No statistically significant differences were found in the volume change (%), or reciprocal of mean root length in the erupted and unerupted groups in the canine, first premolar, or second premolar roots except for an association between the post-operative dental root length of the canine and the maxillary canine eruption status. Therefore, assessment of root development from pre-treatment CBCT scans was not deemed worthy from a diagnostic perspective.In children born with cleft lip and palate, the timing of the secondary alveolar bone graft (SABG) is crucial to its success; this involves estimating the eruption of the permanent maxillary canine. Altered dental eruption in this patient group gives impetus to the identification of dental developmental factors concerning maxillary canine eruption, which may steer the clinical decision of SABG timing. Records of over nine hundred patients who received SABG with pre- and post-operative cone beam computed tomography (CBCT) scans were analyzed for inclusion and divided into two groups (erupting or non-erupting canine after SABG). Roots of the maxillary canines and premolars were segmented from the cementoenamel junction then linear and volumetric measurements were performed. The pre- and post-operative root length and volume differences were calculated and compared statistically using independent sample tests and paired  In the United States, cleft lip and palate is the most common birth defect with approximately 6800 babies born affected each year . Cleft lAlveolar bone grafting is a technique used for bone atrophy in order to restore an adequate bone volume: autologous, heterologous and xenograft are possible materials used in this technique ,10,11. AThere are different types of grafting materials that can be used for secondary alveolar bone grafts. The gold standard for grafting in SABG is iliac cancellous bone ,20.The ap < 0.05) [Timing of the SABG procedure is essential and should be performed before the onset of the permanent maxillary canine eruption. Grafting before the permanent maxillary canine eruption will allow the canine to erupt into the graft, which will functionally load the graft . A study < 0.05) . In addi < 0.05) . Graftin < 0.05) .A systematic review proposes that the optimal timing of SABG is between 8 and 12 years of age . Other sTooth development is altered in children with cleft lip and palate . DelayedFollowing SABG, our null hypothesis is that there is no association between pre-operative dental root formation and maxillary canine eruption status in patients with cleft lip and palate. Our study aims to improve clinicians’ decision-making algorithm when deciding the timing of SABG by investigating the dental development concerning the eruption status of the permanent maxillary canine.In our retrospective case–control study, we examined the records of 918 patients with cleft lip and palate that underwent SABG at Boston Children’s Hospital. This study was conducted in accordance with IRB # P00038300 approved by Boston Children’s Hospital on 20 September 2021. The clinical notes were used adjunct to the cone beam computed tomography (CBCT) imaging. The inclusion criteria included an infant diagnosis of a non-syndromic unilateral complete cleft lip and palate, presence of unerupted cleft-side canine pre-graft, and patients with CBCT data available pre- and post-SABG with the post-surgical CBCT not taken more than two years after the SABG procedure.Exclusion criteria included patients who did not have a pre-surgical CBCT available or a follow-up post-surgical CBCT available within two years of the SABG procedure, a diagnosis of syndromic cleft lip and palate, a diagnosis of an incomplete cleft, the presence of a cleft-side canine that has erupted before the graft, the presence of a prime lateral incisor on the cleft-side necessitating early SABG or a diagnosis of bilateral cleft lip and palate.Deidentified (No PHI) pre-and post-operative CBCT images of the patients were exported for analysis. The patients were divided into two groups after evaluating the post-surgical CBCT scans: (1) cleft-side permanent maxillary canines showing radiographic evidence of erupting within two years of the SABG procedure or (2) cleft side permanent maxillary canines which remained unerupted within two years of the SABG procedure.Density values of different tissues, that is teeth vs. bone, were identified in Hounsfield units (HU) in the axial view and used to segment the maxillary canines and premolars from both groups using the commercial software . Upon the completion of the segmentation process, the root area was sectioned from the crowns below the cementoenamel junction (CEJ) to exclude the crowns. Then, volumetric measurements of the maxillary canine and premolar roots on the ipsilateral side with the alveolar cleft were performed on the resultant images . The volThe root lengths were measured  below tht-test was performed on the mean root volume change (%) between erupting and non-erupting groups for the canine and premolars. Two-tailed independent t-tests and two-tailed paired sample t-tests were used to analyze the data for the reciprocal root length ratios. The level of significance was set at p < 0.05.IBM SPSS Statistics version 28.0.0.0 (190) was used for statistical analysis including the two-tailed independent sample t tests, paired sample t tests and bootstrapping. For the power and sample size calculations, Stata/IC 15.1 was used. A two-tailed independent sample t-test and paired sample t-test, a sample of size n was drawn from the population and will be referred to as sample S. These statistical tests are parametric tests which assume the data is normally distributed. It would be reasonable to assume that the data were normally distributed as the p-value from the Shapiro–Wilk test was <0.05; however, exploratory data analysis (EDA) revealed skewness and kurtosis, and thus a sensitivity analysis was conducted by repeating the independent sample t-test and paired sample t-test with bootstrap. In our bootstrap the sampling distribution was created by resampling observations with replacement from S 2000 times with each resampled set having m observations. In contrast to a traditional approach bootstrapping does not assume any underlying distributions of the data [In the independent sample the data . The nonthe data  and is rthe data , which ot-test for both the volumetric and root length analysis and paired sample t-test for root length analysis. A post hoc was performed as there is currently limited literature on volume to estimate effect size.Post hoc sample size calculations were performed using Stata for the independent sample N = 60 patients were eligible to be included in the study which was then divided into 40 in the erupting canine group and 20 in the non-erupting canine group.In total, 918 patients with cleft lip and palate that underwent SABG at Boston Children’s Hospital were evaluated for inclusion in the study. After examining the CBCTs and medical records, p > 0.05) in mean root volume change (%) of the canine between the erupting and non-erupting groups (p > 0.05). There was no statistically significant difference (p > 0.05) in the mean root volume change (%) of the first premolar using the independent sample t-test with a 61% power (61% power means there is a 61% chance of detecting a difference between the population mean and the target when a difference exists) between the mean of the erupting and non-erupting  between erupting and non-erupting canine groups. There was no difference (p > 0.05) in mean root volume change (%) of the second premolar between the erupting and non-erupting groups  with a power of 5%, and after bootstrapping, there was a similar result (p > 0.05); however, the reciprocal of the mean root length ratio of the canine was significantly different (p = 0.025) post-operatively (p = 0.035). Comparing the reciprocal of the mean root length ratio of the first premolar between the erupting and non-erupting group, there was no statistically significant difference (p > 0.05) pre-operatively (p > 0.05). Comparing the reciprocal of the mean root length ratio of the second premolar between the erupting and non-erupting group, there was no significant difference (p > 0.05) pre-operatively (p > 0.05).Comparing the reciprocal of the mean root length ratio of the canine between the erupting and non-erupting groups , there wratively  with a pratively  with a pratively  with a pratively  with a pratively  with a pt-tests were also performed to compare the reciprocal of the mean root length ratio in the same patient before and after the grafting procedure. The descriptive statistics showed skewness and kurtosis; therefore, a sensitivity analysis using non-parametric bootstrapping was performed. In patients with erupting canines (p < 0.05) pre-operatively and post-operatively. In patients that had a non-erupting canine (p < 0.05) pre-operatively and post-operatively in the paired t-test and in the bootstrapping paired t-test. The second premolar in the non-erupting group was found to be significant in the paired sample t-test (p < 0.05), but the bootstrap paired sample t-test p-value is >0.05 (p = 0.07). However, the bootstrap paired sample t-test confidence interval is 2.88 to 8.87 and does not cross zero.Paired sample  canines , the recg canine , the canOur study proposed a novel approach in analyzing root formation in CBCTs in cleft lip and palate patients. After analyzing pre- and post-operative CBCTs, we found there was no association between pre-operative dental root formation and maxillary canine eruption status in patients with cleft lip and palate; therefore, the null hypothesis was accepted. We could not identify any statistically significant differences in the mean root volume change (%) in the erupted and the unerupted groups in the canine, first premolar, or second premolar roots. Our study indicates that root volume assessment was not valuable in clinical decision-making on whether the cleft side canines would soon erupt.Our study did not find statistically significant differences in the reciprocal mean root length ratio pre-operative or post-operatively in the first or the second premolar. Our study also did not find statistically significant differences in the reciprocal mean root length ratio pre-operatively in the canine. The mean pre-operative canine root length compared with an average canine root length in this study is 18.2% in the erupting group and 17.8% in the non-erupting group, which was not statistically different. This highlights that clinicians in our study were grafting before the conventionally recommended ½ to 2/3 of root development. This reflects the current preference of the Craniofacial team at this center to graft earlier to avoid potential ingress of the canine into the defect which would lead to probable failure of the graft. It is the experience of the team that canines will occasionally erupt with a proportionately lesser amount of root development so a more conservative approach is followed. Success rates of 94% at this center  validatet-tests and paired t-tests with a 2000 bootstrap sample. One difference was found between the paired sample t-test before and after the bootstrap examining the reciprocal of the mean root length ratio. In the second premolar in the non-erupting group, a bootstrap non-parametric test result was favored over the paired sample t-test result due to the data being skewed. The paired sample t-test found the second premolar in the non-erupting group to be significant, but after the bootstrap was performed and re-analyzed with the paired sample t-test, the p-value was not significant. However, the bootstrap paired sample t-test confidence intervals do not contain zero. Confidence intervals not containing zero indicated the result was statistically significant. In a small sample size, the confidence interval is more important than a point estimate from the p-value, where there might be little difference [t-test analysis.Due to the skewness and kurtosis, we elected to perform a sensitivity analysis and then reran the independent sample fference . TherefoA limitation of our study is the small sample size due to the exclusion of many patients from the initial sample population due to patients with CBCTs pre- and post-operatively outside of the time range from the grafting procedure, patients with a syndrome that may affect dental eruption, failed bone grafts, and the presence of a cleft-side prime lateral necessitating early SABG. Additionally, another limitation of our study is the measurements for root volume and root length were performed manually. In future studies, using an automated measurement system  could beVolumetric assessment of root development from CBCTs was not a reliable factor in predicting a successful outcome for canine eruption following secondary alveolar grafting in patients with cleft lip and palate. In addition, conventional radiographic root length assessment in this group of patients did not offer better predictability either. Therefore, success for canine eruption following secondary alveolar grafting requires more clinical judgment than relying solely on root formation.


The COVID-19 vaccination is a key measure to contain the pandemic. It aims to restrict new infections and to reduce severe courses of the disease. This paper examines the influence of various social determinants on COVID-19 vaccination status.The analyses are based on data from the study German Health Update (GEDA 2021), a nationwide telephone-based survey of the adult population in Germany, which was conducted between July and December 2021. In addition to bivariate analyses, the association between the COVID-19 vaccination status and the social determinants was examined using Poisson regression.A total of 86.7% of people aged 18 years and older who participated in GEDA 2021 have been received at least one dose of COVID-19 vaccine. Social differences are evident: The proportion of people vaccinated against COVID-19 increases with age, income and higher education group. Lower vaccination rates are found among people with a history of migration, people living in rural areas and people from East Germany. An age-differentiated analysis shows that the social differences in COVID-19 vaccination uptake are lower among those aged 60 years and older.The presented results should be considered when designing targeted interventions to overcome potential barriers to COVID-19 vaccination uptake. Further research is needed regarding the explanatory factors for the social differences in vaccination behaviour, such as structural and group-specific barriers or psychological determinants. The SARS-CoV-2 virus (Severe Acute Respiratory Syndrome Coronavirus 2) was first detected in December 2019 in Wuhan, China. In early 2020, SARS-CoV-2, which causes the disease COVID-19, spread rapidly around the world . In addi® vaccine [Following the COVID-19 vaccination campaign began in late December 2020 with BioNTechPfizer’s Comirnaty vaccine , five ad vaccine , 9. Howe vaccine , 6. This vaccine . Since tHowever, various studies in Germany indicate social differences in willingness to be vaccinated and in COVID-19 vaccination uptake. For example, the willingness to be vaccinated against COVID-19 is more pronounced among older people, people with higher level of education and higher socioeconomic status, and people without a migration background , 12. AnaThe COVID-19 vaccination rate monitoring in Germany (COVIMO), which has been conducted regularly by the Robert Koch Institute (RKI) since early 2021, collects information on the willingness to get vaccinated and vaccine acceptance of the German-speaking population aged 18 years and older through a nationwide telephone-based survey. According to the results of the eighth survey (data collection: 15.09.–18.10.2021), COVID-19 vaccination rates are lower among people seeking for work or working short-time jobs and those living in the southern federal states of Germany . The ninThis paper aims to examine the influence of different social determinants on the COVID-19 vaccination status based on the sixth wave of the German Health Update (GEDA 2021). GEDA 2021 allows a differentiated description of COVID-19 vaccination rates according to a variety of sociodemographic, socioeconomic and regional characteristics after lifting the vaccination prioritization of particularly vulnerable groups. In addition to descriptive analyses, this paper identifies – by means of multivariate analyses – relevant social determinants of the COVID-19 vaccination status. In comparison to earlier studies, an age-differentiated presentation of the vaccination rates for the selected social determinants is also provided.Sixth follow-up survey of the German Health UpdateData holder: Robert Koch InstituteObjectives: Provision of reliable information on the health status, health behaviour and health care of the population living in Germany and their changes in the course of the SARS-CoV-2 pandemic.Study design: Cross-sectional telephone surveyPopulation: German-speaking population aged 16 years and older living in private households that can be reached via landline or mobile phoneSampling: Random sample of landline and mobile telephone numbers  from the ADM sampling system Sample size: 5,030 respondentsStudy period: July 2021 to December 2021GEDA survey waves:► GEDA 2009► GEDA 2010► GEDA 2012► GEDA 2014/2015-EHIS► GEDA 2019/2020-EHIS► GEDA 2021www.geda-studie.deFurther information in German is available at ‘German Health Update (GEDA)’ is a nationwide cross-sectional survey of the resident population in Germany, which has been conducted regularly since 2008 by the Robert Koch Institute (RKI) on behalf of the Federal Ministry of Health and is part of the health monitoring at the RKI . In addiThe sixth follow-up survey GEDA 2021) was conducted between July and December 2021 as a telephone interview using a programmed, fully structured questionnaire . The follow-up of the GEDA study as a continuous survey enabled the establishment of a flexible surveillance instrument at the RKI. In addition to so-called core modules, current pandemic-related topics such as vaccination behaviour, previous SARS-CoV-2 infections, domestic quarantine as well as special risk factors for SARS-CoV-2 infection could be flexibly integrated into the survey. The data allow analyses of changes in health status , health behaviour and the utilisation of health care services over the course of the pandemic [ was condThe survey is based on a random sample of landline and mobile telephone numbers  . AccordiA total of 5,030 people  participated in GEDA 2021 providing completed interviews. The combined Response Rate 3 (RR3) was calculated according to the standards of the American Association for Public Opinion Research (AAPOR)  and rangThe COVID-19 vaccination status was captured in GEDA 2021 by asking: ‘Have you already been vaccinated against the coronavirus disease COVID-19?’ . Associations between the uptake of COVID-19 vaccination (at least once) and social determinants were examined using the following indicators:Gender at birth was used to describe gender differences, i.e. the gender stated on the birth certificate (according to self-reports). The age of the respondents was categorised into the following groups: 18 to 39 years, 40 to 59 years and 60 years or older.To measure the educational status, study participants’ educational and vocational qualifications were categorised into low (ISCED 0–2), medium (ISCED 3–4) and high (ISCED 5–8) education groups according to the 2011 version of the International Standard Classification of Education (ISCED 2011) .Based on the self-reported monthly net income of the study participants’ households, the net equivalent income was calculated using the new equivalence scale of the Organisation for Economic Co-operation and Development (OECD), taking into account the composition of the household in terms of size and age structure , to consAs an indicator of the current region of residence, the study participants’ information on the federal state in which they currently live was used. For the analyses, the respective federal states in East and West Germany were combined, with the exception of Berlin as a separate category.In order to examine whether living in an urban or rural area has an influence on the COVID-19 vaccination uptake, the four settlement-structural district types of the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR)  were assIn addition to socioeconomic and regional characteristics, the COVID-19 vaccination status is presented by the (non-)presence of a history of migration. This is operationalized on the basis of the country of birth of the respondent and his/her parents as ‘without history of migration’, ‘own history of migration’ (people who have immigrated themselves) and ‘parental history of migration’ (at least one parent was not born in Germany). The term ‘history of migration’ as used in this paper and recommendations for analysing migration-related determinants in public health research are described in detail elsewhere .In the present article, the proportions of people who had received at least one COVID-19 vaccination are reported by selected social determinants and with 95% confidence intervals (95% CI). A significant difference between groups (determined by chi-square tests) is assumed if the p-value is less than 0.05. In the following, only the results of the descriptive analyses that are statistically significant according to respective chi-square test are reported here. To complement the bivariate analyses, multivariate adjusted prevalence ratios (PR) with corresponding 95% CIs and p-values were calculated using Poisson regression to identify relevant associations between the uptake of COVID-19 vaccination and social determinants. All social determinants were included in the regression analysis and adjusted for the survey month. The results of the Poisson regression are presented as a Forest plot. Statistically significant associations with the vaccination status are assumed if the respective 95% CIs of the social determinants do not include a value of 1.The analyses were performed with a weighting factor to correct for deviations of the sample from the population structure. In addition to the design weighting for different selection probabilities (mobile and landline), the sample was adjusted to the official population figures of the Federal Statistical Office with regard to age, gender, federal state, district type (as of: 31.12.2020) and education (micro census 2018). Missing values in the investigated variables were excluded from the bivariate and multivariate analyses.All analyses were conducted with StataSE 17.0  using the survey procedures.The analyses are based on data from 4,954 respondents aged 18 years and older  providing valid information on their COVID-19 vaccination status. Only participants aged 18 years and older were included in the analyses, as the recommendation for COVID-19 vaccination of those between 12 and 17 years of age was only given during the survey period in August 2021 .Overall, 86.7% of participants aged 18 years and older report having been vaccinated against COVID-19 at least once . The proportion of those vaccinated against COVID-19 increases with age , Table 2The results show a socioeconomic gradient in COVID-19 vaccination status . People Moreover, there is a detectable East vs. West gradient in the COVID-19 vaccination status. The proportion of people vaccinated against COVID-19 in West Germany (88.0%) is almost 10 percentage points higher compared to those from East Germany (79.8%). In Berlin, the vaccination rate of 87.1% is at a similar level as in West Germany. The East-West difference in COVID-19 vaccination status is more pronounced among male participants (11.7 percentage points) than among women (4.8 percentage points) . FurtherDifferentiating by age, the social differences in COVID-19 vaccination status are less pronounced among those aged 60 years and older than among 18 to 59-year-olds . RegardiThe multivariate Poisson regression analysis confirms that an age of 40 years and older is positively associated with the uptake of COVID-19 vaccination . In addiConsidering regional differences, while keeping the investigated social determinants statistically constant, there is also an association with the COVID-19 vaccination status: Respondents from East Germany and people living in rural areas have a lower vaccination rate. Furthermore, having a  history of migration remains independently associated to a lower uptake of COVID-19 vaccination according to multivariate control. However, the correlation between vaccination status and living in rural areas (p=0.034) or having a parental history of migration (p=0.039) is less pronounced compared to the other social determinants .This paper examines the influence of selected social determinants on COVID-19 vaccination status in Germany. Based on analyses of the GEDA 2021 study, the results suggest social differences in COVID-19 vaccination. In line with previous studies in Germany, the proportion of COVID-19 vaccinated people increases with age, higher level of education and income , 16, 17.Overall, it should be noted that the present paper describes differences by selected sociodemographic, socioeconomic and regional characteristics. However, the results only allow limited conclusions to be drawn about the reasons for the different uptake of COVID-19 vaccination. For example, the presence of a history of migration per se is not the cause of a lower vaccination rate. Rather, it is necessary to consider the underlying mechanisms and explanatory factors that are linked to the respective social determinants and influence the access to and uptake of vaccination. For example, structural (e.g. difficult access to vaccination services) and group-specific barriers (e.g. poor German language skills) or the influence of psychological factors on vaccination behaviour should be taken into account.People with a history of migration face specific barriers to the uptake of COVID-19 vaccination. The COVID-19 vaccination rate monitoring in Germany as an immigrant society (COVIMO focus survey) showed that German language skills (German as mother tongue or self-assessment of German language skills) explain much of the differences in the COVID-19 vaccination rate between people with and without a history of migration. Moreover, experiences of discrimination in the health or care sector also contribute to explaining the vaccination rate differences . AnotherElderly people have a specific vaccination indication  because Against the background of the generally higher vaccination rates in East Germany, e.g. with respect to vaccination against measles or influenza , 54–56, Psychological factors further contribute to explaining  differences in COVID-19 vaccination uptake. The established ‘5C’ model based on five ‘psychological antecedents of vaccination’: confidence (e.g. in the safety and effectiveness of the vaccine), complacency (perceived risk of the disease), constraints , calculation  and collective responsibility (willingness to protect others) , 59. ConThe influence of psychological factors on vaccination behaviour also differs by social determinants: Accordingly, the results of the representative survey of the BZgA (data collection: 26.07.–07.09.2021) show that older people (60 years and older) have a greater sense of responsibility for the community and confidence in the safety of vaccination, and carefully weigh up benefits and risk of vaccination. The COSMO study also indicates that age and the psychological factors confidence and cost-benefit calculation are associated . With reA major strength of the study is the ability to differentiated analyses of COVID-19 vaccination uptake according to a large variety of social determinants. In addition to age, gender, income and education, other relevant factors of vaccination behaviour were considered in the analyses for this paper, such as history of migration and selected regional characteristics . Simultaneous integration of the influencing factors in the Poisson regression analysis allowed the reciprocal control of the effects on the COVID-19 vaccination status. Compared to vaccination rates based on reported data, surveys such as GEDA 2021 can be used to identify the vaccination potential in different population groups and, by including further information, to design targeted measures aiming to overcome possible vaccination barriers. Accordingly, surveys in which the vaccination rates of different population groups are collected are an important supplement to reported data.Nevertheless, several limitations should be noted. Surveys aimed at directly capturing COVID-19 vaccination behaviour are assumed to have a biased sample. For example, people with positive attitudes towards vaccination are more likely to participate in such surveys than people who are less willing to get vaccinated and are therefore under-represented in the sample , 66. SimAnother limitation is that the case numbers for differentiated analyses by individual subgroups, for example 18 to 59-year-olds who belonging to the low education group or 18 to 59-year-olds having an own history of migration, are rather small. Consequently, comparisons between these subgroups have limited interpretability.A further limitation of the study is that the survey was conducted only in German and therefore people without German language skills were excluded from the survey. As a result, this article describes the proportion of vaccinated people in the German-speaking population aged 18 years and older. Against this background, the vaccination rate differences between people with and without a history of migration shown here may be underestimated. Furthermore, possible explanations for the differences in COVID-19 vaccination status cannot be comprehensively investigated on the basis of the study.Telephone-based surveys also show that people belonging to lower education groups are less likely to participate in the study than those of higher education groups. This can increase the risk of biased results caused by the systematic non-participation of various population groups (non-response bias). Using appropriate weighting procedures see  this is Based on analyses of the GEDA 2021 study, it was shown that the COVID-19 vaccination status differs by the selected social determinants. In order to design target group-specific interventions to overcome potential barriers to vaccination, further research is needed considering possible mechanisms and explanatory factors for the different uptake of a COVID-19 vaccination in the various population groups. Thus, it is not the educational status, the current region of residence or a history of migration per se that is decisive for the COVID-19 vaccination status, but other factors influencing vaccination behaviour must be taken into account, such as group-specific and structural barriers or psychological determinants, such as confidence in the safety of the vaccination.The seroepidemiological ‘Corona Monitoring Nationwide (RKI-SOEP-2)’ study, which was conducted from November 2021 to February 2022 as a cooperative project involving the RKI, the Socio-Economic Panel (SOEP) at the German Institute for Economic Research (DIW), the Institute for Employment Research (IAB) and the Research Centre of the Federal Office for Migration and Refugees (BAMF-FZ) allows various factors influencing COVID-19 vaccination behaviour to be taken into account , 71. A mThe limitation that GEDA 2021 was only conducted in German is addressed by the multilingual survey ‘German Health Update: Fokus’ (GEDA Fokus), which was conducted from November 2021 to May 2022 among people with Croatian, Italian, Polish, Syrian and Turkish citizenship at the RKI . The stuAgainst the background of the socially unequal distribution of SARS-CoV-2 infection risk and of the severe courses of COVID-19 , 74, 75,Increasing age is associated with higher uptake of COVID-19 vaccination.The proportion of people vaccinated against COVID-19 increases with higher levels of education and income.People from East Germany are less likely to be vaccinated against COVID-19.Social differences in COVID-19 vaccination status are lower among those aged 60 years and older than in 18 to 59-year-olds.There is a need to research the underlying mechanisms and explanatory factors of social differences in vaccination behaviour, such as specific access barriers or psychological determinants.


In Australia, peanuts are mainly grown in Queensland with tropical and subtropical climates. The most common foliar disease that poses a severe threat to quality peanut production is late leaf spot (LLS). Unmanned aerial vehicles (UAVs) have been widely investigated for various plant trait estimations. The existing works on UAV-based remote sensing have achieved promising results for crop disease estimation using a mean or a threshold value to represent the plot-level image data, but these methods might be insufficient to capture the distribution of pixels within a plot. This study proposes two new methods, namely measurement index (MI) and coefficient of variation (CV), for LLS disease estimation on peanuts. We first investigated the relationship between the UAV-based multispectral vegetation indices (VIs) and the LLS disease scores at the late growth stages of peanuts. We then compared the performances of the proposed MI and CV-based methods with the threshold and mean-based methods for LLS disease estimation. The results showed that the MI-based method achieved the highest coefficient of determination and the lowest error for five of the six chosen VIs whereas the CV-based method performed the best for simple ratio (SR) index among the four methods. By considering the strengths and weaknesses of each method, we finally proposed a cooperative scheme based on the MI, the CV and the mean-based methods for automatic disease estimation, demonstrated by applying this scheme to the LLS estimation in peanuts. Crop health is impacted by various abiotic and biotic stresses. Environmental factors such as drought, floods, and extreme temperatures can cause abiotic stress whereas the biotic stress can be caused by pathogens such as fungi, bacteria and nematodes . MoreoveEarly detection and identification of such diseases are beneficial for farmers and breeders as they can implement appropriate management strategies to minimise the impact of these diseases and prevent or mitigate possible yield losses. Since manual disease scouting is time-consuming and can introduce human bias , developRemote sensing can be an alternative approach for fast and unbiased disease scouting and measurement . Here, tR2 of 0.82 with NDRE during the late season of peanut growth. They selected the optimal threshold for each vegetation index manually which makes this approach less ideal for automation. In addition, some vegetation indices might not have a clear threshold for healthy and disease plot segmentation, which further impedes the use of this approach for such vegetation indices. Furthermore, the spectral band selection and vegetation index construction are also influential factors that determine what information is more important for crop health and disease estimation.There have been many studies on plant phenotyping using the Red-green-blue (RGB) , multispPhaeoisariopsis personata) and leaf rust (caused by Puccinia arachidis)  then5: 6:  Choose mean-based methods for disease estimation.else ifVI ∈  then7: 8:  Choose MI-based methods for disease estimation.else ifVI ∈ [SR] then9: 10:  Choose CV-based methods for disease estimation.end if11: R2 for MI-based method and 75% of R2 for mean-based method).Following the Procedure 1, we apply the proposed cooperative scheme to DAP-96 UAV images with the regression model from the three methods . The visual mapping of the LLS disease score over the 72 peanut plots is shown in This paper investigated the linear relationship between twelve widely used vegetation indices (VIs) with LLS disease ratings on peanuts. The correlation analysis of vegetation indices with LLS shows that the six vegetation indices namely, NDRE, SAVI, DVI, LAI, SR and REVI are highly correlated with LLS disease rating at the late growth stage of peanut (DAP-96) while the correlation is almost similar and lower for all vegetation indices at the earlier growth stage (i.e. DAP-77 or early stages).α. It seemed both NDRE and REVI involving a red-edge spectral band had a robust performance with |α| in a range of 0.8-1.4 although more experiments will be required on understanding the influence of α on the performance of the MI-based method in the future.The performance of the two alternative methods, namely, CV and MI-based methods proposed in this study were evaluated against that of the mean and threshold-based methods in estimating the LLS disease score using those six selected VIs for UAV images over different peanut plots. The results indicated that the MI-based method outperformed other three methods in all indices in most cases except the case where SR with the CV-based method achieved the best performance over other methods. For indices SAVI, DVI and LAI that depend on RGB and NIR bands without involving a red-edge spectral band, the MI-based method becomes the mean-based method. Hence, it seems that the MI-based method could represent the mean-based method for all selected indices both involving or not involving a red-edge spectral band. However, the MI-based method seemed variable with images/crops and indices in terms of choosing the optimal value for Overall, the threshold-based method seems redundant compared with other three methods in disease detection through analysing the UAV images. Considering the strengths and weakness of each of the MI-based, CV-based and mean-based methods, the following cooperative scheme seems an optimal solution for disease estimation through analysing the UAV images.(a)For indices SAVI, DVI and LAI without involving a red-edge spectral band, either the mean-based method or the MI-based method can be selected;(b)For indices NDRE and REVI involving a red-edge spectral band, the MI-based method should be selected;(c)For SR involving a red-edge spectral band, the CV-based method should be the first choice, backed up by the MI-based method.This study has two limitations. First, it only considered the vegetation index for regression analysis while the inclusion of other stress and multi-index decision-making could enhance the performance. Second, the manual LLS disease score was recorded only at the late growth stage which prevents us from investigating how early this method can be applied for disease estimation. As an extension of this work, advanced data-driven methods such as convolutional neural networks (CNN) can be investigated for building disease estimation models. Also, in choosing optimized parameters for prediction, simulated annealing  may be i


Disorders of consciousness are impaired states of consciousness caused by severe brain injuries. Previous resting-state functional magnetic resonance imaging studies have reported abnormal brain network properties at different topological scales in patients with disorders of consciousness by using graph theoretical analysis. However, it is still unclear how inter-regional directed propagation activities affect the topological organization of functional brain networks in patients with disorders of consciousness. To reveal the altered topological organization in patients with disorders of consciousness, we constructed whole-brain directed functional networks by combining functional connectivity analysis and time delay estimation. Then we performed graph theoretical analysis based on the directed functional brain networks at three topological scales, from the nodal scale, the resting-state network scale to the global scale. Finally, the canonical correlation analysis was used to determine the correlations between altered topological properties and clinical scores in patients with disorders of consciousness. At the nodal scale, we observed decreased in-degree and increased out-degree in the precuneus in patients with disorders of consciousness. At the resting-state network scale, the patients with disorders of consciousness showed reorganized motif patterns within the default mode network and between the default mode network and other resting-state networks. At the global scale, we found a lower global clustering coefficient in the patients with disorders of consciousness than in the controls. The results of the canonical correlation analysis showed that the abnormal degree and the disrupted motif were significantly correlated with the clinical scores of the patients with disorders of consciousness. Our findings showed that consciousness impairment can be revealed by abnormal directed connection patterns at multiple topological scales in the whole brain, and the disrupted directed connection patterns may serve as clinical biomarkers to assess the dysfunction of patients with disorders of consciousness. et al. reported the abnormal connection patterns based on directed functional brain networks at multiple topological scales and their correlations with clinical performances for the patients with disorders of consciousness. The findings suggested that directed interactions at multiple scales may exert a crucial role in the maintenance of consciousness.Guo   VS is characterized by no behavioural signs of self-related or environmental awareness,5 Graph theoretical analysis can be used to detect the altered topological organization in large-scale brain networks for DOC patients by measuring the inter-regional connection patterns.6 Previous DOC patients’ studies have reported abnormal connection patterns in the precuneus,7‐9 and prominent disorganization within and between the default mode network (DMN) and the frontoparietal network (FPN).10‐13 The graph theoretical analysis across multiple scales can provide detailed information on the disrupted connection patterns of functional brain networks for DOC patients.14Functional brain networks are organized across multiple topological scales ranging from individual regions (nodes) to the resting-state networks (RSNs) and the whole brain.15 Dynamic causal modelling (DCM) is a common method to infer a directed functional connection.16 Using this method, previous studies have found abnormal inter-regional interactions in DOC patients.17‐20 However, the DCM is based on specific hypotheses and limited in investigating the connection patterns of several brain regions, which is unsuitable for constructing a large-scale graph. Time delay estimation (TDE), a method recently used for calculating directed propagation activities, does not impose a constraint on the topological scale and could be applied in the whole-brain analysis.21 TDE has been widely used in revealing the characteristic of directed brain networks in healthy populations22‐25 and altered directed interactions in brain disorders.26‐29However, the majority of network studies for DOC patients relied on functional connectivity (FC) analysis measuring static relationships of inter-regional time series, which is technically straightforward but neglects the direction of interaction between distinct brain regions. Detecting the topological organization of directed functional brain networks may reveal the neural mechanism underlying impaired consciousness in DOC patients.The current study aims to construct whole-brain directed functional networks by combining FC analysis and TDE, and perform the graph theoretical analysis at multiple topological scales to detect the abnormal brain network organization in DOC patients. Specifically, we estimated topological properties at the nodal scale, the RSN scale and the global scale in directed functional brain networks. At the nodal scale, the nodal degree and the hub disruption index were calculated to identify the regions with abnormal directed connection patterns in DOC patients. At the RSN scale, we used motif to detect the aberrant organization rules within and between RSNs in DOC patients. At the global scale, the global efficiency and the global clustering coefficient were computed to describe the alterations of whole-brain functional integration and segregation in DOC patients. Finally, we performed a canonical correlation analysis (CCA) to reveal the relationships between the abnormal directed graph theoretical metrics and clinical scores in DOC patients. We hypothesized that DOC was associated with the breakdown of directed interactions at multiple topological scales in functional brain networks.A total of 45 DOC patients were recruited from the Liuhuaqiao Hospital in Guangzhou City, Guangdong Province, China. We excluded low-quality resting-state fMRI (rs-fMRI) data using the following exclusion criteria: (1) severe brain atrophy or focal brain damage (12 patients), (2) artefacts (4 patients) or (3) excessive head motion (translation ≥ 3 mm in any plane or rotation ≥ 3° in any axis) during the rs-fMRI scanning (8 patients). In the end, we included a total of 21 DOC patients  for the subsequent analyses. The Coma Recovery Scale-Revised (CRS-R) was used to assess the states of consciousness of the DOC patients by two medical doctors (QX and RY). CRS-R is a 23-item scale for measuring the behavioural responses of DOC patients, which includes 6 sub-scales for measuring auditory, visual, motor, oromotor, communication and arousal levels, respectively. The detailed clinical information for these patients is listed in 2, data matrix = 64 × 64, slice thickness = 3.6 mm, inter-slice gap = 0.6 mm, 36 axial interleaved slices covering the whole brain and 240 volumes obtained in about 8 min. The high-resolution brain structural images were obtained using a T1-weighted 3D fast spoiled gradient recalled sequence with the following parameters: TR = 8.86 ms, TE = 3.52 ms, FOV = 240 × 240 mm2, data matrix = 256 × 256, FA = 90°, voxel size = 0.94 × 0.94 × 1  mm3 and 176 sagittal slices. Both the fMRI and structural data were acquired in the same session for each subject.All MRI data were acquired on a GE Signa HDX 3 T MR scanner with an eight-channel phased-array head coil. The rs-fMRI data were obtained using a single-shot multi-slice gradient-echo EPI sequence with the following parameters: repetition time (TR) = 2000 ms, echo time (TE) = 26 ms, flip angle (FA) = 90°, field of view (FOV) = 240 × 240 mmhttps://www.fil.ion.ucl.ac.uk/spm) and DPABI (http://www.rfmri.org/dpabi).30 Specifically, we performed (1) removal of the first 10 time points, (2) slice-timing correction, (3) head-motion correction, (4) normalization of the functional and structural images into the MNI-152 standard space with a 3 mm3 isotropic resolution, (5) spatial smoothing with a 6 mm full width at half-maximum Gaussian kernel and (6) band-pass filtering (0.01–0.1 Hz). In addition, we regressed out the nuisance variables, including 24 head movement parameters,31 global brain signal, white matter signal and cerebrospinal fluid signal.The rs-fMRI data were preprocessed using SPM12 , cingulo-opercular network , auditory network , DMN (58 ROIs), visual network , FPN (25 ROIs), salience network , subcortical network , ventral attention network (9 ROIs) and dorsal attention network . In this study, we took each ROI as a node and the inter-nodal directed functional connection as an edge, which was determined by combining the FC analysis with the TDE as follows.For each subject, we parcellated the brain into 264 functional regions of interest (ROIs) according to the Power-264 template.43 Then, according to the method applied in previous DOC studies,45 we binarized the FC matrix at four different threshold levels . Specifically, for a given threshold, we took the above threshold elements as 1 and the others as 0 for each subject.To represent the strength of the edge, we derived the FC matrix for each subject by calculating Pearson’s correction coefficient between all pairs of time series. We only retained positive correlation values in each FC matrix because the interpretation of negative correlation is ambiguous.ix and jx) from two nodes, we fixed one time series and shifted the other forward or backward by several lag values  to calculate the lagged cross-covariance function (CCF). The lagged CCF represents the correlation between two time series at all possible τ and is given byThe direction of each edge was determined using TDE. For two time series   . The det11Finally, for each subject, we constructed the directed functional connection matrix by multiplying each element in the FC matrix by its counterpart in the TD matrix, as illustrated in Din) and out-degree (Dout)47 to measure the driven and driving connection patterns between brain regions. For a given node, the Din is the number of incoming edges that point to the node and the Dout is the number of outgoing edges that point away from the node (Din (Dout) value are considered driven (driving) hubs, which exert more influence over brain network function compared with the nodes with fewer connections. We identified the top 2.5% of the nodes with the highest Din (Dout) as the driven (driving) hubs according to a previous study.48At the nodal scale, we calculated in-degree  of a subject is the slope fitted to the linear regression model between Din (Dout) of the control group and the difference between Din (Dout) of the subject and the control group, which is given byIn addition, we also calculated the hub disruption index of yin/out represents the difference of the Din (Dout) of a subject minus the mean Din (Dout) of the control group, xin/out represents the mean Din (Dout) of the control group and bin/out represents the residual of the regression. The κin (κout) close to −1 suggests radical reorganization of network hubs of the subject, meaning that the nodes with the highest Din (Dout) in the controls show the greatest decrease in the subject, or the nodes with the lowest Din (Dout) in the controls show the greatest increase in the subject.8where M nodes with at least M−1 edges, which is used to reveal basic building blocks in directed brain networks.50 Given a subgraph size, M, there is a constant number of wiring configurations, and these configurations are defined as motif classes. For example, when M = 2, 3, 4 and 5, the number of motif classes is 2, 13, 196 and 9364, respectively. In this study, we considered the three-node motif (M = 3) that has been identified in human structural and functional brain networks.51‐53 For the three-node motif, there are five unidirectional classes and eight reciprocal classes. Only the five unidirectional classes were analysed in this study, which were labelled as M1, M2, M3, M4 and M5  was used to calculate the number of occurrences of each class in a certain network.ectively . In addi54 and the global clustering coefficient 56 were calculated to analyse the functional integration and segregation of the directed brain network. The description of these graph theoretical metrics is listed in the At the global scale, the global efficiency Din and Dout metrics with significant between-group differences, (2) the motif variate, which is the linear combination of MFS metrics with significant between-group differences; and (3) the global variate, which is the global metrics with significant between-group differences. The maximal correlation coefficient between any pair of graph theoretical variate and clinical variate was obtained.CCA is an approach to modelling the maximal correlation between two high-dimensional multivariate datasets based on a linear combination. In this study, we performed CCA to link the abnormal graph theoretical metrics and six sub-scores of CRS-R for DOC patients. Specifically, the graph theoretical metrics with significant between-group differences at any topological scale were linearly combined to a graph theoretical variate, and six sub-scores of CRS-R were linearly combined to a clinical variate for each subject . Three gTo quantify the contribution of original graph theoretical metrics with significant between-group differences and sub-scores of CRS-R for significant CCA modes, we calculated Pearson’s correlation between the graph theoretical metrics and corresponding graph theoretical variates as well as between the sub-scores of CRS-R and corresponding clinical variates for significant CCA modes. Then, the Pearson correlation analysis was performed between the graph theoretical metrics that were significantly correlated with corresponding graph theoretical variates and the sub-scores of CRS-R that were significantly correlated with corresponding clinical variates.Din, Dout, κin, κout, MFS, global efficiency, and global clustering coefficient between the DOC patients and the healthy controls. In the calculations, we regressed out age, sex and mean framewise displacement (FD). False discovery rate (FDR) correction was adopted to control multiple comparisons for the statistical analysis at the nodal scale or RSN scale. Specifically, at the nodal scale, all P-values of 227 Din (Dout) values were corrected using the FDR correction. At the RSN level, all P-values of 245 MFS values, including 165 MFS values between pairs of RSNs, 30 MFS values between one-versus-all-other RSNs and 50 values within RSNs, were also corrected by the FDR method. The significance of the CCA modes was estimated using a non-parametric permutation test with 5000 iterations. The significance threshold was set at P < 0.05 for all analyses.A non-parametric permutation test with 5000 iterations was used to determine significant differences in the To test the robustness of the observed differences in the graph theoretical metrics between the DOC patients and the healthy controls, we repeated the calculations using two additional processing strategies: (1) without spatial smoothing and (2) using the maximum lagged correlation that corresponds to the maximum lagged CCF as the strength of the edge.No significant difference was found in age, sex or mean FD between the DOC patients and the healthy controls. The statistical information of the patients and the controls is listed in Din or Dout. The DOC patients showed significantly lower Din in six nodes and significantly higher Din in four nodes than in the healthy controls. We also found that the Dout was significantly lower in 12 nodes and significantly higher in 7 nodes in the patients than in the controls. The detailed information for these nodes is listed in κin and κout were significantly lower in the patients than in the controls. We found Din (Dout) in several nodes showing radical reorganization in the patients compared with the controls  existed between the RSNs in the patients and the controls. Between one-versus-all-other RSNs: 1, M2 and M3) between one-versus-all-other RSNs between the patients and the controls. The patients had significantly higher MFS in all the three classes between the DMN-versus-all-other RSNs and significantly lower MFS in all the three classes between the AUN-versus-all-other RSNs than the controls. The detailed information of MFS between one-versus-all-other RSNs is listed in Within RSNs: We found that five motif classes  occurred within each RSN for the patients and the controls. Whole brain: The patients showed significantly higher MFS of class M2 and significantly lower MFS of class M4 in the whole brain compared with the controls .No significant difference was observed in the global efficiency between the DOC patients and the healthy controls. The global clustering coefficient was significantly lower in the patients than in the controls  Dout of the left inferior parietal gyrus and (iii) Dout of the right precentral gyrus. Din of the right insula. The detailed information is listed in For CCA mode between the degree variate and the clinical variate, 4 within the DMN, (ii) M5 within the DMN, and significantly negatively correlated with the MFS of (i) M2 between the CON–DMN, (ii) M2 between the DMN-versus-all-others RSNs, (iii) M2 between the FPN-versus-all-others RSNs and (iv) M2 within the whole brain. 2 between the FPN-versus-all-other RSNs and (ii) M2 within the whole brain. The visual sub-score is significantly positively correlated with the MFS of (i) M4 within the DMN and (ii) M5 within the DMN, and significantly negatively correlated with the MFS of (i) M2 between the DMN-versus-all-other RSNs and (ii) M2 within the whole brain. The motor sub-score is significantly positively correlated with the MFS of M4 within the DMN, and significantly negatively correlated with the MFS of M2 within the whole brain. The oromotor sub-score is significantly positively correlated with the MFS of M5 within the DMN and significantly negatively correlated with the MFS of M2 between the DMN-versus-all-other RSNs. The detailed information is listed in For CCA mode between the motif variate and the clinical variate, First, the main results were repeatable when using the non-smoothed data, which are shown in The current study constructed whole-brain directed functional networks by combining FC analysis with TD estimation, calculated multi-scale graph theoretical metrics based on the directed brain networks, and estimated relationships between the abnormal graph theoretical metrics and the sub-scores of CRS-R for DOC patients. We found disrupted directed connection patterns at multiple topological scales in DOC patients, and significant correlations between the disrupted directed connection patterns at both nodal and RSN scales with clinical scores in DOC patients.Din and Dout in the DOC patients compared with the healthy controls  between the RSNs in the DOC patients compared with the healthy controls  within RSNs than in the healthy controls  between the DMN-versus-all-other RSNs in the patients than in the controls  as a target, the transcranial direct current stimulation and the repetitive transcranial magnetic stimulation can prominently improve the clinical performances of MCS patients.80 Thus, we inferred that the DMN plays a pivotal role in maintaining awareness of perceptible surroundings.12We also observed a significant correlation between the abnormal MFS metrics and the sub-scores of CRS-R in the DOC patients . This re32 to construct the directed brain networks because of its reasonable partitioning and extensive use.35‐39 However, there was no established standard for assessing template suitability when constructing brain networks. In addition, we regressed out the global signal when preprocessing the rs-fMRI data to perform TDE.21 Although a portion of the global signal may include neural activity,82 the majority of the components of the global signal contain artefacts related to physiological noises and head motions.83‐85 Because there was no standard method to extract the true signal and denoise the artefacts, the analysis without global signal regression is likely to bias the results of network estimation.86Several limitations should be addressed. First, the current study analysed the rs-fMRI data from 21 DOC patients with different states of consciousness (VS and MCS), which may affect the generalizability of the results. Further studies need to collect a large sample and classify DOC patients into distinct sub-types for detecting the directed brain network organization related to impaired consciousness. Second, the selection of the brain template may affect the results. In the current study, we selected the Power-264 templateThe current study analysed the brain network organization at multiple topological scales based on directed functional connections for DOC patients. At the nodal scale, the patients showed abnormal directed connection patterns in the precuneus and the thalamus. At the RSN scale, we observed the reorganization of three-node directed connection patterns within and between DMN in the patients. At the global scale, we found significantly decreased functional segregation in the patients. Furthermore, the CCA showed the clinical correlations of directed connection patterns at both nodal and RSN scales. The findings may suggest that the disruptions of whole-brain directed interactions are associated with clinical characteristics of impaired consciousness.fcad069_Supplementary_DataClick here for additional data file.


COVID-19 continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear.To project COVID-19 hospitalizations and deaths from April 2023–April 2025 under two plausible assumptions about immune escape (20% per year and 50% per year) and three possible CDC recommendations for the use of annually reformulated vaccines .The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023–April 15, 2025 under six scenarios representing the intersection of considered levels of immune escape and vaccination. State and national projections from eight modeling teams were ensembled to produce projections for each scenario.The entire United States.None.Annually reformulated vaccines assumed to be 65% effective against strains circulating on June 15 of each year and to become available on September 1. Age and state specific coverage in recommended groups was assumed to match that seen for the first  COVID-19 booster.Ensemble estimates of weekly and cumulative COVID-19 hospitalizations and deaths. Expected relative and absolute reductions in hospitalizations and deaths due to vaccination over the projection period.From April 15, 2023–April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November–January. In the most pessimistic scenario , we project 2.1 million  hospitalizations and 209,000  deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000  fewer hospitalizations and 33,000  fewer deaths, while vaccination of all eligible individuals results in 431,000  fewer hospitalizations and 49,000  fewer deaths.COVID-19 is projected to be a significant public health threat over the coming two years. Broad vaccination has the potential to substantially reduce the burden of this disease. Three and a half years after the SARS-CoV-2 virus first emerged in Wuhan, China, it seems the global community has transitioned from confronting COVID-19 as a pandemic emergency to managing it as an endemic, seasonally recurring virus ,4. CurreGoing forward, one of the main tools for mitigating the impact of annual COVID-19 epidemics will be vaccination. As with influenza ,9, contiThe U.S. COVID-19 Scenario Modeling Hub (SMH) is a long-standing multi-team modeling effort that aims to project how the COVID-19 epidemic is likely to unfold in the mid- to long-term under various conditions ,13. ThesHere, we present the results of applying the SMH approach to project the likely course of the COVID-19 epidemic in the United States over a two-year period  under different assumptions about the average speed of antigenic drift and possible recommendations for the use of reformulated annual COVID-19 vaccines from the Centers for Disease Control and Prevention (CDC).To estimate the potential impact of vaccination on COVID-19 hospitalizations and deaths, we invited multiple teams in an open call to provide two years of projections for six scenarios within the SMH framework ,14. TeamSix scenarios were created representing the intersection of two axes: one representing the average speed of antigenic drift  over the two-year projection period, and the second representing differing assumptions about CDC recommendations for, and uptake of, a reformulated SARS-CoV-2 vaccine. The antigenic drift axis consisted of (1) a ‘low immune escape’ scenario, where the SARS-CoV-2 virus evolves away from the immune signature of circulating variants at a rate of 20% per year , and (2) a ‘high immune escape’ scenario with an immune escape rate of 50% per year.The vaccination axis consisted of three levels based on possible COVID-19 vaccine recommendations under consideration by the CDC Advisory Committee on Immunization Practices (ACIP): (1) no recommendation for annual vaccination with a reformulated vaccine, (2) a recommendation for those aged 65 and above (65+), and (3) a recommendation for all eligible groups. Across all scenarios, the vaccine is assumed to be reformulated to match the predominant variants circulating as of June 15 each year, and to become available to the public on September 1 of the same year. The annual uptake of reformulated vaccines in recommended groups is projected to follow the age group specific  uptake patterns observed for the first booster dose in each state  ; correspAll contributing models were directed to incorporate waning immunity, with a requirement that the median waning time of protection against infection aligned with the designated range of 3–10 months. Furthermore, the incorporation of SARS-CoV-2 seasonality was required, though teams had discretion in terms of its implementation. Teams were directed not to consider changes in non-pharmaceutical interventions over the projection period. Full scenario details are available on GitHub.Eight different modeling teams contributed projections of weekly incident and cumulative COVID-19 hospitalizations and deaths for April 15, 2023–April 15, 2025 for all states and at the national level . Each team provided up to 100 representative epidemic trajectories for each scenario and outcome. Trajectories were used to generate a probability distribution of incident outcomes each week. Distributions at each week were combined using the trimmed-linear opinion pool method (LOP) to create ensemble projections ,17–19. Ametafor’ [To estimate the expected impact of vaccination, the mean and variance in cumulative deaths and hospitalizations were calculated over the period of interest based on submitted trajectories. Within each model, the expected impact of vaccination was determined by calculating the difference, or ratio, of projected deaths and hospitalizations between different vaccination scenarios sharing the same rate of immune escape, with variances estimated using the Delta method . These imetafor’ ,22. We nBased on the ensemble of projections from eight contributing models under plausible assumptions about the viral evaluation and annual vaccination recommendations from the CDC, we project that between April 15, 2023 and April 15, 2025, the United States will experience annual COVID-19 epidemics peaking between November and January and causing approximately 1 million cumulative hospitalizations and 100,000 cumulative deaths each year . The extEnsemble projections indicate that annual vaccination has the potential to substantially reduce both hospitalizations and deaths from COVID-19 . In highExpanding vaccination recommendations to all individuals would lead to substantial additional reductions in deaths and hospitalizations . Under tA significant factor contributing to state-level variation in the projected impact of vaccine recommendations is the assumed uptake level of reformulated vaccines , and S5.Based on the ensemble of projections from eight modeling teams for the next two years (April 2023–April 2025), it is expected that COVID-19 will remain a persistent public health threat in the United States for the foreseeable future. Nevertheless, our projections highlight that annual vaccination with reformulated vaccines can substantially mitigate this burden if coverage reaches levels observed for the first  COVID-19 booster.Across all scenarios, our projections indicate that COVID-19 hospitalizations and deaths would be substantially less than what was seen in the early stages of the pandemic . NonethWhile the projected impact of annual vaccination on disease burden is significant, it is highly dependent on assumed vaccine uptake. This gives us reason for both caution and hope. Previous CDC booster recommendations, including that for the 2022 reformulated vaccine , have not achieved the coverage observed for the first booster . ReducedAs with any attempt to project into the future, our projections come with major caveats and limitations. First and foremost, scenario projections are conditional on often strict scenario assumptions. Both vaccine coverage and effectiveness might deviate considerably from scenario assumptions, although historical trends of influenza vaccination suggest that achieving higher coverage is unlikely . Additionally, if future variants differ in intrinsic transmissibility or disease severity from that of the current Omicron lineages, the projected disease burden may alter accordingly. Furthermore, all scenarios were built on the assumption of continuous immune escape with a constant rate. However, the emergence of new SARS-CoV-2 variants showing a significant level of antigenic drift within a very short span  coulDespite its limitations, ensembling scenario-based projections from multiple teams is one of the most robust approaches for estimating COVID-19’s future burden and the potential benefits of vaccination, providing valuable information for public health planning. Our results show that COVID-19 will likely remain a major threat to human health in the United States in the coming years. In the face of this threat, broad vaccination against SARS-CoV-2 has the potential to save tens of thousands of lives each year.Supplement 1


Inflammatory bowel disease (IBD) is a long-term inflammatory immune-mediated gut illness with several extra-intestinal complications. The aims of this study were to identify a novel network-based meta-analysis approach on the basis of the combinations of the differentially expressed genes (DEGs) from microarray data, to enrich the functional modules from human protein–protein interaction (PPI) and gene ontology (GO) data, and to profile the ncRNAs on the genes involved in IBD. The gene expression profiles of GSE126124, GSE87473, GSE75214, and GSE95095 are obtained from the Gene Expression Omnibus (GEO) database based on the study criteria between 2017 and 2022. The DEGs were screened by the R software. DEGs were then used to examine gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The ncRNAs including the miRNAs and ceRNAs were predicted on the PPIs visualized using Cytoscape. Enrichment analysis of genes with differential expression (n = 342) using KEGG and GO showed that the signaling pathways related with staphylococcus aureus and pertussis bacterial infections may stimulate the immune system and exacerbate IBD via the interaction with human proteins including Fibrinogen gamma chain (FGG), Keratin 10 (KRT10), and Toll like receptor 4 (TLR4). By building a ceRNA network, lncRNA XIST and NEAT1 were determined by affecting common miRNAs, hsa-miR-6875-5p, hsa-miR-1908-5p, hsa-miR-186-5p, hsa-miR-6763-5p, hsa-miR-4436a, and hsa-miR-520a-5p. Additionally, the chromosome regions including NM_001039703 and NM_006267, which produce the most potent circRNAs play a significant role in the ceRNA network of IBD. Also, we predicted the siRNAs that would be most effective against the bacterial genes in staphylococcus aureus and pertussis infections. These findings suggested that three genes , six miRNAs , two lncRNAs (XIST and NEAT1), and chromosomal regions including NM_001039703 and NM_006267 with the production of the most effective circRNAs are involved in the ncRNA-associated ceRNA network of IBD. These ncRNA profiles are related to the described gene functions and may play therapeutic targets in controlling inflammatory bowel disease. IBD is associated with periods of stomach pain, fever and fatigue, loss of appetite, bloody stool, weight loss, and a stimulation of immune system cells that cause inflammation by producing cytokines3. IBD is triggered by a combination of environmental variables, infectious pathogens, and genetic predisposition, which results in abnormal immune reactions to intestinal mucosa4. Inflammatory bowel disease has been on the rise over the past few decades, and since it can waste a society's human resources and render them ineffective, must be specified what causes it. This has enabled researchers to develop prevention strategies and therapeutic approaches5.Both Crohn disease (CD) and ulcerative colitis (UC), two primary types of inflammatory bowel disease (IBD), are defined by an abnormal immunological response of the intestinal mucosa. Current research on the development of diseases points to a complicated interplay between numerous environmental and genetic factors7. According to particular research, altering the community's diet has affected the population of the intestinal microbiome, which has triggered the immune system to respond to this microbiome and to result in intestinal inflammation9. Polovsky's experiment showed that whereas lactobacillus and bifidobacterium levels reduce in CD patients compared with control subjects, bacteroidetes levels increase2. According to research, enterobacteria levels considerably rose in CD patients10. Several investigations indicated an association between staphylococcus aureus and pertussis infections and the development or worsening of symptoms in IBD patients13. It seems that more studies should be done in order to determine the molecular mechanism and exact path of inflammatory bowel disease.In the past, some studies investigated external factors affecting the incidence of inflammatory bowel disease, including the amount of smoking in the occurrence or exacerbation of symptoms in patients with inflammatory bowel disease15. Involved in IBD pathobiology, ncRNAs are essential gene regulators at the transcriptional and translational stages16. The miRNAs have received the most attention out of all of ncRNAs, and IBD has been discovered to have many altered miRNA expression profiles17. The modulation of cytokines and chemokines with miRNAs, it is known that aberrant autophagy, intestinal epithelial permeability, and activation of the necrosis factor-B (NF-B) are suggested as other inflammatory mechanisms in IBD20. LncRNAs and circRNAs are knowing essential for gene regulations22. Several circRNAs and lncRNAs have also been discovered as biomarkers for tumor prediction and diagnosis24. It seems that investigating the profiles of noncoding RNAs such as circRNAs and lncRNAs on the gene sets can be an interesting and forward-looking field in the treatment of IBD. Moreover, recent research suggests that circRNAs and lncRNAs may be interesting therapeutic targets for a range of disorders25. The attention of IBD research will undoubtedly shift to lncRNA and circRNA.On the other hand, numerous non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and micro RNAs (miRNAs), have recently been linked to the etiology of inflammatory bowel disease (IBD)Based on the above descriptions, the aim of study was to find the important modules on the gene enrichment using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) studies in Gene Expression Omnibus (GEO) database. Then, to explore the critical miRNAs, lncRNAs and circRNAs on the gene networks. Additionally, we projected the effective siRNAs on the bacterial genes involved in the occurrence of IBD. This study was expected to reveal probable regulatory mechanisms behind the incidence of IBD.http://www.ncbi.nlm.nih.gov/geo) including inflammatory bowel disease, IBD, Homo sapiens (organism). The datasets were filtered on the data obtained from microarray technique, sample size > 50, gene size > 15,000 and without interventional agents between 2017 and 2022. The finalized microarray data for the meta-analysis were GSE126124 (GPL6244)26, GSE87473 (GPL13158)27, GSE75214 (GPL6244)28, and GSE95095 (GPL14951)29. Only samples from each dataset that met the following criteria were chosen to continue the analysis: (I) The GSMs had to be from colon and intestinal tissues (not blood). (II) The tissue should exhibit active inflammation (not inactive). (III) Without receiving any manipulations or treatments, samples from the IBD (Ulcerative colitis (UC) or Crohn's disease (CD)) group. Table The following search terms were used to identify and download the mRNA microarray expression profile datasets from the GEO database (http://string-db.org) online database (version 11.5)30 was used to generate the PPI network, and the following parameters were used: a confidence score > 0.7 is applied as the threshold value to assess the interactions of protein pairs, databases, experiments, and text mining are the active interaction sources. Finding functional connections between proteins may shed light on the processes that give rise to disease development. Open-source bioinformatics software platform for visualizing molecular interaction networks is called Cytoscape (version 3.9.1) that was used to more analysis to find essential genes in the network based on the node and edge percentiles (75th) and network analysis with the Cytoscape tool "NetworkAnalyzer"31, which can calculate a comprehensive set of topological metrics for undirected and directed networks.The Search Tool for the Retrieval of Interacting Genes  (http://david.abcc.ncifcrf.gov) and the Cytoscape plug-in ClueGO33 to determine the biological significance of genes.To identify significantly regulated functions of DEGs, the gene ontology (GO) enrichment analysis was carried outhttp://mirwalk.umm.uni-heidelberg.de), a comprehensive database of predicted and validated miRNA-target interactions, was used to predict relevant miRNAs that can modulate the hub genes , position = 3'UTR). The networks between the key genes and the most effective miRNAs were drawn on the specific criteria of each miRNA. In the next step, using the DIANA (https://diana.e-ce.uth.gr/home)  and starbase database (https://starbase.sysu.edu.cn/index.php)  .The study looked in the proteins of staphylococcus aureus and bordetella pertussis that were interacted with human proteins to trigger or exacerbate the bacterial infections. The bacterial gene sequences involved in the cellular signaling transfection were scanned to predict the nucleotide positions with greater energetic stability for designing of the siRNA using IntaRNA database . In expression analysis, normalization and data processing are crucial procedures since they could have an impact on the results of the meta-analysis. Each of the gene samples (GSM) underwent a log2 transformation. Then, the four datasets were merged and combat procedures from the SVA package35 were applied to the merged data to reduce study-specific batch effects (batch correction). Using the LIMMA package36, Student's t-test was done and genes with differential expression levels between the two groups of controls and IBD patients were identified. DEGs were defined as genes with a P-value < 0.01 and |log2FC|> 1.The R software tool and the Affy packageAfter downloading the GSEs Table , and perA primary network of DEGs  was created using active interaction sources such as experiments, text mining, databases, and interaction scores greater than 0.7 from the STRING server. Then, the network was visualized in Cytoscape software . Additional studies were conducted to discover more crucial genes in the network (118 nodes and 211 edges) on the percentiles (75th) of the node (logFC of each gene) and edge (the sum of the scores of the edges in STRING server) scores  and KEGG analyses, were carried out to further perform a systematic characterization and investigate the biological functions of the identified DEGs in IBD vs. control samples Fig. .Figure 5By considering KEGG enrichment Fig.  and examSmall noncoding RNAs called microRNAs (miRNAs) were chosen for FGG, KRT10, MD2, TLR4, CD14 genes in the pathway upstream. In miRNA-gene network, the edges were weighted by defining of sum of the scores  of each miRNA in the miRWalk database (Supplement 4). The network was finally limited on the miRNAs that were shared among genes Fig. . The lncThe bacterial proteins are proposed in staphylococcus aureus , and in bordetella pertussis  in IBD. The complete genomes of staphylococcus aureus and bordetella pertussis were taken from the NCBI database. The nucleotide sequence of the genes  involved in the occurrences of these infections in humans that may stimulate the path leading to inflammatory bowel disease were scanned for prediction of best positions for designing of siRNAs. In the intaRNA database, the most effective siRNAs on gene function were predicted based on the energy released from the hybridization of siRNA and mRNA Fig. .Figure 137. The development of IBD points to a complicated subject between numerous important factors38. The correct understanding of relationships between these factors clears the pathophysiology of IBDs. IBDs may therefore have potential diagnostic and therapeutic targets if the molecular mechanisms of IBDs are understood using high-throughput technologies, which has been widely employed to study the pathogenic processes of IBD40.The types of inflammatory bowel disease (IBD) including both Crohn's disease (CD) and ulcerative colitis (UC), are characterized by an abnormal immunological response42.In the current investigation, 342 DEGs, including 193 upregulated and 149 downregulated genes, were identified in the IBD samples. The top 75% module of the network's DEGs was subjected to a GO analysis, and the results showed that DEGs were particularly enriched in cytokine activity, cytokine receptor binding, inflammation, response to bacteria, response to molecules of bacterial origin, leukocyte migration, response to lipopolysaccharide, and cytokine-mediated signaling pathways. The aforementioned GO keywords have been shown in prior research to be potentially significant events in the etiology of IBDs44. Immunological system activation causes immune reactions, gastrointestinal system inflammation, and the onset of IBD symptoms45.According to the results of the KEGG pathway analysis, the DEGs were particularly enriched in the signaling pathways for cytokine-cytokine receptor interaction, IL-17, TNF, viral protein interaction, rheumatoid arthritis, lipid and atherosclerosis, chemokine, pertussis, and staphylococcus aureus infection. Previous studies have shown that the development of inflammatory bowel disease is caused by the interaction of immune system molecules , cells , etc.), signaling pathways  and other factors (foreign microbes or immune system-stimulating drugs)49. Some studies have shown that by changing people's diets towards fast foods with high sugar, the microbial population of the digestive tract changed and harmful bacterial species  replaced the beneficial bacterial species  in the digestive tract, which stimulated the immune system and created a response to this harmful microbial population. This results in inflammation and gastrointestinal diseases like IBD51.According to several studies, mycobacterium paratuberculosis stimulates the immune system's signaling pathways, which may trigger or aggravate inflammatory bowel disease39. About 50% of healthy adults have persistent or sporadic staphylococcus aureus colonization of the skin around their noses, but it has recently been identified as a key early colonizer of an infant's gut53. There is little information on the intestinal colonization and fecal transport of methicillin-resistant s. aureus (MRSA) in IBDs55.Although previous studies have found traces of bacterial infection by staphylococcus aureus and pertussis in IBD patients but the pathways and genes involved in the potential incidence of bowel inflammation by infectious agents of staphylococcus aureus and pertussis are interested to findIn this study, the onset of inflammatory bowel disease due to the possibility that infections caused by staphylococcus aureus and pertussis were evaluated. According to the enrichment, there were identified the most susceptible pathways and genes that could be studied to prevent inflammation caused by the bacteria.57. Some studies suggested that FGG (fibrinogen gamma chain) plays as an early mediator in the cross-talk between coagulation and inflammation, and it can stimulate immune system reactions by interacting with bacterial agents and immune system cells58.According to research, KRT10  increases in people with inflammatory bowel disease and physically alters and rearranges the structure of the gastrointestinal tract's epithelial cells. This alteration affects the permeability of the epithelial layer and the cell’s ability to self-renew. These conditions make it possible for pathogens to enter the body's interior layers and induce bacterial infection like IBD62. It has been demonstrated that staphylococcus aureus surface proteins SasG (surface protein G) and Pls (surface protein of certain methicillin-resistant Staphylococcus aureus strains), which were previously discovered through in vitro studies of genome sequences, also contribute to bacterial adhesion to epithelial cells, and in their presence, the adhesion strength of staphylococcus aureus to epithelial cells increases63.The ability of staphylococcus aureus to adhesion to squamous epithelial cells was consistently shown to be influenced by ClfB (clumping factor B), IsdA (iron-regulated surface determinant protein A), SdrC (serine-aspartate repeat-containing protein C), and SdrD (serine-aspartate repeat-containing protein D). A mutant with no copies of all four proteins exhibited total adhesion defects. A vaccine against two or more of these surface proteins could significantly reduce carriage as well as the likelihood of infection and spread64. MD-2 is a small secreted glycoprotein that binds to the hydrophobic region of LPS and the extracellular domain of TLR4. TLR4 is activated by the interaction between MD-2 and LPS65. After LPS stimulation, CD14 inhibits the rise in barrier permeability and leads to activation of the NF-kB signaling pathway66.The pertussis lipopolysaccharides (LPS) and lipooligosaccharides (LOS) are ligands for the receptor complexes that include the Toll-like receptor 4 (TLR4), MD-2, and CD14. Inflammatory and immunological defense responses are triggered by the stimulations of these receptor complexes, which activate signaling pathways like NF-KB and causes the expression of antimicrobial genes and the release of cytokines, which can lead to inflammation68. A palmitate residue is transferred by PagP  from a phospholipid's sn-1 position to the N-linked hydroxymyristate on the proximal unit of lipid A. One outer membrane enzyme involved in the production of lipid A is PagP69.A typical A-B toxin is pertussis toxin (PTX). ADP-ribosyl transferase activity is seen in the A-subunit (PTXA or S1 subunit). The B-subunit, which is made up of the S2–S5 subunits , binds cell surface molecules to enable the toxin to enter the cells. The PTXA ADP-ribosylates the α subunits of heterotrimeric Gi/o proteins, preventing the Gαi/o proteins from inhibiting adenylyl cyclase (AC). One of the ways that PTX causes the many pathogenic consequences in host cells is by the alteration of the Gi/o proteins, which leads to an increased buildup of cAMP. An intracellular signal transduction cascade is activated when the B-subunit interacts with the Toll-like receptor 415. By binding to miRNAs in a competitive manner, circRNAs and lncRNAs can control the expression of genes. More and more research points the roles for circRNA-miRNA-mRNA axis or lncRNA-miRNA-mRNA axis in the development of disorder72. For example, by increasing the expression of miR-146b and its effect on the Siah2 gene, NF-KB pathway becomes more active and causes an increase in the intestine inflammation73. The increase of miR-126 also has the same effect by affecting the IκBα gene19. CircRNA_103516 in PBMCs is reported as an excellent potential biomarker for the diagnosis of IBD. Through hsa-miR-19b-1-5p sponging, dysregulation of circRNA_103516 may contribute to the molecular basis of IBD74. The discovery of lncRNA IFNG-AS1 as a new regulator of IFNG inflammatory responses and the deregulation of lncRNA signatures in UC suggest the potential significance of noncoding RNA pathways in the control of inflammatory bowel disease75.Non-coding RNAs, including miRNAs, circRNAs, and lncRNAs, have been shown to play intricate roles in the development of IBDIn this study, five important human genes  reported in the development and spread of pertussis and staphylococcus aureus infections. Using the miRWalk database, we created an interaction network between some genes  and common miRNAs. In addition, the results showed that NM_001039703 regions with miR-186-5p, miR-4436a, and miR-520a-5p and also NM_006267 regions with miR-186-5p, miR-6763-5p, and miR-520a-5p are hotspots that produce circular RNAs on the function of human genes effective in causing staphylococcus aureus and pertussis bacterial infections. Future experimental studies can clarify the effects of these circRNAs on the regulation of the function of these miRNAs and genes.70. The expression of proinflammatory cytokines generated by E. coli or S. aureus was considerably boosted by XIST silencing. Additionally, NF-κB phosphorylation caused by E. coli or S. aureus and the formation of NLRP3 inflammasome were suppressed by XIST. However, there were some controversies on XIST function but these findings implied that XIST inhibits NF-κB pathway activation triggered by E. coli or S. aureus76. Another study suggested that the stimulatory action of XIST was related to NF-κB. In conclusion, OSAHS (obstructive sleep apnea/hypopnea syndrome) patients had inflammation in their adenoids that was mediated by the XIST-GRα-NF-κB signaling pathway77.The ceRNA network including miRNA-lncRNA-mRNA showed that lncRNA XIST and NEAT1 have the most important role among other lncRNAs in the network by affecting five common miRNAs related to human genes involved in staphylococcus aureus infection and pertussis. Some studies investigated the effects of lncRNA XIST on immune response. Through modifying the expression of ASF1A and BRWD1, lncRNA XIST can act as a ceRNA to sponge hsa-miR-212-3p to control inflammation and apoptosis in the development of AKI (acute kidney injury)15. NEAT1 was highly expressed in IBD and played a role in the inflammatory response by controlling the intestinal epithelial permeability and polar macrophages via exosomes78. According to some researches, TNFRSF1B may contribute to colitis by promoting inflammation. It was discovered that NEAT1 plays a pro-inflammatory effect via controlling TNFRSF1B (tumor necrosis factor superfamily member 1B), and facilitates NF-κB p65 entrance into the nucleus79. Studies suggested that the Neat1-miRNA204-5p axis plays an important role in the regulation of the PI3K-AKT pathway, which plays an important role in activating the pathways that lead to more activity of the immune system80. Studies have shown that the increase of NEAT1 has been observed in various cancers, liver diseases, non-alcoholic fatty liver disease (NAFLD), and liver fibrosis81. Although most studies show an increase in NEAT in IBD, more experimental tests are needed to determine the exact role of lncRNA NEAT1. Other predicted lncRNAs  can also be good subjects for further experimental tests to determine their exact role in bacterial infection and inflammation.The lncRNA NEAT1 is associated to the innate immune response. It seems that this lncRNA has a function in triggering the immune response by activating the kappa pathway82. It was shown that rectal administration of siRNA targeting TNF-a resulted in relative mucosal resistance to experimental colitis using a mouse model of inflammatory bowel disease83. Nanoparticles with surface CD98 antibody and CD98 siRNA (siCD98) loaded on them suppressed the production of this protein in colonic epithelial cells and macrophages84.Considering that inhibiting bacterial genes in staphylococcus aureus and pertussis bacterial infections can prevent the infection process. siRNAs as silencing of these genes may be considered effective to deal with staphylococcus aureus and pertussis infections, there were able to identify the most stable and sensitive spots for the action of siRNAs. The siRNA was functional in lowering the bacterial burden in a mouse model of hematogenous lung infection, according to the in vivo results. The use of siRNA to target coagulase looked to be a novel method of treating MRSA (Methicillin-resistant Staphylococcus aureus) infectionsIn conclusion, the gene hubs obtained from cross talking of human and bacterial pathways were the subjects to find the ncRNA profiles. These regulatory sets can simultaneously affect the human and bacterial gene groups and may be effective therapeutic agents in IBD. Considering that human KRT10, FGG, and TLR4 genes play an important role in the infection by these bacteria, based on the ceRNA networks, lncRNA XIST and NEAT1 suggested to play an important role in regulating the function of hsa-miR-6875-5p, hsa-miR-1908-5p, hsa-miR-186-5p, hsa-miR-6763-5p, hsa-miR-4436a, and hsa-miR-520a-5p, which may regulate the activity of genes involved in the occurrence of staphylococcus aureus and pertussis bacterial infections. The production of circRNAs in NM_001039703 and NM_006267 positions affect miR-186-5p, miR-4436a, miR-520a-5p, miR-186-5p, miR-6763-5p, and miR-520a-5p that act on the functions of KRT10, FGG, and TLR4 genes. The more experimental studies can determine the precise roles of these ncRNAs and genes in the process of causing inflammatory bowel disease. We also predicted the most effective cores for siRNAs to affect staphylococcus aureus  and pertussis  bacterial genes that interacted with human KRT10, FGG, and TLR4 genes. These genes are also known in other bacteria. However, the aforesaid putative genes and ncRNAs in IBD should therefore be confirmed by additional research and experiments with larger datasets.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.Supplementary Information 6.Supplementary Information 7.Supplementary Information 8.