Search

In this perspective article, several internationally recognized experts, members of the editorial team of this journal, discuss a selection of current hot topics identified in Food Science and Foodomics. The topics are comprised of the main areas of Food Science and Foodomics, namely, food safety, food authenticity, food processing, and food bioactivity. Logically, several of the discussed topics involve more than one of the mentioned main areas. Regarding food safety, the topics discussed are the use of analytical nanotechnology, nanometrology, nano-chromatography; the determination of organic contaminants based on MS and NMR; the impact of microplastics and nanoplastics on food or the contamination of foods with plant toxins. Regarding food authenticity, the paper discusses the role of MS, NMR, biosensors and the new trends in foodomics for food authentication. In terms of food processing, the work shows interesting perspectives on novel processing technologies, the effect of food processing on the gut microbiota or in the interaction among secondary metabolites and macromolecules; the development of active packaging, and the potential effects of introducing recycled plastics in food packaging; the new green extraction and encapsulation strategies of bioactive compounds from food by-products; and the anti-biofilm capacity of natural compounds/extracts/vegetal oils and essential oils. Food bioactivity and the relation between food and health includes the bioavailability and bioaccessibility of bioactive compounds; new trends and challenges in the interaction of nutraceuticals with biological systems; how food matrix impacts the bioaccessibility of nutrients and bioactive compounds; or the study of biodiversity, food and human health through one-health concept. We anticipate elaborations on these hot topics will promote further studies in Food Science and Foodomics.

Abstract Human immune cells are under constant evolutionary pressure, primarily through their role as first line of defence against pathogens. Most studies on immune adaptation are, however, based on protein-coding genes without considering their cellular context. Here, using data from the Human Cell Atlas, we infer the gene adaptation rate of the human immune landscape at cellular resolution. We find abundant cell types, like progenitor cells during development and adult cells in barrier tissues, to harbour significantly increased adaptation rates. We confirm the adaptation of tissue-resident T and NK cells in the adult lung located in compartments directly facing external challenges, such as respiratory pathogens. Analysing human iPSC-derived macrophages responding to various challenges, we find adaptation in early immune responses. Together, our study suggests host benefits to control pathogen spread at early stages of infection, providing a retrospect of forces that shaped the complexity, architecture, and function of the human body.

Purpose – The study aims to investigate the effect of autonomy on employee job performance and the mediation effect of engagement. It also explores whether an employee’s age moderates the model. Design/methodology/approach – Data were collected through a face-to-face survey administered to various types of workers in their workplaces. The selection of companies was based on a database available at the university. Response rate was 35%, yielding 210 instruments with complete responses. Structural Equation Modeling was the chosen method for data analysis. Findings – Results demonstrate a positive and significant relationship between autonomy and engagement as well as between engagement and job performance. Moreover, engagement plays a full mediating role in the relationship between autonomy and job performance. Additionally, while age does not moderate the relationship, it does have a differential impact on the mediation process. Practical implications – The creation of management strategies focused on resources such as autonomy must be adapted according to seniority, with the purpose of enhancing employee engagement and performance in today’s organizations. Originality/value – This paper closes a gap between autonomy and Job Demands-Resources theory by providing evidence on the effects of autonomy, engagement and age on job performance.

Abstract This paper presents a computational fluid dynamics (CFD) analysis and blade element momentum (BEM) analysis of horizontal small-scale wind turbines under various parameters. Random airfoils such as the NACA 0012, NACA 0018, NACA 4412, S1016, S1210, S1223, and SC20402 are chosen, and the glide ratio is analysed. A Reynolds number of 100,000 is considered because of the small wind turbine design. The foil with the highest glide ratio is selected. Various notations are used to represent the chord and the twist angle of the blade, and the blade with the best chord and twist angle is chosen. The lift, drag, and power coefficients and power curves are analysed via the BEM. The power curves are evaluated for different air densities, and a higher value of power is obtained. Finally, via CFD, the SST $$K-{\omega }$$ K - ω model for turbulence is analysed for various angles of attack via Ansys Fluent for different air densities. The results are satisfactory compared with those of the CFD and BEM analyses. The Weibull distribution is analysed to understand the required frequencies for various wind speeds so that the installation of wind turbines can be made convenient in preferred areas with suitable wind properties.

Abstract Background Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood psychiatric condition with profound public health, personal, and family consequences. ADHD requires comprehensive treatment; however, lack of communication and integration across multiple points of care is a substantial barrier to progress. Given the chronic and pervasive challenges associated with ADHD, innovative approaches are crucial. We developed the digital health intervention (DHI)—CoolTaCo [Cool Technology Assisting Co-regulation] to address these critical barriers. CoolTaCo uses Patient-Centered Digital Healthcare Technologies (PC-DHT) to promote co-regulation (child/parent), capture patient data, support efficient healthcare delivery, enhance patient engagement, and facilitate shared decision-making, thereby improving access to timely and targeted mental health intervention for children at significant risk for poor outcomes. The present paper will describe our planned protocol to evaluate the efficacy of CoolTaCo via randomized control trial (RCT). Methods/design We will recruit 60 children (ages 8–12) with ADHD who will be randomized to either immediate (n = 30) or delayed (n = 30) treatment (i.e., a waitlist control group). Among those randomized to immediate treatment, half will be assigned to DHI (delivered via a smartwatch and smartphone application), the other half to an active control treatment as usual (TAU). Unlike the DHI group, the TAU group will receive the smartwatch with no assigned activities, applications, or interventions on the devices. The intervention period will last 16 weeks; after a participant has been in the delayed treatment group for 16 weeks and has completed the post-waiting period assessment, they will be randomly assigned to either the intervention or active control group. Thus, 30 participants will complete the intervention, and 30 will complete the active control, with half of the total sample completing a waitlist period. Discussion Individuals with ADHD have complex needs. Despite improvement in outcomes following cognitive behavioral therapies (CBT) and pharmaceutical treatment, long-term maintenance is a challenge often not addressed by traditional medical approaches, and, as we described, ineffective approaches to information sharing across points of care create further barriers to progress. Our research will fill a significant gap in translating early treatment investments and gains into long-term, sustainable outcomes. This study was registered as a clinic trial at ClinicalTrials.gov (Digital Health Intervention for Children With ADHD, ID# NCT06456372) on 06/13/2024.

Abstract As the global momentum for wind power generation accelerates, the industry faces substantial challenges due to premature failures in wind turbine components. These failures, particularly in critical elements like the high‐speed shaft bearing, lead to significant operational losses, including unplanned downtime and elevated maintenance costs. To mitigate these issues, it's crucial to have precise predictions of the remaining useful life (RUL) of these components, enabling timely interventions and more efficient maintenance schedules. This article proposes advanced, data‐driven approaches for estimating the RUL of wind turbine high‐speed shaft bearings, utilizing cutting‐edge techniques such as long short‐term memory (LSTM), bidirectional LSTM (BiLSTM), gated recurrent units (GRU), and random forest (RF) algorithms. Our analysis leverages vibration data from a 2 MW wind turbine equipped with a 20‐tooth pinion gear, providing a thorough validation and comparison of these methodologies against traditional models. Our results reveal that the LSTM and BiLSTM models excel in both accuracy and computational efficiency for predicting RUL and enhancing system prognosis, surpassing the performance of conventional RF and GRU methods. This research underscores the potential of our innovative data‐driven strategies to develop effective RUL estimation algorithms, significantly advancing wind turbine proactive operation and maintenance operations.

Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a fitpercent of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

Abstract In today’s rapidly evolving technological landscape, this study investigates the impact of new technology on organizational work dynamics. By integrating the Job Demands-Resources theory and the Episodic Process Model, we examine the cognitive mechanisms that influence task performance during decision-making episodes. Our research focuses on episodic job demands and resources, emphasizing the mediating role of task absorption in the relationship between these factors and task performance. Our findings reveal that episodic job resources positively affect task absorption and performance, while job demands moderate the relationship between job resources and task absorption. Employing the Beer Distribution Game alongside neuroscience-based eye-tracking techniques, we analyze visual attention dynamics during decision-making episodes, providing novel insights into the interplay between task absorption and task performance. Theoretically, our study highlights the significance of task absorption in understanding how episodic job resources impact decision-making performance. Practically, our results advocate for the implementation of decision-making-focused skills development through physiological measures such as neurofeedback training programs. This research underscores the importance of individual time management in enhancing task performance, contributing to a nuanced understanding of job resources, job demands, and task absorption in the context of technological transformation.

Introducción: La pandemia por SARS-CoV-2, constituyó un reto para las autoridades sanitarias, tanto para los sistemas de atención médica, hospitales y profesionales de la salud. Objetivo: Describir los cuadros quirúrgicos de urgencias, en la pandemia SARS-CoV-2. Material y método: Estudio retrospectivo, descriptivo, observacional de pacientes portadores de patologías quirúrgicas del servicio de Emergencias en los meses de agosto a noviembre 2020. Resultado: n 385 pacientes, con edad promedio de 50 años, el motivo de consulta más frecuente fue el dolor en epigastrio (21,3%), seguido de coloración amarillenta de piel y mucosas (18,7%) y rectorragia (16,8%). El tiempo de evolución en promedio de 3 días. Se realizaron 151 (39%) intervenciones quirúrgicas, de las cuales la más frecuentes fueron la colecistectomía (46,3%) y la apendicectomía (18,5%), 11 tratamientos percutáneos (2,8%) y 24 (6,2%) tratamientos endoscópicos; 199 (51,7%) pacientes se trataron de manera conservadora. Entre las complicaciones post quirúrgicas se constató con mayor frecuencia infección del sitio quirúrgico en un 38,4% y la colección intraabdominal 37%. De todos los pacientes recibidos e internados en el servicio 32 (8,31%) resultaron ser COVID-19 positivo y durante su estancia hospitalaria, presentaron complicaciones 4 (12,5%) que incluyeron hemorragia postquirúrgica en dos pacientes, isquemia mesentérica en una oportunidad y shock séptico a punto de partida pulmonar. Tuvimos 1,3% de óbitos. Conclusión: La edad promedio de los pacientes fue de 50 años. El motivo de consulta más frecuente fue el dolor epigástrico. La colecistectomía fue la cirugía más frecuente y la complicación más común fue la infección del sitio...

Purpose: Non-obstructive azoospermia (NOA) represents the persistent absence of sperm in ejaculate without obstruction, stemming from diverse disease processes. This survey explores global practices in NOA diagnosis, comparing them with guidelines and offering expert recommendations. Materials and Methods:Materials and Methods: A 56-item questionnaire survey on NOA diagnosis and management was conducted globally from July to September 2022. This paper focuses on part 1, evaluating NOA diagnosis. Data from 367 participants across 49 coun-tries were analyzed descriptively, with a Delphi process used for expert recommendations. Results:Results: Of 336 eligible responses, most participants were experienced attending physicians (70.93%). To diagnose azoosper-mia definitively, 81.7% requested two semen samples. Commonly ordered hormone tests included serum follicle-stimulating hormone (FSH) (97.0%), total testosterone (92.9%), and luteinizing hormone (86.9%). Genetic testing was requested by 66.6%, with karyotype analysis (86.2%) and Y chromosome microdeletions (88.3%) prevalent. Diagnostic testicular biopsy, distinguishing obstructive azoospermia (OA) from NOA, was not performed by 45.1%, while 34.6% did it selectively. Differ-entiation relied on physical examination (76.1%), serum hormone profiles (69.6%), and semen tests (68.1%). Expectations of finding sperm surgically were higher in men with normal FSH, larger testes, and a history of sperm in ejaculate. Conclusions:Conclusions: This expert survey, encompassing 367 participants from 49 countries, unveils congruence with recommended guidelines in NOA diagnosis. However, noteworthy disparities in practices suggest a need for evidence-based, international consensus guidelines to standardize NOA evaluation, addressing existing gaps in professional recommendations.

ABSTRACT: Herein, we combined different bioinformatics tools and databases (BV-BRC, ResFinder, RAST, and KmerResistance) to perform a prediction of antimicrobial resistance (AMR) in the genomic sequences of 107 Corynebacterium striatum isolates for which trustable antimicrobial susceptibility (AST) phenotypes could be retrieved. Then, the reliabilities of the AMR predictions were evaluated by different metrics: area under the ROC curve (AUC); Major Error Rates (MERs) and Very Major Error Rates (VMERs); Matthews Correlation Coefficient (MCC); F1-Score; and Accuracy. Out of 15 genes that were reliably detected in the C. striatum isolates, only tetW yielded predictive values for tetracycline resistance that were acceptable considering Food and Drug Administration (FDA)’s criteria for quality (MER < 3.0% and VMER with a 95% C.I. ≤1.5–≤7.5); this was accompanied by a MCC score higher than 0.9 for this gene. Noteworthy, our results indicate that other commonly used metrics (AUC, F1-score, and Accuracy) may render overoptimistic evaluations of AMR-prediction reliabilities on imbalanced datasets. Accordingly, out of 10 genes tested by PCR on additional multidrug-resistant Corynebacterium spp. isolates (n = 18), the tetW gene rendered the best agreement values with AST profiles (94.11%). Overall, our results indicate that genome-based AMR prediction can still be challenging for MDR clinical isolates of emerging Corynebacterium spp.

Job satisfaction and digital talent are topics of growing interest in the context of digital transformation. Digitalization is changing the way organizations operate and how employees perceive their work. The state and its administrative staff is no exception, as these capabilities are essential to perform operational tasks that underpin the public institution's documentary processes. This study investigates the influence of digital talent (independent variable) on job satisfaction (dependent variable), employing structural equation modeling (SEM) using WarpPLS software. Digital Talent is broken down into three sub-variables: Digital Competencies of Employees (DCE), Capacity for Digital Innovation and Creativity (CIDC) and Adaptability and Continuous Learning (ACL), while Job Satisfaction is measured through two sub-variables: Work Environment (WE) and Professional Development Opportunities (PDO). The analyses revealed that Capacity for Innovation and Digital Creativity (CIDC) has a significant impact on Work Environment, with a path coefficient (β) of 0.13 (p = 0.01). Similarly, adaptability and continuous learning (ACL) positively influence the work environment, with a path coefficient (β) of 0.10 (p = 0.04). In addition, a strong relationship was found between professional development opportunities (PDO) and work environment, with a path coefficient (β) of 0.68 (p < 0.001). For the relationship between digital competencies (DCE) and career development opportunities, the path coefficient was 0.10 (p = 0.04). Digital talent is a key predictor of job satisfaction in administrative staff. The results suggest that investing in the development of digital capabilities, especially innovation and creativity, as well as adaptability, is essential to improve the work environment and career development opportunities.

Satellites are increasingly adopting onboard AI to optimize operations and increase autonomy through in-orbit inference. The use of deep learning (DL) models for segmentation in hyperspectral imagery offers advantages for remote sensing applications. In this work, we train and test 20 models for multiclass segmentation in hyperspectral imagery, selected for their potential in future space deployment. These models include 1-D and 2-D convolutional neural networks (CNNs) and the latest vision transformers (ViTs). We propose a lightweight 1D-CNN model, 1D-Justo-LiuNet, which outperforms state-of-the-art models in the hypespectral domain. 1D-Justo-LiuNet exceeds the performance of 2D-CNN UNets and outperforms Apple's lightweight vision transformers designed for mobile inference. 1D-Justo-LiuNet achieves the highest accuracy (0.93) with the smallest model size (4563 parameters) among all tested models, while maintaining fast inference. Unlike 2D-CNNs and ViTs, which encode both spectral and spatial information, 1D-Justo-LiuNet focuses solely on the rich spectral features in hyperspectral data, benefitting from the high-dimensional feature space. Our findings are validated across various satellite datasets, with the HYPSO-1 mission serving as the primary case study for sea, land, and cloud segmentation. We further confirm our conclusions through generalization tests on other hyperspectral missions, such as NASA's EO-1. Based on its superior performance and compact size, we conclude that 1D-Justo-LiuNet is highly suitable for in-orbit deployment, providing an effective solution for optimizing and automating satellite operations at edge.

Conflict of interest: No Introduction and Objectives: Liver damage in preeclampsia is caused by antiangiogenic factors such as soluble tyrosine kinase, placental growth factor, and soluble endoglin. These induce endothelial injury and fibrin deposits in the hepatic microcirculation, thus modifying the physical characteristics of the liver parenchyma and therefore its stiffness. Objectives: To evaluate the correlation between the degree of liver stiffness and the severity of patients with preeclampsia. Patients / Materials and Methods: This study was observational, analytical, cross-sectional, and prospective. It included pregnant women from the 20th week of gestation, dividing them into three groups: those with a normal pregnancy, those with pre-eclampsia, and those with severe features of pre-eclampsia. Transient elastography was conducted on all participants. Pregnant women with chronic systemic arterial hypertension or pre-existing liver diseases were excluded. Descriptive statistics for measures of central tendency were utilized, and a univariate analysis was performed, considering kilopascals as the dependent variable, the three groups as fixed factors, and BMI as a covariate. Results and Discussion: 34 patients were included, 9 in the control group, 12 in the preeclampsia group and 13 in the preeclampsia with severity features group. The mean gestational age was 32 ± 5.8 weeks. The mean age was 27.26 ± 7.73 years. The mean BMI was 28.88 ± 4.83. The mean kPa in the control group was 4.35 ± 0.98, in the preeclampsia without severity features group 5.05 ± 0.87, and in the preeclampsia with severity features group 6.67 ± 1.84. The mean control group CAP was 202.82 ± 21.26 db/m2, in the preeclampsia without severity features group was 227.81 ± 47.81 db/m2, and in the preeclampsia with severity features group was 215.28 ± 37.41 db/m2. Univariate contrasts were significant for preeclampsia with severity criteria features versus preeclampsia F (2 of 23) = 7.679, p = 0.011. Preeclampsia with severity features versus control F (2 of 22) = 11.134, p = 0.003 Conclusions: Liver stiffness significantly increases in patients with preeclampsia and preeclampsia with severity features measured by transient elastography. This increase is due to intrahepatic fibrin deposition, but not by fibrosis (collagen) itself. Transient elastography could be useful as a predictor of severity in patients with preeclampsia.

The cocoa tree (Theobroma cacao L.) is a native crop of the tropical forests of Central America and the Amazon. It plays an important role in the economy of producing regions; however, the infrastructure remains incipient, leading to inadequate processing practices and affecting the quality of the cocoa beans. Therefore, this research aimed to evaluate the quality of 55 samples of Amazonian cocoa beans produced in five regions of state of Pará (Lower Tocantins River, Northeast, West, Southeast, and Trans-Amazon) through physical and physicochemical evaluations (proteins, lipids, moisture, ash, pH, acidity, and water activity), and a questionnaire with producers about fermentation and drying practices. This was followed by physical, physicochemical, antioxidant capacity, quantification of total polyphenols, and bioactive compound evaluations. According to the physical evaluation, the samples met the acceptable commercial standard, but the cut test results showed a lack of standardization in the pre-processing of cocoa beans according to the International Cocoa Organization (ICCO). Among the physicochemical parameters, moisture was within the limit tolerated by legislation, and only lipids showed significant differences. Regarding antioxidant capacity, total polyphenols, and bioactive compounds, only the bioactive compounds showed significant differences, with the Lower Tocantins River region exhibiting higher values for all studied compounds. Inadequate processing practices, such as poor fermentation and drying, may lead to quality deficiencies in cocoa beans. Therefore, this study emphasizes the need for characterization of commercial cocoa beans, as well as standardization in the pre-processing of these beans. It also highlights potential variations in the quality of the beans among producing regions, owing to the vast territorial expanse of Pará, diverse cultivation conditions, variety of cocoa trees, and different methods of cocoa bean pre-processing.

Abstract Purpose Legg Calve Perthes disease (LCPD) is a paediatric hip disorder caused by ischemia of the femoral epiphysis, causing femoral head deformity when untreated. This study aims to determine if previously validated pelvic obliquity radiographic parameters, used for assessing acetabular retroversion in developmental dysplasia of the hip, are applicable to patients with LCPD and its prognostic value. Method A retrospective study of patients with Legg Calve Perthes disease was carried out, analysing 4 pelvic parameters: Ilioischial Angle, Obturator Index, Sharp’s Angle and Acetabular Depth-Width Ratio (ADR). The differences between healthy and affected hips were studied, and subsequently, it was assessed whether these parameters have prognostic value in the disease outcome. Results Statistically significant differences have been obtained in the ilioischial angle, obturator index and ADR, between the affected and healthy hip. However, only the Acetabular Depth-Width Ratio showed predictive value for the disease outcome. Conclusion Although this study revealed differences in pelvic parameters between healthy and diseased hips, with only the ADR showing statistical significance in the disease's evolution and prognosis, further studies with larger sample sizes are necessary.

Abstract The placenta plays a crucial role in protecting the fetus from environmental harm and supports the development of its brain. In fact, compromised placental function could predispose an individual to neurodevelopmental disorders. Placental epigenetic modifications, including DNA methylation, could be considered a proxy of placental function and thus plausible mediators of the association between intrauterine environmental exposures and genetics, and childhood and adult mental health. Although neurodevelopmental disorders such as autism spectrum disorder have been investigated in relation to placenta DNA methylation, no studies have addressed the association between placenta DNA methylation and child’s cognitive functions. Thus, our goal here was to investigate whether the placental DNA methylation profile measured using the Illumina EPIC array is associated with three different cognitive domains (namely verbal score, perceptive performance score, and general cognitive score) assessed by the McCarthy Scales of Children’s functions in childhood at age 4. To this end, we conducted epigenome-wide association analyses, including data from 255 mother-child pairs within the INMA project, and performed a follow-up functional analysis to help the interpretation of the findings. After multiple-testing correction, we found that methylation at 4 CpGs (cg1548200, cg02986379, cg00866476, and cg14113931) was significantly associated with the general cognitive score, and 2 distinct differentially methylated regions (DMRs) (including 27 CpGs) were significantly associated with each cognitive dimension. Interestingly, the genes annotated to these CpGs, such as DAB2, CEP76, PSMG2, or MECOM, are involved in placenta, fetal, and brain development. Moreover, functional enrichment analyses of suggestive CpGs (p

Abstract A critical aspect of simulation models used in cost-effectiveness analysis lies in accurately representing the natural history of diseases, requiring parameters such as probabilities and disease burden rates. While most of these parameters can be sourced from scientific literature, they often require calibration to align with the model’s expected outcomes. Traditional optimization methods can be time-consuming and computationally expensive, as they often rely on simplistic heuristics that may not ensure feasible solutions. In this study, we explore using Bayesian optimization to enhance the calibration process by leveraging domain-specific knowledge and exploiting structural properties within the solution space. Specifically, we investigate the impact of additive kernel decomposition and a stepwise approach, which capitalizes on the sequential block structure inherent in simulation models. This approach breaks down large optimization problems into smaller ones without compromising solution quality. In some instances, parameters obtained using this methodology may exhibit less error than those derived from naive calibration techniques. We compare this approach with two state-of-the-art high-dimensional Bayesian Optimization techniques: SAASBO and BAxUS. Our findings demonstrate that Bayesian optimization significantly enhances the calibration process, resulting in faster convergence and improved solutions, particularly for larger simulation models. This improvement is most pronounced when combined with a stepwise calibration methodology.

Abstract Discinaceae holds significant importance within the Pezizales, representing a prominent group of macroascomycetes distributed globally. However, there is a dearth of genomic studies focusing on this family, resulting in gaps in our understanding of its evolution, development, and ecology. Here we utilized state-of-the-art genome assembly methodologies, incorporating third-generation single-molecule fluorescence and Hi-C-assisted methods, to elucidate the genomic landscapes of Gyromitra esculenta and Paragyromitra xinjiangensis. The genome sizes of two species were determined to be 47.10 Mb and 48.20 Mb, with 23 and 22 scaffolds, respectively. 10,438 and 11,469 coding proteins were identified, with functional annotations encompassing over 96.47% and 94.40%, respectively. Assessment of completeness using BUSCO revealed that 98.71% and 98.89% of the conserved proteins were identified. The application of comparative genomic technology has helped in identifying traits associated with of heterothallic life cycle traits and elucidating unique patterns of chromosomal evolution. Additionally, we identified potential saprotrophic nutritional modes and systematic phylogenetic relationships between the two species. Therefore, this study provides crucial genomic insights into the evolution, nutritional type, and ecological roles of species within the Pezizales.

Abstract Objective Evidence from low- and middle-income countries regarding the effect of smoking in people with diabetes is lacking. Here, we report the association of smoking with mortality in a large cohort of Mexican adults with diabetes. Methods Participants with diabetes mellitus (self-reported diagnosis, use of antidiabetic medications or HbA1c ≥ 6.5%) aged 35–74 years when recruited into the Mexico City Prospective Study were included. Cox regression confounder-adjusted mortality rate ratios (RRs) associated with baseline smoking status were estimated. Results Among 15,975 women and 8225 men aged 35–74 years with diabetes but no other comorbidities at recruitment, 2498 (16%) women and 2875 (35%) men reported former smoking and 2753 (17%) women, and 3796 (46%) men reported current smoking. During a median of 17 years of follow-up there were 5087 deaths at ages 35–74 years. Compared with never smoking, all-cause mortality RR was 1.08 (95%CI 1.01–1.17) for former smoking, 1.11 (95%CI 1.03–1.20) for current smoking, 1.09 (95%CI 0.99–1.20) for non-daily smoking, 1.06 (95%CI 0.96–1.16) for smoking

Summary: Background: Surgical care holds significant importance in healthcare, especially in low and middle-income countries, as at least 50% of the 4.2 million deaths within the initial 30 days following surgery take place in these countries. The Lancet Commission on Global Surgery proposed six indicators to enhance surgical care. In Colombia, studies have been made using secondary data. However, strategies to reduce perioperative mortality have not been implemented. This study aims to describe the fourth indicator, perioperative mortality rate (POMR), with primary data in Colombia. Methods: A multicentre prospective cohort study was conducted across 54 centres (hospitals) in Colombia. Each centre selected a 7-day recruitment period between 05/2022 and 01/2023. Inclusion criteria involved patients over 18 years of age undergoing surgical procedures in operating rooms. Data quality was ensured through a verification guideline and statistical analysis using mixed-effects multilevel modelling with a case mix analysis of mortality by procedure-related, patient-related, and hospital-related conditions. Findings: 3807 patients were included with a median age of 48 (IQR 32–64), 80.3% were classified as ASA I or II, and 27% of the procedures had a low-surgical complexity. Leading procedures were Orthopedics (19.2%) and Gynaecology/Obstetrics (17.7%). According to the Clavien–Dindo scale, postoperative complications were distributed in major complications (11.7%, 10.68–12.76) and any complication (31.6%, 30.09–33.07). POMR stood at 1.9% (1.48–2.37), with elective and emergency surgery mortalities at 0.7% (0.40–1.23) and 3% (2.3–3.89) respectively. Interpretation: The POMR was higher than the ratio reported in previous national studies, even when patients had a low–risk profile and low-complexity procedures. The present research represents significant public health progress with valuable insights for national decision-makers to improve the quality of surgical care. Funding: This work was supported by Universidad del Rosario and Fundación Cardioinfantil-Instituto de Cardiología grant number CTO-057-2021, project-ID IV-FGV017.

Abstract To understand the roles of acute-phase viral dynamics and host immune responses in post-acute sequelae of SARS-CoV-2 infection (PASC), we enrolled 136 participants within 5 days of their first positive SARS-CoV-2 real-time PCR test. Participants self-collected up to 21 nasal specimens within the first 28 days post-symptom onset; interviewer-administered questionnaires and blood samples were collected at enrollment, days 9, 14, 21, 28, and month 4 and 8 post-symptom onset. Defining PASC as the presence of any COVID-associated symptom at their 4-month visit, we compared viral markers (quantity and duration of nasal viral RNA load, infectious viral load, and plasma N-antigen level) and host immune markers (IL-6, IL-10, TNF-α, IFN-α, IFN-γ, MCP, IP-10, and Spike IgG) over the acute period. Compared to those who fully recovered, those reporting PASC demonstrated significantly higher maximum levels of SARS-CoV-2 RNA and N-antigen, burden of RNA and infectious viral shedding, and lower Spike-specific IgG levels within 9 days post-illness onset. No significant differences were identified among a panel of host immune markers. Our results suggest early viral dynamics and the associated host immune responses play a role in the pathogenesis of PASC, highlighting the importance of understanding early biological markers in the natural history of PASC.

Abstract Pituitary neuroendocrine tumors (PitNET) represent the vast majority of sellar masses. Some behave aggressively, growing rapidly and invading surrounding tissues, with high rates of recurrence and resistance to therapy. Our aim was to establish patterns of genomic, transcriptomic and methylomic evolution throughout time in primary and recurrent tumors from the same patient. Therefore, we performed transcriptome- and exome-sequencing and methylome microarrays of aggressive, primary, and recurrent PitNET from the same patient. Primary and recurrent tumors showed a similar exome profile, potentially indicating a stable genome over time. In contrast, the transcriptome of primary and recurrent PitNET was dissimilar. Gonadotroph, silent corticotroph, as well as metastatic corticotroph and a somatotroph PitNET expressed genes related to fatty acid biosynthesis and metabolism, phosphatidylinositol signaling, glycerophospholipid and phospholipase D signaling, respectively. Diacylglycerol kinase gamma (DGKG), a key enzyme in glycerophospholipid metabolism and phosphatidylinositol signaling pathways, was differentially expressed between primary and recurrent PitNET. These alterations did not seem to be regulated by DNA methylation, but rather by several transcription factors. Molecular docking showed that dasatinib, a small molecule tyrosine kinase inhibitor used in the treatment of chronic lymphocytic and acute lymphoblastic leukemia, could target DGKG. Dasatinib induced apoptosis and decreased proliferation in GH3 cells. Our data indicate that pituitary tumorigenesis could be driven by transcriptomically heterogeneous clones, and we describe alternative pharmacological therapies for aggressive and recurrent PitNET.

Abstract The red-legged partridge Alectoris rufa plays a crucial role in the ecosystem of southwestern Europe, and understanding its genetics is vital for conservation and management. Here we sequence, assemble, and annotate a highly contiguous and nearly complete version of its genome. This assembly encompasses 96.9% of the avian genes flagged as essential in the BUSCO aves_odb10 dataset. Moreover, we pinpointed RNA and protein-coding genes, 95% of which had functional annotations. Notably, we observed significant chromosome rearrangements in comparison to quail (Coturnix japonica) and chicken (Gallus gallus). In addition, a comparative phylogenetic analysis of these genomes suggests that A. rufa and C. japonica diverged roughly 20 million years ago and that their common ancestor diverged from G. gallus 35 million years ago. Our assembly represents a significant advancement towards a complete reference genome for A. rufa, facilitating comparative avian genomics, and providing a valuable resource for future research and conservation efforts for the red-legged partridge.

Introduction: Medical and nonmedical ketamine use is increasing in the United States. This will likely lead to an increase in emergency department (ED) visits in individuals experiencing associated side effects. Physicians will need to be able to effectively recognize and manage ketamine-related complications. Case Report: A 31-year-old male with a three-year history of inhalational, intramuscular, and intravenous nonmedical ketamine use presented to the ED twice within a week with symptoms of severe atraumatic back pain, abdominal pain, and dyspepsia. A comprehensive workup, including advanced imaging, was unrevealing for identifiable causes, and the patient was discharged with instructions for primary care follow-up for further evaluation. The patient used information shared on Reddit, an online forum and social network, to identify that the cause of his pain was related to chronic ketamine use. Subsequently, upon discontinuation of ketamine, the pain improved in 24 hours. The patient self-navigated to addiction treatment. Conclusion: Emergency physicians should consider sequelae of chronic ketamine use as a possible cause for gastrointestinal and urologic symptoms in the ED. In addition to thorough examination and assessment for other acute medical problems, patients should be offered education, symptomatic treatment, and linkage to harm reduction and substance use disorder treatment services.

Abstract Objective To evaluate the Refractory Epilepsy Screening Tool for Lennox–Gastaut Syndrome (REST‐LGS) for real‐world identification of LGS in adults and to develop a scoring system for the tool. Methods A retrospective chart review of adults with drug resistant epilepsy (DRE) and intellectual development disorder (IDD) was conducted by 2 primary care providers blinded to diagnosis. The REST‐LGS was designed via the Modified Delphi Consensus and was previously validated. This tool consists of 8 criteria (4 major, 4 minor) considered indicative of LGS. To account for missing data in the earlier validation study and to evaluate applicability in a real‐world setting, the REST‐LGS was refined to include a scoring system in which major criteria were more heavily weighted than minor criteria, producing categories of “likely” (>11 points), “possible” (8–11 points), and “unlikely” (

The developing environmental consequences of excessive dependence on fossil fuels have pushed many countries to invest in clean and renewable energy sources. Mexico is a country that, due to its geographic and climatic diversity, can take advantage of this potential in renewable energy generation and reduce its dependence on fossil fuels while developing strategies to improve its energy system. This study investigated the feasibility of the autonomous use of two hybrid renewable energy systems and a photovoltaic system to power homes in a remote location. With the help of HOMER Pro Version 3.14.5 software, a model was made to evaluate the operation of three systems for one year, and the demand was predicted according to a given scenario. In addition, the optimal configuration of the components of each system was determined. The results showed that the simultaneous use of solar systems with a converter and a backup system consisting of a diesel generator and batteries would be the most viable and reliable option for generating renewable energy at the selected location, offering electricity with a renewable fraction of more than 80%.

Introduction: Effective medical education must balance clinical service demands for institutions and learning needs of trainees. The question of whether these are competing demands or can serve complementary roles has profound impacts on graduate medical education, ranging from funding decisions to the willingness of community-based hospitals and physicians to include learners at their clinical sites. Our objective in this article was to systematically review the evidence on the impact of medical trainees on productivity and efficiency in the emergency department (ED). Methods: We queried PubMed, Embase, Scopus, and Web of Science from earliest available dates to March 2023. We identified all studies evaluating the impact of medical students and/or residents in the ED on commonly used productivity and efficiency metrics. Only studies in EDs in the United States were included. No additional filters were used. We assessed the risk of bias of included studies using the Risk of Bias in Non-randomized Studies – of Interventions (ROBINS-I) tool. Certainty of evidence was rated using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. Study findings were combined in a narrative synthesis and reported according to PRISMA guidelines. Results: The literature search yielded 3,390 unique articles for abstract screening. Eighty-one abstracts were identified as relevant to our PICO question (population, intervention, control, and outcomes), 76 of which had retrievable full-text articles and the themes of which were discussed in a narrative synthesis. We selected 13 of the full-text articles for final inclusion in a systematic review. Studies were roughly split between observational (6) and quasi-experimental (7) designs. The majority of studies (11) were single-site studies. Only two studies could be graded as low risk of bias per the ROBINS-I tool. Conclusion: Low-GRADE evidence suggests that students and residents decrease ED efficiency by a statistically small effect size of debatable clinical importance. Residents provide a moderate boost to ED productivity. Students do not produce a statistically or clinically significant impact on ED productivity. Residents increase emergency department relative value units revenue by $26.30 an hour, while students have no impact. Both types of learners decrease efficiency.

Alloxysta turcica Tataroğlu & Katılmış, 2023, a species recently described from Turkey, is now being synonymyzed with A. minuscula Andrews, 1978. This decision is based on morphological analysis, which has revealed significant similarities between the two species. The reasons and supporting illustrations for this synonymy are provided.

Abstract Investigating the gut microbiome and metabolome frequently requires faecal samples, which can be difficult to obtain. Previous studies have shown that rectal swabs are comparable to faecal samples for analysing gut microbiota composition and key metabolites. In this study, 3D printed rectal swabs were compared with conventional flocked swabs and faecal samples, due to the potential advantages 3D printing as a technique offers for swab production and development. 16S rRNA gene sequencing, qPCR and metabolite profiling (using 1H-NMR spectroscopy) were performed on swab and faecal samples from healthy participants. Faecal calprotectin and total protein analysis were performed on samples from inflammatory bowel disease (IBD) patients. There were no significant differences between both swab types and faecal samples when assessing key measures of alpha and beta diversity, and differences in the abundance of major phyla. There was a strong correlation between both swab types and faecal samples for all combined metabolites detected by NMR. In IBD patients, there was no significant difference in faecal calprotectin and total protein levels between both swab types and faecal samples. These data lead us to conclude that 3D printed swabs are equivalent to flocked swabs for the analysis of the gut microbiome, metabolome and inflammation.

Abstract Electrokinetic convection-enhanced delivery (ECED) utilizes an external electric field to drive the delivery of molecules and bioactive substances to local regions of the brain through electroosmosis and electrophoresis, without the need for an applied pressure. We characterize the implementation of ECED to direct a neutrally charged fluorophore (3 kDa) from a doped biocompatible acrylic acid/acrylamide hydrogel placed on the cortical surface. We compare fluorophore infusion profiles using ECED (time = 30 min, current = 50 µA) and diffusion-only control trials, for ex vivo (N = 18) and in vivo (N = 12) experiments. The linear intensity profile of infusion to the brain is significantly higher in ECED compared to control trials, both for in vivo and ex vivo. The linear distance of infusion, area of infusion, and the displacement of peak fluorescence intensity along the direction of infusion in ECED trials compared to control trials are significantly larger for in vivo trials, but not for ex vivo trials. These results demonstrate the effectiveness of ECED to direct a solute from a surface hydrogel towards inside the brain parenchyma based predominantly on the electroosmotic vector.

Abstract Infection is the leading cause of death in multiple myeloma (MM). However, the cellular composition associated with immune dysfunction is not defined. We analyzed immune profiles in the peripheral blood of patients with MM (n = 28) and B-cell chronic lymphoproliferative disorders (n = 53) vs. health care practitioners (n = 96), using multidimensional and computational flow cytometry. MM patients displayed altered distribution of most cell types (41/56, 73%), particularly within the B-cell (17/17) and T-cell (20/30) compartments. Using COVID-19 as a case study, we compared the immune response to vaccination based on 64,304 data points generated from the analysis of 1099 longitudinal samples. MM patients showed limited B-cell expansion linked to lower anti-RBD and anti-S antibody titers after the first two doses and booster. The percentages of B cells and CD4+ T cells in the blood, as well as the absolute counts of B cells and dendritic cells, predicted vaccine immunogenicity at different time points. In contrast with the humoral response, the percentage and antigen-dependent differentiation of SARS-CoV-2-specific CD8+ T cells was not altered in MM patients. Taken together, this study defined the cellular composition associated with immune dysfunction in MM and provided biomarkers such as the B-cell percentage and absolute count to individualize vaccination calendars.

Abstract Multiple-choice test generation is one of the most complex NLP problems, especially in languages other than English, where there is a lack of prior research. After a review of the literature, it has been verified that some methods like the usage of rule-based systems or primitive neural networks have led to the application of a recent architecture, the Transformer architecture, in the tasks of Answer Extraction (AE) and Question Generation (QG). Thereby, this study is centred in searching and developing better models for the AE and QG tasks in Spanish, using an answer-aware methodology. For this purpose, three multilingual models (mT5-base, mT0-base and BLOOMZ-560 M) have been fine-tuned using three different datasets: a translation to Spanish of the SQuAD dataset; SQAC, which is a dataset in Spanish; and their union (SQuAD + SQAC), which shows slightly better results. Regarding the models, the performance of mT5-base has been compared with that found in two newer models, mT0-base and BLOOMZ-560 M. These models were fine-tuned for multiple tasks in literature, including AE and QG, but, in general, the best results are obtained from the mT5 models trained in our study with the SQuAD + SQAC dataset. Nonetheless, some other good results are obtained from mT5 models trained only with the SQAC dataset. For their evaluation, the widely used BLEU1-4, METEOR and ROUGE-L metrics have been obtained, where mT5 outperforms some similar research works. Besides, CIDEr, SARI, GLEU, WER and the cosine similarity metrics have been calculated to present a benchmark within the AE and QG problems for future work.

O presente relato de experiência descreve e analisa o projeto de extensão 'Educação alimentar e ecológica associada à prevenção da cárie dentária', desenvolvido em uma comunidade ribeirinha do Estuário Amazônico na Usina Vitória, localizada na Ilha das Onças, município de Barcarena/PA. Motivado pelos altos índices de cárie e falta de saneamento básico, o projeto de educação alimentar e ecológica foi realizado para prevenção da cárie. Foi realizada uma revisão integrativa da literatura que identificou boas práticas de educação alimentar e ecológica, e de produção de alimentos saudáveis com potencial de prevenção à cárie. Após a revisão integrativa, uma oficina de educação alimentar e ecológica voltada para saúde bucal foi realizada na comunidade. Este projeto apresentou uma proposta de abordagem prática de educação alimentar e ecológica para o cultivo de hortaliças ricas em flúor, aproveitando materiais recicláveis.

Matrix-bound vesicles (MBVs), an integral part of the extracellular matrix (ECM), are emerging as pivotal factors in ECM-driven molecular signaling. This study is the first to report the isolation of MBVs from porcine arterial endothelial cell basement membranes (A-MBVs) and thyroid cartilage (C-MBVs), the latter serving as a negative control due to its minimal vascular characteristics. Using Transmission Electron Microscopy (TEM), Nano-Tracking Analysis (NTA), Electrochemical Impedance Spectroscopy (EIS), and Atomic Force Microscopy (AFM), we orthogonally characterized the isolated MBVs. We detected the presence and preservation of vascular endothelial cadherin (CD144) in A-MBVs, its low to non-detetcted in C-MBVs, in which SOX9, a chondrocyte marker, was detected. Moreover, we developed a prototype of an immuno-functionalized screen-printed electrode designed for the immunoadsorption of CD144+ MBVs. This device facilitated the electrochemical detection of the targeted vesicles and allowed for their subsequent topological characterization using AFM, which verified the integrity and morphology of CD144+ MBVs post-immunoadsorption. These advancements enhance our comprehension of MBVs as conveyors of tissue-specific signals and pioneer new avenues for harnessing their cargo in biomedical applications. This research sets a significant precedent for future studies on the application of MBVs in regenerative medicine and ECM signaling.

Refletir sobre a sua prática docente permite ao professor a condução mais efetiva dos processos de ensino e de aprendizagem. Neste intuito, objetivou-se descrever a visão dos acadêmicos do Curso de Licenciatura em Ciências Biológicas sobre o ensino de Botânica e a importância para sua formação profissional e prática pedagógica. Os resultados foram baseados em questionários semiestruturados aplicados a discentes das disciplinas de Botânica. Foi evidenciando que o maior índice de reprovação ocorre na disciplina relacionada ao conhecimento sobre as criptógamas, primeiro contato dos alunos com o conteúdo vegetal. Embora aulas práticas sejam aplicadas, os acadêmicos consideraram que a melhor alternativa seria aumentar o número de aulas práticas como estratégia para facilitar o ensino e a aprendizagem em conteúdo de Botânica.

Conflict of interest: No Introduction and Objectives: Cholangiocarcinoma (CCA) represents a global health challenge, with rising incidence and mortality rates. This study aimed to elucidate the clinical course and practices of CCA in Latin America. Patients / Materials and Methods: This observational cohort study investigated individuals diagnosed with CCA between 2010-2023 in five referral centers across Latin America. Demographic, biochemical, and clinical data were analyzed. Results and Discussion: A total of 309 patients were enrolled, demonstrating a balanced distribution of CCA subtypes (intrahepatic, perihilar, and distal), with Hispanics and Caucasians as the predominant ethnic groups, followed by Africans. Major risk factors identified included age, diabetes, obesity, MASLD, bile duct stones, and cholecystitis. Disparities in overweight/obesity prevalence were noted among CCA subtypes and ethnicities, with higher rates in extrahepatic CCAs and among Hispanics and Caucasians. At diagnosis, 72% of patients had ECOG-PS scores of 0-1, with disease presentations ranging from localized (47%) to locally advanced (19%) and metastatic (34%). Patients who did not receive any anti-cancer therapy exhibited a median survival of 2.3 months. Survival rates significantly improved across treatment modalities, with surgery yielding the longest (34 months), followed by chemotherapy (8 months). Notably, Africans presented with worse ECOG-PS scores and more advanced disease, while Hispanics were less frequently treated with chemotherapy, contributing to lower survival rates. Conclusions: The high prevalence of late-stage CCA diagnosis in Latin America, particularly among Africans, alongside a substantial proportion of Hispanic patients not receiving chemotherapy, underscores a dismal prognosis for patients. These findings highlight structural challenges in cancer screening and healthcare access among diverse ethnic backgrounds and lower socioeconomic statuses in the region. Urgent measures are warranted, including identifying preventable risk factors, increasing awareness among high-risk populations, and establishing equitable health coverage to address these disparities.

Background: Allergic rhinitis (AR) is a highly prevalent disease. We aimed to assess the symptoms that physicians who see patients with AR perceive as the most bothersome in their patients. Methods: We performed a cross-sectional study based on an online questionnaire sent to all members of the Allergic Rhinitis and its Impact on Asthma (ARIA) initiative. The survey included questions on the physicians' perceptions of patients’ AR symptoms as well as of their own AR symptoms. Results: Among 401 respondents, 155 (38.7%) reported having AR. ARIA members reported nasal symptoms to be the most frequent (89.7%) and bothersome (80.0%) symptoms experienced by themselves. Likewise, nasal symptoms were reported by ARIA members as the most frequent (94.8% in members with AR vs 96.0% in members without AR) and bothersome (57.0% in members with AR vs 67.9% in members without AR) in their patients. We found a significant association (p = 0.001) between physicians’ own symptoms and those perceived as the most bothersome in their patients. Conclusion: Physicians perceive nasal symptoms to be the most frequent and the most bothersome symptoms in AR patients. The physicians' personal experiences with AR may influence their perception of patients’ symptoms.

Background Hypertension is a global health issue causing increased cardiovascular morbidity and mortality. Adherence to prescribed medication is a crucial factor in obtaining targeted outcomes, and fixed‐dose combined antihypertensive pills (FCAPs) have been shown to help combat difficulties associated with polypharmacy management. This study investigated the influence of combination antihypertensives on blood pressure (BP) management. Methods and Results Data from the 2013 to 2020 NHANES (National Health and Nutrition Examination Survey) were analyzed. Participants were included if between 18 and 79 years of age and were prescribed 2 antihypertensive classes. BP was deemed controlled if

Cancer is a leading cause of death worldwide. Glioblastoma (GBM) is a major challenge in oncology due to its highly invasive nature and limited treatment options. GBM's aggressive migration beyond tumor margins and rapid tumor growth hinders success in patient treatment. Localized therapeutic delivery, such as the use of transition metals like copper, is highlighted as a novel therapeutic agent for many potential biomedical applications. Herein, it is aimed to study the effects of Cu release on the proliferation and invasiveness of cancer cells. To this end, novel copper‐based nanostructures with different release patterns are designed. Using a complex 3D cell culture model to mimic the tumor microenvironment, it is shown that different patterns of copper ion release have a strong impact on GBM progression and invasiveness. The findings highlight the importance of optimizing localized copper release patterns to tailor different tumor treatment strategies. They also show the potential and suitability of 3D microchips as instruments to study the behavior of tumor spheroids. In spite of their limitations, these 3D microdevices enable a controlled and close monitoring of the influence of environmental factors (such as the presence of Cu ions) on the proliferation and invasiveness of the cells, with a better approach to reality compared to 2D models and with a more controlled environment, compared to an in vivo model.

The rapid expansion of freely available Earth observation data, combined with advancements in forest monitoring capabilities, has led to the production of a variety of datasets on forest cover and change at the national and global scales. These datasets are essential for informing science and policy. Yet, this surge in available data products comes with the challenge of reconciling differences in the mapping of forest, non-forest, and forest loss across products. Differences in forest cover mapping between products result in divergent estimates of forest area change, potentially constraining the utility of these products to inform science and policy, consistently, across scales. We use the case of Colombia to demonstrate that these inconsistencies can be largely resolved by advancing operational forest monitoring capabilities toward the representation of forest cover and change as continuous rather than discrete variables. The analysis consisted of a comparison between the global forest change product (GFC) and the official national datasets on forest cover change for Colombia (IDEAM) in terms of overall and per-class classification agreement and estimates of forest-area loss. The comparison was performed after harmonizing the GFC dataset (HGFC) to maximize its overall classification agreement with the IDEAM map, based on the adoption of optimum percent tree cover thresholds, applied to GFC for subnational units. Based on these results, we evaluate whether classification agreement and disagreement between mapped forest and non-forest classes by HGFC and IDEAM can be explained by differences in continuous physical forest attributes, represented by forest Canopy Height (CH) and Above-Ground Biomass Density (AGBD). We produced the analysis for the entire country and also for mountainous and non-mountainous areas separately. We show that the optimal threshold in tree cover that maximizes map agreement, varies largely between subnational units, with values ranging between 20% and 100%. Results show a high overall agreement and also high agreement for stable forest and non-forest classes. Agreement between pixels classified as forest loss was much lower, regardless of the map used as reference. Classification agreement was lower for mountainous areas than for non-mountainous areas, particularly for forest loss and stable forest classes. Pixels representing classification disagreement were characterized by intermediate values of CH and AGBD that are significantly different from pixels classified as non-forest and forest for both maps, with significantly lower and higher CH and AGBD values, respectively. Differences were more notable in non-mountainous areas than in mountainous ones. We conclude that solving these large existing discrepancies in forest classification and forest loss estimates between datasets requires advancing operational capabilities toward the representation of forest cover and change as continuous rather than as categorical variables, with particular emphasis on mountainous areas. We illustrate how moving in such a direction can (1) promote consistency between forest cover definitions and map representation, (2) facilitate comparability among products and estimates of forest area loss at different scales of analysis, and (3) promote accountability in forest area loss assessments.

Accumulation of K+ in shoots is largely dependent on K+ transport via the xylem and has important implications not only for K+ nutrition but also for stress tolerance. In tomato plants, the K+ channel SlSKOR contributed to K+ translocation but the decrease in the shoot K+ content in slskor mutants was only ∼15 %, indicating that additional K+ transport systems operated in the tomato stele. Here, we studied the physiological roles of the transporter SlNRT1.5 in tomato plants, whose homolog in Arabidopsis, AtNRT1.5, contributed to xylem K+ load. By using heterologous expression of SlNRT1.5 in Xenopus oocytes and a slnrt1.5 knock-out mutant, we have gained insights into its role in shoot K+ nutrition. Expression of SlNRT1.5 in Xenopus oocytes resulted in K+ efflux, similar to that mediated by AtNRT1.5, which could indicate that SlNRT1.5 operates as a K+ transport system. Plants lacking slnrt1.5 accumulated less K+ in shoots than WT plants under low external pH (4.5), and low supply of K+ (0.05 mM) and N (0.5 mM). Interestingly, slnrt1.5 plants accumulated less Na+ and Cl- in shoots than WT plants. Further analyses on slskor slnrt1.5 double mutant plants revealed an overlapping role of SlSKOR and SlNRT1.5 in shoot K+ accumulation. Double mutants showed a 40 % decrease in shoot K+ content in comparison with slskor and slnrt1.5 single mutants. Altogether, this study showed that SlNRT1.5 and SlSKOR are major players in shoot K+ accumulation in tomato plants.

Chimeric antigen receptor (CAR) T cell therapy has encountered limited success in solid tumors. The lack of dependable antigens and the immunosuppressive tumor microenvironment (TME) are major challenges. Within the TME, tumor cells along with immunosuppressive cells employ an immune-evasion mechanism that upregulates programmed death ligand 1 (PD-L1) to deactivate effector T cells; this makes PD-L1 a reliable, universal target for solid tumors. We developed a novel PD-L1 CAR (MC9999) using our humanized anti-PD-L1 monoclonal antibody, designed to simultaneously target tumor and immunosuppressive cells. The antigen-specific antitumor effects of MC9999 CAR T cells were observed consistently across four solid tumor models: breast cancer, lung cancer, melanoma, and glioblastoma multiforme (GBM). Notably, intravenous administration of MC9999 CAR T cells eradicated intracranially established LN229 GBM tumors, suggesting penetration of the blood-brain barrier. The proof-of-concept data demonstrate the cytolytic effect of MC9999 CAR T cells against immunosuppressive cells, including microglia HMC3 cells and M2 macrophages. Furthermore, MC9999 CAR T cells elicited cytotoxicity against primary tumor-associated macrophages within GBM tumors. The concept of targeting both tumor and immunosuppressive cells with MC9999 was further validated using CAR T cells derived from cancer patients. These findings establish MC9999 as a foundation for the development of effective CAR T cell therapies against solid tumors.

The Multiclass Classification Performance (MCP) curve is an innovative method to visualize the performance of a classifier for multiclass datasets. On the other hand, the Imbalanced Multiclass Classification Performance (IMCP) curve is a novel approach to visualizing classifier performance on multiclass datasets that exhibit class imbalance, i.e. the proportions of (two or more) class labels are unequal. We have developed an open-source Python package that encompasses the functionality required to calculate and visualize these two novel classification performance measures, along with providing the calculation of the area under the curves. The MCP and IMCP curves offer advantages over the traditional ROC (Receiver Operating Characteristic) curve when dealing with multiclass and imbalanced datasets, respectively. They provide more informative insights into classifier behavior, especially in scenarios involving multiple classes or uneven class distribution.

Capsicum annuum varieties are highly sensitive to drought. Under water stress conditions, these can show yield losses of up to 70 %. Due to the above, this work proposes a novel approach to obtain estimators of drought stress based on linear regression models for morpho-physiological and biochemical variables in jalapeño pepper (C. annuum cv. jalapeno M), bell pepper (C. annuum cv. california wonder), and serrano pepper (C. annnuum cv. serrano tampiqueno). Jalapeno pepper plants were grown for 69 days under permanent water deficit conditions at 40, 60, 80 % and 100 % of field capacity (FC) (100 % FC as control). Throughout the crop cycle, we monitored the plant's height and weight, basal stem diameter, transpiration, photosynthesis, stomatal conductance, NDVI, and proline. This monitoring allowed us to obtain linear regression models from the accumulated values for these variables, from which the slope values (β) were used as estimators of drought stress using the interval estimation method, in the same way, this method was used to estimate water status in bell pepper and serrano pepper. For bell pepper, drought levels of 40, 60, 80 and 100 % FC were imposed for 12 days and serrano pepper 60 and 100 % FC for 63 days. The results showed that this method can be used to estimate drought stress in jalapeno pepper for all the irrigation levels through photosynthesis and NDVI and can be applied for bell pepper and serrano pepper using stem diameter and plant height, and in the case of serrano pepper, NDVI showed adequate results. Also, this work establishes the relationship between the jalapeno pepper responses (morpho-physiological and biochemical) to drought stress during vegetative, flowering, and fruiting stages through a Principal Component Analysis (PCA). The PCA found that interaction among morphological, physiological, and biochemical responses change concerning the phenological stage of the plant. The results suggested several direct and inverse relationships between the variables and showed that drought can be described by stomatal conductance during any phenological stage of the crop. In parallel, the proline content, NDVI and plant height can also describe drought stress during the vegetative and flowering stages. This research is the first to apply this methodology to drought stress estimation in jalapeno, bell pepper, and serrano pepper cultivation. The results could significantly contribute to precision agriculture, sensor development, and water management.

Introduction: Weight regain after bariatric surgery remains a relevant and worrisome topic, requiring greater understanding and involvement in research into new adjuvant treatments. This study aims to compare the preliminary effectiveness and feasibility of the Mindfulness-Based Health Promotion and Attachment-Based Compassion Therapy programs as opposed to usual treatments (workshops) on the eating behavior of patients with progressive weight gain after bariatric surgery in Brazilian patients at a private clinic. It was hypothesized that both interventions are feasible and that the self-compassion program may be more effective than the mindfulness program. Methods: The study will be divided into two phases: a cross-analytical study of those who underwent bariatric surgery and a randomized controlled trial only with the ones who had weight regain. Interventions will be conducted for eight weeks synchronously with three assessment points (baseline, post intervention, and 6-month follow-up), both online. The primary outcome will be a change in eating behavior. Secondary outcomes will include improved quality of life, enhanced body image satisfaction and reduced distortion (Brazilian Silhouette Scales for adults), better weight management (maintenance or weight reduction), increased frequency of activity and monitoring with the surgery team. Qualitative data will also be collected by online identification of a sub-sample of participants. Results: Improvements are expected in eating behavior, weight, reverse progressive weight gain, classification of self-image, quality of life, and levels of mindfulness, self-compassion, and anxiety. Conclusion: This study seeks to gather preliminary evidence on the effectiveness of mindfulness and compassion training for the adjunctive treatment of progressive weight gain in post-bariatric patients.Clinical Trials.gov Registration ID: NCT04171713.

Pulmonary delivery and formulation of biologics are among the more complex and growing scientific topics in drug delivery. We herein developed a dry powder formulation using disordered mesoporous silica particles (MSP) as the sole excipient and lysozyme, the most abundant antimicrobial proteins in the airways, as model protein. The MSP had the optimal size for lung deposition (2.43 ± 0.13 µm). A maximum lysozyme loading capacity (0.35 mg/mg) was achieved in 150 mM PBS, which was seven times greater than that in water. After washing and freeze-drying, we obtained a dry powder consisting of spherical, non-aggregated particles, free from residual buffer, or unabsorbed lysozyme. The presence of lysozyme was confirmed by TGA and FT-IR, while N2 adsorption/desorption and SAXS analysis indicate that the protein is confined within the internal mesoporous structure. The dry powder exhibited excellent aerodynamic performance (fine particle fraction