Search

Abstract Molecular dynamics (MD) simulations can reduce our need for experimental tests and provide detailed insight into the chemical reactions and binding kinetics. There are two challenges while dealing with MD simulations: one is the time and length scale limitations, and the latter is efficiently processing the massive amount of data resulting from the MD simulations and generating the proper reaction rates. In this work, we evaluated the use of regression machine learning (ML) methods to solve these two challenges by developing a framework for ethanol adsorption on an Aluminium (Al) slab. This framework comprises three main stages: first, an all-atom molecular dynamics model; second, ML regression models; and third, validation and testing. In stage one, the adsorption of ethanol molecules on the Al surface for various temperatures, velocities and concentrations is simulated using the large-scale atomic/molecular massively parallel simulator (LAMMPS) and ReaxFF. The outcome of stage one is utilised for training, testing, and validating the predictive models in stages two and three. We developed and evaluated 28 different ML models for predicting the number of adsorbed molecules over time, including linear regression, support vector machine (SVM), decision trees, ensemble, Gaussian process regression (GPR), neural network (NN) and Bayesian hyper-parameter optimisation models. Based on the results, the Bayesian-based GPR showed the highest accuracy and the lowest training time. The developed model can predict the number of adsorbed molecules for new cases within seconds, while MD simulations take a few weeks. This adsorption rate can then be used in macroscale simulations to tackle the time and length scale limitations. The proposed numerical framework has the potential to be generalised and, therefore, contribute to future low-cost binding reaction estimations, providing a valuable tool for industry and experimentalists.

Abstract Wound healing is a complex process orchestrated by interactions between a variety of cell types, including keratinocytes, fibroblasts, endothelial cells, inflammatory cells, and bioactive factors such as extracellular matrix (ECM) components, growth factors, and cytokines. Chronic wounds exhibit delayed proliferative phase initiation, reduced angiogenesis, impaired ECM synthesis, and persistent inflammatory response. Chronic wounds are one of the main challenges to the healthcare system worldwide, with a high cost for medical services. Hence, investigation of new approaches to accelerate wound healing is essential. Phytomedicines are considered as potential agents for improving the wound healing by accelerating epithelization, collagen synthesis, and angiogenesis. These natural compounds have various advantages including availability, ease of application, and high effectiveness in wound managment. This study aimed to investigate the biological effects of saffron or Crocus sativus L. (C. sativus) petal extract on cell survival, migration, and angiogenesis using MTT, scratch and in vitro tube formation assays. Moreover, the expression of collagen type I alpha 1 (COL1A1) and vascular endothelial growth factor (VEGF) were evaluated in human dermal fibroblasts (HDF)s and human umbilical vein endothelial cells (HUVEC)s, respectively. The effect of the C. sativus extract on the skin of diabetic mice was also monitored. The results showed that C. sativus petal extract promoted the viability and migration of HDFs and HUVECs. Moreover, C. sativus petal extract enhanced the formation of tube-like structures by HUVECs cultured on the Matrigel basement membrane matrix, indicating its potential to stimulate angiogenesis. Gene expression studies have shown the the C. sativus extract increases wound healing by upregulation of COL1A1 and VEGF, which are crucial factors involved in collagen deposition, epithelialization, and angiogenesis. Histological analysis revealed that C. sativus petal extract enhanced vascularity and increased the number of fibroblasts and collagen synthesis, ultimately accelerating wound closure compared to wounds treated with eucerin and commercial ointment in diabetic mice. Therefore, C. sativus petal extract has potential as a herbal treatment to improve the healing of diabetic wounds.

Abstract Purpose The present study aimed to test the relationship between the components of the Cognitive Load Theory (CLT) including memory, intrinsic and extraneous cognitive load in workplace-based learning in a clinical setting, and decision-making skills of nursing students. Methods This study was conducted at Shahid Sadoughi University of Medical Sciences in 2021–2023. The participants were 151 nursing students who studied their apprenticeship courses in the teaching hospitals. The three basic components of the cognitive load model, including working memory, cognitive load, and decision-making as the outcome of learning, were investigated in this study. Wechsler’s computerized working memory test was used to evaluate working memory. Cognitive Load Inventory for Handoffs including nine questions in three categories of intrinsic cognitive load, extraneous cognitive load, and germane cognitive load was used. The clinical decision-making skills of the participants were evaluated using a 24-question inventory by Lowry et al. based on a 5-point scale. The path analysis of AMOS 22 software was used to examine the relationships between components and test the model. Findings In this study, the goodness of fit of the model based on the cognitive load theory was reported (GIF = 0.99, CFI = 0.99, RMSEA = 0.03). The results of regression analysis showed that the scores of decision-making skills in nursing students were significantly related to extraneous cognitive load scores (p-value = 0.0001). Intrinsic cognitive load was significantly different from the point of view of nursing students in different academic years (p = 0.0001). Conclusion The present results showed that the CLT in workplace-based learning has a goodness of fit with the components of memory, intrinsic cognitive load, extraneous cognitive load, and clinical decision-making skill as the key learning outcomes in nursing education. The results showed that the relationship between nursing students’ decision-making skills and extraneous cognitive load is stronger than its relationship with intrinsic cognitive load and memory Workplace-based learning programs in nursing that aim to improve students’ decision-making skills are suggested to manage extraneous cognitive load by incorporating cognitive load principles into the instructional design of clinical education.

Introduction: Meeting the needs of shareholders and investors, generating profit and income, and covering current expenses are the primary objectives of any economic entity. Banks and financial institutions are no exception, and calculating and understanding costs is one of their most critical activities. In today's competitive environment, organizations must adopt strategies that enhance the quality of services and products while reducing their costs. To achieve this, having tools for analyzing related costs and formulating cost policies for services and products is essential. Companies that previously used traditional costing systems have had to transition to newer, more dynamic, and flexible costing systems that account for various costs, including products, activities, distribution channels, and customers, reflecting the complexity of modern business and production processes. This article presents a model for calculating the cost of banking services using activity-based costing. Methods: The research described in this article is developmental-applied. Given the various factors affecting costs and their nonlinear and cyclical effects, which render banks as complex systems, the methodology of system dynamics was used for modeling. This research is descriptive in terms of data collection methods, which included library studies reviewing sources and references on activity-based costing and systems dynamics principles, simulations concerning the cost of banking services using systems dynamics, and other sources such as books, magazines, articles, and theses from reputable libraries, information search centers, and credible websites. Results and discussion: In this study, detailed models for two products, mudarabah and deposits, were developed. Cause-and-effect diagrams and their rates and statuses were drawn, and after testing the models, proposed scenarios were designed and compared. Four scenarios were suggested to improve system behavior: improving productivity, adjusting human resources, re-engineering business processes, and automating processes. To select the best policy—one that achieves the most significant cost reduction over a similar period—all policies were compared. The study's findings indicate that the policy of mechanization and process re-engineering is the most effective. Therefore, the bank's general policy for reducing product costs can be a combination of re-engineering and mechanizing processes. Conclusions: Considering the dynamic business environment and banks as complex systems where many variables influence each other, the systems dynamics approach was employed to model the cost of banking services. The simulation results show that a combination of process re-engineering and automation can serve as an effective policy for reducing the cost of banking services.

Abstract Background Effective feedback is fundamental in clinical education, as it allows trainers to constantly diagnose the trainees’ condition, determine their weaknesses, and intervene at proper times. Recently, different feedback-based approaches have been introduced in clinical training; however, the effectiveness of such interventions still needs to be studied extensively, especially in the perioperative field. Therefore, this study sought to compare the effects of apprenticeship training using sandwich feedback and traditional methods on the perioperative competence and performance of Operating Room (OR) technology students. Methods Thirty final-semester undergraduate OR technology students taking the apprenticeship courses were randomly allocated into experimental (n = 15) and control (n = 15) groups through the stratified randomization approach. The students in the experimental group experienced Feedback-Based Learning (FBL) using a sandwich model, and the students in the control group participated in Traditional-Based Training (TBT) in six five-hour sessions weekly for three consecutive weeks. All students completed the Persian version of the Perceived Perioperative Competence Scale-Revised (PPCS-R) on the first and last days of interventions. Also, a blinded rater completed a checklist to evaluate all students’ performance via Direct Observation of Procedural Skills (DOPS) on the last intervention day. Besides, the students in the FBL filled out a questionnaire regarding their attitude toward the implemented program. Results The mean total score of the PPCS-R was significantly higher in the FBL than in the TBT on the last intervention day (P

Abstract Background Moral distress is a multifactorial and complex phenomenon influenced by various individual, cultural, and systemic factors. This study aimed to investigate the frequency and intensity of nurses’ moral distress, explore their experiences, and develop the conceptual model of risk factors of moral distress in surgical units and operating rooms. Method This is a sequential mixed-method study conducted at four teaching hospitals affiliated with the Qom University of Medical Sciences. In the first step, the moral distress of nurses in surgical units and operating rooms was investigated by a survey. The participants included nurses who worked in the operating room and surgical units. (n = 180). The data was collected by a Moral Distress Scale-Revised (MDS-R) questionnaire. In the second step, the experiences of nurses regarding risk factors of moral distress were explored using semi-structured interviews and analyzed using the conventional content analysis by Graneheim and Lundman’s approach. Results One hundred eighty nurses participated in this study. The mean total moral distress scores ranged from 12 to 221, with a mean (SD) of 116.8 (42.73). The causes of moral distress cited with the highest frequency and intensity related to the ‘role of healthcare providers’. The experiences of the participants in the theme ‘Inductive process of moral distress development’ were categorized into three categories: ‘Melting into the faulty system’, ‘Power and the system as distress promotors’, and ‘Perceived unpleasant consequences’. Conclusion The results indicated that the frequency of moral distress in operating rooms and surgical units was at a moderate level and the distress intensity of nurses was at a moderately high level. The results indicated that in the investigated system, the “inductive moral process of distress development” was continuously understood by the participants. This process was influenced by systemic and individual factors. Weak assertiveness, conservative compromise, and desensitization to unprofessionalism as individual factors were effective in causing distress. Risk factors at the systemic level led nurses to melt into the faulty system and created adverse outcomes at the individual level. The lack of systemic support and the stabilization of mobbing by powerful system members had a negative impact on the individual factors of distress development. Also, these factors directly cause negative consequences.

Abstract The failure of the aortic heart valve is common, resulting in deterioration of the pumping function of the heart. For the end stage valve failure, bi-leaflet mechanical valve (most popular artificial valve) is implanted. However, due to its non-physiological behaviour, a significant alteration is observed in the normal haemodynamics of the aorta. While in-vivo experimentation of a human heart valve (native and artificial) is a formidable task, in-silico study using computational fluid dynamics (CFD) with fluid structure interaction (FSI) is an effective and economic tool for investigating the haemodynamics of natural and artificial heart valves. In the present work, a haemodynamic model of a natural and mechanical heart valve has been developed using meshless particle-based smoothed particle hydrodynamics (SPH). In order to further enhance its clinical relevance, this study employs a patient-specific vascular geometry and presents a successful validation against traditional finite volume method and 4D magnetic resonance imaging (MRI) data. The results have demonstrated that SPH is ideally suited to simulate the heart valve function due to its Lagrangian description of motion, which is a favourable feature for FSI. In addition, a novel methodology for the estimation of the wall shear stress (WSS) and other related haemodynamic parameters have been proposed from the SPH perspective. Finally, a detailed comparison of the haemodynamic parameters has been carried out for both native and mechanical aortic valve, with a particular emphasis on the clinical risks associated with the mechanical valve.

Abstract Introduction The present study aimed to assess the status of workplace mental health from the viewpoints of educators, and explore their experiences concerning influential factors on occupational mental health at Shahid Sadoughi University of Medical Sciences. Methods The study was a sequential mixed-method study that was conducted in quantitative and qualitative phases. In the quantitative phase, the perception of educators (n = 205) was assessed by a Workplace Mental Health Questionnaire, including 37 items in 9 categories (including an opportunity to control, an opportunity to use skills, external goals created, environmental diversity, environmental clarity, access to money, physical security, opportunity to contact others, and valuable social status and position). In the qualitative phase, data were collected using semi-structured interviews (n = 21) and were analyzed based on the conventional content analysis approach. Results The results showed that the status of workplace mental health of educators was at a moderate level (mean (± SD) = 115.87 (±3.21). The highest and lowest scores of the median were reported in the domains of “opportunity for control” (median = 4) and “opportunity to contact others” (median = 2.75), respectively. The theme of “contrast between preferences and disappointments in the development path” with two categories including “induced demotivation of system elements” and “tendencies of promotion” was explored from the educators’ perspective. Conclusion The results indicated the moderate level of mental health of educators was influenced by the contrast between preferences and disappointments in the development path. The tendency of educators for promotion was explored as a positive factor in the mental health of educators in the academic environment. A growing desire for creative advancement among educators as a personal factor and a demand to stay updated with all developments as a system factor explained the positive experiences of educators in the university. The results showed the gap between the current situation and the desired state of occupational mental health may result from cultural challenges, lack of adherence to professionalism at the personal level (non-compliance with the principles of well-being and excellence), and interpersonal level (non-compliance with respect, justice, etc.). Moreover, factors disrupting occupational mental health at the system level explored in job stress, a resilient culture, lack of managerial support, ingratitude, lack of reward-effort matching mechanism, and lack of resources.

Phase change materials (PCMs) integrated with photovoltaic-thermal (PVT) collectors can simultaneously generate and store electrical and thermal energy. However, design optimization requires accurate modeling of the complex heat transfer processes in PCMs under varying operating conditions. This study introduces an efficient simulation approach with generalized Nusselt number correlations to enable precise and rapid analysis of PCM thermal performance. A numerical model is developed to quantify heat fluxes, node temperatures, energy and exergy outputs across PCM solid, melting, and liquid states. Extensive analysis is conducted to explore the impact of irradiation, ambient temperature, PCM thickness, tilt angle, and wind speed on PVT performance. Key findings include: (1) thermal energy yield exceeds electrical output by 2.8 times owing to PV's low efficiency, while electrical exergy dominates thermal exergy by 5.3 times highlighting electric output's primacy; (2) electrical output chiefly depends on irradiation, while thermal energy and exergy are highly sensitive to ambient temperature and wind speed; (3) thermal energy escalates 4.5 times faster than electrical energy with irradiation rise, but thermal exergy drops sharply from 10.1 to 0.34 W as ambient temperature increases from 0 to 35 °C due to quality factor degradation. The study provides new generalized correlations, validated model, and extensive performance assessment to advance PCM-based PVT collector design.

Introduction: Patients with end-stage heart failure (HF) may need mechanical circulatory support such as a left ventricular assist device (LVAD). However, there are a range of complications associated with LVAD including aortic regurgitation (AR) and thrombus formation. This study assesses whether the risk of developing aortic conditions can be minimised by optimising LVAD implantation technique.Methods: In this work, we evaluate the aortic flow patterns produced under different geometrical parameters for the anastomosis of the outflow graft (OG) to the aorta using computational fluid dynamics (CFD). A three-dimensional aortic model is created and the HeartMate III OG positioning is simulated by modifying (i) the distance from the anatomic ventriculo-arterial junction (AVJ) to the OG, (ii) the cardinal position around the aorta, and (iii) the angle between the aorta and the OG. The continuous LVAD flow and the remnant native cardiac cycle are used as inlet boundaries and the three-element Windkessel model is applied at the pressure outlets.Results: The analysis quantifies the impact of OG positioning on different haemodynamic parameters, including velocity, wall shear stress (WSS), pressure, vorticity and turbulent kinetic energy (TKE). We find that WSS on the aortic root (AoR) is around two times lower when the OG is attached to the coronal side of the aorta using an angle of 45° ± 10° at a distance of 55 mm.Discussion: The results show that the OG placement may significantly influence the haemodynamic patterns, demonstrating the potential application of CFD for optimising OG positioning to minimise the risk of cardiovascular complications after LVAD implantation.

Background and Purpose: Microbeam Radiation Therapy (MRT) aims to deliver higher doses to the target while minimizing radiation damage to healthy tissues using synchrotron x-ray microbeams. Translational MRT research has now started, driven by promising results from preclinical studies. This study aimed to propose a first dose-outcome model by analyzing micrometric dose distributions obtained with high-resolution 3D dose calculations, accounting for the inherent physical dose distribution complexity in MRT. The feasibility of integrating penMRT, our full Monte Carlo multiscale dose calculation algorithm based on PENELOPE into translational research on veterinary patients was also investigated. Material and Methods: Micrometric dose distributions were calculated in tumor-bearing rats and for a veterinary patient with penMRT, for conformal multi-directional MRT treatment plans. Absorbed dose maps were obtained with 0.005 × 0.005 × 1 mm3 voxel sizes. High-resolution dose-volume histograms were extracted and analyzed against radiobiology studies. Results: The complexity of the MRT dose distribution was properly rendered at a micrometer scale on 3D dose maps, with well separated dose regions observed on the differential dose-volume histograms. The median survival time of glioma-bearing rats varied linearly with the volume fraction of the planning target volume that received doses higher than 50 Gy (R2 = 0.98). The feasibility of using penMRT for treatment planning in large volumes has been shown on a veterinary patient. Conclusions: This study demonstrated the significant added value of penMRT for planning and prescribing MRT treatments. It also shed light on the correlation between the high-resolution 3D dose distributions and the treatment outcome.

The world is confronting a severe water crisis. To clean up water from heavy metals, microorganisms, chemicals, and other types of pollutants, nanocomposites have been receiving great attention specifically due to the high surface area affording to work effectually even at low concentrations. In this research, we synthesized a new amino acid-modified MoS2 nanocomposite by chemically immobilizing Mn (II). The synthesized absorbent MoS2–COOH/gly/Mn was identified by thermogravimetric analysis (TGA), nitrogen adsorption measurement, X-ray diffraction (XRD), analysis of energy dispersive X-ray mapping (EDAX and MAP), field emission scanning electron microscopy (FE-SEM), and Fourier Transform Infrared spectrometry (FT-IR). The nanocomposite was employed as an adsorbent through the solid phase microextraction (SPME) method while trifluralin herbicide was chosen as a model compound. For the monitoring of trifluralin molecules, we employed an ion mobility spectrometry apparatus featuring a corona discharge ionization source. The SPME method's effectiveness was examined by investigating the stirring rate and extraction time as two crucial parameters, aiming to achieve trace analysis of trifluralin. Under the optimized condition of the trifluralin extraction, the coefficient (R2) and linear dynamic range (LDR) correlation were obtained at 0.9961 and 0.5–10 μg L−1, respectively. Relative recovery values the described approach were obtained in the span of 96–97% for agricultural wastewater samples. The quantification (LOQ) and limit of detection (LOD) were calculated at 0.5 and 0.15 μg L−1, respectively. The proposed nanocomposite absorbent has the capability to be applied as an efficient material for the extraction of trifluralin herbicide from different solutions.

Synchrotron Microbeam Radiation Therapy (MRT) has repeatedly proven its superiority compared with conventional radiotherapy for glioma control in preclinical research. The clinical transfer phase of MRT has recently gained momentum; seven dogs with suspected glioma were treated under clinical conditions to determine the feasibility and safety of MRT. We administered a single fraction of 3D-conformal, image-guided MRT. Ultra-high-dose rate synchrotron X-ray microbeams (50 µm-wide, 400 µm-spaced) were delivered through five conformal irradiation ports. The PTV received ~25 Gy peak dose (within microbeams) per port, corresponding to a minimal cumulated valley dose (diffusing between microbeams) of 2.8 Gy. The dogs underwent clinical and MRI follow-up, and owner evaluations. One dog was lost to follow-up. Clinical exams of the remaining six dogs during the first 3 months did not indicate radiotoxicity induced by MRT. Quality of life improved from 7.3/10 [±0.7] to 8.9/10 [±0.3]. Tumor-induced seizure activity decreased significantly. A significant tumor volume reduction of 69% [±6%] was reached 3 months after MRT. Our study is the first neuro-oncologic veterinary trial of 3D-conformal Synchrotron MRT and reveals that MRT does not induce acute to subacute radiotoxicity in normal brain tissues. MRT improves quality of life and leads to remarkable tumor volume reduction despite low valley dose delivery. This trial is an essential step towards the forthcoming clinical application of MRT against deep-seated human brain tumors.

The present work explores the impact of tip clearance on the mean blade height ratio, inlet tip blade angle, and surface roughness of the inducer. The objective is to find an optimized inducer to limit the secondary flow over the blades, which in turn improves the pump efficiency and reduces the life cycle costs. A numerical framework is developed to investigate efficient operational and geometrical parameters on an inducer's cavitation and non-cavitation presentations. The catalyser functioning is simulated by applying a 3D CFD model, and the results are assessed against empirical data. The results show a reliable agreement with empirical data and suggest that the increment of tip clearance in the mean blade height ratio causes the hydraulic performance and the analytical cavitation number to decline in cavitation and non-cavitation conditions. Moreover, the optimum value of 85o is found for the inlet tip blade angle, which improves the non-cavitation performance.

[This corrects the article DOI: 10.1371/journal.pone.0302938.].

BackgroundNurses and researchers emphasize the importance of adding educational content of palliative care to nursing curricula in Iran as a means to improve the quality of care at the end of life and self-efficacy is considered as an important determinant in palliative care nursing. However, undergraduate nursing students are not sufficiently trained to achieve the qualifications required in palliative care. The aim of this study was to determine the effect of combined training (theoretical-practical) of palliative care on the perceived self-efficacy of nursing students.MethodsThis is a semi-experimental study with a pretest-posttest design. Sampling was nonrandomized with convenience method and included 23 seventh-semester students. The intervention consisted of palliative care training for ten theoretical sessions and three practical sessions. Data were collected using demographic and the perceived self-efficacy questionnaires completed before and after the intervention. Data were then analyzed in the statistical SPSS 23 software using descriptive and analytical statistics.ResultsThe mean age of the samples was 22.78 (SD1.17). Most of the participants were male (56.5%) and single(91.3%). The findings showed that, perceived self-efficacy, psycho-social support and symptom management improved significantly after the intervention (pConclusionPalliative care training can increase the nursing students perceived self-efficacy. Since nursing students are the future nurses of the care system, therefore, managers and planners can take a step towards improving the quality of nursing care by using palliative care training programs. Since nursing students will be future nurses in health care system, therefore, managers and planners can take steps to improve the quality of nursing care by using palliative care education programs.

Molecular dynamics (MD) simulations can reduce our need for experimental tests and provide detailed insight into the chemical reactions and binding kinetics. There are two challenges while dealing with MD simulations: one is the time and length scale limitations, and the latter is efficiently processing the massive amount of data resulting from the MD simulations and generating the proper reaction rates. In this work, we evaluated the use of regression machine learning (ML) methods to solve these two challenges by developing a framework for ethanol adsorption on an Aluminium (Al) slab. This framework comprises three main stages: first, an all-atom molecular dynamics model; second, ML regression models; and third, validation and testing. In stage one, the adsorption of ethanol molecules on the Al surface for various temperatures, velocities and concentrations is simulated using the large-scale atomic/molecular massively parallel simulator (LAMMPS) and ReaxFF. The outcome of stage one is utilised for training, testing, and validating the predictive models in stages two and three. We developed and evaluated 28 different ML models for predicting the number of adsorbed molecules over time, including linear regression, support vector machine (SVM), decision trees, ensemble, Gaussian process regression (GPR), neural network (NN) and Bayesian hyper-parameter optimisation models. Based on the results, the Bayesian-based GPR showed the highest accuracy and the lowest training time. The developed model can predict the number of adsorbed molecules for new cases within seconds, while MD simulations take a few weeks. This adsorption rate can then be used in macroscale simulations to tackle the time and length scale limitations. The proposed numerical framework has the potential to be generalised and, therefore, contribute to future low-cost binding reaction estimations, providing a valuable tool for industry and experimentalists. [ABSTRACT FROM AUTHOR]

Background: Feedback‐based learning (FBL) focuses on guiding the learning process according to educational objectives and the student's needs. This study aimed to investigate surgical nursing students' perceptions and explore their experiences of FBL. Method: The present study used a mixed‐methods sequential explanatory design that was conducted in the quantitative and qualitative phases. Surgical nursing students participated in the quantitative phase (n = 105). In the first phase, students completed two questionnaires about FBL and clinical feedback. Semi‐structured face‐to‐face interviews were used to collect qualitative data in the second phase. Graneheim and Lundman's inductive approaches were used to analyse the qualitative data. Results: The mean (SD) score for students' perception of FBL was 3.99 ± 0.70. The qualitative results were explored in two themes, "motivational support for improvement" and "unpleasant learning". Conclusion: In this study, the positive and negative aspects of FBL were explained. FBL is perceived as a motivational support mechanism to improve students' capabilities during their academic courses and also prepare them for future careers. Conversely, FBL may experience unpleasant learning due to negative feedback and negative emotions. [ABSTRACT FROM AUTHOR]

Recent growing interest in using machine learning for turbulence modeling has led to many proposed data-driven turbulence models in the literature. However, most of these models have not been developed with overcoming non-unique mapping (NUM) in mind, which is a significant source of training and prediction error. Only NUM caused by one-dimensional channel flow data has been well studied in the literature, despite most data-driven models having been trained on two-dimensional flow data. The present work aims to be the first detailed investigation on NUM caused by two-dimensional flows. A method for quantifying NUM is proposed and demonstrated on data from a flow over periodic hills and an impinging jet. The former is a wall-bounded separated flow, and the latter is a shear flow containing stagnation and recirculation. This work confirms that data from two-dimensional flows can cause NUM in data-driven turbulence models with the commonly used invariant inputs. This finding was verified with both cases, which contain different flow phenomena, hence showing that NUM is not limited to specific flow physics. Furthermore, the proposed method revealed that regions containing low strain and rotation or near pure shear cause the majority of NUM in both cases—approximately 76% and 89% in the flow over periodic hills and impinging jet, respectively. These results led to viscosity ratio being selected as a supplementary input variable (SIV), demonstrating that SIVs can reduce NUM caused by data from two-dimensional flows and subsequently improve the accuracy of tensor-basis machine learning models for turbulence modeling. [ABSTRACT FROM AUTHOR]

Wound healing is a complex process orchestrated by interactions between a variety of cell types, including keratinocytes, fibroblasts, endothelial cells, inflammatory cells, and bioactive factors such as extracellular matrix (ECM) components, growth factors, and cytokines. Chronic wounds exhibit delayed proliferative phase initiation, reduced angiogenesis, impaired ECM synthesis, and persistent inflammatory response. Chronic wounds are one of the main challenges to the healthcare system worldwide, with a high cost for medical services. Hence, investigation of new approaches to accelerate wound healing is essential. Phytomedicines are considered as potential agents for improving the wound healing by accelerating epithelization, collagen synthesis, and angiogenesis. These natural compounds have various advantages including availability, ease of application, and high effectiveness in wound managment. This study aimed to investigate the biological effects of saffron or Crocus sativus L. (C. sativus) petal extract on cell survival, migration, and angiogenesis using MTT, scratch and in vitro tube formation assays. Moreover, the expression of collagen type I alpha 1 (COL1A1) and vascular endothelial growth factor (VEGF) were evaluated in human dermal fibroblasts (HDF)s and human umbilical vein endothelial cells (HUVEC)s, respectively. The effect of the C. sativus extract on the skin of diabetic mice was also monitored. The results showed that C. sativus petal extract promoted the viability and migration of HDFs and HUVECs. Moreover, C. sativus petal extract enhanced the formation of tube-like structures by HUVECs cultured on the Matrigel basement membrane matrix, indicating its potential to stimulate angiogenesis. Gene expression studies have shown the the C. sativus extract increases wound healing by upregulation of COL1A1 and VEGF, which are crucial factors involved in collagen deposition, epithelialization, and angiogenesis. Histological analysis revealed that C. sativus petal extract enhanced vascularity and increased the number of fibroblasts and collagen synthesis, ultimately accelerating wound closure compared to wounds treated with eucerin and commercial ointment in diabetic mice. Therefore, C. sativus petal extract has potential as a herbal treatment to improve the healing of diabetic wounds. [ABSTRACT FROM AUTHOR]

Simple Summary: The benefit of spatially fractionated radiotherapy for brain tumors is maximized through Synchrotron Microbeam Radiation Therapy (MRT). In 2021, the clinical transfer phase of MRT began: the first brain-tumor-bearing dog patients were treated under clinical conditions in view of the forthcoming clinical transfer. As a primary endpoint, the tolerance of normal brain tissues to MRT was evaluated, while the efficacy in reducing tumor volume was considered as a secondary endpoint. We here present acute to subacute neurologic radiotolerance and tumor volume reduction after MRT for brain tumor treatment in canine patients included in our ongoing veterinary trial, proving that MRT is a safe tool for spontaneous brain tumor treatment in dogs. Synchrotron Microbeam Radiation Therapy (MRT) has repeatedly proven its superiority compared with conventional radiotherapy for glioma control in preclinical research. The clinical transfer phase of MRT has recently gained momentum; seven dogs with suspected glioma were treated under clinical conditions to determine the feasibility and safety of MRT. We administered a single fraction of 3D-conformal, image-guided MRT. Ultra-high-dose rate synchrotron X-ray microbeams (50 µm-wide, 400 µm-spaced) were delivered through five conformal irradiation ports. The PTV received ~25 Gy peak dose (within microbeams) per port, corresponding to a minimal cumulated valley dose (diffusing between microbeams) of 2.8 Gy. The dogs underwent clinical and MRI follow-up, and owner evaluations. One dog was lost to follow-up. Clinical exams of the remaining six dogs during the first 3 months did not indicate radiotoxicity induced by MRT. Quality of life improved from 7.3/10 [±0.7] to 8.9/10 [±0.3]. Tumor-induced seizure activity decreased significantly. A significant tumor volume reduction of 69% [±6%] was reached 3 months after MRT. Our study is the first neuro-oncologic veterinary trial of 3D-conformal Synchrotron MRT and reveals that MRT does not induce acute to subacute radiotoxicity in normal brain tissues. MRT improves quality of life and leads to remarkable tumor volume reduction despite low valley dose delivery. This trial is an essential step towards the forthcoming clinical application of MRT against deep-seated human brain tumors. [ABSTRACT FROM AUTHOR]