Search

BACKGROUND: Mobility is human body movement in all its forms, including bed-to-chair transfer, walking, daily tasks, participating in work and social functions, exercising, and using public transport. The mobility of people living with COPD is affected negatively by the disease symptoms. However, limited data are available on the life-space mobility in people with COPD on long-term oxygen therapy (LTOT). This study aimed to explore the life-space mobility in subjects with COPD on LTOT and verify whether life-space mobility is associated with comorbidities and symptoms, activity in daily life, exercise capacity performance, and quality of life. METHODS: This cross-sectional study enrolled 61 subjects with COPD on LTOT (73.0 ± 8.8 y, FEV1 41.7 ± 16.0% predicted, on LTOT for 2.8 ± 3.3 y). Life-space mobility (Life-Space Assessment), LTOT usage time, comorbidities (Charlson comorbidity index), need for support from a caregiver, exercise capacity (6-min step test), dyspnea (modified Medical Research Council scale), activities of daily living (ADLs, Katz scale), and health-related quality of life (EuroQol 5-Dimension Questionnaire) were assessed. RESULTS: Mobility restriction was identified in 90% of participants. Life-space mobility was negatively associated with the number of comorbidities (rs = -0.31, P = .02), dyspnea symptom (rs = -0.60, P < .001), and positively associated with basic ADLs performance (rs = 0.59, P < .001) and exercise capacity (rs = 0.49, P < .001). Dyspnea and exercise capacity were independent predictors of vital space mobility. CONCLUSIONS: Subjects with COPD on LTOT had limited life-space mobility. Interventions to reduce dyspnea and improve exercise capacity should be prioritized to increase this population's domestic and community mobility. [ABSTRACT FROM AUTHOR]

Background: As the scientific community grapples with the increasing symptomatology stemming from COVID-19, it is becoming increasingly evident that this systemic disease extends beyond its acute respiratory manifestations. While the world was still grappling with the immediate consequences of the pandemic, such as pneumonia, pulmonary thromboembolism, and heightened cardiovascular risk, a series of questions arose concerning the long-term sequelae. The mechanisms and implications of these sequelae remain elusive. Objective: This review explores the impact of COVID-19 on lung function and underscores the significance of thorough assessment and treatment for post-COVID-19 patients, often referred to as Post-Acute Sequelae of COVID-19 (PACS). COVID-19, caused by SARS-CoV-2, exerts its primary effects on the respiratory system and can lead to chronic complications affecting various organ systems. Methods: We carried out searches in three main databases and gray literature, in English, without date restrictions. Results: Lung function assumes a pivotal role, as a substantial number of patients report persistent dyspnea and other respiratory symptoms even after recovery from the acute infection. These lingering symptoms significantly impair patients' quality of life and functional capacity. This study underscores the necessity of precise assessments of lung function, encompassing pulmonary function tests and computed tomography scans, to identify abnormalities and guide treatment strategies. Moreover, we emphasize the vital role of therapeutic interventions and multidisciplinary rehabilitation programs aimed at enhancing the quality of life for PACS patients. Final Considerations: While there exist recommendations for post-COVID-19 rehabilitation, further research is imperative to validate the effectiveness of these interventions and establish a robust evidence base. In summary, this review underscores the enduring impact of COVID-19 on lung function and underscores the importance of individualized care and ongoing research efforts to cater to the needs of post-COVID-19 patients. [ABSTRACT FROM AUTHOR]

ABSTRACT: Anatomopathological descriptions of infections caused by saprophytic algae in dogs are rare. This study reported the anatomopathological and microbiological findings suggestive of disseminated protothecosis in a dog residing in the state of Espírito Santo, Brazil. During necropsy, macroscopic alterations were observed in peripheral lymph nodes, heart, kidneys, pancreas, and lungs. Microbiological, cytological, and histopathological examinations were performed. Cytology and histopathology revealed piogranulomatous inflammation associated with sporangia and endospores, while microbiological culture suggested the growth of Prototheca spp.. These anatomopathological and microbiological findings were crucial for diagnosing and documenting the first case of disseminated Prototheca spp. compatible infection in a dog in the state of Espírito Santo, Brazil.

Abstract Porcine source attracts the biotechnological development of natural xenogeneic materials, due to the availability of collagen in soft tissues, but the use of the demineralized organic matrix of cortical bone remains little explored. This study developed a demineralized porcine cortical bone matrix and analyzed the interference of peroxidation on the composition, thermostability, porosity and swelling of the material. Fresh ribs were processed with 3%-30% hydrogen peroxide under single treatment (G1-G4) or double treatment (G5-G8), using native bone (NB) as a control. Physicochemical characterization, porosity histomorphometry and swelling evaluation were performed. There were infrared bands indicative of the prevalence of collagen and residual phosphate groups even after demineralization, mass loss events by thermogravimetry ranging from 94 to 590 °C, being more accelerated in G7 and G8, with all groups below the thermal stability of the NB, as well as similar endothermic events between treatments in differential calorimetry. Changes in lamellar bone morphology occurred in all tested groups, being more conservative in G1 and G2 and more aggressive in G7 and G8. The single treatment dilated pores and kept the matrix closer to the original, while the double treatment significantly enlarged and fused the bone canals mimicking a mesh. The permeable areas in the bone matrix were larger and the hydrophilicity was greater and more persistent for G5-G8 compared to G1-G4 and NB. Single exposure and at lower concentrations of hydrogen peroxide suggest a better modulation of the tested determinants, for the generation of collagen biomaterial applied to bone regeneration.

ABSTRACT Objectives: to assess the University Student Depression Inventory, Brazilian version (USDI-BR), construct. Methods: a methodological study carried out with a snowball probabilistic sample, consisting of 334 undergraduate and graduate students. Confirmatory factor analysis, reliability using McDonald’s omega coefficient and Cronbach’s alpha were performed. Principal component analysis was performed using the varimax rotation and oblimin rotation, using the Kaiser-Meyer-Olkin criteria, Bartlett’s test of sphericity and scree plot. Results: the USDI-BR presented an internal consistency of items of ω = 0.95 and remained with 30 items, with the addition of 1 factor (Death wish and social withdrawal), totaling 4 factors. Conclusions: the USDI-BR has evidence that points to its validity and also its internal consistency, deserving that new studies be carried out to expand the evidence of its psychometric properties.

Since the advent of deep learning (DL), the field has witnessed a continuous stream of innovations. However, the translation of these advancements into practical applications has not kept pace, particularly in safety-critical domains where artificial intelligence (AI) must meet stringent regulatory and ethical standards. This is underscored by the ongoing research in eXplainable AI (XAI) and privacy-preserving machine learning (PPML), which seek to address some limitations associated with these opaque and data-intensive models. Despite brisk research activity in both fields, little attention has been paid to their interaction. This work is the first to thoroughly investigate the effects of privacy-preserving techniques on explanations generated by common XAI methods for DL models. A detailed experimental analysis is conducted to quantify the impact of private training on the explanations provided by DL models, applied to six image datasets and five time series datasets across various domains. The analysis comprises three privacy techniques, nine XAI methods, and seven model architectures. The findings suggest non-negligible changes in explanations through the implementation of privacy measures. Apart from reporting individual effects of PPML on XAI, the paper gives clear recommendations for the choice of techniques in real applications. By unveiling the interdependencies of these pivotal technologies, this research marks an initial step toward resolving the challenges that hinder the deployment of AI in safety-critical settings.

Microplastics (MPs) pose a clear threat to aquatic organisms affecting their health. Their impact on liver homeostasis, as well as on the potential onset of nonalcoholic fatty liver disease (NAFLD), is still poorly investigated and remains almost unknown. The aim of this study was to evaluate the outcomes of subchronic exposure to polystyrene MPs (PS-MPs; 1–20 μm; 0, 25, or 250 mg/kg b.w./day) on lipid metabolism, inflammation, and oxidative balance in the liver of gilthead seabreams (Sparus aurata Linnaeus, 1758) exposed for 21 days via contaminated food. PS-MPs induced an up-regulation of mRNA levels of crucial genes associated with lipid synthesis and storage (i.e., PPARy, Srebp1, Fasn) without modifications of genes involved in lipid catabolism (i.e., PPARα, HL, Pla2) or transport and metabolism (Fabp1) in the liver. The increase of CSF1R and pro-inflammatory cytokines gene expression (i.e., TNF-α and IL-1β) was also observed in exposed fish in a dose-dependent manner. These findings were confirmed by hepatic histological evaluations reporting evidence of lipid accumulation, inflammation, and necrosis. Moreover, PS-MPs caused the impairment of the hepatic antioxidant defense system through the alteration of its enzymatic (catalase, superoxide dismutase, and glutathione reductase) and non-enzymatic (glutathione) components, resulting in the increased production of reactive oxygen species (ROS) and malondialdehyde (MDA), as biomarkers of oxidative damage. The alteration of detoxifying enzymes was inferred by the decreased Ethoxyresorufin-O-deethylase (EROD) activity and the increased activity of glutathione-S-transferase (GST) at the highest PS-MP dose. The study suggests that PS-MPs affect the liver health of gilthead seabream. The liver dysfunction and damage caused by exposure to PS-MPs result from a detrimental interplay of inflammation, oxidative damage, and antioxidant and detoxifying enzymatic systems modifications, altering the gut-liver axis homeostasis. This scenario is suggestive of the involvement of MP-induced effects in the onset and progression of hepatic lipid dysfunction in gilthead seabream.

O abastecimento de água é parte integrante da totalidade espacial. Nesse contexto, objetiva-se analisar esses sistemas de abastecimento enquanto objeto de estudo da ciência geográfica. Para alcançar esse objetivo, utilizou-se como metodologia uma pesquisa sobre a teoria do espaço geográfico de Milton Santos e sobre as concepções funcionais dos sistemas de abastecimento de água, por meio de uma perspectiva de análise dialética e sistêmica. Portanto, os resultados evidenciaram a identificação funcional dos objetos e ações que fazem parte do abastecimento de água, desde o processo de captação, até as operações de tratamento, adução, reservação e distribuição de água. Assim sendo, as categorias da totalidade espacial proporcionaram a compreensão da materialidade e dos aspectos empíricos da dinâmica geográfica dos sistemas de abastecimento de água.

Abstract Background Japanese Kawasaki disease (KD) risk scores cannot be adopted in non-Japanese patients. In North American populations a baseline coronary artery Z-score > 2 and the Son score are associated with coronary artery aneurysms (CAAs) at 4 and 8 weeks from disease onset. In European populations, the Kawanet and Kawanet-echo scores are associated with intravenous immunoglobulin resistance. This study aims to evaluate the association between KD risk scores and baseline coronary artery Z-scores with CAAs at one, two, and six months in a European population. Methods Historical cohort study of all the children diagnosed with KD in a tertiary care hospital in Milan, Italy, between 1st January 2015 and 31st May 2021. Univariate and multivariate (adjusting for age and corticosteroid therapy) logistic regression analyses were used to study the association between the risk scores, a baseline Z-score ≥ 2 and ≥ 2.5 with CAAs. Results Eighty-nine patients were diagnosed with KD at our Centre, and 12 were excluded based on the exclusion criteria. We included 77 patients, 51 (66%) males, and 26 (34%) females, with a median age at presentation of 27 months (IQR 13–46). A baseline Z-score ≥ 2 was correlated with CAAs at one and two-month follow-ups (odds ratio (OR) 10, 95% confidence interval (CI) 2–72, and OR 18, CI 3-357) but not at six-month follow-up. The Son score showed an association with one and two-month follow-up CAAs (OR 3, CI 1.3-7, and OR 3, CI 1.3-8) but not with a six-month follow-up. Conclusions Patients with a baseline Z-score ≥ 2 are at higher risk for CAAs in the long term. The Son score should be tested in larger European samples. Further studies should keep the observational periods longer than 8 weeks from KD onset.

Anomaly detection is a topic of interest in several areas, ranging from Industry 4.0 to Energy Management, Smart Agriculture, Cybersecurity, and Bioinformatics. In a wide sense, detecting anomalies implies finding samples generated within a process that differs from its standard data generation mechanisms. Identifying these samples is extremely important for a variety of reasons, depending on the specific application and scenario, ranging from the minimization of production costs to maintaining the required safety standards. As such, the increasing availability of wide networks of sensors that yield large amounts of data characterizing the processes under observation allowed the large adoption of deep learning techniques, which proved worthy of attention due to their capability of identifying anomalies with large precision, accuracy and reproducibility. Consequently, there is an extensive need to consolidate research results to provide a common framework to understand the topic and ensure a common foundation to establish future research trends. To respond to this need, this work systematically reviews the state of the art of anomaly detection in Industry 4.0, evaluating gaps in the current knowledge and proposing future directions of interest. To pursue this objective, three main dimensions have been considered: the scenario where the anomaly detection methodologies were applied, the sensing equipment used to gather data characterizing the underlying process, and the algorithm employed to properly interpret the phenomena. The study was conducted following the PRISMA protocol, which allowed the identification of a relevant selection of papers by extracting a meaningful dataset of 78 papers of interest. The analysis highlighted the diffusion of autoencoders in several configurations and application scenarios, highlighting their effectiveness and flexibility for anomaly detection.

Silicon has beneficial effects on many crops, mainly under biotic and abiotic stresses. Silicon can affect biochemical, physiological, and photosynthetic processes and, consequently, alleviates drought stress. However, the effects of Si on potato (Solanum tuberosum L.) plants under drought stress are still unknown. The objective of this study was to evaluate the effect of Si supply on some biochemical characteristics and yield of potato tubers, either exposed or not exposed to drought stress. The experiment was conducted in pots containing 50 [dm.sup.3] of a Typic Acrortox soil (33% clay, 4% silt, and 63% sand). The treatments consisted of the absence or presence of Si application (0 and 284.4 mg [dm.sup.-3]), through soil amelioration with dolomitic lime and Ca and Mg silicate, and in the absence or presence of water deficit (-0.020 MPa and -0.050 MPa soil water potential, respectively), with eight replications. Silicon application and water deficit resulted in the greatest Si concentration in potato leaves. Proline concentrations increased under lower water availability and higher Si availability in the soil, which indicates that Si may be associated with plant osmotic adjustment. Water deficit and Si application decreased total sugars and soluble proteins concentrations in the leaves. Silicon application reduced stalk lodging and increased mean tuber weight and, consequently, tuber yield, especially in the absence of water stress.

Background/Objectives: This study investigates the development of 3D chitosan-x-cobalt ferrite scaffolds (x = 5, 7.5, and 10 wt%) with interconnected porosity for potential biomedical applications. The objective was to evaluate the effects of magnetic particle incorporation on the scaffolds’ structural, mechanical, magnetic, and biological properties, specifically focusing on their biocompatibility and antimicrobial performance. Methods: Scaffolds were synthesized using freeze-drying, while cobalt ferrite nanoparticles were produced via a pilot-scale combustion reaction. The scaffolds were characterized for their physical and chemical properties, including porosity, swelling, and mechanical strength. Hydrophilicity was assessed through contact angle measurements. Antimicrobial efficacy was evaluated using time kill kinetics and agar diffusion assays, and biocompatibility was confirmed through cytotoxicity tests. Results: The incorporation of cobalt ferrite increased magnetic responsiveness, altered porosity profiles, and influenced swelling, biodegradation, and compressive strength, with a maximum value of 87 kPa at 7.5 wt% ferrite content. The scaffolds maintained non-toxicity and demonstrated bactericidal activity. The optimal concentration for achieving a balance between structural integrity and biological performance was found at 7.5 wt% cobalt ferrite. Conclusions: These findings suggest that magnetic chitosan-cobalt ferrite scaffolds possess significant potential for use in biomedical applications, including tissue regeneration and advanced healing therapies. The incorporation of magnetic properties enhances both the structural and biological functionalities, presenting promising opportunities for innovative therapeutic approaches in reconstructive procedures.