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Abstract Paleoclimate studies play a crucial role in understanding past and future climates and their environmental impacts. Current methodologies for performing highly sensitive elemental analysis at micrometre spatial resolutions are restricted to the use of complex and/or not easily applied techniques, such as synchrotron radiation X-ray fluorescence micro-analysis (μ-SRXRF), nano secondary ion mass spectrometry (nano-SIMS) or laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Moreover, the analysis of large samples (>few cm²) with any of these methods remains very challenging due to their relatively low acquisition speed (~1–10 Hz), and because they must be operated in vacuum or controlled atmosphere. In this work, we proposed an imaging methodology based on laser-induced breakdown spectroscopy, to perform fast multi-elemental scanning of large geological samples with high performance in terms of sensitivity (ppm-level), lateral resolution (up to 10 μm) and operating speed (100 Hz). This method was successfully applied to obtain the first megapixel images of large geological samples and yielded new information, not accessible using other techniques. These results open a new perspective into the use of laser spectroscopy in a variety of geochemical applications.

Los esfuerzos de conservación en la región neotropical están limitados por la falta de información disponible sobre las especies, ya que muchas no han sido descritas o se tiene poca información sobre ellas. La Red Internacional de Inventarios Forestales (BIOTREE-NET) concentra y facilita el acceso a la información y el intercambio entre investigadores, gestores y conservacionistas, organizando y estandarizando los datos de especies de árboles procedentes de inventarios forestales en la región mesoamericana en una única base de datos que incluya información espacial. Este artículo explica el ámbito y objetivos de la red, describe la estructura de la base de datos e identifica los principales avances realizados, así como los retos y perspectivas futuras. La base de datos contiene más de 50 000 registros de árboles de unas 5000 especies, distribuidas en más de 2000 parcelas muestreadas desde el suroeste de México hasta Panamá. La información es heterogénea, tanto en su naturaleza y forma como en la cobertura geográfica de los inventarios. La base de datos tiene una estructura relacional, con 12 tablas interconectadas, incluyendo información sobre las parcelas, los nombres de las especies, el diámetro a la altura del pecho de los árboles medidos y sus atributos funcionales. Se ha desarrollado un sistema para la corrección de errores tipográficos y la estandarización taxonómica y nomenclatural utilizando como referencia The Plant List (http://theplantlist.org/). También se han generado modelos de distribución potencial para cerca de 1700 especies utilizando distintos métodos y en el futuro se prevé habilitar también el acceso público a los modelos de distribución de especies a través del portal web (http://portal.biotreenet.com). Aunque BIOTREE-NET ha contribuido al desarrollo de mejores modelos de distribución, su mayor potencial radica, en nuestra opinión, en el estudio a nivel de comunidades. Finalmente, se reconoce la necesidad de expandir la red a través de la participación de más investigadores interesados en colaborar con datos para ampliar el conocimiento sobre la biodiversidad forestal en la región neotropical.

Tradicionalmente se afirma que las sociedades indígenas que habitan bosques tropicales preservan la biodiversidad y los recursos naturales a través de sus pautas tradicionales de subsistencia. Sin embargo, pocos estudios han cuantificado el impacto relativo de esas pautas de uso del suelo en la estructura y en la biodiversidad de especies forestales. En este estudio se compararon el tamaño, la densidad, la diversidad y la composición de árboles entre las tres principales zonas de uso del suelo (agricultura, caza y conservación) en un territorio indígena de la Reserva de Bosawás. Se identificaron y se midieron los árboles que presentaban un diámetro a la altura del pecho (DAP) ≥ 10 cm en 13 transectos de 1 km de longitud repartidos entre las tres zonas. La primera hipótesis plantea que el tamaño, la densidad y la diversidad de árboles son menores en el mosaico de bosques de la zona agrícola que en los bosques de las zonas de caza y de conservación. Ésta se aceptó sólo para el caso del DAP total por transecto, mientras que la altura media, el DAP medio, la densidad de individuos, la densidad de tallos (algunos individuos constaban de múltiples tallos) y la diversidad estimada no fueron significativamente diferentes entre las tres zonas de uso del suelo. En la segunda hipótesis se considera que la composición de especies arbóreas es diferente en la zona agrícola. Los resultados confirman esta afirmación, no obstante la composición también fue distinta entre las zonas de caza y de conservación, y ésta no estuvo significativamente relacionada con la distancia a las comunidades. A pesar de que la zona agrícola abarca toda la actividad agrícola y la mayor parte de la extracción de productos forestales en los territorios indígenas, el mosaico de bosques secundarios y maduros que constituye la mayor superficie de esta zona fue similar en estructura y diversidad a la zona de conservación, donde el impacto humano es casi nulo. Sin embargo, los usos indígenas del suelo incidieron en la composición de especies, recalcando la necesidad de mantener remanentes de bosque maduro en la zona agrícola para servir como refugios de especies y la de fortalecer las normativas que protegen el bosque en las zonas de caza y de conservación.

In contrast to abiotically formed carbonates, biogenetic carbonates have been observed to be nanocomposite, organo-mineral structures, the basic build-blocks of which are particles of quasi-uniform size (10-100 nm) organized into complex higher-order hierarchical structures, typically with highly controlled crystal-axis alignments. Some of these characteristics serve as criteria for inferring a biological origin and the state of preservation of fossil carbonate materials, and to determine whether the biomineralization process was biologically induced or controlled. Here we show that a calcium storage structure formed by the American lobster, a gastrolith initially consisting of amorphous calcium carbonate (ACC) and amorphous calcium phosphate (ACP), post-mortem can crystallize into (thus secondary) calcite with structural properties strongly influenced by the inherited organic matrix. This secondary calcite meets many structural criteria for biominerals (thus called the biomorphic calcite), but differs in trace element distributions (e.g., P and Mg). Such observations refine the capability to determine whether a fossil carbonates can be attributed to biogenic processes, with implications for the record of life on Earth and other terrestrial planets., (© 2024. The Author(s).)

Cryptorchidism (CO) or undescended testes is defined as the failure of one or both testes to be positioned inside the scrotum. Typically, cryptorchidism is detected at birth or shortly thereafter, and in humans, it is considered to be part of the testicular dysgenesis syndrome (TDS), a complex pathology regarding the male reproductive system that apparently involves the interaction of both genetic and environmental harmful factors, mainly during embryonic development. Serotonin (5-HT) is an ancient molecule that participates in a broad range of body functions, and in recent years, its importance in reproduction has started to be elucidated. In male pathologies such as infertility, varicocele, erectile dysfunction, and primary carcinoid tumors, an increase in 5-HT concentration or its metabolites in the blood, semen, and urine has been directly related; nevertheless, the role of 5-HT in CO remains unknown. In the present work, our goal was to answer two important questions: (1) whether some serotonergic system components are present in adult male Oryctolagus cuniculus (chinchilla rabbit) and (2) if there are changes in their expression in an experimental model of CO. Using histological, molecular, and biochemical approaches, we found the presence of some serotonergic system components in the adult chinchilla rabbit, and we demonstrated that its expression is downregulated after CO was pharmacologically induced. Although we did not test the role of 5-HT in the etiology of CO, our results suggest that this indoleamine could be important for the regulation of steroidogenesis and spermatogenesis processes in the chinchilla rabbit during adulthood. Finally, in parallel experimental series, we found downregulation of kynurenine concentration in COI rabbits when compared to control ones, suggesting that CO could be affecting the kynurenine pathway and probably testicular immune privilege which in turn could lead to infertility/sterility conditions in this disorder.

Emotional intelligence (EI) has been widely researched in different fields of knowledge. This paper reviews the literature on emotional intelligence, leadership, and teams in 104 peer-reviewed articles and reviews provided by the Web of Science and Scopus databases from 1998 to 2022. It is a hybrid or mixed review as it uses both quantitative and qualitative analysis techniques. The aims of this study are a performance analysis of the selected documents (years of publication, country, sectors, techniques used, most cited authors, authors with more publications, journals, journal quartiles, and scope of publication), as well as a co-word analysis using Atlas. ti v8. The results of the quantitative analysis indicate that the majority are empirical works. The qualitative analysis is a co-word analysis providing the following results: (i) classification of authors by major themes-categories (EI, leadership, team), (ii) classification of themes within each major theme: three subcategories in EI, 17 subcategories in leadership, and 19 subcategories in team and, lastly, (iii) classification according to the chronological development of main objectives from the most cited authors' articles we analyzed. Leadership (transformational, emergence, virtual, effective, health, effectiveness) is the major theme we studied. Our in-depth review of the articles has shown that emotionally intelligent leaders improve both behaviors and business results and have an impact on work team performance. It also highlighted a positive relationship between emotional competence and team members' attitudes about work. The new trends focus on the impacts of COVID19, the global crisis due to the Ukraine War, working in VUCA and BANI environments, comparative studies between generations, the application of artificial intelligence and the influence of mindfulness on organizations., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Vessel segmentation in fundus images permits understanding retinal diseases and computing image-based biomarkers. However, manual vessel segmentation is a time-consuming process. Optical coherence tomography angiography (OCT-A) allows direct, non-invasive estimation of retinal vessels. Unfortunately, compared to fundus images, OCT-A cameras are more expensive, less portable, and have a reduced field of view. We present an automated strategy relying on generative adversarial networks to create vascular maps from fundus images without training using manual vessel segmentation maps. Further post-processing used for standard en face OCT-A allows obtaining a vessel segmentation map. We compare our approach to state-of-the-art vessel segmentation algorithms trained on manual vessel segmentation maps and vessel segmentations derived from OCT-A. We evaluate them from an automatic vascular segmentation perspective and as vessel density estimators, i.e., the most common imaging biomarker for OCT-A used in studies. Using OCT-A as a training target over manual vessel delineations yields improved vascular maps for the optic disc area and compares to the best-performing vessel segmentation algorithm in the macular region. This technique could reduce the cost and effort incurred when training vessel segmentation algorithms. To incentivize research in this field, we will make the dataset publicly available to the scientific community., (© 2023. Springer Nature Limited.)

Different non-classical crystallization mechanisms have been invoked to explain structural and compositional properties of biocrystals. The identification of precursor amorphous nanoparticle aggregation as an onset process in the formation of numerous biominerals (crystallization via particle attachment) constituted a most important breakthrough for understanding biologically mediated mineralization. A comprehensive understanding about how the attached amorphous particles transform into more stable, crystalline grains has yet to be elucidated. Here, we document structural, biogeochemical, and crystallographic aspects of the formation as well as the further phase transformations of the amorphous calcium carbonate particles formed by cultured specimens of earthworm Lumbricus terrestris. In-situ observations evidence the formation of proto-vaterite after dehydration of earthworm-produced ACC, which is subsequently followed by proto-vaterite transformation into calcite through nanoparticle attachment within the organic framework. In culture medium spiked with trace amounts of Mn 2+ , the cauliflower-like proto-vaterite structures become longer-lived than in the absence of Mn 2+ . We propose that the formation of calcite crystals takes place through a non-classical recrystallization path that involves migration of proto-vaterite nanoparticles to the crystallization site, and then, their transformation into calcite via a dissolution-recrystallization reaction. The latter is complemented by ion-by-ion crystal growth and associated with impurity release. These observations are integrated into a new model of the biocrystallization of earthworm-produced carbonate granules which highlights the sensibility of this process to environmental chemical changes, its potential impact on the bioavailability of contaminants as well as the threat that chemical pollution poses to the normal development of its early stages. STATEMENT OF SIGNIFICANCE: Understanding the mechanisms of nucleation, stabilization and aggregation of amorphous calcium carbonate (ACC) and factors controlling its further transformation into crystalline phases is fundamental for elucidation of biogenic mineralization. Some species of earthworms are natural workbench to understand the biogenic ACC, stabilization and the transformation mechanisms, because they create millimeter-sized calcareous granules from amorphous calcium carbonate, which crystallize to a more stable mineral phase (mostly calcite). This study undergoes into the mechanisms of ACC stabilization by the incorporation of trace elements, as manganese, and the ulterior precipitation of calcareous granules by a coupled process of amorphous particle attachment and ion-by-ion growth. The study points to sensibility of this process to environmental chemical changes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The foveal avascular zone (FAZ) is a retinal area devoid of capillaries and associated with multiple retinal pathologies and visual acuity. Optical Coherence Tomography Angiography (OCT-A) is a very effective means of visualizing retinal vascular and avascular areas, but its use remains limited to research settings due to its complex optics limiting availability. On the other hand, fundus photography is widely available and often adopted in population studies. In this work, we test the feasibility of estimating the FAZ from fundus photos using three different approaches. The first two approaches rely on pixel-level and image-level FAZ information to segment FAZ pixels and regress FAZ area, respectively. The third is a training mask-free pipeline combining saliency maps with an active contours approach to segment FAZ pixels while being trained on image-level measures of the FAZ areas. This enables training FAZ segmentation methods without manual alignment of fundus and OCT-A images, a time-consuming process, which limits the dataset that can be used for training. Segmentation methods trained on pixel-level labels and image-level labels had good agreement with masks from a human grader (respectively DICE of 0.45 and 0.4). Results indicate the feasibility of using fundus images as a proxy to estimate the FAZ when angiography data is not available.

Otoliths are calcium carbonate components of the stato-acoustical organ responsible for hearing and maintenance of the body balance in teleost fish. During their formation, control over, e.g., morphology and carbonate polymorph is influenced by complex insoluble collagen-like protein and soluble non-collagenous protein assemblages; many of these proteins are incorporated into their aragonite crystal structure. However, in the fossil record these proteins are considered lost through diagenetic processes, hampering studies of past biomineralization mechanisms. Here we report the presence of 11 fish-specific proteins (and several isoforms) in Miocene (ca. 14.8-14.6 Ma) phycid hake otoliths. These fossil otoliths were preserved in water-impermeable clays and exhibit microscopic and crystallographic features indistinguishable from modern representatives, consistent with an exceptionally pristine state of preservation. Indeed, these fossil otoliths retain ca. 10% of the proteins sequenced from modern counterparts, including proteins specific to inner ear development, such as otolin-1-like proteins involved in the arrangement of the otoliths into the sensory epithelium and otogelin/otogelin-like proteins that are located in the acellular membranes of the inner ear in modern fish. The specificity of these proteins excludes the possibility of external contamination. Identification of a fraction of identical proteins in modern and fossil phycid hake otoliths implies a highly conserved inner ear biomineralization process through time., (© 2023. The Author(s).)

Variations in the geochemical signatures of fossil brachiopod shells may be due to diagenesis and/or biological processes (i.e., 'vital effects'). It is critical to characterise them in order to identify reliable shell areas suitable for paleoclimate studies. This investigation contributes to an in-depth understanding of geochemical variations in Gigantoproductus sp. shells (SW Spain, Serpukhovian age), throwing light onto the Late Paleozoic Ice Age interpretation. Microstructural, crystallographic, cathodoluminescence and geochemical (minor and trace elements, δ 18 O, δ 13 C, and strontium isotopes) characterisations have been performed on the tertiary layer of the ventral valve, to assess the preservation state. Poorly preserved areas exhibit microstructural and geochemical changes such as recrystallisation, fracturing and higher Mn and Fe enrichment. Moreover, these areas have a higher dispersion of ⁸⁶Sr, ⁸⁷Sr, δ 18 O and δ 13 C than well-preserved areas. Three structural regions have been identified in well-preserved areas of the ventral valve by differences in valve curvature and thickness, such as the umbonal and thick and thin regions. These regions have different proportions of Mg, S, Na, δ 18 O, and δ 13 C, which are interpreted as 'vital effects' and probably related to growth-rate differences during shell growth. The Gigantoproductus tertiary layer seems the most suitable for paleoclimate studies, because it retains the original microstructure and geochemical composition.

Acute cerebral stroke is a leading cause of disability and death, which could be reduced with a prompt diagnosis during patient transportation to the hospital. A portable retina imaging system could enable this by measuring vascular information and blood perfusion in the retina and, due to the homology between retinal and cerebral vessels, infer if a cerebral stroke is underway. However, the feasibility of this strategy, the imaging features, and retina imaging modalities to do this are not clear. In this work, we show initial evidence of the feasibility of this approach by training machine learning models using feature engineering and self-supervised learning retina features extracted from OCT-A and fundus images to classify controls and acute stroke patients. Models based on macular microvasculature density features achieved an area under the receiver operating characteristic curve (AUC) of 0.87-0.88. Self-supervised deep learning models were able to generate features resulting in AUCs ranging from 0.66 to 0.81. While further work is needed for the final proof for a diagnostic system, these results indicate that microvasculature density features from OCT-A images have the potential to be used to diagnose acute cerebral stroke from the retina.

Research that has been conducted documenting species richness patterns on tropical mountains has resulted in conflicting observations: monotonic declines with increasing elevation, monotonic increases with increasing elevation, and a mid-elevation "bulge." Currently, it is unclear if these differences are due to environmental differences among study areas, the taxonomic groups or ecological groups (e.g., growth form) sampled, or the scale of study along elevation gradients. Because of the difficulty in sampling and identifying canopy-dwelling plants, the number of inventories quantifying tropical epiphytes is relatively limited and recent. In this study, we provide a detailed qualitative and quantitative assessment of the vascular epiphyte flora and its spatial distribution on Volcán Maderas, Isla de Ometepe, Nicaragua, including weather and environmental measurements along the entire elevation gradient of the volcano. We sampled epiphytes in five distinct forest types associated with increasing elevation as follows: dry forest, humid forest, wet forest, cloud forest, and elfin forest. Five weather stations were placed along the elevation gradient for us to relate observed patterns to environmental conditions. A mid-elevation peak in species richness was detected for all vascular epiphytes at approximately 1000 m in elevation (cloud forest), yet epiphyte abundance increased with increasing elevation. In total we identified 206 taxa of vascular epiphytes belonging to 26 families and 73 genera. The most species-rich family was the Orchidaceae with 55 species for the entire elevation gradient, followed by Bromeliaceae (29 species), Araceae (23), Polypodiaceae (25), Dryopteridaceae (16), and Piperaceae (11), with all other families represented by fewer than 10 species each. We found that richness patterns differ phylogenetically across epiphyte groups, possibly due to different adaptive strategies, and species for the most part appear to be narrowly distributed within specific habitat zones along the elevation gradient. Variables associated with moisture, precipitation, humidity, mist, or cloud cover are key to understanding the observed patterns., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection triggers inflammatory clinical stages that affect the outcome of patients with coronavirus disease 2019 (COVID-19). Disease severity may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. The aim of this study was to characterize the profile of amino acids and acylcarnitines in COVID-19 patients. A multicenter, cross-sectional study was carried out. A total of 453 individuals were classified by disease severity. Levels of 11 amino acids, 31 acylcarnitines, and succinylacetone in serum samples were analyzed by electrospray ionization-triple quadrupole tandem mass spectrometry. Different clusters were observed in partial least squares discriminant analysis, with phenylalanine, alanine, citrulline, proline, and succinylacetone providing the major contribution to the variability in each cluster (variable importance in the projection >1.5). In logistic models adjusted by age, sex, type 2 diabetes mellitus, hypertension, and nutritional status, phenylalanine was associated with critical outcomes (odds ratio=5.3 (95% CI 3.16-9.2) in the severe vs. critical model, with an area under the curve of 0.84 (95% CI 0.77-0.90). In conclusion the metabolic imbalance in COVID-19 patients might affect disease progression. This work shows an association of phenylalanine with critical outcomes in COVID-19 patients, highlighting phenylalanine as a potential metabolic biomarker of disease severity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Martínez-Gómez, Ibarra-González, Fernández-Lainez, Tusie, Moreno-Macías, Martinez-Armenta, Jimenez-Gutierrez, Vázquez-Cárdenas, Vidal-Vázquez, Ramírez-Hinojosa, Rodríguez-Zulueta, Vargas-Alarcón, Rojas-Velasco, Sánchez-Muñoz, Posadas-Sanchez, Martínez-Ruiz, Zayago-Angeles, Moreno, Barajas-Galicia, Lopez-Cisneros, Gonzalez-Fernández, Ortega-Peña, Herrera-López, Olea-Torres, Juárez-Arias, Rosas-Vásquez, Cabrera-Nieto, Magaña, Camacho-Rea, Suarez-Ahedo, Coronado-Zarco, Valdespino-Vázquez, Martínez-Nava, Pineda, Vela-Amieva, López-Reyes and Mex-Gen-COVID Initiative Group.)

Bonarda, the second red grape variety in Argentina, produces high yields per hectare generating, in several cases, low quality wines. Microwave-assisted extraction (MW) is a novel extraction technique for winemaking, widely applied in other foods. Stems addition (S) during vinification can be a sustainable technology for phenolic and aroma contribution without additional cost. Therefore, this study aimed to evaluate the combined effect of MW application with stem additions in different conditions, before fermentation, on the chemical composition of Bonarda wines. During two consecutive vintages (2018 and 2019), the experimental design consisted of ten treatments (two factors) by triplicate. Two maceration strategies (Factor 1) were applied [control (C), and microwaved-assisted extraction after grape crushing (MW; 2450 MHz, 7600 W, 45-50 °C)], combined with five stem-contact conditions (Factor 2) [control without stems (WS), 50% stems addition (S50), 50% stems addition + MW of the stems (S50MW; 2450 MHz, 7600 W, 60 °C), 100% stems addition (S100), 100% stems addition + MW (S100MW)]. Wines were analyzed for basic chemistry, phenolic composition and color parameters, polysaccharides, and aroma profiles. The 2018 wines showed higher pH and lower volatile acidity with stem additions and MW application in both matrices (grapes and stems). Stem additions increased tannin content by >55% (S100) and by >25% for the other treatments; while MW, mostly in the 2018 season, consistently improved phenolic extraction and polymeric pigments formation, enhancing wine color (greater saturation) and intensifying violet hue. The behavior observed in 2019 was similar, with a more marked effect of MW on wine color (C* ab and polymeric pigments). Likewise, combined strategies increased polysaccharides extraction and modified the volatile profile of wines. The reported results are promising and are considered the first advance in the knowledge of the impact of the proposed combined strategies on the chemical composition of red wines., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This paper reviews the methodology used by the World Economic Forum (WEF) to create the Global Competitiveness Index (WEF-GCI). We propose an alternative competitiveness index that only includes the objective data (hard data) from the WEF-GCI and is created by applying a multivariate statistical procedure (Exploratory Factor Analysis) that allows us to determine the weights from the implicit data structure. The rankings obtained from this index have a high degree of association with those provided by the WEF. The main benefit of this index over the WEF index is that it does not include valuations from opinion surveys given to business executives and/or entrepreneurs of the countries included in the index (soft data). Consequently, the rankings from this alternative index are not affected by political biases or individual interests as it is elaborated only including officially published objective data., Competing Interests: The authors have declared that no competing interests exist.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current coronavirus disease 2019 (COVID-19) pandemic, affecting more than 219 countries and causing the death of more than 5 million people worldwide. The genetic background represents a factor that predisposes the way the host responds to SARS-CoV-2 infection. In this sense, genetic variants of ACE and ACE2 could explain the observed interindividual variability to COVID-19 outcomes. In order to improve the understanding of how genetic variants of ACE and ACE2 are involved in the severity of COVID-19, we included a total of 481 individuals who showed clinical manifestations of COVID-19 and were diagnosed by reverse transcription PCR (RT-PCR). Genomic DNA was extracted from peripheral blood and saliva samples. ACE insertion/deletion polymorphism was evaluated by the high-resolution melting method; ACE single-nucleotide polymorphism (SNP) (rs4344) and ACE2 SNPs (rs2285666 and rs2074192) were genotyped using TaqMan probes. We assessed the association of ACE and ACE2 polymorphisms with disease severity using logistic regression analysis adjusted by age, sex, hypertension, type 2 diabetes, and obesity. The severity of the illness in our study population was divided as 31% mild, 26% severe, and 43% critical illness; additionally, 18% of individuals died, of whom 54% were male. Our results showed in the codominant model a contribution of ACE2 gene rs2285666 T/T genotype to critical outcome [odds ratio (OR) = 1.83; 95%CI = 1.01-3.29; p = 0.04] and to require oxygen supplementation (OR = 1.76; 95%CI = 1.01-3.04; p = 0.04), in addition to a strong association of the T allele of this variant to develop critical illness in male individuals (OR = 1.81; 95%CI = 1.10-2.98; p = 0.02). We suggest that the T allele of rs2285666 represents a risk factor for severe and critical outcomes of COVID-19, especially for men, regardless of age, hypertension, obesity, and type 2 diabetes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Martínez-Gómez, Herrera-López, Martinez-Armenta, Ortega-Peña, Camacho-Rea, Suarez-Ahedo, Vázquez-Cárdenas, Vargas-Alarcón, Rojas-Velasco, Fragoso, Vidal-Vázquez, Ramírez-Hinojosa, Rodríguez-Sánchez, Barrón-Díaz, Moreno, Martínez-Ruiz, Zayago-Angeles, Mata-Miranda, Vázquez-Zapién, Martínez-Cuazitl, Barajas-Galicia, Bustamante-Silva, Zazueta-Arroyo, Rodríguez-Pérez, Hernández-González, Coronado-Zarco, Lucas-Tenorio, Franco-Cendejas, López-Jácome, Vázquez-Juárez, Magaña, Cruz-Ramos, Granados, Hernández-Doño, Delgado-Saldivar, Ramos-Tavera, Coronado-Zarco, Guajardo-Salinas, Muñoz-Valle, Pineda, Martínez-Nava and López-Reyes.)

Adequate iodine nutrition is crucial for all mammals by playing his starring role as a component of thyroid hormones, which are key regulators of cellular processes for life such as differentiation, growth, function, and metabolism. Deficiency or excess of iodine in the diet are worldwide highly frequent conditions that are responsible of health problems like hypothyroidism, hypothyroxinemia, goiter, thyroiditis, hyperthyroidism, and autoimmune thyroid diseases among others. The incorporation of iodine in salt or other nutrients resolved the consequences of severe iodine deficiency like goiter, cretinism. However, this strategy in several countries led to other ailments like Hashimoto autoimmune thyroiditis, hyperthyroidism, and hypothyroidism. The goal of this review is to analyze and discuss the different aspects of iodine nutrition for human health comprising its biological role through thyroid hormones, pathogen control, and the regulation of the intestinal microbiota.

Fundus Retinal imaging is an easy-to-acquire modality typically used for monitoring eye health. Current evidence indicates that the retina, and its vasculature in particular, is associated with other disease processes making it an ideal candidate for biomarker discovery. The development of these biomarkers has typically relied on predefined measurements, which makes the development process slow. Recently, representation learning algorithms such as general purpose convolutional neural networks or vasculature embeddings have been proposed as an approach to learn imaging biomarkers directly from the data, hence greatly speeding up their discovery. In this work, we compare and contrast different state-of-the-art retina biomarker discovery methods to identify signs of past stroke in the retinas of a curated patient cohort of 2,472 subjects from the UK Biobank dataset. We investigate two convolutional neural networks previously used in retina biomarker discovery and directly trained on the stroke outcome, and an extension of the vasculature embedding approach which infers its feature representation from the vasculature and combines the information of retinal images from both eyes.In our experiments, we show that the pipeline based on vasculature embeddings has comparable or better performance than other methods with a much more compact feature representation and ease of training.Clinical Relevance-This study compares and contrasts three retinal biomarker discovery strategies, using a curated dataset of subject evidence, for the analysis of the retina as a proxy in the assessment of clinical outcomes, such as stroke risk.

Background and Objective: Accurate information concerning implanted medical devices prior to a Magnetic resonance imaging (MRI) examination is crucial to assure safety of the patient and to address MRI induced unintended changes in device settings. The identification of these devices still remains a very challenging task. In this paper, with the aim of providing a faster device detection, we propose the adoption of deep learning for medical device detection from X-rays., Method: In particular, we propose a pipeline for the identification of implanted programmable cerebrospinal fluid shunt valves using X-ray images of the radiologist workstation screens captured with mobile phone integrated cameras at different angles and illuminations. We compare the proposed convolutional neural network with published methods., Results: Experimental results show that this approach outperforms methods trained on images digitally transferred directly from the scanners and then applied on mobile phones images (mean accuracy 95% vs 77%, Avg. Precision 0.96 vs 0.77, Avg. Recall 0.95 vs 0.77, Avg. F1-score 0.95 vs 0.77) and existing published methods based on transfer learning fine-tuned directly on the mobile phone images (mean accuracy 94% vs 75%, Avg. Precision 0.94 vs 0.75, Avg. Recall 0.94 vs 0.75, Avg. F1-score 0.94 vs 0.75)., Conclusion: An automated shunt valve identification system is a promising safety tool for radiologists to efficiently coordinate the care of patients with implanted devices. An image-based safety system able to be deployed on a mobile phone would have significant advantages over methods requiring direct input from X-ray scanners or clinical picture archiving and communication system (PACS) in terms of ease of integration in the hospital or clinical ecosystems., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021. Published by Elsevier B.V.)

(1) This study aimed to evaluate characteristics, perinatal outcomes, and placental pathology of pregnant women with or without SARS-CoV-2 infection in the context of maternal PCR cycle threshold (C T ) values. (2) This was a retrospective case-control study in a third-level health center in Mexico City with universal screening by RT-qPCR. The association of COVID-19 manifestations, preeclampsia, and preterm birth with maternal variables and C T values were assessed by logistic regression models and decision trees. (3) Accordingly, 828 and 298 women had a negative and positive test, respectively. Of those positive, only 2.6% of them presented mild to moderate symptoms. Clinical characteristics between both groups of women were similar. No associations between C T values were found for maternal features, such as pre-gestational BMI, age, and symptomatology. A significantly higher percentage of placental fibrinoid was seen with women with low C T s (<25; p < 0.01). Regarding perinatal outcomes, preeclampsia was found to be significantly associated with symptomatology but not with risk factors or C T values ( p < 0.01, aOR = 14.72). Moreover, 88.9% of women diagnosed with COVID-19 at <35 gestational weeks and symptomatic developed preeclampsia. (4) The data support strong guidance for pregnancies with SARS-CoV-2 infection, in particular preeclampsia and placental pathology, which need further investigation.

The perinatal consequences of SARS-CoV-2 infection are still largely unknown. This study aimed to describe the features and outcomes of pregnant women with or without SARS-CoV-2 infection after the universal screening was established in a large tertiary care center admitting only obstetric related conditions without severe COVID-19 in Mexico City. This retrospective case-control study integrates data between April 22 and May 25, 2020, during active community transmission in Mexico, with one of the highest COVID-19 test positivity percentages worldwide. Only pregnant women and neonates with a SARS-CoV-2 result by quantitative RT-PCR were included in this study. Among 240 pregnant women, the prevalence of COVID-19 was 29% (95% CI, 24% to 35%); 86% of the patients were asymptomatic (95% CI, 76%-92%), nine women presented mild symptoms, and one patient moderate disease. No pregnancy baseline features or risk factors associated with severity of infection, including maternal age > 35 years, Body Mass Index >30 kg/m2, and pre-existing diseases, differed between positive and negative women. The median gestational age at admission for both groups was 38 weeks. All women were discharged at home without complications, and no maternal death was reported. The proportion of preeclampsia was higher in positive women than negative women (18%, 95% CI, 10%-29% vs. 9%, 95% CI, 5%-14%, P<0.05). No differences were found for other perinatal outcomes. SARS-CoV-2 test result was positive for nine infants of positive mothers detected within 24h of birth. An increased number of infected neonates were admitted to the NICU, compared to negative neonates (44% vs. 22%, P<0.05) and had a longer length of hospitalization (2 [2-18] days vs. 2 [2-3] days, P<0.001); these are potential proxies for illness severity. This report highlights the importance of COVID-19 detection at delivery in pregnant women living in high transmission areas., Competing Interests: The authors have declared that no competing interests exist.

Objective: The aim of this study is to assess the performance of deep learning convolutional neural networks (CNNs) in segmenting gadolinium-enhancing lesions using a large cohort of multiple sclerosis (MS) patients., Methods: A three-dimensional (3D) CNN model was trained for segmentation of gadolinium-enhancing lesions using multispectral magnetic resonance imaging data (MRI) from 1006 relapsing-remitting MS patients. The network performance was evaluated for three combinations of multispectral MRI used as input: (U5) fluid-attenuated inversion recovery (FLAIR), T2-weighted, proton density-weighted, and pre- and post-contrast T1-weighted images; (U2) pre- and post-contrast T1-weighted images; and (U1) only post-contrast T1-weighted images. Segmentation performance was evaluated using the Dice similarity coefficient (DSC) and lesion-wise true-positive (TPR) and false-positive (FPR) rates. Performance was also evaluated as a function of enhancing lesion volume., Results: The DSC/TPR/FPR values averaged over all the enhancing lesion sizes were 0.77/0.90/0.23 using the U5 model. These values for the largest enhancement volumes (>500 mm 3 ) were 0.81/0.97/0.04. For U2, the average DSC/TPR/FPR values were 0.72/0.86/0.31. Comparable performance was observed with U1. For all types of input, the network performance degraded with decreased enhancement size., Conclusion: Excellent segmentation of enhancing lesions was observed for enhancement volume ⩾70 mm 3 . The best performance was achieved when the input included all five multispectral image sets.

Serotonin (5-HT) is member of a family of indolamine molecules that participate in a wide variety of biological processes. Despite its important role in the regulation of local blood systems, little is known about the physiological function of 5-HT in reproductive organs, its functional implications, and its role in the reproduction of mammals. In the present work, we evaluated the localization and distribution of 5-HT (using histochemical analysis of indolamines) and different components of the serotoninergic system in rat testes. We detected local synthesis and degradation through immunofluorescence and western blot analyses against the TPH1, MAO A , 5-HT T , and VMAT1 serotonin transporters. We also identified the localization and distribution of the 5-HT 1B , 5-HT 2A , and 5-HT 3A receptors. RT-PCR results showed the presence of the Tph1, Maoa, Slc6a4, and Htr3a genes in testes and in the brain stem (Tph1 was used as a negative control). High-performance liquid chromatography was used to determine the presence of 5-HT and the activity of tryptophan hydroxylase in testes homogenates in vitro . Our observations suggest that TPH1 activity and local 5-HT synthesis befall in rat testes. We propose that 5-HT could participate in the regulation of testosterone synthesis and in the spermatogenesis process via local serotoninergic system. However, more studies are needed before concluding that rat testes, or those of other mammals, contain an active form of tryptophan hydroxylase and produce 5-HT., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Jiménez-Trejo, Coronado-Mares, Arriaga-Canon, Herrera, Roque-Ramírez, Chávez-Saldaña, Rojas-Castañeda, Cerbón and Vigueras-Villaseñor.)

One of the most conserved traits in the evolution of biomineralizing organisms is the taxon-specific selection of skeletal minerals. All modern scleractinian corals are thought to produce skeletons exclusively of the calcium-carbonate polymorph aragonite. Despite strong fluctuations in ocean chemistry (notably the Mg/Ca ratio), this feature is believed to be conserved throughout the coral fossil record, spanning more than 240 million years. Only one example, the Cretaceous scleractinian coral Coelosmilia (ca. 70 to 65 Ma), is thought to have produced a calcitic skeleton. Here, we report that the modern asymbiotic scleractinian coral Paraconotrochus antarcticus living in the Southern Ocean forms a two-component carbonate skeleton, with an inner structure made of high-Mg calcite and an outer structure composed of aragonite. P. antarcticus and Cretaceous Coelosmilia skeletons share a unique microstructure indicating a close phylogenetic relationship, consistent with the early divergence of P. antarcticus within the Vacatina (i.e., Robusta) clade, estimated to have occurred in the Mesozoic (ca. 116 Mya). Scleractinian corals thus join the group of marine organisms capable of forming bimineralic structures, which requires a highly controlled biomineralization mechanism; this capability dates back at least 100 My. Due to its relatively prolonged isolation, the Southern Ocean stands out as a repository for extant marine organisms with ancient traits., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Objective: To investigate the performance of deep learning (DL) based on fully convolutional neural network (FCNN) in segmenting brain tissues in a large cohort of multiple sclerosis (MS) patients., Methods: We developed a FCNN model to segment brain tissues, including T2-hyperintense MS lesions. The training, validation, and testing of FCNN were based on ~1000 magnetic resonance imaging (MRI) datasets acquired on relapsing-remitting MS patients, as a part of a phase 3 randomized clinical trial. Multimodal MRI data (dual-echo, FLAIR, and T1-weighted images) served as input to the network. Expert validated segmentation was used as the target for training the FCNN. We cross-validated our results using the leave-one-center-out approach., Results: We observed a high average (95% confidence limits) Dice similarity coefficient for all the segmented tissues: 0.95 (0.92-0.98) for white matter, 0.96 (0.93-0.98) for gray matter, 0.99 (0.98-0.99) for cerebrospinal fluid, and 0.82 (0.63-1.0) for T2 lesions. High correlations between the DL segmented tissue volumes and ground truth were observed ( R 2  > 0.92 for all tissues). The cross validation showed consistent results across the centers for all tissues., Conclusion: The results from this large-scale study suggest that deep FCNN can automatically segment MS brain tissues, including lesions, with high accuracy.

Worldwide, breast cancer (BC) is the leading cause of cancer death among women. For many patients the most effective treatment is a resection surgery that removes the tumor. Within this subset, patients sometimes receive chemotherapy treatment (CT) prior to surgery aiming to reduce tumor size in order to preserve healthy breast tissue. This strategy is commonly called neoadjuvant chemotherapy (NAC). This approach also offers an opportunity to determine treatment sensitivity, especially in aggressive tumors. Post NAC absence of residual disease is associated to long term survival in BC patients and is used to define the need of adjuvant therapy options. Studies suggest that NAC allows the recognition of tumor antigens by immune cells potentiating the eradication of the tumor. However, the dynamic changes in patients' immune cells under NAC remain unclear. Here, we assessed changes in leucocyte and cytokine profiles in order to determine its association to NAC response in BC patients. Peripheral blood patient samples were taken prior to each NAC cycle to assess the abundance of leukocyte subsets and serum cytokines in 20 patients. These immunological features were associated with clinical outcomes including pathological response. We found a positive correlation between plasma Interleukin 10 (IL-10) and classical monocytes in HER2+ BC patients under NAC. We also observed a trend between increased IL-10 and classical monocytes levels and lower rates of pathologic complete response at the end of NAC. These data support the notion that monocyte subsets and IL-10 could be applied as a novel indicator of NAC efficacy in HER2+ BC patients. Finally, we confirm a key role of the immune system in cancer progression and CT response., (Copyright © 2020 Valdés-Ferrada, Muñoz-Durango, Pérez-Sepulveda, Muñiz, Coronado-Arrázola, Acevedo, Soto, Bueno, Sánchez and Kalergis.)

Background: The dependence of deep-learning (DL)-based segmentation accuracy of brain MRI on the training size is not known., Purpose: To determine the required training size for a desired accuracy in brain MRI segmentation in multiple sclerosis (MS) using DL., Study Type: Retrospective analysis of MRI data acquired as part of a multicenter clinical trial., Study Population: In all, 1008 patients with clinically definite MS., Field Strength/sequence: MRIs were acquired at 1.5T and 3T scanners manufactured by GE, Philips, and Siemens with dual turbo spin echo, FLAIR, and T 1 -weighted turbo spin echo sequences., Assessment: Segmentation results using an automated analysis pipeline and validated by two neuroimaging experts served as the ground truth. A DL model, based on a fully convolutional neural network, was trained separately using 16 different training sizes. The segmentation accuracy as a function of the training size was determined. These data were fitted to the learning curve for estimating the required training size for desired accuracy., Statistical Tests: The performance of the network was evaluated by calculating the Dice similarity coefficient (DSC), and lesion true-positive and false-positive rates., Results: The DSC for lesions showed much stronger dependency on the sample size than gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). When the training size was increased from 10 to 800 the DSC values varied from 0.00 to 0.86 ± 0.016 for T 2 lesions, 0.87 ± 009 to 0.94 ± 0.004 for GM, 0.86 ± 0.08 to 0.94 ± 0.005 for WM, and 0.91 ± 0.009 to 0.96 ± 0.003 for CSF., Data Conclusion: Excellent segmentation was achieved with a training size as small as 10 image volumes for GM, WM, and CSF. In contrast, a training size of at least 50 image volumes was necessary for adequate lesion segmentation., Level of Evidence: 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1487-1496., (© 2019 International Society for Magnetic Resonance in Medicine.)

Neural stem/progenitor cells (NSPCs) are self-renewing, multipotent cells located in the embryonic and adult central nervous system (CNS). Extensive preclinical and clinical studies have shed light on the potential of stem cell replacement therapy for various neurodegenerative diseases. The key prerequisite for the success of these clinical applications is the procurement of a sufficient number of high-quality NSPCs. In this study, we explored the biological activity of Quadrella incana leaf in NSPC homeostasis. We showed that the leaf extract of Quadrella incana upregulated NSPC marker and proliferative potential. On the other hand, Quadrella incana leaf suppressed spontaneous unintended NSPC differentiation. Mechanistically, Quadrella incana leaf contributed to the maintenance of NSPCs by upregulating glycolytic flux and redox potential., Competing Interests: The authors declare no conflict of interest., (Copyright © 2020 Mingyu Kang et al.)

Background Enhancing lesions on MRI scans obtained after contrast material administration are commonly thought to represent disease activity in multiple sclerosis (MS); it is desirable to develop methods that can predict enhancing lesions without the use of contrast material. Purpose To evaluate whether deep learning can predict enhancing lesions on MRI scans obtained without the use of contrast material. Materials and Methods This study involved prospective analysis of existing MRI data. A convolutional neural network was used for classification of enhancing lesions on unenhanced MRI scans. This classification was performed for each slice, and the slice scores were combined by using a fully connected network to produce participant-wise predictions. The network input consisted of 1970 multiparametric MRI scans from 1008 patients recruited from 2005 to 2009. Enhanced lesions on postcontrast T1-weighted images served as the ground truth. The network performance was assessed by using fivefold cross-validation. Statistical analysis of the network performance included calculation of lesion detection rates and areas under the receiver operating characteristic curve (AUCs). Results MRI scans from 1008 participants (mean age, 37.7 years ± 9.7; 730 women) were analyzed. At least one enhancing lesion was observed in 519 participants. The sensitivity and specificity averaged across the five test sets were 78% ± 4.3 and 73% ± 2.7, respectively, for slice-wise prediction. The corresponding participant-wise values were 72% ± 9.0 and 70% ± 6.3. The diagnostic performances (AUCs) were 0.82 ± 0.02 and 0.75 ± 0.03 for slice-wise and participant-wise enhancement prediction, respectively. Conclusion Deep learning used with conventional MRI identified enhanced lesions in multiple sclerosis from images from unenhanced multiparametric MRI with moderate to high accuracy. © RSNA, 2019.

Background: Magnetic resonance images with multiple contrasts or sequences are commonly used for segmenting brain tissues, including lesions, in multiple sclerosis (MS). However, acquisition of images with multiple contrasts increases the scan time and complexity of the analysis, possibly introducing factors that could compromise segmentation quality., Objective: To investigate the effect of various combinations of multi-contrast images as input on the segmented volumes of gray (GM) and white matter (WM), cerebrospinal fluid (CSF), and lesions using a deep neural network., Methods: U-net, a fully convolutional neural network was used to automatically segment GM, WM, CSF, and lesions in 1000 MS patients. The input to the network consisted of 15 combinations of FLAIR, T1-, T2-, and proton density-weighted images. The Dice similarity coefficient (DSC) was evaluated to assess the segmentation performance. For lesions, true positive rate (TPR) and false positive rate (FPR) were also evaluated. In addition, the effect of lesion size on lesion segmentation was investigated., Results: Highest DSC was observed for all the tissue volumes, including lesions, when the input was combination of all four image contrasts. All other input combinations that included FLAIR also provided high DSC for all tissue classes. However, the quality of lesion segmentation showed strong dependence on the input images. The DSC and TPR values for inputs with the four contrast combination and FLAIR alone were very similar, but FLAIR showed a moderately higher FPR for lesion size <100 μl. For lesions smaller than 20 μl all image combinations resulted in poor performance. The segmentation quality improved with lesion size., Conclusions: Best performance for segmented tissue volumes was obtained with all four image contrasts as the input, and comparable performance was attainable with FLAIR only as the input, albeit with a moderate increase in FPR for small lesions. This implies that acquisition of only FLAIR images provides satisfactory tissue segmentation. Lesion segmentation was poor for very small lesions and improved rapidly with lesion size., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Pathogenicity island excision is a phenomenon that occurs in several Salmonella enterica serovars and other members of the family Enterobacteriaceae. ROD21 is an excisable pathogenicity island found in the chromosome of S. Enteritidis, S. Dublin and S. Typhi among others, which contain several genes encoding virulence-associated proteins. Excision of ROD21 may play a role in the ability of S. Enteritidis to cause a systemic infection in mice. Our previous studies have shown that Salmonella strains unable to excise ROD21 display a reduced ability to colonize the liver and spleen. In this work, we determined the kinetics of ROD21 excision in vivo in C57BL/6 mice and its effect on virulence. We quantified bacterial burden and excision frequency in different portions of the digestive tract and internal organs throughout the infection. We observed that the frequency of ROD21 excision was significantly increased in the bacterial population colonizing mesenteric lymph nodes at early stages of the infective cycle, before 48 hours post-infection. In contrast, excision frequency remained very low in the liver and spleen at these stages. Interestingly, excision increased drastically after 48 h post infection, when intestinal re-infection and mortality begun. Moreover, we observed that the inability to excise ROD21 had a negative effect on S. Enteritidis capacity to translocate from the intestine to deeper organs, which correlates with an abnormal transcription of invA in the S. Enteritidis strain unable to excise ROD21. These results suggest that excision of ROD21 is a genetic mechanism required by S. Enteritidis to produce a successful invasion of the intestinal epithelium, a step required to generate systemic infection in mice., Competing Interests: The authors have declared that no competing interests exist.

Background: Deep learning (DL) is a promising methodology for automatic detection of abnormalities in brain MRI., Purpose: To automatically evaluate the quality of multicenter structural brain MRI images using an ensemble DL model based on deep convolutional neural networks (DCNNs)., Study Type: Retrospective., Population: The study included 1064 brain images of autism patients and healthy controls from the Autism Brain Imaging Data Exchange (ABIDE) database. MRI data from 110 multiple sclerosis patients from the CombiRx study were included for independent testing., Sequence: T 1 -weighted MR brain images acquired at 3T., Assessment: The ABIDE data were separated into training (60%), validation (20%), and testing (20%) sets. The ensemble DL model combined the results from three cascaded networks trained separately on the three MRI image planes (axial, coronal, and sagittal). Each cascaded network consists of a DCNN followed by a fully connected network. The quality of image slices from each plane was evaluated by the DCNN and the resultant image scores were combined into a volumewise quality rating using the fully connected network. The DL predicted ratings were compared with manual quality evaluation by two experts., Statistical Tests: Receiver operating characteristic (ROC) curve, area under ROC curve (AUC), sensitivity, specificity, accuracy, and positive (PPV) and negative (NPV) predictive values., Results: The AUC, sensitivity, specificity, accuracy, PPV, and NPV for image quality evaluation of the ABIDE test set using the ensemble model were 0.90, 0.77, 0.85, 0.84, 0.42, and 0.96, respectively. On the CombiRx set the same model achieved performance of 0.71, 0.41, 0.84, 0.73, 0.48, and 0.80., Data Conclusion: This study demonstrated the high accuracy of DL in evaluating image quality of structural brain MRI in multicenter studies., Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1260-1267., (© 2019 International Society for Magnetic Resonance in Medicine.)

The biological mediation of mineral formation (biomineralization) is realized through diverse organic macromolecules that guide this process in a spatial and temporal manner. Although the role of these molecules in biomineralization is being gradually revealed, the molecular basis of their regulatory function is still poorly understood. In this study, the incorporation and distribution of the model intrinsically disordered starmaker-like (Stm-l) protein, which is active in fish otoliths biomineralization, within calcium carbonate crystals, is revealed. Stm-l promotes crystal nucleation and anisotropic tailoring of crystal morphology. Intracrystalline incorporation of Stm-l protein unexpectedly results in shrinkage (and not expansion, as commonly described in biomineral and bioinspired crystals) of the crystal lattice volume, which is described herein, for the first time, for bioinspired mineralization. A ring pattern was observed in crystals grown for 48 h; this was composed of a protein-enriched region flanked by protein-depleted regions. It can be explained as a result of the Ostwald-like ripening process and intrinsic properties of Stm-l, and bears some analogy to the daily growth layers of the otolith., (© 2019 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)

Head and neck squamous cell carcinoma (HNSCC) cells that are positive for human papillomavirus (HPV+) favor mitochondrial metabolism rather than glucose metabolism. However, the involvement of mitochondrial metabolism in HNSCC HPV+ cells is still unknown. The aim of this work was to evaluate the role of E6 oncoproteins from HPV16 and HPV18 in the mitochondrial metabolism in an HNSCC model. We found that E6 from both viral types abates the phosphorylation of protein kinase B-serine 473 (pAkt), which is associated with a shift in mitochondrial metabolism. E6 oncoproteins increased the levels of protein subunits of mitochondrial complexes (I to IV), as well as the ATP synthase and the protein levels of the voltage dependent anion channel (VDAC). Although E6 proteins increased the basal and leak respiration, the ATP-linked respiration was not affected, which resulted in mitochondrial decoupling. This increase in leak respiration was associated to the induction of oxidative stress (OS) in cells expressing E6, as it was observed by the fall in the glutathione/glutathione disulfide (GSH/GSSG) rate and the increase in reactive oxygen species (ROS), carbonylated proteins, and DNA damage. Taken together, our results suggest that E6 oncoproteins from HPV16 and HPV18 are inducers of mitochondrial metabolism.