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Terrestrial evapotranspiration is the second-largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross-disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET.

Abstract Over the past five decades, a large number of wild animals have been individually identified by various observation systems and/or temporary tracking methods, providing unparalleled insights into their lives over both time and space. However, so far there is no comprehensive record of uniquely individually identified animals nor where their data and metadata are stored, for example photos, physiological and genetic samples, disease screens, information on social relationships. Databases currently do not offer unique identifiers for living, individual wild animals, similar to the permanent ID labelling for deceased museum specimens. To address this problem, we introduce two new concepts: (1) a globally unique animal ID (UAID) available to define uniquely and individually identified animals archived in any database, including metadata archived at the time of publication; and (2) the digital ‘home’ for UAIDs, the Movebank Life History Museum (MoMu), storing and linking metadata, media, communications and other files associated with animals individually identified in the wild. MoMu will ensure that metadata are available for future generations, allowing permanent linkages to information in other databases. MoMu allows researchers to collect and store photos, behavioural records, genome data and/or resightings of UAIDed animals, encompassing information not easily included in structured datasets supported by existing databases. Metadata is uploaded through the Animal Tracker app, the MoMu website, by email from registered users or through an Application Programming Interface (API) from any database. Initially, records can be stored in a temporary folder similar to a field drawer, as naturalists routinely do. Later, researchers and specialists can curate these materials for individual animals, manage the secure sharing of sensitive information and, where appropriate, publish individual life histories with DOIs. The storage of such synthesized lifetime stories of wild animals under a UAID (unique identifier or ‘animal passport’) will support basic science, conservation efforts and public participation.

Abstract High-throughput imaging (HTI) generates complex imaging datasets from a large number of experimental perturbations. Commercial HTI software programs for image analysis workflows typically do not allow full customization and adoption of new image processing algorithms in the analysis modules. While open-source HTI analysis platforms provide individual modules in the workflow, like nuclei segmentation, spot detection, or cell tracking, they are often limited in integrating novel analysis modules or algorithms. Here, we introduce the High-Throughput Image Processing Software (HiTIPS) to expand the range and customization of existing HTI analysis capabilities. HiTIPS incorporates advanced image processing and machine learning algorithms for automated cell and nuclei segmentation, spot signal detection, nucleus tracking, nucleus registration, spot tracking, and quantification of spot signal intensity. Furthermore, HiTIPS features a graphical user interface that is open to integration of new analysis modules for existing analysis pipelines and to adding new analysis modules. To demonstrate the utility of HiTIPS, we present three examples of image analysis workflows for high-throughput DNA FISH, immunofluorescence (IF), and live-cell imaging of transcription in single cells. Altogether, we demonstrate that HiTIPS is a user-friendly, flexible, and open-source HTI software platform for a variety of cell biology applications.

Summary: Background: Facial recognition software (FRS) has historically been perceived as lacking the capability to identify individuals from cross-sectional medical images. Utilising such data for identification purposes was considered infeasible due to the substantial computational power and specialised technical expertise it would require. However, recent advancements in accessible artificial intelligence-based (AI-based) software and open-source tools have made these applications widely available and easy to use, raising new privacy concerns. Methods: This proof-of-concept was designed as a cross-sectional study and included participants with a verified online presence. Standard magnetic resonance imaging (MRI) head scans were performed on these participants, from which three-dimensional rendering (3DR) images were created using free and publicly available software. These images were used for face searches by free and publicly available FRS. Different head orientations and hairstyles were applied to the 3DR images to assess whether non-facial features influenced the FRS results. All results were obtained between the 10th of February 2024 and the 1st of March 2024. Findings: Face searches of 3DR images in a database containing over 800 million images from the World Wide Web (WWW) yielded correct matches for 50% of the participants in less than 10 min. The user-friendly software required minimal computational knowledge or resources, making this process broadly accessible. Modifying elements such as hairstyles or the orientation of the 3DR to better resemble actual photographs of the participants improved FRS matches. Interpretation: Current existing FRS can swiftly and accurately identify individuals from MRI head scans. This poses a significant privacy risk for participants in enrolled clinical trials and highlights the urgent need for improved data protection measures and increased sensitivity to ensure participant confidentiality. Funding: There was no funding source for this study.

Objective: To assess the influence of social support, smoking, and alcohol use on the oral health-related quality of life (OHRQoL) of pregnant women. Material and Methods: A cross-sectional study was conducted on a random sample of 256 pregnant women at a public healthcare service in southern Brazil. OHRQoL was measured using the Oral Health Impact Profile (OHIP-14) questionnaire. A semi-structured questionnaire was administered to collect demographic, socioeconomic, social support, and deleterious habits data. Clinical examinations were performed to diagnose dental caries (DMFT index) and gingivitis (marginal gingival bleeding). A Poisson regression model was used to investigate the influence of pregnant' characteristics on OHRQoL. With this approach, we calculated rate ratio (RR) and 95% confidence intervals (95% CI). Results: The mean overall OHIP-14 score in the sample was 9.74 (SD=9.00). Pregnant women who presented poor social support reported the worst OHRQoL. Regarding deleterious habits, women who drank alcohol (RR=1.18; IC 95%: 1.05-1.33) and smoked (RR=1.20; 95% IC: 1.07-1.35) during pregnancy had higher means in OHIP-14. In addition, older and non-white women who presented untreated dental caries, ≥15% of marginal gingival bleeding, and low household income also reported worse OHRQoL. Conclusion: Our findings suggest that low support social and poor habits during pregnancy influence women's OHRQoL.

Objective: This study investigated the relationship between impulsivity and early trauma through a network analysis in individuals diagnosed with different substance use disorders. Methods: In a cross-sectional design, the sample included 556 men with substance use disorders (195 with alcohol use, 157 with cocaine/crack use, and 214 with polysubstance use). Early trauma and impulsive behavior were assessed using the Childhood Trauma Questionnaire and the Barratt Impulsiveness Scale, respectively. The connection between trauma and impulsivity was assessed using network analysis through a fused graphical lasso algorithm. Results: No connection was observed between impulsivity and trauma networks in individuals with alcohol use disorder. In those with cocaine use disorder, networks were linked through the motor domain and sexual abuse nodes. Inverse connections were observed between the emotional neglect node and perseverance, but not the non-planning node. In polysubstance use, the connection between impulsivity and trauma networks was weak, with the cognitive complexity node connecting to the trauma network through physical abuse. There connections were inversely proportional between the motor domain and emotional neglect nodes, as well as between cognitive instability and physical neglect. Conclusion: Our results suggest that the relationship between the type of early (childhood) trauma and the expression of impulsivity could lead to different substance use profiles.

Abstract Drought and pluvial extremes are defined as deviations from typical climatology; however, background climatology can shift over time in a non‐stationary climate, impacting interpretations of extremes. This study evaluated trends in meteorological drought and pluvial extremes by merging tree‐ring reconstructions, observations, and climate‐model simulations spanning 850–2100 CE across North America to determine whether modern and projected future precipitation lies outside the range of natural climate variability. Our results found widespread and spatially consistent exacerbation of drought and pluvial extremes, especially summer drought and winter pluvials, with drying in the west and south, wetting trends in the northeast, and intensification of both extremes across the east and north. Our study suggests that climate change has already shifted precipitation climatology beyond pre‐Industrial climatology and is projected to further intensify ongoing shifts.

The goals of this article are to outline meat science research priorities, examine the current state of funding, and bring attention to the need for science-based solutions and innovation that maintains competitiveness for meat products while also addressing the talent pipeline of scientists and development of a workforce. It is the product of a meeting of meat scientists across disciplines and species. The meat industry is a cornerstone to modern society and has significant economic importance, with a global worth exceeding $1 trillion. The U.S. meat industry generates over $239 billion in income, supports 1.7 million jobs, and contributes $41 billion in taxes, while benefitting developed and developing nations through robust global trade. Central to the meat industry’s success is the quality of meat products since consumers must have a desire to purchase and consume meat. Livestock and meat production face many challenges. Research efforts must continually increase efficiency, enhance sustainability, reduce climate impacts, address food security, and embrace artificial intelligence, machine learning, robotics, and talent development. However, efforts to impact these areas must also consider downstream impacts on meat quality or risk erosion of consumer satisfaction and demand for meat products. Thus, meat quality should be a fundamental component of all research concerning livestock and meat production, including poultry, small ruminants, and fish/seafood. Despite its significance, there is a troubling trend of decreased public funding for meat quality research in the U.S., posing risks to this essential food source and the development of future scientists. This article provides an overview of meat quality research funding priorities aimed at supporting a sustainable future for meat production, emphasizing the potential implications if funding does not align with these priorities. Furthermore, it highlights the risks to the talent pipeline and global competitiveness if adequate attention is not directed towards these critical areas.

Inshore and offshore bottlenose dolphin, Tursiops truncatus, ecotypes were distinguished through genetics, distribution, diet, morphology, diversity, and social behaviors. Although T. truncatus is a widely studied species, few studies have focused on offshore populations. Offshore biodiversity is frequently neglected due to the difficulty of data collection, and therefore, it is challenging to assess how threatened these populations are. A small, offshore population of dolphins residing around the Saint Peter Saint Paul Archipelago (SPSPA) in the middle of the Atlantic Ocean has been monitored for several years, and a decrease in the number of dolphin sightings has recently been noticed. We analyzed a comprehensive mtDNA control-region sequence dataset for this species to infer the conservation status and better understand the relationships between the SPSPA population and other offshore populations. We assessed the genetic diversity and population structure of the bottlenose dolphin from inshore and offshore populations of the Atlantic Ocean. Offshore populations are more genetically diverse and have less variation between populations than inshore populations. The offshore populations share haplotypes, indicating potential gene flow. However, the SPSPA population presented the lowest levels of genetic diversity between populations. The conservation status of the SPSPA population is concerning, and it is necessary to apply effective management strategies to guarantee its protection.

Wetland CH₄ emissions are among the most uncertain components of the global CH₄ budget. The complex nature of wetland CH₄ processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH₄ emissions. In this study, we used the flux measurements of CH₄ from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH₄ emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH₄ emissions in all studied wetland types. Ecosystem respiration (CO₂) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH₄ emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH₄ emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH₄ emissions within earth system land models.

Objetivo: avaliar a presença e a extensão dos atributos essenciais da Atenção Primária à Saúde na perspectiva dos usuários da Estratégia Saúde da Família. Método: estudo transversal, quantitativo, com 256 usuários de 26 unidades de saúde da família de Santa Catarina, Brasil, realizado entre junho e dezembro de 2021. Utilizou-se questionário de caracterização e Instrumento de Avaliação da Atenção Primária. Realizou-se análise estatística descritiva e inferencial. Resultados: os usuários avaliaram que as unidades apresentaram índice abaixo do ideal da presença e extensão dos atributos essenciais. Contudo, usuários com algum problema de saúde avaliaram de forma positiva o escore essencial (p=0,001), atributo longitudinalidade (p=0,024) e atributo integralidade (p=0,001). Conclusão: avaliar a presença e extensão dos atributos de forma periódica permite orientar estratégias de fortalecimento e contribui para melhoria contínua da Atenção Primária, com base em indicadores para a gestão em saúde qualificada, sendo diferencial considerar o olhar dos usuários.

Objective: to evaluate the presence and extent of the essential attributes of Primary Health Care from the perspective of users of the Family Health Strategy. Method: this was a cross-sectional, quantitative study of 256 users of 26 family health units in Santa Catarina, Brazil, carried out between June and December 2021. A characterization questionnaire and the Primary Care Assessment Instrument were used. Descriptive and inferential statistics analysis was carried out. Results: users evaluated the units as having a sub-optimal score for the presence and extent of the essential attributes. However, users with health problems rated the essential score (p=0.001), the longitudinality attribute (p=0.024), and the comprehensiveness attribute (p=0.001) positively.). Conclusion: periodically evaluating the presence and extent of the attributes makes it possible to guide strengthening strategies and contributes to the continuous improvement of Primary Care, based on indicators for qualified health management, with the difference of considering the views of users.

Objetivo: evaluar la presencia y extensión de los atributos esenciales de la Atención Primaria de Salud desde la perspectiva de los usuarios de la Estrategia Salud de la Familia. Método: estudio cuantitativo transversal, con 256 usuarios de 26 unidades de salud de la familia del estado de Santa Catarina, Brasil, realizado entre junio y diciembre de 2021. Se utilizó un cuestionario de caracterización y un Instrumento de Evaluación de Atención Primaria. Se realizó análisis estadístico descriptivo e inferencial. Resultados: los usuarios evaluaron que las unidades tenían un índice por debajo del nivel ideal de presencia y extensión de los atributos esenciales. Pero, los usuarios con un problema de salud evaluaron positivamente el puntaje esencial (p=0,001), el atributo longitudinalidad (p=0,024) y el atributo integralidad (p=0,001). Conclusión: evaluar periódicamente la presencia y extensión de los atributos permite orientar estrategias de fortalecimiento y contribuye a mejorar continuamente la Atención Primaria, en base a indicadores para una gestión de la salud calificada, y considerar la perspectiva de los usuarios marca la diferencia.

IntroductionApproximately 10% of breast cancer (BC) cases result from hereditary causes. Genetic testing has been widely implemented in BC care to determine hereditary cancer syndromes and personalized medicine. Thus, identification of individuals carrying germline pathogenic variants could be useful to provide appropriate prophylactic or screening measures for each BC subtype, however, there are few formal recommendations for genetic testing in this sense so far. In this study, we assessed rare germline variants in a specific group of genes in order to determine the association with human epidermal growth factor 2 enriched (HER2+) BC phenotype through a systematic review and meta-analysis comparing subtypes overexpressing HER2 with other clinically recognized subtypes of BC. This review was registered with PROSPERO (ID: CRD42023447571).MethodsWe conducted an online literature search in PubMed (MEDLINE), Scopus, and EMBASE databases. We included original studies that investigated germline variants in HER2+ BC patients and selected the studies that reported only rare and/or pathogenic germline variants. We assessed the risk of bias and quality of the studies using the Joanna Briggs Institute Critical Appraisal checklists and the Modified Newcastle-Ottawa Scale for Genetic Studies, respectively. Considering hormone receptor and HER2 expression status, we compared gene-based risks initially in HR-HER2-, HR+HER2-, HR+HER2+, and HR-HER2+ groups, conducting separate meta-analyses using the random effects model for each comparison, and within them for each gene.ResultsOf the total 36 studies describing germline variants, 11 studies provided information on the prevalence of variants in the different clinically relevant BC subtypes and allowed comparisons. Germline variants within eight genes showed significant differences when meta-analyzed between the BC groups: BRCA1, BRCA2, TP53, ATM, CHEK2, PALB2, RAD51C, and BARD1. Notably, TP53, ATM, and CHEK2 germline variants were identified as predisposing factors for HER2+ subtypes, whereas BRCA1, BRCA2, PALB2, RAD51C, and BARD1 germline variants were associated with a predisposition to low HER2 expression. Main concerns about bias and quality assessment were the lack of confounding factors control; and comparability or outcome assessment, respectively. DiscussionOur findings underscore the connection between germline variants and differential expression of the HER2 protein and BC subtypes.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42023447571.

Abstract We evaluated the landscape of the North and Northwest of Rio de Janeiro, determining changes in forest cover by phytophysiognomy using collection 6 of MapBiomas (1985-2020). We worked in the R environment and QGIS. Among the phytophysiognomies, the Lowland forests showed the greatest area loss until 1985 (93%), becoming highly fragmented and isolated in the landscape. Between 1985 and 2020 the loss of forest was reduced. However, this result is related to the balance of secondary vegetation increase that covers up the losses of mature vegetation, with risks to biodiversity. The main driver of vegetation loss was agriculture, and currently less than 8% of the vegetation is protected. The procrastination in the establishment of conservation units and restoration of permanent protection areas will have serious negative consequences for the conservation of the vegetation in this region.

ABSTRACT BACKGROUND: Some maternal characteristics are related to alcohol intake during pregnancy, which irreversibly compromises the maternal-fetal binomial integrity. OBJECTIVES: To identify the frequency, impact, and factors associated with alcohol consumption during pregnancy. DESIGN AND SETTING: A cross-sectional study was performed at the Hospital Materno Infantil Presidente Vargas (HMIPV) in Porto Alegre/RS between March and December 2016. METHODS: A structured questionnaire was administered along with a medical records review. They refer to the maternal sociodemographic and gestational status, alcohol consumption patterns, and characteristics of the fetus/newborn. In the statistical analysis, P values < 0.05 were considered significant. RESULTS: The frequency of alcohol intake was 37.3%; this was characterized by the consumption of fermented beverages (89.3%), especially during the first trimester (79.6%). Risky consumption (high and/or early) occurred for 30.2% of participants. Risk factors associated with maternal alcohol consumption during pregnancy were tobacco use (P < 0.001) and abortion attempt (P = 0.023). Living with a partner (P = 0.002) and planning pregnancy (P = 0.009) were protective factors. Risky consumption was related to all of the aforementioned variables as well as threatened abortion (P = 0.023). CONCLUSIONS: Alcohol intake during pregnancy is common and affects nearly one-third of pregnant women. Knowledge of the population at risk and protective factors is essential for the development of campaigns that seek to reduce consumption and, therefore, its consequences for the mother and fetus.

Wetland water depth influences microbial and plant communities, which can alter the above- and below-ground carbon cycling of a wetland. Wetland water depths are likely to change due to shifting precipitation patterns, which will affect projections of greenhouse gas emissions; however, these effects are rarely incorporated into wetland greenhouse gas models. Seeking to address this gap, we used a mechanistic model, ecosys, to simulate a range of water depth scenarios in a temperate wetland, and analyzed simulated predictions of carbon dioxide (CO2) and methane (CH4) fluxes over the 21st century. We tested our model using eddy covariance measurements of CO2 and CH4 fluxes collected at the Old Woman Creek National Estuarine Research Reserve (OWC) during 2015 and 2016. OWC is a lacustrine, estuarine, freshwater, mineral-soil marsh. An empirical model found that the wetland water depth is highly dependent on the water depth of the nearby Lake Erie. Future wetland surface water depths were modeled based on projection of Lake Erie's water depth using four separate NOAA projections, resulting in four wetland water-depth scenarios. Two of the four 21st century projections for Lake Erie water depths used in this study indicated that the water depth of the wetland would remain nearly steady; however, the other two indicated decreases in the wetland water depth. In our scenario where the wetland dries out, we project the wetland's climatological warming effect will decrease due to smaller CH4 fluxes to the atmosphere and larger CO2 uptake by the wetland. We also found that increased water level can lower emissions by shifting the site towards more open water areas, which have lower CH4 emissions. We found that decreased water depths would cause more widespread colonization of the wetland by macrophyte vegetation. Using an empirical relationship, we also found that further drying could result in other, non-wetland vegetation to emerge, dramatically altering soil carbon cycling. In three of our four projections, we found that in general the magnitude of CO2 and CH4 fluxes steadily increase over the next 100 years in response to higher temperatures. However, in our driest simulations, we projected a different response due to increased oxidation of soil carbon, with CH4 emissions decreasing substantially from an annual cumulative peak of 224.6 to a minimum of 104.7 gC m-2 year-1. In that same simulation, net cumulative flux of CO2 changed from being a sink of 56.5 gC m-2 year-1 to a source of 369.6 gC m-2 year-1 over the same period, despite a temperature increase from 13.7 °C to 14.2 °C. This temperature shift in our other three cases with greater water depths increased the source strength of CH4 and the sink strength of CO2. We conclude that the magnitude of wetland greenhouse-gas fluxes depended on the water depth primarily as it affected the areal percentage of the wetland available for plant colonization, but dramatic decreases in water depths could cause significant reductions in the wetland CH4 fluxes, while simultaneously altering the wetland vegetation.

A Extensão Universitária é um importante veículo de comunicação entre a universidade e a sociedade, que visa a produção de conhecimentos e a interlocução das atividades acadêmicas de ensino e pesquisa, através de processos ativos de formação. Nesse sentido, a Universidade do Estado de Minas Gerais – Unidade Frutal, tem colocado em prática diferentes iniciativas junto à comunidade externa, no sentido de estimular o interesse pelas ciências. Um dos momentos importantes dessa construção de conhecimento tem culminado nas Feiras de Ciências. Esse relato apresenta um conjunto de atividades desenvolvidas durante nove oficinas ofertadas para os docentes do ensino básico do Município de Frutal - MG. O intuito dessas oficinas é no sentido de auxiliar os professores do ensino fundamental e médio para o desenvolvimento de projetos de pesquisa. As oficinas foram conduzidas algumas semanas antes da II Feira de Ciências da UEMG – Frutal e contaram com a participação de 12 palestrantes de 7 instituições acadêmicas de ensino técnico ou superior, e 15 docentes do ensino básico do Município. As oficinas tiveram como principais metas proporcionar aos docentes: (i) uma autonomia maior na elaboração de projetos de pesquisa; (ii) o entendimento dos procedimentos técnico-metodológicos que compõem um projeto científico; e (iii) a compreensão da importância da padronização e apresentação do projeto científico. Espera-se que os resultados obtidos gerem uma maior e melhor participação desses professores nas próximas feiras de ciências, bem como a capacitação daqueles para a publicação de trabalhos científicos obtidos a partir de seus projetos escolares.

While dysfunction and death of light-detecting photoreceptor cells underlie most inherited retinal dystrophies, knowledge of the species-specific details of human rod and cone photoreceptor cell development remains limited. Here, we generated retinal organoids carrying retinal disease-causing variants in NR2E3, as well as isogenic and unrelated controls. Organoids were sampled using single-cell RNA sequencing (scRNA-Seq) across the developmental window encompassing photoreceptor specification, emergence, and maturation. Using scRNA-Seq data, we reconstruct the rod photoreceptor developmental lineage and identify a branch point unique to the disease state. We show that the rod- specific transcription factor NR2E3 is required for the proper expression of genes involved in phototransduction, including rhodopsin, which is absent in divergent rods. NR2E3-null rods additionally misexpress several cone-specific phototransduction genes. Using joint multimodal single-cell sequencing, we further identify putative regulatory sites where rod-specific factors act to steer photoreceptor cell development. Finally, we show that rod-committed photoreceptor cells form and persist throughout life in a patient with NR2E3-associated disease. Importantly, these findings are strikingly different from those observed in Nr2e3 rodent models. Together, these data provide a road map of human photoreceptor development and leverage patient induced pluripotent stem cells to define the specific roles of rod transcription factors in photoreceptor cell emergence and maturation in health and disease., Introduction The human retina is a transparent multilayered neural tissue lining the posterior two-thirds of the eye that is responsible for detecting visual information and sending it to the brain [...]

Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO2 ) and methane (CH4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post-thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post-thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO2 and CH4  fluxes from decomposition. Thus, the increased C-storage expected from higher productivity was limited and the high global warming potential of CH4 contributed a net positive warming effect. Although post-thaw peatlands are currently C sinks due to high NPP offsetting high CO2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

The object of this study was to characterize the synthesis and metabolism of platelet activating factor (PAF) by intestinal mucosa subjected to ischaemia–reperfusion injury. Canine intestinal mucosa produced 16:0-PAF, 18:0-PAF, and high levels of the corresponding lyso- PAF metabolites. Three h of intestinal ischaemia and ischaemia followed by 1 h of reperfusion did not affect the synthesis or metabolism of PAF by intestinal mucosa. Intestinal mucosa elaborated a factor that rapidly hydrolyzes PAF to lyso-PAF. The observed hydrolysis rate was not altered by ischaemia or ischaemia and reperfusion. In conclusion, this study suggests that intestinal mucosa produces PAF and rapidly hydrolyzes PAF. The PAF synthesis and metabolism rates of intestinal mucosa is not altered by ischaemia reperfusion in this model under the imposed conditions.

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

Introduction: The study was designed to evaluate the frequency of detection and the characteristics of subsolid nodules (SSNs) in outpatients’ chest computed tomography (CT) scans from a private hospital in Southern Brazil. Methods: A retrospective analysis of all chest CT scans was performed in adult patients from ambulatory care (non-lung cancer screening population) over a thirty-day period. Inclusion criteria were age > 18 years and lung-scanning protocols, including standard-dose high-resolution chest CT (HRCT), enhanced CT, CT angiography, and low-dose chest CT (LDCT). SSNs main features collected were mean diameter, number, density (pure or heterogenous ground glass nodules and part-solid), and localization. TheLungRADS system and the updated Fleischner Society’s pulmonary nodules recommendations were used for categorization only for study purposes, although not specifically fitting the population. The presence of emphysema, as well as calcified and solid nodules were also addressed. Statistical analysis was performed using R software, categorial variables are shown as absolute or relative frequencies, and continuous variables as mean and interquartile ranges. Results: Chest computed tomography were performed in 756 patients during the study period (September 2019), and 650 met the inclusion criteria. The IQR for age was 53/73 years; most participants were female (58.3%) and 10.6% had subsolid nodules detected. Conclusions: The frequency of SSNs detection in patients in daily clinical practice, not related to screening populations, is not negligible. Regardless of the final etiology, follow-up is often indicated, given the likelihood of malignancy for persistent lesions.

BackgroundBreast and prostate cancers are the most common malignancies diagnosed in women and men respectively, and present with great clinical heterogeneity, even in tumors with the same histology and same site of origin. Somatic and germline molecular alterations in DNA may have prognostic and predictive impact, influencing response to therapies and overall survival. Our aim is to characterize the somatic and germline genomic landscape of women with locally advanced HER2-positive breast cancer and men with metastatic prostate cancer in Brazil. Secondarily, we aim to identify genetic variants associated with tumor prognosis and treatment response, identify patients carrying pathogenic alterations in cancer-predisposing genes, and characterize the genetic ancestry of the population included in the study.MethodsThis observational multicenter cohort study will include 550 adult patients from the five macro-regions of Brazil, divided into two arms: 1) breast cancer and 2) prostate cancer. Clinical and pathological data will be collected, as well as DNA samples from peripheral blood and tumor samples. In arm 1, the inclusion criteria are a histological diagnosis of breast carcinoma with overexpression of HER-2, clinical stage II or III, and current neoadjuvant treatment with chemotherapy plus trastuzumab. In arm 2, the criterion is a histological diagnosis of prostate adenocarcinoma, clinical stage IV. Whole-exome sequencing (WES) will be performed to identify variants that may be drivers and/or actionable in a specific patient or tumor. These variants will be interpreted and classified according to their population frequencies, in silico predictors, functional studies, and literature data, following international guidelines proposed by expert societies.DiscussionThis trial will contribute to the construction of a robust database that should provide a better understanding of the genomic profile of patients with breast and prostate cancer in Brazil. Considering the miscegenation of the Brazilian population, knowledge generated from these data will have implications for future studies of this specific population.Clinical trial registration[clinicaltrial.gov], identifier [NCT05306600]

ABSTRACT Objective: To evaluate the prognosis and influence of associated factors in patients with congenital heart disease admitted for the first time to the Intensive Care Unit of the Hospital da Criança Santo Antônio/Irmandade da Santa Casa de Misericórdia de Porto Alegre, especially those factors associated with death. Methods: Patients were prospectively and consecutively allocated over a period of one year (August 2005 to July 2006). Now, 15 years after the initial selection, we collected data from these patients in the database of the Cytogenetics Laboratory of the Universidade Federal de Ciências da Saúde de Porto Alegre and in the medical records of the hospital. Results: Of the 96 patients, 11 died and 85 were alive until 20 years old. Four patients died in the Intensive Care Unit. The survival probability up to 365 days of life was 95.8%. The survival assessment identified that the deaths occurred mainly before the patients completed one thousand days of life. We found that complex heart disease was independently associated with an odds ratio of 5.19 (95% confidence interval — CI:1.09–24.71; p=0.038) for death. Conclusions: Knowledge about the factors that interfere with the prognosis can be crucial in care practice planning, especially considering that congenital heart disease is an important cause of mortality in the first year of life.

The severe loss of body condition score (BCS) during the early lactation period has been associated with infertility in cows. However, the mechanisms are not fully understood. The aim of this study was to examine the effect of BCS loss on liver health, and ovarian functions in cows during early lactation. Retrospectively multiparous cows from two farms were categorized based on units of BCS (1–5 scale) loss as Moderate (MOD,

Several theories have been proposed to explain the complex diagnostic aspects related to addiction disorders and their development. Recent frameworks tend to focus on dimensional perspectives of symptoms rather than categorical systems, since substance use disorders are frequently comorbid with other psychiatric and especially personality disorders. However, useful transdiagnostic models that could integrate clinical evaluation derived from neuroscientific theories are lacking. In the present manuscript, the authors propose a model based on a new paradigm, in an attempt to better explain this complex, multifaceted phenomenon. The new paradigm presupposes that emotions and behavior are a response to risk prediction. Individuals make choices and engage in actions to manage potential risks/rewards in order to seek or maintain homeostasis in their internal and external environments – a mechanism that the authors call predostatic (predictive mechanism with homeostatic purpose). The model considers three main modes of the predostatic mind: (1) Alarm Mode, activated by high and/or imminent risk prediction; (2) Seek Mode, activated by long-term risk or reward prediction; and (3) Balance Mode, a self-regulating state of mind related to low risk prediction, a soothing system and a calm state. Addiction is seen as a chronic dysregulation of organism systems leading to internalizing or externalizing phenomena mainly related to the Seek and Alarm Modes, which are persistently activated by reward and risk prediction, respectively, thus hindering Balance. Addiction neuroscience research has shown that chronic drug use or engagement in addictive behaviors can lead to neuroadaptations in the brain reward circuitry, disrupting normal balance and the regulation of reward processes. This dysregulation can contribute to persistent drug-seeking/addictive behaviors despite negative consequences. This newly proposed dynamic and integrative model, named dysregulation based on externalizing and internalizing phenomena of the three main modes of the predostatic mind (DREXI3), proposes six dysregulation dimensions with basic emotional and behavioral symptoms, such as neurophysiological alterations, impulsivity, compulsion, cognitive impairment/psychosis, mood, and anxiety/anger. In this paper, the authors explain the rationale behind DREXI3 and present some hypothetical clinical examples to better illustrate the use of the model in clinical practice. The development of this innovative model could possibly guide tailored treatment interventions in the addiction field.

ABSTRACT Objective: To investigate the detection of subsolid nodules (SSNs) on chest CT scans of outpatients before and during the COVID-19 pandemic, as well as to correlate the imaging findings with epidemiological data. We hypothesized that (pre)malignant nonsolid nodules were underdiagnosed during the COVID-19 pandemic because of an overlap of imaging findings between SSNs and COVID-19 pneumonia. Methods: This was a retrospective study including all chest CT scans performed in adult outpatients (> 18 years of age) in September of 2019 (i.e., before the COVID-19 pandemic) and in September of 2020 (i.e., during the COVID-19 pandemic). The images were reviewed by a thoracic radiologist, and epidemiological data were collected from patient-filled questionnaires and clinical referrals. Regression models were used in order to control for confounding factors. Results: A total of 650 and 760 chest CT scans were reviewed for the 2019 and 2020 samples, respectively. SSNs were found in 10.6% of the patients in the 2019 sample and in 7.9% of those in the 2020 sample (p = 0.10). Multiple SSNs were found in 23 and 11 of the patients in the 2019 and 2020 samples, respectively. Women constituted the majority of the study population. The mean age was 62.8 ± 14.8 years in the 2019 sample and 59.5 ± 15.1 years in the 2020 sample (p < 0.01). COVID-19 accounted for 24% of all referrals for CT examination in 2020. Conclusions: Fewer SSNs were detected on chest CT scans of outpatients during the COVID-19 pandemic than before the pandemic, although the difference was not significant. In addition to COVID-19, the major difference between the 2019 and 2020 samples was the younger age in the 2020 sample. We can assume that fewer SSNs will be detected in a population with a higher proportion of COVID-19 suspicion or diagnosis.

While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.