 60 gluten-free species commonly used in the food industry. Analysis of 50 commercial products demonstrated consistent results compared to the standard method for gluten detection. The complete lack of cross-reactivity of the developed immunoassay with oat products potentially provides an advantage over other gluten detection systems.

Predicting major adverse cardiovascular events after orthotopic liver transplantation using a supervised machine learning model: A cohort study.

BACKGROUND: Liver transplant (LT) patients have become older and sicker. The rate of post-LT major adverse cardiovascular events (MACE) has increased, and this in turn raises 30-d post-LT mortality. Noninvasive cardiac stress testing loses accuracy when applied to pre-LT cirrhotic patients. AIM: To assess the feasibility and accuracy of a machine learning model used to predict post-LT MACE in a regional cohort. METHODS: This retrospective cohort study involved 575 LT patients from a Southern Brazilian academic center. We developed a predictive model for post-LT MACE (defined as a composite outcome of stroke, new-onset heart failure, severe arrhythmia, and myocardial infarction) using the extreme gradient boosting (XGBoost) machine learning model. We addressed missing data (below 20%) for relevant variables using the k-nearest neighbor imputation method, calculating the mean from the ten nearest neighbors for each case. The modeling dataset included 83 features, encompassing patient and laboratory data, cirrhosis complications, and pre-LT cardiac assessments. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC). We also employed Shapley additive explanations (SHAP) to interpret feature impacts. The dataset was split into training (75%) and testing (25%) sets. Calibration was evaluated using the Brier score. We followed Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for reporting. Scikit-learn and SHAP in Python 3 were used for all analyses. The supplementary material includes code for model development and a user-friendly online MACE prediction calculator. RESULTS: Of the 537 included patients, 23 (4.46%) developed in-hospital MACE, with a mean age at transplantation of 52.9 years. The majority, 66.1%, were male. The XGBoost model achieved an impressive AUROC of 0.89 during the training stage. This model exhibited accuracy, precision, recall, and F1-score values of 0.84, 0.85, 0.80, and 0.79, respectively. Calibration, as assessed by the Brier score, indicated excellent model calibration with a score of 0.07. Furthermore, SHAP values highlighted the significance of certain variables in predicting postoperative MACE, with negative noninvasive cardiac stress testing, use of nonselective beta-blockers, direct bilirubin levels, blood type O, and dynamic alterations on myocardial perfusion scintigraphy being the most influential factors at the cohort-wide level. These results highlight the predictive capability of our XGBoost model in assessing the risk of post-LT MACE, making it a valuable tool for clinical practice. CONCLUSION: Our study successfully assessed the feasibility and accuracy of the XGBoost machine learning model in predicting post-LT MACE, using both cardiovascular and hepatic variables. The model demonstrated impressive performance, aligning with literature findings, and exhibited excellent calibration. Notably, our cautious approach to prevent overfitting and data leakage suggests the stability of results when applied to prospective data, reinforcing the model's value as a reliable tool for predicting post-LT MACE in clinical practice.

Diagnosing Alzheimer's disease: Which dementia screening test to use in elderly Puerto Ricans with mild cognitive impairment and early Alzheimer's disease?

Typically, Alzheimer's disease (AD) diagnosis is not made at its earliest period, for instance, at mild cognitive impairment (MCI) and early AD (E-AD). Our study aims to demonstrate a correlation between the screening tools, including the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Clinical Dementia Rating (CDR), and the biological biomarkers in the cerebrospinal fluid (CSF) amyloid beta 1-42 (Aß42), phosphorylated tau (p-tau) proteins and total tau (t-tau)/Aß42 ratio in Puerto Ricans > 55 years old with MCI and E-AD. We evaluated 30 participants, including demographics, memory scales, and CSF biomarkers. Twenty-eight CSF biomarkers (Aß42, p-tau protein, and t-tau/Aß42 ratio) were analyzed using the Meso Scale Discovery Platform (MSD). Associations between memory scales (MoCA, MMSE, CDR) and CSF markers were performed using Spearman rho correlation. Our study revealed a statistical association favoring a direct relationship between MMSE and MoCA with t-tau/Aß42 ratio in CSF (P = 0.022, P = 0.035, respectively). We found a trend toward significance with an inverse relationship with MMSE and Aß42 (P = 0.069) and a direct relationship with MMSE and p-tau (P = 0.098). MMSE and MoCA screening tests were identified with a statistically significant association with the CSF biomarkers, specifically t-tau/Aß42 ratio, in elderly Puerto Ricans with MCI and E-AD. Puerto Ricans > 55 years old with MCI and E-AD could be screened confidently with MMSE and MoCA for a higher likelihood of earlier detection and, thus, initiation of disease-modifying treatment and prompt non-pharmacological interventions.

Comprehensive study reveals phenotypic heterogeneity in Klebsiella pneumoniae species complex isolates.

Here, we conducted a comprehensive analysis of 356 Klebsiella pneumoniae species complex (KpSC) isolates that were classified as classical (cl), presumptive hypervirulent (p-hv) and hypermucoviscous-like (hmv-like). Overall, K. pneumoniae (82.3%), K. variicola (2.5%) and K. quasipneumoniae (2.5%) were identified. These isolates comprised 321 cl-KpSC, 7 p-hv-KpSC and 18 hmv-like-KpSC. A large proportion of cl-KpSC isolates were extended-spectrum-ß-lactamases (ESBLs)-producers (64.4%) and 3.4% of isolates were colistin-resistant carrying carbapenemase and ESBL genes. All p-hv-KpSC showed an antibiotic susceptible phenotype and hmv-like isolates were found to be ESBL-producers (8/18). Assays for capsule production and capsule-dependent virulence phenotypes and whole-genome sequencing (WGS) were performed in a subset of isolates. Capsule amount differed in all p-hv strains and hmv-like produced higher capsule amounts than cl strains; these variations had important implications in phagocytosis and virulence. Murine sepsis model showed that most cl strains were nonlethal and the hmv-like caused 100% mortality with 3 × 108 CFUs. Unexpectedly, 3/7 (42.9%) of p-hv strains required 108 CFUs to cause 100% mortality (atypical hypervirulent), and 4/7 (57.1%) strains were considered truly hypervirulent (hv). Genomic analyses confirmed the diverse population, including isolates belonging to hv clonal groups (CG) CG23, CG86, CG380 and CG25 (this corresponded to the ST3999 a novel hv clone) and MDR clones such as CG258 and CG147 (ST392) among others. We noted that the hmv-like and hv-ST3999 isolates showed a close phylogenetic relationship with cl-MDR K. pneumoniae. The information collected here is important to understand the evolution of clinically important phenotypes such as hypervirulent and ESBL-producing-hypermucoviscous-like amongst the KpSC in Mexican healthcare settings. Likewise, this study shows that mgrB inactivation is the main mechanism of colistin resistance in K. pneumoniae isolates from Mexico.

Clinical practice guidelines for the diagnosis and management of Charcot-Marie-Tooth disease.

INTRODUCTION: Charcot-Marie-Tooth disease (CMT) is classified according to neurophysiological and histological findings, the inheritance pattern, and the underlying genetic defect. The objective of these guidelines is to offer recommendations for the diagnosis, prognosis, follow-up, and treatment of this disease in Spain. MATERIAL AND METHODS: These consensus guidelines were developed through collaboration by a multidisciplinary panel encompassing a broad group of experts on the subject, including neurologists, paediatric neurologists, geneticists, physiatrists, and orthopaedic surgeons. RECOMMENDATIONS: The diagnosis of CMT is clinical, with patients usually presenting a common or classical phenotype. Clinical assessment should be followed by an appropriate neurophysiological study; specific recommendations are established for the parameters that should be included. Genetic diagnosis should be approached sequentially; once PMP22 duplication has been ruled out, if appropriate, a next-generation sequencing study should be considered, taking into account the limitations of the available techniques. To date, no pharmacological disease-modifying treatment is available, but symptomatic management, guided by a multidiciplinary team, is important, as is proper rehabilitation and orthopaedic management. The latter should be initiated early to identify and improve the patient's functional deficits, and should include individualised exercise guidelines, orthotic adaptation, and assessment of conservative surgeries such as tendon transfer. The follow-up of patients with CMT is exclusively clinical, and ancillary testing is not necessary in routine clinical practice.

Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations.

Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that is most prevalent in Northern Europe. Although it is known that inherited risk for MS is located within or in close proximity to immune-related genes, it is unknown when, where and how this genetic risk originated1. Here, by using a large ancient genome dataset from the Mesolithic period to the Bronze Age2, along with new Medieval and post-Medieval genomes, we show that the genetic risk for MS rose among pastoralists from the Pontic steppe and was brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the steppe population and later in Europe, probably driven by pathogenic challenges coinciding with changes in diet, lifestyle and population density. This study highlights the critical importance of the Neolithic period and Bronze Age as determinants of modern immune responses and their subsequent effect on the risk of developing MS in a changing environment.

In your CORT: Corticosterone and its receptors in the brain underlie mate choosiness in female Cope's gray treefrogs (Hyla chrysoscelis).

Selecting an attractive mate can involve trade-offs related to investment in sampling effort. Glucocorticoids like corticosterone (CORT) are involved in resolving energetic trade-offs. However, CORT is rarely studied in the context of mate choice, despite its elevated levels during reproductive readiness and the energetic transitions that characterize reproduction. Few systems are as well suited as anuran amphibians to evaluate how females resolve energetic trade-offs during mate choice. Phonotaxis tests provide a robust bioassay of mate choice that permit the precise measurement of inter-individual variation in traits such as choosiness-the willingness to pursue the most attractive mate despite costs. In Cope's gray treefrogs (Hyla chrysoscelis), females exhibit remarkable variation in circulating CORT as well as choosiness during mate choice, and a moderate dose of exogenous CORT rapidly (<1 h) and reliably induce large increases in choosiness. Here we measured the expression of glucocorticoid (GR) and mineralocorticoid (MR) receptors in the brains of females previously treated with exogenous CORT and tested for mate choosiness. We report a large decrease in GR expression in the hindbrain and midbrain of females that were treated with the moderate dosage of CORT-the same treatment group that exhibited a dramatic increase in choosiness following CORT treatment. This association, however, does not appear to be causal, as only forebrain GR levels, which are not affected by CORT injection, are positively associated with variation in choosiness. No strong effects were found for MR. We discuss these findings and suggest future studies to test the influence of glucocorticoids on mate choice.

Salinity and sedimentation rate influences on the community structure of polychaetes associated with two sympatric congeneric oyster species.

This study focused on spatial-temporal variations in the composition and structure of polychaete communities associated with two coexisting oyster species in a southern Gulf of Mexico coastal lagoon, showed that Crassostrea rhizophorae hosted 23 polychaete species and C. virginica only four. The observed variability was mainly explained by differences in salinity and sedimentation rate, two factors that also influenced the host species distribution. The highest values of richness and diversity occurred at C. rhizophorae sites during the rainy season, coinciding with increased salinity and a decrease in sedimentation rate. The shell-borer species Nereis garwoodi and Polydora websteri occurred in both oysters, but showing higher frequencies in C. virginica during the Nortes season (i.e., the cold fronts season). Our results underscore the contrasting diversity of associated polychaetes with two coexisting oyster species and emphasize the need for considering additional environmental parameters to allow better understanding of the factors that are driving the structure of these communities.

Inherited SCN1A missense mutation in a Dravet Syndrome family: Neuropathological correlation, family screening and implications for adult carriers.

INTRODUCTION: Neuropathological findings in Dravet Syndrome (DS) are scarce, especially in adult patients, and often do not have a genetic confirmation. Additionally, the missense SCN1A pathogenic variant found has only been described as de novo mutation in previous literature. METHODS: We describe the clinical and genetic findings of a family (including three sisters and his father), using Sanger sequencing in the three sisters and in postmortem brain tissue in the father. The present study also shows the neuropathological findings of the father. RESULTS: Despite the presence of long term drug resistant epilepsy, starting with febrile seizures between 6 and 12 months of age, and intellectual disability (ID), the three sisters were diagnosed with DS in adulthood, identifying a missense SCN1A pathogenic variant in exon 20, previously described as de novo -p.Gly1332Glu (c .3995 G>A). The oldest sister had the most severe phenotype, with severe ID and wheel chair dependency, passing away at 52. The other two sisters had a moderate phenotype, being at the present seizure free, but with significant comorbidities, such as crouch gait and parkinsonism. Several relatives from the paternal path (including the father) presented epilepsy, but without ID. The father was diagnosed with Alzheimer´s Disease (AD) at 60, and because he donated his brain, the same variant was confirmed in postmortem study. Neither the MRI nor the histopathology showed specific morphological changes for DS, consistent with previous studies. CONCLUSIONS: This work supports the need to review the clinical and genetic spectra of DS in adults with epilepsy and unknown ID. The clinical consequences of this syndrome seem to have a functional rather than a structural basis, supported by the absence of specific neuropathological findings.

Performance of eight predictive models for hepatocellular carcinoma recurrence after liver transplantation: A comparative study.

INTRODUCTION AND OBJECTIVES: Liver transplantation is the optimal treatment for patients with early hepatocellular carcinoma and cirrhosis. However, hepatocellular carcinoma recurs in approximately 15 % of individuals. This study aimed to assess the efficacy of predictive models for hepatocellular carcinoma recurrence after liver transplantation. PATIENTS AND METHODS: This retrospective study included 381 patients with HCC and evaluated the performance of the following models: R3-AFP score, alpha-fetoprotein (AFP) model, University of California, Los Angeles (UCLA) nomogram, Pre-Model of Recurrence after Liver Transplantation (MORAL), Post-MORAL, and Combo MORAL models, Risk Estimation of Tumor Recurrence (RETREAT) model and Platelet to Lymphocyte Ratio (PLR) model. RESULTS: The R3-AFP score, UCLA nomogram, AFP model, RETREAT, Combo MORAL, and Post-MORAL models exhibited comparable AUROCs, ranging from 0.785 to 0.733. The AUROCs for the R3-AFP model and AFP model were superior to those of the Pre-MORAL and PLR models. The UCLA nomogram, RETREAT score, Combo MORAL model, and Post-MORAL model performed similarly to the first two models, but were only superior to the PLR model. CONCLUSIONS: The R3-AFP model, UCLA nomogram, AFP model, RETREAT, Combo MORAL, and Post-MORAL models demonstrated a moderate predictive capacity for hepatocellular carcinoma recurrence following transplantation. No significant differences were observed among these models in their ability to predict recurrence.

Generation of an Ovomucoid-Immune scFv Library for the Development of Novel Immunoassays in Hen's Egg Detection.

Hen's egg allergy is the second most common food allergy among infants and young children. The possible presence of undeclared eggs in foods poses a significant risk to sensitized individuals. Therefore, reliable egg allergen detection methods are needed to ensure compliance with food labeling and improve consumer protection. This work describes for the first time the application of phage display technology for the generation of a recombinant antibody aimed at the specific detection of hen's ovomucoid. First, a single-chain variable fragment (scFv) library was constructed from mRNA isolated from the spleen of a rabbit immunized with ovomucoid. After rounds of biopanning, four binding clones were isolated and characterized. Based on the best ovomucoid-binding candidate SR-G1, an indirect phage enzyme-linked immunosorbent assay (phage-ELISA) was developed, reaching limits of detection and quantitation of 43 and 79 ng/mL of ovomucoid, respectively. The developed ELISA was applied to the analysis of a wide variety of food products, obtaining a good correlation with a commercial egg detection assay used as a reference. Finally, in silico modeling of the antigen-antibody complex revealed that the main interactions most likely occur between the scFv heavy chain and the ovomucoid domain-III, the most immunogenic region of this allergen.

Production and Characterization of Novel Fabs Generated from Different Phage Display Libraries as Probes for Immunoassays for Gluten Detection in Food.

Gluten is the main fraction of wheat proteins. It is widely used in the food industry because of the properties that are generated in the dough, but it is also able to trigger diseases like allergies, autoimmunity processes (such as celiac disease), and intolerances in sensitized persons. The most effective therapy for these diseases is the total avoidance of gluten in the diet because it not only prevents damage but also enhances tissue healing. To ensure the absence of gluten in food products labeled as gluten-free, accurate detection systems, like immunoassays, are required. In this work, four recombinant Fab antibody fragments, selected by phage display technology, were produced and tested for specificity and accuracy against gluten in experimental flour mixtures and commercial food products. A high-affinity probe (Fab-C) was identified and characterized. An indirect ELISA test was developed based on Fab-C that complied with the legal detection limits and could be applied in the assessment of gluten-free diets.

Epistemología y ontología en Ciencia: el reto de la Inteligencia Artificial / Epistemology and ontology in Science: the challenge of Artificial Intelligence

La brecha entre predictibilidad y comprensibilidad amenaza todo el proyecto científico porque los modelos matemáticos de los procesos, alimentados por enormes cantidades de datos de origen muy diverso, proporcionan resultados excepcionalmente precisos pero, al mismo tiempo, ocultan la explicación de los procesos. El conocimiento de “qué sabemos” de la ontología es tan relevante en ciencia como el de “cómo sabemos” y el de “cuánto sabemos” de la epistemología. La inteligencia artificial (IA) implica la comprensión científica de los mecanismos que subyacen al pensamiento y la conducta inteligente, así como su encarnación en máquinas capacitadas por sus creadores de razonar en un sentido convencional. Su formulación “débil” se refiere al empleo de programas informáticos complejos, diseñados con el fin de complementar o auxiliar el razonamiento humano para resolver o completar complejos problemas de cálculo, de mantenimiento de sistemas, de reconocimiento de todo tipo de imágenes, de diseño, de análisis de patrones de datos, etc., muchos de los cuales serían prácticamente inabordables mediante procedimientos convencionales; pero todo ello sin incluir capacidades sentientes o éticas humanas, que sí serían objeto de una – por ahora – inexistente IA “fuerte”, aquella que igualaría o incluso excedería la inteligencia sentiente humana. La vulgarización de la IA “generativa”, desarrollada para crear contenido – texto, imágenes, música o vídeos, entre otras muchas áreas – a partir de información previa, está contribuyendo a consolidar popularmente la idea errónea de que la actual IA excede el razonamiento a nivel humano y exacerba el riesgo de transmisión de información falsa y estereotipos negativos a las personas. Los modelos de lenguaje de la inteligencia artificial no funcionan emulando un cerebro biológico sino que se fundamentan en la búsqueda de patrones lógicos a partir de grandes bases de datos procedentes de fuentes diversas, que no siempre están actualizadas ni depuradas de falsedades, de errores ni de sesgos conceptuales o factuales, tanto involuntarios como interesados. Y la IA empleada en ciencia no es ajena a estas limitaciones y sesgos. Una cuestión particularmente sensible es la posibilidad de utilizar la IA generativa para redactar o incluso inventarse artículos científicos que llegan a pasar desapercibidos por los revisores por pares de las revistas científicas más prestigiosas del mundo, apuntando a un problema más aún profundo: los revisores por pares de las revistas científicas a menudo no tienen tiempo para revisar los manuscritos a fondo en busca de señales de alerta y, en muchos casos, además carecen de recursos informáticos adecuados y formación especializada.(AU)

The gap between predictability and comprehensibility threatens the entire scientific project because mathematical models of processes, fed by enormous amounts of data of very diverse origin, provide exceptionally precise results but, at the same time, hide the explanation of the processes. The knowledge of “what we know” of ontology is as relevant in science as that of “how we know” and “how much we know” of epistemology. Artificial intelligence (AI) involves the scientific understanding of the mechanisms underlying intelligent thought and behavior, as well as their embodiment in machines trained by their creators to reason in a conventional sense. Its “weak” formulation refers to the use of complex computer programs, designed with the purpose of complementing or assisting human reasoning to solve or complete complex problems of calculation, system maintenance, recognition of all types of images, design, analysis of data patterns, etc., many of which would be practically unapproachable using conventional procedures; but all this without including human sentient or ethical capabilities, which would be the subject of a – at the moment – non-existent “strong” AI, that would equal or even exceed human sentient intelligence. The popularization of “generative” AI, developed to create content – text, images, music or videos, among many other areas – from previous information, is helping to popularly consolidate the erroneous idea that current AI exceeds reasoning human level and exacerbates the risk of transmitting false information and negative stereotypes to people. The language models of artificial intelligence do not work by emulating a biological brain but are based on the search for logical patterns from large databases from diverse sources, which are not always updated or purged of falsehoods, errors or errors. conceptual or factual biases, both involuntary and self-serving. And the AI used in science is no stranger to these limitations and biases. A particularly sensitive issue is the possibility of using generative AI to write or even invent scientific articles that go unnoticed by the peer reviewers of the most prestigious scientific journals in the world, pointing to an even deeper problem: peer reviewers. Reviewers often do not have the time to review manuscripts thoroughly for red flags and, in many cases, they also lack adequate computing resources and specialized training.(AU)

Arterial tortuosity syndrome: Phenotypic features and cardiovascular manifestations in 4 newly identified patients.

Arterial tortuosity syndrome (ATS) is an autosomal recessive connective tissue disease caused by biallelic variants in the SLC2A10 gene (NG_016284.1) and characterised by tortuosity and elongation of the aorta and medium-sized arteries. It is considered an extremely rare disease; only 106 individuals with genetically confirmed ATS have been identified to date. Four cases of ATS from two families are described, contributing to the clinical delineation of this condition. A patient with microcephaly and a complex uropathy and two cases with diaphragmatic hernia are noticed. Regarding the vascular involvement, a predominant supra-aortic involvement stands out and only 1 patient with significant arterial stenoses was described. All presented severe tortuosity of the intracranial arteries. To reduce hemodynamic stress on the arterial wall, beta-adrenergic blocking treatment was prescribed. A not previously described variant (NM_030777.4:c.899T>G (p.Leu300Trp)) was detected in a proband; it has an allegedly deleterious effect in compound heterozygous state with the pathogenic variant c.417T>A (p.Tyr139Ter). The other 3 patients, siblings born to healthy consanguineous parents, had a variant in homozygous state: c.510G>A (p.Trp170Ter).

Altitude and COVID-19 in Colombia: An updated analysis accounting for potential confounders.

We assessed the relationship between the altitude of municipalities and the incidence, mortality, and fatality from COVID-19 and excess of mortality in Colombia between 2020 and 2022. We conducted an ecologic study including all 1122 municipalities in Colombia and used categories of altitude as main independent variable. We fit multivariable regression models for incidence, mortality, fatality rates, and excess of mortality controlling for several variables at municipality level. There was a higher incidence rate, similar mortality rate and lower case-fatality rate for COVID-19 during 2020-2022 in municipalities in the upper category of altitude (>=2500 masl) compared to the lower category (<1000 masl). The excess of mortality was lower but not statistically different in municipalities in the upper category of altitude, and significantly lower in the intermediate altitude category compared to the lowlands. Our findings provide evidence that municipalities with high altitude had similar mortality rate, and lower case-fatality rate and excess of mortality for COVID-19 compared to lowlands in Colombia.

Correction: Propensity-matched analysis of patients with intrahepatic cholangiocarcinoma or mixed hepatocellular-cholangiocarcinoma and hepatocellular carcinoma undergoing a liver transplant.

[This corrects the article on p. 688 in vol. 13, PMID: 36160465.].