The results of the ML-based modeling approaches revealed that the gradient boosting model had a good degree of precision, but the random forest model predicted the strength of the WGP-based CM with a greater degree of precision for CS and FS prediction. The SHAP analysis revealed that fine aggregate was a critical raw material, with a stronger negative link to the strength of the material, whereas WGP and cement had a greater positive effect on the strength of CM. Utilizing such approaches will benefit the building sector by supporting the progress of rapid and inexpensive approaches for identifying material attributes and the impact of raw ingredients.This research employed machine learning (ML) and SHapley Additive ExPlanations (SHAP) methods to assess the strength and impact of raw ingredients of cement mortar (CM) incorporated with waste glass powder (WGP). The data required for this study were generated using an experimental approach. Two ML methods were employed, i.e., gradient boosting and random forest, for compressive strength (CS) and flexural strength (FS) estimation. The performance of ML approaches was evaluated by comparing the coefficient of determination (R Numeroudecrease ,19,20. Idecrease ,22. Globdecrease . Althougdecrease . Comparedecrease . Moreovedecrease . China gdecrease , posing decrease ,29,30. Pdecrease ,29. Thusmissions ,32.Numerous experiments have been conducted to assess the characteristics of CM and compressive strength (CS) is interpreted as significant . The CS 2), statistical checks, k-fold method, and variation in the predicted results (errors). Experimental-based studies entail extensive efforts, expenditures, and time for material collection, sample casting, curing, and performing tests. By decreasing these efforts using advanced techniques such as ML, the construction sector will benefit as a result. Due to the fact that several raw ingredients, such as cement, fine aggregate, water, silica fume, superplasticizer, and WGP, influence the strength of CM, it is difficult to measure their combined influence using experimental methods. In this instance, a SHapley Additive ExPlanations (SHAP) analysis was performed to explore the interaction and impact of raw ingredients on the CS and FS of CM. A data sample is needed for ML techniques, which can be generated from the experimental approach. The data generated may consequently be employed to train ML techniques and approximate material properties. The present study used 6 input parameters to foretell the CS and FS of WGP-based CM and assess the efficacy of each ML approach and the impact of raw ingredients on its strength.This work utilized experimental data to assess the CS and FS of CM with waste glass powder (WGP), used to partially replace cement and fine aggregate, by employing ML methods. Samples of CM were cast using varied quantities of WGP as cement and fine aggregate replacements from 0 to 15%, with an increment of 2.5%. The CS and FS of the samples that contained WGP were recorded at 28 days of age. Two ML methods were employed, i.e., random forest regressor (RFR) and gradient boosting regressor (GBR), to achieve the study’s aims. Both GBR and RFR are ensemble ML methods . BecauseIn order to obtain the desired results, ML approaches require a broad collection of input parameters . In this2 value of the expected outcome indicates the exactness of a model. The R2 value reveals the amount of deviation; a number close to zero indicates greater variation, whereas a number close to one suggests that the prediction model and experimental results are almost entirely matched [Using the experimental data, the CS of CM that contained WGP was evaluated. The procedures utilized cement, fine aggregate, water, silica fume, superplasticizer, and WGP as inputs, with CS and FS serving as the outputs. Ensemble ML approaches with Python code, and Anaconda Navigator software were utilized to achieve the aims of the research. The ML models were operated using Spyder (version 5.1.5). GBR and RFR ML methods were used to assess the CS and FS of WGP-based CM. These ML algorithms are generally used to estimate required results using input variables. These approaches may be used to forecast a material’s strength, temperature resistance, and durability ,53. Duri matched . On bothFriedman  suggesteRFR is accomplished by means of random split selection on bagged decision trees . The con2 is larger. In addition, the desired result requires 10 repeats of the technique. This effort greatly adds to the model’s outstanding accuracy. In addition, each ML technique’s precision was statistically evaluated using error evaluation . The accuracy of the ML methods’ projections was statistically evaluated using Equations (1)–(3) derived from past research [Statistical checks and k-fold techniques were adopted to confirm the deployed ML algorithms. Typically, the k-fold method is employed to evaluate the effectiveness of a model by randomly splitting relevant data samples into 10 classes . As showresearch ,62.(1)M𝑆 = the ingredient subset,𝑝 = the ingredient number in the model.This research also determined global feature impacts and analyzed feature relations with CM, using a game theory approach known as SHAP . SHAP anpatterns . The ϕj using Equations (1)–(3) above for both CS and FS estimation models are shown in In this research, the effect of raw materials on the CS and FS performance of CM was investigated. The SHAP tree explainer is employed in the entire dataset to provide a more detailed explanation of the global feature effects by including local SHAP explanations. 2 in the chemical composition of glass reacts with Ca(OH)2 in the matrix to create a thick C-S-H gel, hence improving the performance of the material [3 to increase material strength. Moreover, WGP interacts primarily with the FA, among other input characteristics. This indicates that the use of WGP as a substitute for FA may result in greater strength compared to its usage as a cement replacement. It is crucial to note that these results are dependent on the kinds of raw materials and the size of the dataset studied in this research. Utilizing varied input settings and data samples could result in distinct outputs.material ,70. Util2. GW has the possibility to be used as a partial substitute for fine aggregate and cement in CM, which is an environmentally favorable technique. Therefore, the use of GW in CM will decrease environmental impacts through the elimination of waste, preservation of natural resources, and reduction in CO2 emissions. Using ML-based modeling and SHAP analysis techniques, this research aimed to expand knowledge about the application of WGP in CM. This work estimated the CS and FS of WGP-based CM using GBR and RFR ML techniques. The accuracy of each technique was evaluated to ascertain which is the most exact predictor. Compared to the GBR method, with an R2 of 0.93 and 0.89 for CS and FS estimation, respectively, the RFR method produced more accurate results, with an R2 of 0.94 and 0.91 for CS and FS prediction, respectively. The disparity between the experimental and anticipated outcomes (errors) further substantiated the superior accuracy of the RFR approach. Compared to the GBR models, the experimental and estimated results for the RFR models showed good agreement, as demonstrated by the error analysis. In predicting the strength of CM, previous research has similarly demonstrated that the RFR method is more exact than the GBR method [Globally, a substantial quantity of GW is produced, most of which is discarded in landfills, posing health and environmental risks . FurtherR method ,71,72.2 is high, a model is more exact. Nevertheless, defining and recommending the optimal ML method for predicting attributes in various study areas is difficult, since the accuracy of an ML methodology is primarily reliant on the size of inputs and data samples used to execute algorithms [2 value, thus resulting in more accurate outputs than the individual ML models. 2 for the GBR and RFR sub-models. The R2 for GBR-CS sub-models ranged from 0.876 to 0.932, with a mean of 0.903. In addition, the R2 for the RFR-CS sub-models varied between 0.927 and 0.944, with an average of 0.938. Likewise, the average R2 values for the GBR-FS and RFR-FS sub-models were 0.866 and 0.905, respectively. These findings reveal that the RFR sub-models are more precise than the GBR sub-models. Additionally, a SHAP analysis is conducted to investigate the interaction and influence of raw materials on the CS and FS of WGP-based CM. FA was demonstrated to be a very effective raw material, exhibiting a stronger negative association with the material’s strength. However, WGP was found to have a greater positive impact on the strength of CM. While WGP has been demonstrated to have beneficial effects, there is evidence that exceeding the optimal dosage may have negative consequences on performance. In addition, the impact of cement on CS and FS was shown to be more beneficial, indicating that strength increases with increasing cement content. However, due to the lack of variation in SF and SP in the data sample, their effect was ambiguous, and larger datasets with more input features may result in better associations.Moreover, the accuracy of both models was examined using statistical and k-fold approaches. When the degree of divergence  is low and Rgorithms . Ensembl2 of 0.93 and 0.89 for CS and FS prediction, respectively, while the RFR models had a higher degree of precision, with an R2 of 0.94 and 0.91 for CS and FS prediction, respectively.It was determined from the modeling methods that the GBR models had a satisfactory degree of precision, with an RThe average variation between predicted and experimental CS (error) in GBR and RFR models was determined to be 1.25 MPa and 1.10 MPa, respectively. Similarly, the average error values in predicting the FS of CM in the GBR and RFR models were 0.12 MPa and 0.10 MPa, respectively. These errors also confirmed the acceptable precision of the RFR models and higher accuracy of the RFR models in forecasting the strength of WGP-based CM.The SHAP study revealed that fine aggregate (FA) was a crucial raw material, with a higher negative correlation to the material’s strength. WGP and cement had a stronger favorable impact on CM’s strength. Due to the deficiency of variance in silica fume (SF) and superplasticizer (SP) in the data set, the effect of SF and SP was unclear.New techniques, such as ML-based modeling and SHAP analysis, will aid the building industry by fostering the advancement of fast and economical ways of determining material properties and the impact of raw ingredients.This research aimed to employ experimental data to develop machine learning (ML)-based models to evaluate the compressive strength (CS) and flexural strength (FS) of cement mortar (CM) that contained waste glass powder (WGP). Two types of ensemble ML approaches, including gradient boosting regressor (GBR) and random forest regressor (RFR), were used to forecast the CS and FS. Moreover, SHapley Additive ExPlanations (SHAP) analysis was carried out to study the impact of raw ingredients on the strength of CM. This research reached the following conclusions:This study employed data for which experimental work was performed in a controlled environment (laboratory). It is suggested that in future studies, actual on-site conditions, such as humidity, temperature, curing, etc., need to be incorporated during the modeling phase to examine their impact on the material’s strength.


The slow dynamic response of a proton exchange membrane fuel cell (PEMFC) to high load change during deficit periods must be considered. Therefore, integrating the hybrid system with energy storage devices like battery storage and/or a supercapacitor is necessary. To reduce the consumed hydrogen, an energy management strategy (EMS) based on the white shark optimizer (WSO) for photovoltaic/PEMFC/lithium-ion batteries/supercapacitors microgrid has been developed. The EMSs distribute the load demand among the photovoltaic, PEMFC, lithium-ion batteries, and supercapacitors. The design of EMSs must be such that it minimizes the use of hydrogen while simultaneously ensuring that each energy source performs inside its own parameters. The recommended EMS-based-WSO was evaluated in regard to other EMSs regarding hydrogen fuel consumption and effectiveness. The considered EMSs are state machine control strategy (SMCS), classical external energy maximization strategy (EEMS), and optimized EEMS-based particle swarm optimization (PSO). Thanks to the proposed EEMS-based WSO, hydrogen utilization has been reduced by 34.17%, 29.47%, and 2.1%, respectively, compared with SMCS, EEMS, and PSO. In addition, the efficiency increased by 6.05%, 9.5%, and 0.33%, respectively, compared with SMCS, EEMS, and PSO. Microgrids offer a potential solution for integrating small-scale renewable energy sources and loads along with energy storage systems and other non-renewable sources . Many is○Distributed energy resources (DERs): include traditional generators like Gensets or natural gas generators that mechanically transform fuel into electricity and heat, as well as renewable energy technologies, including solar and wind power, which operate on natural renewable resources.○Energy storage systems (ESSs): electrochemical (batteries), mechanical (flywheels), and thermal (hot water) systems are examples of systems. This energy can originate from renewable overproduction or be charged when energy is cheaper for peak periods.○Loads: the user loads can be classified as industrial, residential, commercial, and electric vehicles (EVs). In addition, the loads can be classified according to their nature as crucial and non-crucial loads or controllable and non-controllable loads.○Monitoring and Control systems: monitoring systems are required in data acquisition and transmission, whereas intelligent controls are implemented to improve electrical efficiency and cost performance by automatically directing supply to the most efficient available source.A microgrid can be customized to meet each customer’s individual needs by mixing various components, offering the best technical and financial options . These sModularity, scalability, energy management, and resource balancing are essential characteristics of a successful microgrid. The DERs can deliver high performance regardless of the site’s conditions using a proper energy management strategy, whether off-grid or on-grid .PEMFC transforms chemical reactions to DC power. It earned great consideration thanks to its simple size, quietness, and fewer effects on the atmosphere. Several applications, such as trains, aircraft, and electric vehicles, have used PEMFC in recent years . HoweverIn the literature, the EMS can be classified into three major categories: rule-based, artificial intelligence, and optimization-based strategies ,12. RuleThe main contribution of this work is proposing, for the first time, an efficient EMS based on white shark optimizer (WSO) for photovoltaic/PEMFC/lithium-ion batteries/supercapacitors (PV/PEMFC/BSs/SCs) microgrid. The two critical aspects are minimizing hydrogen consumption and improving the hybrids’ system performance. To prove the superiority of the proposed strategy, three EMSs are considered: state machine control strategy (SMCS), classical methodology for maximizing external power supply (EEMS), and optimized EEMS-based particle swarm optimization (PSO).The description of the different components of the hybrid PV/PEMFC/BSs/SCs system is presented in This part deals with the description and modeling of the hybrid renewable energy system component from a photovoltaic array, fuel cell, battery storage, and supercapacitor. The photovoltaic array generates and injects variable energy into the load under different meteorological conditions. Due to its low electricity production, SCs are employed to maintain and absorb oscillating power struggles as well as transient/fluctuating system changes. In addition to having a very large number of cycles with excellent results and no deterioration, SCs are efficient in extremely quick charging and discharges . The batA single-diode electrical model is shown in shR and sR represent shunt and series resistances, respectively. n is the ideality factor, I0 is the saturation current, and thV is the thermal voltage given by the following relation:q seems to be the electron’s charge, cT is the temperature of the cell, and k is the Boltzmann constant.Tc and rT are the experimental and benchmark temperatures, α is the temperature coefficient, and G is the solar radiation. SCI is the short circuit current in A. In sum, considering series and parallel panels, the current produced by the PV array can be estimated as follows:outV is the voltage and outI is the current of the photovoltaic array, respectively. SN and PN are the number of series and parallel cells connected in photovoltaic arrays.The photocurrent is represented as:ocU, intrinsic resistances, and analogous capacitor values are the three basic elements that make up the model , p1, p2, and u are calculated according to the following equations:Movement speed towards prey. When a white shark recognizes the location of prey reliant on the waves created by the prey’s activity, it approaches in the following way:a and b represent one-dimensional binary vectors, f is the frequency of the wavy motion, high and low are the upper and lower random search boundaries, and mv is described as:a0 and a1 are constants.Movement towards optimal prey. After they presumably detect the waves caused by the target’s movement or when they see the target’s movements or smell the fragrance of the prey, white sharks continually travel toward their prey. The prey either escapes or leaves its location to search for food. However, its scent in that position is still there. Accordingly, the white shark updates its position as follows:a0 and a1 are constants.Movement towards the white shark: this phase can be modeled as:r1, r2, and r3 represent the random values ranging in , and D expresses the distance between the target and the shark.Movement towards the white shark: this phase can be modeled as:Fish school behavior: The formula for this phase is provided as follows:The main procedure of WSO is provided in t = 100 s. Throughout this time, the energy generated by the PV increases to contribute to load-shaving while the excess electricity is used to charge the battery and SC. Likewise, when the PV power has a value, the PEMFC power is zero. At t = 250 s, when the battery and SC are simultaneously in the charging mode, the PV is shut off, and the PEMFC returns to share a large amount of load power.The suggested optimized EEMS-based WSO is used to minimize the consumed hydrogen of a hybrid power system shown in A comparison between different EMSs is presented in A new energy management strategy (EMS) using the white shark optimizer technique (WSO) has been proposed to optimally distribute the load demand between the sources in a hybrid PV/PEMFC/BSs/SCs microgrid. The optimized EMS aims to minimize the consumed hydrogen consumption of PEMFC. The optimized EMS avoids the defects of the conventional approach for maximizing external energy (EEMS). The improved EEMS-based WSO is evaluated to EEMS, state machine control (SMCS), and particle swarm optimization (PSO). Two main factors are considered, hydrogen fuel consumption and efficiency. The results reveal that the improved EEMS-based WSO was preferable. Hydrogen consumption has been reduced by 34.17%, 29.47%, and 2.1%, respectively, compared with SMCS, EEMS, and PSO. In addition, the efficiency has been increased by 6.05%, 9.5%, and 0.33%, respectively, compared with SMCS, EEMS, and PSO.6.


The practice of physical activity during adolescence is essential for the proper development of the population. In recent decades, the relevance of physical activity has been increasing, due to the development of the “fat but fit” paradigm. This paradigm shows that adolescents with a high level of physical fitness are healthier than adolescents with poorer physical fitness, regardless of their weight, giving importance to sports practice over other aspects. However, few previous studies have analyzed the differences in physical and body composition between active and sedentary adolescents in this paradigm. For this reason, the objectives of the present study were to establish the differences in body composition, physical performance, and adherence to the Mediterranean diet between active and sedentary adolescents; and to analyze the differences between active and sedentary adolescents according to the “fat but fit” paradigm. The sample consisted of 791 adolescent whose body composition, level of physical activity, adherence to the Mediterranean diet, and physical fitness were measured. It was found significant between active and sedentary adolescents in most of the anthropometric, AMD, and physical fitness variables, with a significant effect of the covariates gender, age, BMI, and biological maturation on the model. The binary logistic regression analysis performed shows that anthropometric variables, AMD, and VO2 max can be considered as primary outcomes to distinguish between active and sedentary groups of adolescents. Furthermore, the results showed that the active adolescents, regardless of their weight status, had lower fat mass and greater muscle mass, as well as a higher performance in the physical fitness tests, and greater adherence to the Mediterranean diet than the sedentary adolescents. To conclude, the practice of physical activity is a determinant for the improvement of body composition, physical performance, and adherence to the Mediterranean diet of the adolescent population, regardless of their gender, age, weight, or maturity status. The practice of physical activity during adolescence is fundamental for the prevention and treatment of different chronic diseases , among wUnfortunately, the reasons why the adolescent population has decreased the practice of physical activity and adherence to certain healthy habits are very diverse. Among them, the barriers found for the practice of physical activity, among which fatigue, obligations, lack of time, and environment/facilities stand out ; the COVTherefore, the practice of physical activity during adolescence is necessary due to the benefits in physical condition and body composition, with previous research finding improvements in muscle mass and decreases in fat percentage with the practice of daily physical activity, as well as improvements in physical fitness . PhysicaAlthough scientific research conducted to date has demonstrated the importance of the practice of physical activity for adolescents, few studies have analyzed the differences between active and sedentary adolescents, and also have limitations that make it difficult to extrapolate the results to adolescents aged 12–16 years old, such as the use of different methodologies to measure the study variables; the small sample size; the different age ranges; or the inclusion of a disparate number of adolescent boys and girls, or adolescents of only one sex .Regarding the “fat but fit” paradox, few studies have been carried out in adolescents, and these are observational studies that have used cardiorespiratory fitness or handgrip strength as variables to determine physical fitness ,23. HoweTherefore, there is a gap in the scientific literature because no previous research has considered the level of physical activity as a variable to determine which adolescents are fit and how this relates to the rest of the health-related variables. Therefore, further scientific research is needed to include the level of physical activity as a discriminating variable, since it provides a great deal of information in this regard and will make it possible to determine the differences between adolescents who are truly active and those who are sedentary. In addition, the limitations found in previous research conducted with adolescents with respect to methodological rigor, non-validated instruments, and reduced samples will be addressed. For these reasons, the objectives of the present study were (a) to establish the differences in body composition, physical performance, and AMD between active and sedentary adolescents; and (b) to analyze the differences between active and sedentary adolescents according to the “fat but fit” paradigm considering different weight status.Based on the results of previous research, two hypotheses are put forward for the present investigation: (a) active adolescents will show better body composition, physical fitness, and AMD than sedentary adolescents; and (b) considering the “fat but fit” paradigm, and in line with previous research conducted with cardiorespiratory fitness and handgrip strength as discriminatory variables, adolescents who show a higher level of physical activity will present higher physical fitness and also better body composition, regardless of their weight status.The present study was cross-sectional, with non-probability convenience sampling. Prior to the start of the study, the institutional ethics committee reviewed and approved the protocol designed in accordance with the World Medical Association code (CE022102). The measurement protocol was registered before the start of the study at ClinicalTrials.gov (code: NCT04860128). The research design and the development of the manuscript also followed the STROBE statement . The samSample size was calculated using Rstudio 3.15.0 statistical software  and using standard deviations (SD) from previous research that examined physical activity level (SD = 0.58)  of adoleThe final sample consisted of 791 adolescents (404 boys and 387 girls) between the ages of 12 and 16 (mean age: 14.39 ± 1.26 years). Of the total sample, 348 adolescents were active, of whom 226 were boys and 122 girls; while 443 adolescents were sedentary, of whom 186 were boys and 257 girls. The average score (from a minimum score of 1 to a maximum score of 5) of physical activity performed was 2.63 ± 0.67 .In order to obtain a representative sample of the urban areas of Region of Murcia (Spain) and in accordance with the data collected by the Regional Statistics Centre of Murcia , which mAll adolescents who participated in the research met the following inclusion criteria: (a) age between 12 and 16 years old; (b) attending compulsory secondary education; (c) not presenting any incapacitating disease that prevented participation; and (d) completing all the questionnaires and physical tests in their entirety.For data collection, tests were selected that had been previously validated in the adolescent population and used in previous studies. To obtain the level of physical activity of the adolescents, the PAQ-A was used, which had been previously validated in Spanish. It had an intraclass correlation coefficient of 0.71 for the final score of the questionnaire . This quThe “Mediterranean Diet Quality Index for children and adolescents” (KIDMED) questionnaire  was usedThe body composition analysis was performed by three accredited International Society for the Advancement of Kinanthropometry (ISAK) anthropometrists . Three basic measurements , three skinfolds , and five girths  were measured according to the protocol standardized by the International Society for the Advancement of Kinanthropometry (ISAK) .The variables were measured twice, with a third measurement being necessary when the difference between the first two measurements was greater than 5% for the skinfolds and 1% in the rest of the measurements. The mean of the measured values, when two measurements were performed, and the median of the values, when three measurements were performed, were used as the final value . All meaTo measure girths, an inextensible tape, Lufkin W606PM , with a 0.1 cm accuracy was used; a skinfold caliper  with an accuracy of 0. 2 mm was used for measuring skinfolds; for body mass, a TANITA BC 418-MA Segmental  with an accuracy of 100 g; and for height and sitting height an SECA stadiometer 213  with an accuracy of 0.1 cm was used. All the instruments were previously calibrated.The intra- and inter-evaluator technical error of measurements (TEM) were calculated in a sub-sample. The intra-evaluator TEM was 0.02% for the basic measurements; 1.21% for skinfolds, and 0.04% for the girths; and the inter-evaluator TEM was 0.03% for the basic measurements; 1.98% for skinfolds and 0.06% for the girths.The final values of the anthropometric measurements were used to calculate the BMI, fat mass (%) , muscle 2 = 0.92–0.89 in the case of boys and an R2 = 0.91–0.88 in the case of girls [The sex-specific formula from Mirwald et al.  was usedof girls .Regarding physical condition, the sit-and-reach test was used to measure hamstring flexibility  Figure . The parThe handgrip strength has been shown to be a valid test to measure musculoskeletal fitness in adolescents  Figure . ConsideThe 20 m sprint indicated the minimum possible time taken by the subject to cover the indicated distance . For itsThe countermovement jump (CMJ) test was used to evaluate the explosive power of the lower limbs through the height of the jump . This teThe 20 m shuttle run  is an inThe physical fitness tests were carried out in the selected high schools, using the class hour belonging to the physical education session and taking advantage of the covered sports pavilions to reduce the polluting variables of the environment as much as possible. All tests were performed on the same day.For data collection, a protocol was established in which the adolescents first completed questionnaires on their level of physical activity and nutritional habits. Subsequently, anthropometric measurements were taken to determine body composition by three accredited ISAK anthropometrists. Next, the sit-and-reach test was performed before the warm-up because previous research has reported the influence of warm-up on sit-and-reach performance in adolescents . Once thThe order of the tests was selected according to the recommendations of the National Strength and Conditioning Association (NSCA), which bases its recommendation on the fatigue generated by the different tests, as well as the metabolic pathways required by each of them .2) was used to calculate the effect size and was defined as: small: ES ≥ 0.10; moderate: ES ≥ 0.30; large: ≥1.2; or very large: ES ≥ 2.0, with an error of p < 0.05 [p < 0.05 was set to determine statistical significance. The statistical analysis was performed with the SPSS statistical package .The distribution of the data was initially evaluated using the Kolmogorov–Smirnov normality test, with all the variables having a normal distribution and allowing statistical analyses based on parametric tests. Descriptive statistics were used to find the mean values and standard deviation. A one-factor ANCOVA was performed to analyze the differences between physically active and sedentary adolescents, with gender, age, BMI, and biological maturation as covariates in the model. A binary logistic regression analysis was used to determine the primary outcomes for establishing differences between active and sedentary adolescents. A MANOVA analysis was performed to establish the differences based on the two independent variables physical activity practice and BMI between sedentary normal weight, sedentary over-weight, sedentary under-weight, active normal weight, active over-weight, and active under-weight adolescents in all analyzed variables. Bonferroni’s pairwise comparison was used for variables that were statistically significant. Partial eta squared  and coefficient of variation (CV) were calculated for the fitness tests that were performed twice. The results were: handgrip strength right arm: ICC = 0.940, CV = 3.14%; handgrip strength left arm: ICC = 0.953, CV = 3.10%; CMJ: ICC = 0.892, CV = 3.35%; and 20 m sprint: ICC = 0.913, CV = 2.15%.p = 0.019–<0.001) in most of the anthropometric, AMD, and physical fitness variables, with a significant effect of the covariates gender, age, BMI, and biological maturation (p = 0.039 < 0.001) on the model. Specifically, according to the basic measurements, only height showed significant differences between active and sedentary adolescents (p = 0.019), with active adolescents being taller than sedentary adolescents, with a small effect size. Most of the anthropometric variables showed significant differences (p < 0.001), with fat mass and sum of three skinfolds being higher in sedentary adolescents, while muscle mass, corrected girths, and waist–hip ratio higher in active adolescents, with a small effect size. Additionally, the nutritional habits showed significant differences (p < 0.001), with AMD being higher in active adolescents, with a small effect size. Regarding physical fitness variables, significant differences were found in all variables (p < 0.001), with active adolescents showing the greatest cardiorespiratory fitness, strength, speed, and jump height, with a small effect size.The results of the comparison between active and sedentary adolescents in the variables analyzed, and the main effect of the covariates, can be found in p = 0.210) and hip girth (p = 0.691); the covariate age showed main effects in all variables (p < 0.001–0.002), except in the waist–height ratio (p = 0.247); the covariate BMI showed main effects in all variables (p < 0.001), except in the sit-and-reach test (p = 0.395); and the covariate biological maturation showed main effects in all variables (p < 0.001–0.039) except in body mass (p = 0.233), height (p = 0.068), and BMI (p = 0.101).The covariate gender showed main effects in all variables (<0.001), except in BMI (p = 0.017), BMI (p = 0.019), muscle mass (p = 0.018), hip girth (0.024), waist–hip ratio (p = 0.017), waist–height ratio (p = 0.050), AMD (p < 0.001), and VO2 max. (p < 0.001) can be considered as primary outcomes to distinguish between active and sedentary groups of adolescents.n = 253), sedentary over-weight (n = 64), sedentary under-weight (n = 87), active normal weight (n = 212), active over-weight (n = 48), and active under-weight adolescents (n = 78) (p < 0.001–0.041). The pairwise comparison between sedentary normal weight–sedentary overweight–sedentary underweight showed significant differences in all variables analyzed except for height (p = 0.136–0.340), AMD (p = 0.316–0.599), and the sit-and-reach test (p = 0.173–0.475). Sedentary overweight adolescents showed higher values for all basic measurements and anthropometric variables than normal weight and underweight adolescents (p < 0.001). Regarding physical fitness variables, this group obtained the highest values in handgrip strength, but their performance was significantly lower in cardiorespiratory fitness, jump height, and 20 m sprint (p < 0.001–0.038).p < 0.001). Significant differences were also observed in handgrip strength, with normal weight adolescents showing higher values (p < 0.001), but no significant differences were found in the rest of the physical fitness variables.Between sedentary normal weight and underweight adolescents, the normal weight adolescents presented higher values in body mass and anthropometric variables (p < 0.001–0.007). Regarding the physical fitness variables, active underweight adolescents showed significantly higher VO2 max values compared to active overweight ones (p = 0.024); handgrip strength was higher in active overweight than in active normal weight (p = 0.002–0.005) and active underweight (p < 0.001), as well as higher in active normal weight than in active underweight (p < 0.001). Lastly, active normal weight showed greater sit-and-reach distance than active underweight (p = 0.006), and greater jump height than active overweight (p = 0.013).Similarly, the differences between active normal weight–active overweight–active underweight adolescents were significant in all variables except for AMD and 20 m sprint. Significantly higher values were found in active overweight adolescents compared to active normal weight and active underweight in all anthropometric variables (p < 0.001–0.030), with sedentary adolescents showing higher values for fat mass and sum of three skinfolds, while active adolescents showed more muscle mass, corrected girths, waist girth, and waist–hip ratio. AMD was significantly higher in active adolescents (p < 0.001). With respect to the physical condition variables, the active adolescents showed higher performance in all the tests (p < 0.001–0.001), except for the sit-and-reach test, in which no significant differences were observed (p = 0.995).When comparing the results obtained for sedentary normal weight and active normal weight, the differences were significant in all the anthropometric variables (p < 0.001–0.034). Active overweight adolescents showed better performance in all physical fitness tests (p < 0.001–0.041), except for the sit-and-reach test, where no significant differences were found (p = 0.898).The differences were also significant in sedentary and active overweight adolescents. In this case, sedentary adolescents had higher levels of fat mass and sum of three skinfolds, while active adolescents had more muscle mass and corrected thigh and calf girth (p = 0.006–0.038). AMD and performance in the physical fitness tests were higher in the active adolescents (p < 0.001–0.039), except for the sit-and-reach test, where no significant differences were found (p = 0.262).Regarding active and sedentary underweight adolescents, the differences were significant in fat mass, muscle mass, and waist–hip ratio, with active adolescents having higher muscle mass and waist–hip ratio (The main objectives of the present investigation were (a) to establish the differences in body composition, physical performance, and AMD between active and sedentary adolescents; and (b) to analyze the differences between active and sedentary adolescents according to the “fat but fit” paradigm considering different weight statuses. Based on the results of previous research, the following hypotheses were put forward: (a) active adolescents will show better body composition, physical fitness, and AMD than sedentary adolescents; and (b) adolescents who show a higher level of physical activity will present higher physical fitness and better body composition, independently of their weight status. A significant difference was found between active and sedentary adolescents in most of the anthropometric, AMD, and physical fitness variables, with a significant effect of the covariates gender, age, BMI, and biological maturation on the model. The binary logistic regression analysis performed shows that the variables body mass, BMI, muscle mass, hip girth, waist-to-hip ratio, waist-to-height ratio, AMD, and VO2 max can be considered as primary outcomes to distinguish between active and sedentary groups of adolescents, and special attention should be paid to the differences in these variables. When comparing the differences between groups according to physical activity and BMI, it was found that, in general, at the same level of physical activity, adolescents with higher BMI showed higher values for anthropometric variables and worse values in the physical fitness tests. On the other hand, at the same BMI, sedentary adolescents generally showed higher values for anthropometric variables and worse values in the physical fitness tests and the AMD.According to the first objective of the present study, to establish the differences in body composition, physical performance, and AMD between active and sedentary adolescents, the results obtained showed that active adolescents had lower values of fat mass and sum of skinfolds, and higher values of height, muscle mass, corrected girths, and waist–hip ratio. In fact, body mass and BMI, muscle mass, hip girth, waist-to-hip ratio, and waist-to-height ratio were found as primary outcomes to distinguish between active and sedentary groups. Previous studies have also found that active adolescents presented higher values of muscle mass and lower values of fat mass, as compared to sedentary adolescents ,9,19, whSurprisingly, the present study also found that active adolescents were taller than sedentary adolescents. Only one previous study has analyzed the difference in height between active and sedentary subjects and found no difference between them . HoweverHowever, the fact that significant differences between active and sedentary adolescents were found in the present study may be because adolescents who are taller in their age range could practice physical activity for a longer period of time than those who are shorter. This could be due to the fact that early maturation, the development of physical capacities, and height, are determining factors for sports performance ,62, and AMD was also shown to be higher in active adolescents and a primary outcome to distinguish between those who are active and sedentary. Previous studies have suggested that there may be a link between healthy physical activity habits and nutritional habits ,71. ThisRegarding the physical condition variables, upper and lower limb strength, sprint speed, and cardiorespiratory fitness, were higher in active adolescents, while the distance reached in the sit-and-reach test showed no significant differences with respect to sedentary adolescents. Scientific evidence has highlighted an association between higher physical activity practice and an increase in physical fitness levels ,74. ThisThe gender covariate showed main effects in all variables analyzed, except in BMI and hip girth. Previous studies have already pointed out that males tend to show lower values for anthropometric variables related to adiposity and higher values for variables related to muscle development  than femThe inclusion of the covariate age showed significant differences in all variables analyzed, except for the waist–height ratio. Previous studies have found that older adolescents presented higher scores in physical fitness tests, greater muscle development, greater AMD, and higher levels of fat mass than the youngest ,86. ThisThe BMI covariate also showed significant differences in all variables, except for the sit-and-reach score. These results are not surprising and are in agreement with those found in previous research in which adolescents with higher BMI scores had higher levels of fat mass and muscle mass , as wellOn the inclusion of the covariate biological maturation, it was found that it had a significant effect on the differences found between the sedentary and active adolescents in all anthropometric and physical variables and AMD, except for the variables body mass, height, and BMI. Previous studies have already pointed to the influence of maturation on anthropometric and derived variables and physical performance among males ,65. MoreThe second objective of the present investigation was to analyze the differences between active and sedentary adolescents according to the “fat but fit” paradigm considering different weight status. When comparing the groups of active and sedentary adolescents with normal weight, the differences were significant in the variables of fat and muscle mass, performance in physical fitness tests, and AMD, with the active adolescents obtaining greater values in all variables. Similar results were found when comparing active and sedentary overweight and underweight adolescents, except for AMD, in which overweight adolescents showed no differences according to the level of physical activity practiced. Paying special attention to the group of overweight/obese adolescents, previous studies have found that active adolescents show better physical performance and lower body fat than sedentary adolescents despite being overweight, giving rise to the so-called “fat but fit” paradigm . HoweverRegarding the comparison of overweight, normal weight, and underweight sedentary subjects, as well as overweight, normal weight, and underweight active subjects, the results in the sedentary and active adolescent groups showed higher values in overweight adolescents in the anthropometric variables as compared to normal weight and underweight adolescents. In addition, overweight adolescents presented lower scores in physical fitness tests, except for hand grip strength, in both the active and sedentary adolescent groups, when compared to normal weight and underweight adolescents. Previous research has also shown that overweight adolescents showed lower scores in jump height, cardiorespiratory fitness, and speed tests, but higher scores in handgrip strength, than normo- and underweight adolescents ,95. An eNotably, in underweight active adolescents, the handgrip strength score was significantly lower compared to overweight and normal weight adolescents, while VO2 max was significantly higher than that of overweight active subjects. Previous data has shown that underweight adolescents had better cardiorespiratory fitness than overweight adolescents , while oRegarding the practical implications of this research, the practice of physical activity during adolescence is essential for an adequate development of body composition, physical capacities, and AMD. In view of the current curriculum and the reduced hours of school physical activity in Spain, the main solution is to give more importance to the subject of physical education within the framework of compulsory education, by increasing the number of hours of physical education in the Spanish educational curriculum, but also by carrying out programs to raise awareness among all those involved in the educational process  of its importance and influence on the future health of adolescents. As a secondary solution, greater importance should be given to the promotion of out-of-school physical activity, increasing the weekly hours of practice, and facilitating access to practice by adolescents, encouraging them to be active for longer each day. These strategies should place special emphasis on overweight and obese adolescents, since they are less active, and the health benefits obtained would be similar to those of adolescents with a better weight status.The present study is not free of limitations. Since this was a cross-sectional design, it was not possible to establish a causal relationship between the variables analyzed. The sample was selected by convenience in the educational centers that could be accessed. Another possible limitation could be the selection of the questionnaire chosen to classify the subjects into active and sedentary, since, although it had been previously validated in a sample of Spanish adolescents, showing adequate validity and reliability for measuring physical activity , the resConsidering the results obtained in the present research, it can be concluded that active adolescents have lower fat mass, higher values of muscle mass and height, greater AMD, greater strength, speed, and cardiorespiratory fitness than sedentary adolescents. Body mass, BMI, muscle mass, hip girth, waist-to-hip ratio, waist-to-height ratio, AMD, and VO2 max were considered as primary outcomes to distinguish between active and sedentary groups of adolescents The comparison between adolescents with different weight status showed higher results in anthropometric variables and lower performance in physical fitness tests, except for handgrip strength, in overweight or obese adolescents, regardless of whether they are active or sedentary. In addition, the more active adolescents within the same weight status group had greater muscle mass, physical performance, and AMD diet than the more sedentary adolescents, in accordance with the “fat but fit” paradigm.


Associations between serum cadmium and diabetes had been reported in previous studies, however there was still considerable controversy regarding associations. Studies in general population that investigated the effects of serum cadmium on diabetes were currently lacking. We designed this cross-sectional study among U.S. adults under high and low cadmium exposure to assess associations between serum cadmium and diabetes.This cross-sectional study analyzed 52,593 adults who aged more than 20 years and participated in the National Health and Nutrition Examination Survey (NHANES), 1999–2020. The missing values and extreme values in the covariables were filled by multiple interpolation. Univariate logistics regression, multivariate logistics regression and smooth fitting curves were used to analyze the association between serum cadmium and diabetes. Simultaneously, sensitivity analysis was carried out by converting the serum cadmium from continuous variable to categorical variable. The stratification logistics regression model was used to analyze whether there were special groups in each subgroup to test the stability of the results.P = 0.007). There was no association between serum cadmium level and the occurrence of diabetes in the high serum cadmium exposure group . These results were consistent across all the subgroups (P for interaction >0.05).In this cross-sectional study, serum cadmium levels were negatively correlated with the occurrence of diabetes in the low serum cadmium exposure group (OR = 0.811, 95% CI 0.698, 0.943; Serum cadmium was negatively associated diabetes among the representative samples of the whole population in the United States under the normal level of serum cadmium exposure. However, there was no association between serum cadmium level and the occurrence of diabetes in the high serum cadmium exposure group. This study promoted an update of new preventative strategy targeting environment for the prevention and control of diabetes in the future. Cadmium is a widespread industrial and environmental pollutant . Routes With the development of economy, diabetes has gradually become one of the major non-communicable diseases endangering the health of people all over the world –18. AccoThe pathogenic factors of diabetes are multifactorial, in addition to the traditional risk factors of diabetes, such as genetic susceptibility, abdominal obesity, unhealthy diet and lifestyle and so on –24, variTherefore, in our study we aimed to investigate if cadmium exposure was associated with diabetes in general adults and determine if the association presented in a dose-response manner under different levels of cadmium exposure.The National Health and Nutritional Health Survey (NHANES) is an extensive cross-sectional survey conducted nationwide. It is an extensive multiagency program designed to monitor adults' and children's the health and nutritional status across the United States . The surThe data set consisted of demoinformatics, body measurement, laboratory, and questionnaire data. In this study, the data set of 11 cycles (1999–2020) in the NHANES database of the National Center for Health of the United States were selected . Meanwhihttps://www.cdc.gov/nchs/nhanes/index.htm), and other places have similar reports.More information from NHANES can inquire on the website ; (2) Participants who did not undergo serum cadmium testing (n = 11720); (3) Participants who lacked diagnostic data for diabetes (n = 4). Finally, 52,593 participants were enrolled. 31,967 participants were assigned to the low cadmium exposure group and 20,626 to the high cadmium exposure group  participants younger than 20 years of age , anthropometry , health-related behaviors , and biochemical indicators . Basic information was collected immediately by investigators, and biochemical samples were stored and managed scientifically and sent to the Laboratory Science Division of the National Center for Environmental Health of the Centers for Disease Control and Prevention , the Laboratory of the University of Minnesota and the University of Missouri-Columbia for testing and analysis.Professional personnel collected blood samples during the physical examination and froze at −20°C after collection. Blood samples were sent to the Laboratory Science Division of the National Center for Environmental Health, Centers for Disease Control and Prevention  for analysis and treatment. The collected and stored materials for metal analysis were pre-screened for background contamination prior to analysis. Serum cadmium was analyzed using a Perkin Elmer SIMAA 6000 instrument. In addition, the quantitative detection of cadmium is based on the measurement of light absorbed at 228.8 and 283.3 nm, respectively by ground state atoms of cadmium from an electroless discharge lamp (EDL) or hollow cathode lamp (HCL) source.The diagnosis of diabetes is made in combination with guidelines issued by the International Diabetes Association (IDM) and the clinical criteria currently in use. Diabetes can be determined if it meets any of the following criteria: (1) participants with fasting blood glucose ≥7.0 mmol/L in laboratory tests; (2) Participants with blood glucose >11.1 mmol/L in OGTT experiment; (3) Participants who were taking diabetes medications; (4) Participants who were diagnosed with diabetes by their doctors during the survey; (5) Participants who self-reported being diagnosed with diabetes.2); Height was measured using electronic Sports Measurements with an accuracy of millimeters. Weight was measured by researchers using a digital Scale and converted pounds to kilograms when the measurement was complete. WC was measured using electronic Sports Measurements with an accuracy of millimeters. TG, ALT, GGT, LDH and other biochemical measurements were analyzed by the University of Minnesota laboratory and the University of Missouri-Columbia. All experimental biochemical data were analyzed under quality control. NHANES Quality Control and Quality Assurance Protocols (QA/QC) meet the requirements of the Clinical Laboratory Improvement Act 1988. Detailed QA/QC instructions are discussed in the NHANES LPM. For detailed instructions on quality assurance and quality control procedures, please refer to the NHANES website.In NHANES, some sociodemographic information is collected by structured data. Here, participants comprised three categories according to their level of education. The lower level of education: education level below grade 11, and secondary education: high school graduate or equivalent and people with higher education: college or higher education. Participants were also divided into three groups according whether they smoked or not. Participants were considered current smokers if they had smoked 100 or more cigarettes in the past and reported smoking several days or daily at the time of the interview. Participants who had smoked fewer than 100 cigarettes in the past but did not currently smoke were considered former smokers, and participants who had fewer than 100 cigarettes in their past were considered nonsmokers. Alcohol consumption is based on the 2015–2020 Dietary Guidelines for Americans issued by the U.S. Departments of Health and Human Services and Agriculture. Male drinkers were defined as had more than two drinks per day, and female drinkers had more than one drink per day. The racial breakdown was based on the time of the survey: Mexican Americans, non-Hispanic whites, non-Hispanic blacks, other Hispanics, and other races. Among the participants, the diagnosis of hypertension was based on the ISH2020 International Hypertension Practice Guidelines published by International Society of Hypertension (ISH) and commonly used clinical criteria : (1) parT-test based on distribution normality. P < 0.05 was considered statistically significant. Univariate logistics and multivariate logistics regression were used to analyze the association between serum cadmium and diabetes. The selection of covariates in multi-factor logistics regression is based on the variables reported in previous relevant literature, variables that affect the outcome in international expert consensus, variables that change the target dependent variable by more than 10% in single-factor analysis and our relevant clinical experience. The included covariables are as follows: age, sex, race, education, BMI, WC, smoking, alcohol consumption, hypertension, HDL, TG, ALT, GGT, LDH, and ALB. In this study, the missing values and extreme values in the covariables are filled by multiple interpolations. In addition, sensitivity analysis was performed to observe significant differences between the newly generated dataset and the original dataset. However, these studies revealed no significant difference (P >0.05). Therefore, according to Rubin's criterion, Our multivariate analysis results are based on the data set after multiple interpolations. Four logistics regression models and smooth fitting curves are constructed in this study. The trend test was carried out by converting the serum cadmium from a continuous variable to a categorical variable. Smooth curve fitting analyses based on logistic regression models of continuous serum cadmium to assess the shape of associations between serum cadmium and diabetes . The mean age of participants was 50.0 ± 18.1 years, and the mean age of the high serum cadmium exposure group was slightly higher than that of the low serum cadmium exposure group (53.6 ± 17.8 vs. 47.7 ± 18.0 years). There were also significant differences between the high and low serum cadmium exposure groups in ethnic education, hypertension, smoking and alcohol consumption (P < 0.001). Compared with the low serum cadmium exposure group, BMI (28.1 ± 6.5 vs. 29.7 ± 7.0 kg/m2), WC (97.3 ±15.6 vs. 100.1 ± 16.3 cm) and ALT [19.0  vs. 21.0  mmol/L] were lower in the high exposure group, GGT [21.0  vs. 20.0  mmol/L], LDH [136.0  vs. 134.0  mmol/L] and serum cadmium  vs. 2.1  mmol/L) levels were higher. In addition, there were significant differences in the distribution of HDL, TG and ALB levels between the two groups (P < 0.001) , Female: 27,245 (51.8%)], there were 31,967 in the low serum cadmium exposure group , 20,626 in the high serum cadmium exposure group . There was significant difference in gender distribution between the two groups (< 0.001) .P > 0.05).Univariate logistics analysis was used for observation of the associations between age, sex, race, education level, BMI, WC, smoking, alcohol consumption, biochemical indicators and the incidence of diabetes before and after multiple interpolation in the US population. In the low serum cadmium exposure group, the associations between variables and diabetes were represented in P = 0.735). There was no difference in the incidence of diabetes among ethnic groups. Among different levels of education, with low level of education as the reference, the incidence of diabetes was lower in those with medium level of education [OR: 0.637 ] and high level of education [OR: 0.565 ]. Compared with non-smokers, former smokers were more likely to develop diabetes, with an OR and 95% CI of 1.49 , respectively. Non-alcoholic participants were more likely to develop diabetes than those who consumed alcohol [OR: 2.078 ]. Meanwhile, we found that BMI, WC and some biochemical indicators, including TG, GGT and LDH, were positively correlated with the occurrence of diabetes; HDL and ALB were negatively correlated with the occurrence of diabetes; ALT level and serum cadmium were not correlated with the occurrence of diabetes (P > 0.05).In the group with high serum cadmium exposure, the association between variables and diabetes was shown in P > 0.05) (P for trend < 0.05). This indicated that there was a stable and negative correlation between serum cadmium level and the occurrence of diabetes  . Supplemdiabetes . In the P for non-linearity was >0.001, indicating a gradual decrease in the rate of diabetes with increased serum cadmium. In the high cadmium exposure group, the association between serum cadmium level and diabetes was linear with monotonicity and transverse axis parallel, and P for non-linearity was >0.001, which indicates that the occurrence of diabetes was not modified by serum cadmium level . The study population was divided into different subgroups according to age, gender, race, BMI, hypertension, smoking and alcohol consumption in subgroup analysis. In these subgroups, the association was stable with no special population being found, meaning that the finding could be generalized to the population. In addition, taking serum cadmium as a categorical variable, we explored the trend of the association between serum cadmium and diabetes, and we got similar conclusions, which further supported our conclusions.The present study used data for adults from 11 cycles of NHANES (1999–2020) to explore the association between serum cadmium levels and diabetes. According to the level of serum cadmium of candidates, the study population was divided into low cadmium exposure group and high cadmium exposure group, and it was demonstrated that the association between cadmium and diabetes was not consistent at different exposure levels. After adjusting for potential confounding, there was a negative association between serum cadmium levels and diabetes. The effect value OR and 95% CI were 0.811 , respectively. No association between serum cadmium levels and diabetes was observed in the high cadmium exposure group (n = 876) showed cadmium was significantly negatively associated with diabetes when only adjusted age and sex in participants from the HUNT3 Survey  observed blood cadmium was positively related to prediabetes, whereas no association was observed between blood cadmium and diabetes. In a Swedish cohort study , Borne et al. Found that elevated blood cadmium levels are not associated with increased incidence of diabetes. A cross-sectional study . Nonetheless, taken these studies together, there would be many limitations these studies, such as the sample sizes differ from different studies. There are also differences in the study population. Since the prevalence of diabetes varies among different races, the baseline of each study population and covariates adjusted are different. Moreover, the association is not explored under different exposure levels of serum cadmium. All of limitations above would not be likely to provide sufficient power to demonstrate cadmium exposure effects on diabetes. Since research on the general population about cadmium exposure to diabetes relatively limited, it's of great significance to supplement research in general population in Americ. Based on summarizing the limitations and bias of previous studies, we designed the study and analyzed associations in a high levels of exposure population and low levels exposure population, therefore our study is different from the previous studies.Amounting studies have been performed to explore the association between serum cadmium levels and diabetes, whereas the results are inconsistent and contradictory. Some epidemiological studies suggested that cadmium exposure may be related higher diabetes risk, one cycle of the U.S. population study (NHANES 1988-1994), Schwartz et al. found the prevalence of diabetes in participants positively associated with urinary cadmium levels . One rec3 Survey . A small3 Survey  conducteal study  also shoIn the present study, we did not observe significant association between serum cadmium and diabetes in high exposure population, which was consistent with the results from previous epidemiological studies , 32. HowSpecial mention should be made of the result that serum cadmium levels were negatively associated with the occurrence of diabetes in the low serum cadmium exposure group, the incidence of diabetes decreased with the increase of serum cadmium level at values under 3.2 mmol/L. As far as we know, the mechanisms involved are not well defined. We speculated that cadmium might play a physiological role at low levels somewhat, although it has not yet been discovered. Cadmium is chemically similar to zinc since they belong to group 12 of the periodic table and both elements are divalent d-block elements . PreviouIt is undeniable that there are several limitations to the present study. Firstly, this study is a cross-sectional study, affected by the inherent defects of the study itself, and causal conclusions are unwarranted. Concerning this, it will be essential to conduct a well-designed cohort study. In addition, in order to explore the association between serum cadmium and diabetes in the general population, this study did not include the special population such as children and pregnant, in the future study, we will try to bring into particular population for analysis. Additionally, due to the limitation of questionnaire information collection and other factors, the study failed to effectively distinguish people with diabetes into type 1 and type 2 diabetes. However, among US adults with diagnosed diabetes, type 1 and type 2 diabetes accounted for 5.6 and 91.2% , respectBased on the perspective of general population exposure to the environment, our results suggested that under the normal level of serum cadmium exposure, there was a negative association between serum cadmium and diabetes among the representative samples of the whole population in the United States, which layed a solid foundation for environmental scientists and clinical scientists to study the association between cadmium exposure and diabetes in the future. In addition, it is with great potential in practice. However, there was no association between serum cadmium level and the occurrence of diabetes in the high serum cadmium exposure group. Future research using multicenter and prospective cohort study designs would still need to verify these results.https://www.cdc.gov/nchs/nhanes/).Publicly available datasets were analyzed in this study. This data can be found here: All datasets can be downloaded in NHANES website . All information from the NHANES program is available and free for public, so the agreement of the medical ethics committee board was not necessary.RG and YW conceived the idea. RG wrote the manuscript. YW and ZC collected, read the literature, and revised the article. ZC collected and collated the data needed for this article. ZC and JD read through and corrected the manuscript. All authors read and approved the final manuscript.


Mycoplasma agalactiae , is a very important disease in dairy sheep. It is distributed worldwide, and causes a marked drop or even complete loss of milk production, arthritis, keratoconjunctivitis, pneumonia, and septicemia. The current study represents the first investigation evaluating the synergistic effect of combining Staphylococcus aureus (S. aureus) within the M. agalactiae vaccine. Apart from the previously known benefits of combined vaccines, such as reduced production costs, time and effort saving, simplifying the immunization schedule, and minimizing the stress of multiple vaccinations, the current study recorded for the first time that the involvement of S. aureus in inactivated vaccines against M. agalactiae elicited a higher antibody response against M. agalactiae, detected by ELISA, than the monovalent M. agalactiae vaccine. The humoral immune response and hematological parameters were significantly improved and manifested by the increased antibody titre, total leukocytic count, neutrophils, and blood platelets. Moreover, the local glandular immunity of the udder, assessed by the somatic cell count (SCC), was enhanced.Contagious agalactia (CA), caused by Mycoplasma agalactiae (Ma)-Staphylococcus aureus (Sa) vaccine (Ma–Sa) against the Ma monovalent vaccine in ewes. Twelve primiparous Ma-free ewes were randomly grouped into three equal groups: first, the control group injected with placebo, second, the group vaccinated with the Ma monovalent vaccine, and third, the group vaccinated with Ma–Sa combined vaccine, with two S/C doses at 45-day intervals. The animals were examined for serological, hematological, and somatic cell count (SCC) changes for 17 successive weeks. A significant increase in anti-Ma antibody mean titers, leukocytes, and platelets was observed in the vaccinated animals, with the highest values in those who received the combined vaccine. Neutrophils were high only in the animals who received the combined vaccine. SCC was lower in the vaccinated animals during the first six weeks. This study concludes that the combined Ma–Sa vaccines enhance immune response and potentiate its efficacy against Ma. This improvement might be attributed to the sensitization/activation effect of S. aureus on platelets, which are recoded to act as a key regulator for the coordination of all components of the innate immune system. Even though this study included a small number of animals, its findings about the potentialities of this inactivated vaccine in the control of CA are strongly encouraging. Further confirmation might be needed through additional replicates and a challenge study is needed before proceeding with widespread use.In Italy, dairy sheep farming represents a vital agro-industry sector, but it is still challenged by contagious agalactia (CA), which is endemic there, and vaccination is the most economical and sustainable tool for control. This study aimed to evaluate the combined  Global sheep and goat milk production has more than doubled during the last decades . In ItalContagious agalactia (CA) is an important disease of small ruminants, causing a marked drop or even complete loss of milk production. According to the World Organization for Animal Health , CA is a notifiable disease  and is gClinical outcomes of CA infection are not restricted to mammary glands, and are gathered under the acronym MAKePS, which stands for mastitis, arthritis, keratoconjunctivitis, pneumonia, and septicemia . It can Mycoplasma agalactiae (Ma) is reported to be the main causative pathogen for CA; however, Mycoplasma capricolum subsp. capricolum, Mycoplasma mycoides subsp. capri, and Mycoplasma putrefaciens have been found to cause a sporadic clinically similar syndrome, particularly in goats [Ma is considered to be the main etiological agent of CA, which primarily affects sheep and goats along with other wild species. The main sources of Ma infection include milk, ocular, nasal, and auricular secretion, as well as through urine and feces [in goats ,15,16. Mnd feces . The incnd feces . CA is cConfirmation of CA can be obtained by isolating the causative mycoplasma. As isolation can take up to 2–3 weeks, PCR offers advantages in terms of time, specificity, and sensitivity. In addition, commercial ELISA kits have been described for serological detection .M. agalactiae is considered the dominant pathogen causing CA [In Sicily, Sardinia, and many Mediterranean basin countries, using CA ,18,19,20Control of CA relies on vaccines, treatment with anti-microbials, and appropriate herd management practices , but vacIn Italy, where CA is endemic, disease control is based on vaccination, anti-microbial treatment, and statutory measures, including quarantine of the infected herds. Unfortunately, antibiotics are not very effective because many of the anti-microbials used are often bacteriostatic rather than bactericidal; however, fluoroquinolones have been shown to be good in vitro, but are discouraged due to their high cost and the risk for the induction of resistance in bacterial pathogens into animal origin food chains . Thus, vMa for the control of CA [Some assays were carried out about in preparation for safe and effective vaccines against ol of CA ,24. Liveol of CA ,21,25, bol of CA ,19.A combination of bacterial and/or viral vaccines containing multiple antigens has many benefits for manufacturers, as it reduces production costs; for administrators, as it saves time and efforts as well as simplifies the immunization schedule; and for the animals, as it minimizes the stress of multiple vaccinations .The effectiveness of a vaccine to prevent disease depends on the potentiality/efficiency of the vaccine and is indicated by the development of a specific humoral immune response . SeroconMa than the traditional monovalent ones? The study is designed to assess whether, and to what extent and how, the combination of another pathogen (in our study S. aureus) in inactivated Ma vaccines could influence the developed humoral immunity, proportion of leukocyte subpopulations, hematological parameters, and SCC in lactating ewes.The main scope of the present study is to try to answer a pressing question: does a bivalent vaccine elicit more immunity/protection against All of the procedures involving animal were in accordance with the international guidelines for care and handling of experimental animals and were approved by the internal Ethic Committee for Animal Experiment in Istituto Zooprofilattico Sperimentale della Sicilia , agreement no. 540/2019-PR (Resp. a Prot. 28875.31) issued on 07/23/2019, pursuant to Article 31 of Legislative Decree 26/2014. The methods were performed by approved staff members. The animals were handled with good clinical practices and efforts were made to minimize suffering.M. agalactiae-free dairy herd composed of 200 heads reared in a semi-intensive production system. The M. agalactiae free status was verified by procedures suggested by the OIE manual [M. agalactiae antibodies using the ELISA test. Milk samples and nasal and auricular swabs from these animals were collected and analyzed by real-time PCR before starting the experiment. All of the samples were negative for Ma DNA. The animals were fed with a complete balanced diet and water ad libitum during the acclimatization and experimental periods, and were randomly divided into three groups in a separate paddock, each containing four ewes. First group was the unvaccinated control group and received the placebo , the second group was subjected to the monovalent M. agalactiae inactivated vaccine, and the third group was injected with the M. agalactiae–S. aureus (Ma–Sa) bivalent (combined) inactivated vaccine. Animals were vaccinated through subcutaneous injection  with two doses of corresponding vaccine for each group at a 45-day interval (T0 and T1). As a result of unexpected snowfall  causing a drastic and sudden drop in temperature, the booster was administered after 45 days according to Nickerson et al. [Twelve Valle del Belìce primiparous ewes, two years of age and in the same lactation stage, were selected from a E manual . The anin et al. , in ordeThe animals were observed and examined daily for clinical signs. Clinical scoring was based on the general behavior, food intake, abnormal local, and systemic reactions, including inflammation at the injection site and nasal discharge. The rectal temperature was recorded for each animal two days prior to vaccination and at the time of vaccination, and daily up to 14 days post vaccination (DPV). The site of vaccine inoculation was monitored for local adverse reactions. All of the animals were examined once a week for 17 successive weeks. Blood  as an anti-coagulant and one without) and milk samples were collected weekly from all of the ewes.Ma and Sa were isolated from previous outbreaks in Sicily dairy sheep farms near this farm, and were confirmed by molecular identification.The farm (autogenous) vaccine was produced by the vaccine laboratory at the Istituto Zooprofilattico Sperimentale della Sicilia in Palermo, Italy. The vaccine was prepared according to the guidelines governing the production of animal husbandry vaccines of veterinary interest . Both Ma and Sa were grown in separate flasks.For vaccine preparation, bacterial strains of Ma was cultivated for 96 h at 37 °C in a microaerophile in Modified Hayflick Mycoplasma medium using PPLO broth base and was enriched with 20% of inactive equine serum [Briefly, ne serum .S. aureus was cultured in TSB culture broth for 24 h at 37 °C under stirring.g for 1 h and resuspended in PBS, pH 7.6, until reaching a titration of 109 CFU/mL. The bacterial suspensions were then inactivated with 5% phenol for 24 h at 37 °C with stirring. The inactivated suspensions were adsorbed under constant and mechanical agitation for three hours at room temperature with aluminum hydroxide in a final concentration of 15%.Both bacterial cultures were centrifuged at 3800× 9 CFU/mL.For the bivalent formulations, equal proportions of bacteria were added to constitute one volume (500 mL) of the bivalent vaccine at a final concentration of 10Sterility and safety tests were then carried out according to the current legislation . The vaccines were stored at 4 °C during the experimental period.Ma with a commercial indirect enzyme-linked immunoassay (ELISA) method  [Rz value was calculated for each sample using the following Formula (1):At the beginning of this study, the sera from all of the animals were collected from the jugular vein in a vacuum tube and were analyzed for the presence of specific antibodies against PRA, SA) . The assRz ≤ 1.0) are negative samples, (1.5 ≤ Rz > 1.0) are suspicious samples, and (Rz > 1.5) are positive samples. Meanwhile, milk samples were proven to be negative for M. agalactiae by Rt-PCR.(Ma antibodies.Upon administration of the first dose of vaccine (T0 time) and for 17 successive weeks, the sera samples were collected from vaccinated and control sheep and analyzed for detection and the configuration of a concentration curve of anti-Blood samples, collected in vacutainer tubes containing EDTA, were rolled gently several times to ensure anticoagulant mixing, and were processed immediately for hematological analysis for complete blood counts with a differential cell count. Analysis was performed using the Abbott Cell-Dyn 3700 Hematology Analyzer using species-specific software for ovine samples and following the manufacturer instructions.Milk samples, preserved in 0.05% potassium dichromate, were transferred to the laboratory and analyzed within 24 h for SCC using an automated counter  .p-value < 0.05 considered significant. When significant, post hoc tests were performed using the Dunn nonparametric multiple comparisons test adjusted with Bonferroni correction using the FSA R (v 0.9.1.) package [Data were presented as means ± standard deviation of the mean. The Kruskal–Wallis nonparametric one-way ANOVA was used to test the difference between groups, with a  package .No local or systemic reaction was observed in the animals injected during the study period.Ma antibody detection by ELISA revealed a significant improvement in the humoral immune response in vaccinated animals. Here, all animals were free of antibodies against M. agalactiae at day 0 (the day of the first inoculation), and upon vaccination, the animals received both kinds of vaccines and showed seroconversion with increased antibody titer means. The level of Ab was increased after the first dose, and its peak occurred at around the 15th day then declined. After a booster dose on the 45th day (T1), Ab re-increased and reached its peak in both the monovalent and bi-valent vaccines at around 70th day before declining. Statistical analysis of the Rz value (representative of Ab titer) revealed a significant difference between the vaccinated and non-vaccinated animals , with higher levels in the group that received the bivalent vaccine, although the difference between the vaccinated groups was not significant. The differential cell count showed a prominent increase in the neutrophil count in the animals that received the bivalent vaccine only, with a significant difference compared with the other two groups. There was no significant difference between the means of the lymphocytes, monocytes, and eosinophils among the three groups . For Hb, there was slight decrease in the monovalent vaccinated animals , while the means of the HTC did not show any significant difference among the three groups. Only the platelets showed an obvious and significant increase in the animals that received bi-valent vaccine compared with the other two groups  vaccines potentiated an immune response against Ma more than the Ma monovalent vaccines, with a similar antigenic concentration.It is clearly demonstrated that combined  usually complements the physical examination, it essentially supports diagnostic investigations and overall health management strategies in ruminants . We lookThe total leukocytes and neutrophils were obviously higher in the vaccinated animals than the control ones, and the highest level was recorded in the animals that received the bi-valent vaccine. However, the total leukocyte count and distribution of granulocytes, monocytes, and lymphocytes remained within a normal range throughout the study in all of the animals. This indicated minimal systemic inflammatory responses to the multiple vaccines or to the method of administration. Only RBCs and HCT were slightly lower than the minimum physiological range in all of the groups, which might be attributed to the stress induced by first lactation or mineral deficiency.Neutrophils, the most common polymorphonuclear leukocytes (PMNs) and found to be increased in this study, play a crucial role in innate immunity against infections . It is nPlatelets were prominently increased in the animals that received a bi-valent vaccine compared with the other two groups in the current study. There is an increasing focus on platelets as key regulators of the immune system. Platelets interact directly with pathogen-associated molecular patterns (PAMPs) ,66. TheyRecently, platelets were reported to play a key role in the coordination of all components of the innate immune system, producing an initial response in their own right and interacting with myeloid, lymphoid, and humoral components of the initial response to infection .Streptococcus pyogenes, S. aureus, Candida species, and Aspergillus spp., through specific virulence factors that target platelets [Some pathogens have been shown to interact with platelets directly, such as latelets ,72,73,74Salmonella Newport SRP vaccine significantly decreased SCC at 30 to 60 days of lactation [S. aureus vaccine in dairy Buffalo using different protocols. The authors recorded lowering in SCC in vaccinated animals compared with the control non-vaccinated animals [Finally, as SCC is considered from many aspects as an indicator of udder health ,76,77, wactation . Other s animals ,83. On t animals ,85,86.S. aureus with M. agalactiae enhances immune stimulation and prove that the Ma–Sa combined vaccine is more potent for stimulating the immune system than a separate Ma vaccine. The reason for this is that it still needs to be identified whether this was due to more antigenic stimuli or directly attributed to S. aureus, as some previous literature reported that S. aureus harbors virulence factors that target and activate platelets. Even though this study included a small number of animals, its findings about the potentialities of this inactivated vaccine in the control of CA are strongly encouraging. This might need further confirmation through additional replicates and further study is needed before proceeding with widespread use.The findings of this study indicate that combining S. aureus in an inactivated M. agalactiae vaccine and its impact on stimulating elicited Ab. The use of an inactivated combined vaccine was associated with a more enforced immune response in animals compared with the single inactivated M. agalactiae  vaccine. The results proved a significant improvement in humoral response and hematological parameters, manifested by an increased Ab titer, total leukocyte count, neutrophils, and blood platelets. This might be attributed to the activation effect of S. aureus on platelets, which is recoded to act as a key regulator for the coordination of all components of the innate immune system, producing an initial response and interacting with other components of the initial response to infection. Moreover, the local glandular immunity of the udder, assessed by SCC, was enhanced.The current study represents the first investigation evaluating the synergistic effect of combining