Training Paradigm Research Articles

ПЕДАГОГІЧНІ ТЕХНОЛОГІЇ ПРОФЕСІЙНОЇ ПІДГОТОВКИ МАЙБУТНІХ ФАХІВЦІВ СОЦІОНОМІЧНОЇ СФЕРИ

The article carries out a thorough and comprehensive analysis of approaches that contribute to the effectiveness of professional training of future specialists in the socionomic sphere in the current socio-cultural situation and in terms of forced distance interaction. The goal of the article is to determine the main pedagogical technologies that are the most effective and characteristic for the training of future specialists in the socionomic area of expertise. According to the goal, the following tasks were set: firstly, on the basis of content analysis, to identify and analyse the main pedagogical technologies that are the most effective and characteristic for the professional training of future specialists in the socionomic sphere; secondly, to justify the effectiveness of the use of certain pedagogical technologies specifically for the training of experts in the socionomic sphere relying on the systematization and conceptualization of advanced pedagogical experience in higher education institutions. It has been established that the pedagogical technologies used in the training of future specialists in the socionomic sphere in the institution of higher education must design a mechanism of management and development of the personality and professional skills of the future experts. This becomes possible only under the condition of a set of students’ and teachers’ actions – cognitive and instrumental ones. The primary development of such technologies is the creation of highly productive students’ educational activities and highly effective managerial teachers’ activities in their educational, professional and creative interaction. It has been found that among the most promising pedagogical technologies capable of implementing the specified strategic tasks are project technology (project method), integrative-modular technologies, modular-rating learning technology, problem-based learning technology, case technologies, information and communication technologies and computer distance learning technologies. The mentioned technologies allow ensuring the comprehensive personal development of future specialists in the socionomic sphere, their preparation for productive professional activity, a high level of study and cognitive activity and self-management of the educational process. In the article, the emphasis is placed on the priority of integrating modern information and communication technologies into professional education for the purpose of forming the professional experience of future specialists in the socionomic sphere, activating thinking, intensification of educational activities, in particular in the distance learning conditions. It has been substantiated that the existing problems in the system of higher education in Ukraine require significant evolutionary changes in the paradigm of professional training and in all components of the educational process. It has been established that the reform of the education process in Ukrainian higher education institutions, which prepare future specialists in the socionomic sphere, should be aimed at including students in an active learning process and exerting a significant influence on the motivational, cognitive, emotional-volitional and psychophysiological spheres of their personality ensuring thereby their further professional and spiritual rise. It was concluded that for the modern theory and methodology of professional education of future specialists in the socionomic sphere, the search for new pedagogical opportunities is connected, first of all, with the rejection of some elements of the traditional educational process, the use of the idea of the integrity of the pedagogical process as a system based on the theory of universal human values, principles of humanization and humanitarization of professional knowledge, person-oriented approach, the priority of subject-subject relations.

Differentially Private Recurrent Variational Autoencoder For Text Privacy Preservation

Deep learning techniques have been widely used in natural language processing (NLP) tasks and have made remarkable progress. However, training the deep learning model relies on a large amount of data which may involve sensitive information like electronic medical records. The attacker can infer sensitive information from the model, which leads to privacy leakage. To solve this problem, we propose a Differentially Private Recurrent Variational AutoEncoder (DP-RVAE) that can generate simulated data in place of the sensitive dataset to preserve privacy. To generate high utility synthetic text, a part of sensitive text data is employed as the conditional input of the model and uses a dropout and noise perturbing mechanism to preserve differential privacy. In addition, we expand the proposed DP-RVAE to a federated learning setting and design a novel training paradigm for NLP tasks. Specifically, DP-RVAE is deployed to the client-side to train and generate personalized text. These DP-RVAE models would be aggregated and updated through the Federated Optimisation (FedOPT) algorithm so that personal information can be well preserved. We evaluate our proposed DP-RVAE through a text classification task on the Tweets depression sentiment and IMDB reviews datasets. Our DP-RVAE achieves a higher average test accuracy by 5.90% and 3.94% compared to the typical centralized training and federated learning approach, respectively. We also perform the keywords inference attack experiment on the medical description dataset collected from the real world. Compared to the typical differentially private preserving approach, the DP-RVAE decreases by 15.2% in average attack accuracy. The experimental results demonstrate that DP-RVAE can be applied to the NLP models to leverage accuracy while preserving sensitive privacy.

Memory phase-specific genes in the Mushroom Bodies identified using CrebB-target DamID.

The formation of long-term memories requires changes in the transcriptional program and de novo protein synthesis. One of the critical regulators for long-term memory (LTM) formation and maintenance is the transcription factor CREB. Genetic studies have dissected the requirement of CREB activity within memory circuits, however less is known about the genetic mechanisms acting downstream of CREB and how they may contribute defining LTM phases. To better understand the downstream mechanisms, we here used a targeted DamID approach (TaDa). We generated a CREB-Dam fusion protein using the fruit fly Drosophila melanogaster as model. Expressing CREB-Dam in the mushroom bodies (MBs), a brain center implicated in olfactory memory formation, we identified genes that are differentially expressed between paired and unpaired appetitive training paradigm. Of those genes we selected candidates for an RNAi screen in which we identified genes causing increased or decreased LTM.

Virtual Reality in Preoperative Planning of Complex Cranial Surgery

Changing paradigms of neurosurgical training and limited operative exposure during the residency period have made it necessary to evaluate newer technologies for training. Virtual reality (VR) technology provides three-dimensional reconstruction of routine imaging, along with the ability to see as well as interact. The application of VR technology in operative planning, which is an important part of neurosurgical training, has been incompletely studied so far. Sixteen final-year residents, post-M.Ch. (magister chirurgiae) residents, and fellows were included as study participants. They were divided into 2 groups based on their seniority for further analysis. Five complex cranial cases were selected and a multiple-choice question-based test was prepared by the authors, with 5 questions for each of the cases. The pretest score was determined based on performance on the test after participants accessed routine preoperative imaging. The posttest score was calculated after use of the VR system (ImmersiveTouch VR System, ImmersiveTouch Inc.). Analysis was performed by the investigators, who were blinded to the identity of the participant. Subanalysis based on the type of case and type of question was performed. Feedback was obtained from each participant regarding VR use. There was an overall improvement in scores from pretest to posttest, which was also noted in the analysis based on the participants' seniority. This improvement was noted to be more for the vascular cases (15.89%) compared with the tumor cases (7.84%). Participants also fared better in questions related to surgical anatomy and surgical approach, compared with questions based on the diagnosis. There was overall positive feedback from participants regarding VR use, and most participants wanted VR to become a routine part of operative planning. Our study shows that there is improvement in understanding of surgical aspects after use of this VR system.

Robust Detection, Segmentation, and Metrology of High Bandwidth Memory 3D Scans Using an Improved Semi-Supervised Deep Learning Approach

Recent advancements in 3D deep learning have led to significant progress in improving accuracy and reducing processing time, with applications spanning various domains such as medical imaging, robotics, and autonomous vehicle navigation for identifying and segmenting different structures. In this study, we employ the latest developments in 3D semi-supervised learning to create cutting-edge models for the 3D object detection and segmentation of buried structures in high-resolution X-ray semiconductors scans. We illustrate our approach to locating the region of interest of the structures, their individual components, and their void defects. We showcase how semi-supervised learning is utilized to capitalize on the vast amounts of available unlabeled data to enhance both detection and segmentation performance. Additionally, we explore the benefit of contrastive learning in the data pre-selection step for our detection model and multi-scale Mean Teacher training paradigm in 3D semantic segmentation to achieve better performance compared with the state of the art. Our extensive experiments have shown that our method achieves competitive performance and is able to outperform by up to 16% on object detection and 7.8% on semantic segmentation. Additionally, our automated metrology package shows a mean error of less than 2 μm for key features such as Bond Line Thickness and pad misalignment.

Human-machine interface for two-dimensional steering control with the auricular muscles.

Human-machine interfaces (HMIs) can be used to decode a user's motor intention to control an external device. People that suffer from motor disabilities, such as spinal cord injury, can benefit from the uses of these interfaces. While many solutions can be found in this direction, there is still room for improvement both from a decoding, hardware, and subject-motor learning perspective. Here we show, in a series of experiments with non-disabled participants, a novel decoding and training paradigm allowing naïve participants to use their auricular muscles (AM) to control two degrees of freedom with a virtual cursor. AMs are particularly interesting because they are vestigial muscles and are often preserved after neurological diseases. Our method relies on the use of surface electromyographic records and the use of contraction levels of both AMs to modulate the velocity and direction of a cursor in a two-dimensional paradigm. We used a locking mechanism to fix the current position of each axis separately to enable the user to stop the cursor at a certain location. A five-session training procedure (20-30 min per session) with a 2D center-out task was performed by five volunteers. All participants increased their success rate (Initial: 52.78 ± 5.56%; Final: 72.22 ± 6.67%; median ± median absolute deviation) and their trajectory performances throughout the training. We implemented a dual task with visual distractors to assess the mental challenge of controlling while executing another task; our results suggest that the participants could perform the task in cognitively demanding conditions (success rate of 66.67 ± 5.56%). Finally, using the Nasa Task Load Index questionnaire, we found that participants reported lower mental demand and effort in the last two sessions. To summarize, all subjects could learn to control the movement of a cursor with two degrees of freedom using their AM, with a low impact on the cognitive load. Our study is a first step in developing AM-based decoders for HMIs for people with motor disabilities, such as spinal cord injury.

Towards a New Paradigm for Digital Health Training and Education in Australia: Exploring the Implication of the Fifth Industrial Revolution

Digital transformation, characterised by advanced digitalisation, blockchain, the Internet of Things, artificial intelligence, machine learning technologies, and robotics, has played a key role in revolutionising various industries, especially the healthcare sector. The adoption of and transition (from traditional) to new technology will bring challenges, opportunities, and disruptions to existing healthcare systems. According to the European Union, we must pursue both digital and green transitions to achieve sustainable, human-centric, and resilient industries to achieve a world of prosperity for all. The study aims to present a novel approach to education and training in the digital health field that is inspired by the fifth industrial revolution paradigm. The paper highlights the role of training and education interventions that are required to support digital health in the future so that students can develop the capacity to recognise and exploit the potential of new technologies. This article will briefly discuss the challenges and opportunities related to healthcare systems in the era of digital transformation and beyond. Then, we look at the enabling technologies from an Industry 5.0 perspective that supports digital health. Finally, we present a new teaching and learning paradigm and strategies that embed Industry 5.0 technologies in academic curricula so that students can develop their capacities to embrace a digital future and minimise the disruption that will inevitably accompany it. By incorporating Industry 5.0 principles into digital health education, we believe students can gain a deeper understanding of the industry and develop skills that will enable them to deliver a more efficient, effective, and sustainable healthcare system.

The state of the art exercise recommendations for older adults with cognitive impairments: A meta‐analysis of the meta‐analysis

AbstractBackgroundThere is accumulative evidence supporting the benefits of regular physical activity in improving cognition in older adults with cognitive impairments (OAwCIs). In the past decades, multiple meta‐analyses (MA) have been published, adding to the body of literature. However, there is limited information on the overall quality and synthesized results of these studies. Thus, initiating an umbrella review, our review synthesis team appraised the evidence generated from the meta‐analysis reviews that included randomized exercise trials for OAwCIs.MethodUpon completing the Prospero registration (ID:109720), we followed the PRISMA guidelines for reviews and performed a literature search up to January 1, 2022 to identify all published meta‐analyses which used randomized controlled trial (RCT) design. Once all potential studies were identified, three reviewers screened and reviewed studies to identify included studies, three reviewers collected and validated the data, and two reviewers assess risk of bias using the AMSTAR 2. After applying the study’s a priori inclusion and exclusion criteria, we quantitatively analyzed the effects of exercise on cognitive performance in OAwCIs.ResultOver 2000 studies were screened for inclusion, 21 MA studies met our inclusion criteria. Based on the AMSTAR 2, three studies were high quality, nine studies were moderate quality, and nine studies were low quality. The included MA evaluated 280 RCTs, which included 22,315 participants over the age of 65 years old diagnosed with mild cognitive impairment (MCI), dementia, or Alzheimer’s disease (AD). Combined exercise training paradigms averaged 188.48±40.72 minutes per week and lasted for 18.49±4.53 weeks. Exercise training significantly improved global cognitive function, with an effect size of 0.55 (95% CI = 0.36‐0.73)ConclusionSustained and prolonged exercise training (cardio endurance type) might provide an attractive and effective intervention for individuals with MCI and AD. This comprehensive umbrella review of meta‐analyses offers valuable and strong evidence‐based exercise recommendations for OAwCIs.

FedDM: Federated Weakly Supervised Segmentation via Annotation Calibration and Gradient De-Conflicting.

Weakly supervised segmentation (WSS) aims to exploit weak forms of annotations to achieve the segmentation training, thereby reducing the burden on annotation. However, existing methods rely on large-scale centralized datasets, which are difficult to construct due to privacy concerns on medical data. Federated learning (FL) provides a cross-site training paradigm and shows great potential to address this problem. In this work, we represent the first effort to formulate federated weakly supervised segmentation (FedWSS) and propose a novel Federated Drift Mitigation (FedDM) framework to learn segmentation models across multiple sites without sharing their raw data. FedDM is devoted to solving two main challenges (i.e., local drift on client-side optimization and global drift on server-side aggregation) caused by weak supervision signals in FL setting via Collaborative Annotation Calibration (CAC) and Hierarchical Gradient De-conflicting (HGD). To mitigate the local drift, CAC customizes a distal peer and a proximal peer for each client via a Monte Carlo sampling strategy, and then employs inter-client knowledge agreement and disagreement to recognize clean labels and correct noisy labels, respectively. Moreover, in order to alleviate the global drift, HGD online builds a client hierarchy under the guidance of history gradient of the global model in each communication round. Through de-conflicting clients under the same parent nodes from bottom layers to top layers, HGD achieves robust gradient aggregation at the server side. Furthermore, we theoretically analyze FedDM and conduct extensive experiments on public datasets. The experimental results demonstrate the superior performance of our method compared with state-of-the-art approaches. The source code is available at https://github.com/CityU-AIM-Group/FedDM.

A Reinforcement Learning Paradigm for Cybersecurity Education and Training

Reinforcement learning (RL) is a type of ML, which involves learning from interactions with the environment to accomplish certain long-term objectives connected to the environmental condition. RL takes place when action sequences, observations, and rewards are used as inputs, and is hypothesis-based and goal-oriented. The key asynchronous RL algorithms are Asynchronous one-step Q learning, Asynchronous one-step SARSA, Asynchronous n-step Q-learning and Asynchronous Advantage Actor-Critic (A3C). The paper ascertains the Reinforcement Learning (RL) paradigm for cybersecurity education and training. The research was conducted using a largely positivism research philosophy, which focuses on quantitative approaches of determining the RL paradigm for cybersecurity education and training. The research design was an experiment that focused on implementing the RL Q-Learning and A3C algorithms using Python. The Asynchronous Advantage Actor-Critic (A3C) Algorithm is much faster, simpler, and scores higher on Deep Reinforcement Learning task. The research was descriptive, exploratory and explanatory in nature. A survey was conducted on the cybersecurity education and training as exemplified by Zimbabwean commercial banks. The study population encompassed employees and customers from five commercial banks in Zimbabwe, where the sample size was 370. Deep reinforcement learning (DRL) has been used to address a variety of issues in the Internet of Things. DRL heavily utilizes A3C algorithm with some Q-Learning, and this can be used to fight against intrusions into host computers or networks and fake data in IoT devices.

Dictionary-enabled efficient training of ConvNets for image classification

Convolutional networks (ConvNets) are computationally expensive but well known for their performance on image data. One way to reduce their complexity is to explore inherited data sparsity. However, since the gradients involved in ConvNets require dynamic updates, applying data sparsity in the training step is not straightforward. Dictionary-based learning methods can be useful since they encode the original data in a sparse form. This paper proposes a new dictionary-based training paradigm for ConvNets by exploiting redundancy in the training data while keeping the distinctive features intact. The ConvNet is then trained on the reduced, sparse dataset. The new approach significantly reduces the training time without compromising accuracy.To the best of our knowledge, this is the first implementation of ConvNet on dictionary-based sparse training data. The proposed method is validated on three publicly available datasets –MNIST, USPS, and MNIST FASHION. The experimental results show a significant reduction of 4.5 times in the overall computational burden of vanilla ConvNet for all the datasets. Whereas the accuracy is intact at 97.21% for MNIST, 96.81% for USPS, and 88.4% for FASHION datasets. These results are comparable to state-of-the-art algorithms, such as ResNet-{18,34,50}, trained on the full training dataset.

A Scoping Review of Simulation-Based Training Paradigms for Carotid Artery Endarterectomy and Carotid Artery Stenting

Surgical simulation has come to the forefront to enhance the training of residents. The aim of our scoping review is to analyze the available simulation-based carotid revascularization techniques, including carotid endarterectomy (CEA) and carotid artery stenting (CAS) and suggest critical steps for evaluating competency in a standardized fashion. A scoping review of all reports on simulation-based carotid revascularization techniques including CEA and CAS was performed in PubMed/MEDLINE, Scopus, Embase, Cochrane, Science Citation Index Expanded, Emerging Sources Citation Index, and Epistemonikos databases. Data were collected according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. The English language literature was searched from January 1, 2000 to January 9, 2022. The outcomes evaluated included measures of assessment of operator performance. Five CEA and 11 CAS manuscripts were included in this review. The methods of assessments employed by these studies to judge performance were comparable. The 5 CEA studies sought to validate and demonstrate improved performance with training or distinguish surgeons by their experience level, either through assessing operative performance or end-product results. The 11 CAS studies used 1 of 2 types of commercial simulators and focused on determining the efficacy of simulators as teaching tools. By examining the steps of the procedure associated with preventable perioperative complications, it provides a reasonable framework for determining which elements of the procedure should be emphasized most. Furthermore, using potential errors as a basis for assessment of competency could reliably distinguish operators based on level of experience. Competency-based simulation training is becoming more relevant as our surgical training paradigm shifts with the increased scrutiny within training programs of work-hour regulations and the need to develop a curriculum to assess our trainees' ability to perform specific operations competently during their stipulated training period. Our review has given us an insight into the current efforts in this space regarding 2 specific procedures that are key for all vascular surgeons to master. Although many competency-based modules are available, there is a lack of standardization in the grading/rating system of what surgeons consider vital steps of each procedure to assess these simulation-based modules. Therefore, the next steps of curriculum development should be based on standardization efforts for the different protocols available.

Gender Differences in Perceptions and Attitudes Toward Vascular Surgery Among Prospective Preclinical Medical Students

Women account for approximately 15% of the vascular surgery workforce, yet represent 50% of all medical school matriculants. Despite a focus on increasing diversity among vascular surgeons, gender disparities in vascular surgery persist. In order to encourage increased representation of women entering vascular specialties, efforts have been made at the national level to create programs for mentorship and leadership development; however, efforts to increase awareness of vascular surgery at early stages of training have been limited. We aimed to characterize the attitudes and perceptions of prospective female vascular trainees in the preclinical phase of medical school. A panel hosted virtually by the Vascular and Endovascular Surgical Society National Vascular Surgery Interest Group (VSIG) was held to introduce the field of vascular surgery to prospective medical students with limited exposure to vascular surgery. Attendees to this event were asked to complete an anonymous survey prior to the start of the panel. Student t test and χ2 test were used to compare survey responses by gender. Out of the 114 attendees, there were 52 responses to the survey. Women made up 48.1% of respondents and were first (44.0%) and second year (56.0%) medical students. There were a similar number of Asian and White respondents of both genders; however, there were fewer women who identified as Black or Hispanic as compared to men (8.0% vs 14.8%; P < .001) (Table I). A greater number of men were interested in vascular surgery as compared to women (48.1% vs 36.0%; P < .001) at the time of the survey; however, women were more likely to be interested in other surgical specialties (ENT, orthopedics, cardiothoracic surgery, ophthalmology) (Table I). Female respondents were significantly less interested in the 5+2 vascular surgery training paradigm as compared to male respondents (P = .012) (Table II). A greater percentage of women reported that they did not have a VSIG at their home institution (32.0% vs 14.8%; P < .001) (Table I). Female respondents had similar interest in integrated vascular surgery programs as male counterparts, but were less interested in the 5+2 training paradigm. With the expansion of integrated programs, students may be encouraged to commit to a specialty earlier in training; however, female respondents were less likely to have a VSIG to facilitate early introductions to vascular surgery. These results highlight the need for early recruitment strategies toward women and an increased focus on establishing VSIGs at institutions.Table IDemographics and perceptions of available National Vascular Surgery Interest Group (VSIG)Female (n = 25)Male (n = 27)P valueYear<.001 MS111 (44.0)12 (44.4) MS214 (56.0)7 (25.9) MS30 (0)5 (18.5) MS40 (0)2 (7.4) Other0 (0)1 (3.7)Program<.001 MD23 (92.0)26 (96.3) DO1 (4.0)0 (0) IMG1 (4.0)1 (3.7)Geographic location<.001 International2 (8.0)4 (14.8) Midwest8 (32.0)10 (37.0) Northeast6 (24.0)9 (33.3) South2 (8.0)1 (3.7) West7 (28.0)3 (11.1)Race<.001 White12 (48.0)12 (44.4) Black1 (4.0)2 (7.4) Asian10 (40.0)11 (40.7) Hispanic1 (4.0)2 (7.4) Other1 (4.0)0 (0)Specialty choice<.001 Cardiothoracic surgery2 (8.0)1 (3.7) Cardiology1 (4.0)2 (7.4) Emergency medicine0 (0)1 (3.7) ENT2 (8.0)0 (0) General surgery4 (16.0)6 (22.2) Internal medicine1 (4.0)1 (3.7) Interventional radiology0 (0)1 (3.7) Ophthalmology1 (4.0)0 (0) Orthopedic surgery1 (4.0)0 (0) Pediatrics0 (0)1 (3.7) Vascular surgery9 (36.0)13 (48.1) Undecided4 (16.0)1 (3.7)Active VSIG at home institution19 (76.0)13 (61.9)0.301VSIG was first introduction to vascular surgery?<.001 Yes11 (44.0)12 (44.4) No6 (24.0)11 (40.7) No VSIG available8 (32.0)4 (14.8)VSIG provides adequate information to gain exposure to vascular surgery?<.001 Yes12 (48.0)14 (51.9) No1 (4.0)4 (14.8) Neutral5 (20.0)5 (18.5) No VSIG available7 (28.0)4 (14.8)Values are number (5). Open table in a new tab Table IIAttitudes and perceptions toward vascular surgery (Likert scale format 0-5)Female (n = 25)Male (n = 27)P valueFamiliarity with vascular surgery3.04 (1.02)3.37 (1.18).287Interest in vascular surgery4.04 (0.79)3.96 (0.71).712Interest in applying integrated vascular surgery program3.52 (0.96)3.52 (1.31).996Interest in applying 5+2 vascular surgery program3.00 (0.96)3.22 (1.05).012Comfort with reaching out to possible mentors3.84 (0.90)3.96 (1.09).661Understanding of pathways to becoming a vascular surgeon3.28 (1.24)3.44 (1.58).68Understanding of avenues to get involved in vascular surgery2.63 (1.01)3.15 (1.38).133Understanding of typical work week of vascular surgeon2.38 (1.10)2.67 (1.14).358Value are mean (SD). Open table in a new tab

Perceptions of the Shared Learning Environment by Vascular and General Surgery Residents

Perceptions of the Shared Learning Environment by Vascular and General Surgery Residents

Modernizing patient-centered manual therapy: Findings from a Delphi study on orthopaedic manual therapy application

BackgroundRecent literature challenges the process by which orthopaedic manual therapy (OMT) has traditionally been applied. Progressive understanding of the complexities surrounding OMT analgesia and the decreased reliance on technique specific characteristics in determining treatment effectiveness promotes an update to training paradigms related to OMT. Objectives: The purpose of this Delphi study was to establish consensus on what trainees should be focusing on when demonstrating OMT techniques and how candidates for OMT should be identified. DesignAn international three-round Delphi study following recommended guidelines for conducting and reporting of Delphi studies (CREDES) was performed. MethodsOne-hundred sixty-four expert manual therapy educators were identified for participation across four countries. Participants were asked to provide what concepts trainees should be focusing on when demonstrating OMT techniques and how candidates for OMT should be identified. Twenty-one themes were identified for each question. ResultsTwenty-eight participants completed all three rounds of the Delphi. Consensus was reached on nineteen themes and eighteen themes respectively. Results from this Delphi stress patient-centered care within a biopsychosocial pain management model. Representation across all pillars of evidence-based practice were represented. Themes reaching consensus within this study favored the importance of neurophysiological, psychological, and biomechanical principles. ConclusionThis Delphi presents consensus-based recommendations for what manual therapy trainees should focus on when demonstrating OMT techniques and on how candidates for OMT should be identified. These findings in collaboration with previous consensus recommendations on concepts to focus on within OMT education promote restructuring of OMT curriculum to evidence-based patient-centered care models.

SP34. Development of Sutureless Vaso-Lock for Vascular Anastomosis

PURPOSE: Micro- and macrovascular anastomoses involve suturing together of blood vessels, which is a critical foundational surgical skill. However, it faces many challenges, such as decade-long training and inherent dexterity of the surgeon. Procedures are long and expensive, require specialized operating rooms and equipment, making them prohibitive in many hospitals. Our team has created a unique anastomotic device, Vaso-Lock, as a sutureless coupler. Vaso-Lock is intraluminal, holding free vessel ends together with traction by anchors. We aim to apply Vaso-Lock to change the paradigm of surgical training and practice, and improve technical capabilities for vascular anastomosis. METHODS: We have utilized 3D-printing to prototype Vaso-Locks with quick design adjustments. Vaso-Lock maintained its intact structure after ethylene oxide sterilization, which was evaluated by scanning electron microscope. Vaso-Lock was deployed in a porcine model for anastomosis of common carotid artery and internal jugular vein. Doppler ultrasound was used to longitudinally assess patency, blood flow velocities, and lumen preservation. Histological studies were performed to evaluate endothelialization and device-vessel interface biocompatibility. RESULTS: Vaso-Lock maintained anastomosis of common carotid artery to internal jugular vein in 3 porcine, with no evidence of leakage after deployment. Doppler ultrasonography demonstrated the mixture of arterial and venous blood inside the Vaso-Lock. During the extraction of Vaso-Lock, no blood clots were identified at the anastomosis site. Guidewire went through the explanted blood vessels anastomosed by the Vaso-Lock without resistance. In terms of histological analysis, we performed four types of staining: H&E, Masson’s Trichrome (blue for collagen), Verhoeff-Van Gieson (black for elastin), and Alizarin Red (red for calcium). All tissue sections with Vaso-Locks displayed open lumen at the anastomosis site. Inflammation cells, along with collagen bundles, appeared around anchors of the Vaso-Lock. Calcium was identified around the Vaso-Lock at 2-week. Intimal growth occurred under the Vaso-Lock at 6-week. We are examining the effect of Vaso-Lock on cellular structure of the blood vessel by immunohistochemistry. We are also evaluating heparinized Vaso-Lock in terms of its long-term patency and biocompatibility. CONCLUSIONS: Vaso-Lock maintained patency at least 6 weeks for arteriovenous anastomosis along with a natural healing response in a porcine model. This novel device will dramatically enhance the efficiency with an assortment of micro- and macrovascular anastomoses ranging from tissue flaps to arteriovenous fistula creations, making anastomosis globally available.

Modelling Microglial Innate Immune Memory In Vitro: Understanding the Role of Aerobic Glycolysis in Innate Immune Memory.

Microglia, the resident macrophages of the central nervous system, play important roles in maintaining brain homeostasis and facilitating the brain's innate immune responses. Following immune challenges microglia also retain immune memories, which can alter responses to secondary inflammatory challenges. Microglia have two main memory states, training and tolerance, which are associated with increased and attenuated expression of inflammatory cytokines, respectively. However, the mechanisms differentiating these two distinct states are not well understood. We investigated mechanisms underlying training versus tolerance memory paradigms in vitro in BV2 cells using B-cell-activating factor (BAFF) or bacterial lipopolysaccharide (LPS) as a priming stimulus followed by LPS as a second stimulus. BAFF followed by LPS showed enhanced responses indicative of priming, whereas LPS followed by LPS as the second stimulus caused reduced responses suggestive of tolerance. The main difference between the BAFF versus the LPS stimulus was the induction of aerobic glycolysis by LPS. Inhibiting aerobic glycolysis during the priming stimulus using sodium oxamate prevented the establishment of the tolerized memory state. In addition, tolerized microglia were unable to induce aerobic glycolysis upon LPS restimulus. Therefore, we conclude that aerobic glycolysis triggered by the first LPS stimulus was a critical step in the induction of innate immune tolerance.

Being an Emotionally Intelligent Leader through the Nine-Layer Model of Emotional Intelligence—The Supporting Role of New Technologies

Several years ago, a characteristic of leadership was the intelligence index, but in recent years this has changed, and emotional intelligence is considered an important parameter for a leader. A leader who shows a high index of emotional intelligence can activate his/her human potential and subsequently others. There is a large body of literature on “what” great leaders should do, but more emphasis needs to be placed on “how” to develop such leaders by focusing on detailed individual behavior change and self-development. The current article aims to investigate the concept of emotional intelligence and describe the levels of the emotional intelligence pyramid model and how these are reflected in the role of leadership. The theoretical model is complemented by a set of metacognitive and metaemotional strategies while emphasizing the role of technologies to provide fertile ground for the implementation of emotional intelligence skills in leadership. The strategies framework provides a training paradigm for implementation in education and working environments. The results of this article provide a new theoretical framework of the emotional skills a leader must possess, and they also provide a useful framework for cultivating them, which will promote long-term human capital development and help everyone achieve educational and professional success. The pyramid model of emotional intelligence and its strategies can have practical applications in any form of leadership, as research has shown a positive correlation between these two concepts.

Task-specific modulation of corticospinal neuron activity during motor learning in mice

Motor skill learning relies on the plasticity of the primary motor cortex as task acquisition drives cortical motor network remodeling. Large-scale cortical remodeling of evoked motor outputs occurs during the learning of corticospinal-dependent prehension behavior, but not simple, non-dexterous tasks. Here we determine the response of corticospinal neurons to two distinct motor training paradigms and assess the role of corticospinal neurons in the execution of a task requiring precise modulation of forelimb movement and one that does not. In vivo calcium imaging in mice revealed temporal coding of corticospinal activity coincident with the development of precise prehension movements, but not more simplistic movement patterns. Transection of the corticospinal tract and optogenetic regulation of corticospinal activity show the necessity for patterned corticospinal network activity in the execution of precise movements but not simplistic ones. Our findings reveal a critical role for corticospinal network modulation in the learning and execution of precise motor movements.

ITACA: An open-source framework for Neurofeedback based on Brain–Computer Interfaces

Background and objective:Neurofeedback (NF) is a paradigm that allows users to self-modulate patterns of brain activity. It is implemented with a closed-loop brain–computer interface (BCI) system that analyzes the user’s brain activity in real-time and provides continuous feedback. This paradigm is of great interest due to its potential as a non-pharmacological and non-invasive alternative to treat non-degenerative brain disorders. Nevertheless, currently available NF frameworks have several limitations, such as the lack of a wide variety of real-time analysis metrics or overly simple training scenarios that may negatively affect user performance. To overcome these limitations, this work proposes ITACA: a novel open-source framework for the design, implementation and evaluation of NF training paradigms. Methods:ITACA is designed to be easy-to-use, flexible and attractive. Specifically, ITACA includes three different gamified training scenarios with a choice of five brain activity metrics as real-time feedback. Among them, novel metrics based on functional connectivity and network theory stand out. It is complemented with five different computerized versions of widespread cognitive assessment tests. To validate the proposed framework, a computational efficiency analysis and an NF training protocol focused on frontal-medial theta modulation were conducted. Results:Efficiency analysis proved that all implemented metrics allow an optimal feedback update rate for conducting NF sessions. Furthermore, conducted NF protocol yielded results that support the use of ITACA in NF research studies. Conclusions:ITACA implements a wide variety of features for designing, conducting and evaluating NF studies with the goal of helping researchers expand the current state-of-the-art in NF training.