Eficacia de los programas de desarrollo socioemocional aplicados en educación primaria: Una revisión sistemática paraguas / Effectiveness of social-emotional development programs applied in primary education: an umbrella systematic review

En la actualidad ha aumentado el desarrollo de programas de entrenamiento en habilidades socioemocionales en la infancia, debido a que se los considera como una herramienta válida para la adaptación y afrontamiento de una gran variedad de situaciones, tanto académicas como personales. Sin embargo, son escasos los estudios que aporten una visión integral de las evidencias disponibles en el contexto de educación primaria. Se presenta una revisión sistemática de tipo paraguas basada en el método PRISMA, que incluye revisiones sobre programas de desarrollo socioemocional aplicados en educación primaria, con el objetivo de sintetizar sus características y recopilar los principales resultados reportados. Se utilizaron las bases de datos: ERIC, WOS, PSYCINFO, SCOPUS y COCHRANE. Tras un proceso por pares ciegos se seleccionaron y analizaron 15 revisiones. Utilizando las herramientas AMSTAR-2 y SANRA se encontró que el 60% de los estudios secundarios presenta una calidad críticamente baja o baja. Se identificaron 39 programas reportados en revisiones de buena calidad, un 51.2% presentaron evidencias moderadas o fuertes e informaron efectos significativos principalmente en ajuste del comportamiento, competencia social y emocional y habilidades académicas. Se discute el impacto de la calidad metodológica encontrada y las evidencias reportados en la interpretación y generalización de los hallazgos.(AU)

Currently, the development of training programs in socioemo-tional skills in childhood has increased because they are considered as a valid tool for adaptation and coping with a variety of situations, both aca-demic and personal. However, there are few studies that show a compre-hensive view of available evidences. This research presents an umbrella re-view based on PRISMA method guidelines. It includes reviews on socio-emotional development programs applied in Primary Education with the aim of synthesizing their characteristics and compiling the main results on their effectiveness. The following databases were used: ERIC, WOS, PSYCINFO, SCOPUS and COCHRANE. After a blind peer process, 15 reviews that met the inclusion criteria were selected and analysed. Using the AMSTAR-2 and SANRA tools, it was found that 60% of secondary studies have critically low or low quality. Thirty nine programs reported in good quality reviews were identified, 51.2% presented moderate or strong evidence and reported significant effectsmainly on behavioral adjustment, social and emotional competencies and academic skills. The impact of the methodological quality found and the evidences on the interpretation and generalization of the findings is discussed.(AU)

Electroactive 4D Porous Scaffold Based on Conducting Polymer as a Responsive and Dynamic In Vitro Cell Culture Platform.

In vivo, cells reside in a 3D porous and dynamic microenvironment. It provides biochemical and biophysical cues that regulate cell behavior in physiological and pathological processes. In the context of fundamental cell biology research, tissue engineering, and cell-based drug screening systems, a challenge is to develop relevant in vitro models that could integrate the dynamic properties of the cell microenvironment. Taking advantage of the promising high internal phase emulsion templating, we here designed a polyHIPE scaffold with a wide interconnected porosity and functionalized its internal 3D surface with a thin layer of electroactive conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) to turn it into a 4D electroresponsive scaffold. The resulting scaffold was cytocompatible with fibroblasts, supported cellular infiltration, and hosted cells, which display a 3D spreading morphology. It demonstrated robust actuation in ion- and protein-rich complex culture media, and its electroresponsiveness was not altered by fibroblast colonization. Thanks to customized electrochemical stimulation setups, the electromechanical response of the polyHIPE/PEDOT scaffolds was characterized in situ under a confocal microscope and showed 10% reversible volume variations. Finally, the setups were used to monitor in real time and in situ fibroblasts cultured into the polyHIPE/PEDOT scaffold during several cycles of electromechanical stimuli. Thus, we demonstrated the proof of concept of this tunable scaffold as a tool for future 4D cell culture and mechanobiology studies.

Recent Advances in Polymers as Matrices for Drug Delivery Applications.

Polymeric-based drug delivery systems have become versatile and valuable candidates in sectors such as pharmaceuticals, health, medicine, etc [...].

Comparison of Ethos template-based planning and AI-based dose prediction: General performance, patient optimality, and limitations.

PURPOSE: Ethos proposes a template-based automatic dose planning (Etb) for online adaptive radiotherapy. This study evaluates the general performance of Etb for prostate cancer, as well as the ability to generate patient-optimal plans, by comparing it with another state-of-the-art automatic planning method, i.e., deep learning dose prediction followed by dose mimicking (DP + DM). MATERIALS: General performances and capability to produce patient-optimal plan were investigated through two studies: Study-S1 generated plans for 45 patients using our initial Ethos clinical goals template (EG_init), and compared them to manually generated plans (MG). For study-S2, 10 patients which showed poor performances at study-S1 were selected. S2 compared the quality of plans generated with four different methods: 1) Ethos initial template (EG_init_selected), 2) Ethos updated template-based on S1 results (EG_upd_selected), 3) DP + DM, and 4) MG plans. RESULTS: EG_init plans showed satisfactory performance for dose level above 50 Gy: reported mean metrics differences (EG_init minus MG) never exceeded 0.6 %. However, lower dose levels showed loosely optimized metrics, mean differences for V30Gy to rectum and V20Gy to anal canal were of 6.6 % and 13.0 %. EG_init_selected showed amplified differences in V30Gy to rectum and V20Gy to anal canal: 8.5 % and 16.9 %, respectively. These dropped to 5.7 % and 11.5 % for EG_upd_selected plans but strongly increased V60Gy to rectum for 2 patients. DP + DM plans achieved differences of 3.4 % and 4.6 % without compromising any V60Gy. CONCLUSION: General performances of Etb were satisfactory. However, optimizing with template of goals might be limiting for some complex cases. Over our test patients, DP + DM outperformed the Etb approach.

Ordering properties of anisotropic hard bodies in one-dimensional channels.

The phase behavior and structural properties of hard anisotropic particles (prisms and dumbbells) are examined in one-dimensional channels using the Parsons-Lee (PL) theory, and the transfer-matrix and neighbor-distribution methods. The particles are allowed to move freely along the channel, while their orientations are constrained such that one particle can occupy only two or three different lengths along the channel. In this confinement setting, hard prisms behave as an additive mixture, while hard dumbbells behave as a non-additive one. We prove that all methods provide exact results for the phase properties of hard prisms, while only the neighbor-distribution and transfer-matrix methods are exact for hard dumbbells. This shows that non-additive effects are incorrectly included into the PL theory, which is a successful theory of the isotropic-nematic phase transition of rod-like particles in higher dimensions. In the one-dimensional channel, the orientational ordering develops continuously with increasing density, i.e., the system is isotropic only at zero density, while it becomes perfectly ordered at the close-packing density. We show that there is no orientational correlation in the hard prism system, while the hard dumbbells are orientationally correlated with diverging correlation length at close packing. On the other hand, positional correlations are present for all the systems, the associated correlation length diverging at close packing.

Manipulating the Spin Orientation of Co Atoms Using Monatomic Cu Chains.

Harnessing the spin of single atoms is at the heart of quantum information nanotechnology based on magnetic concepts. By attaching single Co atoms to monatomic Cu chains, we demonstrate the ability to control the spin orientation by the atomic environment. Due to spin-orbit coupling (SOC), the spin is tilted by ≈58° from the surface normal toward the chain as evidenced by inelastic tunneling spectroscopy. These findings are reproduced by density functional theory calculations and have implications for Co atoms on pristine Cu(111), which are believed to be Kondo systems. Our quantum Monte Carlo calculations suggest that SOC suppresses the Kondo effect of Co atoms at chains and on the flat surface. Our work impacts the fundamental understanding of low-energy excitations in nanostructures on surfaces and demonstrates the ability to manipulate atomic-scale magnetic moments, which can have tremendous implications for quantum devices.

Dosimetrically triggered adaptive radiotherapy for head and neck cancer: Considerations for the implementation of clinical protocols.

PURPOSE: Defining dosimetric rules to automatically detect patients requiring adaptive radiotherapy (ART) is not straightforward, and most centres perform ad-hoc ART with no specific protocol. This study aims to propose and analyse different steps to design a protocol for dosimetrically triggered ART of head and neck (H&N) cancer. As a proof-of-concept, the designed protocol was applied to patients treated in TomoTherapy units, using their available software for daily MVCT image and dose accumulation. METHODS: An initial protocol was designed by a multidisciplinary team, with a set of flagging criteria based only on dose-volume metrics, including two action levels: (1) surveillance (orange flag), and (2) immediate verification (red flag). This protocol was adapted to the clinical needs following an iterative process. First, the protocol was applied to 38 H&N patients with daily imaging. Automatic software generated the daily contours, recomputed the daily dose and flagged the dosimetric differences with respect to the planning dose. Second, these results were compared, by a sensitivity/specificity test, to the answers of a physician. Third, the physician, supported by the multidisciplinary team, performed a self-analysis of the provided answers and translated them into mathematical rules in order to upgrade the protocol. The upgraded protocol was applied to different definitions of the target volume (i.e. deformed CTV + 0, 2 and 4 mm), in order to quantify how the number of flags decreases when reducing the CTV-to-PTV margin. RESULTS: The sensitivity of the initial protocol was very low, specifically for the orange flags. The best values were 0.84 for red and 0.15 for orange flags. After the review and upgrade process, the sensitivity of the upgraded protocol increased to 0.96 for red and 0.84 for orange flags. The number of patients flagged per week with the final (upgraded) protocol decreased in median by 26% and 18% for red and orange flags, respectively, when reducing the CTV-to-PTV margin from 4 to 2 mm. This resulted in only one patient flagged at the last fraction for both red and orange flags. CONCLUSION: Our results demonstrate the value of iterative protocol design with retrospective data, and shows the feasibility of automatically-triggered ART using simple dosimetric rules to mimic the physician's decisions. Using a proper target volume definition is important and influences the flagging rate, particularly when decreasing the CTV-to-PTV margin.

Structural properties of hard-disk fluids under single-file confinement.

The structural properties of confined single-file hard-disk fluids are studied analytically by means of a mapping of the original system onto a one-dimensional mixture of non-additive hard rods, the mapping being exact in the polydisperse limit. Standard statistical-mechanical results are used as a starting point to derive thermodynamic and structural properties of the one-dimensional mixture, where the condition that all particles have the same chemical potential must be taken into account. Analytical results are then provided for the nth neighbor probability distribution function, the radial distribution function, and the structure factor, a very good agreement being observed upon comparison with simulation data from the literature. Moreover, we have analyzed the scaling form for the disappearance of defects in the zigzag configuration for high pressure and have obtained the translational correlation length and the structural crossover in the oscillation frequency for asymptotically large distances.

Patient selection for proton therapy using Normal Tissue Complication Probability with deep learning dose prediction for oropharyngeal cancer.

BACKGROUND: In cancer care, determining the most beneficial treatment technique is a key decision affecting the patient's survival and quality of life. Patient selection for proton therapy (PT) over conventional radiotherapy (XT) currently entails comparing manually generated treatment plans, which requires time and expertise. PURPOSE: We developed an automatic and fast tool, AI-PROTIPP (Artificial Intelligence Predictive Radiation Oncology Treatment Indication to Photons/Protons), that assesses quantitatively the benefits of each therapeutic option. Our method uses deep learning (DL) models to directly predict the dose distributions for a given patient for both XT and PT. By using models that estimate the Normal Tissue Complication Probability (NTCP), namely the likelihood of side effects to occur for a specific patient, AI-PROTIPP can propose a treatment selection quickly and automatically. METHODS: A database of 60 patients presenting oropharyngeal cancer, obtained from the Cliniques Universitaires Saint Luc in Belgium, was used in this study. For every patient, a PT plan and an XT plan were generated. The dose distributions were used to train the two dose DL prediction models (one for each modality). The model is based on U-Net architecture, a type of convolutional neural network currently considered as the state of the art for dose prediction models. A NTCP protocol used in the Dutch model-based approach, including grades II and III xerostomia and grades II and III dysphagia, was later applied in order to perform automatic treatment selection for each patient. The networks were trained using a nested cross-validation approach with 11-folds. We set aside three patients in an outer set and each fold consists of 47 patients in training, five in validation and five for testing. This method allowed us to assess our method on 55 patients (five patients per test times the number of folds). RESULTS: The treatment selection based on the DL-predicted doses reached an accuracy of 87.4% for the threshold parameters set by the Health Council of the Netherlands. The selected treatment is directly linked with these threshold parameters as they express the minimal gain brought by the PT treatment for a patient to be indicated to PT. To validate the performance of AI-PROTIPP in other conditions, we modulated these thresholds, and the accuracy was above 81% for all the considered cases. The difference in average cumulative NTCP per patient of predicted and clinical dose distributions is very similar (less than 1% difference). CONCLUSIONS: AI-PROTIPP shows that using DL dose prediction in combination with NTCP models to select PT for patients is feasible and can help to save time by avoiding the generation of treatment plans only used for the comparison. Moreover, DL models are transferable, allowing, in the future, experience to be shared with centers that would not have PT planning expertise.

Comparison of two brief mindfulness interventions for anxiety, stress and burnout in mental health professionals: a randomised crossover trial.

Background: Anxiety, stress and burnout are a growing reality among mental health professionals, impacting negatively on them and their clients. Mindfulness-based interventions (MBIs) have demonstrated effectiveness in mitigating these sufferings. Nevertheless, there is a lack of knowledge on the impact of MBIs in Cuba. Objectives: To compare the effectiveness of two brief mindfulness-based interventions for reducing anxiety, work stress and burnout. Methods: A total of 104 mental health professionals from Havana (Cuba) participated in a randomised crossover trial. Group A received first an intervention involving body-centred practices (body scan and Hatha yoga) and a second intervention involving mind-centred practices (focused attention and open monitoring meditation). Group B received the same interventions but in reverse order. Four measures (anxiety, stress, burnout syndrome, and antecedents of burnout) were measured at baseline, posttest1, posttest2, and 6-months follow-up. Results: After the first intervention, there was a between-group difference for burnout syndrome, but the ES was similar for both groups. After the second intervention (implementing both practises), groups showed the largest effect sizes, and there was a between-group difference for antecedents of burnout. Results were partially maintained at 6-month follow-up. Conclusion: These results suggest that mind-centred practises can be as effective as body-centred practises for stress, anxiety and burnout reduction. The combination of both types of practises could be the most effective way of teaching mindfulness. About the sequence of implementation, teaching mind-centred practises first and then body-centred practises could be most effective for reducing antecedents of burnout.Clinical Trial Registration: www.clinicaltrials.gov NCT03296254.

Machine learning-based automatic proton therapy planning: Impact of post-processing and dose-mimicking in plan robustness.

PURPOSE: Automated treatment planning strategies are being widely implemented in clinical routines to reduce inter-planner variability, speed up the optimization process, and improve plan quality. This study aims to evaluate the feasibility and quality of intensity-modulated proton therapy (IMPT) plans generated with four different knowledge-based planning (KBP) pipelines fully integrated into a commercial treatment planning system (TPS). MATERIALS/METHODS: A data set containing 60 oropharyngeal cancer patients was split into 11 folds, each containing 47 patients for training, five patients for validation, and five patients for testing. A dose prediction model was trained on each of the folds, resulting in a total of 11 models. Three patients were left out in order to assess if the differences introduced between models were significant. From voxel-based dose predictions, we analyze the two steps that follow the dose prediction: post-processing of the predicted dose and dose mimicking (DM). We focused on the effect of post-processing (PP) or no post-processing (NPP) combined with two different DM algorithms for optimization: the one available in the commercial TPS RayStation (RSM) and a simpler isodose-based mimicking (IBM). Using 55 test patients (five test patients for each model), we evaluated the quality and robustness of the plans generated by the four proposed KBP pipelines (PP-RSM, PP-IBM, NPP-RSM, NPP-IBM). After robust evaluation, dose-volume histogram (DVH) metrics in nominal and worst-case scenarios were compared to those of the manually generated plans. RESULTS: Nominal doses from the four KBP pipelines showed promising results achieving comparable target coverage and improved dose to organs at risk (OARs) compared to the manual plans. However, too optimistic post-processing applied to the dose prediction (i.e. important decrease of the dose to the organs) compromised the robustness of the plans. Even though RSM seemed to partially compensate for the lack of robustness in the PP plans, still 65% of the patients did not achieve the expected robustness levels. NPP-RSM plans seemed to achieve the best trade-off between robustness and OAR sparing. DISCUSSION/CONCLUSIONS: PP and DM strategies are crucial steps to generate acceptable robust and deliverable IMPT plans from ML-predicted doses. Before the clinical implementation of any KBP pipeline, the PP and DM parameters predefined by the commercial TPS need to be modified accordingly with a comprehensive feedback loop in which the robustness of the final dose calculations is evaluated. With the right choice of PP and DM parameters, KBP strategies have the potential to generate IMPT plans within clinically acceptable levels comparable to plans manually generated by dosimetrists.

Equation of state of hard-disk fluids under single-file confinement.

The exact transfer-matrix solution for the longitudinal equilibrium properties of the single-file hard-disk fluid is used to study the limiting low- and high-pressure behaviors analytically as functions of the pore width. In the low-pressure regime, the exact third and fourth virial coefficients are obtained, which involve single and double integrals, respectively. Moreover, we show that the standard irreducible diagrams do not provide a complete account of the virial coefficients in confined geometries. The asymptotic equation of state in the high-pressure limit is seen to present a simple pole at the close-packing linear density, as in the hard-rod fluid, but, in contrast to the latter case, the residue is 2. Since, for an arbitrary pressure, the exact transfer-matrix treatment requires the numerical solution of an eigenvalue integral equation, we propose here two simple approximations to the equation of state, with different complexity levels, and carry out an extensive assessment of their validity and practical convenience vs the exact solution and available computer simulations.

A Case of Sterile Corneal Stromal Infiltration with Hypotonic Maculopathy Under Brimonidine Treatment.

INTRODUCTION: Brimonidine is a commonly used drug for glaucoma treatment, which has been linked to ocular autoimmune disorders like uveitis and conjunctivitis. Corneal pathology under brimonidine is generally less common. CASE DESCRIPTION: Here, we report a 78 -year-old male patient suffering from immune corneal stromal inflammation with hypotony and resulting hypotonic maculopathy after 6 weeks after introduction of brimonidine treatment. Systemic work-up for system autoimmune and infectious diseases was negative. We discontinued brimonidine and administered topical prednisolone under which inflammatory corneal signs and intraocular pressure normalized. Chorioretinal folds persisted after 9 months. CONCLUSION: Our case report suggests monitoring patients under brimonidine for sterile corneal infiltration.

Atmospheric pollen allergen load and environmental patterns in central and southwestern Iberian Peninsula.

Over one quarter of the population in industrialised countries suffers from some type of allergy and inhaled aeroallergens from pollen are the primary cause of allergic ailments. The networks for monitoring biological air quality measure the airborne pollen concentrations that characterize periods of exposure to major airborne aeroallergens but there are certain discrepancies in relation to the allergen-pollen dynamic. In this paper we analyse the airborne allergens Ole e 1, Phl p 1, Phl p 5 and Pla a 1, and interpreted the adjustments and mismatches in their concentrations in relation to airborne pollen. The influence of main environmental patterns was considered. The study was conducted in two urban areas of the centre and southwest of the Iberian Peninsula (Toledo in Spain and Évora in Portugal). Monitoring for pollen followed the standard protocol using Hirst volumetric spore traps and allergenic particles were quantified by ELISA assay. The results indicate that the discrepancies in this relationship were affected by the weather conditions up to 6 days prior. Precipitation and humidity above normal values caused a higher concentration of the allergen Pla a 1. This effect occurred in reverse in the case of humidity for the allergens Ole e 1 and Phl p 1. Humidity and precipitation generated the same pattern in the allergen-pollen relationship in both Phl p 1 and Phl p 5. Our findings show consistent results that allow to interpret the rate of discrepancy between allergen and pollen, and it can be used to improve allergy risk prediction models generated from atmospheric pollen.

The Mechanical, Thermal, and Chemical Properties of PLA-Mg Filaments Produced via a Colloidal Route for Fused-Filament Fabrication.

The effect of Mg particles on the thermal, chemical, physical, and primarily mechanical properties of 3D-printed PLA/Mg composites is studied in this paper. Recently, new colloidal processing has been proposed to introduce Mg particles into the PLA matrix, which ensures good dispersion of the particles and better thermal properties, allowing for thermal processing routes such as extrusion or 3D printing via fused-filament fabrication. The thermal and physical properties are here studied in 1D single-filament-printed PLA/Mg composites with 0 to 10 wt.% of Mg particles by Differential Scanning Calorimetry (DSC); we analyse the PLA chain modifications produced, the crystallinity fraction, and the different crystalline forms of the PLA after thermal processing. Fourier Transform Infrared Spectroscopy (FTIR) is used to confirm the influence of the PLA/Mg colloidal processing after printing. The mechanical properties are measured with a universal tensile test machine on the 1D single-printed filaments via fused-filament fabrication (FFF); the filaments were naturally aged to stable conditions. Filaments with and without a notch are studied to obtain the materials' tensile strength, elastic modulus, and fracture toughness. Different analytical models to explain the results of the PLA-Mg were studied, in which the minimum values for the interface strength of the PLA-Mg composites were calculated.

Thermal treatment of magnesium particles in polylactic acid polymer films elicits the expression of osteogenic differentiation markers and lipidome profile remodeling in human adipose stem cells.

The efficacy of polylactic acid (PLA)/Magnesium (Mg)-based materials for driving stem cells toward bone tissue engineering applications requires specific Mg surface properties to modulate the interface of stem cells with the film. Here, we have developed novel PLA/Mg-based composites and explored their osteogenic differentiation potential on human adipose stem cells (hASCs). Mg-particles/polymer interface was improved by two treatments: heating in oxidative atmosphere (TT) and surface modification with a compatibilizer (PEI). Different contents of Mg particles were dispersed in PLA and composite surface and bulk properties, protein adsorption, stem cell-PLA/Mg interactions, osteogenic markers expressions, and lipids composition profile were evaluated. Mg particles were uniformly distributed on the surface and in the bulk PLA polymer. Improved and modulated particle-polymer adhesion was observed in Mg particle-treated composites. After 21 days in canonical growth culture conditions, hASCs on PLA/MgTT displayed the highest expression of the general osteogenic markers, RUNX2, SSP1, and BGLAP genes, Alkaline Phosphatase, type I Collagen, Osteopontin, and Calcium deposits. Moreover, by LC/MS QTOF mass-spectrophotometry lipidomic analysis, we found in PLA/MgTT-cells, for the first time, a remodeling of the lipid classes composition associated with the osteogenic differentiation. We ascribed these results to MgTT characteristics, which improve Mg availability and composite osteoinductive performance.

Automated clinical decision support system with deep learning dose prediction and NTCP models to evaluate treatment complications in patients with esophageal cancer.

BACKGROUND AND PURPOSE: This study aims to investigate how accurate our deep learning (DL) dose prediction models for intensity modulated radiotherapy (IMRT) and pencil beam scanning (PBS) treatments, when chained with normal tissue complication probability (NTCP) models, are at identifying esophageal cancer patients who are at high risk of toxicity and should be switched to proton therapy (PT). MATERIALS AND METHODS: Two U-Net were created, for photon (XT) and proton (PT) plans, respectively. To estimate the dose distribution for each patient, they were trained on a database of 40 uniformly planned patients using cross validation and a circulating test set. These models were combined with a NTCP model for postoperative pulmonary complications. The NTCP model used the mean lung dose, age, histology type, and body mass index as predicting variables. The treatment choice is then done by using a ΔNTCP threshold between XT and PT plans. Patients with ΔNTCP ≥ 10% were referred to PT. RESULTS: Our DL models succeed in predicting dose distributions with a mean error on the mean dose to the lungs (MLD) of 1.14 ± 0.93% for XT and 0.66 ± 0.48% for PT. The complete automated workflow (DL chained with NTCP) achieved 100% accuracy in patient referral. The average residual (ΔNTCP ground truth - ΔNTCP predicted) is 1.43 ± 1.49%. CONCLUSION: This study evaluates our DL dose prediction models in a broader patient referral context and demonstrates their ability to support clinical decisions.

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.

Natural Ageing of PLA Filaments, Can It Be Frozen?

The physical ageing of polylactic acid (PLA) is a phenomenon that changes the material's properties over time. This ageing process is highly dependent on ambient variables, such as temperature and humidity. For PLA, the ageing is noticeable even at room temperatures, a process commonly referred to as natural ageing. Stopping the ageing by freezing the material can be helpful to preserve the properties of the PLA and stabilise it at any time during its storage until it is required for testing. However, it is essential to demonstrate that the PLA's mechanical properties are not degraded after defrosting the samples. Four different methods for stopping the ageing (anti-ageing processes) are analysed in this paper-all based on freezing and defrosting the PLA samples. We determine the temperature and ambient water vapor influence during the freezing and defrosting process using desiccant and zip bags. The material form selected is PLA filaments (no bulk material or scaffold structures) printed at 190 °C with diameters between 400 and 550 µm and frozen at -24 °C in the presence or absence of a desiccant. The impact of the anti-ageing processes on PLA's ageing and mechanical integrity is studied regarding the thermal, mechanical and fractographical properties. In conclusion, an anti-ageing process is defined to successfully stop the natural ageing of the PLA for an indefinite length of time. This process does not affect the mechanical properties or the structural integrity of the PLA. As a result, large quantities of this material can be produced in a single batch and be safely stored to be later characterised under the same manufacturing and ageing conditions, which is currently a limiting factor from an experimental point of view as polymeric filament properties can show significant variety from batch to batch.