Explaining the emergence of land-use frontiers.

Land-use expansion is linked to major sustainability concerns including climate change, food security and biodiversity loss. This expansion is largely concentrated in so-called 'frontiers', defined here as places experiencing marked transformations owing to rapid resource exploitation. Understanding the mechanisms shaping these frontiers is crucial for sustainability. Previous work focused mainly on explaining how active frontiers advance, in particular, into tropical forests. Comparatively, our understanding of how frontiers emerge in territories considered marginal in terms of agricultural productivity and global market integration remains weak. We synthesize conceptual tools explaining resource and land-use frontiers, including theories of land rent and agglomeration economies, of frontiers as successive waves, spaces of territorialization, friction and opportunities, anticipation and expectation. We then propose a new theory of frontier emergence, which identifies exogenous pushes, legacies of past waves and actors' anticipations as key mechanisms by which frontiers emerge. Processes of differential rent creation and capture and the built-up of agglomeration economies then constitute key mechanisms sustaining active frontiers. Finally, we discuss five implications for the governance of frontiers for sustainability. Our theory focuses on agriculture and deforestation frontiers in the tropics but can be inspirational for other frontier processes including for extractive resources, such as minerals.

A Pilot Clinical and Technical Validation of an Immersive Virtual Reality Platform for 3D Anatomical Modeling and Contouring in Support of Surgical and Radiation Oncology Treatment Planning.

The aim of this study was to validate a novel medical virtual reality (VR) platform used for medical image segmentation and contouring in radiation oncology and 3D anatomical modeling and simulation for planning medical interventions, including surgery. The first step of the validation was to verify quantitatively and qualitatively that the VR platform can produce substantially equivalent 3D anatomical models, image contours, and measurements to those generated with existing commercial platforms. To achieve this, a total of eight image sets and 18 structures were segmented using both VR and reference commercial platforms. The image sets were chosen to cover a broad range of scanner manufacturers, modalities, and voxel dimensions. The second step consisted of evaluating whether the VR platform could provide efficiency improvements for target delineation in radiation oncology planning. To assess this, the image sets for five pediatric patients with resected standard-risk medulloblastoma were used to contour target volumes in support of treatment planning of craniospinal irradiation, requiring complete inclusion of the entire cerebral-spinal volume. Structures generated in the VR and the commercial platforms were found to have a high degree of similarity, with dice similarity coefficient ranging from 0.963 to 0.985 for high-resolution images and 0.920 to 0.990 for lower resolution images. Volume, cross-sectional area, and length measurements were also found to be in agreement with reference values derived from a commercial system, with length measurements having a maximum difference of 0.22 mm, angle measurements having a maximum difference of 0.04°, and cross-sectional area measurements having a maximum difference of 0.16 mm2. The VR platform was also found to yield significant efficiency improvements, reducing the time required to delineate complex cranial and spinal target volumes by an average of 50% or 29 min.

Frequency of Oral Lesions, Olfactory, and Gustatory Disorders and Xerostomia in Patients with COVID-19.

COVID-19, a respiratory illness with a global impact on millions, has recently been linked to manifestations affecting various bodily systems, including the oral cavity. Studies highlight oral issues, like ulcers, blisters, and white patches, alongside olfactory and gustatory dysfunction, influencing an individual's quality of life. In this context, our study aimed to assess the frequency of oral lesions, olfactory and gustatory disorders, and xerostomia resulting from COVID-19. An observational study was conducted with 414 patients to evaluate the frequency of oral symptoms resulting from COVID-19. Patients were diagnosed with mild symptoms and evaluated through clinical examination of the oral cavity and a questionnaire to assess functional alterations. The findings showed that 139 out of 414 patients presented clinical manifestations, with oral lesions being the most prevalent (19.1%), followed by gustatory disorders (18.1%), xerostomia (14.2%), and olfactory dysfunction (14%). The most prevalent oral lesions were ulcerations (n = 51), candidiasis (n = 8), and erythema or red plaques (n = 7). Unfortunately, 50 (12.1%) patients died during this study. Therefore, oral lesions, olfactory and gustatory dysfunctions, and xerostomia are common symptoms associated with COVID-19.

Accuracy of the Verbal Autopsy questionnaire in the diagnosis of COVID-19 deaths in a Brazilian capital.

The Verbal Autopsy (VA) is a questionnaire about the circumstances surrounding a death. It was widely used in Brazil to assist in postmortem diagnoses and investigate excess mortality during the Coronavirus Disease 2019 (COVID-19) pandemic. This study aimed to determine the accuracy of investigating acute respiratory distress syndrome (ARDS) using VA. This is a cross-sectional study with prospective data collected from January 2020 to August 2021 at the Death Verification Service of Sao Luis city, Brazil. VA was performed for suspected COVID-19 deaths, and one day of the week was randomly chosen to collect samples from patients without suspected COVID-19. Two swabs were collected after death and subjected to reverse transcription-polymerase chain reaction (RT-PCR) for SARS-CoV-2 detection. Of the 250 cases included, the VA questionnaire identified COVID-19-related ARDS in 67.2% (52.98% were positive for COVID-19). The sensitivity of the VA questionnaire was 0.53 (0.45-0.61), the specificity was 0.75 (0.64-0.84), the positive predictive value was 0.81 (0.72-0.88), and the negative predictive value was 0.44 (0.36-0.53). The VA had a lower-than-expected accuracy for detecting COVID-19 deaths; however, because it is an easily accessible and cost-effective tool, it can be combined with more accurate methods to improve its performance.

A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Influence of Stroke Onset Location on the Efficacy of Endovascular Thrombectomy: Comparison of Outcomes Between In-hospital vs. Community-Onset Strokes.

BACKGROUND AND PURPOSE: Previous studies have suggested that patients suffering an in-hospital stroke (IHS) may face delays in treatment and worse outcomes compared to patients with community-onset strokes (COS). However, most studies occurred when intravenous thrombolysis was the primary treatment. This study aimed to examine the outcomes of patients experiencing an IHS in the endovascular thrombectomy (EVT) era. MATERIALS AND METHODS: Single-center retrospective cohort study of patients older than 18 years with acute ischemic stroke (AIS) treated with EVT within 12 hours of stroke onset from January 1, 2015, to April 30, 2021. Patients were classified into two groups: in-hospital strokes (IHS) and community-onset strokes (COS). We compared time metrics of stroke care delivery, rate of successful reperfusion, and functional outcome as scored using the modified Rankin Scale (mRS) score at 90 days (favorable outcome was defined as mRS 0-2). Differences in proportions were assessed using Fisher's exact and Chi-Square tests as appropriate. For continuous variables, differences in medians between groups were evaluated using Mann-Whitney U tests. RESULTS: A total of 676 consecutive patients were included, with 69 (10%) comprising the IHS group. IHS patients were more likely to have diabetes (36% vs. 18%, p=0.02) and less likely to receive thrombolysis (25% vs 68%, p<0.001) than the COS group but were otherwise similar. IHS patients had significantly faster overall time metrics, most notably from stroke recognition to imaging (median [IQR], 70 [38-141] min vs 121 [74-228] min, p<0.001). Successful recanalization was achieved in > 75% in both groups (p=0.39), with a median NIHSS at discharge <4 (p=0.18). The 90-day mRS was similar in both groups, with a trend of higher in-hospital mortality in the IHS group (p=0.06). CONCLUSIONS: IHS patients had shorter workflow delays to initiation of EVT compared to their community counterparts but with a similar rate of successful recanalization and clinical outcomes. Importantly, 90 day mortality and mRS scores were equivalent between IHS and COS. ABBREVIATIONS: AIS = acute ischemic stroke; LVO = large vessel occlusion; IHS= in-hospital stroke; COS= community-onset stroke; EVT= endovascular thrombectomy; CSC= comprehensive stroke center; TOAST= Trial of Org 10172 in Acute Stroke Treatment.

Outcomes of SARS-CoV-2 and seasonal viruses among 2 million adults hospitalized for severe acute respiratory infection during the COVID-19 pandemic in Brazil.

BACKGROUND: The outbreak of the COVID-19 pandemic has had a profound impact on the circulation of seasonal respiratory viruses. This study aimed to compare the outcomes of SARS-CoV-2 and seasonal viruses in adults hospitalized with severe acute respiratory infection (SARI) during the COVID-19 pandemic. METHODS: This population-based cohort study included patients aged > 18 years hospitalized for SARI in Brazil between February 2020 and February 2023. The primary outcome was in-hospital mortality. A competing risk analysis was used to account for competing events. RESULTS: In total, 2,159,171 patients were included in the study. SARS-CoV-2 was the predominant virus (98.7%). The cumulative incidence of in-hospital mortality was 33.1%, 31.5%, 21.0%, 18.7%, and 18.6%, for patients positive for SARS-CoV-2, adenovirus, RSV, influenza, and other viruses, respectively. SARS-CoV-2 accounted for 99.3% of the deaths. Older age, male sex, comorbidities, hospitalization in the northern region, and oxygen saturation <95% were the common risk factors for death among all viruses. CONCLUSIONS: In this large cohort study, individuals infected with SARS-CoV-2 or adenovirus had the highest risk of mortality. Irrespective of the virus type, older age, male sex, comorbidities, hospitalization in vulnerable regions, and low oxygen saturation were associated with an increased risk of fatality.

Five-Year Serial Brain MRI Analysis of Military Members Exposed to Chronic Sub-Concussive Overpressures.

BACKGROUND: The Canadian Special Operations Forces Command conducts explosives operations and training which exposes members to explosive charges at close proximity. This 5-year longitudinal trial was conducted in follow-up to our initial trial which examined military breachers with MRI and EEG pre and post blast exposure. PURPOSE: To examine brain MRI findings in military personnel exposed to multiple repeated blast exposures. STUDY TYPE: Five-year longitudinal prospective trial. POPULATION: Ninety-two males aged 23-42 with an average of 9.4 years of blast exposure. FIELD STRENGTH/SEQUENCE: 3 T brain MRI/T1-weighted 3D with reconstruction in three planes, T2-weighted, T2-weighted fluid attenuated inversion recovery (FLAIR) 3D with reconstruction in three planes, T2-weighted gradient spin echo (GRE), saturation weighted images, DWI and ADC maps, diffusion tensor imaging. ASSESSMENT: All MRI scans were interpreted by the two neuroradiologists and one neuroradiology Fellow in a blinded fashion using a customized neuroradiology reporting form. STATISTICAL TESTS: Matching parametric statistics represented the number of participants whose brain parameters improved or deteriorated over time. Odds ratio (OR) and 95% confidence intervals (CI) were computed using log regression modeling to determine volume loss, white matter lesions, hemosiderosis, gliosis, cystic changes and enlarged Virchow Robin (VR) spaces. A Kappa (κ) statistic with a 95% CI was calculated to determine rater variability between readers. RESULTS: A significant deterioration was observed in volume loss (OR = 1.083, 95% CI 0.678-1.731, permutation test), white matter changes (OR: 0.754, 95% CI 0.442-1.284, permutation test), and enlargement of VR spaces (OR: 0.775, 95% CI 0.513-1.171). Interrater reliability was low: κ = 0.283, 0.156, and 0.557 for volume loss, white matter changes, and enlargement of VR spaces, respectively. DATA CONCLUSION: There were significant changes in brain volume, white matter lesions, and enlargement of VR spaces. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

The impact of smoking on COVID-19-related mortality: a Brazilian national cohort study.

INTRODUCTION: Current evidence suggests the potential heightened vulnerability of smokers to severe coronavirus disease (COVID-19) outcomes. AIMS: This study aimed to analyze the clinical outcomes and mortality related to tobacco use in a cohort of hospitalized Brazilian COVID-19 patients. METHODS: This retrospective cohort study analyzed adults hospitalized for COVID-19 in Brazil using the SIVEP-Gripe database (official data reported by public and private healthcare facilities for monitoring severe acute respiratory syndrome cases in Brazil). The inclusion criteria were patients over 18 years of age with a positive RT-qPCR test for SARS-CoV-2. The analysis focused on in-hospital mortality, considering smoking as an exposure variable, and included covariates such as age, gender, and comorbidities. Smoking history was collected from the self-reported field in the database. Statistical analyses included descriptive statistics, crude Odds Ratios, and multivariable binary logistic regression. RESULTS: This study included 2,124,285 COVID-19 patients, among whom 44,774 (2.1 %) were smokers. The average age of the smokers was higher than that of the never-smokers (65.3 years vs. 59.7 years). The clinical outcomes revealed that smokers had higher rates of intensive care unit admission (51.6 % vs. 37.2 % for never-smokers), invasive ventilatory support (31.5 % vs. 20.2 % for never-smokers), and higher mortality (42.7 % vs. 31.8 % for never smokers). In the multivariable analysis, smokers demonstrated a heightened risk of death (aOR 1.23; 95 % CI 1.19-1.25). CONCLUSIONS: This large populational-based cohort study confirms the current evidence and underscore the critical importance of recognizing smoking as a substantial risk factor for adverse outcomes in COVID-19 patients.

Malignant transformation of vestibular schwannoma after radiation therapy.

Stereotactic radiosurgery (SRS) is an effective treatment for vestibular schwannomas, offering high rates of tumor control and low neurological risks. Long-term complications of SRS are not fully understood, with several cases of malignant transformation reported in the literature. We report the case of a 50-year-old female with no prior history of neurofibromatosis who presented in 2013 with MRI evidence of a benign vestibular schwannoma. Despite treatment with CyberKnife SRS, she presented 6 years later with new onset neurologic symptoms. Further investigation showed stable lesion size with increasing vasogenic edema and a new area of enhancement in the brainstem, suspicious for malignant transformation. Subsequent treatment with partial craniectomy and histopathologic analysis was consistent with a malignant peripheral nerve sheath tumor diagnosis. Our case adds to a series of 24 similar cases in the literature, details of which have been summarized in our study. Overall, findings support the need for lifelong surveillance following SRS treatment of benign vestibular schwannomas. Patients should be educated on the potential risk of this complication, and clinicians must maintain a high level of suspicion for potential radiation-induced malignancy during the patient's clinical course.

The association between schizophrenia and increased COVID-19 mortality in a cohort of over 2 million people in Brazil.

OBJECTIVE: To describe the clinical outcomes and risk factors of death related to mental disorders in a cohort of Brazilian hospitalized patients with COVID-19. METHODS: This retrospective cohort study utilized the Brazilian database SIVEP-Gripe to analyze patients aged ≥18 years who had been hospitalized with COVID-19 between 2020 and 2022. The exposure of interest were mental disorders (anxiety, depression, schizophrenia, and bipolar disorder), identified through self-reported fields. The primary outcome was in-hospital mortality. Covariates included demographic and clinical features. Descriptive statistics, t-tests, chi-square tests, and binary logistic regression were used to analyze the data. RESULTS: A cohort of 2,124,285 patients was included in the analysis, with 23,246 individuals (1.1%) having self-reported mental disorders. Among these mental disorders, depression was the most prevalent (52.3%). The mortality rate of the patients with mental disorders was 30.8%. Analysis of risk factors for mortality revealed that age, gender, region, dyspnea, low oxygen saturation, and comorbidities were associated with an increased risk of death. Patients with schizophrenia had a higher mortality risk (aOR:1.68;95%CI:1.54-1.81). CONCLUSIONS: Patients diagnosed with schizophrenia have a greater likelihood of COVID-19- related death than those without mental health conditions. These findings underscore the significant effect of serious mental disorders on COVID-19 mortality.

Machine learning algorithms to predict outcomes in children and adolescents with COVID-19: A systematic review.

BACKGROUND AND OBJECTIVES: We aimed to analyze the study designs, modeling approaches, and performance evaluation metrics in studies using machine learning techniques to develop clinical prediction models for children and adolescents with COVID-19. METHODS: We searched four databases for articles published between 01/01/2020 and 10/25/2023, describing the development of multivariable prediction models using any machine learning technique for predicting several outcomes in children and adolescents who had COVID-19. RESULTS: We included ten articles, six (60 % [95 % confidence interval (CI) 0.31 - 0.83]) were predictive diagnostic models and four (40% [95 % CI 0.170.69]) were prognostic models. All models were developed to predict a binary outcome (n= 10/10, 100 % [95 % CI 0.72-1]). The most frequently predicted outcome was disease detection (n=3/10, 30% [95 % CI 0.11-0.60]). The most commonly used machine learning models in the studies were tree-based (n=12/33, 36.3% [95 % CI 0.17-0.47]) and neural networks (n=9/27, 33.2% [95% CI 0.15-0.44]). CONCLUSION: Our review revealed that attention is required to address problems including small sample sizes, inconsistent reporting practices on data preparation, biases in data sources, lack of reporting metrics such as calibration and discrimination, hyperparameters and other aspects that allow reproducibility by other researchers and might improve the methodology.

Dual RNA-seq of maize and H. seropedicae ZAE94 association, in different doses of nitrate, reveals novel insights into Plant-PGPB-environment relationship.

The interactions between plants, beneficial bacteria and their environment are profoundly shaped by various environmental factors, including light, temperature, water availability, and soil quality. Despite efforts to elucidate the molecular mechanisms involved in the association between plants and beneficial bacteria, like Plant Growth-Promoting Bacteria (PGPB), with many studies focusing on the transcriptional reprogramming in the plant, there is no report on the modulation of genetic controls from both plant and associated bacteria standpoints, in response to environment. The main goal of this study was to investigate the relationship between plant-bacteria-environment signaling, using as a model maize plants inoculated with H. seropedicae ZAE94 and cultivated with different doses of N (0.3 and 3 mM). For this purpose, we performed rRNA-depleted RNA-seq to determine the global gene expression of both maize roots and associated H. seropedicae ZAE94. Our results revealed a differential modulation of maize nitrogen metabolism, phytohormone and cell wall responses when associated with H. seropedicae ZAE94 at different N concentrations. In parallel, a modulation of the bacterial metabolism could be observed, by regulating genes involved in transport, secretion system, cell mobility, oxidoreductases, and chemotaxis, when bacteria were associated with maize roots and cultivated at different doses of N. The molecular and phenotypic data of maize plantlets suggested that different doses of N fertilization differentially regulated the beneficial effects of bacterial inoculation, as higher doses (3 mM) favored shoot elongation and lower doses (0.3 mM) favored increase in plant biomass. Our results provide a valuable integrated overview of differentially expressed genes in both maize and associated H. seropedicae ZAE94 in response to different N availability, revealing new insights into pathways involved in grass-PGPB associations.

Effectiveness of oseltamivir in reducing COVID-19-related in-hospital deaths: A pharmacoepidemiological study.

BACKGROUND: Oseltamivir is a low-cost antiviral agent that could support or complement treatment of COVID-19. This study assessed whether oseltamivir is effective in reducing COVID-19-related mortality. METHODS: This retrospective cohort study evaluated real-world data from a nationwide database of hospitalisation due to severe acute respiratory syndrome in Brazil. Propensity score matching was used to mimic a randomised controlled trial with 'oseltamivir' and 'no antivirals at all' as the intervention and control groups, respectively. RESULTS: A total of 21 480 and 268 486 patients admitted between February 2020 and January 2023 were included in the intervention and control groups, respectively. After matching, the odds ratio (OR) for death was 0.901 (95% confidence interval [CI] 0.873-0.930). The OR (95% CI) for death in patients who were admitted to the ICU, and on non-invasive or invasive ventilation was 0.868 (0.821-0.917), 0.935 (0.893-0.980), and 0.883 (0.814-0.958), respectively. CONCLUSIONS: Overall, the use of oseltamivir was associated with an attributable risk reduction of 2.50% (95% CI 1.77-3.29). Similar results were observed in patients who were admitted to the ICU, and on non-invasive or invasive ventilation. Oseltamivir is a low-cost potential antiviral treatment for COVID-19.

Balancing trade-offs: Enhanced carbon assimilation and productivity with reduced nutritional value in a well-watered C4 pasture under a warmer CO2-enriched atmosphere.

The concentration of atmospheric CO2 and temperature are pivotal components of ecosystem productivity, carbon balance, and food security. In this study, we investigated the impacts of a warmer climate (+2 °C above ambient temperature) and an atmosphere enriched with CO2 (600 ppm) on gas exchange, antioxidant enzymatic system, growth, nutritive value, and digestibility of a well-watered, managed pasture of Megathyrsus maximus, a tropical C4 forage grass, under field conditions. Elevated [CO2] (eC) improved photosynthesis and reduced stomatal conductance, resulting in increased water use efficiency and plant C content. Under eC, stem biomass production increased without a corresponding increase in leaf biomass, leading to a smaller leaf/stem ratio. Additionally, eC had negative impacts on forage nutritive value and digestibility. Elevated temperature (eT) increased photosynthetic gains, as well as stem and leaf biomass production. However, it reduced P and K concentration, forage nutritive value, and digestibility. Under the combined conditions of eC and eT (eCeT), eT completely offset the effects of eC on the leaf/stem ratio. However, eT intensified the effects of eC on photosynthesis, leaf C concentration, biomass accumulation, and nutritive value. This resulted in a forage with 12% more acid detergent fiber content and 28% more lignin. Additionally, there was a decrease of 19% in crude protein leading to a 15% decrease in forage digestibility. These changes could potentially affect animal feeding efficiency and feedback climate change, as ruminants may experience an amplification in methane emissions. Our results highlight the critical significance of conducting multifactorial field studies when evaluating plant responses to climate change variables.

Application of behavior data to predictive exploratory models of metritis self-cure and treatment failure in dairy cows.

The objective was to evaluate the performance of exploratory models containing routinely available on-farm data, behavior data, and the combination of both to predict metritis self-cure (SC) and treatment failure (TF). Holstein cows (n = 1,061) were fitted with a collar-mounted automated-health monitoring device (AHMD) from -21 ± 3 to 60 ± 3 d relative to calving to monitor rumination time and activity. Cows were examined for diagnosis of metritis at 4 ± 1, 7 ± 1, and 9 ± 1 d in milk (DIM). Cows diagnosed with metritis (n = 132), characterized by watery, fetid, reddish/brownish vaginal discharge (VD), were randomly allocated to 1 of 2 treatments: control (CON; n = 62), no treatment at the time of metritis diagnosis (d 0); or ceftiofur (CEF; n = 70), subcutaneous injection of 6.6 mg/kg of ceftiofur crystalline-free acid on d 0 and 3 relative to diagnosis. Cure was determined 12 d after diagnosis and was considered when VD became mucoid and not fetid. Cows in CON were used to determine SC, and cows in CEF were used to determine TF. Univariable analyses were performed using farm-collected data (parity, calving season, calving-related disorders, body condition score, rectal temperature, and DIM at metritis diagnosis) and behavior data (i.e., daily averages of rumination time, activity generated by AHMD, and derived variables) to assess their association with metritis SC or TF. Variables with P-values ≤0.20 were included in the multivariable logistic regression exploratory models. To predict SC, the area under the curve (AUC) for the exploratory model containing only data routinely available on-farm was 0.75. The final exploratory model to predict SC combining routinely available on-farm data and behavior data increased the AUC to 0.87, with sensitivity (Se) of 89% and specificity (Sp) of 77%. To predict TF, the AUC for the exploratory model containing only data routinely available on-farm was 0.90. The final exploratory model combining routinely available on-farm data and behavior data increased the AUC to 0.93, with Se of 93% and Sp of 87%. Cross-validation analysis revealed that generalizability of the exploratory models was poor, which indicates that the findings are applicable to the conditions of the present exploratory study. In summary, the addition of behavior data contributed to increasing the prediction of SC and TF. Developing and validating accurate prediction models for SC could lead to a reduction in antimicrobial use, whereas accurate prediction of cows that would have TF may allow for better management decisions.