Apis mellifera, are currently facing drastic colony losses, some of which lies partially on the infestation by a parasite, varroa destructor. To maintain healthy honey bee colonies breeding for resistance to this infestation seems promising. However, measuring resistance is a tedious task as it is a complex process. One can consider a honey bee colony resistant to varroa infestation when the parasite fails reproducing and thus its population does not grow in the colony, this is called mite non reproduction. In this study we dissected the performance of a scoring method for mite non reproduction and compared it to other known methods to measure resistance. Although the mite non reproduction method is preferred for field studies because of its relative simplicity it appears to lack correspondence with other methods and it should be interpreted cautiously because it is variable. Even though resistance to varroa infestation is desired for breeding decision it should be done carefully when the way to measure such resistance is using the mite non reproduction method. Honey bees, In the current context of worldwide honey bee colony losses, among which the varroa mite plays a major role, the hope to improve honey bee health lies in part in the breeding of varroa resistant colonies. To do so, methods used to evaluate varroa resistance need better understanding. Repeatability and correlations between traits such as mite non-reproduction (MNR), varroa sensitive hygiene (VSH), and hygienic behavior are poorly known, due to practical limitations and to their underlying complexity. We investigate (i) the variability, (ii) the repeatability of the MNR score, and (iii) its correlation with other resistance traits. To reduce the inherent variability of MNR scores, we propose to apply an empirical Bayes correction. In the short-term (ten days), MNR had a modest repeatability of 0.4, whereas in the long-term (a month), it had a low repeatability of 0.2, similar to other resistance traits. Within our dataset, there was no correlation between MNR and VSH. Although MNR is amongst the most popular varroa resistance estimates in field studies, its underlying complex mechanism is not fully understood. Its lack of correlation with better described resistance traits and low repeatability suggest that MNR needs to be interpreted cautiously, especially when used for selection. Apis mellifera colony losses is multifactorial, the parasite Varroa destructor contributes significantly to the weakening of honey bee populations [A. mellifera colonies, with only a few documented exceptions, are dependent on human intervention to survive mite infestations [Today, there is a common consensus that, while the origin of worldwide ulations ,2. The vulations ,4,5. Curstations ,6,7. Howstations . Furtherstations .A. mellifera colonies that do not require acaricide treatments to survive V. destructor infestation were discovered [A. mellifera populations has been confirmed in different regions of the world [A. mellifera colony, the varroa mite population size typically increases exponentially during the season due to the varroa foundresses being able to produce several fertile daughters during several reproductive cycles [V. destructor by maintaining low varroa levels on their own (resistance) [In the 1990s, scovered ,11. Sinche world . This hahe world . In an Ae cycles . Contraristance) . The selistance)  and the One of the important traits identified was termed suppressed mite reproduction (SMR) . It was We believe that the MNR measurement is indispensable to the continuation of comprehensive research on bee resistance to the varroa mite in the future as well as contributing to a successful and pertinent selection of resistant honey bees. However, we are in urgent need of a standard protocol to be used worldwide. Therefore, we aim in this study to validate an MNR protocol and point out the constraints and opportunities of this method to encourage its use in the future.This study investigates (i) the variability of the MNR score (formerly SMR) obtained using the reference protocol, (ii) the repeatability of the MNR trait in comparison with other resistance traits, and (iii) the correlation between MNR and other resistance traits. For this purpose, a total of 275 honey bee colonies was used. All colonies were located in the facilities of Institut Technique et Scientifique de l’Apiculture et de la Pollinisation (ITSAP) and Institut National de Recherche pour l’Agriculture, l’alimentation et l’Environnement (INRAE) ; they were closely monitored for colony dynamics, varroa infestation, and varroa resistance behaviors from 2016 to 2019 , MNR was tested every 10 days for 30 days, thus three times at the end of the beekeeping season for 31 colonies; in the second set of measures (long-term repeatability), MNR was measured between one and five times across the beekeeping season, for 55 colonies.The MNR measurement protocol can lead to a theoretical error of up to 20% in MNR scores . To valiHygienic behavior was tested using the pin-test protocol ,41. ThisVarroa sensitive hygiene (VSH) was measured at the end of the beekeeping season by artificial infestation  in 26 coColony dynamics were monitored using the ColEval method . The numVarroa mite infestation and dynamic were measured in two different ways. First of all, varroa infestation in the brood was measured simultaneously to MNR scoring, as this measure produces an estimation of brood infestation. Secondly, phoretic varroa load was measured using the detergent method ; the numAll statistical analyses and visualizations were executed using R 3.6.2 .is is the sample standard deviation over k colonies.MNR score minimum, mean, and maximum were estimated for the resampling of 10, 35, 50, and 80 cells infested by a single varroa foundress as well as for the first MNR score (corresponding to the first 35 cells dissected) and the total MNR score. Pooled standard deviation, for samples of identical sizes, for the resampled colonies was estimated as follows:Finally, the coefficient of variation (CV), for re-sampled colonies, was estimated as follows:k colonies, as for the standard deviation in Equation (1). Exponential regressions were fitted on the average CV for the MNR score. CVs were predicted, using the package car [The coefficient of variation (CV) is commonly used to assess the precision of an estimate as it is a ratio of deviation to the mean. This estimate was pooled across the kage car , for a nn = 82). To avoid discarding such data points, we applied an empirical Bayes correction, equation (3), as proposed by Mondet et al. 2020 [c as the number of dissected cells infested by a single varroa foundress, nr as the number of non-reproductive mites, and MASS [Bias in MNR score is highly dependent on the number of cells infested by a single varroa foundress that one can find on the selected brood frame. The COLOSS protocol recommends the dissection of a minimum of 35 such cells. Leaning towards the application of this protocol, we managed to score MNR on 35 cells or more (up to 49 cells) in 81% of the tested colonies. However, due to low infestation levels and/or low amounts of capped brood in some colonies, the MNR score was measured on between 34 and as little as one cell infested by a single varroa foundress for 19% of the frames  and long-term (multiple EB_MNR scores within a year) EB_MNR scores, as well as for hygienic behavior (HYG), as the following:p-values adjusted for multiple testing by the Bonferroni correction. The correlation between VSH and EB_MNR was estimated using a Spearman rank correlation.The cleaning of infested brood cells (VSH) was tested with an exact binomial test, with missMDA package [The effects of variables linked to scoring period , location , beekeeper groups and queen origin, experimentation (observer), colony dynamics, and varroa infestation were tested for EB_MNR and HYG. For EB_MNR, nine qualitative and nine quantitative variables were tested using 446 observations on 231 colonies, and for HYG, five quantitative and seven qualitative variables were tested using 375 observations on 175 colonies. When testing EB_MNR and HYG, in order to obtain a complete dataset, missing data for the qualitative variables were set as “unknown” and missing data for the quantitative variables were imputed using the Factor Analysis of Mixed Data (FAMD) imputation function  from the lmerTest package in R [p-values from the model and the significance of the random effects was inferred using confidence intervals, computed with the confint function (lme4 package in R [We performed a backward model reduction on the two datasets (function step from age in R ), as sugage in R , by firsage in R ).n = 39), and 80 cells (n = 32) infested by a single varroa foundress. The MNR score based on the first 35 cells, equivalent to the scoring in the field throughout the experiment, ranged from 0.17 to 0.69, with a mean of 0.39 and a standard deviation of 0.14.Variance of the MNR score (formerly SMR) was estimated by 100 resampling events, for 10, 35, 50   ranged from 0.08 to 0.79. Both raw MNR and EB_MNR have a mean of 0.41, which is expected when applying the empirical Bayes correction as it is equivalent to shrinkage of the data, therefore reducing the dispersion of the data but not affecting its mean. As expected when performing such corrections, the Spearman rank correlation between EB_MNR and raw MNR score was 0.99 (< 10−16) . ThereafRepeatability is a measure of the likelihood of obtaining multiple times the same result. The higher the repeatability, the more likely we are to obtain multiple times the same value—in our case, the same EB_MNR score.EB_MNR short-term repeatability, as estimated by three measures once every 10 days, was 0.43 . Intra-colony variance could be clustered, using k-means, in three groups having average variances of EB_MNR score of 0.034 , 0.011 , 0.003  . Long-teHygienic behavior ranged between 0 and 1, with a mean of 0.74. Hygienic behavior measured multiple times within a year had a repeatability of 0.21 .VSH, measured by artificial infestation on 26 colonies, ranged between 0.10 to 0.97 cleaning rate, with a mean of 0.40 and a median 0.36. Three colonies had a significantly low VSH, meaning that less brood cells were cleaned than expected under the null hypothesis of 0.40 cleaning (the mean VSH score of the tested colonies), whereas four colonies had a significantly higher VSH, meaning that more brood cells were cleaned than expected under the null hypothesis .p-value = 0.29)  and VSH, as both measures were made for the colonies of interest on the same date, while on the same apiary and after the exact same treatment throughout the experiment . Having the two measures scored in the same conditions enables direct comparisons free from external effects. There were no correlations between EB_MNR and VSH  .Variables retained as random effects in the best model were scoring period, breeder’s group, and the observer, while variables retained as fixed effects were the amount of honey in the hive and the recapping behavior of the colony. Overall EB_MNR was significantly influenced by the random effects of scoring period and breeder’s group, with the breeder’s group INRAE, having “survivor” colonies kept for at least three years , presentVariables retained as random effects in the best model were queen’s genetic origin and the testing apiary, while the only variable retained as a fixed effect was the phoretic varroa infestation level, being the only one linked to varroa infestation level in the colony available for HYG measure. Overall, HYG was significantly influenced by the testing apiary and the varroa infestation. The fixed effect linked to varroa infestation was negative , meaningIn this study, we aimed at describing the MNR, more pertinent than the previously known SMR, as the current protocols lead to a large variation in MNR scores. This variation can be lessened by increasing the number of dissected cells or, if this does not lie in the scope of the study, by applying an empirical Bayes correction. MNR short-term repeatability was larger than long-term repeatability, the latter being similar to the repeatability of hygienic behavior. Finally, no correlation between MNR and VSH could be observed in our dataset. This in-depth analysis of mite non-reproduction (MNR) highlights several points that need to be considered when using this trait for experiments and breeding efforts.The current guidelines proposed by COLOSS  for MNR Questions arose especially for colonies with a small number of cells infested by a single varroa foundress. These colonies have the potential to be particularly interesting, as the low varroa load could point to a resistance to infestation. Two approaches can be used to deal with such data: one is to set a cut-off for the number of cells infested by a single varroa foundress necessary to validate the subsequent MNR score and the other is to apply an empirical Bayes correction to the raw MNR scores, leading to shrinkage in MNR score distribution. The first strategy is likely to be preferred by professional beekeepers due to its simplicity, whereas the second might be preferred for research purposes as it avoids the application of arbitrary thresholds. However, both lead to the rejection of the colonies with extreme MNR scores, one by removal and the second by fading due to the shrinkage. This means that potentially resistant colonies are not being taken into account because they cannot be properly evaluated due to a low varroa load. One solution could be to artificially control the hive varroa infestation. However, this could cause bias in the MNR scoring procedure. To date, there has been no strategy developed to counter this bias; we recommend future studies to focus on estimating sampling bias by dissecting an extensive number of cells, ideally full frames without applying cut-off or by carefully combining MNR trait with other traits of the colony. However, the development of such an index relies on a thorough understanding of the different traits to combine and their interactions.The results presented here also highlight the fact that short-term repeatability  of MNR was modest, whereas long-term repeatability (within years) measurements were relatively low, although comparable to those of hygienic behavior ,52, a maThe low repeatability may be partially explained by the variance of estimates described above , meaning that the resistance score of a colony could be much more congruent than what we see in our dataset. A shortcoming of our study is the lack of consideration of environmental variables. However, it is known that environmental variables such as temperature and humidity can potentially affect resistant traits ,55, withAll of the above demonstrate that MNR is a complex mechanism combining multi-factorial effects, such as adult bee behavior, brood and mite physiology, and bee and mite genetics. There is an urgent need for further analysis to disentangle potential environmental effects on the MNR mechanism. We can also assert that experimental design is one of the major limitations to drawing solid conclusions. The lack of balance in the experimental design can lead to spurious effect estimation and interpretations. Controlling the experimental design is somehow difficult in the field but should be evaluated upstream at the research facilities. Lastly, even though we could observe significant differences between VSH across our colonies, contrary to what has been previously found by Harbo and Harris , no corrIn conclusion, the MNR measurement remains one of the few measurements for varroa resistance in honey bee populations, which can be achieved in the field on a relatively large scale. Although time consuming and tedious to implement, it also gives a lot of different information which can help us to better understand the control mechanisms that bees use to counteract the varroa mite. However, the results here highlight the need for a precise protocol using enough single infested cells (>35), performed multiple times over a short period of time to provide solid estimates. The weak points should be taken into consideration when designing an experiment, and a combination of different measurements to correctly assess honey bee resistance like mite infestation levels (inside and outside the brood cells) and genetic analysis could be additionally taken into account when analyzing the varroa resistance of a colony. To date, no breeding programs aiming at obtaining resistant honey bees have produced commercially available colonies. We believe that using the MNR measurement with a new awareness of its weaknesses and strengths could be an important tool for successful future selection programs of resistant honey bees.


To assess what factors were associated with reported changes to usual alcohol drinking behaviour during the start of lockdown in the United Kingdom (UK).Online cross-sectional survey of 30,375 adults in the UK from 21st March to 4th April 2020 (sample weighted). Logistic regression models were used to examine sociodemographic, drinking and COVID-19 factors associated with i) drinking less and ii) drinking more .Of 22,113 drinkers, 48.1 % reported drinking about the same, 25.7 % reported drinking less, and 26.2 % reported drinking more than usual over the past week. Drinking less was independently associated with being younger , male , BAME , low income , having COVID-19 , adhering to COVID-19 protective behaviours , stress about becoming ill from COVID-19  and not being a key worker . Drinking more was independently associated with being younger , female , post-16 qualifications , high income , stress about catching  or becoming ill from COVID-19 , stress about finances , and having an anxiety disorder .In a large, population sample of adults in the UK, around a quarter of drinkers reported drinking more alcohol and a quarter drinking less than usual during the COVID-19 related lockdown. Certain groups, such as those who are younger, female, of high socioeconomic position, have an anxiety disorder, and are stressed about finances or COVID-19 may need targeted alcohol reduction support during lockdown. Reducing alcohol consumption remains a public health priority , and pubn>20,000) in England showed a substantial increase in the prevalence of high-risk drinking since the lockdown alongside an increase in attempts to reduce alcohol consumption among high-risk drinkers  enforceable by law were introduced on 23rd March. Many businesses, including pubs, bars and restaurants, were temporarily closed, and the public were advised to only leave their home for essential journeys and exercise. Early data have indicated that the COVID-19 pandemic has had an impact on people’s alcohol consumption. A large, representative study of adults  associated with sociodemographic characteristics, diagnosed or suspected COVID-19, adherence to COVID-19 protective behaviours, significant stress about catching or becoming seriously ill from COVID-19, significant stress about finances, significant stress about boredom, recent drop in household income, key worker status, or health conditions?2Is heaviness of drinking in the past week associated with sociodemographic characteristics, diagnosed or suspected COVID-19, adherence to COVID-19 protective behaviours, significant stress about catching or becoming seriously ill from COVID-19, significant stress about finances, significant stress about boredom, recent drop in household income, key worker status, or health conditions?In summary, there is a need for population-based evidence on the factors associated with changes to usual drinking and heaviness of drinking during COVID-19 related social distancing and lockdown in the UK. This study used cross-sectional data from a large well-phenotyped study of adults during the first few weeks of social distancing and lockdown in the UK to answer the following research questions:22.1We carried out a cross-sectional analysis of baseline survey data from the University College London (UCL) COVID-19 Social Study assessing alcohol consumption and measures relating to COVID-19 in the UK for participants recruited between 21st March and 4th April 2020.www.covidsocialstudy.org.The UCL COVID-19 Social Study is a large panel study of the psychological and social experiences of adults (aged 18+) in the UK during the COVID-19 pandemic. The baseline survey from the study assessed a range of factors including sociodemographics, health, alcohol consumption, confirmed and suspected COVID-19, and behaviours and attitudes relating to COVID-19. Although participant recruitment was based on a multistage nonrandom sampling approach, the sample was designed to have broad representation across sociodemographic characteristics. Participants were recruited using three primary approaches. First, snowballing was used, including promoting the study through existing networks and mailing lists, print and digital media coverage, and social media. Second, more targeted recruitment was undertaken focusing on (i) individuals from a low-income background, (ii) individuals with no or few educational qualifications, and (iii) individuals who were unemployed. Third, the study was promoted via partnerships with third sector organisations to vulnerable groups, such as adults with pre-existing mental health conditions, and carers. The data are weighted to account for the non-random nature of the sample. For full details on the recruitment strategies and weighting for the study, visit 2.22.2.1Changes in drinking over the past week during social distancing and lockdown was measured with the question: “Over the past week have you drunk alcohol more than usual?” with response options: a) less than usual; b) about the same; c) more than usual; and d) I don’t drink alcohol. Only drinkers  were included in the analysis of changes in drinking. For analysis of drinking less or more than usual, those who responded ‘b’ were coded 0 and those who responded ‘a’ or ‘c’, respectively, were coded 1.2.2.2Heaviness of drinking in the past week was assessed using the question: “How many alcoholic drinks have you had in the past week (e.g. how many glasses of wine / pints of beer or cider / shots of spirits)?” with continuous response options from ‘0’ through to ‘21+’.2.2.3Sociodemographic characteristics included were: age (continuous in years), sex , ethnicity  groups), level of education , and annual household income . Level 2.2.4Participants were asked: “Have you had COVID-19 (coronavirus)?” with response options a) yes diagnosed and recovered, b) yes diagnosed and still ill, c) not formally diagnosed but suspected, d) no. Diagnosed or suspected COVID-19 was coded 1 for those who responded ‘a’, ‘b’ or ‘c’ and 0 for those who responded ‘d’.2.2.5Adherence to COVID-19 protective behaviours was assessed with the question: “Are you following the recommendation from authorities to prevent spread of COVID-19?” with responses on a scale from 1  to 7 (very much so). Responses of 5 and above were coded 1 (indicating adherence) and responses of 4 and below were coded 0.2.2.6Stress about COVID-19, finances or boredom was assessed with the question: “Have any of these things been causing you significant stress? (e.g. they have been constantly on your mind or have been keeping you awake at night)”. Response options included i) catching COVID-19, ii) becoming seriously ill from COVID-19, iii) finances, and iv) boredom. For each of these four response options, a variable was created where those who reported stress about the relevant outcome were coded 1, else they were coded 0.2.2.7Recent drop in household income was assessed with the question “Have you experienced any of the following in the past week?”. Those who reported ‘lost your job/been unable to do paid work’, ‘your spouse/partner lost their job or was unable to do paid work’ or ‘major cut in household income (e.g. due to you or your partner being furloughed/put on leave/not receiving sufficient work)’ were coded 1 for recent drop in household income and those who reported none of these were coded 0.2.2.8Key worker status may be associated with increased exposure to COVID-19. Participants were asked: “Are you currently fulfilling any of the government’s identified ‘key worker’ roles?” Participants were coded 1 if they selected any of the ‘key worker’ roles  and those who responded ‘none of these’ were coded 0.2.2.9The presence of health conditions was assessed with the question: “Do you have any of the following medical conditions?” Those who selected ‘high blood pressure’, ‘diabetes’, ‘heart disease’, ‘lung disease (e.g. asthma or COPD)’, or ‘cancer’ were coded 1 and those who selected none of these were coded 0. These health conditions were included because people with these chronic conditions may be more likely to experience severe COVID-19 symptoms . The pre2.2.10Survey date was coded 0 for those surveys completed on 21st, 22nd or 23rd March (i.e. prior to lockdown commencing), and subsequent dates were coded 1, 2, 3,…, n (i.e. reflecting the progression of time from the start of lockdown).Full details of all of the measures is available in Supplementary File 1.2.3https://osf.io/pnrhq/). Analyses were conducted using R studio on complete cases. To account for the non-random nature of the sample, all data were weighted to the proportions of sex, age, ethnicity, education, and country of living obtained from the Office for National Statistics  of those who reported drinking more than usual, about the same as usual, and less than usual over the past week was calculated. The mean (and standard deviation [SD]) of heaviness of drinking in the past week was calculated.Generalized linear modeling  was used to examine unadjusted and adjusted associations of associations between i) drinking less than usual , ii) drinking more than usual , and iii) heaviness of drinking with the following: age, sex, ethnicity, education level, income, diagnosed or suspected COVID-19, adherence to COVID-19 protective behaviours, significant stress about catching COVID-19, significant stress about becoming seriously ill from COVID-19, significant stress about finances, significant stress about boredom, recent drop in household income, key worker status, presence of health conditions and anxiety disorder, and survey date. The multivariable model was fully adjusted for all of the predictor variables listed. The continuous variable age was transformed by dividing the original variable by the SD to express the variable as a proportion of the SD for ease of interpretation of the odds ratio. Sensitivity analyses were conducted for the associations with heaviness of drinking where the response option ‘21+’ was excluded as this is a non-linear response option.2.4Ethical approval for the COVID-19 Social Study was granted by the UCL Ethics Committee [12467/005]. All participants provided fully informed consent. The study is GDPR compliant.33.1n = 30,516) provided complete data on the variables included in the present analyses. Of the analysed sample, 22,113 were drinkers . Participant characteristics are shown in A total of 33,644 participants responded to the survey between 21st March and 4th April 2020, of whom 30,375 , 48.1 %  reported drinking about the same as usual, 25.7 %  reported drinking less than usual, and 26.2 %  reported drinking more than usual over the past week.Of the 22,113 drinkers . Heaviness of drinking in the past week was independently positively associated with being older, male, white ethnicity, having post-16 education qualifications, having an annual household income over £30,000, not adhering to COVID-19 protective behaviours, not being significantly stressed about catching COVID-19, a recent drop in household income, not being a key worker, not having physical health conditions or a diagnosed anxiety disorder, and with survey date .Table 4FSensitivity analyses were conducted in which the non-linear response option ‘21+’ was excluded (reported in Supplementary Table 4) and the pattern of results remained similar. Unweighted analyses are reported in Supplementary Table 5 and the pattern of results is broadly similar.4Among a large, population sample of 30,375 adults in the UK surveyed in the first two weeks of national COVID-19 related social distancing and lockdown restrictions, adults drank a mean of 4 alcoholic drinks in the past week with almost a third not drinking (34.3 %). Among people who drank, 48 % reported drinking about the same, 26 % reported drinking more and 26 % reported drinking less than usual over the past week. These findings are in line with those from other recent surveys .Younger drinkers were more likely than older drinkers to report changes in their drinking behaviour during lockdown (both drinking less and drinking more over the past week), which is consistent with previous findings . YoungerWomen were more likely to report drinking more than usual and men were more likely to report drinking less than usual during lockdown. The latter finding is consistent with two previous surveys . Women mDrinkers with a low income were more likely to be drinking less than usual, whilst those with a high income and post-16 education qualifications were more likely to be drinking more than usual over the past week, and more heavily. Previous surveys have also found that a greater proportion of those of high SEP reported drinking more during lockdown than those of low SEP . This isBAME groups were more likely than those of white ethnicity to be drinking less than usual. Being of white ethnicity was positively associated with heaviness of drinking, which is in line with previous surveys from before the COVID-19 pandemic . Some BAWe also found that psychological factors predicted changes in drinking behaviours. Stress about catching COVID-19, becoming seriously ill from COVID-19 and finances were all associated with drinking more than usual over the past week, and stress about catching COVID-19 and experiencing a recent drop in household income were also positively associated with heaviness of drinking. This is in line with previous research showing that stress is a risk factor for the onset of alcohol misuse . HoweverExploring mental health more broadly, having a diagnosed anxiety disorder was associated with drinking more than usual though was negatively associated with heaviness of drinking, along with having a physical health condition. It is possible that people with anxiety disorders are changing their drinking behaviour to self-medicate  or as a 4.1A key strength of this study was the large sample size and broad range of measures collected, permitting this detailed analysis of potential factors predicting drinking behaviour during the start of social distancing and lockdown in the UK. The collection of data in real time while the pandemic was at a peak in late March and early April was also a strength, minimising potential recall bias that is likely to be present in any future studies that collect data retrospectively. Another major strength of this study was being able to assess how sociodemographic characteristics and COVID-19-related impacts, such as key worker status, were associated with changes in alcohol consumption – an important area of research highlighted in a recent report by the Institute of Alcohol Studies .A limitation of this study relates to the alcohol consumption measures used. The measure of changes in drinking over the past week did not distinguish between changes in frequency of consumption, quantity per occasion or heavy episodic drinking, which is an important topic for future research. Furthermore, the changes in drinking measure used the reference ‘usual drinking’ rather than specifying before lockdown. We have assumed that participants interpreted ‘usual drinking’ as meaning before lockdown restrictions were introduced as the study period was chosen as the start of social distancing and lockdown in the UK. The measure of heaviness of drinking asks about the number of alcoholic drinks consumed and therefore the overall index does not directly correspond with standardised units. As the survey was conducted at the start of lockdown and the heaviness of drinking measure refers to the past week, the associations detected may reflect the characteristics of people who were drinking alcohol more heavily prior to the COVID-19 pandemic rather than as a response to the lockdown in the UK. However, it was still important to consider the heaviness of drinking as this gives an important indication for the public health implications of respondents’ alcohol consumption.The study did not include a measure of baseline alcohol consumption, although it did ask about consumption in the previous week, which occurred before lockdown came in and focused on drinking behaviour during the first few weeks of lockdown in March 2020. Future studies with prior data may be able to ascertain how long-term trajectories of alcohol consumption were affected by the pandemic. Whilst we do not know the prevalence of high-risk drinking in this sample, our finding that 26 % of adults in the UK reported drinking more could be reconciled with data on the change in high-risk drinking prevalence in England , particu4.2This study has important implications in terms of groups that may need targeted support for alcohol reduction to counteract an increase in drinking during the start of the COVID-19 related lockdown. With one in four drinkers reporting an increase in consumption since lockdown began, these findings emphasise the need for alcohol reduction support with a focus on those groups who are drinking more than usual and drinking heavily. This may be particularly important if a second wave of COVID-19 results in another lockdown. However, more research is needed to understand whether these changes have been sustained or whether people’s drinking have returned (or will return) to usual levels as they gradually resume their normal lives. Heaviness of drinking was positively associated with survey date indicating that heaviness of drinking increased with the time spent in lockdown, therefore it’s important to establish whether any initial changes during the start of lockdown continued, or possibly were even exacerbated.5About half of adult drinkers in the UK reported drinking about the same as usual, a quarter reported drinking more than usual, and a quarter reported drinking less than usual over the past week during the start of the COVID-19 related lockdown. Drinking more than usual during the start of lockdown was associated with being younger, female, of high SEP, having an anxiety disorder, being stressed about finances, or being stressed about catching or becoming seriously ill from COVID-19. This highlights that there are certain groups who need alcohol reduction support during lockdown and to whom it might be particularly important to target support for if there is a second wave of COVID-19.The funders had no final role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. All researchers listed as authors are independent from the funders and all final decisions about the research were taken by the investigators and were unrestricted.All authors conceptualised the study, and contributed to and approved the final version of the manuscript. CG drafted the manuscript and conducted the data analysis.CG, SJ, MO, AS and DF declare no conflicts of interest. JB has received unrestricted research grants from Pfizer related to smoking cessation.


Mycobacterium marinum is a free-living nontuberculous mycobacterium that is widely distributed in freshwater and seawater around the world. Granulomatous skin infection from M. marinum in people who are exposed to fish or aquatic environments is a rare condition known as fish tank granuloma. The granuloma mainly occurs on the skin of the upper limb, in a few cases on the face, and rarely in the nasal cavity. We describe a case of M. marinum infection that presented as a nasal cavity mass. A 57-year-old woman who was receiving infliximab for psoriatic arthritis visited our hospital with a complaint of right nasal obstruction. A granulomatous mass with an irregular surface was found in the anterior part of the right nasal cavity. Tissue biopsy revealed granulation tissue. Since the application of steroid ointment did not reduce the size of the mass, the tumor was resected under local anesthesia, and the base was cauterized. The pathological finding was an inflammatory granuloma with negative Ziehl–Neelsen staining. The granuloma recurred 3 months after resection. The interferon-gamma release assay (IGRA) test was positive, and therefore, a mycobacterial tissue culture test was performed because of suspected nasal tuberculosis, which identified M. marinum. The nasal cavity mass disappeared 2 months after the administration of minocycline, followed by clarithromycin, and subsequent discontinuation of infliximab. M. marinum infection can cause an intranasal mass. IGRA and the mycobacterial tissue culture test are useful for diagnosis. As in this case, the nasal lesion may be excised as an inflammatory nasal granuloma, and therefore, there may be many more “hidden” cases of M. marinum infection. If nasal granulation is present, the possibility of M. marinum infection should be considered. Mycobacterium marinum, which mainly lives in water, accounts for the majority of nontuberculous mycobacteria infections occurring in the skin. In the United States, the incidence of cutaneous nontuberculous mycobacterial infection between 1990 and 2009 was 1.3 per 100,000, of which 45% were M. marinum infections [M. marinum that causes a mass or ulcer on the skin of people who are exposed to aquatic environments including fish tank water [M. marinum infections occur on the upper limbs, and a few occur on the face [M. marinum infections have been reported as intranasal lesions [M. marinum infection that presented as a nasal cavity mass. Interferon-gamma release assay (IGRA) was important for diagnosis. This paper is a rare case report of this infection in the nasal cavity.Infections by nontuberculous mycobacteria are increasing with the increase in the number of patients who use immunosuppressive agents, including antitumor necrosis factor (anti-TNF) biologics , 2. Myco lesions , 7. We rThe limitation of this study is that this is just a single case report, and the detailed epidemiological date including prevalence of the disease in the nasal cavity is not clearly identified. It should be done for confirmation in the future epidemiologic studies.Mycobacterium avium complex were negative. Individual orange-yellow colonies developed after 8 weeks of incubation on liquid (MGIT) media at 37°C and after 3 weeks of incubation on 2% Ogawa egg medium at 30°C. M. marinum was identified using matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry. The lesion disappeared 2 months after administration of oral minocycline  followed by oral clarithromycin  and discontinuation of infliximab .M. marinum infection can cause an intranasal mass, and IGRA and the mycobacterial tissue culture test are useful for diagnosis.The course of this patient resulted in two important clinical suggestions: M. marinum infection can cause an intranasal mass. According to a recent review [M. marinum infections occur in the upper limbs, and there are few facial lesions. Only a few cases have been reported as intranasal lesions [M. marinum exists widely in freshwater and seawater, the infection often occurs in people who engage in fish-related occupations or tropical fish breeders cleaning the fish tank with minor wounds on the upper extremities. In the present case, it is unknown why the lesion occurred in the nasal cavity, but since it developed during the season of Japanese cedar pollinosis, it is possible that the infection occurred from a slight scratch on the nasal vestibular skin and nasal mucosa by the wet hands with contaminated fish tank water, such as from blowing the nose.First, t review , 93% of  lesions , 7. SincM. tuberculosis that was completely lacking in bacillus Calmette–Guérin (BCG) was identified [M. tuberculosis-specific proteins such as early secreted antigenic target 6 (ESAT-6), culture filtrate protein 10 (CFP-10), tuberculosis 7.7 (TB 7.7), and others coded in that area were identified. Because IGRA measures the reaction of interferon-gamma with ESAT-6/CFP-10, it is not affected by BCG vaccination and is widely used as a screening test for tuberculosis infection. Most nontuberculous mycobacterial infections are negative for IGRA, but some nontuberculous mycobacteria, including M. marinum, may be positive for IGRA [M. marinum, like M. tuberculosis, possesses a functional ESX-1 (ESAT system-1) secretion system that exports ESAT-6 and CFP-10. Therefore, when IGRA is positive, not only M. tuberculosis but also M. marinum infection should be considered.Second, IGRA and mycobacterial tissue culture were useful for the diagnosis. When the nasal granuloma is found, it is necessary to distinguish malignant tumors, such as cancer and malignant lymphoma, from benign tumors, such as hemangiomas, polyangiitis granulomatosis, sarcoidosis, and nasal tuberculosis. In this case, we suspected nasal tuberculosis from the positive IGRA test and confirmed the diagnosis by performing tissue culture of mycobacteria. In the 1990s, a gene sequence region of entified . M. tubeM. marinum infection, the presence of mycobacteria cannot be confirmed by pathological examination [In many cases of mination –14, and The number of nontuberculous mycobacterial infections is increasing with the increasing number of patients who use immunosuppressive agents, including anti-TNF biologics . It is nM. marinum infection can cause an intranasal mass. IGRA and the mycobacterial tissue culture test are useful for the diagnosis. We must be aware that M. marinum infection can manifest as an intranasal mass. Pathological examination of the nasal lesion revealed only an inflammatory nasal granuloma, not mycobacterial infection, and there may be many more “hidden” cases of M. marinum infection. In the present case, IGRA was important for diagnosis. IGRA should be more widely used, particularly in patients who are taking immunosuppressive agents; however, the gold standard for diagnosis remains mycobacterial culture. If granulomatous lesions are found in the nasal cavity, it is necessary to perform a mycobacterial tissue culture test for the possibility of mycobacterial infection.In conclusion,


In the row for “Black, non-Hispanic,” the numbers under “Past 30 days binge drinking*” should have read


Increasing grain production is essential to those areas where food is scarce. Increasing grain production by controlling crop diseases and pests in time should be effective. To construct video detection system for plant diseases and pests, and to build a real-time crop diseases and pests video detection system in the future, a deep learning-based video detection architecture with a custom backbone was proposed for detecting plant diseases and pests in videos. We first transformed the video into still frame, then sent the frame to the still-image detector for detection, and finally synthesized the frames into video. In the still-image detector, we used faster-RCNN as the framework. We used image-training models to detect relatively blurry videos. Additionally, a set of video-based evaluation metrics based on a machine learning classifier was proposed, which reflected the quality of video detection effectively in the experiments. Experiments showed that our system with the custom backbone was more suitable for detection of the untrained rice videos than VGG16, ResNet-50, ResNet-101 backbone system and YOLOv3 with our experimental environment. The production of crops is of importance, especially to some areas that are particularly lacking in food. The loss of grain caused by crop diseases and pests accounts for more than 10% of the total crop production loss [Rice is the staple food in China. It may be affected by several diseases and insects, such as rice sheath blight, rice stem borer, rice brown spot. The lesion spot of rice sheath blight is cloud-like, grayish-brown in the middle, and the leaves are withered and yellow, which is caused by fungal infection , the patDiseases of rice plants could be affected by different factors, such as climatic conditions, lighting conditions, humidity, nutrients, fertilizer, water management, and farming conditions. Manual identification and detection of those diseases are often time-consuming, and the recognition accuracy may not be high. It may result in incorrect diagnosis and misuse of pesticides. Compared with the traditional image recognition methods, such as histograms of oriented gradients (HOG)  and scalWith the proposal of convolutional neural networks (CNN) , region-The video object detection has also been developed. YOLO  has obtaDespite the success of the above methods, video detection is different from still-image detection in many ways, and often remains challenges such as video defocus, motion blur and part occlusion . The vidDeep learning methods have been used in the recognition and detection of crop diseases ,31,32,33CNN can be trained to learn the features of images, such as pattern, color, and texture . The plaDetection of crop diseases and pests symptoms is always facing difficulties, since the shape of lesion spots is always irregular, and the boundary between spots and surrounding healthy areas is always not obvious. Especially for video detection, the lesion spots would be blurrier in the moving status, and the irregular shape of the spots changes with the change of the camera angle.In this paper, we develop a video detection system for detecting rice diseases and pests symptoms. The proposed system tries the first step of real-time crop lesion video detection. The system contains a frame extraction module, a still-image detector and a video synthesis module. We use still images from our dataset  to trainTo summarize, we make the following contributions in this paper: (1) we try to propose a set of video detection metrics, which is based on machine learning classifier; (2) we propose a custom DCNN backbone, the backbone is used as the first stage of the “two-stage” detector—Faster-RCNN; (3) we build a video detection system for rice diseases and pests.The dataset was composed of images and videos of rice disease and pest lesions, which were collected in Anhui, Jiangxi and Hunan Province, China, between June and August, 2018. The dataset was about rice sheath blight, rice stem borer symptoms, and rice brown spot. These images were taken by mobile phones, such as iPhone7 and HUAWEI P10, and Sony WIFI-controlled camera, whose model type was DSC-QX10. The image resolution of rice sheath blight was 4928 × 3264 pixels as same as the rice brown spot, and the image resolution of rice stem borer symptoms was 2592 × 1944 pixels. The videos were taken only by iPhone7 with 1920 × 1080 pixels per frame, since iPhone often has a clearer video capture. Image and video collection focused on occurrences of heavy infestation.Training data and test data were composed of 1800 images, 1760 images, and 1760 images for rice sheath blight, rice stem borer, and rice brown spot, respectively . 15, 23,The annotation of rice sheath blight is shown in We try to propose a set of evaluation metrics of rice video detection by referring to the image detection metrics . The eva“Number of true spots detected” in Equation (1) denotes correctly boxed lesion spots. “Number of spots detected” in Equation (1) includes the number of correctly boxed lesion spots and wrong boxed spots. “Number of true spots” in Equation (2) include the boxed and unboxed ones. The same spot only needs to be counted once in a video.To simplify the calculation, we only count whether the lesion spots are detected or not. We use the concept of still-image metrics, such as true positive, false positive, true negative, e.g., “number of true spots detected” has the meaning of true positive, as it denotes the correctly boxed lesion spots; “number of spots detected” has the meaning of true positive and false positive, as it denotes correctly boxed lesion spots and wrong boxed spots; “number of true spots” has the meaning of true positive and true negative, as it denotes the boxed and un-boxed lesion spots.The number of spots in our metrics is counted manually at present as the videos are not annotated. To calculate the metrics automatically needs to annotate the videos  manuallyVideo precision measures how many boxed lesion spots are correct. Video recall measures how many correct lesion spots are boxed out. F1 score is a harmonic average of precision and recall, and comprehensively measures precision and recall. The value of the above equations is always less than 100%, because the denominators are always larger than the numerators according to the definition.The literature  uses theThe equations above could be extended to multiple categories of spots, i.e., the number of spots in the equations could be replaced by more categories of spots. The video metrics could be extended to “total videos” or “average metrics”. Total video detection metrics are the sum counting of spots of multiple videos. Average video metrics are the sum of the total metrics divided by the number of the corresponding indices.The structure of our video detection system consists of three parts: (1) frame extraction module which can be set to any time interval; (2) still-image detector, with a custom DCNN as the backbone. The DCNN backbone is composed of 12 convolutional layers, and the dimensions of each convolutional layer is specific; (3) video synthesis module. Generating a frame, detecting a frame and synthesizing a frame to the video are synchronous. The detailed algorithm of the video detection system is shown in the At the beginning of our video detection system, frames are extracted from the input video. Then, the frame just generated is sent to the still-image detector. We extracted every frame in chronological order. The speed was 30 frames per second. The resolution of the generated frame is the same as that of the original video. For the detection of plant lesion spots, reducing the resolution of the image to improve the detection speed, may not be a better choice, because of the irregular shape of the lesion spots and the unclear boundaries of the spots. If reducing the resolution too much, the spots may be much blurrier and harder to detect.The still-image object detector is adapted from Faster-RCNN  framewor(1) The Faster-RCNN FrameworkFaster-RCNN is the representative structure of two-stage object detector. Regions of Interest (RoI) are generated by Region Proposal Network (RPN), and then transferred to the next part for classification and bounding box regression. As shown in (2) The Custom DCNN BackboneBackbone is the first stage of the “two-stage” detector. Backbone’s function is to extract features of the image and generate the feature map. A custom DCNN was designed as the backbone. Feature extractor is important to two-stage deep learning detector, because the quality of feature extraction affects the quality of detection. The architecture of the backbone is illustrated in (3) RPNRPN in Faster-RCNN is an alternative to “selective search” in Fast-RCNN. Selective search is to divide the whole picture into many small regions, then perform the neural network which generates the bounding boxes in each small region, and finally output small regions and the bounding boxes. Thus, the efficiency is low. RPN runs the neural network once to extract RoIs, which improves the efficiency.(4) RoI Pooling PartRoI pooling part converts region proposals generated by RPN into the feature map of fixed height and width (7 × 7). The advantage of this method is that the size of the input image may not be fixed, as any size of the previous feature map will be RoI pooling into H × 7 × 7 feature map, where H is the number of RoIs .(5) Head of the Faster-RCNN FrameworkThe head is composed of the last two FC layers, whose function is to combine all the local features to the whole features of the object. The dimension of the two FC layers is 1024 respectively. The FC layer outputs two branches, which are the classification branch and the bounding box branch. Classification branch has four dimensions: three dimensions denoting the three categories of rice lesion spots, and one dimension of the background. We used the SoftMax function to calculate the probability. Bounding box branch has 16 dimensions, which are the product of the four dimensions and the four coordinates of each box. The four coordinates are: top left, top right, bottom left and bottom right.For use in the Faster-RCNN framework, we designed a neural network backbone comprised of 12 convolutional layers. The structure of this neural network is depicted in The DCNN backbone architecture is made up of four blocks. The channel of the input layer “Image” is 3 because of the red, green, blue channel of an image. The first block consists of five parts: three convolutional layers which have 64 filters with the size of 3 × 3; a local response normalization (LRN) layer; a max-pooling layer with the kernel of 2 × 2, which is used to downsample the data. The second block also includes five parts: three convolutional layers that have 128 filters with the size of 3 × 3; the same LRN layer; the same max-pooling layer. The third block also consists of five parts: three convolutional layers which have 256 filters with the size of 3 × 3, and other layers are the same as the first block. Finally, the last block also consists of five parts, except for the three convolutional layers which have 512 filters with the size of 3 × 3, the rest are also the same as the first block.We use three convolutional layers in each block, and the convolution kernel of each convolutional layer is 3 × 3, which ensures that the receptive field at the end of each block is large enough, which should be useful for detecting large objects, such as large lesion spots. Meanwhile, as there are only three convolutional layers, and only one max-pooling layer in each block, the information loss caused by convolution and pooling would be reduced to a lower level. The 12 convolutional layer architecture may have high semantic information, which may be sufficient to recognize blurry objects, such as blurry lesion spots.The novelty of the proposed DCNN are as follows: (1) We changed the order of ReLU layers and put the ReLU layer between two convolutional layers, this might be beneficial for the convergence of the deep network. (2) We set the number of convolutional layers to 12, and the depth might be moderate for high semantic recognition. (3) We set the number of blocks  to 4, aKrizhevsky et al. propose local response normalization (LRN) . LRN is  neurons .In the process of studying the proposed DCNN backbone, we tried other different architectures, such as increasing or decreasing the total convolutional layers, increasing or reducing the number of the adjacent convolutional layers. Detailed discussion is in The frames detected in the still-image detector contain detection information, such as classes and the detection confidence. Different box colors were used to distinguish different classes in the experiments. Our video synthesis module receives the just detected frame from the still-image detector and synthesizes the frame to video. The resolution of the generated video is the same as that of the frame.A Linux server with Ubuntu 16.04 was used in the experiments. The server included an Intel i7-6700 K CPU, 64 GB DDR4 RAM, and two NVIDIA Titan X GPUs, with the deep learning platform of Detectron . Before The system with the custom DCNN backbone was trained with CUDA 9.1 and cuDNN 7.1.3. Stochastic Gradient Descent (SGD) with momentum was used to converge the model. The learning rate was set to 0.002, and then decreased every 20,000 iterations by a factor of 0.1. The momentum was set to 0.9 with a weight decay of 0.0001. The mini-batch was set to 1. Detectron resizes the input images to avoid GPU memory overflow during training, thus, the maximum size of the input training images was limited to 2500 pixels, while the minimum was limited to 1500 pixels. The iterations were set to 60,000. In the contrastive experiments, the parameters were set to the appropriate values. In The detection threshold of confidence was set to an appropriate value to filter out the detected lesion spots whose detection confidence was lower than this threshold value. Thus, the higher the threshold was set, the fewer lesion spots would be detected.From the experiments, we learned that, when the video detection threshold was set below 0.2, most of the spots could be detected; when the threshold was set to 0.7, only a few spots could be detected. In order to achieve better detection results, we set the video detection threshold to 0.2, and most of the spots could be detected, with a few redundant overlapping boxes. In our experiments, the three other backbones and YOLOv3 were all set to 0.2.In The detector would be confused about the three categories of rice diseases and pests. Since we used image-training models to detect videos, the property of video defocus, motion blur and part occlusion of videos, and the complex background of videos were all the factors of the confusion. We presented a confusion matrix of the video detection results of Video 1 in We analyze that the reasons why some lesion spots in the videos are not detected, or wrong detected, and the detection confidence is not very high is that the spots in the videos are relatively blurry and distorted compared with the still-images which are used to train the model, which leads to the features may be different from the still-image ones from our dataset. The annotated lesion spots of the sample images we used for training the still-image models are regular, standard and clear, while spots in videos may be distorted, obscured, and blurry. There may be other reasons, like the difficulties in rice video detection illustrated in One of the difficulties of our system was that we used clear photos to train a model, and then used the model to detect a relatively blurrier video frame by frame. We could see the detection effect in We used Video 1 to test and analyze. Each contrastive experiment of different architecture was set with the appropriate hyperparameter after parameter adjustment experiments, the parameters were illustrated in We selected VGG16, ResNet-50, ResNet-101 and our custom DCNN as backbones of the still-image detector (Faster-RCNN framework), to evaluate the performance of these backbones in rice video detection. We used the same image dataset to train models of these backbones, and used Video 1 for detection. The same experimental environment such as the Linux server, GPU, CUDA, and cuDNN was selected. The three other backbones achieved their best video detection effects after the hyper-parameter adjustment. With our experimental environment and dataset, the custom DCNN backbone achieved good experimental results in the rice video detection.We trained these four backbones with pre-trained models using the platform Detectron, the metrics are shown in The rice brown spot video precision of VGG16 and rice stem borer video precision of the custom DCNN are 100% in Knowledge transfer  generally reduces training time. In our experiments, the training time of ResNet-50 with a pre-trained model was nearly one hour less than that of training ResNet-50 from scratch. But from the results of We assume the reason why VGG16, ResNet-50, and ResNet-101 performed not so well in our experiments is that video frames are not always as clear as photos. We used the model trained with clear images to detect blurry video frames. Though what we used were the HD videos, the video frames were still not as clear as photos because of the video defocus and motion blur. The features between clear images and blurry frames might be much different. Thus, those backbones which are special for images may not be suitable for the detection of less clear frames.For another reason, pre-trained models might have the possibility to disadvantageously affect training results. Since the pre-trained model was trained from other objects, the features of other objects might be quite different from the crop lesions. This might be a finding, i.e., for some special-purpose recognition, the detection rate without a pre-trained model might be higher than that with a pre-trained model.YOLOv3  is a staYOLOv3 had a good detection effect on the spots with clear boundaries and regular shapes, especially for the shapes that were similar to the training images, but had a non-ideal detection effect on spots with blurry boundaries and irregular shapes.The sensitivity  of our video detection system was higher than YOLOv3 in We assume that the reasons of the low video recall of YOLO are as follows: (a) YOLO reduces the size of the input image to 608 × 608 pixels (in our experiments), which may reduce the effective pixels; (b) the two-stage system which has the specific feature extractor, may be appropriate for the rice diseases and pests video detection under complex background; (c) there may be the video detection difficulties for YOLO on rice diseases and pests illustrated in The custom DCNN backbone had eminent detection sensitivity  in withered leaves of rice sheath blight and rice stem borer symptoms. It might distinguish different withered leaves in our experimental environment, e.g., withered leaves of rice sheath blight might have fungal infection, while withered leaves of rice stem borer symptoms might have none . From FiFirstly, like other video detection, rice video detection also has problems such as video defocus, motion blur and part occlusion. These may lead to misdetection, or low detection confidence. Secondly, the shape of lesion spots is always irregular, and the boundaries of lesions are always non-obvious. Meanwhile, because of the existence of video defocus and motion blur, the lesion spots of each frame appear fuzzier.Thirdly, we used the relatively clearer images (as shown in Firstly, our video detection system had a relatively long video detection time. Since we used HD videos for detection and detected every frame, the detection time of the 15s 1080P video was about 40s to 50s. Secondly, we did not extract the key frames, while the information of the adjacent frames was mostly repeated, which resulted in the waste of computing resources and detection time. Thirdly, our detection confidence was relatively low. In the case of video defocus, motion blur, the irregular shape and non-obvious bounding of the lesion spots, our detection confidence was not high, and our detection threshold of confidence was set low, too. Finally, the metrics were calculated manually. To compute them automatically is a difficulty. These are all our next research directions.In this paper, we accomplished three categories of rice diseases and pests video detection, which were rice sheath blight, rice brown spot, and rice stem borer symptoms. The video detection way was that we used image-training models to detect untrained videos. We proposed a set of video detection metrics, which was consistent with the detected video in our experimental environment. In addition, we designed a custom DCNN backbone network for video detection, which was suitable for rice video detection with our experimental environment and our detection way. We found that VGG16, ResNet-50 and ResNet-101 might have an unsatisfactory detection effect on slightly blurry images. Furthermore, we tested the state-of-the-art method YOLOv3 on rice lesion spots with the same detection threshold of confidence, and found that YOLOv3 had a non-ideal detection result to objects with blurry boundaries and irregular shapes. We consider that our system could be applied to other crop diseases and pests.


These microenvironments are classically defined as distinct cortex and medulla regions that each contain specialized subsets of stromal cells. Extensive research on thymic epithelial cells (TEC) within the cortex and medulla has defined their essential roles during T-cell development. Significantly, there are additional non-epithelial stromal cells (NES) that exist alongside TEC within thymic microenvironments, including multiple subsets of mesenchymal and endothelial cells. In contrast to our current understanding of TEC biology, the developmental origins, lineage relationships, and functional properties, of NES remain poorly understood. However, experimental evidence suggests these cells are important for thymus function by either directly influencing T-cell development, or by indirectly regulating TEC development and/or function. Here, we focus attention on the contribution of NES to thymic microenvironments, including their phenotypic identification and functional classification, and explore their impact on thymus function.The thymus supports T-cell development  Whilin vitro in the absence of mesenchyme  and FGF10 produced by thymic mesenchyme and their receptor FGF-R2IIIb expressed by TEC were also essential for normal TEC development . In the y mature . Indeed,y mature . Such fiy mature . Similary mature –18. Thusy mature .Sp/SpPax3 mice, which carry a point mutation in Pax3 eliminating protein function, revealed that separation of the thymus from the pharynx, migration of the thymus to its position at the mediastinum and distribution of the thymus:parathyroid domains are dependent on the presence of thymic mesenchyme  T-cell precursors in the presence of TEC alone resulted in an absence of further T-cell development. In contrast, the addition of mesenchymal cells resulted in development to the CD4+CD8+ double positive (DP) and CD4SP and CD8SP stages  technique, where defined thymocyte and stromal subsets can be reassembled into 3-dimensional structures, studies provided evidence that specific stages of thymocyte development are also dependent on the presence of thymic mesenchyme , 23. ForN3 stage . How thyN3 stage , mesenchmponents , suggestCre and Sox1Cre mouse models (crossed to Rosa26 reporter mice) enabled identification of NC-derived mesenchymal cells within adult thymus  and medullary fibroblasts , further characterizing the different mesenchymal populations present in the adult thymus   pathway has been shown to be a key axis for the egress of mature thymocytes , 39, 40,e means) . The sphe egress . Mature e egress . Mesenche egress . Based oTdTom reporter mice , this SP thymocyte accumulation and emigration defect was not observed. While the reasons for this difference are not clear, it may be that while both Wnt1Cre2 and Twist2Cre are active in thymic mesenchyme, the exact subsets that are targeted differ. It will be important to formally define the types of thymic mesenchyme that are targeted in specific Cre expressing mouse strains in order to gain a clearer picture of the role of individual mesenchyme subsets controlling T-cell development.Additional studies have further proposed that expression of the lymphotoxin β receptor (LTβR) by specific thymic stromal compartments, including mesenchyme, may regulate thymocyte egress in the adult thymus. Germline LTβR deletion leads to an intrathymic accumulation of mature thymocytes and reduced recent thymic emigrants (RTE) being indicative of a thymic egress defect , 49. In ese mice . In othevia LTβR within TEC microenvironments influenced thymocyte development. First described by Boehm et al., 2003, mice deficient for LTβR exhibited a clear reduction in mTEC numbers, and severely disrupted medullary organization , identified as CD45−EpCAM-1−CD31−Pdpn+ by flow cytometry, was the DC-defect of Ltbr−/− mice replicated and this pathway was proposed as the mechanism by which LTβR signaling regulates thymic tolerance , a population significantly reduced in Ltbr−/− and LTβRMes mice  demonstrate reduced thymus colonizing cells, albeit such reductions are potentially made up for by subsequent compensatory expansion of thymocytes –bearing progenitor –67. PSGLvia blood vessels, they do so via large venules found at the corticomedullary junction (CMJ), after which they migrate through the cortex towards the subcapsular zone (SCZ) to begin the step-wise development program within the thymus  crossed with LTβRFlox mice, to generate LTβREndo mice (−/− mice) also significantly reduced the TPEC population, suggesting that provision of LTβR ligands by SP thymocytes may act as part of a crosstalk mechanism between thymocytes and endothelial cells to regulate development of the latter  resulted in a significant reduction in the frequencies of both ETP and DN1 thymocytes  is a key regulator of early thymocyte proliferation and differentiation , with meymocytes . In thymymocytes , endotheymocytes . Interesymocytes .Lpp3 through use of VE-CadherinCre to target endothelial cells resulted in the intrathymic accumulation of mature SP thymocytes suggesting a block in thymocyte egress   . Deletios defect . Follow ependent . Thus, Le thymus , 51. As e thymus , 74. Inte thymus , 72, 82.via Cld− vessels whereas little penetration was found around Cld5+ vessels  which in turn upregulates Foxn-1 expression in TEC, leading to increased expression of downstream Foxn-1 targets such as delta-like ligand 4 (DLL4) which are involved in TEC development, maintenance and regeneration (in vitro (exEC) significantly improved thymus regeneration upon damage with exEC reported to home to the thymus and potentially exert this effect intrathymically  causing significantly reduced VEGF expression which resulted in significant changes to the vasculature within the thymus including reduced vessel integrity and disorganized patterning/distribution  is a key regulator of vascular development and has been shown to be key in the thymus endothelial development during neonatal development but is largely dispensable in adults . Thymic ribution . These dThe thymus undergoes drastic age-associated involution which impacts immune function , 94. WitInterestingly, it has also been shown that adipocytes accumulate in the PVS within the aged thymus . While tThe non-autonomous nature of intrathymic T-cell development, and the subsequent requirement for thymocyte-extrinsic signals from thymic stromal cells, is well established. Of the diverse stromal cell types that contribute to cortical and medullary microenvironments, thymic epithelial cells (TEC) have been the predominant focus of study over many years. This is likely due at least in part to their fundamental importance in shaping the functional properties of αβ-T-cells produced in the thymus. Indeed, TEC populations control MHC restriction and determine the specificity of the T-cell receptor repertoire by both positive and negative selection events. In addition to the importance of TEC biology, non-epithelial stromal cells (NES) have also been a focus of study, but to a significantly lesser extent. However, NES such as mesenchyme and endothelium have been implicated in key aspects of thymus function. For mesenchyme, their influence on T-cell development can operate by multiple mechanisms. Thus, mesenchyme-derived signals can either target developing thymocytes directly , 23, or For endothelial populations within NES, growing evidence supports their importance in controlling cellular trafficking into and out of the thymus. As the efficacy of these processes can act as rate-limiting steps in T-cell production , 76, 79,The review was written by KJ and was revised by WJ and GA. All authors contributed to the article and approved the submitted version.Work in the laboratory is funded by the Medical Research Council (MR/T029765/1).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.


To the EditorWhat makes a protein allergenic, and in particular a food allergen, has not yet been defined. Previously, using model systems, it has been shown plant lipids have an essential role in the allergenicity of the Brazil nut allergen Ber e 1 and NKT-like cells are involved in the sensitisation phase to nut proteins . Further6 lipid-mixture loaded APC cells (MUTZ3) as previously described  + and HexCer(t34:1) (C40H77NO9) in negative [M-H]- modes or an ether phosphatidic acid compound PA(O-38:2) (C41H79O7P) in neutral mode. Comparison with molecular markers suggests the position of PL8 on TLC is more compatible with an ether lipid molecule than glucosylceramides.pMJA295 and 297 TCRs displayed stronger activation with PLs in fractions PL5-PL8 but only the response to PL8 was statistically significant. PL8 is enriched in a single molecular species detected both as a free form  and as a lithium adduct . The identity of this compound was investigated using two molecular structure database search tools: d of 5.6 ± 0.1 µM) as demonstrated in ANS titration and NMR exchange experiments [These results suggest specific classes of nut lipids might be involved in activation (CD69+) of CD3 + CD56 + cells from nut-allergic patients and that α/β and γ/δ TCRs sequences such as pMJA297 and 295 might be involved in the lipid recognition. These results complement previous findings that Ber e 1 can accommodate one lipid molecule  able to sensitise and an inactive one. However, taken together these results further support our initial hypothesis that natural plant lipid might play an essential role in the intrinsic allergenicity of the nut major allergen Ber e 1.The putative active lipids described here, the campothecin cross-linked lipid described for Pru p 3  and the In conclusion, we improved and optimised protocols for the isolation of lipid responsive human NKT-like cells, sequenced and expressed lipid binding TCRs and used these TCRs to screen Brazil nut lipid fractions. The results from this study help to characterise the intrinsic factors linked to Ber e 1 allergenicity and to define what makes a common protein within a food matrix context, allergenic to a particular group of susceptible individuals.


Saturday Night Live sketch “Melanianade.” It argues that the comical video reinforces and essentializes negative stereotypes of Eastern European women to depict Melania Trump, seeking to delegitimize white hegemonic masculinity and female complicity. The fictitious Melania Trump’s appearance needs to be understood in her co-construction with her white hegemonic husband and otherwise racialized women in the comedy sketch. These women are the African-American women of Beyoncé’s video “Sorry,” which “Melanianade” copies/satirizes. “Sorry” represents Black female US-American experience, and was broadly understood as Black feminist art/activism. Taking Beyoncé’s place in the video, the fictitious Melania Trump is co-constructed to the absent black feminist bodies as white non-feminist Eastern European Other. Using Beyoncé’s video as a template, “Melanianade” re-affirms a discourse of Otherness that re-establishes the enlightened and emancipated educated (white) feminist American non-immigrant woman as norm, while it also whitewashes the Black American experience, which “Sorry” stands for.This article offers a “feminist critical discourse analysis” of the  Saturday Night Live (SNL) sketch “Melanianade.” I argue that, as the mainstream feminist video seeks to delegitimize white hegemonic masculinity and female complicity, it reinforces and essentializes negative stereotypes about Eastern EuropeanOthering and orientalizing of Eastern European women  feminist American non-immigrant woman as norm. Moreover, as the video uses the well-known song and video to mark MT as Other, it whitewashes the Black American experience, which “Sorry” communicates.This article offers a feminist discourse analysis : “Here lies my last nerve, Donald.” The video represents MT as “beautiful, dutiful,” mirroring media representations, calling her strikingly “passive”  men, and the beautiful younger white Eastern European women as one common dichotomous co-constructions. Another one is the African American woman in opposition to the Eastern European woman.These examples of sentiments against MT show how mainstream discourses see her as the embodiment of an elite version of two very popular, not mutually exclusive stereotypes of post-Soviet women, the slut and the victim. The media studies scholar Roumiana Deltcheva identified the post-1991 most common filmic depictions of Eastern European women: “the scrupulous slut, the conniving trickster, and the helpless victim” , 164. Eark Yoder  are two rk Yoder . Both laBefore further analyzing the location of Eastern European women within the epistemology of ethnicity and racialization in the US on the example of “Melanianade,” I want to briefly come back to the suggestion that MT is a victim of domestic abuse. The depiction of Eastern European women as sexually exploited victims has a long tradition in the US. The US Trafficking Victims Protection Act was strongly influenced by a public case of white female Russian and Ukrainian trafficking victims in 1997 Williams , 94. As SNL writers Chris Kelly and Sarah Schneider chose to use it as a template.  In any case, the widely disseminated cultural knowledge about the feminism of the song and video “Sorry” and its album Lemonade heightens the feminist critique on Trump’s misogyny in “Melanianade.” Additionally, and maybe unintentionally, in using “Sorry,” a piece of art that signifies Black feminist politics, to mark white ethnicity and gender politics, sexualization, and victimization, shows the reference from ethnicity to race, and the damage it does. It highlights the signification of the real existing MT as Other, through the strong reference to African American women and their experiences and history. Through this process of referencing, “Melanianade” whitewashes the referenced subjects and transforms the meaning of a specific Black female embodiment into a more general Otherness. To put it differently, Beyoncé’s video illustrates the corporeal violation but also resistance of African American women; in using the same imagery to signify oppression against white women, the parody “Melanianade” highlights MT’s body in the video, as a somehow different and oppressed body, yet it silences the discussion of color-based racism, which the original brought forward so forcefully.“Melanianade,” staying true to its comedy format, brings forward a very blunt feminist critique. Cecily Strong plays MT on the brink of feminist emancipation. “I can’t take it anymore,” she utters with a saddened face in the opening sequence of the video, and Ivanka, Kellyanne, Omarosa, and Tiffany echo: “you’re breaking us, taking it for granted that we’ll always be there.” They speak to President Trump’s misogyny, to his sexism and racism. They criticize him by imitating a video that has been praised as Black feminist empowerment video  audience watches the video. It presents MT as a “beautiful, dutiful” wife, activating the stereotypes of the silent and devoted Eastern European woman (victim), banned from the public sphere, oppressed by her dominant husband. “Coming from the presumed ‘desolate setting’ of post-communism …, eastern European women are usually seen as particularly docile and submissive in the eyes of Western men. Besides that, eastern European girls still have the reputation of going weak at their knees for western men.”  past prohibits them from becoming fully modern progressive US citizens.In comparison to Beyoncé’s black feminism, MT’s whiteness “sticks out,” becomes highlighted. Public knowledge about Beyoncé’s nickname “Queen B” and the interpretation of her strong feminine agency and power, as being carried out with the attitude of a female ruler or monarch, additionally influence the reading of MT. MT is depicted, much as Beyoncé in “Sorry,” as queen. In her case, however, this does not signify rebellion and agency, but etiquette and superficiality. Since the video connects MT, a white Eastern European woman, and Beyoncé, a Black African American woman, the category of race lingers behind the feminist critique it proposes. Yet, through the non-verbalization of the racialization of Eastern European women or Donald Trump’s racism, it renders the discussion of racism impossible and arguably whitewashes Beyoncé’s Black feminism at the same time. The weak attempt to highlight the intersection between President Trump’s misogyny and racism, by presenting Omarosa as a woman without a last name, addressing the linguistic hegemony and the unwillingness to “learn” non-normative names, does not sufficiently irritate the process of making Black oppression invisible. Thus, the positioning of MT as queen highlights her Eastern Europeanness, bringing up a broader cultural reference from immigration to a long-gone European monarchy. Williams  and SadoOther. The critical tools available within feminist or critical race studies to account for the racialization of white Eastern European women are limited. I follow Stuart Hall, who conceptualizes race as a discursive construct, “principal of classification,” and “a sliding signifier”  song, with a particularly thumping beat created by synthesizers, drums, and bells. Beyoncé’s self-presentation, her clothes, and the dance performances correspond with the genre of R&B, which is generally consider a Black music genre, but also opens it up for other Black artistic expressions and conventions, as already described. Especially powerful is Beyoncé’s feminist usage of the dress and style conventions of R&B, which is usually considered to be a rather misogynistic genre that objectifies women  instrumentalizing their “deceptive sexuality” Williams , 36 or “Although the criticism of this world—the bombastic capitalism of the Trump dynasty—needs to be acknowledged, the strategy with which “Melanianade” brings forward such critique is highly problematic. Sketch writers Kelly and Schneider exchange Beyoncé’s setting—the places of historical and contemporary oppression, the public bus, the Southern mansion and plantation—with a stretch limousine and the Trump Tower. Showing an Eastern European ex-model in an over-decorated gold palace is not nearly as subversive as showing a Black female hip hopper taking control of an antebellum mansion (as “Sorry” does). There is nothing provoking or subversively irritating in showing MT in an environment that signifies wealth and European heritage, sitting in a rococo chair surrounded by marble and chandeliers. On the contrary, it is confirming what journalists and commentators suggest between the lines, when they emphasize the large age difference between the spouses, for example ETN ; namely Otherness needs to be understood as doubled: she is the Other to African American bodies, as well as to the highly progressive (developed) US-American feminist intellectual. This Otherness can be analyzed by Kulpa and Mizielińska , immigration discourses, and discussions on dishonesty or fraud (trickster identity and plagiarism). As representations of difference, these aspects of physical or bodily differences can be understood as racialized. The processes of racialization, however, become understandable only in a reflection of the videos mimicking Beyoncé’s video “Sorry.” The song and video “Sorry” are interpreted as thematizing Black American history, and feminist African American culture, as part of Beyoncé’s “coming out” as Black activist. Closely analyzing the comedy video “Melanianade” in comparison and relation to “Sorry,” I have shown that the meanings of “Sorry” are as significant for the understanding of “Melanianade” as the latter’s content, sound, and visuals. In focusing on the representation of the fictitious MT in contrast and relation to Beyoncé in her video “Sorry,” I have argued that the racialization of Eastern European women can best be accounted for as “in-betwenness” by understanding their locatedness in connection to hegemonic white men and women of color on the intersection of gender, class, age, origin, language, and sexuality. I have further shown that contemporary racializations of MT as Eastern European woman go back to ideas of development and civilization. Following these ideas, Eastern European women are dignified with exotic (old-fashioned) femininity, and constructed as desiring (and confirming) the domination of Northwestern men. The appeal in their exoticism lies particularly in their similarity (including whiteness) to those who create and direct their invisible/visible Otherness. Sexualizing MT, signifying her Otherness through style and language/pronunciation and understanding her as cheater/trickster, slut, and victim of her husband’s toxic masculinity, makes sure that she stays “arrested” in the in-between of Eastern Europeanness. In other words, as white woman, marked through a difference not only to other racialized women, but also white American-born women, MT is assigned to the class of the almost-but-not-quite-yet accomplished progressive and modern working women. The gesture behind “Melanianade” is clearly a feminist one, trying to use and show leveraged pedagogy, to lovingly bully the real MT into her own emancipation and make her want to change her husband. Unfortunately, by appropriating the video “Sorry,” and building on its signification as a stronghold of Black feminism, the video whitewashes the same Black feminism, by leaving out a critique of racialization and race-based violence, and essentializes the racialization of MT as Eastern European Other.Reading the


The study aims to explore the prevalence of heterophoria and associate factors in Tibetan grade-one students.  The Lhasa Childhood Eye Study (LCES) is a school-based cohort study. 1942 grade-one students from 7 elementary schools were randomly sampled by stratified cluster sampling. Ocular examinations were performed in participants, including ocular motility, distance and near visual acuity, cycloplegic autorefraction, and stereoacuity. The near (33 cm) and distance (6 m) fixation cover test was used to differentiate orthophoria, heterophoria, and heterotropia, and the magnitude of the phoria was measured by the Maddox rod and prisma. n = 424). At distance fixation, the prevalence of heterophoria, exophoria, and esophoria was 4.64%, 4.21%, and 0.43% separately, while at near fixation, the prevalence was 22.73%, 22.35%, and 0.38%. No vertical phoria was detected. The mean magnitude of heterophoria at near and distance fixation was −7.63 ± 5.15 PD  and −4.84 ± 5.94 PD . The prevalence of esophoria was associated with hyperopia  and amblyopia  at near and distance fixation. The prevalence of exophoria was associated with myopia at near fixation . In the near heterophoria group, the proportion of children with abnormal stereoacuity was 23.26% (n = 97), significantly higher  than that in orthophoria .  Of 1856 grade-one students completing all the ocular examinations, 1852 participants finished the ocular alignment test. The mean age was 6.82 ± 0.46 years (range 6∼10 years); 981 (52.97%) were males, and 871 (47.03%) were females. The prevalence of phoria was 22.89% ( In Lhasa, grade-one pupils have a lower prevalence of heterophoria. Near exophoria was associated with myopia, while esophoria was related to hyperopia and amblyopia both near and distance. Heterophoria may be one of the affected factors for reducing stereoacuity. Heterophoria refers to a state that both eyes have a tendency to deviate  but can The prevalence of heterophoria varies among countries, geographic regions, and ethnics, ranging from 4.0% to 80.2% . Epidemihttp://www.chictr.org.cn (ChiCTR1900026693). Ethics committee approval was obtained from the Institutional Review Board of Beijing Tongren Hospital, Capital Medical University (TRECKY2019-146). All parents or guardians signed the informed consent forms.The Lhasa Childhood Eye Study (LCES) is a school-based cohort study, aimed to observe the occurrence and development of different ocular diseases in Lhasa school-age children during 2019–2024. Detailed study methods including inclusion and exclusion criteria have been described elsewhere . BrieflyUncorrected and presenting distant visual acuity (VA) were measured for the right eye and left eye using Lea Symbols ETDRS 3-meter Set charts . Pinhole and best corrected distant visual acuity (BCVA) were obtained after the subjective refraction test for students with uncorrected distance VA < logMAR0.0 (20/20). A logarithm of the Lea Symbols Pocket Card chart  was used to test students near VA at 40 cm. The distance vision was performed firstly and then followed by the near vision test.The cover test was used to assess the presence of strabismus by requesting the children to fixate on targets at 33 cm (near) and 6 m (distance). Near fixation was performed firstly and distance fixation secondly. If children had their own glasses, examination would be performed under the best corrected vision with glasses. If children did not have glasses, they would be examined without the glasses. The presence or absence of strabismus was first screened by the Hirschberg test, followed by the cover-uncover test to differentiate phorias and tropias, to determine if a tropia was intermittent or constant and to differentiate unilateral (right or left) and alternating tropia. The size of tropia was measured by the prism cover test.If no strabismus was detected, the alternating cover test was performed to detect heterophoria. When heterophoria was detected, the Maddox rod test and prism would be used to quantity the phoria by an optometrist. To measure the size of the phoria, the prism was placed over the right eye with the base in the appropriate direction and power increased until the student saw the line through the light. The amount of prism is the size of the phoria.In the LCES, the Stereo Fly Test  was used to quantitatively measure the degree of stereoacuity ) for students at 40 cm.Refractive status was measured before and after cycloplegia using an autorefractor . Each student was first administered one drop of topical anesthetic agent  to alleviate discomfort, followed by two drops of 1% cyclopentolate (Alcon) and 1 drop of Mydrin-P  after a 5-minute interval. 30 minutes after the last drop, a third drop of cyclopentolate would be administered if pupillary light reflex was still present or the pupil size was less than 6.0 mm. Three readings of spherocylindrical autorefraction were taken and averaged for analysis.D = DS + 1/2DC. Myopia and hyperopia were defined as SE ≤ −0.50D and ≥ + 2.00D in one or both eyes, respectively [D [Heterophoria was defined as any movement of the eye when performing the alternating cover test , and wheectively . Anisomeively [D . Poor stively [D , 19.P < 0.05 was considered statistically significant. All of the confidence intervals (CIs) are given as 95 % CIs.All the data were filled in forms and were independently entered into the database using EpiData software 3.1  by two individuals. Statistical analysis was performed using SAS software . Descriptive statistics for demographic and outcome variables were presented as mean and standard deviation while the prevalence estimates for heterophoria and stereoacuity were presented as percentages. Polytomous logistic regression with a generalized logit link was used to compare the odds of having heterophoria between children in different refractive, amblyopic, and anisometropic subgroups. The stereoacuity in different heterophoria type subgroups was compared by the chi-square test. Among the 1942 sampled students, 40 were ineligible for LCES according to the inclusion and exclusion criteria. Of the remaining 1902 eligible individuals, 1856 grade-one students completed the general ophthalmic examinations during the period from September to October 2019, with an overall response rate of 97.58%. 1852 participants finished ocular alignment examination and conducted analyze procedure. The mean age was 6.82 ± 0.46 years (range 6∼10 years); 981 (52.97%) were males, and 871 (47.03%) were females .n = 424; 95% CI, 0.21–0.25) in our study. n = 86; 95% CI, 0.04–0.06), 4.21% for exophoria, and 0.43% for esophoria, while at near fixation, the prevalence of heterophoria was 22.73% , 22.35% for exophoria, and 0.38% for esophoria. No vertical phoria was detected.The prevalence of phoria was 22.89% , range −28 to +12 PD, and −4.84 ± 5.94 PD , range −24 to +12 PD. Figures P = 0.03, 95% CI: 1.15–35.28; OR = 5.42, P = 0.04, 95% CI: 1.04–28.24) or amblyopia  tend to develop into esophoria at near and distance fixation. Children with myopia were prone to develop exophoria at near fixation , but not at distance fixation .Age was considered as the main confounder of the model. After adjusted for age, the results are shown in Tables χ2 = 0.017, P = 0.897) in the stereoacuity distribution between distance phoria and orthophoria, but in near heterophoria group, the proportion of children with poor stereoacuity was 23.26% (n = 97), significantly higher  than that in orthophoria .In children with heterophoria, 420 subjects completed stereoacuity examination, in which poor stereoacuity (>60 seconds of arc) was found in 98 (23.33%). The distribution of stereoacuity in phoria and orthophoria children is shown in LECS is the first study to conduct an epidemiological survey of heterophoria in grade-one students in the plateau area of China (Lhasa). In the present study, the prevalence of heterophoria for grade-one students in Lhasa was 23.77%, lower than previous reported surveys , 6, 8, 9Prevalence of heterophoria, age, and risk factors in previous studies are shown in The prevalence of heterophoria in children showed large variations in different countries. In previous surveys, Hashemi et al. , Vilela Different prevalence reported in each study may be related to several reasons, including the criteria for defining heterophoria, age, region, and ethnicity of investigated children. We found that the prevalence of heterophoria in grade-one pupils in Lhasa was 23.77%, which is lower than previous surveys. The lower prevalence in the present study may be related to the following factors. Firstly, different screening techniques for phoria contribute to discrepancy in prevalence rates. In the present study, the most commonly used diagnostic criteria to define the phoria was employed, which is that the Hirschberg test, alternating cover test, and cover-uncover test were combined to screen heterophoria. However, some surveys have shown that only the alternating cover test was used to diagnose phoria, which may include some manifest heterotropia. In addition, the magnitude of deviation was also considered as a diagnostic criterion of phoria in some studies, and it may affect the prevalence of heterophoria. Secondly, the age of screening population affects the prevalence of heterophoria. Chen reported that the incidence of heterophoria increased from the age of 6 years onwards . HoweverIn the LECS study, we found that orthophoria is the most frequent state for near and distance fixation, and the proportion of exophoria had increased at near comparing to distance fixation. In addition, the type of heterophoria was more skewed exophoria at near fixation, which was consistent with Lanca's study . It may Different results of relationship between prevalence of heterophoria and age, gender, ethnicity, and region were reported in previous literature studies. Weymouth et al.  found noIt is generally suggested that refractive error is one of the factors affecting the development of ocular alignment. David and Jackson  found thThe state of heterophoria in amblyopic children is often the most neglected part during clinical practice and no related surveys abroad. Heterophoria was significantly associated with amblyopia. We found that children with amblyopia were more likely to develop esophoria at near and distance fixation. Some research results believe that anisometropia is one of the causes of microtropia , but theIn China, there are more and more children with myopia. The research results further verified that refractive error is one of the risk factors for the occurrence and development of heterophoria. It guides doctors to pay attention to the changes and development of eye positions of children with myopia in the clinic and actively prevent and intervene in time to avoid damage to visual function.Dominant strabismus often causes damage to stereopsis, but few research reports on the effect of heterophoria on stereovision. In current survey, we found that there were more children with abnormal stereoacuity (>60 seconds of arc) in the heterophoria group than that in the orthophoria group at near fixation, which confirmed that heterophoria may be one of the affected factors for reducing stereoacuity. In contrast, Rustein et al.  found noThere are several limitations in the study. First, the disadvantage of the study is the cross-sectional design. Longitudinal research will be needed in the future. Second, the Maddox rod is too subjective for young children. In addition, the Maddox rod was used for distance and near in our study. Ideally, it should be used only for distance not near. It is a major flaw in our technique.In Lhasa, grade-one pupils have a lower prevalence of heterophoria compared to previous studies. Near exophoria was associated with myopia, while esophoria was related to hyperopia and amblyopia both at near and distance fixation. Heterophoria may be one of the affected factors for reducing stereoacuity; however, further more long-term follow-up studies are needed to verify the extrapolation. This survey investigated for the first time the profile of heterophoria distribution for grade-one students in the plateau area of China, which can further supplement the epidemiology database of ocular diseases in China and have promoted the prevention and control of myopia in clinic.