Traumatic encephalopathy syndrome (TES) is used to describe the clinical manifestations of chronic traumatic encephalopathy (CTE). However, effective treatment and prevention strategies are lacking. Increasing evidence has shown that rehabilitation training could prevent cognitive decline, enhance brain plasticity, and effectively improve neurological function in neurodegenerative diseases. Therefore, the mechanisms involved in the effects of rehabilitation exercise therapy on the prognosis of CTE are worth exploring. The aim of this article is to review the pathogenesis of CTE and provide a potential clinical intervention strategy for CTE. In recent years, the concept of traumatic encephalopathy syndrome (TES) has been proposed to describe the clinical manifestations of CTE. TES is a progressive process in which patients present with cognitive dysfunction and neurobehavioral disorders  is an important protein for the growth and development of neurons and the implementation of various activities . APP processing pathways are generally divided into the amyloid pathway (mediated by secretary enzyme β and γ) and non-amyloid (mainly mediated by secretary enzyme α) -mediated AKt/PK pathway  (Gardner and Yaffe It is important to note that different types of rehabilitation exercise, such as aerobic exercise or resistance exercise, as well as the time, intensity and frequency of rehabilitation exercise, often have different effects on the mitigation of neurological diseases. Therefore, follow-up studies are needed to determine the most effective rehabilitation exercise treatment strategy for CTE. In addition, it is necessary to develop personalized strategies for patients with different behavioral abilities in the clinical implementation process to facilitate the smooth development of treatment. For some patients with obvious cognitive impairment, cognitive rehabilitation may be more conducive to symptom relief and progress. At present, there are still few studies on drug development targeting the pathological mechanism of CTE, most of which focus on immunotherapy to slow down P-tau deposition. The therapeutic targets of other pathogenic pathways remain to be discovered, and the therapeutic effects of rehabilitation therapy for CTE, including rehabilitation exercise, still need to be further verified although they have good prospects.The clinical syndrome of CTE, TES, begins early in injury and is difficult to relieve with existing means. This article reviews the potential mechanism of physical rehabilitation exercise in the treatment of CTE from various aspects, aiming to explore the prospect of rehabilitation exercise, an effective and easy-to-implement treatment, for the application of CTE.Further research into the neuropathology of CTE patients is needed, as it can provide valuable information for the development of disease biomarkers and the evaluation of potential treatments. In addition, the impact of rehabilitation exercises on brain health in CTE patients that needs to be validated is important for improving our understanding of the mechanisms of neurodegenerative diseases, and the search for the most appropriate exercise strategy for CTE patients should continue, which may be a promising area of research in the future.


The number of spinal cord injury (SCI) patients is gradually increasing in India. But due to the unavailability of rehabilitation facilities at the grass root level and most of the patient's financial status, institution-based SCI rehabilitation is still not feasible for many of SCI patients. Tele-rehabilitation can help to rehabilitate the SCI patients to a satisfactory extent where providing hospital-based rehabilitation is not possible. During the COVID-19 pandemic, tele-rehabilitation showed its true potential already. Poverty, lack of education, and lack of technical knowledge of the patients can be a major barrier to its implication. However, with the government’s support, suitable manpower, and will to serve, we can deliver tele-rehabilitation services for SCI patients in the remotest and poorest areas of India. The burden of spinal cord injury patients and gap in rehabilitationBased on projections of the latest United Nations data and various International databases, India has now become the most populous country in the world with a population of over 1.42 billion. The incidence of spinal cord injury (SCI) is 9.3-56.1 per million globally depending upon multiple factors [Scope of tele-rehabilitation in IndiaTele-rehabilitation is providing rehabilitation services to patients at their convenient location  through modern communication technologies like telephone, video conferencing, social networks, and other platforms. Laptops, computers, smartphone, wearable devices, webcams, etc. are few necessary devices to deliver it properly. Tele-rehabilitation consists of different aspects of rehabilitation like assessment, management, monitoring, education, and prevention. It provides better accessible rehabilitation allowing the communication and transfer of knowledge between patients, doctors, professionals, and caregivers . With thHow can tele-rehabilitation help the patients with spinal cord injury?Successful SCI rehabilitation depends on the patient and caregiver’s knowledge and practice. Tele-rehabilitation offers benefit to SCI patients irrespective of the neurological level, stage, and duration of SCI (acute/sub-acute/chronic). Basic things like the positioning of the patient, mattress or cushion type, pressure relieving methods, pressure injury prevention methods, nutritional knowledge, etc. can be easily taught. Scheduled defecation and voiding, assisted defecation, cleaning of the catheter (intermittent catheter), care of catheter, maintaining perineal hygiene, dressing of ulcer, basic physiotherapy and occupational therapy, etc. related advice can be delivered to the patient and his/her caregiver through video conferencing easily. Identification of danger signs of autonomic dysfunction, deep vein thrombosis, respiratory infection, etc. can be done through the use of telemedicine.For previous recipients of hospital-based rehabilitation, new emergence of complication can be dealt up to some extent. Besides communication-related technologies can be used for providing different home and lifestyle modification-related advices. Social reintegration tips, vocational rehabilitation advices, psychologist's counseling, dietician's counseling, etc. are feasible through tele-rehabilitation. In a nutshell, it is possible to assess a SCI patient through tele-rehabilitation along with delivery of prevention and management related advices, education, and counseling -5.The SAre we ready for the tele-rehabilitation of spinal cord injury patients?Though tele-rehabilitation has notable positive aspects in SCI rehabilitation, its implication in India is not at satisfactory level yet. Most of the government and private infrastructure lack proper rehabilitation units for SCI patients, let alone tele-rehabilitation services. Due to financial bindings, most patients from rural areas do not have smartphones or other smart devices, or stable internet connections. Moreover, poor literacy and a lack of minimal awareness of technology can cause hindrances to the successful application of tele-rehabilitation .GovernmConclusionAs per the author’s experience and present evidence, hospital-based rehabilitation cannot be replaced by tele-rehabilitation in case of SCI. But the major advantage of tele-rehabilitation is superior reach, feasibility, and ease of monitoring. In a country like India, it is the only way to reach each corner. Though the concept of tele-rehabilitation is still in emerging state in India, but with present technology, economic, and literacy growth, it is not an impossible task. With rising numbers of SCI patients, tele-rehabilitation facilities should be developed with priority.


American football games attract significant worldwide attention every year. Identifying players from videos in each play is also essential for the indexing of player participation. Processing football game video presents great challenges such as crowded settings, distorted objects, and imbalanced data for identifying players, especially jersey numbers. In this work, we propose a deep learning-based player tracking system to automatically track players and index their participation per play in American football games. It is a two-stage network design to highlight areas of interest and identify jersey number information with high accuracy. First, we utilize an object detection network, a detection transformer, to tackle the player detection problem in a crowded context. Second, we identify players using jersey number recognition with a secondary convolutional neural network, then synchronize it with a game clock subsystem. Finally, the system outputs a complete log in a database for play indexing. We demonstrate the effectiveness and reliability of player tracking system by analyzing the qualitative and quantitative results on football videos. The proposed system shows great potential for implementation in and analysis of football broadcast video. With more sophisticated developments in data analysis and storage, there has been significant growth in the demand for data-intensive analytic applications in American football.American football is one of the most popular sports worldwide. The 2022 Super Bowl had 99.18 million television viewers in the US and 11.2 million streaming viewers around the world2 and the National Collegiate Athletics Association (NCAA)3 publish statistical guidance manuals that fully and thoroughly document various types of plays so that when individual games are logged play-by-play, the statisticians and loggers are following standardized play definitions, including how to account for the game clock time that has elapsed during individual play occurrences so that there is no overlapping game clock data across two or more plays.Player identification is a standard way of interpreting sports videos and helping commentators explain games on television. Different from other sports, game interpreting and data analytics in American football are largely based on the concept of play. The plays of an American football game can be represented as a sequence of non-overlapping time segments of a running game clock that generally start with the movement of the ball from the center offensive lineman called the “snap”, and end immediately at the time of each play’s conclusion. American football leagues at several levels of competition such as the National Football League (NFL)4.Player identification facilitates the comprehensive indexing of game videos based on player participation per play. However, in order to meet this demand, data analysis methods need to be specifically designed in comparison with traditional manual methods. Such traditional methods are time-consuming and impractical for handling a large number of football games recorded today. Recent advances in image processing techniques have opened the door for many interesting and effective solutions to this problem. Player identification can be classified into two main categories: Optical Character Recognition (OCR) based and Convolution Neural Networks (CNN) based approaches5. In another example6, bounding boxes of players were extracted by a deformable part model detector, then performed OCR and classification. However, deep learning models have been shown to provide greater capacity in object detection tasks and present more accurate results7.Before deep learning became popular, OCR-based approaches segmented images into HSV color space and classified numbers based on segmentation results8 detected players by the histogram of oriented gradients and a linear support vector machine (SVM) and classified player numbers within a bounding box by training a deep convolutional neural network. There are efforts12 in exploring jersey number recognition by adopting various deep learning models. Gaussian Mixture Model (GMM) is utilized in13 for background subtraction to locate moving foreground objects from the static background and to detect moving players from the field. In14, mask R-CNN and YOLOv2 were compared for player detection using the pre-trained models because of a lack of annotated data. Liu et al.15 proposed a player detection system in basketball using motion detection algorithms. Deep learning approach was used to analyze cricket batting16. Key methods for analyzing cricket batting are also explored17 through key event detection and event importance scoring. Similarly, an SVM classifier is employed in a few Khan et al. papers19 to detect scoreboxes in the video frames. The extracted features are used as input to the classifier, which learns to distinguish between scoreboxes and non-scorebox regions. Once a scorebox is detected, the method further localizes its position within the frame by refining the initial detection with contour analysis, template matching, or edge detection in order to accurately determine the precise boundaries of the scorebox. These localizations are also seen in Guo et al. Localization and Recognition paper20, where they utilize Scale-Invariant Feature Transform (SIFT)-based feature extraction, point matching for scoreboard localization, team recognition techniques for extracting scoreboard information, and post-processing steps to achieve accurate localization and recognition of scoreboards in sports videos. Advancements in computer vision and pattern recognition allow for specific bodily poses to be processed in a much more efficient and accurate manner21. Pose estimation is widely utilized to guide the player detection deep learning network25. Recent effort23 explored human body part cues and proposed a faster region-based convolution neural network (R-CNN) approach for player detection and number recognition, which works well when the player and number are shown clearly to camera but is not often the case for broadcast video. To address the player identification problems in broadcast video, Senocak et al.22 utilized body part features to design a system to recognize body representation at multi-scale and with enhanced accuracy. An adaptive real-time player segmentation approach26 was proposed by training a student network with the data annotated by a teacher network, which saves manual annotating. However, segmentation requires more computational resources, and the use of mask R-CNN causes degraded performance for complex scenarios.The CNN approach in10, basketball23 and soccer27. These studies are not focused on an in-depth analysis of football player detection. Football player identification is challenging due to the frequent clustering pattern of crowded players. Besides the exploration of player identification, specific player detection systems for football games have not been studied very extensively. To date, no database systems for automatic jersey number detection and player information indexing have been reported.Most of the existing sports analysis studies have focused on player detection in hockeyAlthough different player-detecting strategies have been explored in various sports, the achievement of fast and accurate player detection in American football remains elusive. A key element of a successful analysis system is detection accuracy. However, camera blur, player motion, and small targets pose many challenges to achieving satisfactory accuracy for player identification. In addition to player identification, complicated game clock management rules in American football also added challenges in indexing game logs.In comparison with most sport analysis tasks, players participating in football games are usually crowded together and are prone to occlusion. The size of players also varies significantly depending on their positions relative to the camera. The small size of objects increases the difficulty of identifying players. In addition, the instantaneous and rapid movement of the players can blur the image and distort their shape. Different poses during falling and stumbling can further make detection more challenging. A motion-based background subtraction method performs weakly on blurred and occluded objects. Classical object detection algorithms give unsatisfactory results when dealing with crowded settings because overlapping objects can lead to false negative predictions. Since useful information is ignored, sports analysis systems bring incomplete results that may mislead viewers.In this work, we develop an innovative football analysis system that automatically tracks players on a per-play basis and identifies any time the play clock is actuated during the game. The proposed system operates directly on the video footage and simultaneously extracts player information and game clock information on a frame-by-frame basis, while automatically generating logs for play indexing. Figure We propose, to our best knowledge, the first deep learning-based football analysis system for jersey number identification and logging.We devise a two-stage neural network to address player detection and jersey number recognition, respectively. The two-stage design highlights the player-related region for precise jersey number recognition. The first stage, a transformer design, addresses the issue of identifying a player in a crowded setting. The second stage further addresses the issue of data imbalance in jersey number identification.We build a database for play indexing. The system automatically extracts game clock information along with identified jersey numbers, making it possible to generate a game log for player indexing.We conduct experiments on American football videos. The mean average precision of our proposed system achieves We utilize a detection transformer-based network to detect players in a crowded setting and employ a focal loss-based network as a digit recognition stage to index each player given an imbalanced dataset. We then capture game clock data per play. The football analysis system outputs a database containing an index of each play in the game, as well as a list of quarters, game clock start/end times, and participating players. We summarize our contributions as: We propose an automated football analysis system to index each play in a game by quarter, game clock start/end time, and a list of participating players, as shown in Fig. 28 resizes input to 29 resizes input to 30 leads to an unsatisfactory performance for two aspects. First, multiple players are identified within a single bounding box, lacking capability to differentiate crowded players. Second, jersey number information are eliminated in downsized image, as limited number of pixels associated with a jersey number. It thus is prone to detection error. To address this issue, we propose a two-stage design to first highlight a player region and then zoom into the player region for jersey number recognition.We choose a two-stage object detection network to enhance the capability of small object-detection in high definition videos. In sports broadcasting and player identification, the input image is usually in high definition. Conventional object detection networks usually downsize an input image to a specific size, e.g. YOLO31, which can detect players within extremely crowded scenario in order to address the technical challenge caused by highly overlapped targets. The second subsystem processes the detected player proposals and identifies jersey numbers accordingly. The digit recognition subsystem is implemented using RetinaNet5032. The third subsystem extracts game clock information for play indexing. Because of the presence of rewinds and timeouts in the video, the exact timestamp of the game needs to be extracted from each frame. The subsystem operates on frame-by-frame basis to extract game clock time using the Tesseract for optical character recognition. Clock information gets filtered into plays, which provides additional information of the estimated time of each play within a game. Upon completing the three subsystems, the information discovered in the jersey number is further associated to a readable and comprehensive database indexed by its game clock timestamp.The overall flowchart consists of three subsystems of pattern recognition: player detection, jersey number recognition, and clock identification. For the first subsystem, we employ the Detection Transformer31 to address the player detection problem against crowded background settings.Two main challenges are presented for player detection. First, we use data augmentation to alleviate data variation caused by motion effects, such as blurry and distorted objects. Second, we employ DEtection TRansformer (DETR)33 to a portion of training images to create realistic motion-corrupted images. The training images are also scaled for data augmentation, as shown in Fig. To ensure our method is robust to frames that are motion-corrupted, we augment our training dataset with more instances having motion effects. Specifically, we apply a Gaussian filter34, DETR benefits from the bipartite matching and attention mechanism of the transformer encode-decode architecture35, and therefore it excels in solving the detection task within a crowded setting of a football game.Inspired by the transformer model in natural language processing, the player detection model is capable of identifying overlapped bounding boxes by reasoning their spatial relationships of those bounding boxes. Combining a set-based Hungarian loss which enables unique matching between predictions and ground-truth, DETR solves the set prediction problem with a transformer. Compared to conventional object detection methods, such as Faster R-CNN36, a conventional CNN backbone. The feature map is extracted from the input image, then augmented with a positional encoding and then fed into the transformer encoder. Each encoder layer has a multi-head self-attention module to explore the correlation within the input of each layer. For the transformer decoder, the learnable object queries pass through each decoder layer with a self-attention module to explore the relations within itself. In the decoder, another cross-attention module takes the key elements of the feature map from the encoder output as side input to let object queries cross-learn the features from the feature map. At the last step, a feed-forward network (FFN) is connected to each prediction from the decoder to predict the final class label, center coordinates, and dimensions of the bounding box. As in31, the loss function contains Hungarian loss and bounding box loss.The DETR framework in our implementation stems from ResNet5037 with focal loss design as the digit recognition step to alleviate the imbalance issue in the jersey number dataset.Jersey number recognition severely suffers from a data imbalance issue. Obtaining a balanced jersey number dataset with the jersey numbers from 1 to 99 requires a massive dataset for training. We propose to address this problem in two directions. First, rather than recognizing two-digit numbers, we strategically target single digit recognition, therefore dramatically reduce the demand for training data. Second, we employ RetinaNetWith our single digit problem formulation, the number of classes is reduced from 100 to 10. With this significant reduction in the number of classes, it is then possible to achieve accurate results with a training dataset at the thousand level. Although the distribution of the 10 classes may still be uneven, the data imbalance issue will be further addressed by focal loss.38. RetinaNet handles imbalance training classes better with the use of focal loss. Traditionally, class imbalance limits the performance of a classification model because most regions of an image can be classified as background and result in unhelpful contributions towards learning39. As a consequence, the gradient is overwhelmed and leads to degenerated models. Focal loss introduces a focusing parameter to cross entropy loss as defined by40:N denotes the number of classes; i belongs to a true label, otherwise is 0; i-th class; The jersey number recognition subsystem is applied to the detected players from the previous subsystem. Figure Game clock identification first extracts the game clock from the game video. Due to the rewinds and timeouts in the video, the exact timestamp of the game needs to be extracted from each frame. The subsystem then filters through the game clock data to derive individual play windows. It provides the information of the estimated start and end time of each play. The play windows feature the absolute range of frames for each play and are associated with the player detection subsystem to index the players present in each play.41, to build the main software used for game clock subsystem because the clock region location in broadcast video has a distinctive background and uniform font as shown in lower left of Fig. We choose a simple and fast solution, the Tesseract Optical Character Recognition (OCR)A play designation filter program is designed to sift through the text file and output play windows that contain the range of frames for each play. As shown in Fig. The database subsystem synchronizes the results from the game clock and player identification subsystems, and writes the results into a readable format. In addition to the input from the two subsystems, there are two additional inputs that we consider as prior knowledge: team jersey color and team roster.x axis of the color histograms of images is the intensity from 0 to 255, and the y axis is the number of occurrences of that intensity. As an example of the red team player, the red channel intensity value is much higher than blue and green on average. Validation on a large number of red team jersey images analyzed in a similar manner agrees with the observation that the red intensity value is consistently much higher. On the other hand, a white jersey from the other team is hypothesized to show no dominant color channel. As shown in the corresponding color histogram, the white jersey has no dominant color channel. For the other jersey colors, a color filtering method can be easily generalized. Finally, jersey numbers are converted to the names of the players by roster.Home and away team players are categorized by color filtering. Different features of a color histogram are used to differentiate teams. As examples shown in Fig. 34. With each model, we empirically set the IoU to 0.75 to extract the detected bounding box. We compute the Average Precision (AP) and Average Recall (AR) of IoU and different sized objects. The size of small object is from 31 and further train the DETR with ResNet50 as backbone for 500 epochs until it converges using our football players dataset. For comparison, the pretrained Faster R-CNN with ResNet-50 backbone was trained on our dataset for 10,000 epochs until it converged. For each training epoch, we used a batch size of 2, learning rate of In our experiments, we compare the performance of our player detection subsystem with a base line model: Faster R-CNN with ResNet50 backbone32. All images are padded with zeros to avoid distortion. The model was trained for 20,000 epochs with a learning rate of To evaluate the jersey number recognition subsystem, we trained the RetinaNet convolutional neural network with a pretrained weight from Model Zoo datasetFor the game clock subsystem, after clock information is extracted by the OCR, we set the condition for play switching as the period of 40 s of the game clock or the period of 5 s of the snap clock. We test the subsystem with game footage, and three evaluation criterion: the accuracy of the OCR, quarter transition and start/end time of each play. All experiments were carried out in parallel on four Quadro RTX 6000 GPUs.We validated our player detection subsystem using 10 highlight videos from Alabama Crimson Tide football game footages in season 2021–2022. As a proof of concept, we choose highlighted footage which are free of distractions caused by graphics and other media found in full-length footage. The videos are in standard high-definition (HD) display resolution of 1280 × 720 pixels. Frames captured from the video at 30 frames per second, 2866 of which are further filtered out for training and testing. To make sure the training and testing data are independent to each other, 2198 frames from 9 game videos are used for training; 668 frames from another game video are used for testing. For data augmentation, one copy of each image is given a motion-blurry effect. Therefore, the training set contains 4396 frames after augmentation, as examples shown in Fig. In the digit recognition subsystem, 4865 player proposals with visible jersey numbers from two Alabama Crimson Tide football game footages are manually labeled. Lastly, two copies of each image are created. One copy is a scaled version, and the other is a motion blurred version, which brings the final image count to 14,595, with 9730 of the images being augmented copies.IoU from 0.5 to 0.95 with step size of 0.05. We perform both quantitative and qualitative comparison with Faster R-CNN in AP and AR of objects with small size and large size, respectively. The results show that DETR delivered better performance in an extremely crowded setting. With an IoU of 0.5, the average precision is We quantitatively analyze the performance of the player detection subsystem. As shown in Table To analyze the performance qualitatively, we list 3 representative images and their test results using different models. Figure To further validate the robustness of our propose framework, we test the player detection framework in other two football matches in a different season, 2022–2023: Alabama vs Texas A &M and Alabama vs Auburn. The precision, recall, and F1 scores are reported in Table The final break-down and distribution of the jersey number dataset is shown in Fig. In Fig. Evaluation results are shown in Table In full game footage, the reset of the play clock can be used to track the end and subsequent start of each play. Although there are no standards for the end and start of a play in accelerated footage, it is possible to start a new play based on the jump in the play clock.We present a screenshot of data format in the integrated database in Fig. In this paper, we propose an automatic analysis system for American football game based on deep learning. The experimental results demonstrate robustness in handling crowded scenarios and the capability to alleviate data imbalance issues. The proposed end-to-end system delivers complete detecting information using a single pass of football game footage. The uniquenesses of the proposed work are as follows. First, the proposed work gives a complete solution of player detecting and logging in the American football game, and provides expertise in handling the crowded setting of the football game. Currently, there is a lack of research on automatic analysis systems for American football game. Second, the proposed dataset uses bounding box labels solely, without other labeling requirement, such as human body labels. Therefore, the proposed system could be more generalizable with less labor needed.42. The information on the players’ positions could be incorporated into the jersey number recognition. For example, if the center is number 50, the wide receiver cannot also be number 50, so it may help to eliminate confusion between numbers. In addition, We will explore the possibility of identifying complicated human actions43 from football video. Very small objects could be detectable by using ultra-high resolution camera or in combination with a super resolution method. Ball tracking could be fused to the current design and serves as complimentary information towards game clock logging, therefore helping with dividing the plays. The user interface that outputs the database will be further improved by developing a more robust graphic user interface. In addition, the framework is validated in highlight video in this study. To make the framework applicable to full match, we plan to integrate proposed framework with audio detection on whistle. We will use the occurrence of whistle as landmark to divide full match video into game-related contents, the later of which could be directly processed by proposed method.For the future work, we plan to enhance the player detection by integrating information through consecutive frames and replenishing the players whose jersey numbers are not visible in some frames due to movement. The combination of spatial and temporal level feature is expected to be more sensitive to player’s actionWe demonstrate the feasibility of player detecting and logging in American football game. The proposed system enables player identification and time logging, so as to output the game log in a per-play basis. We propose a two-stage network design to first highlight player region and then identify jersey number in zoomed in sub-regions. Our player detection and jersey number recognition subsystems can be directly generalized to other football game footage. The qualitative and quantitative analysis have been thoroughly performed over three subsystems separately and over the entire system. The experimental result illustrates the reliability on handling the challenges of football game analysis.


Poa pratensis), a perennial herb with variable rhizome traits materials: multi-rhizome and few-rhizome. We found that zeatin (ZT) was abundant in the multi-rhizome material, while indole-3-acetic acid (IAA), gibberellic acid (GA3), and abscisic acid (ABA) showed the opposite trend. Metabolomics revealed that the ABC transporter pathway and the histidine metabolism pathway, both related to cytokinin, were significantly expressed in the comparison group. Rhizomes are an ideal plant trait. Our findings provide new insights into the development of perennial rhizomatous herbs and a theoretical basis for the future breeding of rhizomatous plants.Rhizomes are underground stems that grow horizontally from the base of the stem and confer competitive, reproductive, foraging, and regenerative advantages to plants. They are especially important for forage and turfgrasses. Different phytohormones influence the growth and development of plant rhizomes in a variety of ways. Here, we compare the phytohormonal and metabolomic profiles of rhizomes from two contrasting Kentucky bluegrass (−1), which is 2.4-fold that of ‘Anding’ (2.27 μg·g−1). In contrast, the IAA, ABA, and GA3 content of rhizome were markedly higher in ‘Anding’ than ‘Yuzhong’. Correlation analysis revealed significant correlations between ZT and ZT/ABA with the number of rhizomes, diameter of rhizome, and length of rhizome internode, whereas IAA, ABA, GA3, and IAA/ZT were opposite. In the metabolic profiles, we identified 163 differentially expressed metabolites (DEMs) (60 upregulated and 103 downregulated) in positive ion mode and 75 DEMs (36 upregulated and 39 downregulated) in negative ion mode. Histidine metabolism and ABC transporters pathways were the most significantly enriched in the positive and negative ion mode, respectively, both of which are involved in the synthesis and transport of cytokinin. These results indicate that cytokinin is crucial for rhizome development and promotes rhizome germination and growth of Kentucky bluegrass.Rhizome growth and development is regulated by phytohormone. However, endogenous phytohormones affect rhizome initiation, and sustained growth in perennial grass species remains elusive. In this study, we investigated the morphological characteristics and the content of indole-3-acetic acid (IAA), zeatin (ZT), gibberellic acid (GA3), and abscisic acid (ABA) in the rhizomes of two different Kentucky bluegrass. Using ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS), we performed metabolite analysis of two different rhizomes. In our study, the multi-rhizome Kentucky bluegrass material ‘Yuzhong’ had an average of 1113 rhizomes, while the few-rhizome material ‘Anding’ had an average of 347 rhizomes. The diameter of rhizome and length of rhizome internode in ‘Yuzhong’ were 1.68-fold and 1.33-fold higher than that of the ‘Anding’, respectively. The rhizome dry weight of ‘Yuzhong’ was 75.06 g, while the ‘Anding’ was 20.79 g. ‘Yuzhong’ had a higher ZT content (5.50 μg·g Rhizome, a key building block of higher plants, is crucial for plant growth and productivity and has significant biological implications . RhizomeOryza sativa L.), Xia et al. reported that the auxin response mutant dc1 exhibits enhanced apical dominance and reduced tillering, revealing a role for auxin signaling in shoot branching [Triticum aestivum) [Zea mays) [Festuca arundinacea) rhizomes [Paris polyphylla [Fragaria vesca) [Auxin, a core phytohormone for plant growth and development, exhibits polar transport ,9. Auxinranching . Previouranching , wheat (estivum) , and maiea mays) . Howeverea mays) . In the ea mays) . CK is cea mays) . CK biosea mays) . Qiu et ea mays) . The exorhizomes . GA alsolyphylla . Tenreira vesca) . Howevera vesca) ; GA-defia vesca) . GA is pa vesca) . Howevera vesca) . Moreovea vesca) . Until nArabidopsis thaliana or rice, possess rhizomes. The mechanisms underlying the regulation and distribution of endogenous phytohormones in the rhizome of Kentucky bluegrass are still not understood.Kentucky bluegrass is a rhizomatous perennial and an important lawn plant widely planted in temperate regions due to its developed rhizome system, aesthetic, and soft leaves . The plaTherefore, the goal of the present study was to (1) explore the relationships between different phytohormones and rhizome morphology; (2) identify the key endogenous phytohormones that regulate rhizome germination and growth.The rhizomes of Kentucky bluegrass grow vigorously in the spring and fall and become dormant in the summer and winter with the change in growth temperature. During the fall of the second year of the planting, the rhizome phenotypic characteristics of two different Kentucky bluegrass are depicted in Large differences in the endogenous phytohormone content were observed between the different rhizomes A–D. The Endogenous phytohormones can influence each other through synthesis, transport, and metabolism to reach a balanced equilibrium that affects plant growth and development. We therefore analyzed the difference in the phytohormones ratio in different rhizomes. The IAA/ZT ratio was significantly higher in ‘Anding’ than ‘Yuzhong’, whereas the reverse is true for ZT/ABA E,G. TherTo further investigate the difference in the plant signaling pathway of two rhizomes, we used ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) to analyze the expressed metabolites. A total of 1376 metabolites were detected. Principle component analysis (PCA) showed the separation of the samples into two groups, with the first principal component (PC1) and the second principal component (PC2) accounting for 51.08% of the total variation A. This sp < 0.05. In positive ion mode, 163 differentially expressed metabolites (DEMs) were identified, of which 60 DEMs were upregulated and 103 DEMs were downregulated; in negative ion mode, 75 DEMs were identified, of which 36 DEMs were upregulated and 39 DEMs were downregulated  was used for metabolic profiling analysis . The scaegulated .Pathway analysis of the DEMs was performed based on the KEGG database. Histidine metabolism and ABC transporters were screened for significant enrichment in positive and negative ion mode, respectively. Additionally, plant hormone signaling DEMs were also enriched in positive ion mode . Nine DELarge differences in key metabolites of the histidine metabolism pathway and the ABC transporters pathway were observed between the two rhizomes . ImidazoThe correlation between phytohormones and metabolites results is shown in Plants exhibit phenotypic plasticity in response to habitat heterogeneity by altering their morphological characteristics and cellular metabolism to form stable heritable structural features . Under tRhizome growth and development is a complex process regulated by genetic and environmental factors, where phytohormone regulation may be a conserved mechanism in the germination and growth of rhizome . ExogenoVicia faba) inhibited the growth and development of tiller buds. Each phytohormone accumulates and acts in response to the interactions with other phytohormones, genetics, and environment [Paris polyphylla [Poa pratensis. Additionally, GA3 may also influence ABA levels, which are closely related to lateral shoot dormancy; increasing ZT/ABA can weaken apical dominance [Oryza longistaminat [Auxin is one of the most important phytohormones which affect plant morphogenesis and development through synthesis, transport, and signal transduction pathways. In the present study, ‘Yuzhong’ had a higher rhizome number, rhizome diameter, and internode length than ‘Anding’, while the opposite trend was observed for the IAA content. Thimann et al.  showed tironment . Few-rhiironment , possiblironment . Howeverironment . GA has lyphylla  and to ilyphylla . These elyphylla . While Glyphylla , our stuominance , and theominance . Some inominance . Rhizomestaminat . HoweverTwo wild Kentucky bluegrass with different rhizomes were used in this study . Multi-rOn 15 October 2020, all the plants were carefully removed from the soil, and the 1st-order rhizomes were separated. Each plant was a replicate. Then, three plants were randomly selected for the measurement of rhizome morphological parameters, including rhizome number, rhizome diameter, and rhizome internode. The rhizome dry weight was determined after drying for 48 h at 80 °C. The remaining were stored at −80 °C in an ultra-low temperature freezer .Endogenous IAA, ZT, GA3, and ABA were determined by the method outlined by Yang et al.  with som−1, 4140 μg·m L−1, 240 μg·m L−1, and 200 μg·m L−1, respectively. The standard stock solution was diluted to a range of concentrations, including single-label and mixed-label for quantification . The linear regression equations and correlation coefficients of the endogenous hormones were calculated by sequentially injecting the series of concentration standards into the sample under the above chromatographic conditions, using the concentration (X) as the horizontal coordinate and the peak area (Y) as the vertical coordinate , GA3 (0.0207 g), IAA (0.0012 g), and ABA (0.0010 g) were accurately weighed and then diluted to 5 mL with chromatographically pure methanol to make the standard stock solution with concentrations of 260 μg·m Lordinate .g for 20 min at 4 °C. The supernatant was collected, and the extraction was repeated. Then, 10 μL of each sample was removed and pooled as a quality control sample [The frozen rhizomes were used for metabolomics analysis. Six biological replicates were performed for each material. In total, 100 mg of rhizomes was ground in liquid nitrogen. Then, 500 μL of 80% methanol solution was added and allowed to stand for 5 min. The homogenate was centrifuged at 15,000× l sample .m/z 100 to 1500.UPLC-MS/MS analysis was performed using a Vanquish UHPLC system . The mobile phase consisted of water containing 0.1% formic acid (phase A) and methanol (phase B) in positive polarity mode and 5 mM ammonium acetate  and methanol (phase B) in negative polarity mode. The flow rate was 0.2 mL/min and the column temperature was 40 °C. Mass spectrometric conditions included a spray voltage of 3.2kV, sheath gas flow rate of 40 arb, aux gas flow rate of 10 arb, and capillary temperature of 320 °C. The scan range was from https://www.genome.jp/kegg/pathway.html, accessed on 2 May 2022), HMDB database  and LIPID Maps database .Identification of metabolites was performed using the novoDB database. Data and chromatogram peak were analyzed by SCIEX OSV1.4 . Metabolites were annotated using the KEGG database  to transform the data into principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) to obtain the VIP value of each metabolite. In the univariate analysis section, the statistical significance  of each metabolite between the two groups was calculated based on the t-test, and the fold change in metabolites between the two groups was calculated as the FC value. The standard criteria for differential metabolite screening were VIP > 1, p-value < 0.05, and FC ≥ 2 or FC ≤ 0.5. Correlation analysis between the different metabolites was performed using the R cor, and statistical significance was realized using cor.mtest in R. A p-value < 0.05 was considered statistically significant, and correlation plots were drawn using the R corrplot package. Bubble plots were generated using the ggplot2 package in software from R Studio (R version R-3.4.3) and the KEGG database was used to investigate the functions and metabolic pathways of the metabolites. KEGG pathways significantly enriched in differential metabolites were screened using a threshold of p ≤ 0.05.Multivariate statistical analyses were performed using the metabolomics data processing software metaX . The difference between the two materials in all indicators was evaluated by Student’s In the present study, we investigated the role of endogenous phytohormones and metabolism in the growth and development of rhizomes in multi-rhizome and few-rhizome Kentucky bluegrass, demonstrating that phytohormones are important materials in rhizome. Among them, we found that ZT was abundant in the multi-rhizome Kentucky bluegrass. ZT positively correlates with the rhizome number, diameter, internode length, and dry weight of rhizome. There were high concentrations of IAA, ABA, and GA3 in the few-rhizome Kentucky bluegrass. Additionally, histidine metabolism pathways and ABC transporter pathways related to cytokinin were significantly enriched. This finding may suggest that ZT plays a crucial role in regulating rhizome growth and development, and that IAA, ABA, and GA3 may inhibit this process. In addition, ZT may act through histidine metabolic pathways and ABC transporter pathways to affect rhizome growth and development. This provides a scientific basis for the application of rhizome in the rhizomatous plants. Future research should focus on establishing a comprehensive network regulating rhizome growth and developing new cultivars with ideal plant types through molecular breeding to improve the application of rhizomes in production.


As part of the WHO Rehabilitation 2030 call for action, the WHO Rehabilitation Programme is developing its Package of Interventions for Rehabilitation (PIR) to support ministries of health around the globe in integrating rehabilitation services into health systems. As a vital step for this PIR development, we conducted a systematic review of clinical practice guidelines (CPGs) for dementia to identify interventions for rehabilitation and related evidence.Following WHO Rehabilitation Programme and Cochrane Rehabilitation’s methodology, quality CPGs published in English between January 2010 and March 2020 were identified using PubMed, Embase, CINAHL, PEDro, Google Scholar, guideline databases, and professional society websites. Guideline quality was assessed using the Appraisal of Guidelines for Research and Evaluation (II).Of the 22 CPGs that met the selection criteria, 6 satisfied the quality evaluation. Three hundred and thirty rehabilitation-related recommendations were identified, mostly concentrated in the areas of cognition, emotion, and carer support. There were many strong interventions, with moderate- to high-quality evidence that could be easily introduced in routine practice. However, major limitations were found both in the quality of evidence and scope, especially in areas such as education and vocation, community and social life, and lifestyle modifications.Further rigorous research is needed to build quality evidence in dementia rehabilitation in general, and especially in neglected areas for rehabilitation. Future work should also focus on the development of CPGs for dementia rehabilitation. A multipronged approach is needed to achieve Universal Health Coverage for dementia rehabilitation. Dementia is largely an incurable condition that progressively limits a person’s ability to function in everyday life. In line with the World Health Organization’s (WHO) strategic priority of achieving Universal Health Coverage (UHC), “all people should receive quality health services  that meet their needs without being exposed to financial hardship in paying for the services” . As manyMany of those who attended or watched the First WHO Ministerial Conference on Global Action Against Dementia in 2015 would recall a poignant speech by an international advocate who has lived experience with dementia, Kate Swaffer . She aptWhen I was diagnosed with dementia at the age of 49, I was told to get my end of life affairs in order, to give up work, to get acquainted with aged care, and to go home for the time I had left. I term this Prescribed Disengagement, but chose to ignore it and with support from the disability sector, engaged in authentic brain injury rehabilitation and other non-pharmacological and positive psychosocial interventions for dementia, including advocacy .Narratives about dementia, seen as an ultimate death sentence and one of the most commonly feared prospects people have as they get older , are stePeople living with dementia experience varying degrees of challenges in performing daily tasks such as preparing meals, shopping, making phone calls, taking medications, dressing, showering, and toileting as well as communicating with others and participating in everyday social activities . Much ofIn acknowledging the importance of rehabilitation in dementia care and service delivery, one must begin with a recognition that dementia is not an immediate life-ending illness, and despite a decline in their ability to self-care and maintain independence, the person living with dementia can still retain the capacity to enjoy a meaningful life with the most appropriate care and support . In ordeIn the past two decades, a steady number of dementia-specific programs centered around interventions of care that adopt the principles of rehabilitation have been introduced. All have been known for their focus on enabling and empowering the person with dementia to participate in their daily, physical, social, and community activities as well as maintaining independence in their interaction with personal  and broad  environments. These include, for example, reablement approaches to care , cognitiAs part of the WHO Rehabilitation 2030 call for action, the WHO Rehabilitation Programme is developing its Package of Interventions for Rehabilitation (PIR) to support ministries of health around the globe, with a particular focus on low- and middle-income countries (LMICs), in integrating rehabilitation services into health systems . DementiThe first aim of this paper is to report the results of the systematic search and synthesis performed as step 2 of the dementia PIR development, including an exploration of the breadth of functional targets covered by the recommendations and the current state of evidence from the clinical practice guidelines (CPGs) relevant to rehabilitation of people living with dementia. A second aim of the paper is to examine key constraints that hinder adoption of a universal approach to dementia rehabilitation in routine practice. We provide critical discussions concerning strengths, weaknesses, and gaps in available recommendations for dementia rehabilitation; explore and situate this within the context of current societal responses to dementia as a global health issue; and suggest future directions for research, practice, and policy development in dementia rehabilitation for a global audience.This systematic review of CPGs has been developed in full compliance with the methodology developed by WHO Rehabilitation Programme and Cochrane Rehabilitation under the guidance of WHO’s guideline review committee secretariat. The search and selection processes followed WHO’s protocol . The quaSystematic literature searches of practice/clinical guidelines published in English in the past 10 years (January 2010 to March 2020) were conducted by an experienced librarian and the first author and involved four sources: key academic databases , Google Scholar search engine, guideline databases, and professional rehabilitation society websites. The key guideline databases searched included Guidelines International Network, U.S. National Guideline Clearinghouse, UK National Institute for Clinical Excellence, Australian National Health and Medical Research Council clinical practice guidelines, UK National Library for Health Guidelines Database, Scottish Intercollegiate Guidelines Network, Canadian Medical Association Infobase of Clinical Practice Guidelines, L’agence Nationale D’accréditation et D’évaluation en Santé (France), New Zealand Guidelines Group, and eGuidelines. For the professional rehabilitation society websites, we searched relevant national and international professional organizations for psychogeriatrics, geriatrics, nursing, occupational therapy, physiotherapy, exercise physiology, speech pathology, and psychology (see The search combined the following terms and concepts: “guideline” (OR “recommendation”) AND “dementia” AND “rehabilitation” (OR “therapy”). See The search was limited to guidelines, practice, or clinical guidelines focusing on any type of dementia and rehabilitation see , publishstrongly disagree) to 7 (strongly agree). To be included in this review, the guideline must have an average total score of 45 or more for nine key items  and a minimum average score of three for each item of 7, 8, 12, and 22  across two independent reviewers  tool , the goleviewers .Initial screening of 1,595 titles and abstracts and selection of the 72 full texts for review was carried out by Y-HJ and verified by AR. Independent title/abstract and subsequently full-text screening of the 72 retrieved manuscripts was conducted by a nurse (Y.-H. Jeon) and two groups of allied health professionals  to ensure that they meet the eligibility criteria, which yielded 22 guidelines. Two groups  then carried out independent quality evaluations of the 22 CPGs based on the AGREE II. The first author (Y.-H. Jeon), and the last author (A. Rauch), if necessary, were consulted throughout the process and the final decision was based on consensus.Of 22 guidelines, seven met the quality criteria using the AGREE II tool. Due to feasibility, the WHO PIR team set an additional rule for a maximum of six highest quality CPGs to be selected for the final inclusion if more than six CPGs were to be found. The additional criteria were: (a) quality, (b) publication time, (c) multiprofessionality , (d) comprehensiveness . One guideline was published in 2011 and three guidelines were deemed monoprofessional, two of which were for Huntington’s disease only, a rare type of dementia with unique features that are not found in other common dementia types. Coincidentally, the number of guidelines meeting criteria naturally approximated the WHO PIR team’s directive maximum 6. After a discussion among the review team, one Belgian guideline  was exclAs a final step, data extraction of recommendations was completed using a standardized form, which comprised information on the recommendation , the strength of recommendation, and the quality of the evidence used to inform the recommendation. The data extraction was performed by four reviewers  and reviewed by first author (Y.-H. Jeon). The extracted recommendations were then submitted to the WHO project leader (A. Rauch) for a final review before final acceptance of the guidelines and recommendations.As part of the data extraction, recommendations were assigned to a recommendation type: service, assessment, or intervention. A service recommendation refers to how, when, and/or by whom rehabilitation services should be delivered; an assessment recommendation relates to measures or processes for investigating a specific problem/target or outcome; and an intervention recommendation is defined as a specific measure to be applied to improve a particular problem/target or outcome. The targets of the assessments and interventions described in the recommendations have been mapped by the WHO team to an aspect of functioning across rehabilitation domains, using the International Classification of Functioning, Disability and Health ICF; .There was considerable variability in the classification system used to determine quality of evidence and strength of recommendations, with guidelines using a number of different resources. All guidelines assigned quality of evidence levels to their recommendations: Two guidelines (NICE and GAC) used the Grading of Recommendations Assessment, Development and Evaluation (GRADE), the OT guideline used the U.S. Preventive Services Task Force methods, the RN guideline used the Scottish Intercollegiate Guidelines Network, the HD_PT guideline used the Joanna Briggs Institute criteria, and the EHDN guideline used the French Health Authority recommendations. In terms of strength of recommendations, four guidelines  used four different approaches, including the ADAPTE, Joanna Briggs Institute, GRADE, and U.S. Preventive Services Task Force methods, respectively. The other two (RN and EHDN) guidelines did not specify strength of recommendations.n = 7) in such a way that grouping into the new system was not possible. The strength of recommendations was mixed fairly evenly between those considered stronger and others that were weaker or based on expert opinion. Some guidelines did not include a rating for strength of recommendation . The quality of the evidence was also mixed; however, most guidelines were based on a majority of low- to very low-level evidence.To facilitate comparison of recommendations for this review, the quality of evidence and strength of recommendations of each guideline were classified according to a new grouping system; the quality of evidence was rated using the terms high, moderate, low, and very low, and the strength of recommendation was rated using the terms strong, weak/conditional, and expert opinion. This was possible for all guidelines except for the HD_PT guideline, which presented recommendations (As shown in n = 55) and carer/family support (n = 35) domains, followed by activities of daily living, mental emotional, and speech, language communication. Dysphagia, pain, and self-management were the domains with the fewest recommendations . Refer to Of the total 330 rehabilitation-related recommendations identified, intervention recommendations accounted for 73% while only 12% and 15% of the recommendations related to services and assessment, respectively. The GAC guidelines were an exception, containing 53% of the recommendations relating to service. When the recommended assessments and interventions were mapped to 17 rehabilitation domains, the majority of recommendations were in mental cognitive , with appropriate tools and opportunities to deliver rehabilitation interventions in their routine practice Further rigorous research to build quality evidence in dementia rehabilitation especially in neglected areas for rehabilitation such as hearing, education and vocation, community and social life, and lifestyle modifications Rigorous implementation research for dementia rehabilitation models of care that are codesigned in partnership with key stakeholders to bridge the “evidence-to-practice” gap and provide pragmatic guidance for routine clinical practicen = 2) despite the positive effects of physical exercise and fitness on cognition, functional ability and mobility  while the OT guidelines refer to comprehensive rehabilitation. This may echo the current trend in the literature concerning the notion of rehabilitation which at times is used interchangeably with reablement, function-focused care, or restorative care . Poulos Limited attention to rehabilitation in the generic dementia guidelines is not a surprising phenomenon given the lack of acceptability of a need for rehabilitation in dementia care among health care practitioners, which is largely underpinned by a therapeutic nihilism . TherapeAn overwhelming proportion of people living with dementia and their informal carers report feelings of embarrassment, isolation, and lack of support  or beingRecent literature clearly shows a growing desire of those with lived experience (people living with dementia and their family carers) to have access to appropriate rehabilitation interventions and services . DecadesA key feature underpinning these successful programs and interventions is linked to the notion of social health that provides a renewed lens through which health is seen as a dynamic process within a total environment , 2016. IWe propose that a “top-down” shift in mindset stemming from policy makers and health and dementia/aged care service providers has the potential to catalyze a shift toward openness and acceptance of the vast and varied possibilities for rehabilitation, initially among individuals living with dementia and their immediate circle , which in turn will influence broader societal attitudes regarding “life with dementia.” This shift needs to be strengthened by a concurrent “bottom-up” approach, where those people living with dementia and care partners are empowered and supported to access and make an informed choice about rehabilitation interventions and services. Clinicians should also be supported to build their skills for and knowledge and understanding of dementia rehabilitation and provided with appropriate tools and opportunities to deliver rehabilitation interventions in their routine practice .The majority of people with dementia live in LMICs, parts of the world that are often not well equipped to provide rehabilitation services. Rehabilitation is often not prioritized and continues to be underresourced. Estimates for some LMICs suggest that more than 50% of people do not receive the rehabilitation services that they require , with gaTo fulfill this vision equally across all parts of the world, existing gaps need to be addressed with respect to comprehensive policies for dementia and rehabilitation, universal access to rehabilitation services, building workforce capacity through training and implementing clinical guidelines that are reflective of different settings and needs, integration of rehabilitation within primary health care, and strengthening care coordination mechanisms and monitoring of rehabilitation services. Global commitments such as WHO’s Rehabilitation 2030 initiative with its goal of establishing and strengthening networks and partnerships in rehabilitation between low-, middle-, and high-income countries, and the WHO global dementia action plan, provide strategic impetus to overcome these barriers by prioritizing dementia rehabilitation globally. As demonstrated in our review, at the same time, international research initiatives such as strengthening responses to dementia in developing countries are needed to contribute to closing the gap by synthesizing and producing new evidence specifically for LMICs .There is an urgent need for attitudinal, clinical, and policy change, recognizing that people living with dementia should have access to readily available rehabilitation programs and services. WHO’s strategic priority of including rehabilitation among UHC services through “Rehabilitation 2030: a call for action” is gaining momentum through the work of this PIR development. In light of an established wealth of evidence for what works, as well as known gaps and issues in dementia rehabilitation practice and in the context of research and societal responses to dementia as a global health issue, we argue for a multipronged approach to achieve the WHO’s global call for action to ensure UHC for dementia rehabilitation. The need for a greater understanding and acceptance of the concept of rehabilitation in dementia is paramount as it plays a crucial role in delivering and accessing rehabilitation services. Furthermore, there is a strong impetus to use the term “rehabilitation” in dementia care more widely and consistently to improve acceptance of rehabilitation as part of routine practice among stakeholders including people living with dementia, their family and carers, clinicians, health and social care providers, policy makers as well as researchers. Based on the identified rehabilitation recommendations from this review, the WHO PIR Development Group is finalizing the most salient and equitable assessment and interventions for dementia rehabilitation that can be applicable across LMICs and high-income countries. Upon peer review of the final set of interventions, the PIR open source that contains all relevant information resources for rehabilitation will be made available online. Next steps toward enhanced provision of rehabilitation services in dementia must then involve rigorous implementation research codesigned in partnership with key stakeholders  to bridge the “evidence-to-practice” gap and provide pragmatic guidance for routine clinical practice.gnac105_suppl_Supplementary_MaterialClick here for additional data file.


Editorial on the Research TopicHighlights in medical and surgical rehabilitation 2021/22Rehabilitation is a crucial component of universal health coverage, which encompasses promoting good health, preventing disease, treatment, and palliative care. It helps individuals of all ages, from children to older people, to engage in everyday activities independently and participate in education, work, and recreation. Worldwide, approximately 2.4 billion people live with a health condition that could benefit from rehabilitation, and the demand for rehabilitation is predicted to rise due to changes in the population’s health and characteristics. Rehabilitation is essential in achieving Sustainable Development Goal 3: “Ensure healthy lives and promote well-being for all at all ages.”  RehabiliRecently, it is evident that scientific research in physical and rehabilitation medicine (PRM) requires careful consideration of study design and methodology. The research question guides the entire research process and helps in selecting an appropriate study design . There aIn addition to quantitative research methods, qualitative research methodologies can provide important insights into how interventions work and how patients react to new techniques and methods. In the field of rehabilitation science, the number of qualitative studies published in journals of rehabilitation has increased significantly over the past two decades. There are many areas of opportunity and difficulty include paradigm shifts, advances in methodology, emerging technology, advances in quality evaluation, the growing popularity of mixed-methods approaches, and evolving approaches to knowledge translation. Qualitative research should play an important role in the development of rehabilitation science, and it is crucial that qualitative researchers and methods continue to evolve. The objective of qualitative research in medical rehabilitation is to comprehend the experiences and perspectives of patients and healthcare professionals in relation to medical rehabilitation. It entails collecting data using techniques such as interviews, focus groups, and observation, and analyzing the data to identify themes and patterns . QualitaThe field of medical and surgical rehabilitation aims to assist individuals in recovering from illness or injury, enhancing their physical function and overall quality of life. Current trends in medical and surgical rehabilitation include the followings: (1) Provide patient-centered care that is tailored to the patient’s specific needs, goals, and preferences. This requires collaborating with patients and their families to develop individualized treatment plans that are geared toward achieving specific outcomes. (2) Utilizing devices and technologies such as virtual reality, robotics, and wearable sensors to aid in recovery and rehabilitation, medical and surgical rehabilitation has become increasingly technologically advanced. These innovations can provide patients with more effective care. (3) Integration of medical and surgical rehabilitation with other healthcare services, such as primary care, mental health care, and social services. This integrated approach aims to improve outcomes by addressing all aspects of a patient’s health and well-being. (4) Professionals from diverse fields, such as physical therapy, occupational therapy, speech therapy, nursing, psychology, and social work, are increasingly collaborating to provide comprehensive care for patients on medical and surgical rehabilitation teams. (5) Prevention by providing patients and their families with information and resources to assist them in maintaining optimal health and avoiding future health problems.The following are some trends in medical and surgical rehabilitation research:Personalized Rehabilitation: Personalized rehabilitation is gaining popularity, with an emphasis on individualizing rehabilitation programs based on patient characteristics such as age, gender, climate, environment, and nation. This strategy allows for improved patient outcomes and satisfaction .There is a growing interest in developing less invasive techniques for managing pain, such as the unique technique of mechanical needling with sterile water injection for calcification and fibrosis removal treatment by Areerat Suputtitada , 8. ThisTranscranial Magnetic Stimulation (TMS) and Transcranial Direct Current Stimulation (tDCS) are two of the most notable noninvasive brain stimulation techniques that have gained significant attention and have shown promise in treating various neurological and psychiatric conditions. TMS and tDCS are both noninvasive methods that can modulate brain activity without the need for invasive procedures. TMS uses magnetic fields to stimulate neurons in the brain, while tDCS uses a low-intensity electrical current. Both methods have shown efficacy in treating conditions such as depression, anxiety, and chronic pain, and ongoing research is exploring their potential in other areas such as swallowing, balance, and gait ability in stroke rehabilitation , 10.Long-term COVID management in post-acute sequelae of SARS-CoV-2 infection (PASC), refers to ongoing symptoms experienced after recovering from acute COVID-19. Rehabilitation is vital in managing this condition, and emerging trends include a multidisciplinary approach, individualized treatment programs, gradual and graded exercise, tele-rehabilitation, and long-term follow-up. It’s essential for healthcare professionals to stay updated as research on post COVID-19 continues to evolve , 12.Tele-rehabilitation is a new trend that uses technology to remotely provide patients with rehabilitation services. Telemedicine may involve virtual consultations, remote monitoring, and teleexercises. This strategy has gained popularity as a result of the COVID-19 pandemic , 14.Virtual Reality: Virtual reality is being used to create simulated environments in which patients can practice real-world activities such as walking, reaching, and grasping. It has been demonstrated that this method increases patient motivation and participation in rehabilitation –15.Robotics: Robotics is used to assist with rehabilitation exercises, such as upper limb exercises following a stroke. Robotic devices can provide a training regimen that is more intensive and repetitive than conventional therapy , 14, 16.Wearable Technology: Smart watches and fitness trackers are being used to monitor and track rehabilitation progress. This method can assist patients and healthcare professionals in identifying improvement areas and monitoring progress , 14, 17.Mind-Body Approaches, such as mindfulness and yoga, are used to supplement conventional rehabilitation programs. These methods can aid in reducing stress and enhancing well-being, which can have a positive effect on rehabilitation outcomes .Intensity of Exercise: Research is increasingly focusing on the optimal intensity of exercise for various populations and conditions. This strategy aims to maximize rehabilitation outcomes while minimizing injury and overexertion risks .Regenerative Medicine: Stem cell therapy and tissue engineering are being studied as potential treatments for conditions that impair the body’s ability to heal, such as spinal cord injuries and osteoarthritis .In conclusion, rehabilitation plays a crucial role in universal health coverage and the achievement of Sustainable Development Goal 3. It helps individuals of all ages regain independence and improve their quality of life. Qualitative research is essential to understanding the complex experiences and perspectives of patients and healthcare professionals in the field of rehabilitation. Current trends in medical and surgical rehabilitation include personalized care, integration with other healthcare services, technological advancements, interdisciplinary collaboration, prevention, and innovative research areas such as the unique technique of mechanical needling with sterile water injection for calcification and fibrosis removal treatment, noninvasive brain stimulation, long-term COVID management, tele-rehabilitation, virtual reality, robotics, wearable technology, mind-body approaches, optimal exercise intensity, and regenerative medicine. By staying informed and embracing these trends, healthcare professionals can contribute to the advancement of rehabilitation science and provide more effective and patient-centered care.


Only a few studies have evaluated Augmented Reality (AR) in in vivo simulations compared to traditional laparoscopy; further research is especially needed regarding the most effective AR visualization technique. This pilot study aims to determine, under controlled conditions on a 3D-printed phantom, whether an AR laparoscope improves surgical outcomes over conventional laparoscopy without augmentation.Floating AR, Occlusion AR, and without any AR visualization (Control). Surgical performance was determined using objective measurements. Subjective measures, such as task load and potential application areas, were collected with questionnaires.We selected six surgical residents at a similar level of training and had them perform a laparoscopic task. The participants repeated the experiment three times, using different 3D phantoms and visualizations: Differences in operative time, total touching time, and SurgTLX scores showed no statistical significance (According to our results, AR may have great potential in visceral surgery and based on the objective measures of the study, may improve surgeons' performance in terms of an atraumatic approach. In this pilot study, participants consistently took more time to complete the task, had more contact with the vascular tree, were significantly more invasive, and scored higher on the SurgTLX survey than with AR.The online version contains supplementary material available at 10.1007/s11548-022-02809-7. Minimally invasive surgery (MIS) aims to reduce the trauma of an intervention without compromising oncological outcomes . LaparosIn recent years, augmented reality (AR) and surgical navigation have become established in fields with minor organ deformation, such as neurosurgery and orthopedics –6, and hSeveral detailed studies have investigated objective evaluation methods of surgical skill in open, minimally-invasive, and robotic surgery , but onl. [. [Diley et al.  analyzed.  evaluate. [.  evaluateEven though visualization is the primary interaction between the surgeon and the navigation system, little attention has been paid to which AR visualization technique performs best in laparoscopy. Only a few studies , 13 haveA common challenge in monitor-based AR is the correct handling of occlusions . OcclusiThis user study examines how a monitor-based AR laparoscopic system could improve surgical performance compared to conventional laparoscopy on a rigid 3D-printed phantom. We further compare how the correct handling of occlusions between the augmented anatomy and the surgical instruments affects surgical performance.The experimental setup consisted of the Laparoscopic Augmentation System (LAS), two laparoscopic instruments (grasping pliers and scissors) connected to an oscilloscope, two different AR visualization methods, and three different phantoms containing rigid 3D-printed vessels.The study procedure required three vascular structures, as shown in Fig. The segmentations were post-processed with a Gaussian smoothing operator in a medical image data-processing suite  and arranged in a box see Fig. a, b withThe box and a holder see Fig. c were 3D Fig. e, which Finally, a hollow phantom of an abdominal torso and wall was placed over the vessel box and provided appropriate trocars to insert the laparoscopic instruments.Control condition, and (5) surgical instruments. The Magnum graphics middleware [The Laparoscopic Augmentation System (LAS) is a standard laparoscopic system with the vital addition of a computer connected to a tracking system. As shown in Fig. ddleware  served aThe AR visualization consisted of overlays of vessel structures superimposed on the laparoscopic video stream in an AR monitor setup . InspireOcclusion AR, a random forest predictor provided pixel-wise classifications of the instruments in the live laparoscopic video stream to mask the area covered by the instrument. The predictor was trained beforehand with images from the same simulator, labeled in laparoscopic instruments and background. Morphological transformations and Gaussian blurring filtered the segmentation to achieve a gradual fade-out, and weighted averaging with the previous segmentation frames smoothed temporal inconsistencies. This effect can be seen in Fig. In the visualization technique, Floating AR: the AR visualization does not take occlusions of the anatomy with the instrument into account, i.e., the AR visualization always appears floating on top of the instrument , handled the laparoscope. The participants had two primary assignments: (1) Reaching the target by dissecting the tissue-mimicking material surrounding the vessel and (2) identifying the code, i.e., revealing the stripes on the target. Additionally, they were instructed to minimize the amount of removed tissue-mimicking material, reach the target as quickly as possible, and avoid touching the vessel. These additional requirements corresponded to the objective measures.Subjective Questionnaire. The experiment ended with a survey about subjective opinions.Occlusion AR, followed by Floating AR. For the other half, the order was flipped. The participants were unaware of the augmentation techniques. In the third run, all participants performed the Control condition without any AR visualization to counteract learning effects in favor of AR.Half of the participants started with We measured the weight of the removed material, time on task, and time touching the vessel for objective performance measures. We weighed each vessel box before and after the studies with a precision balance  to determine the weight of the removed material. We used the amounts of removed tissue-mimicking material to measure the simulated surgery's invasiveness. Each experiment was timed from when the participants began inserting the instruments into the laparoscopic trainer until they completed the two primary tasks. Furthermore, we recorded the time of each instrument touching the vessel using the oscilloscope by measuring the voltage at 200 Hz and registering a touch when the voltage rose above a threshold.After each run, the participants filled out the SurgTLX survey . They raAfter all three experiment runs, the participants answered a qualitative questionnaire on the usefulness of the presented AR visualization on a 4-point Likert scale, ranging from “very helpful” to “not helpful at all.” Then, the participants indicated if they would like to have any form of AR visualization for specific laparoscopic surgeries. Finally, they submitted their opinion concerning the potentially positive impact of AR on multiple surgical parameters and selected which would most benefit from AR.We included six participants in the study . The nonparametric Friedman test determined the significance in difference between the delta weight, total time, and time of touching among participants using AR or traditional laparoscopy. Our analysis considered values of Control condition consistently revealed longer execution times , sigmoid resection (100%), rectal resection (83%), left pancreatic resection (100%), gastrectomy (67%), nephrectomy (83%), cholecystectomy (67%), and right hemicolectomy (67%). Half of the participants classified the LAS as beneficial for splenectomy (50%) and TAPP (50%). Only 33% expressed a good impact of LAS on appendectomy.All participants (100%) agreed that the LAS could positively influence specific surgical parameters. The two most commonly chosen parameters that could benefit the most from AR were “shortened operative time” (83%) and “reduction of complications” (83%). More than half of the participants stated that AR could speed up the “learning curve” (67%) and “patient safety” (67%), or lead to better “oncological outcome” (50%), and “reduce blood loss” (50%). Five out of six participants (83%) also stated that the LAS system would be very or rather helpful in identifying risk structures. The usefulness regarding stress reduction of the LAS system was rated very or somewhat helpful by 83%.Occlusion AR over Floating AR.Furthermore, five of the six participants (83%) agreed that the simulation was realistic for laparoscopic interventions. Three participants (50%) indicated that the simulated tissue material needs improvement. The tracking marker on the endoscope was considered to be rarely bothersome by four individuals (67%), occasionally irritating by one (17%), and frequently irritating by one (17%). Only one participant (17%) reported noticing delays in the visualization of the LAS. Spontaneously, none of the participants addressed the difference between occlusion handling enabled or disabled. When explicitly prompted, five of the six participants (83%), however, preferred Based on the developed AR system and the experiments performed on the phantom model, AR support for laparoscopic resection can offer advantages in terms of surgical outcomes and patient safety. In fact, the speed of the surgeon in identifying target structures was improved, and both the trauma of the surgical intervention and the risk of touching, and thereby injuring risk structures, were reduced. However, this could not be shown to be statistically significant.Our participants, surgeons in the course of their training, believed that AR could provide significant benefits to laparoscopy, like directly guiding them but also reassuring them of their actions and ultimately increasing patient safety. Their subjective survey results also indicate a lower task load. This reinforces what current literature already suggests: AR could be a strong addition to several surgical interventions and could assist in reducing the surgeon’s stress, thus, decreasing the number of committed mistakes –27.We included only surgeons of the same training level in this study to ensure the comparability of our results. We believe that AR will be of particular help to younger surgeons, as they will be the target user group. The influence of AR depending on the level of training is an exciting topic, especially concerning the development of such systems. Ideally, augmentation should also consider the user’s training level.Occlusion AR and Floating AR. The participants were not made aware of this difference between the runs, and none explicitly mentioned noticing it. However, when asked, the participants often indicated that AR interferes with the fine preparation and that they looked at the second monitor without any AR. Our observations also suggest that most participants used the AR screen initially to understand anatomy but switched instinctively to the non-augmented screen for meticulous vessel preparation. This indicates that AR visualizations can sometimes overwhelm the surgeon with the amount of information presented. The extent to which the type of visualization influences AR performance has unfortunately received too little attention and should be further investigated [Our study did not measure a significant difference between the surgical performance in stigated .The small sample size is an important limitation of the study. Additional research with a substantially larger number of testing participants is needed. However, a study with more participants was disproportionately time and cost-consuming because of the complex experimental setup and the length of each experiment (approx. 60 min). There were 18 vessel models in total, three for each participant. The 3D printed structures were not affected by the experiments, and the soft tissue material could be removed and the boxes refilled.Occlusion AR condition was based on a pixel-wise classification of the laparoscopic video feed and, therefore, in 2D. Our random forest predictor performed well and consistently. We assumed that if the instruments were detected, they would always be in front of the anatomy. A weakness of this approach was that if the instrument was in front of the vessel, but below the soft tissue material, it could not mask the anatomy behind it, resulting in incorrect occlusion. In a follow-up study, we will incorporate 3D tracking of the instruments to ensure correct occlusion handling.The estimation of the instrument position in the Furthermore, the phantom can be improved. Our experiment showed that laparoscopic instruments could realistically cut soft tissue, but grabbing and removing it was inconvenient in some circumstances. Participants sometimes found this frustrating since it did not reflect the actual clinical scenario. In addition, the rigidity of our model may have influenced the evaluation, as viscera and vasculature are deformable in clinical reality.Finally, despite the above-mentioned limitations, sufficient evidence suggests that real-life clinical performance closely matches a simulated setting , 29. BasIn this study, we showed that participants could prepare the target structure more quickly, with less trauma and contact with risk structures with the aid of AR. In particular, a significantly lower degree of invasiveness was measured. We also saw reduced mental and physical task load in the AR conditions. Furthermore, the participating surgeons in training rated AR as very helpful, and they wished to see it incorporated into a wide range of surgical procedures. Although the results of the current study should be applied with caution to clinical practice, we believe that they accurately depict the operating room experience and that AR can have a major impact on surgery. However, further efforts to develop better technologies and evaluate their potential clinical uses are indispensable.Supplementary file1 (AVI 151495 kb)Below is the link to the electronic supplementary material.