PA Model Research Articles

The EU’s longer arm abroad: the role of EU Delegations in crisis management

ABSTRACT Since the establishment of the EEAS as the EU’s diplomatic service and the transformation of the EU’s representation abroad into EU Delegations, the EU has been a pioneer in multilateral diplomacy and contributed to development in its wider neighbourhood. These bodies made a significant contribution to widening the EU’s diplomatic network and strengthening its position in foreign policy and external relations. However, EU Delegations play a minimal role in the EU’s crisis management efforts despite their presence on the ground and their useful recourses, which could, in fact, provide crucial assets to EU-led missions. While the EU has shown successes in diplomacy, its Delegations face the problems of multiple principals and non-exclusive delegation which risk undermining the EU’s overall capacities as a global actor. This article applies the PA model to illustrate these dual problems in the cases of the CSDP missions conducted in Mali and Ukraine.

Identification and validation of plasma AGRN as a novel diagnostic biomarker of hepatitis B Virus-related chronic hepatitis and liver fibrosis/cirrhosis.

The aim of this study was to find novel biomarkers and develop a non-invasive, effective diagnostic model for hepatitis B Virus-related chronic hepatitis and liver fibrosis/cirrhosis. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to assess the expression of differentially expressed genes (AGRN, JAG1, CCL5, ID3, CCND1, and CAPN2) in peripheral blood mononuclear cells (PBMCs) from healthy subjects, chronic hepatitis B (CHB), and liver fibrosis/cirrhosis (LF/LC) patients. The molecular mechanisms underlying AGRN-regulated CHB were further explored and verified in LX2 cells, in which small interfering RNA (siRNA) was used to block AGRN gene expression. Finally, enzyme-linked Immunosorbent Assay (ELISA) was used to measure AGRN protein expression in 100 healthy volunteers, 100 CHB patients, and 100 LF/LC patients, and the efficacy of the diagnostic model was assessed by the Area Under the Curve (AUC). AGRN mRNA displayed a steady rise in the PBMCs of normal, CHB, and LF/LC patients. Besides, AGRN expression was markedly elevated in activated LX2 cells, whereas the expression of COL1 and α-SMA decreased when AGRN was inhibited using siRNA. In addition, downregulation of AGRN can reduce the gene expression of β-catenin and c-MYC while upregulating the expression of GSK-3β. Furthermore, PLT and AGRN were used to develop a non-invasive diagnostic model (PA). To identify CHB patients from healthy subjects, the AUC of the PA model was 0.951, with a sensitivity of 87.0% and a specificity of 91.0%. The AUC of the PA model was 0.922 with a sensitivity of 82.0% and a specificity of 90.0% when differentiating between LF/LC and CHB patients. The current study indicated that AGRN could be a potential plasma biomarker and the established PA model could improve the diagnostic accuracy for HBV-related liver diseases.

The mitochondrial carrier homolog 2 is involved in down-regulation of influenza A virus replication.

The mitochondrial carrier homolog 2 (MTCH2) is a mitochondrial outer membrane protein regulating mitochondrial metabolism and functions in lipid homeostasis and apoptosis. Experimental data on the interaction of MTCH2 with viral proteins in virus-infected cells are very limited. Here, the interaction of MTCH2 with PA subunit of influenza A virus RdRp and its effects on viral replication was investigated. The human MTCH2 protein was identified as the influenza A virus PA-related cellular factor with the Y2H assay. The interaction between GST.MTCH2 and PA protein co-expressed in transfected HEK293 cells was evaluated by GST-pull down. The effect of MTCH2 on virus replication was determined by quantification of viral transcript and/or viral proteins in the cells transfected with MTCH2-encoding plasmid or MTCH2-siRNA. An interaction model of MTCH2 and PA was predicted with protein modeling/docking algorithms. It was observed that PA and GST.MTCH2 proteins expressed in HEK293 cells were co-precipitated by glutathione-agarose beads. The influenza A virus replication was stimulated in HeLa cells whose MTCH2 expression was suppressed with specific siRNA, whereas the increase of MTCH2 in transiently transfected HEK293 cells inhibited viral RdRp activity. The results of a Y2H assay and protein-protein docking analysis suggested that the amino terminal part of the viral PA (nPA) can bind to the cytoplasmic domain comprising amino acid residues 253 to 282 of the MTCH2. It is suggested that the host mitochondrial MTCH2 protein is probably involved in the interaction with the viral polymerase protein PA to cause negative regulatory effect on influenza A virus replication in infected cells.

Application of machine learning methods in the analysis of interface bonding strength for overmolded hybrid thermoset‐thermoplastic composites

AbstractThe focus of this study is to apply finite element method (FEM) and machine learning methods to investigate the interfacial bonding strength of continuous fiber reinforced thermoset composite (TSC)‐thermoplastic structures manufactured through co‐curing and overmolding processes, with polyamide 6 (PA 6) as the thermoplastic material. A model for interfacial healing degree in TSC‐PA 6 structures was developed. Then, FEM was employed to study the influence of various injection overmolding process parameters on the interfacial bonding strength of TSC‐PA 6 structures. The results show that there is a strong correlation between the degree of interface healing and the bonding strength. Subsequently, six machine learning methods were employed to correlate interfacial healing degree with diverse injection molding process parameters. Simulation data were utilized for training, calibration, and validation of the six machine learning models. Based on the results of simulation and machine learning predictions, a quantitative analysis of the significance of injection molding process parameters on healing degree was conducted. These parameters are ranked in descending order of importance as follows: insert temperature, melt temperature, and injection rate.Highlights The interfacial healing degree model of PA 6 was established and validated through the integration FEM and experiment. Six machine learning models were built to predict the interfacial healing degree. Grad boosting performed best in predicting the interfacial healing degree. Insert temperature had the greatest impact on the interface healing degree.

Discussion on Informatization Teaching Design and Practice of English Course for Higher Vocational Hotel Service Majors in the Internet Era

Abstract This study explores the design and practice of informatization teaching in English for senior hospitality service majors, based on the ARCS model, and optimizes the teaching process through the Analysis of learning situation and the design of teaching practice sessions. The study adopts the classroom attention model (PA model) to analyze students’ behaviors with multivariate behavioral models and predicts students’ English scores based on the NB algorithm. The experimental results show that there is a significant difference between the reform class and the regular class in terms of the total scores of the basic English post-test, and the speaking, Listening and reading scores of the reform class are significantly higher, where the value of the full score significance (two-tailed) is 0.022. In addition, a cluster analysis of 400 students was conducted, and the correlation between students’ attention and their scores was explored. The Analysis of the teaching model showed that students were satisfied with the blended teaching, especially in “overall design and effectiveness” and “choosing the reformed teaching course again”.

AGING AND WELL-BEING: TESTING MINDFULNESS AS A MEDIATOR AND RESILIENCE AS A MODERATOR IN A NIGERIAN SAMPLE

Abstract The mediating role of mindfulness on the relationship between age and affect (both positive and negative) has been established in Western samples. However, these associations have not been well considered within additional cultural contexts. The present study examined whether mindfulness mediates the relationship between increased age and both positive (PA) and negative (NA) affect. We also took an exploratory approach to assess the strength and direction of the age-affect relationship as a function of resilience. Participants were 242 (95 women, age range = 18-75 years, Mage = 41.79; SDage = 13.58) adults, affiliated with the University of Nigeria-Nsukka, who completed the Positive and Negative Affect Scale, Brief Resilience Scale, and the Mindful Attention Awareness Scale through Qualtrics. Separate moderated-mediation analyses were conducted for PA and NA. For the PA model, the only significant association was between age and mindfulness, with higher age predicting increased self-reported mindfulness. For the NA model, higher self-reported mindfulness predicted lower levels of NA. When NA was simultaneously regressed on age and mindfulness, the direct effect between age and NA was non-significant, but the indirect effect of age on NA through mindfulness was significant, suggesting that the association between age and negative affect was mediated by mindfulness. Resilience did not provide a significant moderating influence in the PA and NA models. The present findings suggest that older adults may experience diminished levels of negative affect due to an increased capacity for mindfulness. Hence, mindfulness-based interventions may be helpful in improving the well-being of older populations.

Pathologies in satisfaction classes

We study subsets of countable recursively saturated models of PA which can be defined using pathologies in satisfaction classes. More precisely, we characterize those subsets X such that there is a satisfaction class S where S behaves correctly on an idempotent disjunction of length c if and only if c∈X. We generalize this result to characterize several types of pathologies including double negations, blocks of extraneous quantifiers, and binary disjunctions and conjunctions. We find a surprising relationship between the cuts which can be defined in this way and arithmetic saturation: namely, a countable nonstandard model is arithmetically saturated if and only if every cut can be the “idempotent disjunctively correct cut” in some satisfaction class. We describe the relationship between types of pathologies and the closure properties of the cuts defined by these pathologies.

CS-GA-XGBoost-Based Model for a Radio-Frequency Power Amplifier under Different Temperatures.

Machine learning methods, such as support vector regression (SVR) and gradient boosting, have been introduced into the modeling of power amplifiers and achieved good results. Among various machine learning algorithms, XGBoost has been proven to obtain high-precision models faster with specific parameters. Hyperparameters have a significant impact on the model performance. A traditional grid search for hyperparameters is time-consuming and labor-intensive and may not find the optimal parameters. To solve the problem of parameter searching, improve modeling accuracy, and accelerate modeling speed, this paper proposes a PA modeling method based on CS-GA-XGBoost. The cuckoo search (CS)-genetic algorithm (GA) integrates GA's crossover operator into CS, making full use of the strong global search ability of CS and the fast rate of convergence of GA so that the improved CS-GA can expand the size of the bird nest population and reduce the scope of the search, with a better optimization ability and faster rate of convergence. This paper validates the effectiveness of the proposed modeling method by using measured input and output data of 2.5-GHz-GaN class-E PA under different temperatures (-40 °C, 25 °C, and 125 °C) as examples. The experimental results show that compared to XGBoost, GA-XGBoost, and CS-XGBoost, the proposed CS-GA-XGBoost can improve the modeling accuracy by one order of magnitude or more and shorten the modeling time by one order of magnitude or more. In addition, compared with classic machine learning algorithms, including gradient boosting, random forest, and SVR, the proposed CS-GA-XGBoost can improve modeling accuracy by three orders of magnitude or more and shorten modeling time by two orders of magnitude, demonstrating the superiority of the algorithm in terms of modeling accuracy and speed. The CS-GA-XGBoost modeling method is expected to be introduced into the modeling of other devices/circuits in the radio-frequency/microwave field and achieve good results.

Stable and Efficient Animal Models of the Peritoneal Adhesion

AbstractPeritoneal adhesion (PA) is a widespread complication of surgery arising from physiological problems. Various therapies and medicines for anti‐PA have been studied but lack unified and standard PA models. Various experimental techniques are applied to establish and investigate reliable models for inducing PA in pigs and rats. This study utilizes four scoring systems to evaluate the severity of adhesions. In pigs, U‐shape incision, L‐shape incision, ileum resection, cecum abrasion & peritoneum abrasion, and cecum purse‐string & peritoneum abrasion models are established, to assess the impact of laparotomy incision and double opposed wound on adhesion formation. For rat models, the exposed double opposed wound models are created, including peritoneum resection & cecum abrasion, peritoneum abrasion & cecum abrasion, two knots & cecum abrasion, and four knots & cecum abrasion models, to explore the influence of double opposed wounds and foreign materials. The findings suggest that the peritoneum resection & cecum abrasion model is a reliable and reproducible PA model, as it exhibits a high adhesion rate and consistent adhesion scores across all evaluation approaches. The utilization of the double‐opposed wound model and evaluation systems contributes to more scientifically rigorous and efficient preclinical evaluations of various anti‐adhesion agents.

Computational fluid dynamics simulations of mitral paravalvular leaks in the human heart

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Warsaw University of Technology - BIOTECHMED-3 project under the program Excellence Initiative: Research University. Background Presence of paravalvular leaks (PVL) can lead to hemolysis and high shear stress that affects erythrocytes passing through PVL channels may be the main reason behind this pathology. In vitro, shear stress forces above 300 Pa cause erythrocyte destruction. Distribution of shear stress can currently be precisely determined with computational fluid dynamics (CFD). CFD is a numerical modelling method based on solving equations of differential balance of mass, momentum and energy for a small section of fluid known as a computational cell. Purpose To investigate the magnitude of shear stress forces that affect erythrocytes in PVL channels and define properties of PVL channels that increase the likelihood of hemolysis. Methods Models of left-sided heart chambers with artificial mitral valves and PVLs were created based on cardiac computed tomography data from subjects with PVLs. Computational fluid dynamics principles were applied to create patterns of blood flow through PVL channels. 4 channels with cross-sectional areas (CSA) of 26.2 mm2 (model I), 15.7 mm2 (model 2), 20.4 mm2 (model 3) and 32 mm2 (model 4) were examined. Length of PVL channels was 6.5, 9.5, 7.3 and 3.25 mm respectively. In models I,III and IV the PVL channel was located anteriorly around the mitral annulus, whereas in model II a posterior location was described. Blood flow was simulated using a commercial CFD software (ANSYS Fluent 2020R1). Simulations were performed for heart rate of 60 beats per minute. The following variables were examined regarding blood flow through PVL channels: wall shear stress, shear stress in fluid, volume of PVL channels in which shear stress exceeded 300 Pa and duration of exposure of red blood cells to shear stress above 300 Pa. Obtained values were compared with lactate dehydrogenase (LDH) activities in subjects whose cardiac CTs were used to create PVL models. One of the models of the left ventricle is presented in picture 1. Studied PVL channels are presented in picture 2. Results In all models shear stress value of 300 Pa was exceeded. Maximal wall shear stress and maximal shear stress in fluid values were not related to CSA of the PVL channel. Lowest values of all examined variables were obtained for model 2, which had the longest PVL channel and a posterior location. The lowest LDH activity was noted in model with the lowest volume of the PVL channel with shear stress above 300 Pa (model 2) and the highest LDH activity in model with both the highest volume of the PVL channel with shear stress above 300 Pa and longest exposure to shear stress exceeding 300 Pa (model III). Conclusions Presence of PVLs is always accompanied by some degree of hemolysis. Shear stress values in PVL channels are not related to CSA of these channels. Volume of PVL channels in which shear stress exceeds 300 Pa and duration of exposure of erythrocytes to shear stress above 300 Pa may influence the severity of hemolysis.

Effect of varying shear rates at different resting times on the rheology of 3D printable concrete

3D printing offers a paradigm shift in the construction industry. The material undergoes different stages like mixing, pumping, extruding, and printing with disparate shearing patterns and the effect of shear rates must be brought into consideration. The rheological properties of 3D printable concrete with varying shear rates at different resting times were studied. The designed mix has an ultra-high compressive strength of 110 MPa. Different hystresis curves with shear rates of 0–25 s−1 (P1) and 0–50 s−1 (P2) are studied. The tests were conducted at 10 min intervals up to 30 min resting time. The experimental down flow curves are further analyzed using the Bingham model, the modified Bingham model, and the Herschel-Bulkley model. It is observed that the rheological properties of 3D printable concrete are highly dependent on the resting time, and the applied shear rates and demand judicious selection of rheological models to predict yield stress and plastic viscosity. The comparison between experimental and analytical models indicates better predictability with the modified Bingham and Herschel- Bulkley model. The yield stress values for the modified Bingham model were found to be varying from 95 Pa to 178 Pa and Herschel-Bulkley model from 130 Pa to 177 Pa for P1 and P2, respectively.

Psychological Autopsy Structured on Individual Cases: Methodological Considerations for A New Protocol

Psychological autopsy is an investigative procedure used in cases of "equivocal death" (a situation in which the cause of death is uncertain); it originated in the early 1960s and has since spread to the United States, Europe, and especially Cuba. The initial MAP (Modelo de Autopsia Psicologica) protocol, developed specifically in Cuba, has since evolved into the more current MAPI (Modelo de Autopsia Psicologica Integrado). It is characterized by the use of a retrospective analysis of the deceased's life, with emphasis on risk factors, mental health history and interpersonal relationships. The Psychological Autopsy is considered one of the most valuable suicide research tools. Information is collected and included in 16 categories (Shneidman) from multiple sources through structured interviews. Despite its widespread use, the original PA model has several methodological problems that can be overcome through a revision of the protocol from a specialized perspective tailored to each case. The innovative PASIC (Psychological Autopsy Structured on Individual Cases) protocol aims to adapt the psychological autopsy protocol to each case, making it unique and personalized. PASIC, therefore, is based on principles of individuality and its management by a single specialized professional figure. This makes it more effective in identifying which subjects to interview and what type of interview to use. The professional will be able to select the appropriate measures to obtain reliable and effective sources of information. Through a review of the origin and development of the psychological autopsy, this article aims to describe the structural and operational features of the new PASIC method and its advantages over the previous protocols.

EXPLORING CULTURALLY RESPONSIVE PHYSICAL ACTIVITY AS A RECRUITMENT AND RETENTION TOOL FOR AFRICAN AMERICAN WOMEN

Abstract Physical activity (PA) is associated with lower cognitive decline and incident dementia for older adults. Yet, PA data (interventions) on older African American (AA) women, a population disproportionately affected by premature aging, are lacking. This limitation reduces the efficacy of PA to reduce cognitive decline, particularly for people of color and more so women of color whose race and gender create unique spaces for PA engagement. Although AA women desire to engage in PA, they face social, structural, and behavioral barriers to PA, challenges that parallel those faced in preventing premature aging (Li et al., 2018). Extant literature on AA women’s PA investigates social determinants of health (SDoH) and calls for more attention as to how these factors intertwine to shape these women’s PA over time (Fleury & Lee, 2006). Culturally responsive physical activity programs (CRPA) offer a framework for addressing these factors synergistically to promote PA in a way that is desirable to AA women. Specifically, CRPA provides a strength– based approach to explicate the ways PA can redress social, structural, and behavioral causes of cognitive decline and barriers to PA (cf., Joseph et al., 2020). The purpose of this poster is to explore the benefits of CRPA interventions on preventing cognitive decline. Implications include refining current models of PA as premature aging prevention measures by increasing our knowledge of the sociocultural factors shaping AA women’s aging and PA behavior and providing greater insight into the mechanisms for recruiting and retaining AA women into PA- based cognitive decline interventions.

Weight Status Among Minnesota Hispanic or Latino/a Youth: An Exploration of Protective Factors.

Pediatric obesity disproportionately impacts Hispanic or Latino/a adolescents. Culturally appropriate family-based behavioral initiatives to improve weight status are warranted. The purpose of this research was to determine prevalence rates and identify protective factors associated with having overweight/obesity (body mass index ≥ 85th percentile) to inform Hispanic or Latino/a-targeted behavioral intervention development. Secondary data analyses of a population-based statewide survey. Minnesota public high schools. Male (n = 2,644) and female (n = 2,798) Hispanic or Latino/a 9th and 11th graders (N = 5,442). Obesity-related behaviors (meeting fruit and vegetable [F&V] and physical activity [PA] recommendations), family caring, family country/region of origin, and weight status. Stepwise logistic regression models (F&V, PA), stratified by biological sex, were used to identify protective factors of overweight/obesity. The overall prevalence of meeting F&V and PA recommendations was 11.0% and 11.8%, respectively. Meeting F&V recommendations was not protective against overweight/obesity in either sex. Yet, males and females who met PA recommendations had significantly lower odds of having overweight/obesity (p < .05). In F&V and PA models, family caring was protective against overweight/obesity in females (p < .05), and family country/region of origin was protective against overweight/obesity in both sexes (p < .05). Findings illustrate a need for obesity prevention initiatives for Hispanic or Latino/a youth. More research is needed to understand the protective nature of family caring and country/region of origin.

Clinical and biochemical predictors and predictive model of primary aldosteronism.

BackgroundPrimary aldosteronism (PA) is the most common cause of secondary hypertension. The diagnosis of PA currently requires multiple complicated measures. The aims of this study were to identify easy-to-obtain clinical and biochemical predictors, and to create predictive model to facilitate the identification of a patient at high risk of having PA.Materials and methodsThis 2-year retrospective cohort study was conducted at a tertiary care medical center. A total of 305 patients who had been tested for plasma aldosterone concentration (PAC) and plasma renin activity (PRA) were identified. Patients with incomplete results of PAC and PRA and those who had an established diagnosis of Cushing’s syndrome or pheochromocytoma were excluded. Logistic regression analysis was used to identify significant predictors and to create predictive model of PA.ResultsPA was diagnosed in 128 of the patients (41.96%). Significant predictive factors for PA were age >60 years (OR 2.12, p = 0.045), female (OR 1.65, p<0.001), smoking (OR 2.79, p<0.001), coronary artery disease (OR 2.29, p<0.001), obstructive sleep apnea (OR 1.50, p = 0.017), systolic blood pressure >160 mmHg (OR 1.15, P<0.001), serum potassium <3 mEq/L (OR 3.72, p = 0.030), fasting blood glucose >126 mg/dL (OR 0.48, p = 0.001) and estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 (OR 1.79, p = 0.001). Predictive model was created with a total score ranged from 0 to 42. A score above 7.5 indicated a higher probability of having PA with a sensitivity of 72% and a specificity of 70%. The diagnostic performance of the predictive model based on area under the curve was 71%.ConclusionsThe clinical and biochemical predictive factors including predictive model identified in this study can be employed as an additional tool to help identify patients at risk of having PA and could help reduce the number of screening and confirmation tests required for PA.

Behavioral modeling and digital predistortion of RF power amplifiers based on time-delay kernel ridge regression

This paper, investigates and presents the behavioral modeling and digital pre-distortion (DPD) of radio frequency power amplifiers (RFPAs) using a time-delay kernel ridge regression (KRR) algorithm. The KRR is an advanced machine learning algorithm that can be effectively used for modeling the baseband characteristics of the RFPA considering both the effects of memory and transistor non-linearity. Compared to the traditional artificial neural network (ANN) based approach which is computationally intensive, the proposed approach using KRR with radial basis kernel function and min-max normalization method, extracts the PA behavioral and DPD model in a short time and yield consistently better results. The performance of the proposed approach in extracting PA and DPD model is demonstrated experimentally on a GaN based class AB power amplifier. The experimental results illustrates that, when compared to ANN based model, the proposed approach yields more accurate PA and DPD models, with an improvement in modeling performance by 2 dB in terms of normalized mean square error (NMSE). In addition, compared to the ANN based approach, the DPD model developed using the proposed approach exhibit improved linearization performance in suppressing spectral regrowth due to PA non-linearity.

Psl-Dependent Cooperation Contributes to Drug Resistance of Pseudomonas aeruginosa in Dual-Species Biofilms with Acinetobacter baumannii.

Co-infection of Pseudomonas aeruginosa (Pa) and Acinetobacter baumannii (Ab) is frequently observed in intensive care unit (ICU) patients but difficult to eliminate. Current clinical practice based on microbial population characterization and single-species-based antibiotic resistance profiling has ignored the potential interspecies interactions, which might lead to novel drug-resistance phenotypes. Here, we investigated the impacts of interspecies interactions on antibiotic therapies by establishing a Pa and Ab dual-species biofilm model. Our data showed that antibiotic exposure would reshape the community compositions of dual-species biofilms, and those of the extracellular polymeric substance (EPS) matrix of Pa, Psl exopolysaccharide in particular, promoted its interactions with Ab against imipenem stress. We further found other EPS structural fiber-eDNA contributed to the Psl-dependent dual-species biofilm stability under antibiotic treatment. Thus, targeting the EPS structural fibers such as Psl and extracellular DNA (eDNA) is a potent strategy for controlling polymicrobial biofilm related infections.

The Normative Study of Acoustic and Aerodynamic Characteristics of Voice among Healthy Adult Turkish Speaker Population.

Phonatory Aerodynamic System (PAS Model 6600) is an evaluation instrument that assesses the effectiveness of surgical interventions, treatments, and therapy for voice disorders. It can be used for the assessment of voice disorders by supporting other perceptual and instrumental methods. It is important to establish normative data, because the use of appropriate norms is necessary for diagnostic and descriptive accuracy. Therefore, this study is aimed primarily at establishing adult normative databases for phonatory aerodynamic measures obtained with the KayPENTAX PAS Model 6600 among healthy adult Turkish speakers and then examining the effect of age, gender, and age-gender interaction variables on these measures. The contribution of the study is considered so important since it will generate normative data for all measurements—except the mean pitch—by the five protocols of PAS for the first time. Two hundred and six healthy Turkish speakers with normal voice (106 women and 100 men) were included in the study and stratified into three age groups. Forty-five phonatory aerodynamic measures across five PAS protocols (vital capacity, maximum sustained phonation, comfortable sustained phonation, variation in sound pressure level, and voicing efficiency) were collected. Age, gender, and age-gender interaction variables were analyzed for 45 PAS parameters. Significant gender and age effect was found for 30 and 19 variables, respectively. Gender-age interaction together was observed for only 6 parameters. Significant differences were not found for the remaining 10 parameters. Significant age and gender effects were observed for 35 phonatory and aerodynamic measures which are essential part of the objective clinical assessment of voice. Consequently, normative data used as reference in voice assessment should be generated according to age and gender differences.

Physical activity dimensions after stroke: patterns and relation with lower limb motor function

BackgroundStroke survivors show deteriorated physical functioning and physical activity levels. Physical activity levels of stroke survivors are generally low. It is increasingly recognized that physical activity is a multidimensional construct that cannot be captured in a single outcome. In-depth insight into multidimensional physical activity patterns may guide the development and timing of targeted rehabilitation interventions. This longitudinal cohort study explored how multidimensional physical activity outcomes develop during recovery in the subacute phase after stroke and if changes in physical activity were correlated to recovery of lower limb motor function.MethodsPatients were recruited during inpatient rehabilitation. At 3, 12, and 26 weeks post-onset, motor function was measured by the Fugl-Meyer Lower Extremity Assessment (FMA-LE). Physical activity was measured with the Activ8 accelerometer in multiple outcomes: counts per minute during walking (CPMwalking; a measure of Intensity), number of active bouts (Frequency), mean length of active bouts (Distribution) and % of waking time in upright positions (Duration). Generalized estimating equations (GEE) were used to study changes in physical activity over time and the relation with the change in lower limb motor recovery.ResultsThirty-nine patients (age 56 ± 9, 77% male, 89% ischemic stroke) were included. GEE models showed a significant main effect of time for PA Intensity (+ 13%, p = 0.007) and Duration (+ 64%, p = 0.012) between 3 and 12 weeks. Motor function did not show a significant effect in all PA models across the 3 timepoints (p > 0.020). A significant interaction effect of time × motor function was observed (p < 0.001).ConclusionsPatterns of PA recovery depend on the PA dimensions: PA Intensity and Duration increased mostly between 3 and 12 weeks post-stroke, whereas Frequency and Distribution did not show substantial changes. Further, no strong associations with motor recovery and high inter-individual variability were documented, which underlies the need to consider factors specific to the disease, the individual patient and the context.

LGG-09. SENOLYTIC AGENT NAVITOCLAX TARGETS VINBLASTINE- AND MAPK INHIBITORS-INDUCED SENESCENT TUMOUR CELLS IN PAEDIATRIC LOW GRADE GLIOMAS

Pilocytic astrocytoma (PA, WHO grade I), the most common paediatric brain tumour, is characterized by constitutive activation of the MAPK pathway. PA tumours show a slow growth, without tendency to progress to high-grade malignancies. However, a significant group of patients for whom a total resection is not feasible require additional therapy. The typical proliferative index of a PA, measured by Ki-67 staining, is 1–2%, whereas a large part of the tumour is Ki-67 negative and expresses markers of oncogene-induced senescence (OIS) such as SA-β-Gal positivity and the cell cycle inhibitors p16INK4a (CDKN2A) and p21Cip1 (CDKN1A). Conventional treatments (i.e. chemotherapy) tend to target only proliferative cells and the effect of new molecularly targeted therapies (e.g., MAPK pathway inhibitors) on senescent cells remains unclear. Here, we discuss the opportunities to combine these therapies with new compounds targeting the senescent cells, referred to as senolytics, using three different PA models. (1) Ex vivo culture of human PA tumours (2) Two cell lines: the DKFZ-BT66 PA human cell line, carrying the oncogenic driver KIAA1549:BRAF-fusion, used as a model of OIS; and the proliferative BT40 cell line harbouring the BRAFV600E mutation; (3) In vivo xenograft model induced by orthotopic transplantation of BT40 cells. We have previously shown that OIS cells exhibit an increased sensitivity to senolytic compounds, such as navitoclax, a clinically approved BCL2/XL inhibitor, relative to proliferative controls (Buhl et al, Clin Cancer Res. 2019). Our current research demonstrates that treatments with low doses of chemotherapy (e.g., vinblastine) or MAPK inhibitors (e.g., dabrafenib or trametinib) triggers a therapy-induced senescence response in proliferative cells (e.g., abolished proliferation, SA-β-Gal positivity, SASP production), making these senescent cells sensitive to senolytic compounds, including navitoclax. Together, our research provides a strong rationale supporting the combined use of senolytics with current conventional and targeted therapies against human PA.