Novel Methods for Personalized Gait Assistance: Three-Dimensional Trajectory Prediction Based on Regression and LSTM Models.

Enhancing human-robot interaction has been a primary focus in robotic gait assistance, with a thorough understanding of human motion being crucial for personalizing gait assistance. Traditional gait trajectory references from Clinical Gait Analysis (CGA) face limitations due to their inability to account for individual variability. Recent advancements in gait pattern generators, integrating regression models and Artificial Neural Network (ANN) techniques, have aimed at providing more personalized and dynamically adaptable solutions. This article introduces a novel approach that expands regression and ANN applications beyond mere angular estimations to include three-dimensional spatial predictions. Unlike previous methods, our approach provides comprehensive spatial trajectories for hip, knee and ankle tailored to individual kinematics, significantly enhancing end-effector rehabilitation robotic devices. Our models achieve state-of-the-art accuracy: overall RMSE of 13.40 mm and a correlation coefficient of 0.92 for the regression model, and RMSE of 12.57 mm and a correlation of 0.99 for the Long Short-Term Memory (LSTM) model. These advancements underscore the potential of these models to offer more personalized gait trajectory assistance, improving human-robot interactions.

Targeting CCR3 with antagonist SB 328437 sensitizes 5­fluorouracil­resistant gastric cancer cells: Experimental evidence and computational insights.

Gastric cancer (GC) ranks fifth globally in cancer diagnoses and third for cancer-related deaths. Chemotherapy with 5-fluorouracil (5-FU), a primary treatment, faces challenges due to the development of chemoresistance. Tumor microenvironment factors, including C-C motif chemokine receptor 3 (CCR3), can contribute to chemoresistance. The present study evaluated the effect of CCR3 receptor inhibition using the antagonist SB 328437 and the molecular dynamics of this interaction on resistance to 5-FU in gastric cancer cells. The 5-FU-resistant AGS cell line (AGS R-5FU) demonstrated notable tolerance to higher concentrations of 5-FU, with a 2.6-fold increase compared with the parental AGS cell line. Furthermore, the mRNA expression levels of thymidylate synthase (TS), a molecular marker for 5-FU resistance, were significantly elevated in AGS R-5FU cells. CCR3 was shown to be expressed at significantly higher levels in these resistant cells. Combining SB 328437 with 5-FU resulted in a significant decrease in cell viability, particularly at higher concentrations of 5-FU. Furthermore, when SB 328437 was combined with 5-FU at a high concentration, the relative mRNA expression levels of CCR3 and TS decreased significantly. Computational analysis of CCR3 demonstrated dynamic conformational changes, especially in extracellular loop 2 region, which indicated potential alterations in ligand recognition. Docking simulations demonstrated that SB 328437 bound to the allosteric site of CCR3, inducing a conformational change in ECL2 and hindering ligand recognition. The present study provides comprehensive information on the molecular and structural aspects of 5-FU resistance and CCR3 modulation, highlighting the potential for therapeutic application of SB 328437 in GC treatment.

Microbiome and plant cell transformation trigger insect gall induction in cassava.

Several specialised insects can manipulate normal plant development to induce a highly organised structure known as a gall, which represents one of the most complex interactions between insects and plants. Thus far, the mechanism for insect-induced plant galls has remained elusive. To study the induction mechanism of insect galls, we selected the gall induced by Iatrophobia brasiliensis (Diptera: Cecidomyiidae) in cassava (Euphorbiaceae: Manihot esculenta Crantz) as our model. PCR-based molecular markers and deep metagenomic sequencing data were employed to analyse the gall microbiome and to test the hypothesis that gall cells are genetically transformed by insect vectored bacteria. A shotgun sequencing discrimination approach was implemented to selectively discriminate between foreign DNA and the reference host plant genome. Several known candidate insertion sequences were identified, the most significant being DNA sequences found in bacterial genes related to the transcription regulatory factor CadR, cadmium-transporting ATPase encoded by the cadA gene, nitrate transport permease protein (nrtB gene), and arsenical pump ATPase (arsA gene). In addition, a DNA fragment associated with ubiquitin-like gene E2 was identified as a potential accessory genetic element involved in gall induction mechanism. Furthermore, our results suggest that the increased quality and rapid development of gall tissue are mostly driven by microbiome enrichment and the acquisition of critical endophytes. An initial gall-like structure was experimentally obtained in M. esculenta cultured tissues through inoculation assays using a Rhodococcus bacterial strain that originated from the inducing insect, which we related to the gall induction process. We provide evidence that the modification of the endophytic microbiome and the genetic transformation of plant cells in M. esculenta are two essential requirements for insect-induced gall formation. Based on these findings and having observed the same potential DNA marker in galls from other plant species (ubiquitin-like gene E2), we speculate that bacterially mediated genetic transformation of plant cells may represent a more widespread gall induction mechanism found in nature.

Individualized Three-Dimensional Gait Pattern Generator for Lower Limbs Rehabilitation Robots.

In the field of robotic gait rehabilitation, controlling robotic devices to follow specific human-like trajectories is often required. In recent years, various gait generator models have been proposed, providing customized gait patterns adjustable to a range of heights and gait speeds. However, these models were developed with a focus on gait rehabilitation devices designed to control the angular trajectories of the subject's joints, e.g. exoskeletons. Similar devices, e.g. end-effector robots, control the orientation and also the 3D position of the subject's joints and cannot easily implement these models. In this study, it is proposed a new individualized three-dimensional gait pattern generator for gait rehabilitation robots. The generator employs multi-variable regression models to predict the joint angular trajectories of the pelvis, hip, and ankle along the gait cycle. The 3D joints positions are then reconstructed by applying the predicted angular trajectories over a human model inspired on the inverted pendulum analogy using inverse kinematics. The generator's performance was statistically evaluated against real gait patterns from 42 participants walking at 8 different velocities. The predicted trajectories matched the measured ones with an average Root Mean Squared Error of 25.73 mm for all joints at all Cartesian axes, with better results between 3.3 - 5.4 km/h. Suggesting to be a good solution to be applied in end-effector gait robotic rehabilitation devices.

Design and Development of an Objective Evaluation System for a Web-Based Simulator for Trauma Management.

BACKGROUND: Trauma injuries are one of the main leading causes of death in the world. Training with guidelines and protocols is adequate to provide a fast and efficient treatment to patients that suffer a trauma injury. OBJECTIVES: This study aimed to evaluate deviations from a set protocol, a new set of metrics has been proposed and tested in a pilot study. METHODS: The participants were final-year students from the Universidad Autónoma de Madrid and first-year medical residents from the Hospital Universitario La Paz. They were asked to train four trauma scenarios with a web-based simulator for 2 weeks. A test was performed pre-training and another one post-training to evaluate the evolution of the treatment to those four trauma scenarios considering a predefined trauma protocol and based on the new set of metrics. The scenarios were pelvic and lower limb traumas in a hospital and in a prehospital setting, which allow them to learn and assess different trauma protocols. RESULTS: The results show that, in general, there is an improvement of the new metrics after training with the simulator. CONCLUSION: These new metrics provide comprehensive information for both trainers and trainees. For trainers, the evaluation of the simulation is automated and contains all relevant information to assess the performance of the trainee. And for trainees, it provides valuable real-time information that could support the trauma management learning process.

Modified Needleman-Wunsch algorithm for trauma management performance evaluation.

BACKGROUND: Trauma injuries are one of the leading causes of death in the world, representing approximately 8 % of all deaths. Therefore, trauma management training is of great importance and new training courses have arisen during the last decades. However, actual training courses do not typically analyze compliance with the protocols and guidelines available in the literature. Considering general trauma management guidelines such as the Advanced Trauma Life Support (ATLS) manual and the expertise of trauma specialists, a trauma management automated evaluation system has been designed in this paper. METHODS: A modification to the Needleman-Wunsch (NW) algorithm is developed, including all relevant aspects of trauma management to automatically evaluate how a trauma intervention has been implemented according to trauma protocols. This allows to consider more information with respect to the order of the actions taken and the type of actions performed than current evaluation methods, such as checklists or videos recorded in simulation. A web-based trauma simulator is used so that it can be used at any setting with internet connection. Final-year medical students and first- and second-year residents performed an experimental test, where a trauma score is obtained with the modified NW algorithm. This automatic score relates to how similar the actions are to trauma protocols. RESULTS: The results show the best combination of the scores used for the modified NW variables. This combination has an error, for the different case scenarios created, below 0.07 which verifies the values obtained. Additionally, trauma experts verified the results obtained showing a median difference of 0 between the protocol adherence evaluation using the algorithm and the one provided by the trauma experts. CONCLUSIONS: The best set of score values to apply to the modified NW algorithm show that the modified NW algorithm provides a successful objective measurement with respect to the protocol compliance.

The real bacterial filtration efficiency to evaluate the effective protection of facemasks used for the prevention of respiratory diseases.

The real protection offered by facemasks to control the transmission of respiratory viruses is still undetermined. Most of the manufacturing regulations, as well as scientific studies, have focused on studying the filtration capacity of the fabrics from which they are made, ignoring the air that escapes through the facial misalignments, and which depends on the respiratory frequencies and volumes. The objective of this work was to define a Real Bacterial Filtration Efficiency for each type of facemask, considering the bacterial filtration efficiency of the manufacturers and the air that passes through them. Nine different facemasks were tested on a mannequin with three gas analyzers (measuring inlet, outlet, and leak volumes) inside a polymethylmethacrylate box. In addition, the differential pressure was measured to determine the resistance offered by the facemasks during the inhalation and exhalation processes. Air was introduced with a manual syringe for 180 s simulating inhalations and exhalations at rest, light, moderate and vigorous activities (10, 60, 80 and 120 L/min, respectively). Statistical analysis showed that practically half of the air entering to the system is not filtered by the facemasks in all intensities (p < 0.001, ηp2 = 0.971). They also showed that the hygienic facemasks filter more than 70% of the air, and their filtration does not depend on the simulated intensity, while the rest of the facemasks show an evidently different response, influenced by the amount of air mobilized. Therefore, the Real Bacterial Filtration Efficiency can be calculated as a modulation of the Bacterial Filtration Efficiencies that depends on the type of facemask. The real filtration capacity of the facemasks has been overestimated during last years since the filtration of the fabrics is not the real filtration when the facemask is worn.

Neurodata Tracker: Software for computational assessment of hand motor skills based on optical motion capture in a virtual environment.

Objectives: Deficits affecting hand motor skills negatively impact the quality of life of patients. The NeuroData Tracker platform has been developed for the objective and precise evaluation of hand motor deficits. We describe the design and development of the platform and analyse the technological feasibility and usability in a relevant clinical setting. Methods: A software application was developed in Unity (C#) to obtain kinematic data from hand movement tracking by a portable device with two cameras and three infrared sensors (leap motion®). Four exercises were implemented: (a) wrist flexion-extension (b) finger-grip opening-closing (c) finger spread (d) fist opening-closing. The most representative kinematic parameters were selected for each exercise. A script in Python was integrated in the platform to transform real-time kinematic data into relevant information for the clinician. The application was tested in a pilot study comparing the data provided by the tool from ten healthy subjects without any motor impairment and ten patients diagnosed with a stroke with mild to moderate hand motor deficit. Results: The NeuroData Tracker allowed the parameterization of kinematics of hand movement and the issuance of a report with the results. The comparison of the data obtained suggests the feasibility of the tool for detecting differences between patients and healthy subjects. Conclusions: This new platform based on optical motion capturing provides objective measurement of hand movement allowing quantification of motor deficits. These findings require further validation of the tool in larger trials to verify its usefulness in the clinical setting.

Global beta-diversity of angiosperm trees is shaped by Quaternary climate change.

As Earth's climate has varied strongly through geological time, studying the impacts of past climate change on biodiversity helps to understand the risks from future climate change. However, it remains unclear how paleoclimate shapes spatial variation in biodiversity. Here, we assessed the influence of Quaternary climate change on spatial dissimilarity in taxonomic, phylogenetic, and functional composition among neighboring 200-kilometer cells (beta-diversity) for angiosperm trees worldwide. We found that larger glacial-interglacial temperature change was strongly associated with lower spatial turnover (species replacements) and higher nestedness (richness changes) components of beta-diversity across all three biodiversity facets. Moreover, phylogenetic and functional turnover was lower and nestedness higher than random expectations based on taxonomic beta-diversity in regions that experienced large temperature change, reflecting phylogenetically and functionally selective processes in species replacement, extinction, and colonization during glacial-interglacial oscillations. Our results suggest that future human-driven climate change could cause local homogenization and reduction in taxonomic, phylogenetic, and functional diversity of angiosperm trees worldwide.

Classification of Kinematic and Electromyographic Signals Associated with Pathological Tremor Using Machine and Deep Learning.

Peripheral Electrical Stimulation (PES) of afferent pathways has received increased interest as a solution to reduce pathological tremors with minimal side effects. Closed-loop PES systems might present some advantages in reducing tremors, but further developments are required in order to reliably detect pathological tremors to accurately enable the stimulation only if a tremor is present. This study explores different machine learning (K-Nearest Neighbors, Random Forest and Support Vector Machines) and deep learning (Long Short-Term Memory neural networks) models in order to provide a binary (Tremor; No Tremor) classification of kinematic (angle displacement) and electromyography (EMG) signals recorded from patients diagnosed with essential tremors and healthy subjects. Three types of signal sequences without any feature extraction were used as inputs for the classifiers: kinematics (wrist flexion-extension angle), raw EMG and EMG envelopes from wrist flexor and extensor muscles. All the models showed high classification scores (Tremor vs. No Tremor) for the different input data modalities, ranging from 0.8 to 0.99 for the f1 score. The LSTM models achieved 0.98 f1 scores for the classification of raw EMG signals, showing high potential to detect tremors without any processed features or preliminary information. These models may be explored in real-time closed-loop PES strategies to detect tremors and enable stimulation with minimal signal processing steps.

Malnutrition, Functional Decline, and Institutionalization in Older Adults after Hospital Discharge Following Community-Acquired Pneumonia.

BACKGROUND AND AIMS: Community-acquired pneumonia (CAP) is a major threat to older adults, but mid-term implications are poorly described. The aim was to analyze functional decline, institutionalization, malnutrition, and risk factors after hospital admission for CAP. METHODS: This prospective observational study included patients over 65 years discharged after CAP between May 2019 and July 2021. We performed a comprehensive geriatric assessment and a general nutritional assessment 30-60 days after CAP. This included the MNA and blood test with trace elements and vitamins. The main outcomes were functional decline, institutionalization, and malnutrition. Multivariate logistic regression was used for the analyses. RESULTS: In total, 144 patients of 77.15 ± 7.91 years, 55.6% male, and 9% previously institutionalized were analyzed. At hospital admission, the Charlson Comorbidity Index (CCI) was 1.5 ± 1.6, the Pneumonia Severity Index was 98.1 ± 25.9, and the previous Barthel Index (BI) was 93.06 ± 17.13. Hospital stay was 9.72 ± 7.88 days. After 44.6 ± 14.4 days, 48.6% patients showed functional decline and 19.4% were institutionalized. Age (OR 1.17; CI 95% 1.09-1.26), previous institutionalization (29.1; 3.7-224.7), BI (1.09; 1.05-1.14), CCI (1.5; 1.1-2.1), and length of stay (1.1, 1.02-1.18) were independently associated with functional decline. The only predictors of new institutionalization were previous BI (0.96; 0.93-0.99) and length of stay (1.06; 1.00-1.13). The MNA indicated malnutrition in 28% of the community-dwelling patients and 67.9% of those institutionalized, with risk of malnutrition being 45.7% and 9.5%, respectively, after an average of 44.6 days of CAP diagnosis. The predictors of malnutrition were previous institutionalization (10.62; 2.20-51.21), BI (0.95; 0.92-0.98), and length of stay (1.12; 1.04-1.20). Micronutrient deficiencies were mainly zinc (61.8%), vitamin D (54.5%), and vitamin C (45.1%). An MNA score < 17 points or hypoalbuminemia showed good specificity to identify these deficiencies. CONCLUSIONS: After CAP admission, functional decline, institutionalization, and malnutrition rates were high. Longer hospital stay was a common risk factor for all outcomes. The presence of hypoalbuminemia or an MNA < 17 in older patients should prompt suspicion of deficiencies in micronutrients, such as vitamin D, C, and zinc.

Understanding climate change impacts on biome and plant distributions in the Andes: Challenges and opportunities.

Aim: Climate change is expected to impact mountain biodiversity by shifting species ranges and the biomes they shape. The extent and regional variation in these impacts are still poorly understood, particularly in the highly biodiverse Andes. Regional syntheses of climate change impacts on vegetation are pivotal to identify and guide research priorities. Here we review current data, knowledge and uncertainties in past, present and future climate change impacts on vegetation in the Andes. Location: Andes. Taxon: Plants. Methods: We (i) conducted a literature review on Andean vegetation responses to past and contemporary climatic change, (ii) analysed future climate projections for different elevations and slope orientations at 19 Andean locations using an ensemble of model outputs from the Coupled Model Intercomparison Project 5, and (iii) calculated changes in the suitable climate envelope area of Andean biomes and compared these results to studies that used species distribution models. Results: Future climatic changes (2040-2070) are projected to be stronger at high-elevation areas in the tropical Andes (up to 4°C under RCP 8.5), while in the temperate Andes temperature increases are projected to be up to 2°C. Under this worst-case scenario, temperate deciduous forests and the grasslands/steppes from the Central and Southern Andes are predicted to show the greatest losses of suitable climatic space (30% and 17%-23%, respectively). The high vulnerability of these biomes contrasts with the low attention from researchers modelling Andean species distributions. Critical knowledge gaps include a lack of an Andean wide plant checklist, insufficient density of weather stations at high-elevation areas, a lack of high-resolution climatologies that accommodates the Andes' complex topography and climatic processes, insufficient data to model demographic and ecological processes, and low use of palaeo data for distribution modelling. Main conclusions: Climate change is likely to profoundly affect the extent and composition of Andean biomes. Temperate Andean biomes in particular are susceptible to substantial area contractions. There are, however, considerable challenges and uncertainties in modelling species and biome responses and a pressing need for a region-wide approach to address knowledge gaps and improve understanding and monitoring of climate change impacts in these globally important biomes.

Simulation-Based Education in Trauma Management: A Scoping Review.

Trauma injuries are an important healthcare problem and one of the main leading causes of death worldwide. The purpose of this review was to analyze current practices in teaching trauma management using simulations, with the aim of summarizing them, identifying gaps and providing a critical overview on what has already been achieved. A search on the Web of Science website for simulation-based trauma training articles published from 2010 onwards was performed, obtaining 1617 publications. These publications were screened to 35 articles, which were deeply analyzed, gathering the following information: the authors, the publication type, the year of the publication, the total number of citations, the population of the training, the simulation method used, the skills trained, the evaluation type used for the simulation method presented in the paper, if skills improved after the training and the context in which the simulation took place. Of the 35 articles included in this review, only a few of them had students as the target audience. The more used simulation method was a high-fidelity mannequin, in which the participants trained in more technical than non-technical skills. Almost none of the studies introduced an automated evaluation process and most of the evaluation methods consisted of checklists or questionnaires. Finally, trauma training focused more on treating trauma patients in a hospital environment than in a pre-hospital one. Overall, improvements in the evaluation method, as well as in the development of trauma training on undergraduate education, are important areas for further development.

The Need for Trauma Management Training and Evaluation on a Prehospital Setting.

Trauma is one of the leading causes of death in the world, being the main cause of death in people under 45 years old. The epidemiology of these deaths shows an important peak during the first hour after a traumatic event. Therefore, learning how to manage traumatic injuries in a prehospital setting is of great importance. Medical students from Universidad Autónoma performed 66 different simulations to stabilize a trauma patient on a prehospital scene by using a web-based trauma simulator. Then, a panel of trauma experts evaluated the simulations performed, observing that, on average, an important number of simulations were scored below 5, being the score values provided from 0, minimum, to 10, maximum. Therefore, the first need detected is the need to further train prehospital trauma management in undergraduate education. Additionally, a deeper analysis of the scores provided by the experts was performed. It showed a great dispersion in the scores provided by the different trauma experts per simulation. Therefore, a second need is identified, the need to develop a system to objectively evaluate trauma management.

Prediction of Pathological Tremor Signals Using Long Short-Term Memory Neural Networks.

Previous implementations of closed-loop peripheral electrical stimulation (PES) strategies have provided evidence about the effect of the stimulation timing on tremor reduction. However, these strategies have used traditional signal processing techniques that only consider phase prediction and might not model the non-stationary behavior of tremor. Here, we tested the use of long short-term memory (LSTM) neural networks to predict tremor signals using kinematic data recorded from Essential Tremor (ET) patients. A dataset comprising wrist flexion-extension data from 12 ET patients was pre-processed to feed the predictors. A total of 180 models resulting from the combination of network (neurons and layers of the LSTM networks, length of the input sequence and prediction horizon) and training parameters (learning rate) were trained, validated and tested. Predicted tremor signals using LSTM-based models presented high correlation values (from 0.709 to 0.998) with the expected values, with a phase delay between the predicted and real signals below 15 ms, which corresponds approximately to 7.5% of a tremor cycle. The prediction horizon was the parameter with a higher impact on the prediction performance. The proposed LSTM-based models were capable of predicting both phase and amplitude of tremor signals outperforming results from previous studies (32--56% decreased phase prediction error compared to the out-of-phase method), which might provide a more robust PES-based closed-loop control applied to PES-based tremor reduction.

The Kidney in Heart Failure: The Role of Venous Congestion.

Heart failure can lead to renal impairment, an interaction now termed "cardiorenal syndrome." The prevalent physiological explanation for the renal impairment that accompanies heart failure centers around the forward failure hypothesis, which emphasizes the role of left ventricular dysfunction in causing edema, and the backward failure hypothesis, which singles out venous congestion as the dominant mechanism of edema and reduced glomerular filtration rate. In this review, we provide an appraisal on venous congestion, an extremely important contributor that has received little attention. We also summarize the pharmacology of loop diuretics, explain current understanding of diuretic resistance, and address controversies regarding decongestive treatments.

High exposure of global tree diversity to human pressure.

Safeguarding Earth's tree diversity is a conservation priority due to the importance of trees for biodiversity and ecosystem functions and services such as carbon sequestration. Here, we improve the foundation for effective conservation of global tree diversity by analyzing a recently developed database of tree species covering 46,752 species. We quantify range protection and anthropogenic pressures for each species and develop conservation priorities across taxonomic, phylogenetic, and functional diversity dimensions. We also assess the effectiveness of several influential proposed conservation prioritization frameworks to protect the top 17% and top 50% of tree priority areas. We find that an average of 50.2% of a tree species' range occurs in 110-km grid cells without any protected areas (PAs), with 6,377 small-range tree species fully unprotected, and that 83% of tree species experience nonnegligible human pressure across their range on average. Protecting high-priority areas for the top 17% and 50% priority thresholds would increase the average protected proportion of each tree species' range to 65.5% and 82.6%, respectively, leaving many fewer species (2,151 and 2,010) completely unprotected. The priority areas identified for trees match well to the Global 200 Ecoregions framework, revealing that priority areas for trees would in large part also optimize protection for terrestrial biodiversity overall. Based on range estimates for >46,000 tree species, our findings show that a large proportion of tree species receive limited protection by current PAs and are under substantial human pressure. Improved protection of biodiversity overall would also strongly benefit global tree diversity.

Asociación y valor predictivo del índice poder mecánico-distensibilidad pulmonar con días libres de ventilación mecánica en pacientes con COVID-19 en una unidad de terapia intensiva / Association and predictive value of the mechanical power-lung compliance index with free days off mechanical ventilation in patients with COVID-19 in an intensive care unit / Associação e valor preditivo do índice de potência mecânica/complacência pulmonar com dias livres de ventilação mecânica em pacientes com COVID-19 em unidade de terapia intensiva

Resumen: Introducción: El poder mecánico (PM) se asocia a mortalidad y se debe ajustar a las características pulmonares en pacientes COVID-19. Material y métodos: Estudio observacional, retrospectivo y analítico, de septiembre de 2020 a febrero de 2021. Los parámetros de ventilación y análisis de la curva ROC y modelos de regresión de Poisson para OR. Objetivo primario fue determinar la asociación entre el índice PM/Cest y días libres de ventilación mecánica (DLVM). Resultados: Se incluyeron 43 pacientes. Se dividió en sobrevivientes (n = 25, 58.1%) y no sobrevivientes (n = 18, 41.9%). Se eligió mediana de DLVM con los parámetros de VMI. El índice PM/Cest inicial ABC 0.73 [IC 95% (0.58-0.88), p = 0.008], punto de corte de 0.90 Joules/min/mL/cm H2O. La regresión multivariable de Poisson el índice PM/Cest inicial OR 0.18 [IC 95% (0.03-0.98), p = 0.047]. Discusión: Coppola y colaboradores documentaron que en pacientes con SDRA no COVID-19, el valor de PM absoluto no demostró significancia; al ajustarlo a Cest fue independiente para mortalidad. Conclusiones: El índice PM/Cest al inicio se asoció de forma significativa e independiente con DLVM en COVID-19. Punto de corte de 0.9 J/min/mL/cmH2O con mejor sensibilidad y especificidad para predecir los DLVM y esto podría reducir la mortalidad.

Abstract: Introduction: Mechanical power (MP) is associated with mortality and must be adjusted to the pulmonary characteristics in COVID-19 patients. Material and methods: Observational, retrospective, analytical study from September 2020-February 2021. Ventilation parameters and ROC curve analysis and Poisson regression models for OR. Primary objective was to determine the association between the PM/Cest index and free days of mechanical ventilation (FDMV). Results: 43 patients were included. It was divided into survivors (n = 25, 58.1%) and non-survivors (n = 18, 41.9%). Median FDMV was chosen with the IMV parameters. The initial MP/Cest index ABC 0.73 [95% CI (0.58-0.88), p = 0.008], cut-off point of 0.90 J/min/mL/cmH2O. The multivariate Poisson regression showed the initial MP/Cest index OR 0.18 [95% CI (0.03-0.98), p = 0.047]. Discussion: Coppola et al. documented in patients with non-COVID-19 ARDS, the absolute MP value did not demonstrate significance; when adjusted to Cest, it was independent for mortality. Conclusions: The MP/Cest index at baseline was significantly and independently associated with FDMV in COVID-19. Cut-off point of 0.9 J/min/mL/cmH2O with better sensitivity and specificity to predict FDMV and this could reduce mortality.

Resumo: Introdução: A potência mecânica (PM) está associada à mortalidade e deve ser ajustada para características pulmonares em pacientes com COVID-19. Material e métodos: Estudo observacional, retrospectivo, analítico de setembro de 2020 a fevereiro de 2021. Os parâmetros ventilatórios, análise da curva ROC e modelos de regressão de Poisson para OR. O objetivo primário foi determinar a associação entre o índice PM/Cest e dias livres de ventilação mecânica (DLVM). Resultados: Foram incluídos 43 pacientes. Dividiu-se em sobreviventes (n = 25, 58.1%) e não sobreviventes (n = 18, 41.9%). A mediana do DLVM foi escolhida com os parâmetros do VMI. Índice inicial PM/Cest ABC 0.73 [IC 95% (0.58-0.88), p = 0.008], ponto de corte de 0.90 J/min/mL/cmH2O. Regressão multivariável de Poisson no índice PM/Cest inicial OR 0.18 [IC 95% (0.03-0.98), p = 0.047]. Discussão: Coppola et al. documentaram em pacientes com SDRA não-COVID-19, o valor de PM absoluto não mostrou significância; quando ajustado a Cest, foi independente para mortalidade. Conclusões: O índice PM/Cest ao início se associou de maneira significativa e independentemente com DLVM na COVID-19. Ponto de corte de 0.9 J/min/mL/cmH2O com melhor sensibilidade e especificidade para predizer DLVM e isso poderia reduzir a mortalidade.

Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation.

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles.