Exposure to indoor particulate matter (PM) is a potential risk factor that increases systemic inflammation and affects erythropoiesis. This study investigated the association between exposure to indoor PM and blood indicators related to anemia (BIRA) in housewives. Indoor PM and blood folate status are important factors in the risk of anemia. This was a housewife cohort study; we recruited 284 housewives in Seoul and Ulsan, Republic of Korea. Indoor exposure to PM2.5 and PM10 was measured by gravimetric analysis and sensors. We investigated the BIRA, such as hemoglobin (Hb), hematocrit, mean corpuscular volume (MCV), mean corpuscular Hb (MCH), and mean corpuscular Hb concentration (MCHC). Statistical analysis was performed by multiple linear regression model and mediation analysis. The association between BIRA and PM was assessed by multiple linear regression models fitted by mediation analyses. The increase in the level of indoor PM2.5 was associated with a decrease in MCV (Beta coefficient (B): −0.069, Standard error (SE): 0.022) and MCH  in gravimetric measurements. The increase in the level of indoor PM2.5 was associated with a decrease in Hb , hematocrit , and MCV  and MCH  in sensor measurements (PM2.5-Lag10). Further, we identified a serum folate-mediated PM effect. The indoor PM exposure was significantly associated with decreased Hb, MCV, and MCH in housewives. Taken together, our data show that exposure to indoor PM is a risk factor for anemia in housewives. Blood folate concentration can be a mediating factor in the effect of indoor PM on BIRA. Therefore, folate intake should be recommended to prevent anemia in housewives. Moreover, indoor PM exposure should be managed. Housewives with children spend relatively more time at home when compared with working women. As a result, they are exposed to a greater amount of indoor particulate matter (PM) through housework such as cooking, cleaning, laundry, and childcare. Many women and children are exposed to high levels of indoor toxic air pollutants when using fuel for cooking and heating at home . PM exhiBlood indicators related to anemia (BIRA) include hemoglobin (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular Hb (MCH), and mean corpuscular Hb concentration (MCHC). Hb refers to its concentration in the blood. Hct refers to the percentage of the volume in contact with red blood cells (RBCs) in whole blood . The WHOExposure to air pollution can increase oxidative stress, a possible contributing factor to anemia ,6. OxidaProlonged exposure to PM can increase the risk of cardiovascular, respiratory, and endocrine diseases and systemic inflammation . AdditioSeveral studies have measured the association between Hb and indoor air pollution, few have investigated the relationship between PM and anemia. More research is needed on this topic because of its increasing public health importance. Therefore, this study focused on the short- and long-term effects of exposure to PM in housewives, using BIRA. We established a “Housewife Cohort” to examine the association between exposure to PM and the health of housewives. We hypothesized that increased exposure to indoor pollution would adversely affect the BIRA of women and cause anemia. We recruited mothers from an ongoing cohort study, the Korean Children’s Environmental Health Study (Ko-CHENS). The specific cohort profile has been previously described . A PM suIn this study, 284 participants were recruited from the 319 housewives of Ko-CHENS, aged between 20 and 50 years during the observation period of 2018–2020 .n = 100)  . SmokingA clinical nurse collected the blood from most participants at hospital; once for the short-term study and twice for the long-term study. Participants were in a fasting state, and blood (25 mL) and urine (15 and 50 mL) were collection. Whole blood and serum and urine were collected in EDTA tubes and stored at 4 °C. White blood cells (WBCs), RBCs, Hb, Hct, MCV, MCH, MCHC, and platelets were analyzed by flow cytometry using the analysis equipment, ADVIA2120i . Folic acid and ferritin, major variables associated with anemia, were tested using the CIA analysis method with ADVIA Centaur XP  analysis equipment. Trans,trans-Muconic acid  was assessed in the urine samples using high performance liquid chromatography-triple tandem mass spectrometry (HPLC-MS/MS). To maintain standardization, all samples were analyzed through SCL, a certified company .Direct measurements of indoor PM exposure were conducted through using the gravimetric analysis, sensors, light scattering method, and outdoor monitoring. In addition, PM concentration was repeatedly measured based on the period and life activities of the housewife. Gravimetric analysis was performed twice a year during the study period, and the sensor method was used continuously. Outdoor monitoring data were collected from the Korea Meteorological Administration. PM concentrations were compared and the exposure factors were identified. The effect of exposure to PM on the health was confirmed by using questionnaires and analysis of blood/urine samples. The addresses of all the participants were collected while determining the outdoor PM values, which were then compared with those published by the Air Korea Monitoring Network. Exposure values were corrected according to the exposure formula, as described previously ,16.Gravimetric analysis was performed during continuous PM exposure over one 24 period. Briefly, PM was collected on filter paper, which was first weighed at 20 °C and 50% relative humidity before exposure. First, we checked for any contamination in the separator and the normal operation of the collector. Next, the PM sample was collected on the filter paper by fixing it to the holder so that air did not leak (flow rate = 5 L/min). As per indoor air quality process test standards, we selected a place > 1 m away from the inner wall, ceiling, and floor surface (a relatively large living room in the house) and used a 1.0–1.5 m tall tripod to install the PM equipment (PM10 and PM2.5). If the house was not spacious or well-organized, PM was measured by installing the equipment at an appropriate position as deemed fit by the measurer. This is currently considered one of the most reliable methods for measuring PM concentration. After collecting the sample for 24 h, the filter paper was weighed and the concentration of PM in the indoor air was measured by determining the difference in the weight of the filter paper before and after collection. t is the time spent in the microenvironment (h) and c is the concentration of air pollutants in the microenvironment.We used a light scattering sensor and the Internet of Things (IoT) to convert real-time measured values and concentration values into a DB for 1 year per ID (study participants) continuously to determine the extent to which housewives were exposed to PM . Additionally, we used the Community Multiscale Air Quality (CMAQ) model, a computational tool for measuring air quality data, to reproduce the seasonal PM concentration field (1-km grid resolution) for 1 year. The outdoor PM concentration was corrected using the CMAQ, and the concentration estimate of the unmeasured point was improved by considering the average outdoor concentration reproduced in the model. The outdoor sensor values were evaluated for integrated PM exposure via time-weighted average concentrations based on the CMAQ values. The latter was calculated using the average occupancy period and average exposure concentration based on region and distribution (Equation (1)),p < 0.05. All analyses were performed using SAS  and R .The housewife cohort construction data were extracted through multilinear regression and mediation analyses. We used the correlation between indoor and outdoor PM exposure and anemia  by utilizing the PM weight method and sensor measurement data. First, weight measurements were correlated through multiple linear regression analyses. Data were adjusted for BMI, ferritin, and t,t-MA, smoking, alcohol experience. BMI is an index related to lifestyle, it can be a confounding factor between X: indoor PM and Y: BIRA(blood index related to anemia). Ferritin is also a confounding factor of PM and anemia. T,t,MA  is an indicator of VOC metabolites. Second, long-term sensor measurement values were analyzed using multiple linear regression analyses based on the 1-year exposure values and health effects. Data were adjusted for BMI, ferritin, smoking, and alcohol experience. Third, a mediation analysis was performed according to short-term and long-term PM exposure, blood folate concentration, and BIRA without adjusted confounding variables. The effect of folate was confirmed through a mediated analysis on the correlation between exposure to PM and BIRA. Data were considered significant if The characteristics of the study participants are listed in 2.5 and PM10 concentrations.The association between gravimetric PM2.5 and PM10 and BIRA is presented in 2.5 sensor exposure values and the BIRA. The results of long-term exposure on the BIRA are listed in A significant correlation was observed by mediation analysis between gravimetric PM10 and blood folate, MCH, and MCHC in Acute exposure to PM generally induces alterations to DNA methylation based on inflammation and oxidative stress. Once inhaled, PM causes inflammation by creating oxidative stress in the lungs and triggering the production of main species of ROS , adversely affecting red blood cells and causing anemia ,6,10. InMost studies have actively investigated PM on iron deficiency and another anemia ,8,19. Seare associated with cardiovascular disease [Exposure to PM can increase the concentration of systemic inflammatory markers, which  disease ,22. An i disease ,10,23. P disease ,24. The  disease ,25.Previous studies have indicated an association between low-folate status and anemia . AlthougOxidative stress is a common denominator in the pathogenesis of many chronic diseases; therefore, antioxidants are frequently used to protect cells and reverse oxidative damage. Antioxidants mediate hematopoietic homeostasis and oxidative stress, which supports our findings ,29. FoliThis suggests that the folate pathway is an essential part of the versatile cellular mechanism that responds to oxidative stress, and plays a crucial role in fundamental cellular processes . FurtherFew studies have investigated the effect of indoor air pollution on anemia, although the investigation of chronic effects on blood health is increasing ,32,33. COur study shows strong short- and long-term effects to exposure to PM, similar to those reported by studies on the effects of smoking. It is difficult to investigate the relationship between indoor air pollution and health effects because of the difficulties in isolating the temporal and spatial fluctuations of exposure, different chemical compositions of indoor air pollution, study groups of different ages, and other environmental and individual risk factors. Our study obtained the same results by simultaneously executing a short-term indoor study and a long-term study under several constraints. Hence, our study shows reliable results. In addition, the mediation analysis was performed to provide evidence for the mediating effect of blood folic acid ,37,38.This study diversified the design for both short- and long-term studies on exposure to indoor and outdoor PM in housewives according to the measurement period. We evaluated their health effects through mediation analysis. The results of indoor and outdoor PM exposure data were compared and presented using various measurement methods. We evaluated the health effects of indoor PM on housewives by correcting for actual exposure; we constructed individual exposure values that considered both indoor and outdoor exposure, rather than by using simple measurement values. The sample size was very small and statistical power was limited. This was due to difficulties in recruiting participants, and accurately measuring exposure and outcome variables. The exposure data estimated by the modeling method had a relatively high percentage of missing data because of limitations in the IoT sensors. Development of precision PM sensor technology and the continuity of communication connections remain important challenges. In addition, the data were related to Korean housewives alone; therefore, the results of this study cannot be generalized .This study focused on the short- and long-term effects of exposure to PM and BIRA in housewives. We believe that this study will help to advance the development of individual exposure-assessment techniques for PM. Identifying the mechanism underlying the risk of short- and long-term exposure to PM will enable further research and help to build a risk assessment system. Additionally, this study will expand the development of the PM exposure measurements and information platforms. Moreover, it has provided scientific information on the health effects of indoor PM on housewives, which will relieve public anxiety regarding this problem.This study can serve as a baseline to investigate the effect of interventions on public health because it offers a detailed scientific analysis of PM exposure for women with indoor lifestyles. The health of housewives is closely related to the health of infants and children; therefore, this study is also useful for the overall health management of households. The expansion of our study can support public health management policies and prepare countermeasures to reduce the exposure to PM in different daily life environments. Finally, it can help to construct actual PM exposure assessment data based on domestic living patterns and indoor pollution.


Leptospira. Regional differences in the disease manifestation and the role of ecological factors, specifically in regions with a subarctic and arctic climate, remain poorly understood. We here explored environmental and socio-economic features associated with leptospirosis cases in livestock animals in the Russian Arctic during 2000–2019. Spatial analysis suggested that the locations of the majority of 808 cases were in “boreal” or “polar” climate regions, with “cropland,” “forest,” “shrubland,” or “settlements” land-cover type, with a predominance of “Polar Moist Cropland on Plain” ecosystem. The cases demonstrated seasonality, with peaks in March, June, and August, corresponding to the livestock pasturing practices. We applied the Forest-based Classification and Regression algorithm to explore the relationships between the cumulative leptospirosis incidence per unit area by municipal districts (G-rate) and a number of socio-economic, landscape, and climatic factors. The model demonstrated satisfactory performance in explaining the observed disease distribution , with human population density, livestock units density, the proportion of crop area, and budgetary investments into agriculture per unit area being the most influential socio-economic variables. Climatic factors demonstrated a significantly weaker influence, with nearly similar contributions of mean yearly precipitation and air temperature and number of days with above-zero temperatures. Using a projected climate by 2100 according to the RCP8.5 scenario, we predict a climate-related rise of expected disease incidence across most of the study area, with an up to 4.4-fold increase in the G-rate. These results demonstrated the predominant influence of the population and agricultural production factors on the observed increase in leptospirosis cases in livestock animals in the Russian Arctic. These findings may contribute to improvement in the regional system of anti-leptospirosis measures and may be used for further studies of livestock leptospirosis epidemiology at a finer scale.Leptospirosis is a re-emerging zoonotic infectious disease caused by pathogenic bacteria of the genus  Animal leptospirosis is a re-emerging focal infectious disease (zoonosis) that is common in humans and animals globally –5. Over Leptospira in the external environment . Due to the high heterogeneity of population density, we excluded those areas with a population density exceeding the mean plus three standard deviations  from further analysis. Such areas are represented by small but densely populated urban territories with a scarcity of agricultural livestock. Additionally, all the other districts with no livestock population were excluded. Thus, the total number of territorial units suitable for the analysis was 166. The majority of the study area lies north of 60°N; however, some of the Krasnoyarsk Krai districts extend southward, up to 52°N . The zone under consideration includes nine regions whose territories are crossed by the Arctic Circle: Arkhangelsk Oblast, Murmansk Oblast, Republic of Karelia, Republic of Komi, Yamalo-Nenets Autonomous Okrug, Nenets Autonomous Okrug, Krasnoyarsk Krai, Republic of Sakha (Yakutia), and Chukotka Autonomous Okrug. These regions are subdivided into 199 districts with areas varying from 4 to 798,000 km to 52°N .http://docs.cntd.ru/document/gost-25386-91), laboratory confirmation was performed using the microscopic agglutination test (MAT) method with a set of 7 reference cultures: Pomona, Tarassovi, Canicola, Hebdomadis, Sejroe, Grippotyphosa, and Icterohaemorrhagiae with preliminary testing on a reference culture previously identified as typical for the specific region. The reaction was evaluated with a positive cut-off using a serum dilution of 1:50 for unvaccinated animals and 1:100 for vaccinated animals with dark-field microscopy. For previously vaccinated animals, testing was conducted at least 3 months following the vaccination. In the case of a positive MAT result with no clinical signs, confirmatory testing using real-time polymerase chain reaction was conducted . Cases were detected both by herd owners and during routine government monitoring. Under the state standard GOST 25386-91 , calculated according to the European Union methodology [https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Livestock_unit_(LSU)]Pop_dens—population density, people per km2Rural_prop—the proportion of the rural populationCrop_prop—the proportion of crop area in the total area of the region, as a factor presumably associated with the number of synanthropic rodents that are carriers of pathogenic LeptospiraInv_area) and per capita (Inv_pop).The volume of budgetary investments into the development of agriculture as a proxy for the level of financing of agriculture; relative indicators were considered: per unit area of the district  was used as a data source for socio-economic indicators. The altitude was calculated based on the GTOPO30 digital elevation model with a spatial resolution of 30” (https://earthexplorer.usgs.gov/). The soil pH data at zero depth were taken from the ISRIC World Soil Information digital database with a spatial resolution of 250 m . The quality of the regression model was assessed using the coefficient of determination (R2), which shows the proportion of data variation explained by the model. The R2 was reported for: (The cumulative number of leptospirosis cases for the entire observation period per unit area by the districts (G-rate) was chosen as a measure for the intensity of the leptospirosis epidemic within the study area –49. The ination R, which sted for:  the overted for: , 54.p-value, confirm the null hypothesis of a random spatial distribution of the residuals. Furthermore, the model was used to predict the values in the rest of the study area, both using the parameters of the current climate and the projected climate. To provide accuracy of predictions, only those districts of the study area with the values of the primary explanatory factors within the range defined by the training districts (N = 151) were used. To visualize the expected change in the G-rate under a future climate, a map was created, which showed the ratio of its predicted to its current value for the training and predictive regression model.The absence of spatial clustering of regression residuals was verified using Global Moran's I index. The values of this index, which are near zero at a high To determine the seasonality of leptospirosis emergence, the seasonality index S was used and was calculated as the number of cases for a given month averaged over several years divided by the average annual number of cases for the corresponding year , 56. AddThe statistical analysis of data was carried out using MS Office Excel  with the @Risk v 4.5 simulation analysis package . The Forest-based Classification and Regression analysis as well as other spatial data processing and visualization were performed using the geographic information systems ArcGIS Pro 2.6.1 and ArcMap 10.8.1 .Between 2000 and 2019, 808 cases of leptospirosis in livestock were recorded in the subarctic and Arctic regions of Russia. Based on the distribution of the detected cases by year , there aThe calculation of the seasonality index revealed the prevalence of the relative number of cases in March as S = 1.53 (95% CI: 0–4.00), in June as S = 2.27 (0–5.76), and in August as S = 1.73 (0–9.6).An analysis of location of the leptospirosis cases, considering a 2.5-km buffer zone reflecting the possible uncertainty in geolocation, showed that all cases occurred in the polar or boreal climatic regions, with a predominance of croplands, forests, shrublands, and settlements as land-cover types. Most of the cases occurred in the “Polar Moist Cropland on Plains” ecological zone . Thus, eR2 = 0.94 ± 0.03; p-value ≤ 0.001) and an acceptable fit to the validation data . The relative importance of the variables based on the simulation results is shown in p-value = 0.820). Comparison of the predicted and observed log G-rate demonstrates a satisfactory model fit to the training data with R2 = 0.82, p-value < 0.05  showed a high model fit to the training data  that makes it difficult to implement space-time regression models. Hence, in our study we considered the aggregated number of cases per unit area throughout the whole study period, which provides response variable values more suitable for modeling.The Forest-based Classification and Regression method is a popular machine learning method used in classification and forecasting. This tool allows analysts to easily incorporate tabular attributes, features, and explanatory rasters when building predictive models, and expands predictive modeling capabilities to be accessible to all geographic information system (GIS) users. Our research demonstrated the effectiveness of the spatial Forest-based Classification and Regression algorithm for analyzing results under various climate change scenarios. The integration of the Forest-based Classification and Regression tool as a spatial algorithm for exploring these factors makes it easier to consider different scenarios than using traditional regression methods due to reduced demands on the input data distribution and format.Nevertheless, the study had some limitations in terms of the method used. First, there were a limited number of spatial units available for analysis. As a data-driven method, the Forest-based Classification and Regression tool performs better with large datasets [at least several hundred input analysis units according to the method guidance provided by the software producer , while iIt should also be noted that our forecast is based only on the expected changes in climate in the future, which according to our model has a significantly smaller effect on the concentration of leptospirosis cases than the socio-economic determinants. Thus, a change in the structure of animal farming, expansion of cultivated areas, financial support for agriculture, and the occupation of new territories could collectively have a much stronger impact on the leptospirosis incidence outweighing the influence of climatic factors.Our study provided empirical evidence that the factors involved in transmission of leptospirosis in the Arctic and subarctic regions of Russia are complex and include environmental and socio-demographic indicators. The assessment of the significance of the main factors (socio-economic and climatic) when using the Forest-based Classification and Regression method indicated that the main contribution to the increased incidence of leptospirosis is from socio-economic conditions related to the population agricultural activity. Indicators of precipitation and temperature regime were the predominant contributors among the climatic factors.The information obtained in this study on the risk factors for livestock leptospirosis outbreaks supports the One Health approach to animal disease prevention and control, which takes into account anthropogenic factors, animal density distribution factors, and the environment. Future research should be specifically designed to assess the impact of interventions under different scenarios.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.OZ, AB, and FK: conceptualization. FK and OZ: methodology, software, writing—original draft preparation, and visualization. AB and FK: validation. FK, OZ, and GS: formal analysis. OZ and NT: investigation. NT, SM, and GS: resources. FK and AG: data curation. FK, AB, OZ, and SM: writing—review and editing. AB, II, and AG: supervision. AB, FK, and DK: project administration. All authors have read and agree to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


A group of 276 Italian students from primary and middle school (aged 8–15) completed self-reports assessing moral disengagement, socio-conventional perception of moral rules, and participation in bullying as bully, defender of the victim and passive bystander. Results from structural equation modeling analysis confirmed that moral disengagement and socio-conventional comprehension of aggressions are separate and moderately connected morality dimensions. Controlling for age, gender and SES, only moral disengagement was positively associated with perpetrating bullying. These results point to moral disengagement as the critical component of moral cognitions to be addressed in interventions.The present study investigated the extent to which moral disengagement and the tendency to consider moral rules as socio-conventional rules are distinct dimensions of morality, and their association with three different forms of participation in bullying . These two types of moral cognitions have been theorized in different models of morality and are usually studied independently, even if research on  The motivation of activating moral disengagement comes from the need to solve the cognitive dissonance , as the feelings . Then, wir peers . With reir peers , and lowir peers . In someir peers , but their peers .moral , socio-conventional , and personal   . An impo states) .a priori, leading the action.The moral domain is constructed and developed through experiences of actions that have negative or positive effects on the welfare of others or oneself. The socio-conventional domain, instead, refers to actions regulated by rules thought to depend on authorities’ statement (context authority’s dependence) and not on superior moral values, they are considered non-universally valid and their transgressions are evaluated less serious than breaking moral rules. The organization of moral knowledge in latent domain structures, informing and influencing the social information processing, has been hypothesized to be shaped by the repeated social interactions . After eunderstanding of bullying as breaking of a socio-conventional rule in relation to passive bystanding, even if this behavior was associated with higher recognition of bullying as harming the victim and empathizing with the victim  domains appeared when the adolescents evaluated hypothetical situations about delinquent behavior. That is, they attributed the delinquent behaviors that they perpetrated, but not other delinquent behaviors, to non-moral rule domains. This domain shift, only emerging in relation to one’s own transgressions, may serve a similar function as moral disengagement, by legitimizing one’s own transgressive behaviors, reducing the cognitive dissonance and preserving the self-esteem. This theorization about domain shifts suggests a possible relation, if not partial overlap, between the organization of moral knowledge in domains and the moral disengagement mechanisms. Nevertheless, the scarcity of research on the association between the two constructs does not allow to establish to what degree they are inter-related and their relative weights in explaining social behaviors.In general, very few studies have investigated moral disengagement and social domains in the same framework in relation to youth’s behavior in bullying . Both thIn this study we investigated the intertwin of moral disengagement and the perception of aggressions as socio-conventional rule transgressions in association with perpetrating bullying, defending the victim and passive bystander behavior in bullying, focusing on late-childhood and early adolescence as critical age levels , 2012.a priori (before the action) organization of the socio-moral knowledge, while moral disengagement should be a more dynamic process, at the beginning working a posteriori, after the perpetration of the action. Nevertheless, as both these constructs should emerge from social interactions , attending one primary school  and one middle school  in Northern Italy. Participants’ majority (85.9%) had an Italian background. To assess the socioeconomic/cultural status (SES) participants reported their parents’ jobs and qualifications: 32.9% had families of low-average SES. 32.2% of average SES and 31.8% of average-high SES; 3.1% were not able to provide this information.Participants were 276 fourth to eight-graders  = 8.422 p = 0.751, CFI = 1.000, RMSEA = 0.000 (90% CI.000.044), moral disengagement factor Chronbach’s alpha = 0.78.We administered a self-report questionnaire specifically devised to assess moral disengagement in bullying situations . The mea2(15) = 22.956 p = 0.085, CFI = 0.995, RMSEA = 0.044 (90% CI.000.078), socio-conventionality factor Chronbach’s alpha 0.96.A measure adapted by the scale developed by We assessed forms of participation in bullying as perpetrator, defender, and passive bystander by administering a peer report measure adapted from School principals and teachers’ committees authorized the participation of some classrooms in grades four and five (last two grades of primary school), and six to eight (middle school). Participants’ parents/legal guardians authorized students’ participation in the study by providing active consent in response to a letter describing the study and its aims. The 72.3% of families authorized their children participation. Measures were group-administered in classroom situations, during the regular school hours, by a researcher assistant who discussed with the participants the definition of bullying and answered their questions. Participants were informed that they could withdraw from the study at any time without providing any explanation.We used Structural Equation Modeling , SES and age were included among predictors to control for their effects.As third step, we tested a SEM model in which the three forms of behaviors in bullying were regressed on the final latent structure of morality emerging from step two. Gender (2), which needs to be non-significant for good fitting models, but which is also sensitive to the sample size and tends to become significant for large samples; the CFI index, with a value ≥0.90 for acceptable fit  and expecting a value of RMSEA equal to 0.08, a sample of 200 participants was enough to provide a power of 1.00  = 33.937 p = 0.670, CFI = 1.000, TLI = 1.000, RMSEA = 0.000 (90% CI.000.033), 5 factor model χ2 Difference test (11) = 88.975 p = 0.000. One factor (the fourth extracted factor), was loaded only by the seven parcel scores of moral disengagement. The remaining five factors expressed the dimensionality of the measure assessing the socio-conventionality of aggressions. The first extracted factor expressed the authority dependence and was positively loaded by the six indicators of teacher and principal dependency. The three scores of context dependency characterized the second extracted factor. The third extracted factor was loaded positively by teacher dependency of verbal aggression and negatively by the principal dependency of the physical aggression, thus mainly expressing the different perception of seriousness of these two forms of aggression. The fifth extracted factor was mainly loaded by the teacher dependency (0.661) and the principal dependency (0.295) of relational aggression, thus expressing the specificity of this form of aggression. The sixth extracted factor was mainly characterized by principal dependency of verbal (0.247) and relational violence (0.221), expressing some residual variance explained by this type of authority. The moral disengagement factor correlated moderately and significantly with first , second , and fifth extracted factors  and non-significantly with third factor (0.014). On summary, EFAs provided a first indication that moral disengagement and conventionality of aggression are distinct morality dimensions.The EFAs indicated a six factor model as the best model of parcel scores : χ2(39) 2(90) = 263.730 p = 0.000, CFI = 0.934, RMSEA = 0.084 (90% CI.072.095). The two-factor model fitted the data adequately, with significantly lower Chi-square than the one-factor model: χ2(89) = 136.920 p = 0.000, CFI = 0.982, RMSEA = 0.044 (90% CI.029.058), χ2 Difference test with Satorra–Benter correction (1) = 94.307 p = 0.000. Then the two-factor model was retained as the final morality model  = 282.201 p = 0.000, CFI = 0.965, RMSEA = 0.048 (90% CI.037.058). Bullying was higher for boys and defending for girls. Older youths showed higher defending. Moral disengagement was positively associated with bullying perpetration and marginally (p = 0.067) negatively with defending. The socio-conventional perception of aggressions was not associated with any of the three behaviors.The model  in whichGoal of this study was to investigate whether and to what extent moral disengagement and the socio-conventional perception of aggressions  are possibly related dimensions of morality, and their associations with participation in bullying as bullying perpetrator, defender of the victim, and passive bystander. Our findings confirmed that moral disengagement mechanisms and the socio-conventional perception of aggressions are distinct dimensions of morality, only moderately associated. Only moral disengagement was associated with higher perpetration of bullying and  with lower defending.a priori, before the perpetration of the action, while moral disengagement is a mechanism working  a posteriori, after the transgression perpetration, to avoid negative emotions. This difference between the two dimensions can be particularly evident in the case of bullying. Students who bully others are aware of the importance of other’s well-being and they know that bullying is wrong , in that the distinction may be blurred in people’s mind, or can vary significantly depending on the person  may detect some associations between the two moral dimensions we investigated and passive bystanding.Passive bystanding was associated with neither moral disengagement nor social domain knowledge. Also for this behavior other factors may be more relevant. a priori and a posteriori functioning of these constructs, but we need more studies investigating the possible intersections of different dimensions of morality, also in relation to moral emotions.The main limitation of this study consists in the cross-sectional nature of the data that does not allow to draw strong conclusions on the direction of the associations. Notwithstanding, to our knowledge this is the first study investigating the possible relation between the organization of moral knowledge in domains and moral disengagement mechanisms, also in connection with three participant behaviors in bullying. In this perspective, our results contribute to the literature on morality clarifying that the two moral dimensions are actually distinct constructs, only moderately associated, and with different relations with youth’s behaviors in bullying. We interpreted this distinction mainly with the Lastly, our results can contribute to the literature on anti-bullying interventions, as we confirmed that moral disengagement is a moral cognitive dimension affecting the perpetration of bullying more than others. Therefore, we need more anti-bullying interventions addressing this aspect.Due to limitations from the Privacy Law restrictions and the participants’ ethical consents, the raw data cannot be made accessible out of the research team. Aggregated analyses results, however, can be requested from the corresponding author.SC made substantial contributions to the conception of the work, the acquisition, analysis, and interpretation of data for the work, drafting the work, and revising it critically for important intellectual content, provided approval for publication of the content, and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved. JF made substantial contributions to the conception of the work, interpretation of data for the work, drafting the work and revising it critically for important intellectual content, provided approval for publication of the content, and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved. HF made substantial contributions to the conception of the work, drafting the work, and revising it critically for important intellectual content, provided approval for publication of the content, and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Objective: Cataract, which is the clouding of the crystalline lens, is the most prevalent eye disease accounting for 51% of all eye diseases in the U.S. Cataract is a progressive disease, and its early detection is critical for preventing blindness. In this paper, an efficient approach to identify cataract disease by adopting luminance features using a smartphone is proposed. Methods: Initially, eye images captured by a smartphone were cropped to extract the lens, and the images were preprocessed to remove irrelevant background and noise by utilizing median filter and watershed transformation. Then, a novel luminance transformation from pixel brightness algorithm was introduced to extract lens image features. The luminance and texture features of different types of cataract disease images could be obtained accurately in this stage. Finally, by adopting support vector machines (SVM) as the classification method, cataract eyes were identified. Results: From all the images that we fed into our system, our method could diagnose diseased eyes with 96.6% accuracy, 93.4% specificity, and 93.75% sensitivity. Conclusion: The proposed method provides an affordable, rapid, easy-to-use, and versatile method for detecting cataracts by using smartphones without the use of bulky and expensive imaging devices. This methodcan be used for bedside telemedicine applications or in remote areas that have medical shortages. Previous smartphone-based cataract detection methods include texture feature analysis with 95 % accuracy, Gray Level Co-occurrence Matrix (GLCM) method with 89% accuracy, red reflex measurement method, and RGB color feature extraction method using cascade classifier with 90% accuracy. The accuracy of cataract detection in these studies is subject to changes in smartphone models and/or environmental conditions. However, our novel luminance-based method copes with different smartphone camera sensors and chroma variations, while operating independently from sensors’ color characteristics and changes in distances and camera angle. Clinical and Translational Impact—This study is an early/pre-clinical research proposing a novel luminance-based method of detecting cataract using smartphones for remote/at-home monitoring and telemedicine application. I.Cataract is mymargin an eye disease that causes permanent blindness when not treated in time. According to the National Eye Institute, 24.4 million Americans have cataracts, and it is estimated that the number of people affected by cataracts will increase to 38.7 million by 2030 Cataract types are defined by the location where the opacities exist within the lens and are graded by how severe the opacities are at that location. Depending on the location of the opacities, as shown in Image processing and machine learning algorithms have been developed to detect eye diseases by analyzing eye image features et al. have used a combination of statistical texture features and adopted the K-Nearest Neighbor (k-NN) algorithm as a classifier to detect cataracts on an Android-based smartphone et al. have utilized an external microscope on an Android-based smartphone to detect cataracts from Red, Green, Blue (RGB) images captured from the subject’s retina. The reported accuracy of their method was 89% et al. proposed a self-screening application for detecting cataracts based on red reflex measurements et al. adopted a cascade classifier to detect the pupil and extract RGB feature values Fuadah Since these studies are highly dependent on smartphone camera sensor characteristics as well as ambient light, distance, and environmental conditions, the accuracy of detecting cataracts in these studies is subject to changes in smartphone models and/or environmental conditions.To overcome these disadvantages of color-based methods used in the mentioned studies, we propose an alternative luminance-based method for cataract disease diagnosis. Luminance-based models have been used in different studies to detect diseases such as cancer and have been compared with color-based detection methods in different color spaces In The results of these studies indicate that switching from color-based method to luminance-based method improves the detection accuracy and feature extraction. Moreover, color-based detection systems are more dependent on the camera sensors’ characteristics and environmental conditions compared to luminance-based detection methods.In this paper, we propose a novel and robust luminance-based eye image analysis technique. Specifically, we detect cataracts by using pixel brightness transformation to extract luminance values of images acquired with a smartphone camera. To validate the method, we used different iPhone models  to capture images in different light, distance, and angle conditions using an eye model The novel luminance-based method copes with different smartphone camera sensors and chroma variations, and it is independent of sensors’ color characteristics and changes in environmental factors. For classification, the Support Vector Machine (SVM) classifier was utilized to distinguish diseased eyes from healthy eyes. To overcome the data sample limitation, a 10-fold cross validation resampling procedure was implemented to evaluate the machine learning model. As a result, the proposed method detects cataracts from images captured by the smartphone camera. The proposed method only differentiates healthy eyes from diseased eyes, and it does not differentiate between types of cataracts.The rest of this paper is organized as follows: II.Images captured by the smartphone camera are utilized to monitor the conditions of the eye for healthy or cataract cases. Our proposed method to diagnose cataracts consists of four main steps: 1) data acquisition, 2) preprocessing, 3) feature extraction, and 4) classification. A.In this paper, we used an Axis Scientific 7-Part Human Eye  ambient lighting, 2) distance between the smartphone camera and eye model, 3) camera angle relative to eye model, and 4) smartphone camera characteristics. Demonstration of different distances, angles, and smartphones are shown in •Fixed distance, camera angle, and smartphone to 20 cm, 0-degree, and iPhone X, respectively, while increasing ambient light intensity from 1600 lumens to 6100 lumens with step size of 1500 lumens.•Fixed ambient light intensity, camera angle, and smartphone to 3100 lumens, 0-degree, and iPhone X, respectively, while increasing the distance from 10 cm to 50 cm with step size of 10 cm.•Fixed distance, ambient light intensity, and smartphone to 20 cm, 3100 lumens, and iPhone X, respectively, while changing camera angle directions into 45° upside, 45° downside, 45° left side, 45° right side, and 0° center.•Fixed distance, camera angle, and ambient light intensity to 20 cm, 0-degree, and 3100 lumens, respectively, while changing smartphone to iPhone 6, iPhone X, and iPhone 11 Pro. The different ambient light environments were set up in a dark room where the light sources were picked using dimmable lights and the color Muse device To investigate the effect of each environmental factor on image features, we evaluated the effect of that factor on image features by constraining all other environmental factors and changing only one factor at each data acquisition stage. Hence, we had four phases of validation for environmental factors as follows:B.Since we used 3 different smartphones in this study, each having their own camera sensor characteristics and flashlight specifications, we had to calibrate the camera sensor and measure the amount of light coming from the smartphones’ flashlights. To calibrate the luminance reflection from different smartphones, we first measured the maximum luminance coming from an identical smartphone’s flashlight as shown in Next, we switched to different smartphones to calibrate the flashlight power. The flashlight power on each phone is adjustable and we tuned the flashlight to have a controlled and fixed amount of emitted light from each smartphone’s flashlight. Specifically, the emitted light from iPhone 6, iPhone X, and iPhone 11 Pro’s flashlights were measured at 112, 136, and 154 lumens, respectively, and we adjusted all smartphone flashlight intensities to 100 lumens using the smartphone’s flashlight tuning application C.The preprocessing step is necessary for effective and accurate feature extraction of the images. The two main parts of the preprocessing step are image segmentation and denoising. Images captured by a smartphone camera include other parts of the eye . Hence, image segmentation is required to extract the cornea region from the original image. The image segmentation was performed by using semi-automatic cropping of the eye image to extract the region of interest (ROI). The cropping was performed using a circle mask by marking the center of the circle and the radius of the circle. Here, the cornea was extracted from the eye image as shown in Taking into consideration that noise has a negative impact on acquired images, it is necessary to denoise the images using median filtering before processing to reduce the impact on eye segmentation and identification caused by irrelevant background in the images. The median filter has been widely applied in removing pepper salt and glare noise from an image while preserving edges and keeping main color feature information. In this study, the median filter was utilized to preprocess and smoothen the source images as shown in An example of pepper salt denoising is shown in D.Because most cataract diseases appear in the shape of a circle in the lens area, the watershed algorithm can be applied for image segmentation and visualization of the diseased areas Gradian magnitude is calculated using the following equation We implement the closing reconstruction algorithm which is the erosion of dilation of image A by a structuring element B, using the following equation E.BV) BV) change depending on the acquired images BV) from the R, G,R, G,R, G,BV) are calculated using the following equation from R, G,G,Our proposed cataract detection method uses luminance values reflected from an eye to detect cataracts. In a smartphone, the luminance value can be determined by exposure time  were allocated for training and validation, and the remaining 30% (30 images) for testing. Moreover, we applied the support vector machine (SVM) for the classification step. The SVM can be efficiently implemented on smartphones, and it has been adopted for eye disease diagnosis In this paper, we adopt Gaussian kernel for the SVM classifier to distinguish our samples into healthy and diseased classes. To prevent overfitting, 10-fold cross-validation was performed on the training and validation data. Therefore, 9-folds were used to train the SVM model and 1-fold to validate the model.III.Images from 100 eye samples of different environments were gathered in this paper. Among these 100 samples, 50 were diseased eye samples and the other 50 were healthy samples. First, we evaluated the impact of different environmental factors on image features using 15 randomly picked images, among 50 images for each environment, by constraining three factors and altering the fourth factor. We repeated this by alternating all four environmental factors one by one. The results of the impacts of different environmental factors on RGB and luminance values are shown in The results of changing ambient light while fixing other environmental factors is shown in As shown in TP is true positive (diseased eye correctly diagnosed as diseased), FP is false positive , TN is true negative , and FN is false negative . Adopting the above equations, the accuracy of detecting the diseased eye with the proposed method was 96.6%, the sensitivity was 93.75%, and the specificity was 93.4%.The performance of our proposed method is evaluated in terms of sensitivity, specificity, and accuracy, which are defined as:IV.In this paper, we have investigated the feasibility of detecting cataracts using smartphones. We have proposed an accurate, portable telemedicine solution which can detect cataracts by adopting a novel luminance-based feature extraction algorithm. This method can be used for bedside, clinical, and community applications, which are the main pillars of translational medicine et al.et al. and Kaur et al, Previous methods of detecting cataracts using smartphones include the GLCM method proposed by Fuadeh et al.The drawback of the GLCM method proposed by Fuadeh The drawback of the method proposed by Lau and Chan A comparison in terms of accuracy between our method and the mentioned studies has been presented in the following table.As shown in All the mentioned studies have used a single smartphone for image acquisition and acquired the data in a controlled environment. The results of their studies are heavily dependent on the smartphone’s camera configuration and sensor characteristics, the distance between the smartphone and eye, and the camera angle. However, our proposed method is effective irrespective of those environmental factors.The accuracy, specificity, and sensitivity of the proposed method to detect signs of cataracts was 96.6%, 93.4%, and 93.75%, respectively. Experimental results in this study show that the method can accurately detect cataracts from different distances, smartphones, and camera angles. It also shows that changing environmental factors had a very limited impact (average 2.8% impact) on the outcome results. Alternating the camera distance, smartphone, and camera angle had 3.3%, 3%, and 2.2% impact, respectively on the outcome results, which was negligible. We can implement our method on any smartphone, including iOS or Android phones, with adequate hardware using a re-targetable application platform


SARS-CoV-2 is one of the most threatening pandemics in human history. As of the date of this analysis, it had claimed about 2 million lives worldwide, and the number is rising sharply. Governments, societies, and scientists are equally challenged under this burden.This study aimed to map global coronavirus research in 2020 according to various influencing factors to highlight incentives or necessities for further research.The application of established and advanced bibliometric methods combined with the visualization technique of density-equalizing mapping provided a global picture of incentives and efforts on coronavirus research in 2020. Countries’ funding patterns and their epidemiological and socioeconomic characteristics as well as their publication performance data were included.Research output exploded in 2020 with momentum, including citation and networking parameters. China and the United States were the countries with the highest publication performance. Globally, however, publication output correlated significantly with COVID-19 cases. Research funding has also increased immensely.Nonetheless, the abrupt decline in publication efforts following previous coronavirus epidemics should demonstrate to global researchers that they should not lose interest even after containment, as the next epidemiological challenge is certain to come. Validated reporting worldwide and the inclusion of low-income countries are additionally important for a successful future research strategy. In December 2019, a new coronavirus (CoV) variant infected some patients in China. It was transmitted at a seafood and wet animal wholesale market in Wuhan city, Hubei Province. This novel zoonotic coronavirus was named SARS-CoV-2 because it also causes severe acute respiratory syndrome (SARS) [As of this analysis , more than 93 million COVID-19 cases have been confirmed, with the number continuing to rise rapidly. Over 2 million people have died in association with SARS-CoV-2 infection as of that date [Indeed, it was expected that the number of publications on CoV would increase sharply in 2020, but to what extent and with what participation were not clear . There aTo achieve this objective, this study mapped the world according to various influencing factors, leading to an advanced and meaningful assessment of the research of the first COVID-19 pandemic year 2020, which will certainly not be the last.This study followed the methodological approach of the bibliometric platform New Quality and Quantity in Science (NewQIS) . For theThe aim was to provide solid information on research patterns in terms of trends, incentives, challenges, obstacles, and necessities for all parties involved. Socioeconomic parameters and research-specific conditions at the country level were included in the analyses to assess regional performance according to the need for valuable and balanced research that is accessible and appropriate for all parts of the world.To capture all CoV-related articles published in 2020, the following elaborated search term was applied in the Web of Science Core Collection (WoS) search field: Title: “corona virus*” OR “coronavirus*” OR “SARS” OR “MERS” OR “covid-19” OR “severe acute respiratory syndrome” OR “middle east respiratory syndrome” AND Topic: virus* OR epidem* OR CoV OR Co-V OR patient* OR outbreak* OR “corona virus” OR “coronavirus” OR “covid-19” OR “severe acute respiratory syndrome” OR “middle east respiratory syndrome”. This string ensured the representativeness of the database generated. Then, the entries were filtered by original articles to base the evaluation on actual research on coronavirus. No language filter was applied. The year 2020 was chosen as the time frame. The date of data collection was January 12, 2021.The metadata of the datasets collected in this way were stored and sorted according to the individual evaluation parameters and linked by assigning identification numbers to each entry. Some parameters had to be additionally corrected manually, such as matching institution names and funding sources.In addition to established bibliometric parameters such as publication performance, citation parameters, and networking, CoV-specific parameters were also analyzed in this study. These relate to epidemiological characteristics (numbers of cases associated with COVID-19 ), socioeIn addition, an analysis of the development of publication and citation numbers in 10 time intervals, into which the year 2020 was divided, was carried out. Furthermore, an analysis of research areas was performed employing clustering with the application VOSviewer developed by van Eck and Waltman [Although the methodology used provides a valid source of data, some limitations must be considered when evaluating the results. First, all analyses can only be as good as the database used. For all NewQIS studies, WoS serves as the standard data source. Despite the often-documented English bias and the limitation of a somewhat restricted dataset, according to the high indexing requirements , the datCOVID-19 as the most frequently occurring keyword indicates that almost all coronavirus research in 2020 related to SARS-CoV-2 infection, as confirmed by a manually performed review of the articles included in the database.In addition, analysis of the most frequently used keywords (threshold: 200 occurrences) revealed 4 thematic clusters dealing with the psychological and physical impacts of COVID-19, immunological and biochemical issues, and epidemiological and public health issues . The artApplying search terms yielded 67,437 publications on CoV in 2020, of which just under half were original articles  that comprised the analysis database. Of the other document types, 12,435 were letters, 12,245 were editorial material, 6956 were classified as early access, and 6556 were reviews, to name the most common publication types. Looking at the overall evolution of CoV research, the year 2020 was exorbitantly outstanding . The epiAlthough the 2020 articles are still very young to generate a significant number of citations and thus recognition in the scientific community, which underlies a citation half-life of 7-8 years for biomedical articles, some articles already received an exceptionally high number of citations. The 10 most frequently cited articles are summarized in In total, 170 countries or autonomous regions participated in research on CoV in 2020 that was indexed in WoS. By far, the United States had the most publications (n=9018), followed by China (n=5053), Italy (n=3195), the United Kingdom (n=3135), and India n=1847; A.In contrast, China received the most citations . The United States got considerably fewer citations on their CoV-related articles . It is followed by the United Kingdom , Italy , and Germany . India ranked only 12th with 6351 citations B.Resulting from these numbers, China also led the ranking when looking at the citation rates of countries with at least 30 articles on CoV in 2020 (threshold) with a citation rate of 30.78. It was followed by the Netherlands (citation rate=19.56), Russia (citation rate=17.04), Austria (citation rate=16.18), and Vietnam (citation rate=16.07). In this term, the United States and the United Kingdom ranked nearly similarly, at only 22nd (citation rate=9.54) and 23rd (citation rate=9.52), and India was even only ranked at 79th . China showed the highest distance from the regression line  toward a favorable publication performance , while India, the United States, and Brazil showed the highest deviations toward a more negative relationship . The most publishing European countries were also in the positive range of deviation from the regression line but on a lower level than China  was analyzed. The coefficient of determination was r2=0.64 A showingan China B.CASES) with at least 30 articles on CoV (threshold), southeastern countries were ahead. New Zealand, with only 1900 registered cases, could be ranked first (RCASES=1105.26), followed by Vietnam (RCASES=1099.54), China (RCASES=512.34), Australia (RCASES=438.50), and Thailand (RCASES=119.46). On the other hand, among the most publishing countries besides China, Italy ranked next at 21st, followed by the United Kingdom (26th), Germany (30th), the United States (51st), and India (69th) due to their enormous incidence rates . When looking at the countries with more than 100 articles on CoV in 2020, Jordan, as an upper-middle-income economy, led the ranking (RGDP=1543.10). It was followed only by high-income economies until position 21 (upper-middle-income economy=South Africa). Rank 2 could be attributed to Italy (RGDP=1438.54), followed by Switzerland (RGDP=1325.11), New Zealand (RGDP=1201.37), and Israel (RGDP=1178.45). In addition, the number of articles was significantly correlated with gross expenditures on research and development in purchasing power parity in international $ .The inclusion of socioeconomic features of the publishing countries revealed a different ranking. The first ratio related the publication output per country with its economic power (ranked GDP [RPOP) of the same countries, only high-income countries were leading. Switzerland ranked first (RPOP=80.08), followed by Norway (RPOP=45.20), Israel (RPOP=42.82), Belgium (RPOP=42.25), and Austria , followed by the United States (number of grants=3983), the United Kingdom (number of grants=1179), Spain (number of grants=589), and Brazil  of the International Committee on Taxonomy of Viruses. The involvement of the Netherlands in the CSG contributes to its high citation rate (rank 2 behind China) because the term is internationally accepted, and subsequent publications naturally are in unison on the designation of SARS-CoV-2 . In addiWhen the publication numbers are related to the number of COVID-19 cases, other countries showed up in leading positions. With New Zealand, Vietnam, China, Australia, and Thailand at the top, parts of the eastern and southeastern world showed leading performances due to their very low case numbers in combination with relatively high publication numbers. Countries’ awareness of the problem influences not only the containment of the pandemic but also their research efforts and the amount of government spending on research and development. The success of achieving low case numbers was explained by the rapid implementation of nonpharmaceutical measures, determined responses, rigor and brevity of containment measures, and testing strategies by public health authorities ,30. VietAfrica has the lowest confirmed case rate of any continent. Only South Africa reported numbers among the 20 most-affected countries.  This is Nevertheless, the low incidence rates in countries with poor health care systems and the associated low quality of the tests are often questioned. High risk is associated with misdeclaration or misreporting of the COVID-19 development. Therefore, globally transparent and traceable reporting is of immense importance, and the development in these regions must be closely monitored in the future .On the other hand, regions with extremely high case numbers, such as the United States, India, Brazil, and some European countries, were proportionally more involved in CoV research. That is also shown by the correlation between COVID-19 cases and article numbers, which is highly significant. Only Russia, with the fourth highest case numbers, fell slightly behind but still shows an enhanced contribution rate to CoV research compared to other scientific topics.This is also made possible by the intensive funding of the governments of the severely affected countries. In line with these figures, the high Italian case numbers prompted unusually high levels of cooperation with the United States, the United Kingdom, and Spain.Saudi Arabia, which ranks in the middle of COVID-19 case numbers, was funded primarily through its universities, resulting in a relatively high ranking in publication numbers. This is likely due to the experience gained during the MERS epidemic, which mainly affected Saudi Arabia, accounting for 77% of cases globally. The results of an earlier analysis looking at CoV research up to the COVID-19 outbreak showed that Saudi Arabia even ranked 11th in overall publication performance . Jordan,The awareness and preparedness of countries affected by previous CoV epidemics also led to high interest in CoV research during the 2020 COVID-19 crisis. Although disease containment may have led to a rapid decline in publication numbers, this experience appears to have been so fresh that the propensity for ad hoc research was high. On the other hand, maintaining a reasonable level of interest would have resulted in a better scientific baseline for all containment efforts at the onset of COVID-19 worldwide. This lesson learned should be kept in mind for all future research planning.The results of this study demonstrate the extraordinary momentum of CoV research in 2020 due to the ongoing global spread of COVID-19. They also reveal the need for continued interest and dedication by scientists even after pandemics are contained. It is to expect that the next pandemic will come and also become a threat anywhere in the world. Well-prepared and sound scientific support enables decisive measures. The experience of highly developed scientific nations must be linked with that of less developed research structures to be of global benefit.


Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis is usually based on manual myocardial (MYO) segmentation of MRI sequences. As manual segmentation is tedious, time-consuming, and with low replicability, automatic MYO segmentation using machine learning techniques has been widely explored recently. However, almost all the existing methods treat the input MRI sequences independently, which fails to capture the temporal information between sequences, e.g., the shape and location information of the myocardium in sequences along time. In this article, we propose a MYO segmentation framework for sequence of cardiac MRI (CMR) scanning images of the left ventricular (LV) cavity, right ventricular (RV) cavity, and myocardium. Specifically, we propose to combine conventional neural networks and recurrent neural networks to incorporate temporal information between sequences to ensure temporal consistency. We evaluated our framework on the automated cardiac diagnosis challenge (ACDC) dataset. The experiment results demonstrate that our framework can improve the segmentation accuracy by up to 2% in the Dice coefficient. Coronary artery disease (CAD) is the most common cause of death globally. It affects more than 100 million people, and results in about 10 million death each year . MRI is Recently, automatic MYO segmentation of CMR image sequences has attracted considerable attention in the community , 5. On tCurrently, there exist two approaches for automatic MYO segmentation. In the traditional MYO segmentation approach , 8, a maOn the other hand, temporal consistency has been extensively used to improve segmentation accuracy in a variety of applications. Yan et al.  added teIn this article, we propose to exploit temporal consistency for MYO segmentation of CMR sequences for automatic CAD diagnosis. Particularly, we propose to combine conventional neural networks and recurrent neural networks to perform segmentation in two stages. The first stage contains an initial segmentation network (ISN) to get the initial segmentation without temporal information, while the second includes a temporal consistency based network (TCN) for refinement considering temporal consistency. The contributions of our study are:We proposed to use temporal consistency for accurate MYO segmentation of CMR sequence, and our framework is able to incorporate temporal information between CMR frames.To further exploit the temporal consistency among frames, we adopted a bi-directional training approach that can reduce segmentation error introduced by the first few frames in the training process.We conducted comprehensive experiments on the ACDC dataset. Compared with the residual 3D U-net model of Yang et al. , our fraCardiac MRI image is a widely used imaging tool for the assessment of MYO micro-circulation. It utilizes the electromagnetic signal with characteristic frequency produced by the hydrogen nuclei under a strong contrasting magnetic field and weak oscillating near field as the imaging agent.Due to the high capacity for discriminating different types of tissues, CMR image is one of the most prominent standards for cardiac diagnosis through the assessment of the left and right ventricular EF and SV, the left ventricle mass and the myocardium thickness. For example, Bernard et al.  obtainedIn order to evaluate the MYO function, accurate segmentation of the LV cavity, RV cavity, and MYO need to be acquired from the framework. Medical image segmentation has attracted much attention recently –26. MYO The first approach is based on point distribution models (PDMs) . A good The prediction results of ASM must be constrained into certain shape variations so that the shape of the segmentation result does not go too far from the regular myocardium shape. Note that this is very important when artifacts and defects in the CMR image make the myocardium boundary unclear and hard to recognize. However, ASM is based on linear intensity information in the image, which is insufficient to model the appearance of CMR data with huge intensity variations and large artifacts. In addition, ASM requires a manual initialization shape and the final segmentation result is very sensitive to the shape and position of this initialization. Thus, a fully automatic and non-linear model is needed.The second approach adopts machine learning techniques to perform image segmentation. For example, Zhang et al.  used a sAlthough these above methods showed great improvements in the segmentation performance compared to ASM or AAM. They treat each frame independently, which makes the segmentation results of some specific sequences inaccurate or the overall results lack coherence.On the other hand, temporal consistency has been extensively used to improve the segmentation accuracy in various applications in multiple image modalities, which includes US, computerized tomography (CT) and CMR. Painchaud et al.  proposedThe automatic cardiac diagnostic challenge (ACDC) dataset consists of both patients with CAD and healthy individuals, whose diagnosis results are extracted from clinical medical cases. There are 150 patients in total and are evenly divided into five subgroups based on their diagnosis results. The five subgroups of patients have systolic heart failure with an infraction, dilated cardiomyopathy, hypertrophic cardiomyopathy, abnormal right ventricle, and no abnormality, respectively. A total of 50 of the patients made up the test dataset on the ACDC website, and the other patients are released as the training dataset. CMR sequences of all patients are collected by two MRI systems with different magnetic strengths . For each frame in the patient's CMR sequence, there contains a series of short-axis slices covering the LV from base to apex , yt,k depends on three variables: (1) the output of the previous ConvLSTM layer yt,k−1; (2) the extracted features in hierarchical ConvLSTM from ISN gt,k; and (3) the hidden state of the same ConvLSTM layer for the previous frame yt−1, k. Note that there is no direct connection between two levels of bi-directional ConvLSTMs in TCN's hierarchical LSTM model. The input of TCN (with 4 channels) will be copied into two copies. The one for level 2 bi-directional ConvLSTM will have 8 channels as the result of an extra 3D Convolution and Max Pooling operations. The one for level 1 bi-directional ConvLSTM will have 4 channels. The outputs from two bi-directional ConvLSTM will be combined by pointwise addition.The network structure of TCN is shown in hinput is the input of ConvLSTM, and hstate is the hidden state input of ConvLSTM. [A|B] is the concatenate operation for tensors A and B on the feature axis. For the first frame of a CMR sequence, hstate is a matrix of ones, which means no prior information is known.In Equation (3), We notice that the prediction results of myocardium segmentation in the CMR image are highly related to the segmentation result of frames either behind or after it. The first frame of the CMR sequence will not receive enough information if we only use forward Conv LSTM. T, while the other will propagate backward, from frame T to frame 1. T is the total number of frames in one CMR sequence. t takes in two inputs: the cell state at time t−1 and the ISN's output for a frame of CMR image at time t. The Backward ConvLSTM cell at time t also takes in two inputs: the cell state at time t+1 and ISN's output for a frame of CMR image at time t. When the ConvLSTM cell is initialized, the cell's hidden state is initialized as a zero vector. Such an approach can better exploit the temporal information along with the frames, thus, improving the segmentation accuracy.Therefore, we adopted a bi-directional training approach to alleviate this problem. Specifically, we used two Conv LSTMs in our TCN model. One will propagate forward, from frame 1 to frame Note that our method is trained in two phases. In the first phase, ISN is trained. ISN's parameters are updated using the ground truth label from ACDC dataset frames at ED and ES. In the second phase, ISN and TCN are trained together. The supervision signal will only enter the framework from the output of TCN. The computation graph of ISN and TCN are connected, and the gradient can flow from TCN to ISN properly. TCN will give out segmentation result for each frame of the CMR sequence. Among all results, we will only take out the frame at ED and ES time for lost function calculation.x-axis and y-axis, respectively. During testing and validation, we did not employ any augmentations. For each iteration, a complete CMR sequence containing 28–40 frames of a patient was used for training. Due to the limited GPU memory, the batch size is set to 1, which means in each iteration, 1 CMR sequence containing 28–40 frames is fed for training. We trained ISN for 10 epochs with a learning rate of 0.0001. Then, we trained ISN and TCN together with a learning rate of 0.0001 and a learning rate decay of 0.7 per epoch for another 10 epochs. Three loss functions including soft Dice loss, cross-entropy loss, and contour loss  implementation is used as our baseline. We compared the proposed framework (Res U-net+ConvLSTM) and Res U-net. Res U-net and ConvLSTM are implemented using PyTorch based on Xingjian et al.  and Isenour loss  are usedWe split the ACDC dataset into the training set, validation set, and testing set by a ratio of 7:2:1 based on the patient number. Therefore, there are 70 patients in the training set, 20 patients in the validation set, and 10 patients in the testing set. Dice coefficient and Inter-section over Union (IoU) are used to evaluate the segmentation performance, which is defined as:P and T refer to the prediction and ground truth mask, respectively. n is the index of all voxels .in which T while our framework (Res U-net+bi-ConvLSTM) refers to training in bi-direction. We noticed that our framework outperforms baseline implementation in all metrics for both ED and ES frames. Specifically, our Res U-net+f-ConvLSTM implementation has an improvement of 0.01, 0.10, −0.81, 0.61, 0.55, and 0.30% on the Dice coefficient of LV, RV, and MYO at ED frame and ES frame, respectively. The experiment results of Res U-net+f-ConvLSTM and our framework show that by adding a backward training step, we can further increase the segmentation performance. Our framework's implementation has an improvement of 1.11, 0.64, 0.82, 0.83, 2.39, and 1.02% on the Dice coefficient of LV, RV, and MYO at ED frame and ES frame, respectively.Note that the work  used theQuantitative segmentation results and grading results demonstrate the superiority of our framework compared with the Res U-net baseline implementation. However, there are still some cases where our framework cannot predict reasonable boundaries. For example, There are some cases as shown in Note that compared with existing works for MYO segmentation of CMR sequences, our main contribution is to adopt temporal consistency for coronary artery disease (CAD) diagnosis which has not been extensively explored before. The results show that temporal consistency is important in the MYO segmentation of CMR sequences. Compared with existing works making use of temporal consistency, our methodology differs from the others as follows. Yan et al.  incorporIn this article, we proposed an MYO segmentation framework of CMR sequences for CAD diagnosis. Specifically, we proposed to combine conventional neural networks and recurrent neural networks to incorporate temporal information between sequences to ensure temporal consistency. Extensive experiments showed that compared with Res U-net, our proposed framework can achieve an improvement of 1 to 2% in Dice coefficient. In addition, we introduced a bi-directional training approach to further reduce segmentation error introduced by the first few frames in the forward training process. Experiment results demonstrate that our bi-directional training approach can further improve the segmentation performance.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.YC, WX, JZha, and HQ contributed to data collection, analysis, and experiment. DZ, YS, HY, JZhu, YD, and QJ contributed to discussion and writing. YZ, MH, and XX contributed to project planning, development, discussion, and writing. All authors contributed to the article and approved the submitted version.This study was supported by the National Key Research and Development Program of China (No. 2018YFC1002600), the Science and Technology Planning Project of Guangdong Province, China , Guangdong Peak Project (No. DFJH201802), and the National Natural Science Foundation of China (No. 62006050).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Ruminococcus sp. supplementation and/or heat stress (HS) on the growth, serum biochemistry, tissue antioxidant, phagocytic assay, histopathology, and bursa gene expression of broilers. Day-old broiler chicks were allotted into six groups according to HS and/or Ruminococcus with or without enzyme supplementation. The first group was the control one, with a formulated diet and normal environmental temperature but without any supplement. The second group fed on Ruminococcus-supplemented diet (1 kg/kg diet). The third group fed on a formulated diet without supplement, and Ruminococcus and digestive enzymes were given in drinking water (0.1 ml/L). The fourth one was the heat stress group, with a normal formulated diet. The fifth and the sixth groups served as second and third groups, respectively, but with heat stress. The results of this experiment indicated that thermal temperature negatively affected the parameters of growth performance, serum biochemical, tissue antioxidants, and phagocytic assay. Moreover, heat stress led to pathological lesions in the internal organs and affected the expression of some genes related to heat stress, including proapoptotic genes such as caspase8 and bax, inflammatory genes such as NF-κβ1, and heat shock protein such as HSP 70 in the bursal tissue. These bad effects and abnormalities were mitigated by Ruminococcus alone or with enzyme supplementation, which improved all the above-mentioned parameters.This research was conducted to evaluate the impact of dietary or drinking water  Ruminococcus are anaerobic, Gram-positive gut microbes related to the class Clostridia . They are digestive enzymes with GIT microbiota obtained from BACTIZAD Company.The GIT microbiota were obtained from Egavet Company, Egypt, including Ruminococcus-supplemented diet (1 kg/kg diet). The third group (E), the intestinal microbiota with digestive enzymes group, fed on a formulated diet without supplement, and Ruminococcus and digestive enzymes were given in drinking water (0.1 ml/L). The fourth (HS) one was the heat stress group and fed on a formulated diet without any supplement but exposed to heat stress . The fifth (R+HS) and the sixth (E+HS) groups served as second and third groups, respectively, but with heat stress. All groups of chicks were kept in a clean room with good ventilation and vaccinated at 7–12 days against Newcastle disease and infectious bursal disease, respectively. Food and water were added ad libitum to the chicks, and they were maintained for 42 days under good sanitation and hygiene.For the present research, 180 Cobb-505 1-day-old broiler chicks (40–45 g/chick) were obtained from a private farm in the Governorate of Kafrelsheikh. The protocol of the experiment was ethically approved by the Research Ethical Committee of the Faculty of Veterinary Medicine, Kafrelsheikh University, Egypt . The birds were allotted by ranking method into six groups; each group contained 30 birds in three replicates. The first group (control) was the control one and fed on formulated diet according to NRC , withoutThe feed proximate analysis was done , and theAt the termination of the growing period (42 days), three broilers were taken randomly from each replicate (nine birds/group), deprived of food for 12 h, and then weighed individually. After that, the birds were euthanized by using an overdose of anesthesia and slaughtered to complete the bleeding, followed by plucking of the feathers. The dressed weight was taken after the removal of the head, viscera, shanks, gizzard, liver, heart, and immune organs. The dressing percentage was calculated on the basis of live weight, where dressing percentage was defined as carcass weight divided by the final live weight record of the bird.The birds for the sample collection were randomly selected and anesthetized by an intraperitoneal injection of sodium pentobarbital (50 mg/kg). Two samples from each bird (5 ml blood/sample/bird) were collected from the wing vein (six samples/group). The first sample was collected with an anticoagulant for hematological examination and phagocytic assay and the second one without anticoagulant for serum separation. The serum activities of aspartate transaminase (AST), alanine transaminase (ALT), and alkaline phosphatase (ALP) were measured by using commercial kits obtained from BIODIAGNOSTIC Company, Giza, Egypt.After the sample collection, the birds were euthanized by using an overdose of the anesthesia for tissue sample collection. The tissue samples were bursal sample (six samples/group) for gene expression and kept at −80°C until use, liver sample (six samples/group) for the activities of antioxidant enzymes , and malondialdehyde (MDA) concentration and liver, spleen, and intestine for histopathology.g for 20 min at 4°C for the separation of supernatants. The supernatant was used for determining the activities of antioxidant enzymes  and MDA concentration.Each liver sample (1 g) was homogenized with 5 ml phosphate buffer, pH 7.4, on ice using an electrical homogenizer. Tissue homogenate was centrifuged at 1,200 × Briefly, CAT activity was assessed according to the method described by Aebi  and exprCandida albicans. Equal volumes of fresh heparinized blood sample, C. albicans suspension , and fetal bovine serum were mixed and incubated at 37°C for 30 min. The samples were centrifuged at 1,500 rpm for 10 min, and then the sediment was resuspended on a glass slide. The slides were then fixed with methanol for further staining with polychrome methylene blue and eosin stain. The phagocytic activity (PA) and phagocytic index (PI) were determined. PA was calculated as the percentage of phagocytic cells that engulfed yeast cells, while PI was assessed as the total number of yeast cells phagocytized per phagocytic cell.Analyses of phagocytic activity and index were done according to the approach mentioned by Kawahara et al.  and El-KHepatic, intestinal, and spleen sections have been taken after necropsy and immediately fixed in 10% buffered formalin and treated with the routine paraffin embedding portion for histopathological evaluation. Then, 3-μm-thick sections were cut and stained using H&E .For complete RNA extraction, bursal samples were used with easy RED total RNA extraction kits  as per the instructions defined by the manufacturer. The completeness of the RNA was tested using the electrophoresis of agarose gel. The first cDNA branch was synthesized to complete the RNA using the cDNA synthesis kit Intron-Power (cat. no. 25011).Gallus gallus) genes, specific primers were used with GAPDH as housekeeping  gene primer sequence  lesions in the form of panting, increased water intake (thirst), diarrhea, reduced feed consumption, legs and wings outstretched, and prostration. On the other side, the PM lesions were manifested as congested carcass and mucoid exudate in the nostrils and mouth. The above-mentioned changes were decreased in the treated groups .Ruminococcus sp. significantly (P ≤ 0.05) increased the BW and total weight gain and decreased the FCR compared to the control group  decreased in the HS group compared to the control group, which was improved with treatments.Dietary supplementation of digestive enzymes and/or ol group . On the Ruminococcus sp. on some carcass traits of broilers. There were significant (P ≤ 0.05) and insignificant (P ≤ 0.05) increases in dressing and gizzard and heart percent, respectively, in the group that was supplemented with digestive enzymes and/or Ruminococcus sp. without heat stress compared to the control and R groups. Moreover, the thermal temperature significantly (P ≤ 0.05) decreased liver percent compared to the other groups. Meanwhile, the immune organs, including the thymus and bursa, and spleen were insignificantly and significantly (P ≤ 0.05) decreased, respectively, in the HS group compared to the other groups.Ruminococcus sp. There were insignificant (P ≤ 0.05) increases in red blood cell count and hemoglobin percent in groups that were supplemented with digestive enzymes and/or Ruminococcus sp. without heat stress compared to the control group. Moreover, the previous measurements were significantly (P ≤ 0.05) decreased in the HS group compared to the groups that were supplemented with digestive enzymes and/or Ruminococcus sp. with heat stress. On the other hand, the hematocrit percent was increased in the Ruminococcus sp. group (R) insignificantly and significantly (P ≤ 0.05) compared to the control and the group that received digestive enzymes and Ruminococcus sp. (E group). without heat stress, respectively. Meanwhile, the hematocrit percent was significantly (P ≤ 0.05) decreased in heat stress groups compared to the other groups without heat stress.P ≤ 0.05) increase in the total leukocytic count in the HS group compared to the other groups with or without heat stress. This decrease was improved with treatments even with heat stress. Moreover, the lymphocyte and heterophils were significantly (P ≤ 0.05) decreased and increased, respectively, in the HS group when compared to the other groups with or without heat stress. Meanwhile, the eosinophil and monocyte levels were not affected by heat stress or treatments. On the other hand, the basophil level was significantly (P ≤ 0.05) increased in the HS group when compared to the other groups with or without heat stress.Regarding the results of the leukogram, there was a significant (P ≤ 0.05) increase in the activities of the liver enzymes  enzymes in the HS group compared to the other groups. Moreover, the previous enzymes were significantly (P ≤ 0.05) increased in heat stress groups and supplemented with digestive enzymes and/or Ruminococcus sp. compared with the control group and groups that were supplemented with digestive enzymes and/or Ruminococcus sp. without heat stress.P ≤ 0.05) increased in the HS group compared to the other groups  increased, respectively, in the group that was supplemented with digestive enzymes and Ruminococcus sp. (E group) without heat stress compared to the control group and group that received Ruminococcus sp. (R group) only without heat stress or digestive enzymes. Meanwhile, tissue CAT activity was insignificantly (P ≤ 0.05) increased in the group that was supplemented with Ruminococcus sp. (R) without digestive enzymes and heat stress compared to the control group and group that received digestive enzymes and Ruminococcus sp. (E) without heat stress. Moreover, all antioxidant enzyme activities were improved with a digestive enzyme and Ruminococcus sp. supplementation (E).The level of MDA in liver tissue was significantly (r groups . This elP > 0.005), while supplementation of heat-stressed birds with Ruminococcus sp., in both powder and liquid forms, showed a marked increase of phagocytic activity and index in comparison with the HS group (P > 0.005). Supplementation of the liquid form (E) was associated with a significant increase of phagocytic activity than of the powder form (R) of Ruminococcus (P > 0.05).Both phagocytic activity and index  were marRuminococcus (R) showed the same morphology as that in the control group. Meanwhile, there was obvious cytoplasmic vacuolation observed in birds supplemented with the liquid form of Ruminococcus (E). This vacuolation was consistent with mild glycogen storage. The liver of birds exposed to heat stress was severely affected and showed massive degeneration of hepatocytes as fatty degeneration and heterophilic infiltration. In heat-stressed birds treated with powder (R) Ruminococcus, the liver showed a marked decrease of hepatic vacuolation of hepatocytes with mild mononuclear cell infiltration. In heat-stressed birds treated with liquid (E) Ruminococcus, the liver showed normal hepatocytes with slight periportal mononuclear cell infiltration  and liquid (E) forms of Ruminococcus showed a nearly similar morphology to that noticed in the control group. The spleen of birds exposed to heat stress was severely affected and showed marked lymphoid depletion and necrosis with massive histiocytic infiltration and complete absence of the normal architectural pattern of the spleen. In heat-stressed birds treated with powder (R) Ruminococcus, the spleen showed normal morphology with white and red pulp and slight lymphocytic depletion and histiocytic infiltration; however, in heat-stressed birds treated with liquid (E) Ruminococcus, the spleen showed mild lymphocytic depletion  and liquid (E) Ruminococcus-treated group, the bursal follicle remained in the same normal structure as the control ones, but with less cellularity in the medulla. In the heat stress-treated group, the bursal follicles showed a small-sized cortex with slightly packed lymphocytes, medullary necrosis, and hyalinization. Microcysts were observed in the mucosal folds. There was interstitial edema with increased thickness of the interfollicular connective tissue. In heat-stressed birds treated with powder Ruminococcus (HS+R), the bursal follicles were well-formed, with intact cortex and less cellularity in the medulla. Meanwhile, in heat-stressed birds treated with liquid Ruminococcus (HS+E), the bursal follicles were completely filled with lymphoid cells  and liquid (E) Ruminococcus-treated groups, there was a marked increase of thymic elements. In the HS-treated group, the thymus compartment showed severe necrosis with mononuclear inflammatory cell infiltration and loss of the normal architecture of the thymic compartments. In the heat stress group treated with powder and liquid Ruminococcus (HS+R and HS+E), the thymic compartments showed a marked decrease of medullary depletion with a marked increase of thymocytes . A marked decrease of these genes with supplementation of Ruminococcus spp. as powder or liquid was relevant with the control group (P > 0.005). A significant decrease of both caspase 8 and bax gene expression was noticed in supplementation with the liquid form than the powder form of Ruminococcus (P >0 0.05). The bursal tissues of HS animals revealed a marked elevation of NF-κβ1 than that of the normal group (P > 0.005), which decreased to the normal limits of the control groups. In the same way, HSP 70 mRNA expression was markedly increased in HS than control birds and significantly decreased in heat-stressed birds supplemented with Ruminococcus sp. than HS birds (P > 0.05).The response of some genes related to heat stress, including proapoptotic genes such as caspase8 and bax, inflammatory genes such as NF-κβ1, and heat shock protein such as HSP 70, is illustrated in The results of the clinical signs in the HS group are compatible with the results of Li et al.  who repoRuminococcus sp. supplementation. Dietary supplementation of probiotics with or without heat stress enhanced the production parameters and traits of the carcass and improved the clinical blood parameters. Moreover, Abramowicz et al.  percent. These results are in harmony with the results of Dinu et al. , Chaturvr chicks . Howeverr chicks  reportedr chicks  who repor chicks . These ar chicks .In the heat stress group, the activities of the serum enzymes  were significantly increased. These results may be attributed to the inflammatory process that resulted from heat exposure and are indicated by histopathology. The above-mentioned result is consistent with those of Bueno et al.  and HuanThe results of the liver, bursa, and spleen weights, growth performance, tissue antioxidant, and pathology are consistent with the results of the phagocytic assay. The result of the phagocytic assay is compatible with those of Laganá et al. , QuinteiOn the other hand, the results of the histopathology confirm and support previous results. In the heat-stressed birds, the result of the liver pathology is in agreement with that of Aengwanich and Simaraks , whereinOn a molecular basis, it was noticed that heat stress increased the apoptotic biomarkers including caspase 8 and bax genes. A marked elevation of inflammatory genes was also demonstrated, while the HSP genes' level of expression was variable according to the species and the duration of heat exposure. Our previous studies on hepatic and splenic tissues revealed a marked elevation of the different biomarkers such as heat shock proteins, inflammatory, and apoptotic genes , 32–77.Herein we selected the bursal tissues to explore the noticeable early signs of bursal involution, which indicated the presence of intra-follicular mucosal cysts and interstitial fibrosis. The early bursal atrophy was correlated well with the marked upregulation of apoptotic genes, including bax and caspase 8. On the other hand, HPPs are considered one of the cellular homeostasis mechanisms against heat stress. Experimental studies reported the upregulation of HSPs in chronic heat conditioning in a time-dependent manner.As molecular chaperones, heat shock proteins play a crucial role by helping to correctly pliage and avoid the aggregation of emerging and stress-accumulated misplant proteins that have a defensive feature, which allows the cells to survive under conditions otherwise considered lethal . The resThe present experiment demonstrated that the administration of a probiotic with or without enzymes throughout the rearing period of the broiler chicks with or without heat stress had the most beneficial effect on growth performance, enzymatic activity of serum liver, liver tissue antioxidants and peroxide, and phagocytic assay. Moreover, the supplements improved the pathological lesions in the internal organs that resulted from heat stress.The datasets used and/or analyzed during the current study are available from corresponding author on reasonable request.The animal study was reviewed and approved by Research Ethical Committee of the Faculty of Veterinary Medicine, Kafrelsheikh University, Egypt .All authors designed and conducted the experiment, wrote the manuscript, read, and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.