The association between probable post-COVID-19 condition and sleep-related parameters: a longitudinal study of non-hospitalised patients.

The long-term effects of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection on sleep remain poorly known. We evaluated the association between probable post-COVID-19 condition and changes in sleep quality and quantity before and after SARS-CoV-2 infection in a consecutive sample of non-hospitalized adults. Individuals were identified with SARS-CoV-2 infection in 2020 at the central laboratory of a tertiary hospital in Porto and followed as outpatients. We included patients diagnosed with SARS-CoV-2 infection ≥3 months before this evaluation, with no missing data on key variables (n = 2445). Participants completed a questionnaire that included sociodemographic, clinical, and infection-related questions. We computed changes in sleep-related parameters referred to 1 month before diagnosis and 1 week before the questionnaire. Multinomial logistic regression models were fitted to compute crude and adjusted odds ratios and 95% confidence intervals (95% CIs). Compared to the pre-infection period, those with probable post-COVID-19 condition reported a greater decrease in hours of sleep, had a 2.60 (95% CI 2.02-3.34) higher adjusted odds of perceiving their sleep quality as worsened and experienced a significant increase in number of days with sleeping disturbances as defined according to multiple items. The association between post-COVID-19 condition and indicators of poor sleep health requires special attention from healthcare professionals and services. It is essential that appropriate multidisciplinary care is provided to mitigate the physical, psychological, social, and professional impact of sleeping problems in these already burdened patients.

Acid-Catalyzed Liquefaction of Biomasses from Poplar Clones for Short Rotation Coppice Cultivations.

Liquefaction of biomass delivers a liquid bio-oil with relevant chemical and energetic applications. In this study we coupled it with short rotation coppice (SRC) intensively managed poplar cultivations aimed at biomass production while safeguarding environmental principles of soil quality and biodiversity. We carried out acid-catalyzed liquefaction, at 160 °C and atmospheric pressure, with eight poplar clones from SRC cultivations. The bio-oil yields were high, ranging between 70.7 and 81.5%. Average gains of bio-oil, by comparison of raw biomasses, in elementary carbon and hydrogen and high heating, were 25.6, 67, and 74%, respectively. Loss of oxygen and O/C ratios averaged 38 and 51%, respectively. Amounts of elementary carbon, oxygen, and hydrogen in bio-oil were 65, 26, and 8.7%, and HHV averaged 30.5 MJkg-1. Correlation analysis showed the interrelation between elementary carbon with HHV in bio-oil or with oxygen loss. Overall, from 55 correlations, 21 significant and high correlations among a set of 11 variables were found. Among the most relevant ones, the percentage of elementary carbon presented five significant correlations with the percentage of O (-0.980), percentage of C gain (0.902), percentage of O loss (0.973), HHV gain (0.917), and O/C loss (0.943). The amount of carbon is directly correlated with the amount of oxygen, conversely, the decrease in oxygen content increases the elementary carbon and hydrogen concentration, which leads to an improvement in HHV. HHV gain showed a strong positive dependence on the percentage of C (0.917) and percentage of C gain (0.943), while the elementary oxygen (-0.885) and its percentage of O loss (0.978) adversely affect the HHV gain. Consequently, the O/C loss (0.970) increases the HHV positively. van Krevelen's analysis indicated that bio-oils are chemically compatible with liquid fossil fuels. FTIR-ATR evidenced the presence of derivatives of depolymerization of lignin and cellulose in raw biomasses in bio-oil. TGA/DTG confirmed the bio-oil burning aptitude by the high average 53% mass loss of volatiles associated with lowered peaking decomposition temperatures by 100 °C than raw biomasses. Overall, this research shows the potential of bio-oil from liquefaction of SRC biomasses for the contribution of renewable energy and chemical deliverables, and thereby, to a greener global economy.

Thermochemical Liquefaction as a Cleaner and Efficient Route for Valuing Pinewood Residues from Forest Fires.

Biomass thermochemical liquefaction is a chemical process with multifunctional bio-oil as its main product. Under this process, the complex structure of lignocellulosic components can be hydrolysed into smaller molecules at atmospheric pressure. This work demonstrates that the liquefaction of burned pinewood from forest fires delivers similar conversion rates into bio-oil as non-burned wood does. The bio-oils from four burned biomass fractions (heartwood, sapwood, branches, and bark) showed lower moisture content and higher HHV (ranging between 32.96 and 35.85 MJ/kg) than the initial biomasses. The increased HHV resulted from the loss of oxygen, whereas the carbon and hydrogen mass fractions increased. The highest conversion of bark and heartwood was achieved after 60 min of liquefaction. Sapwood, pinewood, and branches reached a slightly higher conversion, with yields about 8% greater, but with longer liquefaction time resulting in higher energy consumption. Additionally, the van Krevelen diagram indicated that the produced bio-oils were closer and chemically more compatible (in terms of hydrogen and oxygen content) to the hydrocarbon fuels than the initial biomass counterparts. In addition, bio-oil from burned pinewood was shown to be a viable alternative biofuel for heavy industrial applications. Overall, biomass from forest fires can be used for the liquefaction process without compromising its efficiency and performance. By doing so, it recovers part of the lost value caused by wildfires, mitigating their negative effects.

Mapping Utility Poles in Aerial Orthoimages Using ATSS Deep Learning Method.

Mapping utility poles using side-view images acquired with car-mounted cameras is a time-consuming task, mainly in larger areas due to the need for street-by-street surveying. Aerial images cover larger areas and can be feasible alternatives although the detection and mapping of the utility poles in urban environments using top-view images is challenging. Thus, we propose the use of Adaptive Training Sample Selection (ATSS) for detecting utility poles in urban areas since it is a novel method and has not yet investigated in remote sensing applications. Here, we compared ATSS with Faster Region-based Convolutional Neural Networks (Faster R-CNN) and Focal Loss for Dense Object Detection (RetinaNet ), currently used in remote sensing applications, to assess the performance of the proposed methodology. We used 99,473 patches of 256 × 256 pixels with ground sample distance (GSD) of 10 cm. The patches were divided into training, validation and test datasets in approximate proportions of 60%, 20% and 20%, respectively. As the utility pole labels are point coordinates and the object detection methods require a bounding box, we assessed the influence of the bounding box size on the ATSS method by varying the dimensions from 30×30 to 70×70 pixels. For the proposal task, our findings show that ATSS is, on average, 5% more accurate than Faster R-CNN and RetinaNet. For a bounding box size of 40×40, we achieved Average Precision with intersection over union of 50% (AP50) of 0.913 for ATSS, 0.875 for Faster R-CNN and 0.874 for RetinaNet. Regarding the influence of the bounding box size on ATSS, our results indicate that the AP50 is about 6.5% higher for 60×60 compared to 30×30. For AP75, this margin reaches 23.1% in favor of the 60×60 bounding box size. In terms of computational costs, all the methods tested remain at the same level, with an average processing time around of 0.048 s per patch. Our findings show that ATSS outperforms other methodologies and is suitable for developing operation tools that can automatically detect and map utility poles.

An Ontology-Based Cybersecurity Framework for the Internet of Things.

The use of sensors and actuators as a form of controlling cyber-physical systems in resource networks has been integrated and referred to as the Internet of Things (IoT). However, the connectivity of many stand-alone IoT systems through the Internet introduces numerous cybersecurity challenges as sensitive information is prone to be exposed to malicious users. This paper focuses on the improvement of IoT cybersecurity from an ontological analysis, proposing appropriate security services adapted to the threats. The authors propose an ontology-based cybersecurity framework using knowledge reasoning for IoT, composed of two approaches: (1) design time, which provides a dynamic method to build security services through the application of a model-driven methodology considering the existing enterprise processes; and (2) run time, which involves monitoring the IoT environment, classifying threats and vulnerabilities, and actuating in the environment ensuring the correct adaptation of the existing services. Two validation approaches demonstrate the feasibility of our concept. This entails an ontology assessment and a case study with an industrial implementation.

Escherichia coli α-hemolysin counteracts the anti-virulence innate immune response triggered by the Rho GTPase activating toxin CNF1 during bacteremia.

The detection of the activities of pathogen-encoded virulence factors by the innate immune system has emerged as a new paradigm of pathogen recognition. Much remains to be determined with regard to the molecular and cellular components contributing to this defense mechanism in mammals and importance during infection. Here, we reveal the central role of the IL-1ß signaling axis and Gr1+ cells in controlling the Escherichia coli burden in the blood in response to the sensing of the Rho GTPase-activating toxin CNF1. Consistently, this innate immune response is abrogated in caspase-1/11-impaired mice or following the treatment of infected mice with an IL-1ß antagonist. In vitro experiments further revealed the synergistic effects of CNF1 and LPS in promoting the maturation/secretion of IL-1ß and establishing the roles of Rac, ASC and caspase-1 in this pathway. Furthermore, we found that the α-hemolysin toxin inhibits IL-1ß secretion without affecting the recruitment of Gr1+ cells. Here, we report the first example of anti-virulence-triggered immunity counteracted by a pore-forming toxin during bacteremia.

Rethinking life and predicting its origin.

The definition, origin and recreation of life remain elusive. As others have suggested, only once we put life into reductionist physical terms will we be able to solve those questions. To that end, this work proposes the phenomenon of life to be the product of two dissipative mechanisms. From them, one characterises extant biological life and deduces a testable scenario for its origin. The proposed theory of life allows its replication, reinterprets ecological evolution and creates new constraints on the search for life.

Marine litter weight estimation from UAV imagery: Three potential methodologies to advance macrolitter reports.

In the context of marine litter monitoring, reporting the weight of beached litter can contribute to a better understanding of pollution sources and support clean-up activities. However, the litter scaling task requires considerable effort and specific equipment. This experimental study proposes and evaluates three methods to estimate beached litter weight from aerial images, employing different levels of litter categorization. The most promising approach (accuracy of 80 %) combined the outcomes of manual image screening with a generalized litter mean weight (14 g) derived from studies in the literature. Although the other two methods returned values of the same magnitude as the ground-truth, they were found less feasible for the aim. This study represents the first attempt to assess marine litter weight using remote sensing technology. Considering the exploratory nature of this study, further research is needed to enhance the reliability and robustness of the methods.

A deep learning approach based on graphs to detect plantation lines.

Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information from diverse imagery conditions. However, even state-of-the-art methods may stumble in complex plantation patterns. Here, we propose a deep learning approach based on graphs to detect plantation lines in UAV-based RGB imagery, presenting a challenging scenario containing spaced plants. The first module of our method extracts a feature map throughout the backbone, which consists of the initial layers of the VGG16. This feature map is used as an input to the Knowledge Estimation Module (KEM), organized in three concatenated branches for detecting 1) the plant positions, 2) the plantation lines, and 3) the displacement vectors between the plants. A graph modeling is applied considering each plant position on the image as vertices, and edges are formed between two vertices (i.e. plants). Finally, the edge is classified as pertaining to a certain plantation line based on three probabilities (higher than 0.5): i) in visual features obtained from the backbone; ii) a chance that the edge pixels belong to a line, from the KEM step; and iii) an alignment of the displacement vectors with the edge, also from the KEM step. Experiments were conducted initially in corn plantations with different growth stages and patterns with aerial RGB imagery to present the advantages of adopting each module. We assessed the generalization capability in the other two cultures (orange and eucalyptus) datasets. The proposed method was compared against state-of-the-art deep learning methods and achieved superior performance with a significant margin considering all three datasets. This approach is useful in extracting lines with spaced plantation patterns and could be implemented in scenarios where plantation gaps occur, generating lines with few-to-no interruptions.

Extracellular Vesicles and Infection: From Hijacked Machinery to Therapeutic Tools.

Extracellular vesicles (EVs) comprise a broad range of secreted cell-derived membrane vesicles. Beyond their more well-characterized role in cell communication, in recent years, EVs have also been shown to play important roles during infection. Viruses can hijack the biogenesis of exosomes (which are small EVs) to promote viral spreading. Additionally, these exosomes are also important mediators in inflammation and immune responses during both bacterial and viral infections. This review summarizes these mechanisms while also describing the impact of bacterial EVs in regulating immune responses. Finally, the review also focuses on the potential and challenges of using EVs, in particular, to tackle infectious diseases.

Biodegradable Microcapsules of Poly(Butylene Adipate-co-Terephthalate) (PBAT) as Isocyanate Carriers and the Effect of the Process Parameters.

Poly(butylene adipate-co-terephthalate) (PBAT), a biodegradable flexible, and tough polymer is herein used, for the first time, to encapsulate and protect isocyanate derivatives. Isocyanates are essential building blocks widely employed in the chemical industry for the production of high-performing materials. Microencapsulation of isocyanates eliminates the risks associated with their direct handling and protects them from moisture. In light of this, and having in mind eco-innovative products and sustainability, we present a straightforward process to encapsulate isophorone diisocyanate (IPDI) using this biodegradable polymer. Spherical and core-shell microcapsules (MCs) were produced by an emulsion system combined with the solvent evaporation method. The MCs present a regular surface, without holes or cracks, with a thin shell and high isocyanate loadings, up to 79 wt%. Additionally, the MCs showed very good isocyanate protection if not dispersed in organic or aqueous solutions. Effects of various process parameters were systematically studied, showing that a higher stirring speed (1000 rpm) and emulsifier amount (2.5 g), as well as a smaller PBAT amount (1.60 g), lead to smaller MCs and narrower size distribution.

Spectroscopic Detection of Biosignatures in Natural Ice Samples as a Proxy for Icy Moons.

Some of the icy moons of the solar system with a subsurface ocean, such as Europa and Enceladus, are the targets of future space missions that search for potential extraterrestrial life forms. While the ice shells that envelop these moons have been studied by several spacecrafts, the oceans beneath them remain unreachable. To better constrain the habitability conditions of these moons, we must understand the interactions between their frozen crusts, liquid layers, and silicate mantles. To that end, astrobiologists rely on planetary field analogues, for which the polar regions of Earth have proven to be great candidates. This review shows how spectroscopy is a powerful tool in space missions to detect potential biosignatures, in particular on the aforementioned moons, and how the polar regions of the Earth are being used as planetary field analogues for these extra-terrestrial environments.

First Report on the Synergistic Interaction between Essential Oils against the Pinewood Nematode Bursaphelenchus xylophilus.

Control of the pinewood nematode (PWN), the causal agent of pine wilt disease, can be achieved through the trunk injection of nematicides; however, many pesticides have been linked to environmental and human health concerns. Essential oils (EOs) are suitable alternatives due to their biodegradability and low toxicity to mammals. These complex mixtures of plant volatiles often display multiple biological activities and synergistic interactions between their compounds. The present work profiled the toxicity of eight EOs against the PWN in comparison to their 1:1 mixtures, to screen for successful synergistic interactions. Additionally, the main compounds of the most synergistic mixtures were characterized for their predicted environmental fate and toxicity to mammals in comparison to emamectin benzoate, a commercial nematicide used against PWN. The mixtures of Cymbopogon citratus with Mentha piperita and of Foeniculum vulgare with Satureja montana EOs showed the highest activities, with half-maximal effective concentrations (EC50) of 0.09 and 0.05 µL/mL, respectively. For these, complete PWN mortality was reached after only ca. 15 min or 2 h of direct contact, respectively. Their major compounds had a higher predicted affinity to air and water environmental compartments and are reported to have very low toxicity to mammals, with low acute oral and dermal toxicities. In comparison, emamectin benzoate showed lower nematicidal activity, a higher affinity to the soil and sediments environmental compartments and higher reported oral and dermal toxicity to mammals. Overall, uncovering synergistic activities in combinations of EOs from plants of different families may prove to be a source of biopesticides with optimized toxicity against PWNs.

Contrastive language and vision learning of general fashion concepts.

The steady rise of online shopping goes hand in hand with the development of increasingly complex ML and NLP models. While most use cases are cast as specialized supervised learning problems, we argue that practitioners would greatly benefit from general and transferable representations of products. In this work, we build on recent developments in contrastive learning to train FashionCLIP, a CLIP-like model adapted for the fashion industry. We demonstrate the effectiveness of the representations learned by FashionCLIP with extensive tests across a variety of tasks, datasets and generalization probes. We argue that adaptations of large pre-trained models such as CLIP offer new perspectives in terms of scalability and sustainability for certain types of players in the industry. Finally, we detail the costs and environmental impact of training, and release the model weights and code as open source contribution to the community.

A Brief Evaluation of Antioxidants, Antistatics, and Plasticizers Additives from Natural Sources for Polymers Formulation.

The circular economy plays an important role in the preparation and recycling of polymers. Research groups in different fields, such as materials science, pharmaceutical and engineering, have focused on building sustainable polymers to minimize the release of toxic products. Recent studies focused on the circular economy have suggested developing new polymeric materials based on renewable and sustainable sources, such as using biomass waste to obtain raw materials to prepare new functional bio-additives. This review presents some of the main characteristics of common polymer additives, such as antioxidants, antistatic agents and plasticizers, and recent research in developing bio-alternatives. Examples of these alternatives include the use of polysaccharides from agro-industrial waste streams that can be used as antioxidants, and chitosan which can be used as an antistatic agent.

Development and In Vitro Validation of Antibacterial Paints Containing Chloroxylenol and Terpineol.

The establishment of self-disinfecting surfaces is an important method to avoid surface contamination. Recently, paints with antimicrobial properties have been developed to be applied on different surfaces, avoiding contamination with pathogens. In this work, self-disinfecting paints containing Chloroxylenol (CLX), Terpineol (TRP), and a mixture of both substances were developed. The goal was to evaluate and validate these paints using international standards for eventual commercialization and application in scenarios where surface contamination represents a problem. The paints were challenged with five different bacteria, Gram-positive and Gram-negative, before and after a scrub resistance test, where the long-term efficacy of the paints was evaluated. The antibacterial activity assessment was performed following ISO 22196 and JIS Z2801. In general, the paints showed very promising results, demonstrating their antibacterial activity, before and after scrub resistance test. The paint incorporating the mixture of CLX and TRP (CLX+TRP) stood out by revealing consistent results of antibacterial activity both before and after the scrub resistance test for most of the tested bacteria. The cytotoxicity of the developed paints was assessed in vitro by performing tests by direct contact with a human skin cell line, HaCaT, and testes on extracts with HaCaT and a pulmonary cell line, A549. The methodologies for cytotoxicity assessment were developed based in ISO 10993. For genotoxicity assessment, alkaline comet assay was conducted on both cell lines. The cytotoxicity assessment revealed promising results with the paints, demonstrating values of cellular viability above 70% and values of lactate dehydrogenase (LDH) leakage below 30%. The genotoxic assessment also revealed acceptable values of primary DNA damage for the developed antibacterial paints. In general, the selected methodologies presented good potential to be applied in the validation of both efficacy and safety of the antimicrobial paints, aiming to be applied in real scenarios.

Longitudinal Imaging of the Skull Base Synchondroses Demonstrate Prevention of a Premature Ossification After Recifercept Treatment in Mouse Model of Achondroplasia.

Achondroplasia is the most common form of short-limb dwarfism. In this disorder, endochondral ossification is impaired due to gain-of-function mutation in the Fibroblast Growth Factor Receptor 3 (FGFR3) gene. In addition to short limbs, cranial base bones are also affected leading to shortening of the skull base and to serious neurological complications associated with foramen magnum stenosis. These complications are thought to be due to the delay or premature arrest of skull base growth, caused by an accelerated ossification of the sphenooccipital (SOS) and the intraoccipital (IOS) synchondroses. Skull synchondroses consist of two opposite growth plates sharing a common reserve zone of chondrocytes. In this study, we first characterized the skull base synchondroses ossification in a mouse model of achondroplasia carrying the human G380R mutation (Fgfr3 ach/+ ). We then addressed whether Recifercept, a soluble FGFR3, could prevent premature closure of these synchondroses. Postnatal radiological observations revealed the presence of bony bridge structures in one or more synchondroses in Fgfr3 ach/+ mice as early as postnatal day 3 in the most severe cases. The presence of early ossification correlated with the severity of the disease as it was associated with an arrest of the cranial base bone growth. Histological analyses indicated changes in the synchondroses structure and matrix proteoglycan contents confirming a process of ossification. Treatment of Fgfr3 ach/+ mice with Recifercept compared with vehicle prevented premature synchondrosis ossification and the transition to bone, resulting in improved skull shape and cranium ratio. Given the impact of Recifercept on synchondrosis inactivation, it is possible that it could prevent one of the most severe complication of achondroplasia if used early enough during bone development. These data support the clinical development of Recifercept for achondroplasia, and suggests that early treatment may be required to best address impaired endochondral bone growth. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Non-Formaldehyde, Bio-Based Adhesives for Use in Wood-Based Panel Manufacturing Industry-A Review.

There is a strong need to develop and implement appropriate alternatives to replace formaldehyde-based adhesive systems, such as phenol-formaldehyde, in the industry of wood-based panels (WBPs). This is due to the toxicity and volatility of formaldehyde and restrictions on its use associated with some formaldehyde-based adhesives. Additionally, the current pressure to reduce the dependence on polymeric materials, including adhesives, from petrochemical-based sources has led to increased interest in bio-based adhesives, which, in some cases, already provide acceptable properties to the end-product. Among the potential raw materials for good-quality, renewable-based adhesive formulations, this paper highlights tannins, lignin, and protein sources. However, regarding renewable sources, specific features must be considered, such as their lower reactivity than certain petrochemical-based sources and, therefore, higher production costs, resource availability issues, and the need for toxicological investigations on alternative systems, to compare them to conventional systems. As a result, further research is highly encouraged to develop viable formaldehyde-free adhesive systems based on renewable sources, either at the technical or economical level. Moreover, herein, we also showcase the present market of WBPs, highlighting the obstacles that the alternative and new bio-based adhesives must overcome.

Non-Destructive Measurement of the Internal Quality of Citrus Fruits Using a Portable NIR Device.

The citrus industry has grown exponentially as a result of increasing demand on its consumption, giving it high standing among other fruit crops. Therefore, the citrus sector seeks rapid, easy, and non-destructive approaches to evaluate in real time and in situ the external and internal changes in physical and nutritional quality at any stage of fruit development or storage. In particular, vitamin C is among the most important micronutrients for consumers, but its measurement relies on laborious analytical methodologies. In this study, a portable near infrared spectroscopy (NIRS) sensor was used in combination with chemometrics to develop robust and accurate models to study the ripeness of several citrus fruits (oranges, lemons, clementines, tangerines, and Tahiti limes) and their vitamin C content. Ascorbic acid, dehydroascorbic acid, and total vitamin C were determined by HILIC-HPLC-UV, while soluble solids and total acidity were evaluated by standard analytical procedures. Partial least squares regression (PLSR) was used to build regression models which revealed suitable performance regarding the prediction of quality and ripeness parameters in all tested fruits. Models for ascorbic acid, dehydroascorbic acid, total vitamin C, soluble solids, total acidity, and juiciness showed Rcv2 = 0.77-0.87, Rcv2 = 0.29-0.79, Rcv2 = 0.77-0.86, Rcv2 = 0.75-0.97, Rcv2 = 0.24-0.92, and Rcv2 = 0.38-0.75, respectively. Prediction models of oranges and Tahiti limes showed good to excellent performance regarding all tested conditions. The resulting models confirmed that NIRS technology is a time- and cost-effective approach for predicting citrus fruit quality, which can easily be used by the various stakeholders from the citrus industry.

Three-dimensional kinematic analysis of upper limb movements between individuals with and without subacromial shoulder pain exploring the statistical parametric mapping.

Subacromial shoulder pain (SSP) accounts for 44-65% of all cases of shoulder pain. Kinematic alterations in the upper limbs have been observed in individuals with SSP, although there is no consensus on such alterations in the literature. Therefore, the present study aimed to compare the three-dimensional kinematics of the scapula, trunk, and arm during shoulder flexion-extension and abduction-adduction movements in individuals with SSP and a control group using statistical parametric mapping (SPM). We evaluated 117 participants [61 with SSP and 56 in the control group (CG)]. The three-dimensional kinematic analysis was performed starting from arm extension/adduction (0%), moving to flexion/abduction, and ending returning to extension/adduction, respectively (100%) in both groups. SSP group flexed more their trunk (0-100%, p < 0.001) and rotated scapula internally (0-20%, p < 0.001 and 75-100%, p < 0.001); rotated upwards (17-32%, p < 0.005 and 58-87%, p < 0.003) and posteriorly tilted (28-79%,p < 0.001 and 81-95%,p < 0.006) less than CG group during arm abduction-adduction. Through arm flexion-extension, the SSP group flexed (38-82% p < 0.009) less their trunk, rotated upwards (5-10% p = 0.021) less their scapula, and posteriorly tilted scapula (0-100% p < 0.001) more than CG. Combining conventional variables used to describe motion in individuals with SSP, such as minimum and maximum values, range of motion, and results provided by SPM can furnish a detailed description of the compensations and limitations of the patient, enabling a better understanding of the function of the scapular girdle as well as improvements in the evaluation process and clinical decision making.