People with gestational diabetes have enhanced learning requirements during pregnancy, and management of their disease often requires the translation of health information into new health behavior changes. Seeking information from the internet to augment learning from health professionals is becoming more common during pregnancy. YouTube is a popular free and accessible web-based resource, which may be particularly useful for individuals with low health literacy or other barriers to receiving high-quality health care; however, the quality and content of YouTube videos varies, and little is known about those covering gestational diabetes.We aimed to systematically evaluate the quality, content, and reliability of YouTube videos about gestational diabetes.A systematic search of YouTube videos was conducted over the course of 1 week in April 2020 using the following keywords: “gestational diabetes,” “gestational diabetes management,” “gestational diabetes treatment,” and “pregnancy and diabetes.” The search results were displayed by relevance, replicating a default YouTube search attempt. The first 60 results from each keyword were reviewed (n=240). Exclusion criteria were videos unrelated to gestational diabetes, videos not in English, and those for which the full video was not available at the time of review. For each unique video, a gestational diabetes content score was used to rate video comprehensiveness and accuracy, and the DISCERN instrument, a validated metric to assess consumer health information, was used to evaluate the reliability of information presented. Videos were further categorized by quality: videos with DISCERN scores lower than 3 (out of 5) or a content score less than 4 (out of 7) were categorized as low quality, and all others were designated high quality. We performed descriptive analysis and compared video characteristics by source and quality rating.P<.001); high- and low-quality videos otherwise had similar views and viewer interaction numbers.For 115 unique videos, the mean content score (out of 7) was 3.5 (SD 2.0) , and the mean DISCERN score (out of 5) was 2.7 (SD 0.7), representing low to moderate information comprehensiveness and reliability respectively. Video sources were categorized as personal vlog , web-based education , medical , business or company , and media clip . DISCERN and content scores trended higher among medical and web-based education videos. The majority of videos (n=88) were categorized as low quality, while 27 videos were categorized as high quality. Video duration was longer for high-quality videos (Although high-quality videos about gestational diabetes exist, reliability, accuracy, and comprehensiveness were low overall, and higher quality was not associated with increased viewer interaction. It is important to acknowledge the limitations of this platform and to assist patients in accessing high quality content and differentiating the quality of information sources. Gestational diabetes is one of the most common complications of pregnancy. Untreated or undertreated gestational diabetes is associated with perinatal and maternal complications, including preeclampsia, macrosomia, neonatal hypoglycemia, and maternal risk of developing type 2 diabetes . BecauseThe internet is a widely available, increasingly accessed resource for health information, and it is a common source of information for pregnancy-related health concerns ,12. MultGiven the emerging role of web-based platforms—including YouTube—as health information resources, and the importance of optimizing health care information and interventions for individuals with gestational diabetes, it is important to learn more about the content and quality of resources about gestational diabetes that are available on YouTube. Restrictions on access to care , limitedWe systematically reviewed YouTube content on gestational diabetes on April 30, 2020. Search terms were identified in consultation with 2 perinatal diabetes care specialists (CN and LY), and Google Trends was used to identify top searches associated with gestational diabetes. The search was then conducted on a cache-cleared web browser using incognito mode with the following terms: “gestational diabetes,” “gestational diabetes management,” “gestational diabetes treatment,” and “pregnancy and diabetes.” The search was conducted via public access—a registered account was not used.Search results were displayed by relevance, which is the default search setting. The first 60 results—representing the first 3 pages of results—from each keyword search were reviewed and analyzed. The sample size and sort strategy were selected based on research indicating that the majority of internet searchers view only 1 page of results, and 83% of searchers view no more than 3 pages . Duplicacharacter video, which was defined as a video in which a specific, identifiable person was presenting. Video source was determined based on the affiliation of each video’s author when available , or the channel description and theme .Descriptive characteristics of each video were collected, including video length, number of comments, channel number of subscribers, number of views, number of likes, and number of dislikes. Collection of this information was completed by 1 reviewer (EB), over the course of 1 week  to minimize variability in number of views and other characteristics collected. Source characteristics were also gathered from each video. These included the video source and whether the video was a Criteria to judge video content were formulated from American College of Obstetricians and Gynecologists recommendations for management of gestational diabetes, and in consultation with perinatal diabetes care specialists (CN and LY). Video comprehensiveness and accuracy of information provided about (1) screening or testing guidelines; (2) treatment for gestational diabetes self-management; (3) nutrition information; (4) information about the purpose of gestational diabetes treatment and benefits; (5) blood glucose level monitoring guidelines; (6) gestational diabetes effects on long-term maternal health; and (7) gestational diabetes effects on the fetus. These topics were selected because they represent key foundational knowledge regarding gestational diabetes that is essential for participants to understand their condition, participate in self-monitoring and management, and engage in health care to prevent adverse perinatal outcomes. To evaluate videos, we used a content score—1 point for each content area addressed accurately in the video ; thus, a maximum score of 7 was possible if a video covered the comprehensive range of topics about gestational diabetes accurately. Similar assessments have been performed in prior evaluations of YouTube videos as a health information source -36.The DISCERN instrument  was usedA combination of both scoring techniques was used to divide videos into high- and low-quality categories. Videos with a mean DISCERN score less than 3 or a content score less than 4 were defined as low quality; otherwise, videos were defined as high quality. These quality cutoffs were chosen because they correspond to a DISCERN rating representing potentially important shortcomings or an inclusion of fewer than half of the expert-developed content topics, respectively, both of which affect the overall quality of the video as a reliable comprehensive source of information.After determining evaluation criteria, 2 videos were assessed collaboratively by 3 reviewers  to establish consensus on the application of these criteria and scoring. Subsequently, these 3 reviewers independently evaluated the same 15 randomly selected videos for content and reliability. The remaining videos were then divided evenly among the reviewers, and each was evaluated using the established standardized criteria. Data for each video were collected and stored using REDCap (Vanderbilt University) software.P value<.05 was considered significant.Statistical analyses were performed using Excel software . Interrater agreement was analyzed using intraclass correlation coefficients and single-factor analysis of variance. Descriptive statistics were used to evaluate study data. Frequencies were used to describe categorical variables; normally distributed continuous variables were presented as means, and nonnormally distributed variables as medians. The Kruskal-Wallis test for intergroup comparison, Spearman rank correlation, and Wilcoxon rank-sum test were used for analysis involving nonnormally distributed continuous variables. A This study was deemed exempt from review by the Northwestern University institutional review board because it does not involve human participants.The mean scoring disparity for the 15 videos was 0.27 (for DISCERN), and correlation was 88% (intraclass correlation 0.81), indicating a high level of interrater agreement. Of the 240 videos initially identified, 109 were duplicates, 3 were in a language other than English , 2 with full videos unavailable at the time of data recording, and 11 had a primary topic that was not gestational diabetes. After applying exclusion criteria, 115 videos remained for analysis . Video cP<.001) and topic score (P<.001).DISCERN scores  ranged fP<.001), with more comments (P<.001), likes (P=.001), and dislikes (P=.01); there was no significant difference in views (P=.22) or subscribers (P=.60). The mean DISCERN score was highest for web-based education videos , followed by that for videos from medical institutions or hospital . Web-based education was the source with the highest average topic score .The sources of videos included medical institutions or hospitals , web-based education , personal vlog , business or company , and media . The single video in the media category had the second highest number of views, comments, and subscribers; the highest number of dislikes; and was in the top 10 videos by number of likes; however, because the media category had only 1 video, it was not included in comparisons of characteristics by source. Among other sources , personaP<.001), but the numbers of views, comments, likes, dislikes, and subscribers were not associated with quality (Of 115 videos reviewed, 27 videos were designated as high quality, and 88 videos were designated as low quality. The low-quality group included 12 videos that were rated as low only because they included fewer than 4 topics; their DISCERN scores ranged from 3.0 to 3.6. Therefore, the scoring system did not result in a large number of videos with reliable in-depth information about a small number of topics, but instead, a small number of videos with moderate reliability and low topic comprehensiveness, being found in the low-quality categorization. Longer video duration was associated with higher quality ( quality . Among hIn this study, we identified no relationship between video quality and indicators of video popularity. These findings indicate that the information available to pregnant individuals with gestational diabetes is highly variable in quality, and may not deliver accurate or comprehensive information to users.YouTube has been evaluated as a source of health information on a variety of topics, including emerging infectious diseases and pregnancy ,44, mediInterestingly, in our study, one of the lowest rated videos overall by both DISCERN criteria and topic coverage had some of the highest views, likes, comments, and channel subscribers. This video was a media clip related to a television personality; therefore, the high numbers of views, likes, comments, and subscribers are likely because viewers accessed the clip for entertainment rather than for information about gestational diabetes. However, this highlights an important aspect of finding health information on YouTube—the search algorithm may not take the quality of the video into account for any specific search term, and quality varies significantly between videos. As we found and as has been seen previously, there are rare videos available with both good reliability and comprehensive topic coverage; however, it is difficult to ensure that these videos are accessed, as they are not necessarily the most viewed, liked, or highly ranked videos available ,45,46.Pregnant patients increasingly seek health education via web-based sources, including YouTube, and web-based media can be helpful adjuncts to clinical care ,25,47-49However, it is also important to note that YouTube has the potential to address the specific needs of individuals with gestational diabetes. Health information and supportive social networks—which are both easily accessed via the internet—have been found to influence the challenges experienced by people with gestational diabetes -51. In aTo the best of our knowledge, this study is the first to assess the reliability, content, and quality of YouTube videos about gestational diabetes, but it has several limitations. First, while the sample size was chosen to encompass the majority of videos likely to be encountered by individuals searching for information about gestational diabetes, we cannot ensure that all videos that a user may find were included, given the dynamic nature of video uploading. Search history or location may also affect ranking and accessibility of videos in ways that were not demonstrated in this paper. Second, we could not evaluate the target audience for each video, because most videos do not indicate their audience and default search setting will not necessarily preclude people from accessing videos aimed at different groups. As such, our assessment of quality and reliability may not reflect all videos with which pregnant individuals engage. Additionally, our search was limited to English-language videos, and future work is necessary to corroborate our findings with those for videos in other languages.We also noted little gender, racial, or ethnic diversity among YouTube presenters in videos about gestational diabetes. Especially because social media sites, and YouTube specifically, may be sought as a more personal or personal-experience based resource, this lack of diverse representation is a noteworthy limitation. Based on the representation found in the videos evaluated, many patients may not see themselves or their experiences reflected fully.Despite the relatively low quality and comprehensiveness found among YouTube videos for individuals with gestational diabetes, YouTube is an easily accessible and increasingly important source of health information. Providers caring for individuals with gestational diabetes should remain aware of the limitations of this resource, especially when discussing information sources with patients. Further study may be helpful in elucidating ways to harness the potential strengths of YouTube for providing high-quality accessible health information.


In China, the burden of shigellosis is unevenly distributed, notably across various ages and geographical areas. Shigellosis temporal trends appear to be seasonal. We should clarify seasonal warnings and regional transmission patterns.Reff) to quantify the transmissibility.This study adopted a Logistic model to assess the seasonality and a dynamics model to compare the transmission in different areas. The next-generation matrix was used to calculate the effective reproduction number (Reff of Longde County (3.76) is higher than Xiamen City (3.15), higher than Chuxiong City (2.52), and higher than Yichang City (1.70).In China, the rate of shigellosis fell from 35.12 cases per 100,000 people in 2005 to 7.85 cases per 100,000 people in 2017, peaking in June and August. After simulation by the Logistic model, the ‘peak time’ is mainly concentrated from mid-June to mid-July. China's ‘early warning time’ is primarily focused on from April to May. We predict the ‘peak time’ of shigellosis is the 6.30th month and the ‘early warning time’ is 3.87th month in 2021. According to the dynamics model results, the water/food transfer pathway has been mostly blocked off. The transmissibility of different regions varies greatly, such as the mean The ‘early warning time’ for shigellosis in China is from April to May every year, and it may continue to advance in the future, such as the early warning time in 2021 is in mid-March. Furthermore, we should focus on preventing and controlling the person-to-person route of shigellosis and stratified deploy prevention and control measures according to the regional transmission. AlthougThe seasonality of epidemics of shigellosis is known. Two peaks of shigellosis incidence were reported in Vietnam, with the central peak occurring during the rainy season and a secondary peak in the early or late rainy season . In ChinMost studies adopted the Autoregressive Integrated Moving Average model (ARIMA) to predict the trend of shigellosis incidence . HoweverThis study calculated the seasonality of reported cases each month in China from 2005 to 2017. We then chose four locations in China to investigate variations in transmissibility.22.1This disease monitoring and control endeavor was part of the Chinese Center for Disease Control and Prevention's (CDC) normal responsibilities in Yichang City, Xiamen City, Chuxiong City, and Longde County, thus no institutional review or informed consent was necessary. All data analyzed were anonymized.2.2The provincial dataset of reported shigellosis from all over China  from 2005 to 2017 was collected from the Public Health Science Data Center of the Chinese Center for Disease Control and Prevention (CDC). It included the monthly reports of cases and incidence of shigellosis in the whole population and separated age groups from 2005 to 2017. The study collected the shigellosis data of each patient from four areas' CDC, i.e., Yichang City from 2005 to 2018, Xiamen City from 2005 to 2018, and Chuxiong Yi Autonomous Prefecture  from 2008 to 2018, and Longde County from 2005 to 2018. In the 2005 Shigellosis incidence map, the geographic coordinates of four chosen sites were determined . The var2.3The Logistic model is an ordinary differential equation (ODE) model used to describe the self-growth characteristics of biological populations . The equn). k is the correlation coefficient, and N is the upper limit of cumulative cases. After the illness has become saturated in the population, the mean of c represents a constant. According to the characteristics of the Logistic model, it calculates the third derivative of equation The left side of the equation shows the instantaneous rate of cumulative cases br, and the mortality rate is dr.The disease does not spread vertically. All persons are equally susceptible. The natural birth rate is b)β and βw, respectively. Meanwhile, we hypothesized that symptomatically infected persons are transmissible at κ times the rate of asymptomatically infected people.The susceptible people will be infected after contact with an infected person or contaminated water/food. The transmission rate was c)p) of exposed individuals will change to symptomatically infected people (I) following an incubation period. In contrast, the rest (p) of exposed individuals will become asymptomatic (A) following a latency period .A proportion (1-d)γ and γ′, respectively, with 1/γ and 1/γ′ representing their average infectious periods.Both symptomatic and asymptomatic infected people will recover at the rate e)μ and μ′ respectively for symptomatic and asymptomatic people. We assumed μ' = cμ.The infected people shed pathogens into W at rates f)Shigella will die in the water/food after a given time, and the daily decreasing rate of the pathogen is εW.Two transmission routes are considered in this study. The first one is from person-to-person and the second one is water/food-to-person. In the SEIARW model, the compartment ectively . The comThe differential equation is expressed as follows:S, E, I, A, R, and W at time t. In the model adapted the mass action incidence rate The left side of the equation shows the instantaneous rate of change of ulations . Standar studies . Althoug studies . ActuallThe equation is as follows:2.5R0) was always defined as the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population  (Reff to quantify the transmissibility.The basic reproductive number (pulation . Howeverr (Reff) . TherefoReff : bw = 0; C): b and bw = 0; D): control (no intervention).The ‘knock-out’ simulation, which involves blocking the various shigellosis transmission channels, is another approach for estimating transmissibility , 2020b. 2.6β, b, βw, bw, κ, ω, p, γ, γ′, ε, c, μ, μ′, br and dr refer to a)κ, γ′, ε and c as 0.3125 (range: 0–1), 0.0286 (range: 0–0.0357), 0.6931 (range: 0–1) and 0.3125 (range: 0–1), respectively, based on the epidemiological characteristics of shigellosis and our previous studies (We set parameters  studies .b)p = 0.1 in the SEIARW model.The proportions of asymptomatic individuals were reported to range from 0.0037 to 0.27 . We set c)ω as 1 (range: 0.3333–1).The incubation of shigellosis was reported to range from 1 to 3 days . We assud)γ to 0.0741 (range: 0.0477–0.1428).The symptoms of shigellosis usually last for a week, but some individuals may experience them for several weeks . In the e)br and dr were 0.00605 and 0.00524 in Yichang City, 0.01027 and 0.00456 in Xiamen City, 0.0108 and 0.00643 in Chuxiong City, 0.01651 and 0.00758 in Longde County. According to the local Statistical Yearbook, the total population of each year was determined differently in four districts.The The definition of parameters 2.7R2) calculated SPSS 21.0  was adopted to judge the model goodness of fit. The Linear model in SPSS 21.0 was used to fit and predict the data of peak and early warning time.Berkeley Madonna 8.3.18  was employed for the model simulation. The simulation methods (Runge–Kutta method of order four with tolerance set to 0.001) were the same as those previously published research . Berkele2.8In our model, the seven parameters were split into 1,000 values according to their range. The value of mean and mean ± SD was exited after the sensitivity analysis in the model. As the simulation method was the same in each year with different areas, the sensitivity analysis was just performed for 2009 data of Longde County.33.1In China , the incidence of shigellosis has fallen from 35.12 cases per 100,000 in 2005 to 7.85 cases per 100,000 in 2017 . The repThe reported cases and incidence per month seasonally decreased from 2005 to 2017, in the whole population and among infants under 1 . The repIn The median incidence in males was higher than in females in Xiamen City  and Longde County . However, in Chuxiong City, the median incidence was higher in females than males  . There w3.2R2 = 0.915, P < 0.001; < 1 years old: R2 = 0.989, P < 0.001).The Logistic model  had a veχ2 = 0.0003, P > 0.999; Xiamen City: χ2 = 0.0007, P > 0.999; Chuxiong City: χ2 = 0.0005, P > 0.999; Long County: χ2 = 0.0087, P > 0.999). Owing to the limited number of reported cases after 2013 in Longde City, we just modeled the data from 2005 to 2013.The SEIARW model  fitted t3.3There is a seasonal transmission characteristic of shigellosis in all provinces in China , which iR2 = 0.638, P = 0.001) and ‘early warning time’  in total population. We predict the ‘peak time’ is 6.30 months and ‘early warning time’ is 3.87 months in the total population of 2021. There is slowly rising trend in the ‘peak time’  and slowly decreasing trend in the ‘early warning time’  in < 1 years old. We predict the ‘peak time’ is 6.90 months and ‘early warning time’ is 4.47 months in < 1 years old of 2021.From 2005 to 2017, the result of the Logistic model in the total population  located 3.4bw = 0) was consistent with that in scenario D (control). Meanwhile, the number of cases in scenario A (b = 0) was consistent with scenario C (b and bw = 0). However, in Chuxiong City and Longde County, the number of cases in scenario B (bw = 0) was slightly different from scenario D (control).In Yichang City and Xiamen City, the ‘knock-out’ simulation  showed tReff showed a higher order of transmissibility , and the ‘early warning time’ was 4.23 months. Although the shigellosis incidence is decreasing in China, it is essential to build an early warning process, especially for children under five . Our resShigella . A shigeShigella , while aShigella . Indeed,4.4The ‘knock-out’ simulation revealed that water and food have a little role in the transmission of shigellosis, suggesting that the disease is predominantly transmitted from person to person. This is congruent with the results of other studies . However2. However, Yichang City reported 4,135,900 residents for 21,084 km2. The contact frequency and the travel population in Xiamen City should be much higher than Yichang City. Our finding suggests that decreasing the travel population and contact frequency might reduce the transmission of shigellosis.Our work further indicated that the transmissibility in Longde County was higher than in Xiamen City, followed by Chuxiong City and Yichang City, which might be due to the lower economic situation in Longde County and Chuxiong City than in Yichang City and Xiamen City. According to the Statistical Yearbook, Xiamen City, a Chinese special economic zone, had 4,110,000 population in 2018 over a surface of 1,700.61 km5Because this study, like many modeling studies, relies on assumptions, the truth may be more complex. The logistic model was used at the national level, but more specific evaluations of individual provinces or cities are required. Another restriction is that, while we studied transmissibility in different places, aspects such as weather, economics, and demography were not included in our datasets and could not be analyzed in this study. We need to explore further the economic, environmental, and cultural influences which could correlate with shigellosis transmission.6Shigellosis remains a high disease burden in China, especially for children under 1. The month of the ‘peak time’ is 6.76 months, ‘epidemic acceleration’ is 4.50 months, and the recommended ‘early warning time’ is 4.23 months. The seasonality and transmission features are different in several areas. The prevention and control measures should be applied, especially in low-income provinces in China.Institutional review and informed consent were not required for this study. All data analyzed were anonymized.Not applicable.Data supporting the conclusions of this article are included within the article.Bill & Melinda Gates Foundation (INV-005834), the Science and Technology Program of Fujian Province (No: 2020Y0002), and the Xiamen New Coronavirus Prevention and Control Emergency Tackling Special Topic Program (No: 3502Z2020YJ03).This study was partly supported by the Conceptualisation: Tian-mu Chen, Zeyu Zhao, Meng Yang, Roger Frutos, and Jinlong Lv; Methodology: Tian-mu Chen, Zeyu Zhao, Qingqing Hu, Qiuping Chen, Roger Frutos, Zhao Lei, and Mingzhai Wang; Data analysis: Roger Frutos, and Jing-An Cui; Writing - original draft: Tian-mu Chen, Meng Yang, Zeyu Zhao, and Jinlong Lv; Writing - review & editing: Benhua Zhao, Yanhua Su, Yong Chen, and Xu-Sheng Zhang; Data collection: Hao Zhang, Xiongjie Zhai, and Jinlong Lv. All authors have read and agreed to the final version of the manuscript.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Presbyopia can be defined as the refractive state of the eye in which, due to a physiological decrease in the ability to accommodate, it is not possible to sustain vision without fatigue in a prolonged manner, along with difficulty focusing near vision. It is estimated that its prevalence in 2030 will be approximately 2.1 billion people. Corneal inlays are an alternative in the correction of presbyopia. They are implanted beneath a laser-assisted in situ keratomileusis (LASIK) flap or in a pocket in the center of the cornea of the non-dominant eye. The purpose of this review is to provide information about intraoperative and postoperative KAMRA inlay complications in the available scientific literature. A search was conducted on PubMed, Web of Science, and Scopus with the following search strategy:  AND (“complication” OR “explantation” OR “explanted” OR “retired”). The bibliography consulted shows that the insertion of a KAMRA inlay is an effective procedure that improves near vision with a slight decrease in distance vision. However, postoperative complications such as corneal fibrosis, epithelial iron deposits, and stromal haze are described. Presbyopia can be defined as the refractive state of the eye in which, due to a physiological decrease in the ability to accommodate, it is not possible to sustain vision without fatigue in a prolonged manner, along with difficulty focusing on near vision ,2,3,4. PSurgery for presbyopia includes a wide range of surgical approaches and procedures. Strategies include different corneal approaches, such as the application of excimer and femtosecond lasers in techniques such as monovision, sectoral modification in corneal multifocality (PresbyLASIK), and conductive keratoplasty, where electromagnetic radiation is used as the radiofrequency energy ,9,10. Si® IQ PanOptix®, Alcon Laboratories, Inc., Fort Worth, TX, USA) and apodized diffractive designs , and refractive , pseudo accommodative AcrySoft ReSTOR , and extended depth of focus (EDOF) designs  [® Presbyopic, IOLtech, La Rochelle, France) with phakic intraocular lenses (pIOLs) is used for its predictability, fixation technique, and support for presbyopia correction [Currently, multifocal intraocular lenses (MIOLs) are also an effective alternative for the correction of pseudophakic presbyopia. MIOLs are grouped according to their optical characteristics: nonapodized (AcrySoftzerland) ,15,16. Arrection ,18.KAMRA inlay surgery is a type of vision correction procedure that involves the implantation of a small, circular device called a KAMRA inlay into the cornea of the eye . The KAMKAMRA inlay surgery is typically performed as an outpatient procedure and takes about 15–30 min to complete. The procedure is generally well tolerated and has a low risk of complications . Before Synthetic keratophakia was first described by Barraquer in 1949 [® Near Vision  [There have been important advances in the design and material of corneal implants. Currently, the models used are thinner and permeable to oxygen, and the use of the femtosecond laser facilitates their intracorneal placement. Three types of implants are considered to have good results : cornealCA, USA) ; refractCA, USA)  and IcolCA, USA) ; and smaCA, USA) . The RaiCA, USA) .The purpose of this review is to provide information about intraoperative and postoperative KAMRA inlay complications in the available scientific literature.A systematic literature search was performed using the PubMed/MEDLINE (77 articles), Web of Science (55 articles), and Scopus (54 articles) databases. The search strategy included the terms  AND (“complication” OR “explantation” OR “explanted” OR “retired”). Databases were searched for publications from January 2011 to January 2022.The inclusion criteria were as follows: (1) studies with humans; (2) case reports; (3) case series; (4) cohort, cross-sectional, and case–control studies; and (5) randomized clinical trials. The exclusion criteria were as follows: (1) animal studies; (2) the article was a letter to the editor, conference abstract, study protocol, or literary review; (3) the article was not available in English; and (4) nonindexed publications.A total of 186 articles were identified. After removing duplicates, article grading and data extraction were independently performed by two authors, MCSG and RCP, according to the inclusion and exclusion criteria. If there was a conflict with the selection of an article, the third author, JMSG, decided the outcome. A total of 20 articles were finally included in the review.The literature consulted shows that both the insertion of a KAMRA in presbyopic emmetropes ,37,38,39Dexl et al.  followedHowever, postoperative complications such as halos, dry eyes, and alterations in night vision have been described  and hypeAlthough the KAMRA corneal inlay is a removable device, patients may experience residual corneal haze, hyperopic shift, and deficits in uncorrected distance visual acuity (UDVA) after explantation compared to pre-implantation UDVA .Darian-Smith et al. retrospectively analyzed the visual outcomes of KAMRA inlay insertion in a cohort of patients reporting success of procedure, complications, patient satisfaction, and refractive outcomes at the TLC Laser Centre, Toronto. The explantation rate was 11.42%; 28.5% of patients required enhancements after inlay insertion . MoshirfAlthough patients experience better near and intermediate vision after KAMRA surgery , follow-m) was significantly increased at all postoperative measurements compared with baseline. Optimal near-vision results require slightly myopic MRSE, with −0.75 considered an ideal compromise between near and far vision.Refractive instability is also a predictable consequence after KAMRA surgery and has been reported by several authors ,47,52. MKAMRA inlay implantation has been described as successful in the majority of patients; in the actual scientific literature the decentration and repositioning rate ranges from 1.2% to 8.8% . The smaDecentration of the inlay implies damage to visual quality and poor refractive results . In FiguNew techniques and devices, such as ocular coherence tomography for anterior segment (AS-OCT) imaging, could help to locate and measure the decentration of a KAMRA inlay . Figure After the United States of America Food and Drug Administration approved KAMRA, the device gained in popularity . The refMigration and extrusion are two potential complications that can occur with the KAMRA inlay ,40,49,52The permeability of implants to water and other molecules  determines the biocompatibility of the implant and its survival in the corneal stroma ,58. ExtrCorneal haze  is a comThe migration of surface proinflammatory cytokines is a local source of proteolytic enzymes and cytokines responsible for interface haze formation ,61. It iThe cornea is an avascular tissue: on its anterior face, in intimate contact with the precorneal tear film, it absorbs oxygen, and on its posterior face, bathed by aqueous humor by diffusion, it receives glucose.Keratocytes occupy 3–5% of the stromal volume. Its function consists of maintaining the collagen fibers and the extracellular matrix through a constant synthesis activity favoring metabolic gradients through the stroma so that waste products pass into the aqueous humor and nutrients flow to the cornea .The microperforations of the KAMRA inlay optimize the flow of nutrients from the cornea . HoweverNumerous authors describe a series of cases of stromal opacity after implantation of a KAMRA ,40,45,60Infectious keratitis is an infection of the cornea; it is a serious and potentially vision-threatening condition that can occur after KAMRA inlay surgery, although it is rare . InfectiDuignan et al.  describeEpithelial ingrowth is a potential complication that can occur after the implantation of a KAMRA inlay . EpithelDexl et al.  describeCastro et al.  showed aBinocularity is the result of the processing of motor and sensory skills that allows obtaining a spatial reference from using both eyes simultaneously, merging a single image at the cortical level; when this happens, a stereoscopic vision or three-dimensional image is achieved ,70,71,72KAMRA inlay surgeries in presbyopic emmetropes and KAMRA inlay surgeries combined with LASIK in patients with ametropia is an effective procedure that improves uncorrected near visual acuity with a slight decrease in distance vision in the eye with the implant or in both eyes.This pinhole implant surgery can have moderate to severe complications, such as refractive instability, epithelial ingrowth, or infectious keratitis. Refractive outcomes should be considered with caution due to possible conflicts of interest between the authors of the publications and manufacturers.


To evaluate the association of near heterophoria with refraction and axial length (AL) in Chinese school children.  This school-based cross-sectional study included 15,081 Chinese primary school children (grades 1–6) examined during 2017. Near heterophoria was measured at 33 cm using the Maddox rod and prism test. Noncycloplegic refraction and AL were also measured. A generalized additive model with a Gaussian link was used to determine the association of near heterophoria with refraction and AL. Analyses were adjusted for age to account for differences in the age distribution of the sample. P < 0.001). The mean AL in children with orthophoria was 0.11 mm shorter than that in children with either exophoria or esophoria (P < 0.001). Near heterophoria exhibited a significant correlation with refraction and AL, irrespective of age.  Overall, data were analyzed for 11,013 students ranging in age from 6 to 13 years. The most common type of near heterophoria was exophoria (64.96%), the proportion and value of which increased according to grade. Exophoria accounted for 62.53% , 65.03% , and 67.51%  of near heterophoria cases for grades 1-2, grades 3-4, and grades 5-6, respectively. Prism diopter (PD) values for near heterophoria in these grades were −6.30 ± 3.69, −6.81 ± 4.01, and −8.32 ± 5.12 PD, respectively. The average spherical equivalent (SE) in children with orthophoria was 0.23 D and 0.25 D lower than those in children with exophoria and esophoria, respectively ( Exophoria represents the most common type of near heterophoria in children. Children with more severe near heterophoria, whether exophoria or esophoria, exhibited a higher degree of myopia and longer AL than those with relatively less severe near heterophoria. These results highlight the need for further, long-term investigation regarding the role of near heterophoria in visual development. Myopia is among the leading causes of visual impairment worldwide, representing a global public health concern due to its increasing prevalence. By 2050, an estimated 2.5 billion and 1 billion people will be affected by myopia and high myopia, respectively . Myopia Heterophoria is a latent deviation of the eyes that is only revealed in the absence of an adequate stimulus to fusion . AlthougGiven the high prevalence of myopia in the Chinese population –26, someNCT04073238) and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.This cross-sectional study included 15,081 school children (aged 6 to 13 years) who underwent assessments in Tianjin, China, in 2017. Written informed consent was obtained from at least one parent, and each child provided verbal consent prior to visual screening and participation in the study. The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Tianjin Eye Hospital (2021020). This trial was registered on ClinicalTrials.gov . The corneal reflections test (Hirschberg test), unilateral cover test, and alternate cover test were also performed. Children with abnormal findings or strabismus were excluded from the study. The degree of near heterophoria was measured using the Maddox rod and prism test . BrieflyOrthophoria was defined as the degree of heterophoria between −2 PD and +2 PD. Myopia was defined as a spherical equivalent (SE) ≤−0.50 diopters (D), while hyperopia was defined as an SE ≥+2.00 D.r = 0.847, P < 0.001; r = 0.842, P < 0.001, respectively). All statistical analyses were performed using the MGCV package in R software (version 3.6.2). The normality of the data was assessed using the Shapiro–Wilk test. AL was compared among children with different heterophoria status using the one-way analysis of variance (ANOVA). Non-normally distributed refraction data for different types of near heterophoria and differences in near heterophoria among different school grades were compared using the Kruskal–Wallis H test. The Spearman rank correlation coefficients were used to evaluate the relationship between age and near heterophoria. Associations of near heterophoria with SE and AL were analyzed using generalized additive models (GAMs), and the smooth terms were represented as penalized thin-plate regression splines. In model 1, a GAM with a Gaussian link was applied to evaluate the associations of near heterophoria with SE and AL. The natural spline smoothing functions of near heterophoria were used as the independent variable, while SE or AL was used as the dependent variable. In model 2, the natural spline smoothing functions of near heterophoria and age were entered for covariate adjustment. The level of statistical significance was set at P < 0.05.As we observed a strong correlation between right and left eye values for SE and AL, analyses were performed using data from right eyes only (P < 0.05). However, no significant difference was found in heterophoria between the two groups (P=0.197).A total of 15,081 school children ranging in age from 6 to 13 years were examined, including 376 (2.49%) children with strabismus. Children with missing data, significant systemic illnesses, and strabismus were excluded, resulting in a total enrollment of 11,013 children  with a mean age of 9.26 ± 1.73 years. A total of 1,559 (14.16%) students wore glasses regularly. P < 0.001).Children with orthophoria constituted 23.30%  of the sample. Exophoria and esophoria were observed in 64.96%  and 11.74%  of children, respectively. The mean values of near heterophoria were −0.06 ± 0.50 PD, −7.15 ± 4.41 PD, and 5.74 ± 4.54 PD in children with orthophoria, exophoria, and esophoria, respectively. The Shapiro–Wilk test revealed that the overall distribution of near heterophoria was non-normal . As shown in Myopia was observed in 31.24% , 54.21% , and 77.96%  of children in grades 1-2, grades 3-4, and grades 5-6, respectively. Emmetropia was observed in 67.79% , 44.88% , and 21.34%  of children in grades 1-2, grades 3-4, and grades 5-6, respectively. Rates of hyperopia were only 0.97% , 0.91% , and 0.70%  in grades 1-2, grades 3-4, and grades 5-6, respectively. H = 21.328, P < 0.001; F = 9.098, P < 0.005, respectively). The average SE in children with orthophoria was 0.23 D lower than in children with exophoria and 0.25 D lower than in children with esophoria (P < 0.001). Mean AL was 0.11 mm shorter in children with orthophoria than in children either with exophoria or esophoria (P < 0.001) (SE and AL differed significantly between different types of near heterophoria (< 0.001) .r = −0.082, P < 0.001). Although age adjustment in model 2 decreased the correlation between near heterophoria and AL, the correlation between the two variables remained significant (P < 0.01)  .This school-based survey was initiated in 2017 to investigate the associations of near heterophoria with AL and refraction among school children in Tianjin, China. Interestingly, our findings indicated that exophoria was the predominant type of near heterophoria in school-aged Chinese children. The prevalence of exophoria also increased as grade level increased. Notably, the present study was the first to report that greater degrees of near exophoria or esophoria were associated with longer AL and more severe myopia.In this study, the most common type of near heterophoria in Chinese school children was exophoria (64.69%), irrespective of ametropia or age, occurring slightly more frequently than in previous studies , 22, 23.Direct comparisons of our findings to those of previous studies were difficult given differences in region, myopia definitions, and measurement methods , 29. In The children were divided into three groups according to grades . Different grades had different learning environments and learning tasks, which had different requirements for vision. These differences may cause variable near heterophoria and refraction. However, because the age of primary school entrance varied greatly, the ages of the two adjacent grades might overlap, so the children from the two adjacent grades were put together to analyze.Notably, both the proportion and value of exophoria increased as grade level increased in our study. Anderson et al. reported greater near exophoria among children with myopia assessed over a 10-year follow-up period, which might help to explain this finding . PreviouAlthough analyses were adjusted for age to eliminate its confounding effects on AL and binocular vision, near heterophoria and noncycloplegic refraction remained significantly associated in the adjusted model. These results highlighted the need for further research to determine the exact mechanisms by which myopia develops and progresses in children with near heterophoria.The present study had some limitations, including regional bias, as all participants attended elementary schools in Tianjin. In addition, noncycloplegic autorefraction measurements were used for analysis. Although such measurements had exhibited good consistency with other values obtained in large-scale refraction screening of the population , 35, theThis study demonstrated that near heterophoria exhibited a significant correlation with refraction and AL. The most frequent type of near heterophoria in Chinese elementary school children was exophoria. Greater degrees of near heterophoria were associated with longer AL and a higher degree of myopia, irrespective of age. These findings highlighted the need to investigate the influence of near heterophoria on visual development in large-scale studies with longer follow-up periods.


This article presents multi-omic integration with sparse value decomposition (MOSS), a free and open-source R package for integration and feature selection in multiple large omics datasets. This package is computationally efficient and offers biological insight through capabilities, such as cluster analysis and identification of informative omic features.https://CRAN.R-project.org/package=MOSS.https://github.com/agugonrey/GonzalezReymundez2021.Supplementary information can be found at  Omic data are characterized by many features from multiple layers of data . Thus, traditional methods (e.g. ordinary least squares) are insufficient to obtain significant insights from this multi-layer, high-dimensional data. To effectively integrate multi-omic data, novel methods have been developed  to handle these limitations. MOSS is a free and open-source R package that performs data integration and feature selection on large datasets. It combines the flexibility of sparse value decomposition (SVD) with parallel and in-disk computations to accommodate data sizes reaching biobank dimensions.The package’s primary function is called moss. Omic data are given to moss as a list where each element corresponds to a different omic (see help pages for function moss). Each omic enters the function as a numeric array. The rows of each array represent samples (e.g. a subject per row) and the column of each array an omic feature (e.g. expression of a gene). The rows of the different numeric arrays on the list need to be sorted in the same order (i.e. each row belongs to the same sample across omic blocks). Integration of omic blocks occurs by appending them, column-wise, into an extended matrix. Before making the extended matrix, blocks are normalized and standardized. If missing values are present, they are imputed by the mean. The effects of potential confounders can be internally adjusted by giving moss a data frame, vector or matrix with covariates. When omic blocks are too big to be handled in memory, File-backed Big Matrix (FBM)  on the integrated omic blocks to obtain latent dimensions as sparse factors (i.e. with zeroed out elements), representing variability across subjects and features. Sparsity is imposed via Elastic Net (MOSS matches the performance of current analogous methods . To illun = 1e5 and p = 1e6 in One of MOSS's essential capabilities is the handling of big data. While other tools demonstrate similar analytical performance , MOSS isIn Omic integration emerged as a group of techniques to collectively analyze multiple omic data layers and retrieve helpful information of shared biological processes (As a features selection tool, MOSS performance is best as the number of signal features decreases (e.g. some signaling pathways affected in cancer, such as canonical MAPK pathway; Despite its benefits as a data integration and mining tool, MOSS lacks statistical inference to support feature selection. Future versions of MOSS can deal with these limitations by adopting fast bootstrap techniques applied to high-dimensional SVD (In sum, MOSS is a flexible and fast tool to perform data integration. It shares capabilities with popular methods, including estimation of latent data dimensions, feature selection and convenient graphical displays. Nevertheless, unlike these methods, MOSS integrates datasets too large to be handled in RAM and requires considerably shorter amounts of time.


Successive BLP techniques have yielded higher performance with lower computational expense, yet at the same time they have drifted further from the original motivational justification of bilinear models, instead becoming empirically motivated by task performance. Furthermore, despite significant success in text-image fusion in VQA, BLP has not yet gained such notoriety in video question answering (video-QA). Though BLP methods have continued to perform well on video tasks when fusing vision and non-textual features, BLP has recently been overshadowed by other vision and textual feature fusion techniques in video-QA. We aim to add a new perspective to the empirical and motivational drift in BLP. We take a step back and discuss the motivational origins of BLP, highlighting the often-overlooked parallels to neurological theories . We seek to carefully and experimentally ascertain the empirical strengths and limitations of BLP as a multimodal text-vision fusion technique in video-QA using two models (TVQA baseline and heterogeneous-memory-enchanced ‘HME’ model) and four datasets . We examine the impact of both simply replacing feature concatenation in the existing models with BLP, and a modified version of the TVQA baseline to accommodate BLP that we name the ‘dual-stream’ model. We find that our relatively simple integration of BLP does not increase, and mostly harms, performance on these video-QA benchmarks. Using our insights on recent work in BLP for video-QA results and recently proposed theoretical multimodal fusion taxonomies, we offer insight into why BLP-driven performance gain for video-QA benchmarks may be more difficult to achieve than in earlier VQA models. We share our perspective on, and suggest solutions for, the key issues we identify with BLP techniques for multimodal fusion in video-QA. We look beyond the empirical justification of BLP techniques and propose both alternatives and improvements to multimodal fusion by drawing neurological inspiration from Dual Coding Theory and the Two-Stream Model of Vision. We qualitatively highlight the potential for neurological inspirations in video-QA by identifying the relative abundance of psycholinguistically ‘concrete’ words in the vocabularies for each of the text components ( Though successive BLP techniques focus on leveraging higher performance with lower computational expense, which we wholeheartedly welcome, the context of their use has subtly drifted from application in earlier bilinear models e.g., where in non-textual features   and morefeatures , BLP hasfeatures . In thisfeatures  with deeg Theory  and the g Theory , and proIn this section we outline the development of BLP techniques, highlight how bilinear models parallel the two-stream model of vision, and discuss where bilinear models diverged from their original motivation.Early works use vector concatenation to project different features into a new joint feature space. Working from the observations that “perceptual systems routinely separate ‘content’ from ‘style”’, i.e., multimodal compact bilinear pooling (MCB). We note that for MCB, the learned outer product is no longer on convolution maps, but rather on the indexes of image and textual tensors. Intuitively, a given index of an image or textual tensor is more abstracted from visualisable meaning when compared to convolution map. As far as we are aware, no research has addressed the potential ramifications of this switch from distinct maps to feature indexes, and later usages of bilinear pooling methods continue this trend. Though MCB is significantly more efficient than full bilinear expansions, they still require relatively large latent dimension to perform well on VQA (d ≈16000).W by decomposing it into two rank-reduced projection matrices:To further reduce the number of needed parameters, X ∈ ℝm×o, Y ∈ ℝn×o, o < min is the output vector dimension, ⊙ is element-wise multiplication of vectors or the Hadamard product, and 1 is the unity vector. MLB performs better than MCB in := i1, …, in−1, in, in+1, …, iN) jn, in) of rd order tensor The tucker decomposition of a real 3τ ∈ ℝd1×d2×d3(core tensor), and d2×d2, ℝd3×d3(factor matrices) respectively.where MUTAN: The MUTAN model uses a reduced rank on the core tensor to constrain representational capacity, and the factor matrices to encode full bilinear projections of the textual and visual features, and finally output an answer prediction, i.e:where i.e., take two functions as inputs. i.e.:All the BLP techniques discussed up to now are ‘second-order’, i ∈ {1, …, p} where p = 1. Though MFH slightly outperforms MFB, there has been little exploration into the theoretical benefit in generalising to higher-order BLP.for Block term decomposition: Introduced in a 3-part paper  are the ‘factor matrices’ that intuitively expand the nth dimension of nth dimension of a, b) here refers to the Stiefel manifold, i.e., St: where Bilinear superdiagonal model: The BLOCK model uses block term decompositions to learn multimodal interactions. The authors argue that since BLOCK enables “very rich (full bilinear) interactions between groups of features, while the block structure limits the complexity of the whole model”, that it is able to represent very fine grained interactions between modalities while maintaining powerful mono-modal representations. The bilinear model with inputs o dimensional space with tensor products:R1, R2, R3) is defined as:where This can be written asR1 from R2 from R3:where j − i containing the corresponding values of where We aim to highlight and explore a broad shift away from BLP in favour of methods such as attention in video-QA benchmarks. Several video models have incorporated and contrasted BLP techniques to their own model designs for language-vision fusion tasks. not involve language have found success using BLP techniques. i.e. (RGBT). Where recent research in video-QA tasks  has moved away from BLP techniques, several video tasks that do In this section, we outline the video-QA datasets we use in our experiments.i.e., .Count: Counting the number of times a specific action is repeated .repeated  e.g., “HAction: Identify the action that is repeated a number of times in the video clip. There are over 22k multiple choice questions e.g., “What does the girl do 5 times?”.Trans: Identifying details about a state transition , and aims to generate hard and confusing incorrect answers by sampling from correct answers of the same question type. Models on EgoVQA have been shown to overfit due to its small size. To remedy this, Most video-QA datasets focus on video-clips from the 3https://github.com/jayleicn/TVQA) and HME-VideoQA (https://github.com/fanchenyou/HME-VideoQA) implementations.In this section, we describe the models used in our experiments, built from the official TVQA  or BERT embeddings (∈ℝ768). Formally, nq, nai, ns is the number of words in q, ai, S respectively and d = 300, 768 for GloVe or BERT embeddings respectively.Context matching: Context matching refers to context-query attention layers recently adopted in machine comprehension      of outpuTo better handle semantic meaning through long sequential video data, recent models have integrated external ‘memory’ units  alongsidHeterogeneous read/write memory: The memory units in HME use an attention-guided read/write mechanism to read from/update memory units respectively(the number of memory slots used is a hyperparameter). The claim is that since motion and appearance features are heterogeneous, a ‘straightforward’ combination of them cannot effectively describe visual information. The video memory aims to effectively fuses motion (C3D (ion (C3D ) and appion (C3D  and VGG ion (C3D ) featureion (C3D .Encoder-aware question memory: Previous memory models used a single feature vector outputted by an LSTM or gated recurrent unit (GRU) for their question representation  for both the datasets and code used in our experiments. In this section we outline our experimental setup and results. We save our insights for the discussion in the next section. See our GitHub repository  and cross-covariance ∑r=01. CCA finds pairs of linear projections of the two views Canonical cross correlation analysis (CCA)  is a metρ is the correlation co-efficient. As ρ is invariant to the scaling of w0 and w1, the projections are constrained to have unit variances, and can be represented as the following maximisation:where s.tHowever, CCA can only model linear relationships regardless of the underlying realities in the dataset. Thus, CCA extensions were proposed, including kernel CCA (KCCA)  and latet, v are encoded in neural-network transformations Ht, Hv = ft, fv , and then the canonical correlation between both modalities is maximised in a common subspace .DCCA is a parametric method used in multimodal neural networks that can learn non-linear transformations for input modalities. Both modalities corr = corr, fv)max We use DCCA over KCCA to co-ordinate modalities in our experiments as it is generally more stable and efficient, learning more ‘general’ functions.We use a 2-layer DCCA module to coordinate question and context  features , Table 4As described in the previous section, we replace a concatenation step in the HME model between textual and visual features with BLP . The goaNo BLP Improvements on TVQA: On the HME concat-to-BLP substitution model . However, we cannot simply conclude our poor results are due to our relatively small latent spaces because: (I) MCB is our best performing BLP technique. However, MCB has been outperformed by MFH on previous VQA models and it has been shown to require much larger latent spaces to work effectively in the first place .Unimodal biases in TVQA and joint representation: Another explanation may come from works exploring textual biases inherent in TVQA to textual modalities  module introduced in BLP has no effect: Our experiments on the EgoVQA, TGIF-QA, and MSVD-QA datasets are on concat-to-BLP substitution HME models. Our results are inconclusive. There is virtually no variation in performance between the BLP and concatenation implementations. Interestingly, EgoVQA consistently does not converge with this simple substitution. We cannot comment for certain on why this is the case. There seems to be no intuitive reason why it’s 1st person content would cause this. Rather, we believe this is symptomatic of overfitting in training, as EgoVQA is very small and pretrained on a different dataset, and BLP techniques can sometimes have difficulties converging.Does better attention explain the difference?: Attention mechanisms have been shown to improve the quality of text and visual interactions. We have experimented with BLP in two video-QA models and across four datasets. Our experiments show that the BLP fusion techniques popularised in VQA has not extended to increased performance to video-QA. In the preceding sections, we have supported this observation with experimental results which we contextualise by surveying the surrounding literature for BLP for multimodal video tasks. In this section, we condense our observations into a list of problems that BLP techniques pose to video-QA, and our proposal for alternatives and solutions:Inefficient and computationally expensive across time: BLP as a fusion mechanism in video-QA can be exceedingly expensive due to added temporal relations. Though propagating information from each time step through a complex text-vision multimodal fusion layer is an attractive prospect, our experiments imply that modern BLP techniques simply do not empirically perform in such a scenario. We recommend avoiding computationally expensive fusion techniques like BLP for text-image fusion throughout timesteps, and instead simply concatenate features at these points to save computational resources for other stages of processing . Furthermore, we note that any prospective fusion technique used across time will quickly encounter memory limitations that could force the hidden-size used sub-optimally low. Though summarising across time steps into condensed representations may allow more expensive BLP layers to be used on the resultant text and video representations, we instead recommend using state-of-the-art and empirically proven multimodal attention mechanisms instead  to focus on relevant video and question features. We therefore recommend using attention mechanisms for their strong performance and relatively interpretable behaviour, and avoiding BLP for specifically video-text fusion.cognition, emotioncognition, and viocognition. Likewiscognition, action cognition and videcognition. On the cognition. Our obsEmpirically justified on VQA: Successive BLP techniques have helped drive increased VQA performance in recent years, as such they remain an important and welcome asset to the field of multimodal machine learning. We stress that these improvements, welcome as they are, are only justified by their empirical improvements in the tasks they are applied to, and lack strong theoretical frameworks which explain their superior performance. This is entirely understandable given the infamous difficulty in interpreting how neural networks actually make decisions or exploit their training data. However, it is often claimed that such improvements are the result of some intrinsic property of the BLP operator, e.g., creating ‘richer multimodal representations’:   features as visual(or auditory) imagens. There are many insights from DCT that could guide and drive multimodal deep learning:ry (DCT)  broadly ry (DCT) . DCT conI) Logogens and imagens are discrete units of recognition and are often related to tangible concepts . By drar models ) as oppor models  are a moII)(III) Imagens  may be a function of many modalities, i.e., one may recognise something as a function of haptic and auditory experiences alongside visual ones. We believe this implies that non-verbal modalities (vision/sound etc.) should be in some way grouped or aggregated, and that while DCT remains widely accepted, multimodal research should consider ‘verbal vs non-verbal’ interactions as a whole instead of focusing too intently on ‘case-by-case’ interactions, i.e., text-vs-image and text-vs-audio. This text/non-text insight may be related to the apparent difference in text-vision video task performance previously discussed.(IV) Multimodal cognitive behaviours in people can be improved by providing cues. For example, referential processing (naming an object or identifying an object from a word) has been found to additively affect free recall (recite a list of items), with the memory contribution of non-verbal codes (pictures) being twice that of verbal codes , we rescale the scores for each dataset such that the lowest score is 0 (highly abstract), and the highest score is 1 (highly concrete). Though we cannot find a concreteness score for every word in each dataset component’s vocabulary, we see that the four video-QA datasets we experiment with have more concrete than abstract words overall. Furthermore, we see that answers are on-average significantly more concrete than they are abstract, and that (as intuitively expected) visual concepts from TVQA are even more concrete. modern multimodal deep learning practices. We offer a few experimentally and theoretically guided suggestions to consider for multimodal fusion in video-QA, most notably that attention mechanisms should be prioritised over BLP in text-vision fusion. We qualitatively show the potential for neurologically-motivated multimodal approaches in video-QA by identifying the relative abundance of psycholinguistically ‘concrete’ words in the vocabularies for the text components of the 4 video-QA datasets we experiment with. We would like to emphasise the importance of related neurological theories in deep learning and encourage researchers to explore Dual Coding Theory and the Two-Stream model of vision.In light of BLP’s empirical success in VQA, we have experimentally explored their use in video-QA on two models and four datasets. We find that switching from vector concatenation to BLP through simple substitution on the HME and TVQA models does not improve and in fact actively harm performance on video-QA. We find that a more substantial ‘dual-stream’ restructuring of the TVQA model to accommodate BLP significantly reduces performance on TVQA. Our results and observations about the downturn in successful text-vision BLP fusion in video tasks imply that naively using BLP techniques can be very detrimental in video-QA. We caution against automatically integrating bilinear pooling in video-QA models and expecting similar empirical increases as in VQA. We offer several interpretations and insights of our negative results using surrounding multimodal and neurological literature and find our results inline with trends in VQA and video-classification. To the best of our knowledge, we are the first to outline how important neurological theories


Plasmodium malariae is a neglected human malaria parasite with low parasitemia that often results in the misdiagnosis and underestimation of the actual disease burden of this pathogen. Microscopy is the best diagnostic tool, despite the fact that rapid diagnostic tests (RDTs) are the best surveillance tool for malaria diagnosis in many rural areas for their ease of use in elimination settings. For parasite antigen detection other than P. falciparum, RDTs depend on essential glycolytic Plasmodium proteins, i.e., Plasmodium lactate dehydrogenase (pLDH) and Plasmodium aldolase (pAldo) antigens. There is a lack of species-specific test kits for P. malariae, and overall, its rapid antigenic test accuracy is questionable. False negative results can accelerate the burden of asymptomatic malaria infection and transmission. Here, we report a case of a malaria patient in Bangladesh infected with P. malariae who tested negative on pLDH and pAldo based RDTs. This case provides useful information for health providers to be aware of possible RDT failure and also for the future development of analytically sensitive test kits for P. malariae. Plasmodium malariae is one of the six parasites causing human malaria. Because of its low parasitemia and lower pathogenicity, it is often neglected. This protozoan parasite has been observed in all malaria-prone regions of the world [P. falciparum is the dominant and most relevant species, but P. malariae is present as well [P. malariae in the Chittagong Hill Tracts, but this parasite was documented in 9.5% of all malaria-positive asymptomatic participants [Plasmodium antigens, such as P. falciparum histidine-rich protein-2 (PfHRP2) for the diagnosis of P. falciparum only, and Plasmodium lactate dehydrogenase (pLDH) for the diagnosis of all Plasmodium species (pan-specific) or specifically P. falciparum (PfLDH) and/or P. vivax (PvLDH). Moreover pan-specific Plasmodium aldolase (pAldo) RDTs are available. However, none of the antigen detection kits is specific for P. malariae, P. ovale spp., or P. knowlesi [P. knowlesi is endemic, it remains problematic to distinguish P. malariae from P. knowlesi due to their similar morphology [he world . In Bang as well ,3,4,5. Aicipants . Rarely,icipants . Moreoveicipants . Speciesicipants . For theicipants . Malariaknowlesi . Today, rphology . Hence, P. malariae that tested negative on RDT (based on PfHRP2/pLDH) in Bangladesh despite the presence of a relatively high parasitemia. In this case, we report an infection with P. malariae. The initial parasite density count was 5380 P/µL. This initial count was performed by an experienced and WHO-certified microscopist. The patient received treatment in accordance with the national guideline [TM Rapid Malaria Pf/Pan , and (3) BinaxNOW® Malaria Test . The sample tested negative for PfHRP2  in Bandarban, Chittagong Hill Tracts, Bangladesh (92.3120° E longitude and 21.6523° N latitude). The patient resided near the AUHC and reported no travel activity in the past three months outside his territory. At the AUHC, the sample tested negative on RDT using a CareStart™ Malaria HRP2/pLDH (Pf/Pv) Combo  RDT. However, microscopical blood film examination confirmed infection with uideline . Three mr PfHRP2 a–c and nr PfHRP2 a,d.P. malariae was confirmed using 18S ribosomal RNA (rRNA) Plasmodium sp. and species-specific PCRs [P. malariae . On the other hand, a negative result for CareStart™ Malaria HRP2/pLDH (Pf/Pv) Combo  defined no cross reactivity of the sample with P. falciparum or P. vivax antigenic target  acts as a prognosis marker of disease severity in gression . In thisP. malariae to persist for a very long time in host facilities. Thus, circulating LDH antigen released by parasites assists in the formation of host antibodies [P. malariae [Studies have shown that PfHRP2 has a relatively long half-life (2–4 weeks), favoring the development of anti-PfHRP2 antibodies in the host blood and leading to false negative results The current authors also proposed that the similar blocking effect may hinder the performance of LDH or aldolase . A 72 hotibodies . This anmalariae .Plasmodium species, namely, P. falciparum and P. vivax. Neglected Plasmodium species like P. malariae are often overlooked. In our case, the RDT diagnosis of a symptomatic patient with relatively high parasitemia failed. It is evident that no reliable screening kits/RDTs are available for the diagnosis of P. malariae. Diagnosis with microscopy and PCR is often not possible in endemic rural settings. Since (mono-) infections of P. malariae are not uncommon, proper diagnosis may reveal more subclinical malaria cases in endemic countries. Lately, the paradigm shift from malaria control to malaria elimination in Bangladesh underscores the importance of having an efficient method of point-of-care testing for P. malariae. We recommend that the health care team in endemic areas be aware of RDT failings and propose that additional microscopical or molecular diagnostic tools might be needed to avoid false negative results. In endemic areas, malaria case management mainly focuses on the most relevant


Teachers’ self-efficacy is an important indicator of student teachers’ preparedness for teaching. Interventions using video lessons are effective in increasing student teachers’ self-efficacy. However, there is a lack of research on emotional and reflective processes in the context of video-based interventions.The present study examined emotions and reflection as well as their effects on changes in self-efficacy in a video-based intervention. A total of 159 student teachers participated in the study. The participants were randomly assigned to three groups: Two groups analyzed video lessons in which group roup one received open-ended observation tasks (ig1) and group two received structured observation tasks (ig2). Participants in the control group (cg) analyzed text-based case studies with open-ended observation tasks.d = 0.68) in video group two (ig2), whose members analyzed videos using structured observation tasks but not in video group one (ig1), whose members analyzed open-ended observation tasks, and in the control group. In addition, there were significant relations between positive arousal and reflection. Finally, regression analyses showed that reflection was a significant predictor for changes in self-efficacy, whereas no significant effect of emotional arousal was detected.The results show that self-efficacy increased with medium effect size (In conclusion, the findings of this study indicate that video-based interventions with structured observation tasks increased self-efficacy among student teachers. Furthermore, the findings provide novel evidence on the association between reflection, self-efficacy and emotion in video-based interventions in teacher education. LearninWhereas some studies show that video-based interventions trigger reflective processes e.g., , few stuTo address this research gap, the present study focused on beginning student teachers’ self-efficacy concerning adaptive teaching in heterogeneous classrooms and their changes during a video-based intervention. The video lessons showed typical teaching situations for dealing with heterogeneity in elementary schools, with a focus on the different performance levels and requirements for students. Our study explored the emotional and reflective processes among student teachers analyzing video lessons or equivalent written case studies and investigated the effects of emotion and reflection on changes in their self-efficacy.2.2.1.According to cf., Personal experience is the most effective source because it provides information about one’s successes or failures. Self-efficacy is positively influenced in the case of success and negatively in the case of failure. In vicarious experiences, learning occurs from models. Individual self-efficacy is affected by observing model competency behaviors and comparing them to one’s competencies. Vicarious experiences are particularly effective when different successful models can be compared. Verbal persuasion of meaningful others can have an impact on one’s self-efficacy. Finally, physiological and affective states provide information about arousal during situations in which capabilities are practiced. In particular, negatively evaluated somatic information decreases self-efficacy, and positively read somatic information increases self-efficacy cf., .A few empirical studies revealed associations between emotions and teacher self-efficacy e.g., . HoweverVideo lessons have become a popular tool to foster teacher self-efficacy e.g., . Various2.2.Emotional experience is described as a complex phenomenon that arises, is maintained, and diminishes in reciprocal dependence on cognitions. Furthermore, emotions are integrated into current action and interact with goals, expectations, and subjective evaluations . Emotioncf., In addition to activating cognitive and motivational processes, video lessons are likely to engage student teachers emotionally as well . Since v2.3.cf., cf., Another strand of theory addresses the role of reflection in authentic learning situations in (student) teachers’ professional development cf., . AlthougReflection in the context of video lesson analysis describes comprehensive reflection on teaching practice while viewing a video and on one’s own beliefs. According to cf.In the context of learning with video lessons, it is particularly interesting how reflection and emotions interact. Several theories describe the relationship between emotion and cognitive processes e.g., . For exa3.The relevance of using video lessons to promote professional competencies in teacher education was emphasized e.g., . Video lFurthermore, analyzing video lessons encourages students´ reflection skills e.g., . EmotionIn our study, a 90-min intervention was administered to student teachers in a pre-post-experimental design. Students analyzed two video lessons (ig), or two equivalent written case studies (cg). Participants were asked to observe the case studies using either open-ended  or structured observation tasks (ig2).Against the theoretical and empirical background of the subject area, the present study examined the following questions:RQ 1: Does student teachers’ self-efficacy increase during a video-based intervention?RQ 2: What role do emotion and reflection play in changes in self-efficacy during a video-based intervention?hypothesis 1).To answer the research questions, we developed four hypotheses. First, we assumed that self-efficacy increases while analyzing video lessons e.g., . Therefohypothesis 2a). In addition, due to the variation of the observation tasks, different depths of reflection can be expected with the highest values on reflection in structured observation tasks. Therefore, participants in ig2 will report a deeper reflection than participants in ig1 and cg (hypothesis 2b).Second, Banduras’ self-efficacy theory (1986) allows for the assumption that analyzing video lessons is more stimulating for students’ emotional arousal than reading case studies. Empirical findings verify this assumption e.g., . We hypohypothesis 3).Third, theoretically and empirically, there is evidence for a correlation between reflection and emotion e.g., . Consequhypothesis 4).Finally, there is evidence for bilateral correlations between reflection and self-efficacy e.g.,  as well 4.4.1.via the virtual campus and filled in the first questionnaire (pretest). Then they received theoretical input on teaching in heterogeneous classes  in an online learning environment. After completing the first case study,via the MetavideoportalThe intervention was implemented on elementary student teachers in an online learning environment. Data were collected during a 90-min intervention in November 2021. After a short welcome in the plenum, in which the students received information about the learning unit and the link to a virtual campus, they were assigned randomly into three groups. Each group received a digital schedule 4.2.N = 156, but with a relatively high dropout of 39% (N = 62) during the study. However, this was not considered a systematic dropout. There were no significant differences between participants who participated fully and those who dropped out early during the study (p = 0.094) or with regard to prior experience with the topic heterogeneity (p = 0.413), prior experience with video lesson analysis (p = 0.478), self-efficacy (p = 0.591), and positive (p = 0.267) and negative emotional arousal (p = 0.477). The participants were randomly assigned to three groups (according to their birth month), resulting in an initial N = 58 in ig1, N = 47 in ig2 and N = 51 in cg. A total of 87.7% of the participants were female, 10.3% are male, and 10 participants did not answer the question on gender. In all three groups, students were, on average, in their 2nd semester . Participants in both intervention groups were, on average, 20 years old . Participants in the cg were, on average, 21 years old .Participants were drawn from students enrolled at an elementary teacher education lecture and seminars at a German University. The University of Bamberg is a public university in Bavaria with a high percentage of teaching students (about 20%). Participants of our study were intended to work in elementary schools and their studies focused on primary education. The initial sample was 4.3.To investigate the hypotheses we used three measurement tools to evaluate self-efficacy, emotion, and reflection. Furthermore, previous experience, reflection skills, and interest and relevance were used as control variables.4.3.1.Self-efficacy of Adaptive Teaching in Heterogeneous Classrooms by I feel able to make reasoned decisions about differentiation in the classroom.). The reliability of this scale was good to very good . However, 10 adjectives belonged to positive arousal on the scale, and 10 items to negative arousal. The higher the mean values, the higher the arousal. The internal consistencies were good to very good  and theoretical contextualization . Participants had to rate their answers on a 4-point-Likert scale. The reliability of these scales was good to very good  on a 7-point Likert scale. A categorical variable was used to investigate previous experience . Additionally, interest and relevance were also rated on a 4-point Likert scale . We checked the differences for emotional arousal as well as for reflection using two-factor ANOVAs with repeated measures and planned contrast comparisons (hypothesis 2). The planned contrasts were adjusted to the hypotheses: In hypothesis 2a, the video groups (ig1 and ig2) were compared with the control group. In hypothesis 2b, the group with structured observation tasks (ig2) was compared with the two groups with open-ended observation tasks. Correlation analyzes were conducted to evaluate the association between emotional arousal and reflection (hypothesis 3). Finally, the prediction of self-efficacy was checked with a regression analysis. Self-efficacy (posttest 2) was the dependent variable, and emotion and reflection were the independent variables. Self-efficacy (pretest), previous experience in analyzing video lessons, general reflection skills, interest, and relevance were the control variables in the regression models. To control for multicollinearity, stepwise sequential regression models were calculated (hypothesis 4). For all parametric tests, Cohen’s d was calculated and interpreted according to small effect, ≥ 0.05 medium effect, and ≥ 0.08 large effect.The statistical software package Social Science (SPSS), Version 23, was used for the statistical analysis of the data. To identify changes in self-efficacy, a two-factor repeated measures ANOVA and single ANOVAs with repeated measurement for each group to examine group differences were conducted . Descriptively, cg showed a higher mean in posttest 1  compared to the means of the other two measurement points . The means for positive emotional arousal in ig1 were constant  and ig2 , negative emotional arousal decreased slightly during the intervention, and the mean value in cg increased again at posttest 2 .All means for tant see . The statant see . Howeverself-efficacy between pretest and posttest 2 in ig1  and cg . In ig2  there was a slight, observable increase. All mean values were in the upper range of the 4-point Likert scale.There were no differences in reflection, means for theoretical contextualization were in the middle range. The lowest means were observed in ig1 , followed by the mean values of cg , and finally, the highest mean values were in ig2 . The means of theoretical evaluation were, in general, higher than those of theoretical contextualization. Moreover, a similar picture emerges in all groups as in the scale theoretical evaluation. The lowest mean values were observable in ig1 . This was followed by the mean values of cg , and finally, the highest mean values were in ig2 .Concerning control variables were collected at one measurement point. First, reflection skills (pretest) showed high means, with the highest values in ig1  and cg , compared to ig2 . There were high standard deviations in all groups. Second, 42.1% in ig1, 54.4% in ig2, and 56.5% in cg indicated students’ previous experience in analyzing video lessons (pretest). Third, interest and relevance (posttest) showed the highest mean values in ig2 , compared to cg  and ig1 . All mean values were in the higher range of the 5-point Likert scale.The 5.2.N = 72) shows no significant overall improvement in self-efficacy (p = 0.228), but a significant interaction effect between measurement repetition factor and grouping factor  with a medium effect size (d = 0.71). The calculation of single ANOVAs with repeated measures for the different groups showed that differences between Pretest and Posttest 2 were significant only in ig2  and showed a medium effect (d = 0.680). Even after the Bonferroni correction, the effect was significant. In ig1 (p = 0.253) and cg (p = 0.871) there are no significant changes . The calculation of a two-factor repeated measures ANOVA  = 4.68, p = 0.017, d = 0.51], but no significant interaction of emotion and the group factor . There was no significant main effect  and no interaction effect  for negative emotional arousal (see It was assumed that participants in both intervention groups (ig1 and ig2) experienced more positive and negative emotional arousal than participants in cg. The two-factor ANOVAs with repeated measures show a significant overall improvement in positive emotional arousal  and no significant interaction of reflection and the group factor . A similar model emerges concerning theoretical evaluation. There are no significant main  or interaction effects , but medium to high effect sizes. This is why the contrast comparison was calculated. There is a significant contrast comparison (p < 0.001) with a high effect size (d = 4.50) between ig2 and the other groups  for changes in self-efficacy (model 2). The added control variables of prior experience in analyzing video lessons (model 3), reflection skills (model 4), and interest and relevance (model 5) had no significant effect. Since the model quality does not change due to the addition of the control variables, it can be assumed that model 2 is the most informative as it explains most of the variance with only a few variables. While there are no effects of emotional arousal on self-efficacy, reflection is a significant predictor of self-efficacy. Therefore, hypothesis 4a must be rejected and hypothesis 4b may be accepted.Model 1 shows that neither positive nor negative emotional arousal are significant predictors for changes in self-efficacy. However, reflection  is a significant predictor . The results can also be partially attributed to the scale being limited to four rating options. Similar mean values are shown concerning the reflection scales. In all groups, the students rated their reflection concerning theoretical contextualization and theoretical evaluation as medium to high. In general, participants in all groups experience a higher positive emotional arousal compared to negative emotional arousal. This finding is in line with previous research studies, which also found more positive emotions than negative emotions in the context of video lesson analysis compared to a text-based control group cf., . HoweverThis study investigated changes in self-efficacy as a result of the video-based intervention. We found students’ self-efficacy increased, with a medium effect size, while analyzing video lessons with structured observation tasks. This result is in line with other studies, which reported that domain-specific self-efficacy increased through video-based interventions . Howevercf., The second area of investigation focused on the role of emotions and reflection during the intervention. Contrary to our expectations, there were no significant differences in positive emotional arousal or negative emotional arousal between the intervention groups  and the control group . However, there were descriptive differences that did not achieve the level of significance. This descriptive result is in line with the findings of In this study, we investigated the differences in depth of reflection between the intervention group with structured observation tasks, and two other groups with open-ended observation tasks (text-based and video). We assumed that students who analyzed the video lessons with structured observation tasks would show a higher depth of reflection. As expected, our results demonstrate partly that there are significant differences in reflection between the groups concerning open-ended observation tasks and the group concerning structured observation tasks. One possible explanation for this finding is that structured observation tasks lead to a deeper reflection compared to open-ended observation tasks. This assumption is supported by empirical work showing a greater depth of reflection among in-service teachers viewing their teaching (video) and completing structured observation tasks. Overall, these findings confirm the assumption that both the use of video lessons, particularly instructional embedding, are helpful for student learning e.g., . Our resAnother area of investigation focused on the relationship between emotion and reflection. In this study, a significant relationship between reflection and positive arousal was found. There was no relationship between negative emotional arousal and reflection. This result goes against the findings of The final area of investigation focused on the role of emotions and reflection for changes in self-efficacy during video-based interventions. As expected, our results show that reflection has a significant effect on changes in self-efficacy. However, emotional arousal was not predictive of changes in self-efficacy. This means that students with deeper reflection showed a greater increase in self-efficacy. One possible explanation for the low emotional arousal in our study is that students have too little experience with teaching. Students at the beginning of their teacher education program see less personal connection in typical classroom situations. It can be assumed that these findings might change with different video material e.g.,  or with 6.1.N = 107), which was calculated in advance using G*Power analyzes, could not be reached because 39% of students dropped out. We believe that with a larger sample, results with medium effects that did not show significant p-values in the current study would have been significant. Second, dropout analyzes showed no differences in study duration, prior experience, and self-efficacy, but there may be differences in students’ motivation. Many participants in the video group with structured observation tasks ended the intervention early. One possible explanation is that students probably worked more intensively and longer with the videos may be due to the more detailed observation tasks than students in the other groups (open-ended observation tasks), which is why they dropped out early. Future research studies could attempt more balance between groups and use incentives. Third, the data from self-report instruments may have been biased due to socially desirable responses as well as students´ lack of practical experience, which could have led to results that differ from those obtained using other methods such as behavioral observation. Fourth, the validity of the self-developed reflection scale was not verified. Fifth, only the area of theoretical reflection was observed. It seems worthwhile to evaluate different levels of reflection more objectively  and in more detail ” project. The funders had no role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript. The authors are responsible for the content of this publication.The 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.