Plasmodium knowlesi is recognized as the fifth Plasmodium species causing malaria in humans. It is morphologically similar to the human malaria parasite Plasmodium malariae, so molecular detection should be used to clearly discriminate between these Plasmodium species. This study aimed to quantify the rate at which P. knowlesi is misidentified as P. malariae by microscopy in endemic and non-endemic areas.P. knowlesi as P. malariae by microscopy and confirmation of this by molecular methods in MEDLINE, Web of Science and Scopus were reviewed. The risk of bias in the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS). The pooled prevalence and 95% confidence interval (CI) of the misidentification of P. knowlesi as P. malariae by microscopy were estimated using a random effects model. Subgroup analysis of the study sites was performed to demonstrate any differences in the misidentification rates in different areas. Heterogeneity across the included studies was assessed and quantified using Cochran’s Q and I2 statistics, respectively. Publication bias in the included studies was assessed using the funnel plot, Egger’s test and contour-enhanced funnel plot.The protocol of this systematic review was registered in the PROSPERO International Prospective Register of Systematic Reviews (ID = CRD42020204770). Studies reporting the misidentification of P. knowlesi cases in humans were included. Overall, the pooled prevalence of the misidentification of P. knowlesi as P. malariae by microscopy was estimated at 57% . Subgroup analysis demonstrated the highest rate of misidentification in Sawarak, Malaysia , followed by Sabah, Malaysia , Indonesia , and then Thailand .Among 375 reviewed studies, 11 studies with a total of 1569 confirmed P. malariae-positive diagnoses made by microscopy in P. knowlesi endemic areas be reported as P. malariae/P. knowlesi malaria, the possibility of microscopists misidentifying P. knowlesi as P. malariae is a diagnostic challenge. The use of molecular techniques in cases with malariae-like Plasmodium with high parasite density as determined by microscopy could help identify human P. knowlesi cases in non-endemic countries.Although the World Health Organization (WHO) recommends that all The online version contains supplementary material available at 10.1186/s12936-021-03714-1. Plasmodium knowlesi was first recognized as a cause of simian malaria in long-tailed or pig-tailed macaques [P. knowlesi as a cause of human malaria was reported in Sarawak, Malaysia, in 2004 [P. knowlesi malaria in humans has been reported throughout Malaysia [P. knowlesi malaria has also been reported in travellers returning from endemic countries [macaques . It was macaques . The lar in 2004 . Since tMalaysia  and otheMalaysia –26, IndoMalaysia –30, SingMalaysia , 32, BruMalaysia , CambodiMalaysia , 35, LaoMalaysia , 37, MyaMalaysia , the PhiMalaysia , and VieMalaysia . Moreoveountries –54.P. knowlesi infections are asymptomatic, approximately 19% of infected patients develop severe infections, including acute kidney injury (AKI) (45.6%), jaundice (42%), and hyperparasitaemia (32.5%), as the common clinical manifestations [P. knowlesi infection have been linked to delayed parenteral treatment [P. knowlesi infection include older age, male sex, plantation work, sleeping outside, and travelling in areas where monkeys live [P. knowlesi malaria between humans might occur with mosquitoes as vectors, given the presence of family clustering [Although most stations . Deaths reatment . In the reatment . The riseys live , 55, 57.ustering .P. knowlesi malaria is inaccurate since the morphological features of the early trophozoites of P. knowlesi resemble those of Plasmodium falciparum, and the growing trophozoites are similar to the band-form trophozoites of Plasmodium malariae [P. knowlesi is misidentified as P. malariae by microscopy was estimated and quantified to clarify the inherent disadvantage of solely utilizing microscopy to identify P. knowlesi infection in endemic and non-endemic areas.The identification or detection of malaria parasites relies on the results of analysis based on microscopy, the standard for malaria diagnosis. However, the use of microscopy to diagnose malariae , 58. In This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  AND knowlesi AND (microscopy OR microscopic OR blood film OR “blood film” OR “thick film” OR “thin film”) AND (PCR OR “polymerase chain reaction”). The searches aimed to find original articles in any language and ended on August 17, 2020.Searches of potentially relevant articles published from January 1, 1993, to August 17, 2020 were performed in MEDLINE, Scopus and Web of Science. The search terms used were  the confirmation of P. knowlesi cases by molecular methods. Studies/papers were excluded for the following reasons: absence of P. malariae or P. knowlesi as determined by microscopy, absence of P. knowlesi as determined by PCR, microscopic findings of P. malariae/P. knowlesi, P. knowlesi in macaques, submicroscopic P. knowlesi, unextractable data, case–control studies, case reports or case series, clinical trials, conference abstracts, experimental research, guidelines, letters to the editor, test performances, review articles, systematic reviews and use of the same participants or data set as in another study.Original research articles were eligible to be included in the present study if they were on retrospective or prospective cross-sectional studies and reported: (1) the misidentification of Plasmodium spp., target genes, number of P. malariae and P. knowlesi identified by microscopy (including mixed infections), number of P. malariae and P. knowlesi identified by PCR (including mixed infections), and number of species discordances. Raw data from each study were stored in a standardized datasheet before data synthesis. Data selection and extraction were managed using Endnote Software X7 .The selection of the included studies according to the eligibility criteria was performed by two of the authors (MK and AM). Any discrepancies between these two authors were resolved by discussion in order to reach a consensus. For each study that was included in the analysis, the following information was extracted: name of the first author, year of publication, study area (years of the survey), study design, age range (years) of the participants, sex  of the participants, PCR detection for The risk of bias for each study was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) . This toPlasmodium species discordance  as identified by microscopy and the number of P. knowlesi cases identified by PCR were used to analyse the pooled prevalence of the misidentification of P. knowlesi as P. malariae. The pooled prevalence of discordance of the misidentification of P. knowlesi as P. malariae was estimated by a random effects model using the numerator in the prevalence calculation as the number of discordances, and the denominator as the number of PCR-positive malaria cases. The pooled prevalence and 95% confidence interval (CI) of the misidentification were estimated using a random effects model. Subgroup analysis of the study sites was performed to demonstrate any differences in the pooled prevalence in both endemic and non-endemic countries. The existence and level of heterogeneity across the included studies were assessed using Cochrane Q and I2 statistics, respectively. Publication bias was assessed using funnel plot asymmetry and Egger’s test for asymmetry.Data from the included studies were analysed using the STATA Statistical Software Version 15.0 . The number of cases of P. malariae (n = 5), no P. knowlesi (n = 10), unextractable data (n = 8), case–control studies (n = 4), case reports or case series (n = 30), clinical trial (n = 1), conference abstract (n = 1), experimental studies (n = 21), guidelines (n = 2), letter to the editor (n = 1), microscopy findings reported as P. malariae/P. knowlesi (n = 6), P. knowlesi in macaques (n = 2), test performances (n = 13), review articles (n = 24), submicroscopic P. knowlesi (n = 2), systematic review (n = 1), and use of the same participants or data set (n = 1) , no cles n = , submicrP. knowlesi. All of these seven studies reported mean/median age in the range of 11–91 years, and the proportion of males was between 70 and 77.9%. Seven studies [P. knowlesi, with the exception of the study by Goh et al. [P. malariae cases, while PCR identified 45. Also, microscopy identified 182 P. knowlesi cases, while PCR identified 1569.The characteristics of the included studies are presented in Table  studies , 19, 27  studies , 23, 24 h et al. , in whicThe risk of bias in each study was assessed using QUADAS. The results of the quality assessment are presented in Fig. P. knowlesi was misidentified as P. malariae by microscopy was 1170. Based on the 11 included studies, the pooled prevalence of the misidentification of P. knowlesi as P. malariae by microscopy was 57%   [The total number of instances in which 5, 100%) , while t5, 100%) .Fig. 3Po2: 95%, 2 studies), and Sabah, Malaysia . The study by Yusof et al. [P. knowlesi as P. malariae was demonstrated in Thailand  and Aceh, Indonesia .Subgroup analysis of the study sites was performed to demonstrate the differences in the geographical distribution of the misidentification Fig. . The resf et al.  demonstrThe funnel plot could not be generated because few studies were included in the present study. Egger’s test demonstrated that no small-study effect was found , indicating no publication bias among the included studies.P. knowlesi is well documented in Malaysia, the pooled quantification of the misidentification of this species as P. malariae has not been previously described. In this study, such misidentification was quantified using 11 studies [P. knowlesi was endemic in the last decade. In these areas, the number of P. knowlesi cases was not available until PCR testing was used to identify it in 2004 [P. knowlesi targeting 18S rRNA gene targets [P. knowlesi significantly increased, while a small number of P. malariae cases were still observed by PCR in Sabah during 2008–2011 [P. malariae cases identified by microscopy in the last decade was caused by the emergence of P. knowlesi malaria, as these two species are morphologically similar and difficult to distinguish from each other using microscopy. While the highest prevalence of the misidentification of P. knowlesi as P. malariae occurred in Sabah and Sawarak, microscopically misdiagnosed cases of P. malariae were not found in other parts of Malaysia, such as Pahang and Kelantan [P. knowlesi as P. malariae in the study by Yusof et al. [Although  studies , 24, 27, in 2004 . Molecul targets , 61, wit targets . From th008–2011 , 15, 18 008–2011 . This inKelantan . This exf et al.  in nine f et al. –19.P. knowlesi was endemic, it was also frequently misidentified as P. falciparum or P. vivax malaria by microscopy [P. knowlesi and P. falciparum occurs at the stage of young rings of both species, which contain double chromatin dots, multiple-infected erythrocytes, and applique forms [P. knowlesi and P. malariae occurs in the trophozoite, schizont, and gametocyte stages [P. knowlesi infections in endemic areas. Moreover, P. malariae is less endemic in Southeast Asia, where the presence malarial parasites with morphology similar to that of P. malariae coupled with high parasitaemia has been reported as P. knowlesi infection by default [P. malariae-positive diagnoses by microscopy in P. knowlesi endemic areas be reported as P. malariae/P. knowlesi [In areas in which croscopy . The simue forms ; while te stages . The rec default . Moreoveknowlesi .P. knowlesi is not endemic, such as Thailand and Indonesia, a low prevalence of the misidentification of P. knowlesi as P. malariae by microscopy was observed. Only one case of P. knowlesi misidentified as P. malariae from 33 confirmed cases of P. knowlesi was recorded by Jongwutiwes et al. during 2008–2009 [P. knowlesi was recorded by Putaporntip et al. during 2006–2007 [P. knowlesi were misdiagnosed from 19 confirmed cases of P. knowlesi as recorded by Coutrier et al. [P. knowlesi was also misidentified as P. falciparum and P. vivax, as reported by studies in both Thailand and Indonesia [P. knowlesi because its ring forms were similar to those of P. falciparum, or sometimes its growing trophozoites were similar to those of P. vivax. Misidentification, such as the misdiagnosis of P. falciparum as P. knowlesi, might cause the administration of chloroquine, and the resistance of P. falciparum to chloroquine can increase the likelihood of patient mortality. Further, the misidentification of severe P. knowlesi as P. vivax malaria may lead to treatment failure, such as missed parenteral treatments as per national guidelines, which have been reported to be associated with fatal outcomes [P. knowlesi mono-infection, mixed-infections of P. knowlesi combined with other Plasmodium species were also recorded in Thailand and Indonesia, such as mixed-infections with P. falciparum or mixed-infections with P. vivax malaria, which microscopists reported as P. falciparum or P. vivax mono-infections [P. knowlesi malaria in those co-infected patients in non-endemic countries such as Thailand and Indonesia were less likely since low parasite density of P. knowlesi was observed [P. knowlesi was responsive to chloroquine treatment in cases of mixed infections with P. vivax malaria. In addition, severe adverse events from unnecessary primaquine treatments were not experienced among co-infected patients [In areas where 008–2009 , and onl006–2007 . There w006–2007 , as onlyr et al. . In addindonesia , 27. Thioutcomes . In addifections , 24, 27.observed , 24, andP. knowlesi/P. malariae as determined by microscopy were not included in the present study since the number of misidentifications could not be estimated.The present study had some limitations. First, high heterogeneity among the included studies was observed, although subgroup analysis was performed; therefore, the results of the pooled prevalence needed to be interpreted carefully. Second, a low number of included studies were used for pooled analysis; therefore, the pooled prevalence might not have been precisely estimated. Third, studies reporting on P. malariae-positive diagnoses made by microscopy in P. knowlesi endemic areas be reported as P. malariae/P. knowlesi, the possibility of the misidentification of P. knowlesi as P. malariae by microscopists is a diagnostic challenge in both endemic and non-endemic countries. Assuming the low incidence of P. malariae in Malaysia and Southeast Asia, cases of symptomatic malaria with hyperparasitaemia and parasite morphology resembling that of P. malariae should be diagnosed as P. knowlesi/P. malariae by microscopy, so that severe complications among patients infected by P. knowlesi can be reduced.Although the WHO recommends that all Additional file 1: Checklist S1. PRISMA Checklist S1.Additional file 2. Methodological quality summary.


Traditional text annotation-based video retrieval is done by manually labeling videos with text, which is inefficient and highly subjective and generally cannot accurately describe the meaning of videos. Traditional content-based video retrieval uses convolutional neural networks to extract the underlying feature information of images to build indexes and achieves similarity retrieval of video feature vectors according to certain similarity measure algorithms. In this paper, by studying the characteristics of sports videos, we propose the histogram difference method based on using transfer learning and the four-step method based on block matching for mutation detection and fading detection of video shots, respectively. By adaptive thresholding, regions with large frame difference changes are marked as candidate regions for shots, and then the shot boundaries are determined by mutation detection algorithm. Combined with the characteristics of sports video, this paper proposes a key frame extraction method based on clustering and optical flow analysis, and experimental comparison with the traditional clustering method. In addition, this paper proposes a key frame extraction algorithm based on clustering and optical flow analysis for key frame extraction of sports video. The algorithm effectively removes the redundant frames, and the extracted key frames are more representative. Through extensive experiments, the keyword fuzzy finding algorithm based on improved deep neural network and ontology semantic expansion proposed in this paper shows a more desirable retrieval performance, and it is feasible to use this method for video underlying feature extraction, annotation, and keyword finding, and one of the outstanding features of the algorithm is that it can quickly and effectively retrieve the desired video in a large number of Internet video resources, reducing the false detection rate and leakage rate while improving the fidelity, which basically meets people's daily needs. With the continuous improvement of information technology, people's demand for video information resources has also increased, and how to do a good job of processing data and information has become one of the very important research topics of relevant units . In the The corresponding output is obtained by activation function or specific weights, and the obtained computational structure is input to the next neuron . The reaOn this basis, the application value of deep neural networks has begun to receive general attention from experts and scholars, such as gradual application in video, audio, and text . For exan frames, the key frame extraction algorithm extracts m key frames from them, which is denoted as K = {f1, f2, ...fn}, and compares them one by one with the shot n frames starting from the first key frame and takes the smallest value as the key frame reference value. In this paper, the shortcomings of existing methods are comprehensively analyzed in video retrieval, and corresponding improvement methods are proposed in shot segmentation, key frame extraction, video annotation methods, and query expansion methods. Combined with the characteristics of sports video, this paper proposes a key frame extraction method based on clustering and optical flow analysis, and experimental comparison with the traditional clustering method. The quality of video content description depends on the good or bad features, and people can use good features of the relevant use of video research in many aspects, such as video retrieval and video classification and a series of operations; not only that, the technology largely promotes the future development and practical application of video and video feature extraction to alleviate the direct impression on video analysis and application; that is, the basis and focus of video processing technology are about the feature extraction of video, and accurate feature recognition is the prerequisite for the annotation of video.This study further extends the network structure of video classification and investigates the image classification retrieval model based on the Tensor Flow framework, which demonstrates high retrieval accuracy and classification accuracy in the image classification process and further simplifies the structure of the whole model. The fidelity refers to the degree of similarity between the extracted key frames and the corresponding video; i.e., the higher the fidelity is, the better the key frames are restored to the original video. Assuming that the shot S contains In recent years, with the continuous development of science and technology, content-based video retrieval has developed rapidly, and the main purpose of this retrieval is to search for similar videos in the video library based on the video related content provided by the user as the search condition . In the The researchers classified more than 1 million high-resolution images from the database through a convolutional neural network, and the researchers found that using a convolutional kernel size of about 3 × 3 for image feature extraction in the CNN can achieve significant results. The researchers built the spatiotemporal network by utilizing two CNN structures, a spatial network using a single frame of images from the video for network input and a temporal network using multiple frames of optical streams for network input . In otheIn addition, the accuracy of feature extraction can be improved by using the transfer learning method. Among the abovementioned feature extraction, color features are not sensitive enough to perceive changes such as orientation of the image to capture local features of the target in the image. Texture is only a surface feature extraction method that does not fully reflect the properties of the object; therefore, it jointly proposed features that fuse texture and color features. In video feature extraction, the appropriate selection of key frames is a key aspect, and treating key frame features as video features based only on the image level will result in the loss of time-domain information of the video, so some people process the video directly to extract features . A relatWhen performing video retrieval, the underlying feature extraction of the video is commonly in the form of color features described in the previous section, represented as a color histogram. The color histogram approach is used to form the color histogram features of the video by integrating all pixel points within the same pixel region of the video during feature extraction. Although this method of extracting color histogram features can perform efficient video feature extraction in a short time, this method ignores information related to video features such as video texture and shape when extracting video features, resulting in large errors when using the extracted features for similarity matching . At the H is the Hessian matrix, T denotes the transpose of the matrix, w is the parameter in the neural network, and E is the training set error. A local minimum is obtained by an optimization algorithm , and then the first term of the above equation is 0. Neglecting the third higher-order infinitesimal term yieldsIn this paper, an end-to-end design idea is adopted for the classification and retrieval of sports videos; i.e., the input is the data of the whole picture and the category of the output picture, and the whole classification process is done automatically by the system without human operations such as parameter setting. Deep neural Inception V3 is used as the base network, and the network parameters and network structure are slightly modified based on the characteristics of sports videos, and the modified network converges faster, and the accuracy of classification is improved. In neural networks, such a core problem becomes the reduction of the number of connection weights to reduce the complexity of the model; a very common method is to add a penalty term after the loss function, in order to reduce the complexity of the model, usually using a 2-parameter number, but the 2-parameter error makes the weights and thresholds sparse, and then usually use a 1-parameter number to penalize the weights and thresholds. This algorithm is an improvement of the penalty term algorithm. The algorithm is a Hessian matrix-based network pruning algorithm that first constructs a local model of the error surface and analyzes the impact of perturbations in the weights. By performing Taylor expansion on the error function,E is minimized, we can obtainThis method can be written by setting one of the weights to 0; thus,H is the Lagrangian multiplier, and by taking the partial derivative of the function L, we can obtain Δw, Δw leading to the error asAccording to the pruning algorithm, the 10 Inception modules of the deep neural network were trained. According to the introduction of the Inception v3 model above, the team added a bilinear structure to the Inception v3 model to reduce the dimensionality of the feature map. It is also found that the reduction of parameters accelerates the convergence speed. Therefore, for each inception module, two bilinear structures are removed in the experiments in this paper. In addition, it is found that the first few convolutional layers extract the low-dimensional features of the image, while the later convolutional layers extract the high-dimensional features, so the last convolutional layer of the original network is removed, and the high convolutional kernel channels of the first two convolutional layers and the low convolutional kernel channels of the last two convolutional layers are cut off, and the softmax layer of the original network is replaced by a Sigmoid fully connected layer. The structure and parameters of the redesigned network are shown in Traditional information retrieval is based on ordinary sets and Boolean logic, and the information to be retrieved is expressed in the form of Boolean expressions for logical comparison with user input; such a retrieval method is logically simple and easy to implement; however, the keywords input by users is often natural languages with strong ambiguity, and the traditional retrieval model does not have the concept of relevance, and only when the content to be retrieved matches exactly the query words can it be successfully retrieved, as shown in Some current retrieval models inevitably cause semantic loss when dealing with natural language, and the retrieval results are mostly unsatisfactory. Ontologies, as a knowledge modeling tool, offer the possibility to improve retrieval systems. A video retrieval system is a retrieval system for users, and the ultimate goal is to ensure that users can retrieve the video information of interest. However, often the search terms users input into the retrieval system do not express what they want to express well, which requires the retrieval system to understand the user's intention “intelligently” and improve the hit rate of retrieval, which requires the use of query expansion techniques. Several query expansion methods are described below.The transfer learning analysis starts with correlation analysis of words and phrases in all documents, calculating the relevance of each word or phrase pair based on cooccurrence, and when the user enters a keyword to search, the word with the highest relevance to the word to be searched is found among these related words and added to the set of query words for joint search. Word clustering is the clustering analysis of words based on their cooccurrences, which is used to expand the query. If two words are related to each other, then the chance of cooccurrence of these two words in the set is high. However, words often have multiple meanings, and for words with multiple meanings, clustering algorithms usually assign them to different clusters based on different word meanings, resulting in less accurate query results and affecting the accuracy of retrieval.M × N of M words and N documents, the matrix is reduced to P ×P by removing some of the rows and columns using SVD. In order to reduce the loss of information, only the least significant part of the frequency matrix is ignored. The documents processed by the SVD technique can be used for interdocument similarity comparison, while the top N matching outputs are output. The retrieval effect of this method is not very obvious, while the selection for the low-dimensional space is often difficult, limiting the space for the use of this technique.Indexing potential semantic indexing is assuming that words in high-dimensional space can be represented using low-dimensional space. This technique uses singular value decomposition (SVD) method, which is a dimensionality reduction technique. Assume that, given a word frequency matrix In addition, transfer learning methods are often used by means of similarity dictionaries. Similarity dictionaries are often used to deal with word ambiguity, and the technique treats a query as a concept. User input is often too homogeneous and has a lot of ambiguity, and it is better to expand the user input into multiple query words with similar meanings for joint search by query expansion methods. Therefore, the selection of extended terms can be obtained by cooccurrence with query terms. For example, the phrase finder technique represents any concept A as a tuple set, which contains all the words cooccurring with concept A and their frequency of occurrence, and the tuple set is the pseudodocument. When the user enters a query term, the system automatically calculates the relevance of the query term to the words in the pseudodocument and outputs the results in a ranked manner as query extensions for joint search. The similarity dictionary has excellent retrieval effect and high accuracy rate of query, but it is too complicated to establish the concept of association between all words in advance, and the calculation is too complicated, and the retrieval efficiency is low.The transfer learning analysis is a combination of global analysis and local analysis. Using the local feedback method to select relevant documents, the phrase finder technique in global analysis is applied to the cooccurrence idea in the selection of extension terms, which well avoids the situation that irrelevant documents may appear in local feedback and improves the query efficiency compared to the global analysis. The local clustering method in local analysis divides related documents into different clusters when selecting extensions and assumes that the most relevant extensions to the query term are all in the same cluster. However, in fact, there are often other irrelevant clusters besides the most relevant clusters that also contain some of the extension terms, and this phenomenon can be explained by topic overlap. In local clustering, the default related words are in the largest cluster, but if there is topic overlap in the largest cluster, the accuracy of the query of this method will be greatly reduced. A good query method should not have such topic overlap and must ensure that there is no significant decrease in precision for each query. The local context only selects words that cooccur with all query terms at the same time as extensions, ensuring high relevance to the maximum extent. This method was used in the INQUERY system and achieved good results on the TREC standard test set.T, R, I), where (1) the set of nodes O = {Term1, Term2, Term3, ... ,Termn} denotes the set of terms. (2) The set of arcs belongs to (P ∗ P), which represents the binary relation on T. The relation is_a, part_of, or kind_of is satisfied between Termi and Termj. (3) O is the set of instances. The sports video ontology is modeled by Protégé according to the above definition and saved automatically as an OWL format file. The effect of modeling part of the sports video ontology is shown in In this paper, a graphical deep neural network modeling approach is chosen to build a sports video ontology model, in addition to combining the search term detection technique of transfer learning to build a video intelligent classification system. Firstly, the sports ontology is defined as a triple Sport Onto = (Define the goal: to describe the structure of sports video concepts, their attributes, and the relationships between them through the OWL language using ontological ideas.Establish a hierarchy: Establishing a hierarchy between concepts requires that the concepts do not intersect with each other, and the subclasses of each class should be disjoint; e.g., the subclasses basketball and baseball of the ball class in the ontology of this paper do not intersect with each other. The edges in the hierarchy diagram of the ontology represent the relationship between concepts, such as Is_A, Part_of, and Kind_of.Define the attributes and constraints of concepts: The hierarchy is equivalent to the skeleton of a human body, and the attributes and constraints are equivalent to the flesh and blood of a human being. There are two kinds of attributes of concepts: one describes its own information, and the other is used to represent the relationship between concepts, i.e., numerical attributes and object attributes.Coding of the designed ontology using OWL language.The process of constructing ontologies through the language of transfer learning is as follows:There are many factors that affect the similarity between concepts in ontologies, such as semantic overlap, distance similarity, literal similarity, and attribute matching. When making the similarity selection, we need to combine the ontology model structure and properties for comprehensive consideration and combine all relevant factors together for similarity calculation. After determining the similarity of concepts in the ontology, the threshold value is needed to judge the similarity between concepts. Only concepts whose similarity to the query term exceeds the threshold value are included in the query extension set during the extension term selection. There are various ways to determine the threshold value, such as artificially evaluating the similarity value between a small part of concepts in the ontology with a tentative threshold value, and if all similarities are greater than the threshold value, the tentative threshold value is reasonable. If the similarity between some concepts is less than the threshold, but the concept actually meets the system requirements, and the threshold is too large and should be reduced. Manual adjustments are made through continuous experiments until the threshold value basically meets the ontology model requirements.In this paper, the proposed methods are tested by experiments, including shot segmentation, key frame extraction, video annotation, and keyword query expansion. The video clips for validating the shot segmentation and key frame extraction methods are obtained from Tencent video, and the video clips for validating the video annotation and keyword query expansion methods are obtained from UCF101 dataset. In this paper, the proposed method and the traditional shot segmentation method with double-threshold detection are tested and compared based on the same sports video clips, and the results are shown in It can be seen from the data in the table that the efficiency of the method proposed in this paper has been improved compared with the dual-threshold detection method for lens boundary detection, which saves about 19.2%∼30.1% in time, because the dual-threshold detection algorithm is artificially set the threshold value, which is not well applicable to the sports video material selected in this paper; in addition, the dual-threshold detection method is a frame-by-frame analysis of the video to detect the mutation boundary, and the computational effort is relatively large. The automatic threshold-based histogram difference method proposed in this paper automatically sets the threshold value according to the complexity of the video content when performing shot mutation detection, and the processing of image frames takes the method of interframe statistics, which will improve computational efficiency.As shown in Selecting appropriate video features can present a better video retrieval effect. In this paper, the shortcomings of existing methods are comprehensively analyzed in video retrieval, and corresponding improvement methods are proposed in lens segmentation, key frame extraction, video annotation methods, and query expansion methods. The histogram difference method based on automatic threshold, which sets its own threshold according to the complexity of image content, improves the accuracy of lens mutation detection; the key frame extraction method based on clustering and optical flow analysis, which combines clustering analysis and motion analysis while avoiding the shortcomings of each, increases the flexibility of the number of key frames extracted while reducing the computation; regarding the improvement based on the traditional deep neural network, the ontology-based keyword query expansion method analyzes and expands the semantic meaning of the user input words to be retrieved and jointly searches the expanded words with the query words to improve the accuracy of retrieval.In order to evaluate the algorithm more accurately, two parameters, fidelity and matching degree, are chosen to evaluate the key frame extraction method in this paper. In order to clearly verify the feasibility of the key frame extraction method based on clustering and optical flow analysis proposed in this paper, the experiments in this paper compare the key frame extraction method based on clustering and the method in this paper based on some shots in video sports_3, and the results are shown in This data shows that the key frame extraction method based on clustering and optical flow analysis proposed in this paper is better than the clustering-based key frame extraction method in terms of key frame extraction effect, both in terms of fidelity and matching degree. The clustering-based method clusters all image frames according to the difference degree when performing key frame extraction, which is effective for key frame extraction, but the number of clustering centers needs to be set in advance; i.e., the number of key frames is fixed.In sports video clips, the amount of important information in the footage varies due to the different degrees of description of motion information in the footage, and the traditional clustering analysis method extracts a fixed number of key frames, which usually has missed detection for sports videos with diverse motion information. The key frame extraction method based on clustering and optical flow analysis proposed in this paper combines clustering analysis with optical flow analysis and performs optical flow analysis again for video frames with relatively large amount of motion information. This method further analyzes the motion image frames, which can avoid the fixed number of extracted key frames in the clustering method and improve the fidelity and matching degree of key frame extraction.Among them, the reference key frames are voted by relevant video researchers, which can represent the video content information in theory. From the figure, we can see that the proposed method is basically similar to the reference key frames in terms of the number of extracted key frames, and from the content expression, except for the slight difference of individual video frames, the overall is similar and can well express the video content information. The clustering-based key frame extraction method is significantly less than the reference key frame in terms of the number of extracted key frames, and in terms of the content, the number of extracted key frames is relatively small, and the expression of the video content is not comprehensive, especially in the expression of motion details that is not as detailed as the method in this paper. The fundamental reason is that the method proposed in this paper performs additional optical flow analysis for video frames with more motion based on the clustering analysis of video frames, so that the extracted key frames describe the video motion information in more detail and therefore better represent the video content.The video annotation method proposed in this paper is based on the extraction and classification of video frame features by convolutional neural network, so the effectiveness of the feature extraction method represents the effectiveness of the video annotation method. In order to achieve better validation, this paper tests the neural network and the improved network by UCF101 dataset, and the accuracy and completeness rates of this paper are shown in In order to better verify the effectiveness of the method in this paper, the sports ontology was chosen as the domain ontology, and 5000 sports articles and news corpus crawled online were used as the training set to construct the connectivity graph. The search completion rate, search accuracy rate, and reconciliation average are used as the evaluation criteria of the retrieval method. In this paper, we use the dataset mentioned in the previous section to compare the keyword query expansion method based on sports ontology and the word association matrix query expansion method and use the retrieved text “four people play basketball in the park” to obtain the keywords in the keyword set to be retrieved after text preprocessing “four,” “people,” “park,” “play,” and “basketball,” and the extended keywords and the corresponding similarity are obtained for these keywords based on the method proposed in this paper, as shown in The input retrieved text “four people playing basketball in the park” was preprocessed, and query expanded to obtain the extended keyword set, which was sorted by similarity value from largest to smallest. The evaluation results of this retrieval method outperformed the word association matrix-based method, with the accuracy, completeness, and summation averages improving by 5.83%, 1.82%, and 6.32%, respectively, indicating that the query expansion method based on sports ontology proposed in this paper can improve the query effect and can complete the video retrieval task well.By comparing this method with the traditional keyword-based retrieval method, different numbers of videos were selected to evaluate the two methods based on the search completion rate and the search accuracy rate. The number of videos retrieved by the traditional keyword-based video retrieval method is much higher than the number of manual retrievals, but the proportion of correct retrievals is very small, because the traditional keyword-based retrieval method uses manual annotation, and the annotation of video materials is not accurate due to the influence of too many subjective factors. The results of this paper are better than those of the keyword-based retrieval method in terms of both completeness and accuracy, indicating that the convolutional neural network structure proposed in this paper provides relatively accurate annotation of videos, and the ontology-based query term expansion method also plays a significant role in improving the retrieval results. From the data, the video retrieval method based on convolutional neural network proposed in this paper reduces the redundancy phenomenon of video retrieval to a certain extent and can basically meet the retrieval needs of users.The histogram difference method based on automatic threshold proposed in this paper takes a frame-by-frame statistical approach in performing shot mutation detection to reduce the computational effort to a certain extent, and the reasonable setting of threshold value by the automatic threshold method also plays a key role in the accurate segmentation of video shots. In this paper, the shortcomings of existing methods are comprehensively analyzed in video retrieval, and corresponding improvement methods are proposed in shot segmentation, key frame extraction, video annotation methods, and query expansion methods. Combined with the characteristics of sports video, this paper proposes a key frame extraction method based on clustering and optical flow analysis, and experimental comparison with the traditional clustering method. Since the traditional clustering method requires a preset number of cluster centers when performing cluster analysis, which also limits the number of key really extracted, making the method too inflexible when performing key frame extraction, the method in this paper extracts key frames by combining. By comparing this method with the traditional keyword-based retrieval method, different numbers of videos were selected to evaluate the two methods based on the search completion rate and the search accuracy rate. For the user's query words, the ontology-based keyword query expansion method proposed in this paper reasonably expands the query words based on semantics to form an extended word set, which is jointly queried with the query words, and the experimental comparison with the extended query method based on word association matrix shows that this method is higher than the word association matrix-based method in terms of reconciliation mean, which proves the effectiveness of this method. In the future, news corpus crawled online should be used as the training set to construct the connectivity graph.


Sixteen participants (12.9%) had sarcopenia; 12 subjects with sarcopenia had concomitant malnutrition. The prevalence of severe and very severe obstruction (GOLD3/GOLD4) was 91.7%. It was significantly higher in patients with malnutrition-sarcopenia syndrome. Conclusions: Malnutrition was found in nearly one out of four subjects with COPD, while sarcopenia was one out of seven patients. About 10% of our study sample had malnutrition-sarcopenia syndrome. The prevalence of severe and very severe obstruction was significantly higher in patients with malnutrition-sarcopenia syndrome.Purpose: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the world population. In addition to airflow obstruction, COPD is associated with multiple systemic manifestations, including impaired nutritional status or malnutrition and changes in body composition . Poor nutritional status and sarcopenia in subjects with COPD leads to a worse prognosis and increases health-related costs. Data from previous studies indicate that 30–60% of subjects with COPD are malnourished, 20–40% have low muscle mass, and 15–21.6% have sarcopenia. This study aimed to assess the prevalence of malnutrition, sarcopenia, and malnutrition-sarcopenia syndrome in elderly subjects with COPD and investigate the relationship between COPD severity and these conditions.Patients and methods: A cross-sectional study involving 124 patients with stable COPD, aged ≥60, participating in a stationary pulmonary rehabilitation program. Nutritional status was assessed following the Global Leadership Initiative on Malnutrition (GLIM) criteria and sarcopenia with the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria. The results of pulmonary function tests and exercise capacity were obtained from the hospital database. Results: 22.6% of participants had malnutrition according to the GLIM criteria. Subjects with malnutrition had lower gait speed ( Chronic obstructive pulmonary disease (COPD) is ranked highly among civilization diseases. Currently, it is the fourth leading cause of death in the world population, and it is predicted to be the third one in the nearest future . ChronicCOPD is an inflammatory condition . In addiA nutritional intervention  aimed to increase muscle mass may favorably influence the rehabilitation process in undernourished elderly subjects with COPD, improving respiratory muscle force, physical capacity, overall health condition, and quality of life ,15,16. SWhile it is true that the prevalence of sarcopenia or malnutrition in subjects with COPD has been investigated in many studies, there are only a few reports in which the most recent diagnostic criteria (GLIM and EWGSOP2) were applied ,21,22,23We performed a cross-sectional analysis of a group of patients with chronic stable COPD from the Pulmonary Rehabilitation Ward (Great Poland Centre of Pulmonology and Thoracic Surgery) between September 2019 and November 2020. All patients admitted to the pulmonary rehabilitation ward in this period who met the inclusion criteria were enrolled.Each subject gave written informed consent before the study, conducted under the Declaration of Helsinki. The study protocol was approved by the Bioethical Committee of the Poznan University Medical Sciences, Poland .-age 60 years and more,-COPD diagnosed based on recommendations from the Global Initiative for Chronic Obstructive Lung Disease (GOLD) ,-good verbal communication, absence of cognitive impairment,-absence of active inflammation-informed, written consent to participate in the study.The inclusion criteria were as follows:-active malignancy,-contraindications for the body composition analysis with a bioimpedance method .The exclusion criteria involved:All participants had the following parameters assessed: cognitive performance, malnutrition (following the GLIM criteria), and sarcopenia (according to the EWGSOP2 recommendations). Additionally, the results of pulmonary function tests and exercise tests were obtained from the hospital database.All patients were screened with the Abbreviated Mental Test Score (AMTS) to exclude subjects with cognitive impairment . The AMTMalnutrition was diagnosed based on the GLIM criteria . In the The diagnosis of malnutrition was confirmed if at least one phenotypic and at least one etiologic criterion was fulfilled, as recommended by the GLIM experts.(1)unintentional body weight loss: the loss of >5% habitual body mass within the past six months, or the loss of >10% in more than six months,(2)2 in subjects below 70 years and <22 kg/m2 in individuals 70 years or older,low body mass index (BMI): <20 kg/m(3)2). ALM index below the cut-off points for the Polish population (5.6 kg/m2 in women and 7.4 kg/m2 in men) [low muscle mass (LMM): muscle mass was assessed based on the measurement of appendicular lean mass and calculation of the Appendicular Lean Mass (ALM) and an ALM index, which represents the ratio of ALM (kg) and square of height (m in men)  was indiPhenotypic criteria:The appendicular lean mass was measured with the electrical bioimpedance method (BIA) .(1)reduced food intake or assimilation was recognized in subjects declaring any reduction in food intake within the past three months in the MNA-SF questionnaire,(2)the disease burden/inflammatory condition was recognized in all participants with a COPD diagnosis.Etiologic criteria:Following the F-A-C-S (Find Cases-Assess-Confirm-Severity) algorithm , we usedThe upper limb muscle strength was assessed based on a handgrip test with a hand dynamometer . The measurements were done with precision to 0.1 kg. The participants performed the handgrip test in a sitting position, with arms bent to 90 degrees in the elbow and arm joints. Each upper limb was tested twice. The mean of all measurements was used as a final result. The cut-off points for low muscle strength were following the EWGSOP2 recommendations (16 kg for women and 27 kg for men) .The lower limb muscle strength was measured with a Chair Stand Test (CST) . ParticiFollowing the FACS algorithm, reduced muscle strength was diagnosed in individuals with decreased upper limb muscle strength and/or reduced lower limb muscle strength .The method adopted for muscle mass assessment was previously described in malnutrition diagnosis.GOLD 1 (mild obstruction) FEV1 ≥ 80%GOLD 2 (moderate obstruction) FEV1 ≥ 50%GOLD 3 (severe obstruction) FEV1 ≥ 30%GOLD 4 (very severe obstruction) FEV1 < 30%Information on the results of spirometry was obtained from the hospital database. Spirometry was performed with LUNGTEST 1000 device . All subjects enrolled in the study had chronic obstructive pulmonary disease diagnosed based on GOLD recommendations (post-bronchodilator forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio < 0.7) [Each participant performed the Six-Minute Walk Test (6MWT) to assess his/her physical capacity. Patients walked for six minutes in a straight corridor 30m long under the supervision of hospital physiotherapists, and the distance covered was measured. Blood pressure was taken, and blood oxygen saturation was measured with a pulse oximeter  directly before the test and after completing it. The 6MWT was finished earlier in case of dyspnea precluding its continuation, chest pain, severe lower limb pain, or cramps.Although there are no cut-off points for the Six-Minute Walk Test, it is widely accepted ,30,31,32n) and percentage (%). For quantitative data, mean (M) and standard deviation (SD) are shown.Qualitative data are presented as number  likelihood ratio chi-square tests (for contingency tables larger than 2 × 2). Fisher’s exact test was used for 2 × 2 contingency tables if the sample size was smaller than 40 and at least 1cell had an expected count smaller than 5. The p-value of less than 0.05 was considered significant. The statistical analysis was performed with STATISTICA 10 PL .We used the following statistical tests: the Shapiro–Wilk test to assess the distribution of quantitative variables of normality; the Levene’s test to assess the equality of variances; the Student n = 9) and very severe obstruction (n = 12), combined categories of mild to moderate obstruction (GOLD 1 + GOLD 2) and severe to very severe obstruction (GOLD 3 + GOLD 4) were used in further analysis.The study sample consisted of 124 patients of the pulmonary rehabilitation ward, aged at least 60 (mean age 69.4 ± 6.1 years). Forty percent of the study population were women. All subjects had COPD diagnosed based on the GOLD recommendations. p < 0.0000) and lower body composition parameters . There was a tendency towards higher upper and lower limb strength in patients with normal nutritional status (p = 0.0567). Malnourished participants had lower gait speed (p = 0.0112) and worse results forthe 6MWT (p = 0.0079). They also scored lower in the SARC-F questionnaire (p = 0.0336).Thirty-eight subjects (30.6%) were at risk of malnutrition based on the MNA-SF score; the diagnosis of malnutrition was confirmed with the GLIM criteria in 28 patients . Sarcopenia was diagnosed in 16 patients (12.9%); 12 of them had malnutrition concomitantly  .p < 0.0001) and lower gait speed (p = 0.0395) than subjects without this condition. Significant differences in body composition were also observed. Patients with sarcopenia had lower body weight, BMI, BFM, SMM, FFM, FMM and PBF. Additionally, these subjects had worse results of the 6MWT (p = 0.0001) and had lower FEV1 (p = 0.0002), indicating more severe obstruction in comparison with participants without sarcopenia.p = 0.0396) and FEV1 (p = 0.0171). Moreover, subjects with MSS covered shorter distance during the 6MWT (p = 0.0002) as compared to individuals without the syndrome.Malnutrition-sarcopenia syndrome was diagnosed in 1 out of 10 participants. p = 0.0000) and subgroup with only one condition (p = 0.0480). The MSS subgroup had lower BMI than subjects without any condition (p = 0.0000) and patients with one condition (p = 0.0471).Participants with concomitant malnutrition and sarcopenia also had significantly lower muscle mass and lower body fat mass. Although the spirometry results did not differ between the subgroups, the prevalence of severe and very severe obstruction was higher in subjects with MSS. Patients with concomitant malnutrition and sarcopenia covered a shorter distance during the 6MWT than subjects without any condition (p = 0.0003) and individuals with malnutrition or sarcopenia alone (p = 0.0315).To the best of our knowledge, this is the first study to assess the prevalence of malnutrition, sarcopenia, and malnutrition-sarcopenia syndrome using the most recent diagnostic criteria (GLIM and EWGSOP2) in elderly subjects with COPD. Both malnutrition and sarcopenia are common in patients with COPD. Malnutrition may affect about 50% of elderly individuals with COPD , and sarAlmost one of four participants had malnutrition in our study population, and one out of seven had sarcopenia. Sarcopenia was much more prevalent in patients with severe and very severe airflow obstruction. It should be emphasized that both conditions were diagnosed in nearly 10%of subjects. Malnutrition may lead to sarcopenia due to inadequate calorie and protein intake necessary for maintaining muscle mass. Sarcopenia, in turn, may exacerbate malnutrition by reducing mobility necessary for the everyday preparation of meals and food shopping . ConsequThe prevalence of malnutrition and sarcopenia in subjects with COPD has been assessed in many studies. However, these studies used various screening tools and not up-to-date diagnostic criteria  criteria for the diagnosis of malnutrition from 2015 or the older EWGSOP criteria for sarcopenia from 2010), which makes a direct comparison difficult ,35,36,37n = 12) of patients with sarcopenia in our study had concomitant malnutrition. In addition to an association between sarcopenia and COPD severity, we observed a relationship between sarcopenia and the results of pulmonary function tests and 6MWT tests.We found four studies assessing the prevalence of sarcopenia diagnosed based on the EWGSOP2 criteria in patients with COPD, including two papers concerning elderly subjects ,19,20,21Lengelé et al.  have demIt should be emphasized that overlooking of malnutrition may lead to sarcopenia, particularly in elderly subjects. Concomitance of these conditions increases the risk of death, as evidenced by Hu et al.  in the aDespite the well-known adverse consequences of malnutrition and sarcopenia and their high prevalence in elderly subjects with COPD, both conditions are rarely diagnosed in such patients. Lack of diagnosis precludes implementation of therapeutic intervention. Based on our results, we suggest screening for both malnutrition and sarcopenia in all elderly subjects with COPD, regardless of its severity. Such an approach would necessitate the involvement of a dietician and a physiotherapist and should positively influence prognosis in such patients.Our study has some limitations. First, the study group consisted of patients involved in pulmonary rehabilitation, so their physical condition must have been relatively good—to allow for such activity. Therefore, our results are not representative of the total COPD population. Secondly, we assessed the GLIM etiologic criterion concerning reduced food intake or assimilation using the subjective answers to the MNA-SF questionnaire items. Although subjects enrolled in our study had no cognitive impairment, determining if one’s food intake declined over the past three months due to loss of appetite, digestive problems, and chewing or swallowing difficulties (the MNA-SF item) might have been difficult for some of them. Moreover, the lack of multivariate analyses is a limitation of our study.The strong point of our study is that this is the first analysis of the prevalence of both malnutrition and sarcopenia in elderly patients with COPD, in which the most recent diagnostic criteria have been used. It should be emphasized that elderly patients with COPD are at particular risk for both conditions.Malnutrition according to the GLIM criteria was found in nearly one out of four subjects with COPD, while sarcopenia according to the EWGSOP2 in one out of seven patients. About ten percent of our study sample had malnutrition-sarcopenia syndrome. The prevalence of severe and very severe obstruction was significantly higher in patients with malnutrition-sarcopenia syndrome. Subjects with the MSS had also worse results of the Six Minute Walk Test, which is a poor prognostic factor in COPD.


Using a series of Implicit Association Test (IAT) experiments, we tested this possibility for both actions performed in physical space (grasp vs. look at) and those performed when using digital technology (content generation vs. content consumption). For both the physical and digital environments, the results showed an association between the adverb near and actions related to the role of agent, and between the adverb far and actions related to the role of observer. Present findings are the first experimental evidence of an implicit association between different adverbs of place and different actions and of the fact that adverbs of place also apply to the digital environment.Neuropsychological, behavioral, and neurophysiological evidence indicates that the coding of space as near and far depends on the involvement of different neuronal circuits. These circuits are recruited on the basis of functional parameters, not of metrical ones, reflecting a general distinction of human behavior, which alternatively attributes to the individual the role of agent or observer. Although much research in cognitive psychology was devoted to demonstrating that language and concepts are rooted in the sensorimotor system, no study has investigated the presence of implicit associations between different adverbs of place ( All human languages contain special grammatical terms that serve to distinguish between different sectors of space, using the speaker or addressee as a frame of reference. Crosslinguistic research suggests that a large proportion of languages in the world make a fundamental binary distinction between terms that refer to something that is a short distance away and terms that refer to something that is a great distance away . Among tThe discovery of the neurophysiological basis of the distinction of physical space into near and far has not been trivial. Indeed, at a level of physiology of vision, no index allows distinguishing in a binary way “near” from “far”. It is only possible to have visual information about which object is “closest”. Information on the distance between the observer and static objects is based on cues provided by the coordinated use of the two eyes, mainly stereopsis and eye convergence, which compare the parameters coming from different objects simultaneously present . The sitNeuropsychological studies investigating neglect patients ,7 have sThe main difference between the stick and the laser pointer is functional. With the stick, you reach the target, and you can exert such force that you can break the target, rotate it, push it, or make it feel touched in the case of an animated being. In the latter case, you can communicate something to the target, you can catch his attention, you can push him in a certain direction, stroke him with a light touch, or punish him with a heavy touch. The effects on the target are exactly those that would be produced by the use of the arm/hand. With the laser pointer, in contrast, you can point to something very precisely, but you are not able to physically modify the target. You can neither break it, nor move it, nor draw his attention if he is not looking at you. The laser pointer behaves in a similar way to the eyes; it has the same ability to focus on an extremely precise point of space from which we can obtain the information that is interesting at that moment. Several studies on monkeys, patients, and normal participants also support the view that tool use can modulate peripersonal space ,13,14,15far vs. near) that are inconsistent with the real position of the object influences the kinematics of the reaching movement [Taken together, the neuropsychological, behavioral, and neurophysiological evidence suggests that the binary cognitive/linguistic distinction of space into near and far is not defined by metrical parameters but by functional ones, that is, it depends on the possibility to voluntarily act on the target to modify its physical state. This position is in agreement with embodied cognition theories ,23, accomovement . More inmovement . This laHowever, as far as we know, there is no experimental evidence that indicates an association at a cognitive level between spatial adverbs and actions with different functional characteristics, in a context that does not involve the participant in the execution of an action. The first objective of this study was to fill this gap by studying the presence of implicit associations between adverbs of space and labels referring to different actions performed in the physical environment.In addition, today, many of our activities are carried out using smartphones, and the COVID-19 pandemic has helped to increase the imbalance between actions in the physical and digital space. The digital space is an information space designed as a network of more or less static addressable objects, where information is perceived, stored, and retrieved, and where an individual can interact with others. Obviously, digital space is not constrained by metrical parameters, and we access to it by clicking the app icons which are present on the screen. Thus, digital space may be coded as peripersonal or extrapersonal according to the same rules that apply in the physical space, which is peripersonal when objects can be acted upon and a clear interaction is present and extrapersonal when objects can be just perceived. If so, then the app icons may reveal the potential actions to be performed on the target, and consequently they may be associated with the near or far space. Indeed, as with physical space, also with digital space, our behaviors may be divided into perceiving or acting. The terms used to categorize these different online behaviors are, respectively, “content consumption” and “content generation” . Contentnear is associated with actions that require reaching the target , and the adverb of space far with actions in which reaching the target is not allowed  and, congruently, whether in the digital environment, the adverb of space near is associated with app icons directing to content generation actions  and the adverb of space far with those directing to content consumption actions .Specifically, we propose that in both physical and digital environments the binary cognitive/linguistic distinction of space into near and far reflects an encoding in an operational/functional format . We aimed to test whether, in the physical environment, the adverb of space To this end, we used a series of Implicit Association Test (IAT) ,28 expernear and far and the actions grasp and look at (Experiment 1), and (ii) in the digital environment, to investigate the implicit association between the adverbs of space near and far and apps directing to content generation and content consumption actions (Experiments 2–4). We expected an association between near + grasp/far + look at, in the physical environment, and between near + content generation apps/far + content consumption apps, in the digital one.Specifically, in the present study, four experiments were conducted using the IAT: (i) in the physical environment, to investigate the implicit association between the adverbs of space https://osf.io/9g235/?view_only=f072f3bb7ea34def93ea3cb07b9f2e78 (accessed on: 15 November 2021)The data for each experiment are available at the link: near and far, needed to respectively classify objects at a reachable distance and landscapes and pictures showing individuals performing a reach and grasp action or a look at action. These actions are characterized by different functional characteristics. The reach and grasp action changes the state of the target as it moves it, whereas the look at action does not. According to the evidence reviewed in the Introduction, the binary distinction of space into near and far is defined by functional parameters, that is, it depends on the possibility to voluntarily act on the target to modify its physical state. Therefore, we expected an association near + grasp/far + look at.The aim of Experiment 1 was to test for the presence of an implicit association between the adverbs of space https://implicit.harvard.edu) to participate in the experiment. Participants were asked not to run the experiment more than once and not to share the link with others. Information about gender and age, but not on identity, was requested on the research platform before starting the experiment. All data were collected online, and no information about participants’ identity (neither name nor email address) was recorded. The number of data present for each experiment always corresponded to the number of students who answered the call for that experiment. We assume that no participant has taken part in more than one experiment as no student has been sent more than one link.For all the experiments reported in this article, the following indications apply. Participants were unaware of the purposes of the study. Procedures were in accordance with the guidelines of the Declaration of Helsinki. Data collection was carried out from March to December 2020. Participants were actively recruited by sending an invitation on Google Classroom to all students enrolled in the different teaching courses at the University of Ferrara. Interested students contacted the authors via email granting informed consent. Each interested student was emailed a private link to the Project Implicit research platform  volunteered to take part in Experiment 1.Forty-three participants  for the far category, five images showing landscapes; (iii) for the grasp category, images portraying a man or a woman grasping five different objects; (iv) for the look at category, images portraying a man or a woman looking at the same objects, at the same distance, with a Plexiglass placed between the actor and the object.Stimuli used in Experiment 1 consisted of 20 colored pictures, subdivided into four categories: (i) for the The link opened a webpage where participants were first asked to enter their gender and age and then displayed instructions for performing the task. In particular, a double entry table was presented in which images and associated categories were shown , accompaStimuli appeared one at a time in the middle of the screen, together with the names of the contrasted categories on the left and right at the top of the screen. If the participant made an error, a red X appeared below the stimulus and the trial continued until the correct key was pressed.The experimental session lasted about 10 min on average and consisted of 180 trials subdivided into seven blocks, following the standard task procedure described by Nosek, Greenwald, and Banaji . In thisgrasp category  and images belonging to the look at category . They were asked to press the E key for grasp and the I key for look at. In Block 2 , participants practiced sorting images belonging to the near category  and images belonging to the far category . They pressed the E key for near and the I key for far. In Blocks 3  and 4 , participants categorized images belonging either to the action and distance categories . They pressed the E key for grasp and near and the I key for look at and far. In Block 5 , participants practiced sorting images belonging to the action categories with the reverse key mapping from Block 1, i.e., grasp with the I key and look at with the E key. In Blocks 6  and 7 , participants sorted images from all four categories with the opposite key pairings from Blocks 3 and 4 , i.e., look at and near with the E key and grasp and far with the I key , participants practiced sorting images belonging to the he I key .The order of the action categories blocks (Blocks 1 and 5) and the combined blocks (Blocks 3 + 4 and Blocks 6 + 7) was counterbalanced across subjects. That is, half of the participants (Order 1) administered the blocks in the order just outlined, whereas the other half (Order 2) completed the task with Block 1, Block 3, and Block 4 switched with Block 5, Block 6, and Block 7 .https://implicit.harvard.edu). Response time is the time from the onset of a single stimulus to the categorization of that stimulus.Response times and errors were collected online through the Project Implicit research platform  removed responses faster than 350 ms and slower than 10,000 ms, (b) computed the mean of correct latencies for each combined block , (c) computed one pooled standard deviation for all trials in Block 3 and Block 6 (SD3–6) and another for Block 4 and Block 7 (SD4–7), (d) replaced errors with the mean of the correct responses in that response block (computed in Step b) plus a 600 millisecond penalty, (e) averaged the resulting values for each of the four blocks , (f) computed the two mean differences (BlockM6 − BlockM3) and (BlockM7 − BlockM4), (g) divided each difference score by its associated pooled standard deviation, and (h) computed D as the equal-weight average of the two resulting ratios.Specifically, to calculate BlockM6 − BlockM3 corresponded toBlockM7 − BlockM4 corresponded toAccording to the present blocks sequence, D score indicated an association near + grasp/far + look at.Therefore, a positive D scores of all participants were calculated.The mean and the standard deviation of D score was compared against zero  using a one sample t-test.To test the significance of the association revealed by the IAT, the mean D score  = 4.595, p < 0.001, 95% C.I. ), indicating an association near + grasp/far + look at. That is, participants associated the adverb of space near more with the action category grasp and the adverb of space far more with the action category look at . The percent error was 5.64%.Results showed a positive and significant near and the reach and grasp action and between the adverb far and the look at action.Results of Experiment 1 indicated the presence of implicit associations between adverbs of space and different actions performed in the physical environment. Specifically, they showed a significant association between the adverb Therefore, these results suggest that the use of proximal or distal adverbs of space is related to the potential possibility of acting to modify the objects present in that space.near and far depends on the presence of digital actions that, respectively, involve or not a modification of the digital content.The aim was to use the IAT to study for the first time the presence of implicit associations between spatial adverbs and app icons that direct to online actions with different functional characteristics. The starting hypothesis was that not only the conceptual knowledge of the physical world is mapped within our sensorimotor system ,23 but anear and far, needed to respectively classify objects at a reachable distance and landscapes, and social and no social app icons. Social app icons  address content generation actions, and no social app icons address content consumption actions  We expected an association near + social/far + no social.Experiment 2 tested for the presence of an implicit semantic association between the adverbs M age = 23.65, SD age = 4.59, 44.1% women) volunteered to take part in Experiment 2.Thirty-four participants  for the far category, five images showing landscapes; (iii) for the social category, images showing App icons addressing five social media sites ; (iv) for the no social category, images showing App icons addressing five information media sites   for the  Google) .Procedure  and dataBlockM6 − BlockM3 corresponded toBlockM7 − BlockM4 corresponded toAccording to the present blocks sequence, D score indicated an association near + social/far + no social.Therefore, a positive D score  = 5.609, p < 0.001, 95% C.I. ), indicating an association of near + social/far + no social. That is, participants associated the adverb of space near more with the app category social and the adverb of space far more with the app category no social . The percent error was 5.64%.Results showed a positive and significant Results of Experiment 2 showed an implicit association between spatial adverbs and app icons that direct to online actions with different functional characteristics. Specifically, the difference between social and no social apps concerned the digital actions they addressed, that is, content generation and content consumption. Therefore, present results suggest that adverbs of space also apply to digital space.near and social and between far and no social depended on the label used to classify the apps, which explicitly referred to social activity. Unfortunately, no other labels could be found that would allow easy categorization of the icons.However, some linguistics researchers criticize the idea that demonstratives are a particular class of spatial terms based on our bodily experience with concrete objects in space and propose that demonstratives are used primarily for social and interactive purposes . This poExperiment 3 was designed to test the hypothesis of an implicit association between spatial adverbs and different categories of app icons, without using a category label that refers to social activity. Since we could not find labels to categorize multiple apps, we decided to use only two apps, i.e., WhatsApp and a weather information app. WhatsApp allows users to send text messages and voice messages; make voice and video calls; and share images, documents, user locations, and other content. Undoubtedly, it is an app that requires content generation. On the contrary, using an app to check the weather requires content consumption. We used images of the most used weather forecasting apps in Italy .M age = 22.42, SD age = 2.18, 53.8% women) volunteered to take part in Experiment 3.Twenty-six participants  for the far category, five images showing landscapes; (iii) for the WhatsApp category, images showing five different WhatsApp icons; (iv) for the Weather category, images showing five different weather forecasting Apps  for the ing Apps .Procedure  and dataBlockM6 − BlockM3 corresponded toBlockM7 BlockM4 corresponded toAccording to the present blocks sequence, D score indicated an association near + WhatsApp/far + Weather.Therefore, a positive D score  = 2.384, p < 0.05, 95% C.I. ), indicating an association of near + WhatsApp/far + Weather. That is, participants associated the adverb of space near more with the app icon WhatsApp and the adverb of space far more with the app icons Weather . The percent error was 5.10%.Results showed a positive and significant WhatsApp, an app that requires content generation, was associated to the adverb near, while Weather forecasting apps, requiring content consumption, were associated to the adverb far.Results of Experiment 3 confirmed those of Experiment 2. They showed an implicit association between different adverbs of space and different categories of app icons. Specifically, However, even in this case, an alternative interpretation may question whether the results depended on the functional characteristics of the digital actions evoked by the app icons. Indeed, it is possible that the highlighted association depended on the presence of landscapes, a possible destination of a journey, and on the interest in weather that can jeopardize the decision to move.Experiment 4 aimed to test the hypothesis of an implicit association between spatial adverbs and categories of app icons related to content consumption and content generation, avoiding confounding variables related to category labels and the meaning of the stimuli. For this purpose, we selected WhatsApp and Google Chrome icons. Google Chrome is a web browser, that is, a software application for accessing information on the World Wide Web and, therefore, refers to content consumption.M age = 21.39, SD age = 3.25, 59.1% women) volunteered to take part in Experiment 4.Forty-four participants  for the far category, five images showing landscapes; (iii) for the WhatsApp category, images showing five different WhatsApp icons; (iv) for the Google category, images showing five different Google icons  for the le icons .Procedure  and dataBlockM6 − BlockM3 corresponded toBlockM7 − BlockM4 corresponded toAccording to the present blocks sequence, D score indicated an association near + WhatsApp/far + Google.Therefore, a positive D score  = 3.549, p < 0.001, 95% C.I. ), indicating an association of near + WhatsApp/far + Google. That is, participants associated the adverb of space near more with the app icon WhatsApp and the adverb of space far more with the app icon Google  and Google , respectively.Results of Experiment 4 confirmed those of previous experiments, that is, we observed an implicit association between different adverbs of space, near and far depends on the functional characteristics of the potentially performed actions in that space. This position stems from neuroscientific evidence pointing to separate neuronal circuits coding the near peripersonal space, that, is the area of space reachable by body parts, in which objects can be manipulated, and the far extrapersonal space, that is, the area of space out of reach, in which objects can be only perceived [near and actions able to act on the target and between far and actions devoted to the use or perception of target information. This binary distinction between actions with different functional characteristics is present not only in the physical space  but also in the digital one. Digital behaviors are divided into content generation and consumption: the first produces new digital content to be published online, and the second is limited to the use of content already present on the network [The present study aimed to test the semantic association between adverbs of place and the concept of acting vs. perceiving. Specifically, we hypothesized that the use of adverbs erceived ,50,51,52 network .near (images showing objects at a reachable distance) and the category far (images showing landscapes), with actions characterized by different functional characteristics, performed in the physical (Experiment 1) and digital (Experiments 2–4) environment.To this end, we used a series of IAT experiments ,28 to innear and grasp and between far and look at. Note that in both grasp and look at stimuli, the objects were placed at the same distance from the agent. In the first case, the agent touched the object with the extended arm, in the second one, a transparent Plexiglas barrier was placed between the agent and the object, and the agent’s hand was resting on the table. This detail is important for several reasons. The first one is that it excludes that IAT results depended on a different distance between the agent and the object. A farther metric distance could easily be associated with the considerable distance from which you look at the landscapes used as stimuli for the far category. The second reason regards the necessity to carefully distinguish the encoding of peri- and extrapersonal space in a metric format  from that in an operational/functional format  [In Experiment 1, actions were grasp  and look at . Results confirmed the hypothesis, showing a stronger association between e agent) . We hypoe agent) ,55.near and content generation apps and between far and content consumption apps. While possible alternative explanations could apply for Experiments 2 and 3, we found no possible confounding variable linked to category labels, the meaning of the stimuli, or other that could explain the results of Experiment 4 in an alternative way. Specifically, present results suggest that adverbs of space also apply to digital space and that the distinction into near and far depends on the functional characteristics of digital actions addressed by the app icons. In future experiments, the usage of the digital app by the participants will also be taken into account. In fact, many people may be using platforms like Instagram or Twitter more for content consumption than for content generation. Current results already indicate a strong effect that would likely be reinforced if we could only consider participants using these apps for content generation. Furthermore, the next experimental steps will aim to generalize these results to contexts that do not contrast social activities with non-social activities. For example, we will test the hypothesis in a condition where content generation does not involve a social environment, e.g., a single-player game.In Experiments 2–4, actions were represented by different app icons addressing either content generation or content consumption behaviors. In all these experiments, results confirmed the hypothesis showing an association between grasp and to look at) are specifically associated to different adverbs of space  depending on the possibility to perform that action at that space. That is, grasping is only possible in the near space. Therefore, these results are in favor of the first hypothesis and can hardly be explained by the second one.Regarding the physical space, several neuroscience findings showed the crucial role of action consequences in the coding of space, as extensively discussed in the Introduction . HoweveWhile neuroscience research has devoted many resources to studying the role of the sensorimotor system in coding of physical space, in the era of smartphones, almost no studies are present on the influence that the acquisition of digital skills and the constant utilization of technological devices has on sensorimotor abilities and processes. The only few studies suggest that something interesting is happening there. For instance, touchscreen users showed larger amplitude of cortical potentials in response to tactile stimulation of the fingertips compared to nonusers, and amplitude was directly proportional to the recent phone use history . Moreovenear/far association could reflect a figurative closeness rather than a spatial or agency-related effect. We trust that in the future all alternative explanations will be taken into consideration allowing to verify the correctness of our interpretation.Obviously, this being the first study that deals with the relationship between spatial concepts and different apps, the absence of control conditions may limit the internal validity of the study. Further studies will be needed to rule out that the results do not depend on other factors such as, for example, different attitudes towards different apps. Among others, one possibility could be that participants might perceive WhatsApp as a more trustworthy app than Google. In this case, the A further and important limitation of the present study is evident, due to the restrictions caused by the COVID-19 pandemic which made it impossible to expand the experimental sample to other categories. All participants in the study were students belonging to generation Z . The average Gen Z received their first mobile phone at age 10.3 years, grew up playing with their parents’ mobile phones in a hyper-connected world, and the smartphone is their preferred method of communication. Together with Millennials (born between 1980 to 1996), they are defined as digital natives, as opposed to digital immigrants  . Indeed,near and far and, respectively, actions that determine an effect in space  and actions that only allow the perception of objects in space . This same result was also found for the digital space, as even in this environment our behaviors are divided into acting and perceiving. Specifically, results indicated an implicit association between the adverb near and app icons  that direct to content generation actions and the adverb far and app icons  that direct to content consumption actions. For the first time, present findings suggest that adverbs of space also apply to digital space.Present findings suggest that the distinction in the use of proximal or distal space adverbs depends on the characteristics of the actions potentially suitable to be performed in that space. The results showed, for the first time, an implicit association between the adverbs of


Conus omaria venom, is a potent antagonist at α7 nAChRs. We determined the co-crystal structure of OmIA with Lymnae stagnalis acetylcholine binding protein (Ls-AChBP) that identified His5, Val10 and Asn11 as key determinants for the high potency of OmIA at α7 nAChRs. Remarkably, despite a competitive binding mode observed in the co-crystal structure, OmIA and analogues displayed functional insurmountable antagonism at α7 and α3β4 nAChRs, except OmIA analogues having long side chain at position 10 ([V10Q]OmIA and [V10L]OmIA), which were partial insurmountable antagonist at α7 nAChRs in the presence of type II positive allosteric modulators (PAMs). A “two-state, two-step” model was used to explain these observations, with [V10Q]OmIA and [V10L]OmIA co-existing in a fast reversible/surmountable as well as a tight binding/insurmountable state. OmIA and analogues also showed biphasic-inhibition at α7 nAChRs in the presence of PNU120596, with a preference for the high-affinity binding site following prolonged exposure. The molecular basis of binding and complex pharmacological profile of OmIA at α7 nAChRs presented in here expands on the potential of α-conotoxins to probe the pharmacological properties of nAChRs and may help guide the development novel α7 modulators.OmIA, isolated from  Conus venoms (12–20 amino acids (aa)). Classical α-conotoxins are characterised by a CC–Xm–C–Xn–C framework forming three possible disulfide connectivities: globular , ribbon  and bead   based on the number of residues within the two loops  braced by the disulfide bonds. The pharmacological targets tend to correlate to the loop size, with α3/5-conotoxins active toward muscle nAChRs, while the 5/5, 4/3, 4/4, 4/5, 4/6 and the most common 4/7 subgroup mainly interacting with neuronal nAChRs   with thel nAChRs . The exq2+, low agonist sensitivity in the resting state, inotropic/metabotropic dual action, rapid activation and fast desensitization. Agonist activation of α7 nAChRs is also sensitive to modulation by positive allosteric modulators (PAMs), with type I PAMs potentiating peak agonist responses and type II PAMs prolonging the opening times of nAChR by reducing receptor desensitization -acetylcholine binding protein (AChBP) that revealed three residues, His5, Val10 and Asn11, play essential roles in the activity of OmIA at α7 nAChRs. Interestingly, despite a competitive binding mode observed in the OmIA/Ls-AChBP complex, OmIA and analogues for the first time were found to display functional insurmountable antagonism at α7 and α3β4 nAChRs, with OmIA analogues having long side chains at position 10 acting as partial insurmountable antagonists at α7 nAChRs in the presence of type II PAMs. These studies provide with new insights into the pharmacological properties of α-conotoxins as well as the important α7 nAChR subtype.OmIA, α-conotoxin purified from 7 nAChRs . In thisI-CysIII and CysII- CysIV for globular isomer. Peptide cleavage from resin and global side chain deprotection were done by treatment with scavenger mixture (trifluoroacetic acid (TFA)/water/triisopropylsilane, 95:2.5:2.5, v/v/v) for 30 min at 40°C on Razor system . The cleaved peptides were precipitated with cold diethyl ether, centrifuged (1957xg x3), redissolved in 50% aqueous acetonitrile (ACN) and lyophilized.α-Conotoxin OmIA and its variants were assembled by solid-phase methodology on a Liberty PRIME peptide synthesizer  using Fmoc chemistry and standard side chain protection, except for cysteine residues. Cys residues were orthogonally protected in pairs with acid-labile trityl (Trt) and acid-stable S-acetamidomethyl (Acm) respectively on Cys2) (10 mg/ml dissolved in MeOH) while stirring until a pale yellow colour persisted. The solution containing partially oxidized peptide was then diluted with an equal volume of 50 mM HCl in 50% aqueous MeOH. Simultaneous removal of the Acm group and the second disulfide bridge formation were accomplished by the continued addition of I2 . The oxidation reaction was monitored via analytical high performance liquid chromatography (a linear gradient of 10–40% solvent B (90%ACN/0.05%TFA) over 30 min at a flow rate of 1 ml/min on a C18 column  and electrospray ionization-mass spectrometry. The oxidation reaction was quenched by the addition of ascorbic acid and diluted 20-fold with solvent A. Bicyclic peptide was purified by reverse phase- high performance liquid chromatography (RP-HPLC) on a C18 Vydac column  using a linear gradient of 5–45% solvent B over 40 min at a flow rate of 16 ml/min. The final product was collected and analyzed by analytical HPLC and matrix-assisted laser desorption/ionization-time of flight.Disulfide bonds were formed selectively via a directed two-step oxidation. Trt protecting groups of the first Cys pairs were removed after peptide cleavage from resin, while Acm groups on the second Cys pairs remained intact. The oxidation of peptides was carried out in a buffer of 90% acetic acid/10% methanol (MeOH) with peptides at final concentration of 2 mg/ml. The first disulfide bridge formation between free cysteines was performed upon the dropwise addition of iodine , Ls-AChBPs were removed from Ub-tag by DUB enzyme (produced in-house). De-tagged Ls-AChBP was further purified by size exclusion chromatography to assess homogeneity and oligomerization state. The IMAC purified Ls-AChBP was analyzed on a calibrated analytical HiLoad 16/600 column and  for Ls-AChBP respectively using AKTA fast protein liquid chromatography system . The fractions containing the proteins were pooled and concentrated to the desired concentration using an Amicon centrifuge filter .The over-expression of escribed . UbiquitCircular dichroism (CD) analysis was used to study the secondary structure of peptides. CD spectra were obtained from Jasco J-810 spectropolarimeter . Peptides were dissolved in 20 mM ammonium bicarbonate buffer pH 7.4 and 55% trifluoroethanol at a final concentration of 50 μM. All measurements were done at room temperature under a nitrogen atmosphere (15 ml/min) with a scanning speed at 10 min and a 4 s response time. Absorbance was measured in the far-UV region (185–260 nm) via a cell with a path length of 1 cm and the capacity of 400 μL. Interference due to solvent, cell, or spectropolarimeter optics was eliminated via the subtraction of CD spectra of the pure solvents from those of the peptide. CD data in ellipticity was calculated to mean residue ellipticity [(θ)] using the equation: (θ) = θ/[10 × Np ×  × l], where θ is the ellipticity in millidegrees, C is the peptide molar concentration (M) of the peptide, l is the cell path length (cm), and Np is the number of peptide residues.Ls-AChBP and OmIA were mixed at a molar ratio of 1:2 at 4°C for 1 h before setting up crystallisation trials. Crystals were successfully grown at room temperature using the hanging drop method by mixing volumes of protein and reservoir solution at a ratio 2:1. The crystals for OmIA were grown at 0.2 M ammonium sulfate, 5% PEG4000 and 0.1 M sodium acetate trihydrate at pH 4.6. The crystals were cryo-protected with reservoir solution plus 20% (v/v) glycerol in liquid nitrogen.Purified de-tagged Ls-AChBP (PDB 2C9T) as search model. Refinement against experimental data was done using Phenix. refine and COOT until clear electron densities for OmIA were visible  FBS. Cells were passaged every 3–5 days using 0.25% trypsin/EDTA at a dilution of 1:5. Experiments were conducted over several months and spanned on average a minimum of 10–20 passages. Responses were not affected by cell passage number with consistent control responses recorded over the duration of experiments as responses.Cell culture was performed as previously described . Briefly2, 1.2 NaH2PO4, 5.0 NaHCO3, 140 NaCl, 11.5 glucose, 5 CaCl2, 10 HEPES at pH 7.4]. FLIPR data was normalised to the maximum choline response in the SH-SY5Y cells to yield the %Fmax. A four-parameter Hill equation was fitted to the data using GraphPad Prism 9.0. For the examination of biphasic behaviours, a biphasic model was fitted to the data using GraphPad Prism 9.0. Experiments were performed in triplicates in three independent experiments. IC50 and EC50 values are reported as means ± S.E.M.FLIPR assay was performed as previously described . Briefly3H]-epibatidine to the recombinantly expressed Ls-AChBP was determined in competitive radioligand binding assays. Briefly, [3H]-epibatidine  and increasing concentrations of test ligand in a final volume of 100 ml were incubated in 96-well plates  precoated with 1 ng/ml of Ls-AChBP per well in binding buffer . The mixture was then removed and 100 ml of scintillant  added to each well. Bound radioactivity was measured with a Wallac 1450 MicroBeta liquid scintillation counter (Perkin Elmer).The ability of VxXIIB variants to displace the binding of OmIA. The degree of maximal response depression increased as the concentration of OmIA and analogues increased, suggesting insurmountable antagonism by OmIA. In contrast, [V10Q]OmIA depressed the maximal response and caused a rightward shift in the EC50 for choline (p < 0.05), suggesting [V10Q]OmIA has a different mechanism of action compared to OmIA and [N9H]OmIA , and [V10Q]OmIA had 3.6-fold increased potency at α3β4 nAChRs and 6-fold decreased potency at α7 nAChRs in the presence of TQS compared to wildtype (p < 0.05)   . Similar < 0.05) .Ls-AChBP, with the largest reduction exhibited by [V10K]OmIA and [V10E]OmIA  (p < 0.05) (50 10-fold at TQS-α7 nAChRs (p < 0.05) but slightly decreased OmIA activity at α3β4 nAChRs (p > 0.05).At nAChRs, the substitution of long charged side chain amino acid into position 10 abolished OmIA activity ( < 0.05) . Meanwhi < 0.05) . While OmIA to display high affinity partial inhibition and a lower affinity inhibitory action at PNU120596-α7 nAChRs. Partial inhibition by OmIA and [N9H]OmIA may arise through OmIA being a partial agonist, however, OmIA and all analogues were unable to induce Ca current , or becaThe complex pharmacological profile of OmIA and analogues seen at PAM-α7 nAChRs, with different PAMs differentially enhancing this phenomenon at α7 nAChRs, suggests a direct involvement of type II PAMs in modulating this phenomenon. In contrast, at α3β4 nAChRs, any surmountable antagonism of [V10Q]OmIA and [V10L]OmIA or the biphasic behavior of OmIA are less apparent. The effect of PAMs on OmIA pharmacology may arise from enhanced channel gating and associated conformational changes in the orthosteric ligand binding site induced by PNU120596 and TQS  Supplem. Long siLs-AChBP and a model of α-conotoxin OmIA complexed with α7 nAChRs that explains its high potency at α7 nAChRs. OmIA displayed functional insurmountable antagonism at human α7 nAChRs despite a binding to the othosteric site. OmIA pharmacology provides significant new insights into mechanisms of inhibition of α7 nAChRs, and the influence of type II PAMs on nAChR function. These results may facilitate the design of α-conotoxin analogues with novel features and potentially innovative therapeutic leads.In summary, we report the crystal structure of OmIA with