One of the most effective solutions in medical rehabilitation assistance is remote patient / person-centered rehabilitation. Rehabilitation also needs effective methods for the “Physical therapist – Patient – Multidisciplinary team” system, including the statistical processing of large volumes of data. Therefore, along with the traditional means of rehabilitation, as part of the “Transdisciplinary intelligent information and analytical system for the rehabilitation processes support in a pandemic (TISP)” in this paper, we introduce and define: the basic concepts of the new hybrid e-rehabilitation notion and its fundamental foundations; the formalization concept of the new Smart-system for remote support of rehabilitation activities and services; and the methodological foundations for the use of services  of the remote Patient / Person-centered Smart-system. The software implementation of the services of the Smart-system has been developed. The methodology of rehabilitation measures in a pandemic has several significant features associated with the unpredictability and high rate of emergence of problems of high complexity, limited communication between the therapist and the patient, the need for high responsiveness of decision-making and their compliance, the scale of the process and the associated need to use scalable operating tools, etc. One of the most effective solutions in medical rehabilitation assistance is remote patient/personal-centered rehabilitation. It requires online monitoring tools, telemetry and interventions focused on the patient's capabilities, developed Internet interaction, intelligent information technologies, and services. Patient / Person-centered rehabilitation also needs effective methods in the “Physical therapist – Patient – Multidisciplinary team” system, statistical processing of large volumes of data, etc. Therefore, along with the traditional means of rehabilitation, as part of the “Transdisciplinary intelligent information and analytical system for the rehabilitation processes support in a pandemic (TISP)”  the SmarThe objective of the research described herein is to develop a formal model, software implementation, and the methodological foundations for the use of services of the remote Patient / Person-centered Smart-system for providing medical rehabilitation assistance to patients in a pandemic .Smart-system for remote support of rehabilitation activities and services is a complex, integrated, patient / person-centered information subsystem of TISP for the provision of medical care, solving various clinical, organizational, and research tasks in the field of rehabilitation medicine: consultations; remote observation and support of rehabilitation processes and activities; classification, forecasting, and knowledge extraction; research and review of the new domain areas; use of remote communication technologies; elements of artificial intelligence, in particular, ontology engineering;  and machAccording to the World Health Organization, rehabilitation is a set of processes designed to ensure that people with impaired functions due to illness, injury, and birth defects, adapt to new living conditions in the society in which they live. Rehabilitation of people who have recovered from COVID-19 disease is, of course, an extremely important social problem. This fact is already well understood by the international medical community. At the same time, the availability of rehabilitation measures in different countries is quite different. In countries with developed insurance medicine, the rehabilitation process in the corresponding specialized centers is available to many. Unfortunately, in Ukraine the situation is different. The needs of patients for outpatient rehabilitation services far exceed the available resources; this requires finding alternative solutions and connecting modern and advanced technologies to support patients. Therefore, there is a great need for the use of a new modern direction of rehabilitation medicine: telerehabilitation.In the modern world, the generally accepted definition of the concept of telerehabilitation or E-rehabilitation  is a comTelerehabilitation is the embodiment of several modern technological trends at once. First of all, telerehabilitation is impossible without telecommunication technologies. Secondly, telerehabilitation requires the usage of specialized hospital information systems  for rehabilitation. These systems are needed both for the administration of patients and (this is the most important part), for the creation of a number of rehabilitation documents in accordance with the structure of the rehabilitation cycle, for example, an individual rehabilitation plan, categorical profile of a patient, rehabilitation prognosis, etc. Thirdly, an important part of telerehabilitation technologies is the functional assessment of the patient's condition at home using miniature devices (embedded systems and wearable devices) and modern algorithms for evaluating data in accordance with the point-of-care testing trend, which is carried out directly at the patient's location, outside the doctor's office. Finally, telerehabilitation is impossible without the active involvement of the patient in the decision-making process for their diagnosis and treatment. This is one of the main trends in modern medicine, which was supported, among other things, at the level of legislative initiatives in the health care system of Ukraine.The rapid development of telerehabilitation worldwide and the acquisition by this direction of medicine of transdisciplinary connections with various subject areas that go beyond the modern paradigm of e-health, led to the emergence of the most modern type of rehabilitation medicine – Hybrid e-rehabilitation medicine. The Hybrid e-rehabilitation notion shown in  consistsTelecommunication technologies. This means the delivery of rehabilitation services over telecommunication networks and the internet. Also, this allows patients to interact with providers remotely and can be used both to assess patients and to deliver therapy.Rich Internet Applications (RIA). These are chiefly the Hospital Information Systems (HIS). A HIS is a comprehensive, integrated information system designed to manage all aspects of a hospital's operation, such as medical, administrative, financial, and legal issues and the corresponding processing of services. Another feature of such systems is the provision of communication between patients and doctors from the multidisciplinary rehabilitation team.Telemetry. This is a set of technologies that allow remote measurement, and collection and transmission of information about performance indicators  of the patient's body in real-time.Wearable devices and Embedded systems. Wearables may be for widespread use in which case they are just a particularly small example of mobile computing. Alternatively, they may be for special purposes such as fitness trackers or medical devices. They may incorporate special sensors such as accelerometers, heart rate monitors, or on the more advanced side, electrocardiogram (ECG), blood oxygen saturation (SpO2) monitors and blood pressure monitoring devices. These functions are often bundled together in a single unit, like an activity tracker or a smartwatch like the Apple Watch Series or Samsung Galaxy Gear Sport. Devices such as these are used for physical training and monitoring overall physical health, as well as for alerting to serious medical conditions such as seizures . Currently, other applications within healthcare are being explored, such as: forecasting changes in mood, stress, and health; measuring blood alcohol content; measuring athletic performance; long-term monitoring of patients with heart and circulatory problems that records an electrocardiogram and is self-monitoring; health risk assessment applications, including measures of frailty and risks of age-dependent diseases; and automatic documentation of care activities.Biofeedback (BF). Biofeedback is the process of gaining greater awareness of many physiological functions of one's own body. Biofeedback .D – is a set of web services (RIA) and desktop applications that are available for usage in the Smart-system S :Where:S .is a web service or desktop application that implements specific algorithms, processes, and functions of the Smart-system S, each function is the result of coordination and interaction of the Smart-system S elements.is a set of functions, the functional filling-up of the Smart-system j-th function of Smart-system S. The formation of this subset allows creating personalized pipelines and scenarios for using the developed web services and desktop applications , which enables more flexibly in use of the services of the Smart-system for PM&R doctors. The formation of such pipelines and scenarios is beyond the scope of this article and should be considered separately.is a subset of web services and desktop applications that are required to implement the At the current stage of development, the Smart-system includes various technologies, web services, and desktop applications, in particular:Where:T1 – Remote consulting service – Smart-system's telemedicine module (which provides online video and audio communication) using modified open-source software Jitsi Meet .T2 – Digital doctor's office of specialized medical care service, in particular the PM&R doctors. In the personal digital office, there are services for managing online appointments, including video consultations, personal doctor's and patient's profiles, fiscal management, a calendar for scheduling and planning consultations, access to the electronic health records , and a module for carrying out electronic advisory conclusions on the results of the video consultation.T3 – Service for automated processing and integration of all basic workflows of a medical institution for interaction between an administrator, a doctor, and a patient.T4 – Collaborative service for the creation and use of file-sharing and exchange services, in particular, for interacting and exchanging medical digital images via Digital Imaging and Communications in Medicine (DICOM). DICOM is the standard for the communication and management of medical imaging information and related data. DICOM is most commonly used for storing and transmitting medical images enabling the integration of medical imaging devices such as scanners, servers, workstations, printers, network hardware, and picture archiving and communication systems (PACS) from multiple manufacturers. It has been widely adopted by hospitals and is making inroads into smaller applications such as dentists' and doctors' offices. DICOM incorporates standards for imaging modalities such as radiography, ultrasonography, computed tomography, magnetic resonance imaging, and radiation therapy. DICOM includes protocols for image exchange , image compression, 3-D visualization, image presentation, and results reporting.T5 – UkrVectōrēs  web service. This is a NLU-powered toolkit for knowledge discovery, classification, diagnostics, and prediction – an entities similarity tool. You can think about UkrVectōrēs as a kind of “cognitive-semantic calculator.” The online toolkit UkrVectōrēs covers the following elements of distributional analysis . This is a distributed information system that allows you to store, use and share various collections of electronic documents (video and audio content) of arbitrary domain areas for distance learning of patients and their relatives, in particular, a rehabilitation complex of exercises and activities.Consider in detail some services and applications developed according to the generalized formalization concept of the Smart-system for telemedicine support of rehabilitation measures, in particular, UkrVectōrēs and vHealth services.The distributed numerical feature representations of words (word embeddings) and word vector space models, as a result, are well established in the field of computational linguistics and have been here for decades, see The network service UkrVectōrēs computes the semantic relations (similarity) between the entities of the Ukrainian language within the selected distributional semantic model of the vector representation of entities (entities embeddings). UkrVectōrēs is a natural language distributional analysis and distributional semantic modeling web service (toolkit), a natural language research technique based on the study of the environment (distribution), individual entities in the text without the full lexical or grammatical meanings of these entities. In the general case, distributional analysis, and distributional semantic modeling  use, basThe network service UkrVectōrēs is a tool that allows exploring the semantic relationships between entities in the framework of predictive models of distributional semantics (PMDS), using an open-source software library genism  for processing and mathematical modeling of the natural language . The user can choose one or several carefully prepared predictive models of distributional semantics (or use other models of vector representation for words of the Ukrainian language) learned on various text corpora, in particular, such as the WB  dataset.The UkrVectōrēs service covers the following elements of the distributional semantic analysis / modeling:computation of semantic similarity between pairs of entities (words) within the selected PMDS;-1 and 1 . 0 value roughly means the entities lack similar contexts, and thus their meanings are unrelated to each other. 1 value means that the entities' contexts are absolutely identical, and thus their meaning is quite similar;computation of the entity closest to a given one within the selected PMDS (computation of semantic associates). In distributional semantics, words are usually represented as vectors in a multi-dimensional space of their contexts. Semantic similarity between two entities is then calculated as a cosine similarity between their corresponding vectors; it takes values between applying simple algebraic operations to entity vectors  within the selected PMDS;generation of the semantic maps (using the open-source software toolkit TensorFlow) of relations between input entities ;using other freely shared PMDS via special configuration file.Let us consider the methodology of a user experience with the graphical user interface of the UkrVectōrēs single-page application, in particular, for the distributional semantic analysis of natural language texts.Computation of the semantic associates for a given entity (word) within the selected distribution-semantic model. To use this function, you need to:https://ukrvectores.ai-service.ml/  and select the Semantic Associates operation mode in the main menu, as shown in Open the graphical user interface (GUI) of the UkrVectōrēs Single Page Application (SPA) using the current version of Google Chrome, Mozilla Firefox, or Microsoft Edge web browser. To do this, enter the following link in the address bar of the web browser: -size 500 -negative 5 -window 5 -threads 24 -min_count 10 -iter 20).Using the drop-down list of the select component named Models (in Ukrainian – Моделі) in In the field of the input component named “Enter the word lemma,” specify the desired word lemma for which you want to compute semantic associates , as shown in Semantic Associates will be displayed on the screen as shown in Using the “Entity” (in Ukrainian – “Сутність”) element, the user can choose to display the semantic associates alphabetically as shown in Using the “Cosine similarity” (in Ukrainian – “Косинусна близькість”) element, the user can choose to display the semantic associates by the cosine similarity coefficient (by increasing or decreasing) as shown in Generation of semantic maps  of relations between words within the selected distributional semantic model. To use this function, you need to:https://ukrvectores.ai-service.ml  and select the Semantic map mode in the main menu, as shown in Open the GUI of the UkrVectōrēs SPA using the current version of Google Chrome, Mozilla Firefox, or Microsoft Edge web browser. To do this, enter the following link in the address bar of the web browser: Using the drop-down list of the select component named Models (in Ukrainian – Моделі) in An example of visualization of the semantic associates of the lemma of the word “rehabilitation” (in Ukrainian – реабілітація) is shown in https://ukrvectores.ai-service.ml/ and is free for use in R&D and teaching purposes.The compilation & deployment technologies, and more detailed description of the source code of the UkrVectōrēs service, as well as the methodology for training the distributional semantic model of the vector representation of entities  in Europe”), are available in . Currently, the most recent version of the UkrVectōrēs service is available at The digital library of media content of the TISP Smart-system subsystem - the vHealth service  is a distributed information system that allows the storage, use, and sharing of various collections of electronic documents (video and audio content) of arbitrary domain areas, for distance learning of patients and their relatives, in particular, a rehabilitation set of exercises.One of the main tasks and purposes of the vHealth service is the integration of information resources and efficient navigation within them. Integration of information resources is their unification to use different information while preserving its properties, presentation features, and the ability to process it. The pooling of resources can occur both physically and virtually. However, at the same time, such a combination should provide the user with the perception of the necessary information as a single information space: an electronic library should ensure work with databases and high efficiency of the information search. Effective navigation in the electronic library is the ability of the user to find the information of interest to them in all available information space with the greatest completeness and accuracy at the least effort. To solve this problem, the vHealth service uses smart search based on predictive models of distributional semantics.The vHealth service has the following features:complete control over media content and user data;support for multiple publishing workflows: public, private, unlisted, and custom;types of multiple media support: video, audio, image, pdf (and docx in future releases);multiple media classification options: categories, tags, and custom;intelligent information search in real time based on the predictive models of distributional semantics ;playlists for audio and video content: create playlists, add, and reorder content;SPA responsive design: including light and dark themes;advanced users' management: allows self-registration, invite only, closed;configurable actions: allows download, add comments, add likes, dislikes, report media;enhanced video player: customized video.js player with multiple resolution and playback speed options;multiple transcoding profiles: sane defaults for multiple dimensions  and multiple profiles ;chunked file uploads: for pausable/resumable upload of content;logging of the user's session with the system with the ability to switch to each of the previously existing system states;manipulating the structure of the description of the media content object;support of the appliance of hypertext and hypermedia links, which provides the user with a quick transition from an object or its element to another interrelated object or element.Let us consider a brief look of the user experience with the graphical user interface of the vHealth single-page application.The GUI of the popular media platform Youtube, which is the standard for media content distribution systems, was taken as the basis for the development of the GUI of the vHealth SPA. During the development of the GUI of the vHealth network tool, one of the most important requirements for the modern graphical interface and user experience of the software system was met - the Do What I Mean concept. Therefore, the system works predictably, so that the user intuitively understands in advance what action the program will perform after receiving his command. This greatly improves the interaction of the user with the system and does not require the development of additional techniques and user settings for interacting with the graphical interface of the software system.The main elements of the GUI of the vHealth SPA are shown in the central part of the interface contains all media content available to the user according to his profile. Media content (by default) is categorized;the part of the interface on the left side contains the items of the main menu of the vHealth network tool, in particular, the items: “Upload” (in Ukrainian – Завантажити) (the function of uploading new media content); “My files” (in Ukrainian – Мої файли) (the function of viewing the uploaded media content in the user profile); “My playlists” (in Ukrainian – Мої плейлісти) (formation of playlists - playlists of media content with setting up workflows for publishing content); “History” (in Ukrainian – Історія) ; Stuff (in Ukrainian – Персонал) ; “Categories” and “Tags” ;the graphical interface of the user's profile (account) is shown in https://vhealth.ai-service.ml/ and is free for use f R&D and teaching purposes. To start working with the vHealth service, you need to be an authorized user (log in), so the demo account was created to demonstrate how the service works. You can log in using the login and password of the demo profile account .The compilation, deployment, and a more detailed description of the source code of the vHealth service, as well as the methodology of user interaction with the GUI of the vHealth application, require a separate review and is beyond the scope of this article. Currently, the most recent version of the vHealth service is available at The top-priority challenges were faced by the medical rehabilitation system in Ukraine. Particularly important tasks include, first of all, the rehabilitation of patients who have recovered from COVID-19 disease. This fact is well understood both by the society and the leadership of the Ministry of Health of Ukraine, which is creating a special working group on this problem. Ukraine has a system of medical and prophylactic institutions designed for psychological and physical rehabilitation of military personnel; these use modern rehabilitation technologies. However, long-term rehabilitation in such centers is not available to everyone. Therefore, the use of telerehabilitation technology for patients with post-traumatic stress disorder and similar disorders in combination with a means of objective control of the functional state is extremely important.In a large-scale pandemic, the number of patients undergoing rehabilitation therapy is growing unexpectedly. Therefore, it is very important today to create intelligent information-analytical systems to support rehabilitation processes, which solve a set of problems related to improving the effectiveness of combating such a global natural phenomenon.The V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine  is currently working on a project of the National Research Foundation of Ukraine  entitled “Development of the cloud-based platform for patient-centered telerehabilitation of oncology patients with mathematical-related modeling.”A special role in the implementation of all functionalities for the rehabilitation of patients in a large-scale pandemic includes:support of information-analytical processes of data collection and processing;classification of patients by health status;methodological recommendations for comprehensive rehabilitation;study of the fundamental causes and consequences of crisis (see pandemic) situations in the country and in the world;support for decision-making at all levels of public administration, development, and correction of the general policy of development of the state and its separate regions;providing information and advisory assistance to the population;methodological principles of recovery and rehabilitation in accordance with the recommendations of the WB and ICF.The project is based on cognitive information technology, which fully provides the process of analyzing large amounts of information resources. Cognitive services implement structuring and classification of information, synthesize the necessary documents based on semantic analysis, identify the characteristic properties of information processes and provide decision support at all stages of their life cycle: assessment of the patient's condition, formulation of rehabilitation diagnosis and rehabilitation goal, rehabilitation program assessment of functional consequences, determination of rehabilitation potential taking into account the nature of diseases, patient resources, as well as psychological and socio-environmental factors indicated by the ICF, adopted by the World Health Organization (WHO).The peculiarity of the system is that it is based on knowledge-oriented technology, ontology engineering, and a transdisciplinary paradigm.Rehabilitation specialists are faced with the need to determine the patient's rehabilitation potential for further routing and prognosis of recovery, as well as ongoing monitoring of the effectiveness of rehabilitation interventions. On the basis of this assessment, a rehabilitation plan and program are developed, indicating the prognosis for achieving certain tasks. There are numerous scales of functional assessment to assess rehabilitation potential. However, the analysis of these scales reveals the absence of specialized scales for assessing the cardiorespiratory system.In recent years, the Institute of Cybernetics team has developed an innovative method of scaling the electrocardiogram and heart rate variability. We have developed a method  and software for scaling the electrocardiogram, which is able to quantify the smallest changes in the electrocardiographic signal. The idea of our approach is first to measure the maximum number of routine and original electrocardiogram ECG parameters and heart rate variability, and second, to position each parameter on the scale between the absolute norm and extreme pathology.This technique is successfully used for functional assessment in the process of telerehabilitation of patients recovering after COVID-19 as well as patients with post-stress disorders.The purpose of our research was to develop a formal model, software implementation, and the methodological foundations for the use of services of the remote Patient / Personal-centered Smart-system for providing medical rehabilitation assistance to patients in a pandemic.In this paper, we introduced and defined:the basic concepts of the new Hybrid E-rehabilitation notion and its fundamental foundations;the formalization concept of the new Patient / Person-centered Smart-system for remote support of rehabilitation activities and services;the methodological foundations for the use of services  of the remote Patient / Person-centered Smart-system.The software implementation of the services of the Smart-system for remote support of rehabilitation activities and services has been developed, in particular:the digital library of media content of the telerehabilitation subsystem of TISP – the vHealth service;the UkrVectōrēs service - NLU-powered network tool for knowledge discovery, classification, diagnostics, and prediction.The research results were presented by our team on the All-Ukrainian forum “Ukraine 30: Education and Science” in section - “Big data Ukraine platform.” Also, the research results (in teleconference and offline) were presented during the workshop “Digital services and devices for rehabilitation measures support.”This study can be extended by future research in several directions, both in theory and in practice. Further research is also planned in the definition and application of efficient mathematical methods for big data analysis; modeling and creating scenarios (workflows) for predicting and optimizing the entire complex of rehabilitation procedures and their routing using system tools; and technologies, and experience in the development of rehabilitation systems and complexes that have already been tested by our team.In a future study, our teams plan to implement HIS to optimize the time spent by specialists of the multidisciplinary team in the use of ICF in the rehabilitation of cancer patients (including breast cancer). Further research will aim to determine and apply effective mathematical methods of big data analysis, modeling and developing of prediction scenarios, and optimization of the full set of rehabilitation procedures and their routing. This will employ tools already tested in the team system, technologies, and experience in developing rehabilitation systems.


Pain is the most incapacitating symptom of knee osteoarthritis (OA), with intermittent and/or continuous nature as described by the patients. Accuracy of pain assessment tools across different cultures is important. This study aimed to translate and culturally adapt the Intermittent and Constant OsteoArthritis Pain (ICOAP) measure into Arabic (ICOAP-Ar) and evaluate its psychometric properties in patients with knee OA.The ICOAP was cross-culturally adapted following the recommended guidelines from English. Knee OA patients from outpatient clinics were recruited to assess the structural  and construct validity (Spearman’s correlation coefficient - rho) to assess the relationship between the ICOAP-Ar and the pain and symptoms subscales of the Knee Injury and Osteoarthritis Outcome Score (KOOS), in addition to internal consistency . A week later, test-retest reliability (intraclass correlation coefficient (ICC)) was evaluated. Following four weeks of physical therapy treatment, the ICOAP-Ar responsiveness was evaluated using the receiver operating characteristic curve.Ninety-seven participants were recruited (age = 52.97 ± 9.9). A model with single pain construct showed acceptable fit (Comparative fit index = 0.92). The ICOAP-Ar total and subscales had a strong to moderate negative correlation with the KOOS pain and symptoms domains, respectively. The ICOAP-Ar total and subscales demonstrated satisfactory internal consistency (α = 0.86–0.93). The ICCs were excellent (ICCs = 0.89–0.92) with acceptable corrected item total correlations (rho = 0.53–0.87) for the ICOAP-Ar items. The ICOAP-Ar responsiveness was good with moderate effect size (ES = 0.51–0.65) and large standardized response mean (SRM = 0.86–0.99). A cut-off point of 51.1/100 was determined with moderate accuracy . No floor or ceiling effects were found.The ICOAP-Ar exhibited good validity, reliability, and responsiveness after physical therapy treatment for knee OA, which renders it reliable for evaluating knee OA pain in clinical and research settings.The online version contains supplementary material available at 10.1186/s12891-023-06492-w. Joint osteoarthritis (OA) is an active pathological joint condition associated with considerable multifactorial health burden , 2. It iLower extremity joints are the most affected by OA. This made the lower extremity joints the most common joints requiring replacement surgeries , 11. KneThe availability of a valid tool for measuring knee OA pain is important for patient assessment and follow-up. The importance is greatly emphasized with the conduction of multicenter and multinational studies targeting patients with knee OA. This necessitates standardized measurement tools for producing comparable and meaningful data. This is achieved by cross-cultural adaptation of a measurement tool across different languages. Focus groups examined the quality and characteristics of pain experienced by patients with hip and knee OA and reported two distinct types of pain; the intermittent and constant OA pain . TherefoThe ICOAP questionnaire has been cross-culturally adapted to different languages other than the original English version –25. ReceTherefore, the purposes for the current study were to appropriately translate and cross-culturally adapt the ICOAP measurement tool into Arabic and assess the psychometric properties of the culturally adapted Arabic version (ICOAP-Ar). The examined properties were validity , reliability , and responsiveness.Patients with Knee OA were recruited from those referred to the outpatient physical therapy clinic of King Fahd Military Medical Complex, Saudi Arabia, and Therapy & Rehab. Center, Egypt. The study was approved by the Institutional Review Board of the King Fahd Military Medical Complex, Saudi Arabia (AFHER-IRB-2020-024). All participants received verbal and written information about the study and signed the consent form.Eligible participants had to meet the knee OA diagnostic criteria according to the American College of Rheumatology (ACR) . These iThis psychometric testing study had two phases. Phase I for the translation and cross-cultural adaptation of the ICOAP measurement tool to create its equivalent Arabic version (ICOAP-Ar). Phase II was conducted to evaluate the psychometric properties of the ICOAP-Ar.After permission from the original developer (Dr. Gillian Hawker) was granted, and in accordance with the recommended guidelines , this prStage V, the prefinal version of the ICOAP-Ar was pilot-tested on a sample of 30 patients with knee OA for clarity and understanding to examine its face validity. The patients were asked to complete the prefinal ICOAP-Ar. Then, the participants were interviewed to record their feedback, using written feedback reports, about the questionnaire in terms of meaning of items, clarity of instructions and ability to self-complete it, and relevance to their condition. Participants’ interview reports were reviewed by the consensus panel and the ICOAP-Ar was modified as necessary.Eligible patients with knee OA were invited to join the study and were informed about the purpose of the study. After signing a consent form, participants were instructed to complete the ICOAP-Ar. The same patients were asked to retake the ICOAP-Ar 72–96 hours later for assessing the test-retest reliability of the ICOAP-Ar. Finally, after receiving four weeks of physical therapy treatment, responsiveness of the ICOAP-Ar was assessed.Structural validity of the ICOAP-Ar was examined using the exploratory factor analysis (EFA) to verify its dimensionality as previously recommended . Then, c95).Different measures were calculated to assess the reliability of the ICOAP-Ar. These included the test-retest reliability, internal consistency , standard error of measurement (SEM), and smallest detectable change at 95% confidence interval  scales after completing a physical therapy course. The GRoC was used as an external reference for calculation of measurement error and responsiveness. All study procedures and measures were administered and supervised by trained physical therapists.The ICOAP is an 11-item questionnaire. Each item is rated from 0 to 4 on a 5-point Likert scale. It has two subscales: constant pain (5 items) and intermittent pain (6 items). A score is calculated for the constant (0–20) and intermittent (0–24) subscales separately and for total pain (0–44), which are further normalized to a score of 0 (no pain) -100 (extreme pain) .The KOOS is a self-reported questionnaire used to subjectively assess five knee OA-relevant domains: Pain, Symptoms, Activities of Daily Living (Function), Sport and Recreation Function (Sport/Rec) and knee-related Quality of Life (QOL). It comprises 42 questions across the 5 subscales. A 5-point Likert scale is used to answer questions, and standardized answers are assigned a score from 0 (no symptoms) to 4 (extreme symptoms). Finally, a normalized score  is calculated for each subscale .The GRoC is a 15-point Likert scale used to assess the patient perceived deterioration or improvement following an intervention, ranging from − 7  to + 7 , with 0 indicating no change of condition. The GRoC includes a single question about change in health status after 4 weeks of physical therapy for knee OA .P ≤ 0.05 for all the analyses.Descriptive statistics were calculated, and data presented using frequencies and percentages for categorical variables and mean ± standard deviation for continuous variables. The normalized scores (0-100) of the ICOAP-Ar total and subscales were used for data analysis. Statistical analysis was performed using the Statistical Package for the Social Sciences  version 21. The level of significance was set at The sample size was calculated using the PASS software (Version 20.0.2) considering the Spearman’s correlation coefficient (rho) for testing the construct validity of the ICOAP-Ar. Based on acceptable rho value of at least 0.3 (R1 in PASS), a power of 90% and p value of 0.05, a sample size of 92 participants was required.The CVI, for the entire scale (S-CVI) and for each item independently (I-CVI), was used to evaluate the content validity of the ICOAP-Ar with an acceptable value of at least 0.8. Additionally, the S-CVI was calculated using the average I-CVI scores (S-CVI/Ave), and the proportion of scale items that were reported relevant by all the experts (S-CVI/UA).The EFA was implemented using the principal component analysis with varimax rotation and eigenvalue = 1, and based on acceptable values of greater than 0.5 for the Kaiser-Meyer-Olkin (KMO)  and lessConstruct validity was evaluated by calculating the rho between the ICOAP-Ar score and the relevant pain and symptoms score of the KOOS. The coefficient is classified as follows: rho = 0.3–0.7 moderate correlation, and > 0.7 strong correlation . We hypo95 were calculated using the formula: SEM =(SD×[√(1-ICC)]), where SD was the sample’s standard deviation and SDC95 = SEM ×1.96 ×√2, respectively [A Cronbach’s alpha value of ≥ 0.7, and corrected item-total correlation of ≥ 0.3 were considered acceptable , 38. Tesectively .change= ICOAP-ARfinal – ICOAP-ARbaseline) of the ICOAP-Ar total and subscale pain scores and the GRoC. The Spearman’s correlation coefficient was calculated with the same classification as described above [To assess responsiveness of the ICOAP-Ar, several approaches were implemented. We compared the pre- (baseline) and post-treatment (after four weeks) ICOAP-Ar total and subscale pain scores using the Wilcoxon Signed-Ranks test. The standardized effect size (SES) and standardized response mean (SRM) were calculated to evaluate the effect size, which was interpreted as large (≥ 0.80), moderate (≥ 0.50) or small (≥ 0.20). A hypothesis-testing approach was utilized to assess the correlation between the score changes (ICOAP-Ared above . It was 2 + (1 − specificity)2 [Finally, anchor-based responsiveness of the ICOAP-Ar score was assessed adopting the GRoC score as the external anchor. Participants were categorized according to their reported GRoC scores to either improved (GRoC ≥ 3) or stable group (GRoC < 3 to >-3). Receiver operating characteristics (ROC) curve of the ICOAP-Ar final score was blotted to calculate the area under the curve (AUC). An AUC value of ≥ 0.7 was considered adequate to indicate agreement with the GRoC . The cutficity)2 .The presence of floor and ceiling effects was evaluated as it compromises the responsiveness of a measurement tool. The floor and ceiling effects were considered present if more than 15% of the sample scored the lowest or highest possible score on baseline ICOAP-Ar subscales and total pain .The demographic data of the participants are summarized in Table Few differences were identified between the original and backward-translated versions of the ICOAP. Upon meeting with the author of the ICOAP scale, the panel of experts had consensus on most of the scale items. The main concerns were related to the translation of the words “frustrated or annoyed” and “upset or worried” in item 4 and 5, respectively. These terms could have nearly similar meanings when translated into Arabic. This was also reported by the participant’s feedback during pilot testing of the prefinal version of the ICOPA-Ar. Accordingly, the panel agreed after elaboration from the author to translate “frustrated or annoyed” to “إحباط أو إنزعاج” and “upset or worried” to “الضيق أو القلق”. Other than that, the participants did not report any difficulty regarding the clarity or understanding of the ICOAP-Ar during pretesting with a measured CVI between 0.97 and 1 for all the items.The ICOAP-Ar was very clear and easily understood by both the panel of experts and participants with an excellent I-CVI for all the items (I-CVI = 1). Similarly, the S-CVI, S-CVI/Ave and S-CVI/UA all had a perfect value of 1 Table .The EFA showed suitability for factor analysis with KMO = 0.88 and acceptable Bartlett’s index p < 0.001). The analysis yielded two factors that accounted for 67.8% of the variance. However, all the items loaded across the two factors. Items 1,2,3,6,7, and 8 loaded more on the first factor (loading range = 0.6–0.85), while items 4,5,10, and 11 loaded more on the second factor (loading range = 0.67–0.86). Item 9 loaded equally across factors (0.54–0.58). Therefore, we proceeded with the CFA considering a one factor model. The CFA revealed an acceptable factor loading for all the items  and moderate  negative correlation with KOOS pain and symptoms domains, respectively. The ICOAP-Ar constant pain domain had the lowest correlation with the KOOS pain and symptoms domains, while the ICOAP-Ar total had the highest correlation with the KOOS pain domain Table .95 ranged between 16.8 for the ICOAP-Ar total and 19.7 for its constant pain domain  and its domains showed excellent internal consistency. They also had excellent test-retest reliability (ICC = 0.98 − 0.92). The SEM for the ICOAP-Ar total and its constant and intermittent pain domains was 6.1, 7.1, and 6.3, respectively. The SDCin Table .The corrected item-total correlations were acceptable for the ICOAP-Ar items. The corrected item-total correlation coefficient ranged between 0.53 and 0.82 for the total scale. For the scale domains, it ranged between 0.55 and 0.77, and 0.75 and 0.87 for the intermittent and constant pain domains, respectively (Table P < 0.001). The mean score change for the entire sample ranged between 11.9 and − 12.9. The SES (0.51–0.65) and SRM (0.86–0.99) values for the ICOAP-Ar total and subscales were moderate and large, respectively. Additionally, there was a significant negative moderate correlation  between the ICOAP-Ar total and subscale change score and the GRoC (Table Forty-one (54.7%) patients reported improvement according to their GRoC score. There was a significant difference between the pre- and post-treatment ICOAP-Ar total and subscale scores  reported that EFA of the ICOAP scale revealed a single pain construct suggesting sufficient homogeneity between the 11 scale items . This waOur predictions regarding the construct validity of the ICOAP-Ar were all confirmed. The ICOAP-Ar total and subscales scores had strong (rho= -0.71 to -0.76) to moderate (rho= -0.57 to -0.68) negative correlations with the KOOS pain and symptoms subscales, respectively. This finding is in agreement with previous studies validating the Portuguese (rho= -0.61 to -0.81) , PersianIt is important to note that the ICOAP-Ar  correlation coefficients were higher with the KOOS pain domain than those calculated with the KOOS symptoms domain. This interesting finding was in line with the previous studies that validated the different versions of the ICOAP scale. It was consistently observed in studies that used the KOOS pain and symptoms subscales to examine the construct validity of the ICOAP scale , 23, as The internal consistency of the ICOAP-Ar total and subscales was excellent , which indicates the consistency and homogeneity of the scale items. This corresponds well with the Cronbach’s alpha values reported for the original   and diff95 value of 16.8 points for the ICOAP-Ar total score. This means that an ICOAP-Ar score change of at least 16.8 points is required to be interpreted as a real within-subject change of knee OA pain [The ICOAP-Ar total (ICC = 0.91) and its constant (ICC = 0.92) and intermittent (ICC = 0.89) pain subscales showed excellent test-retest reliability reflecting the questionnaire’s good reproducibility. The obtained values are slightly higher than those reported for the original version (ICC = 0.85) , but com OA pain .95 values (3.7/10.3 points) of the ICOAP total pain were reported for the traditional Chinese version (tChICOAP) only [95 values for the other language versions from the published data. The SEM/MDC95 values were 6.7/18.5 and 6.9/19.1 points for the Persian and Portuguese ICOAP total pain, respectively [95 values for the ICOAP-Ar total pain are highly comparable to those for the other language versions, except the tChICOAP. This could be attributed to the sample criteria and baseline tChICOAP total pain score. The baseline tChICOAP total pain score (34.52) is less than that for the ICOAP-Ar (55.76). Accordingly, one could logically speculate limited score variability for the tChICOAP compared with the ICOAP-Ar upon retest, which was represented by the higher test-retest reliability for the tChICOAP  compared with the ICOAP-Ar  total pain score.The SEM/MDCAP) only . Howeverectively , 23. It Our findings provided evidence supporting the accuracy and sensitivity to change of the ICAOP-Ar after physical therapy treatment for knee OA. The ICOAP-Ar total and subscale pain scores were significantly reduced after the four-week treatment period revealing a moderate effect size (SES = 0.51–0.65), but large SRM (0.86–0.99). Responsiveness of the original ICAOP scale was previously examined, and the findings showed variable low (SES = 0.46–0.54), moderate (SES = 0.5–0.88), and large (SES = 0.93–1.71) effect size for pharmacological treatment, intra-articular injection, and joint replacement surgery, respectively , 47–50.Responsiveness of the ICOAP to physical therapy treatment was assessed for the Portuguese version . CompareThe predefined hypothesis regarding the correlation between the score changes of the ICOAP-Ar total and subscale pain and the GRoC were established showing a moderate negative correlation rho= -0.44 to -0.48), which is consistent with the findings of the Portuguese version (rho= -0.56 to -0.64) . The acc to -0.48Some limitations of this study should be addressed. Unfortunately, we were not able to validate the ICOAP-Ar scale for the hip OA patients as we could not recruit enough participants to perform reliable data analysis. Our sample may not be representative since it had a short knee OA duration. However, the impact knee OA duration may have on the psychometric properties of the ICOAP-Ar is expected to be minimal. We did not examine the responsiveness characteristics of the ICOAP-Ar in patients with knee OA receiving treatments other than the physical therapy, which we believe is important to provide comprehensive data regarding the validation of the ICOAP-Ar scale.The ICOAP scale was successfully cross-culturally adapted into Arabic following international guidelines. The ICOAP-Ar total and subscale is a valid and reliable tool to assess knee OA pain. It has also demonstrated adequate accuracy and sensitivity to knee pain change in response to physical therapy intervention. An ICOAP-Ar total score of 51.1 points could be used as a cut-off to discriminate the response of patients with knee OA to physical therapy treatment.Below is the link to the electronic supplementary material.Supplementary Material 1


To investigate the relationship between intraretinal hyperreflective foci (HRF) and visual function in intermediate age-related macular degeneration (iAMD).Retrospective, cross-sectional study. iAMD patients underwent spectral domain optical coherence tomography (SD-OCT) imaging and vision function testing: normal luminance best corrected visual acuity (VA), low luminance VA (LLVA), quantitative contrast sensitivity function (qCSF), low luminance qCSF (LLqCSF), and mesopic microperimetry. Each OCT volume was graded for the presence and number of HRF. Each HRF was graded for: separation from the retinal pigment epithelium (RPE), above drusen, and shadowing. Central drusen volume was calculated by the built-in functionality of the commercial OCT software after manual segmentation of the RPE and Bruch’s membrane.HRF group: 11 eyes; 9 patients; mean age 75.7 years. No-HRF group: 11 eyes; 10 patients; mean age 74.8 years. In linear mixed effect model adjusting for cube-root transformed drusen volume, HRF group showed statistically significant worse VA, LLVA, LLqCSF, and microperimetry. HRF group showed worse cone function, as measured by our pre-defined multicomponent endpoint, incorporating LLVA, LLqCSF and microperimetry (p = 0.018). For eyes with HRF, # of HRF did not correlate with any functional measures; however, % of HRF separated from RPE and # of HRF that created shadowing were statistically associated with low luminance deficit (LLD).The association between the presence of HRF and worse cone visual function supports the hypothesis that eyes with HRF have more advanced disease. Age related macular degeneration (AMD) is the leading cause of central vision loss in Americans over the age of 50.  Based onIn parallel to the advancement of our understanding of OCT pathologies seen in AMD, it is also known that while patients with non-neovascular AMD can measure relatively well in visual acuity (VA) tests under normal luminance, they can exhibit significant deficits in other visual functional tests. For example, patients with non-neovascular AMD, as compared to normal controls, can have equivalent normal luminance BCVA, but worse visual functions, as measured by low luminance (LL) VA, microperimetry, dark adaptation rod function,  and mesoIn recent years, several studies have attempted to correlate OCT pathological features with visual function testing in AMD, but the results have been inconclusive. Neely et al.  found tha priori, as all three outcomes measure to some degree cone function and can be considered collectively.As an extension of previous works, the current study aimed to correlate HRF, as detected on b-scan OCT images, with various visual function tests, including microperimetry, normal luminance VA, LLVA, qCSF and low luminance qCSF (LLqCSF). qCSF testing leverages active learning to allow for testing of contrast sensitivity at various combinations of spatial frequencies and contrast levels, whereas traditional Pelli-Robson charts only measure contrast at a single spatial frequency . qCSF haOur study was a retrospective cross-sectional study that was approved by the University of Texas Southwestern  institutional review board. It adhered to the Declaration of Helsinki and the Health Insurance Portability and Accountability Act.Participants. All study participants provided written informed consent, and were seen at the Retina Foundation of the Southwest . Inclusion criteria included: patients aged 55 years or older, iAMD as determined by retinal specialist (K.G.C) based on clinical examination and multimodal imaging, , which uses a line-scanning laser ophthalmoscope for fundus tracking at 25 frames per second. Visual sensitivity thresholds at each location were measured using a 4 − 2 staircase strategy. A customized stimulus pattern consisting of Goldman spot size III at 37 locations and sampling the central 6º radius of the macular region was used. Microperimetry results were obtained on the same date as other vision function assessments, and involved a minimum of 2 prior baseline assessments. All MAIA results were required to be reliable, defined as having a false-positive rate of ≤ 25%. False-positive rates were determined based on the percentage of positive responses to presentations of suprathreshold stimuli to the optic nerve head . The microperimetry parameter examined in this study was the mean of the pointwise sensitivity results. All but three eyes underwent MAIA mesopic microperimetry testing.Contrast sensitivity testing. qCSF testing was performed with spectacle correction at 3 m in a dimly-lit room, under both standard luminance and low luminance . Each patient was presented with a series of 25 triplets (75 optotypes of various sizes and contrasts), and asked to identify the letters on a NEC LED monitor (Manifold Contrast Vision Meter) with a screen size of 19.4 × 11.0 degrees of visual angle and a background luminance of 90 cd/ m2 . The optotypes used were special bandpass-filtered Sloan optotypes, and the optotypes for each round of testing were chosen from a wide range of contrast levels (Michelson contrast 0.20 − 98.20%) and spatial frequencies (1.0–27 cpd) to maximize the information gained [n gained . The patHyperreflective foci and central drusen volume grading. Each SD-OCT volume was graded by a board-certified retinal specialist (T.Y.A.L.) for the number of hyperreflective foci seen within the scanned volume. A hyperreflective focus by definition has a reflectivity similar to or more intense than that of the retinal pigment epithelium (RPE)-Bruch’s membrane band and is at least 3-pixel wide [xel wide  as measuxel wide . Large bxel wide . In addiStatistical analysis. Linear mixed effects models, adjusting for cube-root transformed drusen volume and VA, were used to compare the 7 visual function outcomes between the HRF and no-HRF groups. A random intercept for patients was included in the models to account for the correlation between OD and OS of bilateral patients. The multicomponent endpoint, combining LLVA, LLqCSF and average mesopic MAIA threshold, was also compared between the two groups, using the nonparametric O’Brien’s test. To quantify the spread of signal intensities within each eye recorded across the 37 targets on MAIA microperimetry, mean and standard deviation (SD) of signal intensity for each eye was calculated. The mean and SD of MAIA microperimetry signal intensities of the HRF group and no-HRF group were compared, using linear mixed effects model. For the HRF group, Spearman’s correlation coefficient was used to examine the correlation between the number of HRFs and the functional metrics within each eye. Considering potential correlation between the eyes from the same patient, a sensitivity analysis of using one eye per patient was also carried out. Spearman’s correlation coefficient was used to examine the correlation between the 4 qualitative variables of HRF and the functional metrics within each eye. All statistical analysis was performed using the Stata v17.0 software.In total, 11 eyes from 9 patients and 11 eyes from 10 patients were included in the HRF and no-HRF group, respectively. The mean age was 75.7 and 74.8 years for the HRF and no-HRF group, respectively p = 0.83). 89% and 40% patients were female in HRF and no-HRF group, respectively. All patients were Caucasian, and there was no difference in age between the groups. There was a difference in the mean central 3 mm drusen volume between the HRF group .The signal intensity variation on MAIA testing within each eye was compared between the HRF and no-HRF group, using linear mixed effects models. The HRF group showed higher intra-eye variations (p = 0.004) and lower mean signal intensity (p = 0.016).We performed additional analyses for the HRF group. No significant correlation between the number of HRF and the 7 functional measures was observed. Each HRF was also graded qualitatively on whether it was separated from the RPE, above drusen and created shadowing of the underlying structures. The % of HRF separated from the RPE and total number of HRF that created shadowing were statistically associated with LLD.a priori, as all three measure cone function to varying degrees.Our study was carried out to interrogate the concept that patients with HRF represent a more advanced state of iAMD and, as such, these patients will exhibit worse visual function, when compared to iAMD patients without HRF. Indeed, our data demonstrated that eyes with HRF, as compared to eyes without HRF, exhibited worse cone function. Not only did eyes with HRF showed worse VA, LLVA, LLqCSF and average mesopic MAIA threshold, they also performed worse on our pre-defined multicomponent end point. We chose to include LLVA, LLqCSF and mesopic MAIA in our multicomponent endpoint Coincidentally, our HRF group also had a higher mean central drusen volume. In our secondary analysis adjusting for the presence and absence of HRF, cube-root transformed central drusen volume was found to be associated with LLD measurement, which was in contrast to our prior study showing no such correlation in eyes with iAMD . In our In our study, eyes with HRF had both lower mean MAIA threshold values and higher intra-eye signal intensity variation. Again, the presence of HRF appears to indicate more diffuse, advanced disease that involves localized damage and dysfunction within the cone cells, leading to more variable signal intensity measurements. However, within the HRF group, a higher number of HRF within each eye did not correlate with any of the 7 functional measures: VA, LLVA, LLD, qCSF, LLqCSF, LLDqCSF and average MAIA threshold. This is either because our study was underpowered to detect a difference or the number of HRF is not an accurate surrogate marker for disease severity. Perhaps, the HRF area would be a more robust predictor for worse visual function, as HRF area has been shown to be significantly correlated with progression to late AMD over the course of one year . Of noteA recent study by Echos et al.  demonstrOur study demonstrated an association between the presence of HRF with cone mediated visual function in eyes with iAMD, thus further supporting the usefulness of using HRF as a surrogate marker for disease severity. However, our study is limited by the small sample size and its cross sectional nature. As the next step, a larger study including patients with both early and iAMD will be conducted. Longitudinal imaging and functional data will be collected to investigate whether longitudinal structural changes, such as the change in HRF area, are correlated with change in visual function.


Anterior decompression and fusion (ADF) using the floating method for cervical ossification of the posterior longitudinal ligament (OPLL) is an ideal surgical technique, but it has a specific risk of insufficient decompression caused by the impingement of residual ossification. Augmented reality (AR) support is a novel technology that enables the superimposition of images onto the view of a surgical field. AR technology was applied to ADF for cervical OPLL to facilitate intraoperative anatomical orientation and OPLL identification. In total, 14 patients with cervical OPLL underwent ADF with microscopic AR support. The outline of the OPLL and the bilateral vertebral arteries was marked after intraoperative CT, and the reconstructed 3D image data were transferred and linked to the microscope. The AR microscopic view enabled us to visualize the ossification outline, which could not be seen directly in the surgical field, and allowed sufficient decompression of the ossification. Neurological disturbances were improved in all patients. No cases of serious complications, such as major intraoperative bleeding or reoperation due to the postoperative impingement of the floating OPLL, were registered. To our knowledge, this is the first report of the introduction of microscopic AR into ADF using the floating method for cervical OPLL with favorable clinical results. In recent years, extended reality (XR) technology, which collectively refers to mixed reality (MR), augmented reality (AR), and virtual reality (VR) technologies, has been developing rapidly. XR technology is beginning to be used in social applications such as education and training, work support, and leisure as well as in the medical field. XR technology is finding its place in healthcare, and spine surgery is no exception. In the past few years, computer-aided technology, such as conventional navigation systems, has advanced. In surgery, a surgical imaging support tool is becoming an indispensable technology, and further utilization of XR technology is expected ,2. A uniCervical ossification of the posterior longitudinal ligament (OPLL) is a degenerative spinal disease that causes neurological dysfunction ,4,5. In Conventional three-dimensional (3D) navigation systems have limitations in displaying the positional relationships between the surgical target and the basic structures in the surgical field. This can make it difficult for surgeons to accurately identify the full shape of OPLL and avoid the insufficient decompression caused by the impingement of residual ossification. However, AR support is a novel technology that enables the superimposition of images, such as radiographs and navigation pathways, onto a view of the surgical field ,23. In rMoreover, AR support is highly flexible and can be integrated with navigation systems, making it an ideal technology for spine surgery. AR support can display preoperative imaging data on the patient during surgery, allowing the surgeon to precisely align implants and instruments with the patient’s anatomy ,25. AR sIn this study, we report our surgical experience of applying AR support to ADF using the floating method. Our results demonstrate that AR support can improve the accuracy of surgery by enabling surgeons to better identify the full shape of OPLL and avoid the insufficient decompression caused by residual ossification.This study was a retrospective observational study. This study was approved by the institutional review board of the Saiseikai Kawaguchi General Hospital , and written informed consent was obtained from all participants. All of the surgeries were performed by attending spine surgeons that were certified by the Japanese Orthopaedic Association and the Japanese Society for Spine Surgery and Related Research.This study included 14 patients who underwent AR-assisted spinal surgery since March 2021 and 53 patients who underwent spinal surgery without AR support  before 2021 at Saiseikai Kawaguchi General Hospital and Tokyo Medical and Dental University.At our institution, patients with cervical OPLL who have OPLL with a ≥50% occupying ratio and/or K-line (−) OPLL were generally treated with ADF. In ADF, the anterior OPLL floating technique was utilized in all patients, as described by Yamaura et al. ,11,12,18TM Surgical Imaging System, Medtronic Navigation Inc., Littleton, MA, USA) was used to create an augmented image model in the navigation system   A.TM, Medtronic Navigation Inc., MA, USA). The outline of the ossification was marked on the monitor using axial computed tomography (CT) views taken with the intraoperative O-arm system. The ossification was marked for each axial slice from the cranial end to the caudal end of the OPLL. The bilateral vertebral arteries were also marked in the same manner. After all ossification and vertebral arteries within the surgical area were marked on the axial views, they were reconstructed on the 3D image  were used C. A regiThe decompression area was determined with reference to the ossification outline visualized under the AR microscope view A. To avoNeurological status was assessed preoperatively and 1 year postoperatively using the Japanese Orthopaedic Association (JOA) scoring system. The JOA recovery rate was calculated as described by Hirabayashi et al. . AdditioThe lateral cervical spine radiographs of the neutral standing positions were obtained before and 1 year after surgery to measure the (1) C2–7 angle (C2–7 lordotic angle), (2) cervical sagittal vertical axis (SVA) (center of gravity of the head–C7 SVA), and (3) C7 slope . Decompr2 test or the Mann–Whitney U test. A p-value of less than 0.05 was considered statistically significant.Neurological and radiographic assessments were performed by observers other than the principal surgeon. Statistical analyses were performed using the JMP software . Intergroup comparisons were drawn using the χ2. The surgical procedure details are shown in In total, 14 patients with cervical OPLL underwent ADF with microscopic AR support. The cohort included 4 women and 10 men with a mean age of 63.5 ± 10.9, and the mean BMI was 26.4 ± 5.1 kg/mp = 0.007). Regarding intra-/postoperative complications, there was no significant difference in the incidence of CSF leakage or nerve palsy between the two groups. Graft dislodgement was only observed in the non-AR-supported group. Reoperation due to inadequate decompression and graft dislodgement was only seen in the non-AR-supported group . Impingement of floating OPLL was seen in one case in the AR-supported group, but after surgery the degree of spinal cord compression decreased, clinical symptoms improved, and no major complications requiring reoperation occurred in the AR-supported group. There was no difference in the postoperative cervical spine alignment  between the two groups.The patient data for the AR-supported and non-AR-supported groups are summarized in A 58-year-old man presented with bilateral hand clumsiness and gait disturbance. He underwent ADF using the floating method at the C4–C7 levels A,B. An iTo our knowledge, this is the first report on the introduction of microscopic AR into ADF using the floating method for the treatment of cervical OPLL. The microscopic AR support is considered to be effective because the shape of ossification, which is not directly visible intraoperatively, can be visualized through a microscope, which enables sufficient decompression of the OPLL, even when the number of corpectomies is reduced. In addition, reoperations due to major complications such as decompression failure and graft dislocation could be eliminated.AR technology has been introduced into surgery since the 1990s. Franken et al. explored a three-dimensional on-screen microsurgical system (TOMS) that eliminated the need to view the operative field through microscope eyepieces . In the In recent years, AR technology has been employed in spine surgery. AR guidance in spine surgery enables the accurate placement of instruments such as pedicle screw insertion, rod bending, and percutaneous vertebroplasty ,32. FurtADF for cervical OPLL is an ideal surgical technique for the direct decompression of the spinal cord, where the ossification is floated or resected ,12,13,14Recent advancements in intraoperative imaging modalities, such as mobile CT and navigation systems, and their application to ADF using the floating method for OPLL enable surgeons to easily identify the ossification outline during an operation. Because of these technological advances, insufficient decompression caused by the impingement of ossification can be reduced, improving clinical outcomes ,22. FurtIn this study, ADF using the floating method with AR support was performed in 14 patients, and favorable postoperative results were obtained. Based on the improvement in the JOA score (52.5%–71.4%), operative time (271.2–335.9 min), and blood loss (287.5–600 g) values reported in previous multicenter studies, our surgical outcomes with AR support were comparable with previous reports ,39,40,41The practical applications of ADF using the floating method with AR support are numerous and significant. One of the main advantages of AR support is the ability to accurately identify the shape and location of OPLL during surgery. This can help reduce the risk of insufficient decompression and improve surgical outcomes. By overlaying preoperative images onto the surgical field, AR provides real-time visualization of the shape and location of OPLL, allowing surgeons to make more precise and informed decisions during the procedure. AR also enhances the visualization of anatomical structures, such as nerves and blood vessels, which can be difficult to identify during surgery. In addition, AR support for ADF using the floating method allows for “selective wedge corpectomy” and reduces the number of corpectomies that are needed, as it allows the visualization of ossification behind the vertebral body, which is not visible. Furthermore, AR support for ADF using the floating method has been shown to reduce the need for reoperation due to postoperative graft dislodgement or insufficient decompression. This is a significant advantage because additional surgeries increase the risk of major complications and can negatively impact patient outcomes. Therefore, although complications have occurred in some cases, the potential benefits of AR navigation in reducing the need for reoperation and improving intraoperative accuracy and safety should be recognized.This study has two main limitations, its retrospective nature and the small sample size, which may affect the strength of our conclusions and the generalizability of our findings. The limited case series is due to the fact that only a few centers have access to AR support technology. Despite these limitations, our study provides valuable insights into the potential benefits of using AR support in surgical contexts. We hope our research serves as a basis for future large-scale prospective studies that can further validate and strengthen the evidence in this area. Ultimately, we believe that our results will contribute to the development of the ADF surgical floating and decompression technique for cervical OPLL and hold clinical significance.This is the first report on the introduction of microscopic AR into ADF using the floating method for the treatment of cervical OPLL. AR support for ADF using the floating method had favorable clinical results and enabled sufficient decompression of OPLL.


Prostate cancer is the most prevalent cancer in men worldwide and is promoted by the sex hormone androgen. Expression of androgen from the testis can be significantly reduced through castration. However, as most prostate cancer patients acquire castration resistance, additional therapeutic solutions are necessary. Although anti-androgens, such as enzalutamide, have been used to treat castration-resistant prostate cancer (CRPC), enzalutamide-resistant CRPC (Enz-resistant CRPC) has emerged. Therefore, development of novel treatments for Enz-resistant CRPC is urgent. In this study, we found a novel anti-androgen called pinostilbene through screening with a GAL4-transactivation assay. We confirmed that pinostilbene directly binds to androgen receptor (AR) and inhibits its activation and translocalization. Pinostilbene treatment also reduced the protein level and downstream gene expression of AR. Furthermore, pinostilbene reduced the protein level of AR variant 7 in the Enz-resistant prostate cancer cell line 22Rv1 and inhibited cell viability and proliferation. Our results suggest that pinostilbene has the potential to treat Enz-resistant CRPC. In 2015–2020, 109.9 per 100,000 men of all races and ethnic groups developed prostate cancer2. In the United States, the incidence of prostate cancer increased by 3% every year from 2014 to 20192. Although prostate cancer has the second highest 5-year relative survival rate of 97%, due to the high incidence rate, the death toll per 100,000 people in 2015–2020 was 18.8, which is second highest after lung cancer2. In early stages, prostate cancer is subclinical and indolent3. However, it induces abnormal urination as a salient symptom4. Patients with this disease have prostatic hypertrophy that leads to frequent urination and nocturia5. In more advanced stages, patients suffer from retention of urine and pain in the back, hips, or limbs6.Prostate cancer is the most common type of cancer found in men globally7. Androgen receptor promotes the transcription of prostate-specific antigen (PSA) and transmembrane protease serine 2 (TMPRSS2) in the prostate9. PSA has been reported to promote the growth of AR-positive hormone-refractory prostate cancer cells such as CWR22rv1 and high passage LNCaP10. PSA promotes prostate cancer cell migration involved in the progression of prostate cancer11. Serum PSA level is an indicator of the disease12. It has been reported that TMPRSS2 plays an important role in prostate cancer cell invasion, tumor growth, and metastasis by activating matriptase and promoting extracellular matrix degradation14.Androgen receptor (AR) is a steroid hormone receptor activated by male sex hormones such as testosterone and dihydrotestosterone (DHT) and acts as a transcription factor by binding to the promoter in the nucleus16. Orchiectomy, LHRH agonist, or antagonist treatment is often used as the first-line option to reduce the level of androgen produced in the testicles18. However, despite receipt of these treatments, most patients with metastatic prostate cancer eventually develop castration-resistant prostate cancer (CRPC) because of the small amounts of androgens produced in other organs such as the adrenal glands20. Anti-androgens such as enzalutamide, which inhibits AR level and downstream signaling by binding to AR ligand binding domain (LBD), were developed to treat CRPC22. Nevertheless, a significant number of CRPC patients is innately resistant (primary resistance) or acquire resistance (secondary resistance) to the anti-androgen treatment, hindering treatment of CRPC23. Several studies have pointed out that one of the causes of enzalutamide resistance is AR splice variants25. Most AR splice variants lack the C-terminal LBD and have an intact N-terminal transactivating domain and DNA-binding domain (DBD)26. AR variant 7 , which lacks LBD, is one of the major constitutively active splice variants that is not regulated by androgens or anti-androgens and can induce the expression of androgen-responsive genes28. It was reported that the mRNA expression of ARv7 is 20-fold higher in hormone-refractory prostate cancer than hormone-naïve prostate cancer28. For this reason, ARv7 is heavily involved in enzalutamide resistance (Enz-resistance) and hinders treatment of CRPC29. Therefore, it is necessary to develop drugs targeting Enz-resistant CRPC by inhibiting ARv7.Because AR and male sex hormones contribute to prostate carcinogenesis, hormone therapy is an essential option for prostate cancer patientsPinus sibirica, is a monomethylated derivative of resveratrol that has anti-obesity, anti-inflammatory, hepatic protection, and neuroprotection capabilities31. Pinostilbene is also reported to inhibit proliferation of androgen-responsive human prostate cancer LNCaP cells, although its target and exact action mechanism are not known32.Pinostilbene, a natural product found in In this study, we found that pinostilbene inhibits the transactivation of AR and investigated how it binds to AR. We explored how pinostilbene suppresses AR by analyzing its protein and mRNA levels. We found an inhibitory effect of pinostilbene on nuclear localization of AR and confirmed cytotoxicity and growth inhibition effects on prostate cancer cell lines. Furthermore, we revealed the efficacy of pinostilbene on 22Rv1, the Enz-resistant prostate cancer cell line. Here we present the effect of pinostilbene in inhibiting the action of ARv7, an AR variant.We performed an AR-LBD-GAL4 transactivation assay to identify novel compounds that can inhibit dimerization of AR by binding to its ligand binding domain (AR-LBD) Fig. A. We co-Among the candidates, we found that pinostilbene effectively inhibits the luciferase activity of AR that is increased by DHT Fig. B,C.We tested the interaction of GST-AR LBD and pinostilbene through Surface Plasmon Resonance Analysis. Recombinant GST-AR LBD was successfully bound to the sensor chip for SPR analysis  in the promoter DNA sequences to initiate transcriptionWe also confirmed the suppression of nuclear localization of AR by pinostilbene through a cell fractionation assay. When LNCaP cells were treated with DHT, the protein expression of AR increased in the nuclear fraction. In contrast, when pinostilbene and DHT were used together, AR in the nuclear fraction was significantly decreased Fig. B. Taken The LNCaP cell line is a prostate cancer cell line whose growth is highly affected by the expression and activity of AR. Therefore, we tested whether pinostilbene can modulate the viability and growth of LNCaP through AR inhibition.40, pinostilbene showed little cytotoxic effect 45. In phase III studies, the most frequent side effects of enzalutamide treatment were psychiatric and vascular disorders46. Therefore, it is essential to develop a new anti-androgen drug to counter the resistance to enzalutamide and reduce its side effects.Castration resistance has been an issue of interest in the field of prostate cancer for decades. The development of drugs that target androgens has been effective because adrenal androgens have the potential to promote prostatic cancer growth even if testicles are removed through orchiectomy47. Moreover, SREBP-1 was reported to regulate AR promoter activity and transcriptional expression in prostate cancer cells48. Therefore, we hypothesize that pinostilbene may regulate the gene expression of AR by regulating SREBP-1. We are also aware of the possibility that pinostilbene may regulate alternative splicing of AR. Although molecular mechanism leading to alternative splicing of AR and how anti-androgens inhibit AR splicing have been unclear, recent studies have shown that it is mediated by various splicing factors such as KDM4B and hnRNP F50. In addition to these hypotheses, there is also a possibility that pinostilbene may regulate the mRNA stability of ARv7. In further study, we are going to test how pinostilbene affects the expression or activity of splicing factors or mRNA stability.Decrease in the levels of full-length AR and ARv7 was not induced by proteasomal degradation because MG132 treatment did not rescue the reduction of AR protein by pinostilbene treatment  increases its hydrophobicity and cell membrane permeability, resulting in a higher effective intracellular dosage, implying that pinostilbene is more effective in the body than resveratrol31.Resveratrol , a precursor to pinostilbene , has been shown to have anticancer activity against prostate cancer and to inhibit transcription activity of AR as well as its protein expression53. However, in cell level, we could not find any combination effect of enzalutamide and pinostilbene. Further validation of combination effects of pinostilbene and another anti-androgen are needed.Co-treatment with enzalutamide is also an important therapeutic option in CRPC. Studies have reported that the combination of enzalutamide and other anti-androgens that target ARv7 has potential in the treatment of Enz-resistant CRPCIn this study, we found pinostilbene to be a novel AR antagonist through GAL4-AR-LBD transactivation assay. We confirmed that pinostilbene can directly bind to LBD of AR and can effectively modulate AR expression and expression of its downstream genes at the cellular level. We also found that treatment of prostate cells with pinostilbene inhibited nuclear localization of AR. Finally, we confirmed the AR-dependent cytotoxicity of pinostilbene in LNCaP cell lines. In addition, we confirmed that pinostilbene is cytotoxic even in the Enz-resistant prostate cancer cell line 22Rv1), and that it reduces expression of ARv7 and full-length AR. These results strongly suggest pinostilbene as an attractive option for treating Enz-resistant CRPC.2. HEK-293A cells, HaCaT cells, and 22Rv1 cells were cultured in DMEM/High Glucose (Hyclone) supplemented with 10% FBS and 1% penicillin–streptomycin at 37 °C with 5% CO2.LNCaP cells were cultured in RPMI-1640  supplemented with 10% fetal bovine serum  and 1% penicillin–streptomycin  at 37 °C with 5% COFirefly luciferase and Renilla luciferase reporter plasmids. After 24 h incubation, 100 nM 5α-Androstan-17β-ol-3-one  were treated with or without different concentrations of neuroprotection library compounds (InterPham) or pinostilbene hydrate  for 12 h.HEK-293A cells were transfected with GAL-hAR-658-919 , UAS-promoter E. coli BL21-Codon Plus (DE3) RIPL strain. Transformed E. coli were selected and grown in ampicillin agar plates at 37 °C. Selected colonies were picked and cultured in LB media until the OD 0.6–0.8. After ice incubation for 20 min, 0.5M IPTG was added for protein induction and incubated at 18 °C for 24 h. E. coli was resuspended with 1× cold PBS and disrupted by a sonicator. Cell lysates were centrifuged at 18,000 rpm, and the supernatants were obtained and incubated with glutathione-sepharose 4B agarose beads  at 4 °C for 24 h. After incubation, the lysates were centrifuged and supernatants were removed. Pellets were obtained and washed by 1× PBS with 1% Triton X-100. GST-AR-LBD proteins were eluted with GST elution buffer .GST-tagged AR-LBD protein was expressed in SPR analysis was performed by IMSPR-Pro-HT (ICLUBIO). Brief procedure was performed by manufacture’s guide. Recombinant GST-AR-LBD proteins were immobilized on –COOH sensor chip  through amine coupling using EDC (1-ethyl-3-(3-dymethylaminopropyl)carbodiimide)/NHS (N-hydroxysuccinimide) and remaining succinimide esters on sensor chip were blocked and de-activated by etahnolamine. Ligands in indicated concentration solved in 1% DMSO were flowed into the AR-LBD-immobilized chip. Then the chip was washed with 1% DMSO. Bound ligands were detached by 10 mM NaOH solution. The Response units (RU) was measured throughout all steps with iMSPR ProX  using iMSPR software. Data evaluation and comparison, presentation were performed using TraceDrawer 1.9.2 .http://www.rcsb.org/). Already bound small molecules such as sulfate ions, ligand (DHT), and water molecules were removed. Then the macromolecule file was converted to PBDQT format for docking analysis. Grid square for ligand docking is set to cover all AR LBD. Molecular docking was performed by Autodock Vina module in PyRx software34. Visualization of docking pose and prediction of binding site between AR LBD and pinostilbene was performed by PyMOL software AR LBD (PDB: 2pip) structure file was downloaded from the Protein Data Bank , anti-AR-V7 specific , anti-PSA , anti-GAPDH , anti-Lamin A/C .Cells were lysed by lysis buffer ) and disrupted by a sonicator. Cell lysates were centrifuged at 15,000 rpm and soluble supernatants were separated. 15–30 μg of cell lysates were mixed with sample buffer  and separated by 10% SDS-PAGE. The proteins were transferred to nitrocellulose membrane. Membranes of each protein size were probed with the primary antibodies and the corresponding secondary antibodies. The signals were detected using LAS-500  according to manufacturer’s protocol. All signals were quantified using Image J softwarehAR, 5′-ATGGTGAGCAGAGTGCCCTA-3′ and 5′-GTGGTGCTGGAAGCCTCTCCT-3′hPSA, 5′-AAAAGCGTGATCTTGCTGGG-3′ and 5′-CATGACCTTCACAGCATCCG-3′hTMPRSS2, 5′-TCTAACTGGTGTGATGGCGT-3′ and 5′-GGATCCGCTGTCATCCACTA-3′hGAPDH, 5′-CCAAGGAGTAAGACCCCTGG-3′ and 5′-AGGGGAGATTCAGTGTGGTG-3′hARv7, 5′-CCATCTTGTCGTCTTCGGAAATGTTA-3′ and 5′-TTTGAATGAGGCAAGTCAGCCTTTCT-3′RNA was isolated using TRI reagent (Bio Science Technology). cDNA was synthesized using an ImProm-IITM Reverse Transcription System (Promega) and following the manufacturer’s instructions. Endogenous mRNA level was measured by A StepOnePlus Real-Time PCR System. The sequences of primers used in RT-qPCR are as follows:2 for 24 h. Media was changed with FBS-free RPMI-1640 for 12 h. Serum-starved LNCaP cells treated with indicated chemicals for 6 h. Then cells were resuspended with lysis buffer  and incubated for 20 min on ice. Samples were centrifuged at 14,000 rpm for 10 min at 4 °C. the supernatants were obtained as cytoplasmic fractions. Remaining pellets were washed with lysis buffer and centrifuged at 14,000 rpm for 10 min at 4 °C. Supernatants were removed, and pellets were obtained as nucleoplasmic fractions. Nucleoplasmic fractions were resuspended with lysis buffer and completely disrupted by a sonicator. Proteins of cytoplasmic and nucleoplasmic fractions were quantified in the same amount and subjected to Western blot.LNCaP cells were cultured with RPMI-1640 supplemented with 10% FBS and 1% penicillin–streptomycin at 37 °C with 5% CO5 LNCaP cells were cultured on 0.1% gelatin coated glass chip in 6 well plates. After treatments of indicated drugs, cells were fixed with 4% paraformaldehyde for 30 min and washed 3 times with 1× PBS. Cells were permeabilized with 0.5% NP-40 in PBS for 30 min and blocked with blocking solution  for 2 h in room temperature. Mouse anti-AR antibody was added at 1:500 in blocking solution for 2 h, washed with PBS, and incubated with Goat anti-Mouse IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488  at 1:500 in blocking solutions for 2 h. Nuclei of cells were stained with 2 μg/ml of Hoechst 33342 for 30 min. Images were obtained using a laser scanning confocal microscope . Image modification and quantification were performed using Image J software54.2 × 104 indicated cells were cultured in 100 μL media (RPMI-1640 or DMEM) with supplemented by 10% FBS or 10% charcoal-stripped FBS in 96 well plate. For cytotoxicity test with normal media condition, all cell lines cultured in the media supplemented with 10% FBS were cultured in 96 well for 24 h. For cytotoxicity test with charcoal-stripped condition, LNCaP cells are first cultured in the media supplemented with 10% FBS in 96 well. After 48 h, media were changed with 10% charcoal-stripped media and cultured for 72 h. 22Rv1 cells were cultured in the media supplemented with 10% charcoal stripped FBS for 1 week. Then 22Rv1 cells were cultured in 96 well plate with charcoal-stripped media. LNCaP cells were treated with indicated concentrations of reagents for 24 h. 22Rv1 or HaCaT cells were treated with indicated concentrations of reagents for 48 h. After incubation, cells were treated with 10 μl of CCK-8 solution and incubated 4 h at 37 °C. The absorbance was measured at 450 nm with INNO  using INNO X software.1 × 104 indicated cells were cultured in 6-well plate. After 24 h incubation at 37 °C with 5% CO2, cells were treated with indicated reagents for 2 weeks. Media were removed, and the cells were washed with 1× PBS. After the wash, the cells were stained with 0.5% crystal violet in PBS for 1 h with gentle shaking. Crystal violet solutions were removed, and the stained cells were washed with 1× PBS 3 times. Stained crystal violet dyes in cells were dissolved with 20% acetic acid and measured at 595 nm with Infinite 200 Pro NanoQuant using i-control 1.9 Magellan™ software .1 × 10All statistical analysis were performed using GraphPad Prism version 9.0. The unpaired Student’s t-test, one-way ANOVA, and repeated measure ANOVA were used to determine significance. A p-value p < 0.05, p < 0.01, p < 0.001 and p < 0.0001 are indicated by *, **, ***, and ****, respectively. All data are presented as mean ± SD or SEM.Supplementary Figures.