The adjuvant-induced arthritis (AIA) model is widely used in research to investigate arthritis pathogenesis. Hind paw inflammation is the main outcome in this model with high loss of mobility function partly related to pain. However, analgesics such as non-steroidal anti-inflammatory drugs or opioid drugs interfere with the inflammation process related to arthritis, thus reducing their beneficial use in this model. Therefore, we investigated the effect of nefopam on arthritis development in order to improve pain management in the AIA model.Mycobacterium butyricum on defining day (D) 0. At D6, rats (n = 10) received nefopam  or NaCl 0.9% IP or 1% sucrose in water (n = 5 for each). Rats were monitored with the arthritic index (AI) and ankle circumference. Pain was assessed by scoring based on behavioral indicators. Histology, RT-qPCR, and microcomputed tomography were performed.Female Lewis rats were randomly divided into two groups, and each group received an injection of The clinical parameter AI and ankle circumference were not different in both groups at various time points. However, pain score was significantly lower in the nefopam group at the early stage of the disease. At a later stage of the disease, inflammation was mildly lower whereas bone erosion and bone loss parameters increased in the nefopam group.Nefopam provided a slight reduction in the level of pain at the arthritis onset without reducing arthritis severity and bone loss in the rat AIA model. However, it should be administrated orally for a shorter period to avoid inflammation reduction in the long run. This model is widely used to investigate arthritic diseases –3. This os (PO)] . The aimad libitum food and water access. Mycobacterium butyricum  dissolved in 200 μl sterile mineral oil (5 mg/ml) was injected at the base of the tail in order to induce arthritis. The day (D) of arthritis induction was considered as D0. Rats were killed at D17, left ankles and blood samples were collected and stored at −80°C until further investigations.This study was approved by the Ethical Committee for Animal Experiments of Saint-Etienne University (agreement number: 2019032816186046). Experiments were conducted using 6-week old Lewis female rats . Animals were housed with a 12 h light/dark cycle and with n = 5) or orally at 60 mg/kg/day (expected dose) (n = 5). In the two control groups, rats received NaCl 0.9% IP (n = 4) or oral sugar water . The nefopam administration began at D6, 4 days before arthritis onset at D10 in this model. Drink consumption was assessed 1 week before nefopam administration through the percentage of body weight. Then, drink consumption was measured every day to assess and adapt the nefopam dose received. Drink consumption was normalized by body weight to have an approximate idea of the nefopam dose received by animals.The animals were divided into four groups. In the nefopam groups, rats received nefopam either IP at 20 mg/kg/day (ed dose)  in sugarClinical monitoring was performed by the measurement of two parameters representative of arthritis severity: arthritic index (AI) based on joint swelling and animal mobility and ankle circumference. As previously used , the AI Right hind ankles were fixed in 10% formalin for 72 h at 4°C. After decalcification, ankles were cryoprotected, embedded, and frozen at −80°C. Cryosections (30 μm) were performed using Microm HM 560 Cryostat  and stained with H&E. The histology of ankle allowed us to assess inflammation especially in the navicular bone, which is the most sensitive bone in the AIA model . RNA was separated from proteins after centrifugation in chloroform. RNA was purified with RNeasy plus . Quality and quantity of RNA were assessed by the Experion RNA analysis  and QuantIT RiboGreen RNA assay (Thermo Fisher Scientifc), respectively. Reverse transcription (RT) was performed on 1 μg of RNA. Quantitative RT polymerase chain reaction (PCR) was conducted on the CFX96 RealTime System (BioRad) with LightCycler FastStart DNA Master plus SYBRgreen I . The results were normalized to the housekeeping gene expression hypoxanthine-guanine phosphoribosyltransferase. Primer sequences of candidate genes are detailed in ex vivo with a microcomputed tomography  at 70 kVp (peak kilovoltage) and reconstructed under a resolution of 12.5 μm. Segmentation parameters for reconstruction and trabecular analysis were (sigma/support/threshold) 1/2/215 for trabecular bone and 0.7/2/215 for cortical bone.Rat ankles were scanned p < 0.05. When no difference was observed between animals that received the treatment IP and orally for each group, data were pooled as follows; the nefopam group includes all animals which received nefopam IP and orally, and the control group includes animals that received NaCl 0.9% IP and sugar water through drinks.All statistical analyses were performed using R software. A nonparametric analysis was performed by the Wilcoxon test. Results were considered significantly different when We first evaluated the effect of nefopam on arthritis severity. Arthritis onset was at the same time in all 4 groups. AI and mean ankle circumference began to increase at D10 for nefopam and control groups. Mean clinical score and mean ankle circumference kinetics were not different between nefopam and control groups .vs. the control group, with a (p = 0.06) decreasing trend at D11, D13, and D14 (p < 0.05). Measures of pain indicators were similar in the nefopam and control groups for each day, except at the D13. At this time when the clinical kinetic score reaches its zenith, the nefopam group showed few pain indicators than the control group .Inflammation of the synovial membrane was similar in the nefopam and control groups, especially in the navicular bone with the infiltration of immune cells with synovial hypertrophy . At the p = 0.1822 for cortical porosity) of bone loss in the nefopam group compared to the control group, cortical porosity and bone volume/total volume (BV/TV) were not different between the two groups , nefopam slightly reduced the pain score. Nefopam has been shown to have antinociceptive effects on rodents , 9, so i, nefopamIn our study, the AIA model was used due to its reliability in onset and progression . FurtherIt is important to mention some limitations in this study. First of all, the number of animals per group was not very high but was sufficient to perform statistical analyses. This choice was made from an ethical point of view in order to reduce the number of animals that could suffer. For the animals that received oral nefopam, the dose per animal was not exactly known since the animals were housed in groups in order to avoid social stress. However, this mode of administration is not invasive and depends on the voluntary activity of the animals. It could also be hypothesized that oral administration ensures a continuous effect on pain management unlike IP administration, which can be intermittent.To conclude, nefopam was effective in reducing pain in the AIA model in the early stage of the arthritis. Oral administration could be the best way to treat pain in this model as it is less invasive than other administration methods, and nefopam dosage can be easily adapted in order to reduce pain score. However, its administration after the pain peak should be reconsidered as the pain was no longer reduced. Moreover, a prolonged administration of nefopam slightly reduced the inflammation. More investigations are necessary to determine the best administration protocol of nefopam in the AIA model, in order to apply it on other inflammation disease models and then improve pain management.The original contributions presented in the study are included in the article/The animal study was reviewed and approved by Ethical Committee for Animal Experiments of Saint-Etienne University (agreement number: 2019032816186046).in vivo experiment. ED and M-TL carried out molecular biology. All authors approved the final version.ED and HM designed the study, analyzed the results, and wrote the manuscript. ED, HM, MM, AV-B, and SP contributed to the Medac provided nefopam for free for this research.HM reports non-financial support from Medac related to this work. Medac provided for free the nefopam. HM reports personal fees and non-financial support from AbbVie; personal fees from Accord; personal fees from Amgen; grants, personal fees and non-financial support from Biogen; grants, personal fees, and non-financial support from Bristol Myers Squibb; personal fees and non-financial support from Cell Trion Healthcare; grants and non-financial support from Fresenius Kabi; personal fees and non-financial support from Galapagos; non-financial support from Janssen; grants personal fees, and non-financial support from Lilly; personal fees and non-financial support from MSD; grants, personal fees, and non-financial support from Nordic Pharma; personal fees, non-financial support and other from Novartis; grants, personal fees and non-financial support from Pfizer; personal fees from Roche Chugai; grants, personal fees, and non-financial support from Sanofi, outside the submitted work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


MSX1, PAX9, WNT10A, and LRP6. Thus, mutations in these genes can cause congenital tooth agenesis in humans. In this study, we identified a novel nonsense WNT10A variant, NM_025216.3(WNT10A_v001):c.1090A > T, which produces a C-terminal truncated gene product, p.(Lys364*), in a sporadic form of congenital tooth agenesis. The variant was not found in the healthy parents and thus was considered to cause congenital tooth agenesis in the case.Congenital tooth agenesis is one of the most common anomalies in humans. Many genetic factors are involved in tooth development, including  Congenital TA is the most frequent dental anomaly in humans, with a frequency of 6.8%  for hypodontia and 0.1%  for oligodontia in the Japanese population. We previously demonstrated that the sibling recurrence risk ratio of oligodontia is 43.8%, suggesting that oligodontia exhibits a dominant mode of inheritance in most cases6.Congenital tooth agenesis (TA) is classified by the number of missing teeth: hypodontia is defined as five or fewer missing teeth, excluding the wisdom teeth, while oligodontia is defined as six or more missing teethWNT10A. WNT10A is the most frequent cause of human nonsyndromic TA , including in the Japanese population6. The WNT signal stabilizes intracellular β-catenin, which activates lymphoid enhancer factor/T-cell factor protein. In tooth germ cells, WNT/β-catenin signaling induces the expression of essential transcription factors for human tooth development, such as MSX1, PAX9, RUNX2, and BMP410. However, the genetic causes remain unknown in more than 50% of human TA cases17. Therefore, we performed whole-exome sequencing analysis to explore the genetic cause of an individual case.Robust tooth development requires a variety of growth factors produced by the oral ectodermal epithelium, such as fibroblast growth factors, bone morphogenic proteins, and the gene The patient was a 21-year-old woman with a tooth missing at 17, 13, 12, 22, 23, 27, 28, 38, 48 (FDI tooth numbering system), confirmed by X-ray photography Fig. . The patWNT10A variant, NM_025216.3(WNT10A_v001):c.1090 A > T, was identified in the proband (II:1). With a specific primer set , the nucleotide substitution was confirmed by polymerase chain reaction and Sanger sequencing, revealing that the variant was not shared with the healthy parents .According to the manufacturer’s protocol, genomic DNA was extracted from 2 ml of saliva with the Oragene® DISCOVER kit. Then, whole-exome sequencing (WES) was performed with the proband’s genomic DNA. A novel heterozygous nts Fig. . The var18. Thus, the PyMOL Molecular Graphics System (PyMOL) was used to graphically predict the effect of the truncated form of the WNT10A variants detected by WES in three dimensions. Specifically, the anti-parallel beta-sheet secured by disulfide bonds in the C-terminus of WNT ligands is a crucial region for binding to the FZD receptor. The nucleotide substitution identified in the current case resulted in a premature stop codon at nucleotide 1090. Thus, the product of the WNT10A gene lacks the C-terminus, resulting in the variant p.Lys364*. Because the amino acid sequence, especially the arrangement of cysteine residues in the C-terminus, is highly conserved between WNT10A and WNT3  receptor and LDL receptor-related protein 5/6 (LRP5/6) Fig. . With crNT3 Fig. , they shNT3 Fig. .Fig. 2StWe performed a luciferase assay in 12-well plates with a stable PC3 reporter cell line of TCF/LEF-responsive luciferase. The following expression vectors were cotransfected: LRP6, FRIZZLED4, and WNT10A (500 ng/well). The cells with C-terminal–truncated WNT10A (p. Lys364*) exhibited significantly decreased WNT/β-catenin signaling compared with the level of the wild-type control Fig. . WesternThe relevant data from this Data Report are hosted at the Human Genome Variation Database at 10.6084/m9.figshare.hgv.3273.


Behavioral coordination is involved in many forms of primate interactions. Co-representation is the simultaneous mental representation of one’s own and the partner’s task and actions. It often underlies behavioral coordination and cooperation success. In humans, the dyadic social context can modulate co-representation. Here, we first investigated whether individual differences in co-representation in the joint Simon task in capuchin monkeys and Tonkean macaques can be explained by social factors, namely dyadic grooming and sociality index, rank difference and eigenvector centrality. These factors did not predict variation in co-representation. However, in this specific task, co-representation reduces rather than facilitates joint performance. Automatic co-representation therefore needs to be inhibited or suppressed to maximize cooperation success. We therefore also investigated whether general inhibitory control (detour-reaching) would predict co-representation in the joint Simon task in Tonkean macaques, brown capuchin and marmoset monkeys. Inhibitory control did neither explain individual differences nor species differences, since marmosets were most successful in their joint performance despite scoring lowest on inhibitory control. These results suggest that the animals’ ability to resolve conflicts between self and other representation to increase cooperation success in this task is gradually learned due to frequent exposure during shared infant care, rather than determined by strong general inhibitory control. Further, we conclude that the joint Simon task, while useful to detect co-representation non-invasively, is less suitable for identifying the factors explaining individual differences and thus a more fruitful approach to identify these factors is to design tasks in which co-representation favors, rather than hinders cooperation success.The online version contains supplementary material available at 10.1007/s10071-022-01622-8. Various natural forms of human and nonhuman primate cooperation like coalition formation, food sharing, group hunting, territorial defense, biparental care, communication or social play involve behavioral coordination with other individuals , capuchin monkeys (Sapajus apella) and Tonkean macaques (Macaca tonkeana) tested with a joint Simon task  and in case of a correct choice, both partners receive a reward, independent of which actor provided it. This task set-up is similar to the cooperative designs used with human adults, in which dyads are explicitly instructed to cooperate, sometimes emphasized by the promise that the best performing dyads in a given group of participants will receive a reward . Thus, when sharing the task with a partner, typically error rates in response choices (mainly in primates) and in first heading directions  or incompatible trials . Typically, answering to incompatible stimuli is more difficult than answering to compatible ones when individuals share the task with a joint action partner : Since in the joint Simon task co-representation reduces rather than facilitates cooperation success , the amount of correct response choices  in incompatible trials indicates how flexible co-representation is deployed to increase SO distinction and improve joint performance. Such flexibility requires the inhibition of co-representation, and electrophysiological and fMRI evidence indeed shows the recruitment of control mechanisms in the joint Simon task to inhibit motor responses when it is the partner’s turn, and to increase action monitoring and joint attentional processes , cooperative flexibility hypothesis, Miss et al. An alternative to general inhibitory control is that the suppression of co-representation is achieved through repeatedly and frequently experiencing SO integration—distinction conflicts during joint action  tend to be better cooperators in joint pulling tasks requiring simultaneous actions. Based on the findings in animals and humans, strong social bonds can be predicted to lead to stronger SO integration and co-representation. However, based on the conflicting role of co-representation and the necessity of SO distinction in the joint Simon task, we may likewise predict higher cooperation success (and thus weaker co-representation) in dyads with stronger social bonds. This is particularly likely if the suppression of co-representation does not require general inhibitory control ability but can be achieved otherwise, for instance through repeated exposure to SO conflicts in joint action contexts and training. This latter pathway would be consistent with the cooperative flexibility hypothesis, which proposes co-representation as a universal, automatic process in primates, and that the flexibility to suppress it is not primarily dependent on advanced general cognition but is enhanced when individuals are frequently exposed to SO integration—distinction conflicts.Our goal was to investigate if social factors or general inhibitory control ability could explain individual differences in co-representation in the Tonkean macaques, the brown capuchin and the common marmoset monkeys from Miss et al.  and MissTo examine the role of general inhibitory control ability in suppressing co-representation in the joint Simon task, we tested in the Tonkean macaques, the brown capuchins and the common marmosets whether inhibitory control skills independently assessed with a detour-reaching task  and consume it, while the other two cups were opened to uncover the non-baited side. In case of an incorrect choice, the non-selected cups were opened to uncover the baited side and the screen was lowered.A test session started with two to six motivation pre-trials in which the sounds were broadcast from a central position  to ensure that the subjects remembered the corresponding sound-side association and to check their motivation of receiving food items as rewards. The test session was only started on a particular day if they chose each baited side twice correctly during these pre-trials. If this criterion was not met, the subjects were tested the following day. In every test trial, the sounds were played back from either the left- or the right-hand side, thus either eliciting stimulus incompatibility or not. In compatible trials, sound “A” was played back from the left-hand side and sound “B” from the right-hand side, whereas in incompatible trials, sound “A” was played back from the right-hand side and sound “B” from the left-hand side. The order of the two sounds and of the sides from which they were broadcast as well as the sides of the subjects were pseudo-randomized and counterbalanced. Since in the joint task, the individuals shared the task with a partner monkey, we expected a joint Simon effect  in the focal individual, expressed in increased error rates in incompatible trials and consequently fewer joint rewards.In the marmosets, the dyads were formed within their family groups  and preselected according to observations of affiliative behaviors during the training phase, such as entering together and remaining in proximity in the testing cage, participating next to each other in trials and occasionally food sharing. The composition of the dyads was the same over all sessions. In the brown capuchins and the Tonkean macaques, the dyads were not predefined but formed in every session according to which animals decided to enter the experimental facility together at the same time. According to this free partner choice method, the composition of the dyads could vary across sessions but the dyads contained only partners that tolerated each other’s close proximity in the context of receiving food simultaneously. In both species, this resulted in pairings with the same partner individual in at least two sessions . Table Macaca tonkeana). The group consisted of 28 individuals during the period of data collection: 18 adults , four sub-adults , five juveniles  and one newborn. We also observed 14 individuals in a group of semi-free ranging brown capuchins (Sapajus apella) which consisted of 19 individuals during the study period: six adults , six sub-adults , five juveniles  and two newborns. All animals were housed at the Primate Centre of the University of Strasbourg, France and were captive born. The Tonkean macaques and the capuchin monkeys both had permanent access to a wooded park of 3788 m2 and 2332 m2 respectively, connected to a heated indoor-outdoor shelter. They were provisioned with commercial primate pellets twice a day and with fresh fruit and vegetables once a week. Water was available ad libitum. The Tonkean macaques moreover had 24 h access to Machines for Automated Learning and Testing (MALT) with the option to perform several cognitive tasks  in a group of semi-free ranging Tonkean macaques  was removed from the group on June 1, 2018 and transferred to another park. Therefore, the total amount of observational time was slightly lower (5 h) for this individual compared to the others. Observations were only recorded when the individual was in complete view (in the park or the outdoor shelter) and were balanced evenly throughout the day (8 h 30–18 h). An individual was observed only once a day and the order of the focal follows was assigned randomly every day. If the focal animal could not be located, the next assigned individual was observed instead. No more than four individuals from the assigned order could be skipped to avoid recording when most group members were in the indoor shelter or out of view. Focal samplings were only used for analyses if the total time during which the focal animal was in view was at least 5 min. Toward the end of the observational periods, specific individuals were prioritized to correct for unbalanced distribution of observational sessions across time.Behaviors were defined based on the social repertoire of Tonkean macaques .Behavioral observations were recorded either on paper or on an IPod Touch with the Animal Pro Behavior software . Based on an entire week of behavioral observations , inter-observer reliability between BS and FM was calculated on the durations (s) of observed social grooming and social contact behavior (ICC = 0.99) and on the recorded agonistic events as well as the identities of the observed individuals . With the Tonkean macaque data, we calculated Elo-ratings . For the observed dyads in the joint task, we calculated dyadic grooming indices (DGI) and dyadic composite sociality indices (DSI) based on the durations of the behaviors grooming and sitting in contact  using the package “lme4” with the Tonkean macaque and brown capuchin data to analyze a potential influence of social factors on the subjects’ strength of co-representation . Accordingly, to test for a potential influence of social factors on the Tonkean macaques’ joint Simon effects, we built a model on the joint task data with choice (either correct or incorrect answer) as a binary response variable and compatibility, absolute rank difference, DGI, DSI and eigenvector centrality as fixed factors. To test for a potential influence of social rank differences on the capuchins’ joint Simon effect, we built a model on the joint task data with choice as a binary response variable and compatibility and absolute rank difference as fixed factors. Both models included individual, session and partner as random factors, and were compared to a control model, containing only the control factor (compatibility) and the random factors. For all statistical analyses, model parameters were approximated using maximum likelihood estimation and model performance was assessed by likelihood ratio tests. All figures were generated using the package “ggplot2”.Callithrix jacchus) tested with the identical detour-reaching task  in a counterbalanced and pseudo-randomized order with the rule that the reward never appeared in the same location in more than two consecutive trials. In the more difficult central trials, the reward was placed in the middle of the Plexiglas barrier so that it was fully occluded by it. The two lateral conditions served as a distraction and an attenuation of the level of difficulty since the subject could directly reach for the food item.We measured inhibitory control ability with a detour-reaching task adapted for primates . As soon as the individual was attentive, we called her name and removed the cardboard screen. In case the first attempt was not successful, we kept the panel in place for max. 2 min to allow further attempts to reach around the panel and retrieve the food item. The individuals completed a session on the same day in as many trial-blocks as needed. All trials were video-recorded.κ = 0.97) for successful first attempts in the Tonkean macaques and the brown capuchins with 20% randomly selected video sessions. For the model calculations, we built glmms using the package “lme4” with the Tonkean macaque, the brown capuchin, and the marmoset data to analyze a potential influence of inhibitory control ability on the individuals’ strength of co-representation . Accordingly, we built models on the joint task data with choice as a binary response variable and compatibility and inhibitory control as fixed factors. The models included individual , session and partner as random factors, and were compared to a control model, containing only the control factor (compatibility) and the random factors.We scored all trials from the videos as either a successful first attempt  or not  and calculated the measure of successful detour-reaching per individual as the percentage of correct trials at first attempt out of the 20 central trials. We assessed interrater reliability  as binary response variable and all variables of interest  as fixed factors. This model was compared to the null model consisting of the intercept and random effects only. Individual nested in species, and session were included as random factors. For the fixed factor session, we set a priori polynomial contrast to test for trends across time. For pairwise comparisons between species, we performed Tukey adjusted post hoc tests using the package “emmeans”. Variance Inflation Factors (VIFs) were calculated to examine if predictors did not violate any multicollinearity assumptions using the package “car” . The proportion of the total variance accounted for by the model was assessed by the conditional Rp > 0.05, ∆AIC = 5.36, Ntotal = 209, Nindividuals = 7; brown capuchins: p > 0.05, ∆AIC = 1.87, Ntotal = 184, Nindividuals = 6]. In both models, only the fixed factor compatibility remained as a significant predictor, and none of the other fixed factors  showed a significant effect , the integration in the affiliative social network , and the bond strength with a given partner (the dyadic grooming index (DGI) and the dyadic composite sociality index (DSI)) could explain variation in co-representation in the Tonkean macaques and the brown capuchin monkeys. We built models on the joint Simon task data with choice as a binary response variable and found that the models did not improve compared to the control models containing only the fixed factor compatibility and the random factors  and revealed a significant effect of species and session . The monkeys improved their inhibitory control score over time (liner trend of session: β (SE) = 1.61 (0.39), 95% CI = , z = 4.10, p < 0.001). The capuchin monkeys generally had the highest inhibitory control scores (mean ± SEM = 82.00% ± 2.00%), followed by the Tonkean macaques (mean ± SEM = 23.57% ± 5.85%) and the common marmosets (mean ± SEM = 17.00% ± 17.00%). Pairwise Tukey adjusted post hoc tests revealed that the inhibitory control scores were significantly higher in the capuchins than in the marmosets (β (SE) = 5.11 (1.33), 95% CI = , z = 3.83, p < 0.001) and higher than in the Tonkean macaques (β (SE) = 3.27 (1.01), 95% CI = , z = 3.24, p = 0.003). No difference was found between the marmosets and the Tonkean macaques (β (SE) = − 1.85 (1.24), 95% CI = , z =− 1.49, p = 0.30) . In the marmosets, all dyads of a group are generally tolerant enough to be tested together, thus leading to ceiling effects regarding social tolerance. This first explanation is not unlikely because in humans, the influence of social factors on co-representation is often only observable in strong social contrasts. In particular, co-representation was observed in a cooperative but not a competitive task framing  co-representation is not entirely determined by strong general cognitive factors ..Indeed, we found that general motor inhibitory control as measured with a detour-reaching task was linked neither to co-representation nor the ability to suppress it, within each of the three species but also when all species were analyzed together. Among the three species, the common marmosets showed the lowest level of motor inhibitory control, as expected from the fact that they have by far the smallest brains among the primates tested here  as well as the ability to enhance SO distinction , and to measure for each of them separately how they are modulated by social factors. Joint Simon task studies in humans suggest that the influence of social factors increases with mutual dependency between co-actors  but seems rather strongest in those species who most routinely rely on, and thus accumulate greater experience in cooperation during their daily life, such as the cooperatively breeding common marmosets and humans. The advanced cognitive abilities of humans compared to primates were therefore not a precondition for the emergence of co-representation and cooperative flexibility during evolutionary times. Rather, it allowed our ancestors to deploy preexisting cooperative predispositions in ever more complex ways.Supplementary file1 (DOCX 734 kb)Below is the link to the electronic supplementary material.


Video question answering (Video-QA) is a subject undergoing intense study in Artificial Intelligence, which is one of the tasks which can evaluate such AI abilities. In this paper, we propose a Modality Attention Fusion framework with Hybrid Multi-head Self-attention (MAF-HMS). MAF-HMS focuses on the task of answering multiple-choice questions regarding a video-subtitle-QA representation by fusion of attention and self-attention between each modality. We use BERT to extract text features, and use Faster R-CNN to ex-tract visual features to provide a useful input representation for our model to answer questions. In addition, we have constructed a Modality Attention Fusion (MAF) framework for the attention fusion matrix from different modalities , and use a Hybrid Multi-headed Self-attention (HMS) to further determine the correct answer. Experiments on three separate scene datasets show our overall model outperforms the baseline methods by a large margin. Finally, we conducted extensive ablation studies to verify the various components of the network and demonstrate the effectiveness and advantages of our method over existing methods through question type and required modality experimental results. In recent years, studies on video question answering (Video-QA) based on both vision and natural language have successfully benefited from deep neural networks –5. This Most existing methods –11 attraThe Video-QA task is essentially the fusion of multiple modal data to generate accurate answers to questions related to the video story. Most models for Video-QA, e.g., –17 usualIn this paper, we propose a novel modal attention fusion model with hybrid multi-head self-attention for Video-QA task based on BERT . We expeA recent direction in Video-QA leverage text modality such as subtitle in addition to video modality for video understanding. It has been gathering a rising attention in recent years, with the release of various Video-QA benchmarks such as STAGE , it hasIn the past few years, many studies have thus focused on self-attention models, which aim to identify various complex relations to answering questions. For example, Li et al.  proposedOur work is designed on Video-QA tasks with BERT and Fast R-CNN. In this section, we formally describe the BERT and Faster R-CNN models.We use BERT  as the We use the Faster R-CNN  model toFeature extraction: Faster R-CNN utilizes the VGG16 network to extract the feature map of the candidate image, which is shared for the subsequent RPN layer and fully connected layer.RPN network: RPN network is used to generate candidate area frames. This layer determines that the anchor point belongs to the foreground or the background, and then uses the bounding box regression to correct the anchor frame to obtain an accurate candidate frame.ROI pooling layer: This layer collects the input feature maps and candidate target regions to extract the feature maps of the target region, and then transmits them to the subsequent fully connected layer.Target classification and regression: Faster R-CNN utilizes the feature map of the target area to calculate the category of the target area, and utilizes the bounding box regression to obtain the final precise position of the detection frame.The structure of our proposed framework aims to select the correct answer in the Video-QA tasks shown in . We proc768 with 5 candidate answer representations qa represents the maximum number of tokens per hypotheses. For each hypothesis, MAF-HMS learns to predict its correctness score and to maximize the score of the correct answer.We create 5 hypotheses by concatenating a question representation q ∈ ℝSimilarly, we create subtitle representations as At first, we extract the sequence of image frames at 3 fps for the video. Then, extract a high-level semantic representation for each image frame. CNN has been recognized as a powerful deep learning model that can capture the visual concept of the image, so our paper uses the Faster R-CNN model to extract visual characteristics We extracted video representations Two separate BERT layers are first applied on the subtitle-QA (s and qa) and Video-QA (v and qa) representations. The pre-trained BERT model can be automatically fine-tuned to achieve the most advanced performance in various NLP tasks. The first token in each input by BERT is [CLS], which is used to obtain the output in the classification task. The [SEP] token is added to indicate the separation between the two inputs. In this article, we consider the tokens of input for two BERT layers as follows:The output of BERT layers consists of a set of text and video features. These text and video features are flattened and expressed as Modality attention fusion framework is designed to fuse video features, subtitle features and QA features into the final MAF features, which are then fed into the hybrid multi-head self-attention layer to obtain the final prediction result.The QA features Where fc is a fully-connected layer. The fused subtitle features Similarly, we can define the fused video features as follows:We add fused subtitle features and fused video features to get the final fused features, also called MAF features More recently, studies on Video-QA task –29 show Where However,  showed tIn the hybrid multi-head self-attention, we add multiple intrinsic inter-vector similarities γ to express complex intrinsic relationships of heads on γi,j denotes the learnable parameter that can automatically measure the correlation between each head during training.where h is the number of heads, and we introduce a new matrix After obtaining the feature vector through hybrid multi-head self-attention, the probability y of each answer is the correct answer is predicted by the fully-connect and softmax layer:We evaluate our method on three video QA datasets. More details are given below.TVQA dataset is a benchmark for Video-QA, containing 152545 human annotated multiple-choice question-answer pairs , 21.8K video clips from 6 TV shows . The questions in TVQA dataset have five answer candidates and only one of them is ground-truth answer. The format of the questions is designed as follows: “[What/How/Where/Why/who]___[when/before/after/…]___?”, and the two part of the question requires visual and linguistic understanding. There are total 122,039 QAs for train set, 15,253 QAs for validation set and 7,623 QAs for test set, respectively.MSVD-QA is based on MSVD  video daIt is an open-ended dataset that contains 10K videos and 243K question answer pairs. It consists of five types of questions, including what, how, where, when and who. Compared to the other two datasets, videos in MSRVTT-QA contain more complex scenes. They are also much longer, ranging from 10 to 30 seconds long, equivalent to 300 to 900 frames per video. Splits for train, validation and test are with the proportions are 65%, 5%, and 30%, respectively.We compared our model with several methods:Combines information from different modalities with LSTMs and cross-attention.Utilize progressive attention memory to update the belief for each answer.Using Word2Vec and Bi-LSTM for visual and language representations.Using RCNN for visual and BERT for language representations.In all the experiments, the recommended train/validation/test split was strictly followed, we independently repeated each experiment 10 times and reported average results of ACC. (accuracy).We use BERT-Base uncased model, it has 12 layers and 768 hidden sizes. In our experiments, the maximum number of tokens per sequence is set to 128, the batch size is 64, the learning rate is set to 0.0001, and the epochs are set to 10. Our evaluation is performed on a machine with Intel(R) Xeon(R) Gold 6132 CPU (2.60GHz), 256G RAM and Nvidia GeForce RTX 2080 Ti.Table 1, we noted that our approach outperforms the best previous method by 1.53/1.74 accuracy points on the test/val. As compared to the STAGE, we noted the performance is substantially improved. Considering that there are 15,253 and 7,623 validation and test questions, this establishes the strength of our task. We can see that, our model outperforms the baseline models by a large margin. In particular, the scores of our model across all the TV shows are more balanced than the scores from other models, which mean our model is more consistent and robust.From We believe the reasons behind the performance boost are the following:Compared with LSTM-based models , BERT-based models (STAGE and MAF-HMS) enable capturing longer dependencies between and within different modalities, especially when there is a long subtitle.Our approach can properly integrate input features from different modalities to help answer questions.Hybrid multi-head self-attention can more fully consider the contribution of each modality, and fusion of multi-head results can make the model extract more important features more accurately and improve the performance of our model.Fig 4, we compare our MAF-HMS with Two-stream, PAMN, Multi-task and STAGE on MSVD-QA dataset. Our MAF-HMS achieves the most promising performance in overall accuracy, which demonstrates the superiority of the proposed method on the non-trivial scenarios.Results on MSVD-QA and MSRVTT-QA. As is shown in The MSVD-QA and MSRVTT-QA datasets represent highly challenging benchmarks for machine compared to the TVQA, thanks to their open-ended nature. Our MAF-HMS model outperforms existing methods on both datasets, achieving 36.82% and 35.26% accuracy which are 2.67 points and 0.22 points improvement on MSVD-QA and MSRVTT-QA, respectively. This suggests that the model can handle both small and large datasets better than existing methods.Table 2, we have the following observations.For further analysis, our model shows substantial improvement over the baseline, we evaluated our models with different variants. In these experiments, we choose the same train-and-test setting. From Table 2, we summarize the ablation analysis of MAF-HMS on TVQA dataset in order to measure the validity of the key components of MAF-HMS. Using BERT for contextual word embeddings significantly improves performance comparing to GloVe embedding and LSTM counterpart.We design a simpler model with GloVe and LSTM for text representation. As is shown in To measure to effectiveness of all components, we evaluate the following settings:MAF-HMS w/o HMS. Remove the hybrid multi-head self-attention unit in the MAF-HMS.MAF-MS. To verify the validity of hybrid multi-head attention unit, we employ the standard multi-head attention as a substitute.MAF-HMS w/o MAF. To measure to effectiveness of MAF component, MAF-HMS w/o MAF underperforms MAF-HMS, which shows that the modality attention fusion framework is important in understanding video questions.MAF-HMS w/ VTF. We use VTF  instead of MAF.MAF-HMS w/ DMF. DMF  is the modal fusion mechanism of PAMN.MAF-HMS w/ JMCQ. JMCQ (Video-Text Fusion) is the modal fusion mechanism of Two-stream.The three “w/” variants have little performance improvement compared to MAF-HMS w/o MAF, and our MAF-HMS has increased by 3.96 points. Thus, MAF component contribution is huge. Finally, we compare our method with two simple variants that drop the HMS and replace the HMS with a standard multi-headed self-attentive unit to show the contribution of our hybrid multi-head self-attention unit. Without HMS, we find out that the performance of our MAF-HMS model decreases by 1.08 points on TVQA dataset. We adopt the multi-headed self-attentive to replace the HMS, the result demonstrates the positive role of HMS.In this section, we provide analysis the qualitative examples of TVQA benchmark solved by MAF-HMS. We selected a few successful and unsuccessful prediction samples from TVQA dataset. Following, we list some of these observations.For example, the utterance “How did you come to work today” is very important to answer the question, information from neighboring utterances, e.g., “By bus” is the key message to answer the question. All this information is contained in a single modality and is easy to capture, whether it is baselines or our model. Such contextual relationships are prevalent throughout the TVQA dataset. In addition, these are difficult to find the answer information from the subtitles. If there is a lack of key information in the subtitles, such as the question, "what did he hand her", if the context dependence is not obvious in the subtitles, we can find the answer from the video features, e.g., "A man’s hand holding a hamburger". There are strongly related entities in the visual features, our method will give correct predictions based on these fusion features.We further investigate the performance of MAF-HMS by comparing with STAGE on TVQA dataset. For example, the question “Where did she go after she confessed to him”, there are strongly related entities in the visual features, and the answer can be found from the visual modalities, both MAF-HMS and STAGE obtain accurate prediction for such questions. However, in another question “what did he hand her”, there is some disturbing information with confusion. We can find the wrong answer "diaper bag" from the subtitle "well, this is his diaper bag", and find the correct answer "hamburger" in the video representation, there are strongly related entities in the question features. Other answers can be found in subtitles and video representations, and our model can more accurately eliminate interference options and find the answer directly from the subtitles with understanding the semantics of the question better.Finally, we show two failure cases. For example, in the question “Who tells Anton that he has quite the temper when interrogating him in the interrogation room?” and the answer is the names of 5 characters, character’s face which is very challenging to capture using the visual concepts extracted by Faster R-CNN. MAF-HMS fails to predict the correct answer as the visual concept features are insufficient in capturing textual cues in the video. Furthermore, in another question “Who is sitting at the computer when the group is talking”, our model is difficult to find the action concept features associated with the question and answer from the subtitles and visual features, so we predict failure. When the answer is not explicit in the video frames or the subtitles, our method gives an incorrect prediction, however our MAF-HMS still achieves outstanding results.From these examples, we can see that our model is able to solve both visual and language modalities multiple-choice questions.In this section, we evaluate the proposed model with different question types on TVQA dataset.Fig 5 exhibits the performance comparison by 5W1H  question type between Two-stream, PAMN, Multi-task, STAGE and MAF-HMS on the validation set of TVQA benchmark.This section describes the analysis of MAF-HMS by comparing the accuracy with respect to question type. The For fair comparison with existing methods, we tried to reproduce the results on Two-stream, PAMN, Multi-task and STAGE. Notwithstanding the effect achieved on “who” question is not satisfactory, MAF-HMS obtains an average of 72.19% accuracy for the majority of question types, significantly higher than other baselines. Especially, reached 81.93% accuracy performance on “when” question. The reason is that “when” type sentences contain more interactions and inferences between video representation and text representation, and our model can further integrate patterns with BERT and Faster R-CNN to answer multiple choice questions more effectively. The results confirm that our approach shows additional benefit in mining the modal relations between text and video representation, which implies the superiority of MAF-HMS to help infer the correct answer.To investigate whether MAF-HMS is sensitive to the modality entities, we provide the analysis of MAF-HMS by the required modality for all datasets. For comparison purpose, we also designed three types of labels according to which modality is required for answering prediction.V. There are only strongly related entities in the visual features.S. There are only strongly related entities in the subtitle features.V&S. There are strongly related entities in the visual features and subtitle features.Fig 6, we have manually labeled 3000 (1000 per each type) examples for each dataset.As is shown in It can be seen that require subtitle and video modalities for answer prediction  achieves the highest accuracy score among all datasets, label V has the lowest accuracy score. It means that effectively fusing multi-modal information can strengthen the model’s ability to understand video, and achieving the impressive performance on multi-modal tasks.In this work, we presented the MAF-HMS model for Video-QA tasks. We use a modality attention fusion framework that combines visual and subtitles representation features to capture the semantics more accurately. We process video and subtitle features with two independent BERT layers, and use BERT to combine visual conceptual features and subtitles and questions with each candidate answer for embedding. These input features use modal attention fusion and a hybrid multi-head self-attention mechanism to obtain the final answer prediction.Experiments were conducted to test the performance of our model. Results show that our model gave correct predictions from the language and visual representations on TVQA dataset. In our experiments, the MAF-HMS was evaluated on multiple Video QA datasets, especially, has achieved a test accuracy rate of 72.21% on TVQA dataset. Although the MSVD-QA and MSRVTT-QA datasets are much more challenging and open-ended nature, we are still able to achieve 36.82% and 35.26% accuracy which are 2.67 points and 0.22 points improvement on MSVD-QA and MSRVTT-QA. In addition, we perform an ablation study and analysis to clarify the strengths of our model, demonstrate the effectiveness of our model in Video-QA. Finally, experimental results demonstrate the effectiveness of our method in question type and required modality tasks.S1 Dataset(ZIP)Click here for additional data file.


Interdisciplinary collaboration between healthcare providers with regard to consultation, transfer and advice in terminal care is both important and challenging. The use of video communication in terminal care is low while in first-line healthcare it has the potential to improve quality of care, as it allows healthcare providers to assess the clinical situation in real time and determine collectively what care is needed. The aim of the present study is to explore the intention to use video communication by healthcare providers in interprofessional terminal care and predictors herein.In this cross-sectional study, an online survey was used to explore the intention to use video communication. The survey was sent to first-line healthcare providers involved in terminal care  and consisted of 39 questions regarding demographics, experience with video communication and constructs of intention to use  based on the Unified Theory of Acceptance and Use of Technology and Diffusion of Innovation Theory. Descriptive statistics were used to analyze demographics and experiences with video communication. A multiple linear regression analysis was performed to give insight in the intention to use video communication and predictors herein.Mean (M) = 3.6; Standard Deviation (SD) = .88). The regression model was significant  and explained 44% of the variance in intention to use video communication, with ‘Outcome expectancy’  and ‘Social influence’  as significant predictors.90 respondents were included in the analysis.65 (72%) respondents had experience with video communication within their profession, although only 15 respondents (17%) used it in terminal care. In general, healthcare providers intended to use video communication in terminal care (Healthcare providers have in general the intention to use video communication in interprofessional terminal care. However, their actual use in terminal care is low. ‘Outcome expectancy’ and ‘Social influence’ seem to be important predictors for intention to use video communication. This implicates the importance of informing healthcare providers, and their colleagues and significant others, about the usefulness and efficiency of video communication.The online version contains supplementary material available at 10.1186/s12904-022-01100-5. Paliative care is provided to improve quality of life of patients who are diagnosed with an incurable and progressive illness, from which they will die within days up to several years. Palliative care includes disease and symptom oriented care, care in the dying phase, as well as bereavement and support of the family after death of the patient –3. TermiIn the Netherlands, 72.7% of the patients who died at home received intensive care in the last 2 weeks of their life, i.e. additional care by general practitioners . The genVideo communication has the potential to support collaboration between healthcare providers and patients in a simpler, faster and more efficient way . ResearcHowever, healthcare providers have mixed feelings about the use of video communication as difficulties are seen in the number of connection problems that cause interruptions in the conversation, and the inability in comforting the patient when talking about sensitive topics , 20. Als“What is the intention of healthcare providers to use video communication in interprofessional terminal care and which predictors influence this intention?”. It is expected that some of the healthcare providers do already use video communication within their work as healthcare provider (users) and some do not (non-users). A secondary research question is what the differences are between these two groups regarding intention to use and predictors herein.Implementation of video communication in terminal care may be accelerated if more is known about the relationship between intention to use video communication in terminal care and predictors herein. The Unified Theory of Acceptance and Use of Technology (UTAUT) is a widely recognized theoretical model describing predicting factors for intention to use of technology . In addiA cross-sectional study was performed among first-line healthcare providers working in The Netherlands for investigating the intention to use video communication in interprofessional terminal care and predictors herein, and what the differences are between ‘users’ and ‘non-users’.An online survey  was set up and distributed via an anonymous link from October till December 2020. Participants were eligible if they worked in first-line healthcare , i.e. care at home, hospices or nursing homes . ParticiDo you have experience with video communication in your work as healthcare provider (yes/no)?’. If so, follow-up questions were displayed regarding experience with different applications and functions. The second part ended with the question ‘Do you use video communication also in terminal care (yes/no)?’. The third part consisted of 31 items on constructs about intention to use video communication based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and Diffusion of Innovation theory (DOI) [The survey consisted of 39 questions divided into three parts: 1) demographic characteristics, 2) experience with video communication within the work as healthcare provider, 3) constructs about intention to use video communication within terminal care. The survey started with an information letter and consent form, followed by four questions about demographics. The second part started with the question: ‘ry (DOI) , 27. Forn = 3), Outcome expectancy (n = 3), Effort expectancy (n = 4), Attitude (n = 4), Social influence (n = 3), Facilitating conditions (n = 4), Anxiety (n = 3) and Self-efficacy (n = 3). Another validated construct about Personal innovativeness (4 items) based on DOI was added [For the correct completion of items in the third part, respondents were asked to consider their experience with video communication in the terminal care in the past 6 months, and if they had no experience with this, to fill out the items based on their own expectations about the use of it in the upcoming 6 months. The constructs included based on the UTAUT were: Intention to use . However, no other items were excluded as Cronbach’s alpha did not increase sufficiently. In addition, all constructs were kept in the analysis as these were based on validated questionnaires , 30.Descriptive analysis of the demographics  included calculation of frequencies, percentages, means (M) and standard deviation (SD) Table . In visup < .05). If the Levene’s test for equality of variance was significant (p < .05) the Welch t-test was used. The Mann-Whitney U test was used instead of a t-test if the mean construct score was not normally distributed within each group.Mean construct scores of ‘Intention to use’ and predictors were calculated based on the individual item scores and ranged between 1 and 5. A higher score on the construct ‘Intention to use’ was indicative for an higher intention to use video communication, with a middle score of 3 indicative for a neutral/ inconclusive score. A higher score on a predictor was indicative of a more positive relationship with intention to use video communication, with also a middle score of 3 indicative for a neutral/ inconclusive score. The exemption was the predictor “anxiety”, for which a higher score was indicative for less anxiety, with a middle score of 3 indicative for a neutral score. Differences in mean construct scores between users and non-users were analyzed using an independent t-test (p < .05). The correlation coefficients were interpreted as follows: <.30 as very low correlation; ≥.30 and < .50 as low correlation; ≥.50 and < .70 as moderate correlation; >.70 as high correlation.Pearson correlation coefficients were used to analyze the strength of the bivariate correlation between ‘Intention to use’ and predictors  in the regression analysis was relatively low and the dependent variable ‘Intention to use’ was not normally distributed . The F-ratio was used for interpreting the significance (p < .05) of the adjusted R2. The Beta’s of the standardized coefficients were used for interpreting the contribution of each possible predictor in the model. Significance of each Beta was tested with a t-test (p < .10). The data were analyzed using SPSS, version 24.0 .A multiple linear regression analysis was performed to predict ‘Intention to use’ as the dependent variable (outcome), and the predictors as independent variables. A check on assumptions was performed for normal distribution of standardized residuals, and for linearity-, homoscedasticity- and multicollinearity of the regression model. All predictors were added (‘Enter’ method) because the model was theoretically substantiated. The ‘adjusted RThis study was not subject to Medical Research Involving Human Subjects Act, as healthcare professionals were not asked to act or to change behaviors and the questions were not of a drastic nature –34.In total 146 respondents started with the survey, of which 90 respondents were included in the data-analysis , occupational therapist (n = 1) and rehabilitation doctor (n = 1).The characteristics of the respondents are shown in table M = 42.7; SD = 12.2) and non-users  was significant (p < .01). No other significant differences were found between users and non-users. 15 (17%) respondents had also experience with video communication in terminal care.65 (72%) respondents had experience with video communication in their work as healthcare provider (users) and 25 not (non-users). All volunteers were classified as non-users, as they indicated not to use video communication in their work as healthcare provider. The difference in mean (M) age between users of video communication (n = 65) the most frequent mentioned applications for video communication were Microsoft Teams (n = 46), Zoom (n = 33), WhatsApp (n = 26) and Skype (n = 11). Healthcare providers used video communication for group communication (n = 58), one-to-one communication (n = 54), video communication via smartphones (n = 32), chat function (n = 20), looking at a file together (n = 19) and saving and sharing files (n = 15).Among users (Approximately 65% of the respondents ‘(strongly) agreed’ towards the items related to ‘Intention to use’  for users experienced with video communication in their work as healthcare provider  vs. non-users . The scores for predictors for intention to use indicated that most respondents (strongly) agreed with items related to ‘Effort expectancy’  and ‘Facilitating conditions’ , and (strongly) disagreed with items related to ‘Anxiety’ . The scores on items belonging to other predictors  were less conclusive with a substantial number of neutral scores at individual items and mean construct scores close to 3. The mean construct scores for ‘Social influence’, ‘Facilitating conditions’, ‘Anxiety’ and ‘Personal innovativeness’ were significantly higher for users experienced with video communication in their work as healthcare provider vs. non-users . Contrary, users scored significant lower for ‘Self-efficacy’ (p < .01).The mean construct score table  for ‘IntIn table 2 of the multiple linear regression analysis was .442 , meaning that all potential predictors together predicted 44% of the variation in the intention to use video communication. In table The adjusted RThis study showed that the majority of healthcare providers have the intention to use video communication in the first-line terminal care, especially healthcare providers who have experience with video communication. ‘Outcome expectancy’ and ‘Social influence’ are significant predictors for intention to use video communication in terminal care. This means that the usefulness and efficiency of video communication in terminal care-, and the influence of colleagues and significant others-, are important predicting aspects for healthcare providers to actually use video communication in terminal care. These findings are in line with another study about the implementation of video communication in home-based palliative care . Other sMost of the healthcare providers 72%) have already used video communication in their profession. However, the use of video communication in interprofessional terminal care is still relatively low (17%). This is especially true for volunteers, as none of them had already experience with video communication within their work as healthcare provider. However, even excluding volunteers, only 19% of healthcare professionals have experience with video communication in terminal care. This is striking as in other studies healthcare providers have indicated that they do see value in the use of video communication in terminal care as it is more time efficient, it can help to get a better assessment of a patient’s situation and it can improve interprofessional communication , 25, 36.2% have aBased on this study, in the implementation of video communication special attention should be paid towards current non-users of video communication. This sub group scored significant lower at intention to use video communication and at several predictors hereof . This is in accordance with another study in which healthcare providers experienced in the use of information and communication technology (like video communication) were more inclined to use it in diabetes management . In thisOther important aspects in the implementation of video communication for interprofessional collaboration seem to be differences in profession and experience in working with technology. For instance, volunteers did not have any experience with video communication in their work as healthcare provider while most of the healthcare providers from other professions did so. Hence, in the implementation of video communication for interprofessional collaboration in terminal care it is important that factors related to the heterogeneity of healthcare providers are taken into account.The strength of this study is the theoretical underpinning of the model used to predict intention to use video communication. 44% of the variation in the regression model for ‘Intention to use’ is predicted by the included factors. Maybe one or more variables are overlooked, like variables related to data security and ethical concerns as these aspects were not explicitly scored in this study but seen as part of the construct ‘Facilitating conditions’ . BesidesHealthcare providers have the intention to use video communication in terminal care, however actual use was low. In this study, outcome expectancy was an important predictor of intention to use video communication, which underlines the importance of informing healthcare providers about the usefulness and efficiency of video communication. Social influence was also a significant predictor, indicating that support by colleagues and significant others is important as well. Healthcare providers without experience with video communication within their work as healthcare provider had a significant lower intention to use video communication in terminal care. Therefore, it is recommended to pay special attention towards these inexperienced healthcare providers when implementing video communication for interprofessional collaboration in terminal care.Additional file 1:Appendix 1. Results part 3 of the survey


Brugia malayidue to the activation of TRP-2. Here we show that DEC causes transient paralysis inC. elegans at high concentrations and is 200x less potent compared to its effect onB. malayi.C. elegans trp-2(sy691) mutants are like the wild-type and only paralyzed by high concentrations of DEC. Our results demonstrate that high concentrations of DEC cause paralysis ofC. elegans independent of TRP-2.Diethylcarbamazine (DEC) has been used to treat lymphatic filariasis in tropical countries since the 1940s. Its mode of action is still unclear, with several reports suggesting a host immune system-mediated mechanism. We previously demonstrated that DEC causes transient spastic paralysis in the filarial nematode The direct effect of DEC on the whole worms was first reported in filariaB. malayi . Low (4µM) concentrations of DEC caused transient spastic paralysis due to muscle contraction in both male and female worms . Electrophysiological, genetic, and behavioral assays revealed DEC acts by targeting the TRP channels, TRP-2 in the muscle cells ofB. malayi .Diethylcarbamazine (DEC) is a classic anthelmintic used to treat diseases caused by filarial nematodes like lymphatic filariasis and loiasis. DEC is very effective in clearing the microfilaria from the blood, but the therapeutic effects are transient as the microfilariae return in the blood after a few hours (Hawking and Laurie 1949). The mode of action of DEC has not been well understood, and many reports suggest that DEC acts by stimulating the host immune system . DEC causes rapid, concentration-dependent paralysis that persists for a few hours before the worms recover. The IC50for the paralyzing effect of DEC at 30s post-treatment was 4.4±0.3mM. For this study, we first treated wild-type N2 worms with different concentrations of DEC and found that DEC was only effective at high concentrations . DEC causes transient, flaccid paralysis , and the worms start to recover 40 minutes post-treatment of 3mM DEC . We plotted the concentration-response plot for the DEC-induced paralysis 30s post-treatment and found the IC50to be 0.8±0.2mM .C. eleganshave a thicker cuticle , preventing the entry of the drug and thereby limiting its effects. We used abus-12(e2740) that has a fragile cuticle  and found DEC had similar effects compared to the N2 . The IC50forbus-12was 0.5±0.04mM, indistinguishable from N2, indicating DEC passes through the cuticle, and its lack of potency may be due to reduced effect on its target receptor.We have previously reported that DEC has paralyzing effects on the filarial nematodeB. malayi, current responses to DEC are abolished when the TRPC gene trp-2is knocked down , indicating that TRP-2 could be the putative target for DEC. TheC. elegans genome encodes for three TRPC genes,trp-1,trp-2, andspe-41,whereas the parasitic worm genomes encodetrp-2 andspe-41. SPE-41 is enriched in the male sperm head  and may not play a role in DEC-mediated paralysis. Phylogenetic analysis in parasite wormbase (www.parasite.wormbase.org) suggests thatC. elegans'TRP-2 is the closest ortholog to the filarial TRP-2s and is present in a different node to TRP-1. To test if DEC acts through TRP-2 inC. elegans, we usedtrp-2(sy691), a null allele , and assayed the effects of DEC on motility. We observed that DEC caused transient paralysis in thetrp-2mutants similar to the N2 strains with an IC50of 0.4±0.1mM Fig 1G and H). Our results suggest that, unlike filaria, TRP-2 might not be the putative target for higher concentrations of DEC in the free-living nematodeC. elegans.InC. elegans at higher concentrations independent of TRP-2. TRP-2 is expressed in the body wall muscle ofB. malayi and not inC. elegans,where it is expressed neuronally . According to Wormbase, most of the TRP channels inC. elegansare expressed neuronally or in the intestine. The DEC activation of TRP channels in these tissues might not be sufficient to cause potent paralysis. Also, DEC might be targeting a different TRP channel in the muscle cells ofC. eleganswith a lower potency. Our results suggest DEC has a parasite-specific effect in paralyzing the worm, and it causes transient paralysis at very high concentrations inC. elegans, independent of its putative parasitic target TRP-2.Our results demonstrate that DEC causes transient paralysis inStrains:bus-12(e2977),andtrp-2(sy691), were obtained from the Caenorhabditis Genetic Centre . AllC. eleganshermaphrodites were maintained on 60mm Petri dishes containing standard NGM, spread with E. coli OP50 as food stored at 20ºC. Well-fed, motile young adult worms, approximately three days after hatching, were used in all experiments.Strains used in this study, Wild-type (Bristol N2),Drugs:Diethylcarbamazine citrate  used in this study was obtained from Sigma Aldrich . 100mM stock DEC was prepared by dissolving in distilled water and stored at -20°C.Motility assays:C. eleganswere treated with various concentrations of DEC . Worm motility was recorded for 30s before the addition of DEC, 30s following the addition of DEC and at 2, 40, and 120-min post-treatment to generate a concentration- and time-course response analysis. Motility was recorded for 30s for all time points.Motility assays were performed on young adult hermaphrodites. Fifteen worms from each strain were transferred to a 96 well plate (1 worm/well) containing RPMI media at a final volume of 200µL. After allowing 20 min for acclimatization, DEC was added and video recordings were performed using WormLab software with a purpose-built illumination stand (MBF Bioscience) equipped with a Nikon 60 mm Microlens  and an AVT Stingray F-504B digital camera . Videos were captured at 7.5 frames per second and saved as AVI files. To determine the potency of DEC on young adult hermaphrodite,Data Analysis and Statistics:Caenorhabditis elegansto determine the average speed of the 45 individual worms (n=15 per strain). Wormlab analyzed, frame by frame, the detected changes in movement to track the total length of forward and reverse movement in micrometers and the average speed of the worm in micrometers per second (μm/s). The data were analyzed using GraphPad Prism 5.0 software .We used WormLab software  to track and analyze the recorded videos of the


FSTL1 showed a significantly higher expression in AVM ECs than in normal ECs. Under hypoxia, CSPG4 expression was significantly lower in AVM ECs than in normal ECs. Accordingly, the angiogenic effect was increased in AVM ECs compared with that in normal ECs. These results provide a basic knowledge for an AVM treatment strategy.Arteriovenous malformation (AVM) is characterized by high-flow blood vessels connecting arteries and veins without capillaries. This disease shows increased angiogenesis and a pathophysiological hypoxic environment in proximal tissues. Here, we analyzed the effects of hypoxia on angiogenesis in the endothelial cells (ECs) of AVM and normal tissues. ECs from human normal and AVM tissues were evaluated using immunocytochemistry with CD31. In vitro tube formation under hypoxia was tested in both ECs using Matrigel. The relative expression of angiogenesis-related genes was measured using real-time PCR. Under normoxia, CD31 was significantly higher in AVM ECs (79.23 ± 0.65%) than in normal ECs (74.15 ± 0.70%). Similar results were observed under hypoxia in AVM ECs (63.85 ± 1.84%) and normal ECs (60.52 ± 0.51%). In the tube formation test under normoxic and hypoxic conditions, the junction count and total vessel length were significantly greater in AVM ECs than normal ECs. Under both normoxia and hypoxia, the angiogenesis-related gene  Arteriovenous malformation (AVM) is a rare disease characterized by arteries that are directly connected to draining veins with a high flow rate, without an intervening capillary network. Arteriovenous shunting without an intervening capillary network leads to the formation of an abnormal vascular network around the nidus as new blood vessels are formed. Extracranial AVM can be caused by various factors such as hormonal changes, infections, and trauma, and can occur in any body part . AlthougAVM is pathophysiologically related to angiogenesis, which may be due to hypoxia or ischemia conditions. Although the exact cause is unknown, AVM has the pathologic shunt congenitally. As AVM progresses, high-pressure arterial blood is directly shunted into low-pressure veins, dilating the vessels and recruiting new blood vessels. Such continued stimulation increases the risk of hemorrhage and bleeding, deteriorated flow can cause blood steal phenomena, and the circulation of high-flow blood creates a relatively hypoxic environment in the proximal tissues at the AVM site. Patients with AVM often have a high hemorrhage risk and may require several surgeries along with embolization and sclerotherapy ,3,4.Anti-angiogenic drugs such as vascular endothelial growth factor (VEGF) blockers are also used to prevent the vicious cycle of regeneration by stimulating angiogenesis, as various dynamic entities occur during AVM treatment. Rapamycin, which is the mammalian target of the rapamycin (mTOR) inhibitor and also known as sirolimus, is used for AVM treatment, and trametinib, the MEK1 inhibitor, receives attention as AVM treatment nowadays. Aside from this, non-steroid anti-inflammatory drugs, analgesics, and low molecular weight heparin are used as the treatment of AVM patients. ,11,12,13To understand and treat AVM, its mechanism and physiopathology should be evaluated, and the related genes should be analyzed to develop therapeutic strategies. In this study, we investigated the effects of hypoxia on endothelial cells (ECs) from AVM tissues and assessed the expression of related genes.Immunocytochemical fluorescence tests were performed on ECs that were isolated and cultured from human normal and AVM tissues. A green color was observed on the cell membrane, indicating CD31-positive staining. These results confirmed that the cultured and isolated cells were ECs .The comparison of CD31 expression in normal ECs and AVM ECs was assessed using immunofluorescence microscopic image analysis after incubation under each condition (normoxia and hypoxia) for 14 h. Under normoxia, CD31 immunoreactivity was found in 79.23 (±0.65%) of the area in AVM ECs, which was greater than that in normal ECs (74.15 ± 0.70%). Similarly, under hypoxia, CD31 immunoreactivity was found in 63.85 (±1.84%) of the area in AVM ECs, which was significantly higher than that in normal ECs , suggesting that angiogenesis is more active in AVM ECs .p < 0.05). Similarly, under hypoxia, the number of junctions and the total vessel length increased significantly in AVM ECs compared to those in normal ECs (p < 0.05). Additionally, both normal and AVM ECs showed a significantly increased number of junctions and total vessel lengths under hypoxia than under normoxia  (data was not shown), were measured using real-time PCR. Under both normoxia and hypoxia, FSTL1 expression was significantly higher in AVMs than in normal tissues. Under hypoxia, FSTL1 expression was significantly increased in the ECs of both AVM and normal tissues. CSPG4 expression was significantly lower in AVM ECs than in normal ECs under normoxia, because the capillary network was absent in AVM. In particular, under hypoxia, CSPG4 expression decreased significantly in AVM ECs compared to that in normal ECs. MARCKS expression was lower in AVM ECs than that in normal ECs under both normoxia and hypoxia. Although there was no marked difference in the expression levels of MARCKS between normoxia and hypoxia, MARCKS expression was significantly decreased in normal ECs and AVM ECs  [This study was approved by the Institutional Review Board of Kyungpook National University Hospital  and was performed in accordance with the Helsinki Declaration. Ten patients (five with and five without AVM) were enrolled in this study. After obtaining patient consent, AVM tissues were collected during surgical resection of AVM lesions and normal arterial vasculature tissues were collected during other surgeries from discarded normal subcutaneous tissues, including normal arterial vasculature. Surgical samples were rinsed with phosphate-buffered saline. Tissues were cut into small pieces using a surgical scalpel and scissors. To separate the epidermis and dermis, tissues were incubated in 0.01% dispase II  for 24 h at 4 °C. After incubation, the dermal layer was collected and placed in 10 mL of Hank’s balanced salt solution . The supernatant was removed, 5 mL of collagenase type I was added, and the samples were incubated at 37 °C and 170 bpm in a shaking incubator for 1 h. Endothelial cell growth basal medium-2 medium  was added, and the sample was passed through a 70 μm nylon filter. After centrifugation , ECs were grown in EMB-2 medium and incubated at 37 °C with an oxygen level that was the same as that in air and 5% COGermany) .2 and 5% CO2 at 37 °C. To establish hypoxic partial pressure, a hypoxia chamber  was used. Cultured ECs were exposed to hypoxic conditions for 14 h.Hypoxic conditions used in the experiments consisted of 1% O® 488 A-11008; Invitrogen, Carlsbad, CA, USA, 1:100), was added and incubated for 1 h. After washing with Tween-20 three times for 10 min each, Vectashield (H-1200 with DAPI) was added to the slide, and the slides were covered. Cells were evaluated using a fluorescence microscope . CD31 expression was quantified by measuring the percentage area of immunoreactivity using the ImageJ software .For staining, cells were cultured in an eight-well chamber. When the cells reached approximately 70–80% confluence, they were fixed in 4% formaldehyde for 24 h, immersed in 0.3% Triton-X100 in Tris-buffered saline for 10 min, and rinsed three times with deionized water for 1 min. Ten drops of blocking buffer immunotech-normal serum were added to each well and allowed to react for 5 min. After removing the serum, the primary antibody, CD31 , was added to the wells and incubated at 4 °C for 24 h. After washing three times, the secondary antibody, goat anti-rabbit IgG H&L . Angiogenesis was detected using photographs of blood vessels and anchorage junctions using AngioTool64 software  [To analyze angiogenesis, 50 μL of each ice-state extracellular matrix solution  was added to a 96-well plate and incubated at 37 °C for 1 h to form a gel. ECs were added at a density of 1 × 10MD, USA) .Real-time PCR was performed to analyze gene expression in the cells after exposure to hypoxic conditions. First, RNA was extracted from each group using TRIzol and reverse-transcribed into cDNA using a reverse transcription premix . Reactions were performed using SYBR Green PCR Master Mix  in a real-time PCR detection system . GAPDH was quantified in parallel, with the target gene as an internal control. Normalization and fold-changes were calculated using the Ct method .p < 0.05.Data are presented as the mean ± standard deviation of all experimental replicates. One-way ANOVA was used for multiple comparisons in experiments with one independent variable in Excel . Statistical significance was set at FSTL1 expression was significantly increased in AVM, whereas CSPG4 showed a relatively lower increase under hypoxic stimulation because of structural abnormalities in AVM. MARCKS appears to be associated with angiogenesis but not AVM. Further studies are needed to improve the treatment strategies.Angiogenesis is increased in AVM, which is difficult to treat and is characterized by direct shunting from the arteries to the veins with a fast and high-pressure flow.