Physico-chemical changes of the native and the pretreated sustainable wastes were evaluated by compositional analysis, scanning electron microscopy (SEM), X-ray diffractometry (XRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA). These investigations showed major structural changes after the optimized sequential pretreatment. This pretreatment not only influences the delignification process, but also affects the functionalization of cellulose chemical structure. NZ released a higher glucose concentration (328.8 and 996.8 mg/dl) than that of ZnCl2 (Z), which released 203.8 and 846.8 mg/dl from CS and TP, respectively. This work led to the production of about 500 mg/dl of ethanol, which is promising and a competitor to other studies. These findings contribute to increasing the versatility in the reuse of agricultural and agro-industrial wastes to promote interaction areas of pollution prevention, industrialization, and clean energy production, to attain the keys of sustainable development goals.Improper lignocellulosic waste disposal causes severe environmental pollution and health damage. Corn Stover (CS), agricultural, and aseptic packaging, Tetra Pak (TP) cartons, agro-industrial, are two examples of sustainable wastes that are rich in carbohydrate materials and may be used to produce valuable by-products. In addition, attempts were made to enhance cellulose fractionation and improve enzymatic saccharification. In this regard, these two wastes were efficiently employed as substrates for bioethanol production. This research demonstrates the effect of disodium hydrogen phosphate (Na Shockingly, a growing developing populace and innovative advancements have led to an increment in solid wastes. Agricultural wastes such as rice straw, wheat straw, and corn stover are attractive to be used as a lignocellulosic feedstock for biofuel production instead of traditional disposal by transportation to landfills, incineration, and composting .Corn Stover (CS) is one of the lignocellulosic materials that have high productivity, local availability, and almost no cost. The global annual corn production is about 1 billion tons . Two-thiIn another way, Tetra Pak (TP), as an example of agro-industrial wastes, multi-layer poly-coated paperboards named after their first and largest manufacturer, is widely used as aseptic packages for beverages such as milk and juice . It is cAs a result, utilization of biomass resources and solid wastes based on the agricultural  and agro-industrial  wastes for developing biomass-derived biofuels to address the shortage of fossil resources has become imperative.Lignocellulosic biomass is used for second-generation biofuel production that has several positive impacts on three fundamental pivots: (1) the economic pivot, as it is sustainable, increases investment in plant and equipment, leads to agricultural development, increases the number of rural manufacturing jobs, and reduces the dependency on imported fuels; (2) the energy security pivot, as it is renewable, available, and reduces the use of fossil fuels; and (3), the environmental pivot, as it is biodegradable, improves land and water use, leads to high combustion efficiency, reduces greenhouse gases (GHG), and consequently reduces air pollution .Lignocellulosic biomass is composed of approximately 38–50% cellulose, 23–32% hemicellulose, and 15–25% lignin . This st2 [Many strategies of lignocellulose pretreatment including carboxylic acid treatment, ammonia fiber explosion, microbial delignification, steam explosions, ionic liquid, organosolvent, alkali pretreatment, acid pretreatment, ozonolysis, subcritical water, and supercritical CO2 ,12 have 2 . Inorgan3PO4 × 12H2O, Na2CO3, Na2S and Na2CO3.1.5H2O2 [3PO4 has a greater ability to extract lignin from lignocellulosic biomass than Na2CO3. Other types of metal salts such as sulfates, phosphates, and chlorides are reported in lignocellulosic pretreatment [2, ZnCl2, and FeCl3 on the pretreatment of Miscanthus straw were investigated and proved that while FeCl3 removed 100% of the xylan, ZnCl2 released a larger glucose yield (90%) compared to FeCl3 (55%) [Inorganic salts can be classified into alkalic  or metal.1.5H2O2 ,16,17. T.1.5H2O2 ,19,20. Q.1.5H2O2  found threatment ,22,23. Tl3 (55%) .2 (Z), and the combined Na2HPO4 –ZnCl2 (NZ) in presence of autoclaving for bioethanol production has been conducted. Accordingly, the feasibility of the pretreatment using these salts was evaluated for two kinds of wastes; one is an example of agricultural waste, Corn Stover, and the other is an example of agro-industrial waste, Tetra Pak. To provide more information about the physico-chemical changes that occurred through these pretreatment processes, the compositional structure, crystallinity, functional groups, and surface morphology of untreated and pretreated CS and TP have been compared. Moreover, their effect on glucose production yields in subsequent enzymatic hydrolysis has been investigated. Consequently, their effect on bioethanol production yield was investigated as well. To date, scarce applications have been proposed for the pretreatment using a combination of alkalic and metal salts for pretreatment of agriculture and/or agro-industrial wastes . Indeed,2 as a transition metal salt to produce CSZ and TPZ, respectively, and alkalic and metal salt (Na2HPO4 and ZnCl2) to produce CSNZ and TPNZ, respectively, with the assistance of autoclave to break the TP and CS complex structure. The effect of these salts on the physico-chemical properties, the enzymatic hydrolysis, and further bioethanol production has been investigated.Lignin and hemicellulose, present in the plant cell wall to cover and protect the cellulose, obstructs the cellulose fractionation, and hinders the enzymatic hydrolysis that converts the cellulose to glucose, which consequently leads to the production of bioethanol by further processing. Hence, in this work, the CS and TP were pretreated using different salts: ZnCl2HPO4-ZnCl2 led to higher solid recovery, lignin removal, and cellulose recovery than the pretreatment using ZnCl2 only for the two substrates. The solid recovery in the case of TPNZ and TPZ samples was higher than the solid recovery in the case of CSNZ and CSZ, which may be related to the higher lignin and hemicellulose content in the CS, which are dissolved and leads to a lower solid recovery. The recovery of cellulose fraction was higher than 90% for TP and CS substrates. This means that the pretreatment using Na2HPO4-ZnCl2 is safer and more protective of cellulose, which indicates high selective solubilization. The lignin removal was between 31.2 and 37% in all samples, except in the case of the TPNZ sample (67.1%), which may be related to the lignin fiber weakness due to the industrial processing of the T substrate which facilitated the lignin dissolution and revealed the effectiveness of the Na2HPO4–ZnCl2 pretreatment.The chemical composition  of TP, CS, and their pretreated samples  are analyzed and listed in 2HPO4-ZnCl2), in addition to the nature of raw material (TP is better than CS). The higher lignin content in CSZ and CSNZ than TPZ and TPNZ may be the reason for the higher cellulose protection, lower cellulose fractionation, and lower glucose yield [The efficiency of the pretreatment process was reflected in the enzymatic hydrolysis, which was conducted using CS, TP, and their pre-treated samples . The delse yield .Generally, the improvement in the produced glucose after pretreatment may be related to the low lignin content, which implies exposure of a higher number of active sites and the 1-beta glucoside bonds of the cellulose to the enzymes . These r2, respectively. This improvement can be explained by one of the possible mechanisms of the cellulose fractionation/transformation and can subsequently enhance the enzymatic hydrolysis. Firstly, zinc salts make the crystalline cellulose of CS and TP more swollen and easier to degrade by the action of the enzyme [2 acts as a Lewis acid that can activate specific functional groups and cleave the C–O bond during the depolymerization process, especially the glycosidic connections within lignocellulosic structures [As shown in e enzyme ; secondlructures ; finallyructures .2HPO4 with ZnCl2 for pretreatment of CS and TP enhanced the enzymatic hydrolysis by 9.75 and 1.73 times compared with untreated CS and TP, respectively. This improvement is a result of the dual action of Na2HPO4 with ZnCl2. Moreover, this pretreatment exhibited higher improvement during the enzymatic hydrolysis for the two substrates due to its high buffering capacity which encourages the formation of acidic compounds including acetic acids from hemicelluloses and organic acids from lignin, which lead to the destruction of lignin and facilitates enzyme accessibility [2 and Na2HPO4 can boost bioethanol production from the raw substrate, as shown in 2 and Na2HPO4 was clearly confirmed when compared to the literature [On the other hand, combining Nasibility . The sacterature ,31,32,332HPO4 -glycosidic linkages between glucose and cellulose, C1–H deformation with ring vibration, C–C stretching, and C–O–C, which are the cellulose characteristics peaks for pyranose ring skeletal vibration [2 and PO3 phosphate–carbon complexes [−1 have appeared in the TPNZ and CSNZ samples, and these bands are related to the presence of the PO4−3 group, which indicates successful functionalization [2, indicating that it is a non-derivative solvent. The Z and NZ pretreatments decreased the aromatic content and increased the oxygen functional groups, which revealed the high delignification efficiency, which might significantly boost the number of active sites on the surface and improve the enzymatic hydrolysis.The samples showed the broad band at 3323 cmellulose ,36. Howeg groups . The pear lignin ,39. It il groups ,41. Taki samples ,43. This samples . The banestroyed . After tr lignin . This peibration . In TPNZlization . The spe2 with CS than TP. From our previous work, the original crystal structure of CS and TP was destroyed by phosphate groups during the NZ pretreatment, and it appeared as amorphous without any crystalline peaks as a result of reducing the number of the intermolecular hydrogen-bonding networks of cellulose during the oxidation process [2HPO4, which could depict the successful functionalization without lowering the crystalline cellulose content, as proved in the FTIR analysis results in 2+ and cellulose molecules that lead to rapid depolymerization of cellulose during the pretreatment [The changes in the microstructure of TP, CS, and Z and NZ pretreated samples have a strong influence on the physicochemical characteristics that were analyzed by XRD. As shown in  process . The peareatment . In addireatment .2, the TPZ decomposes mainly in one step, like TP, but at a lower temperature  is narrower in TPNZ than in TP or TPZ samples, indicating a more heterogeneous distribution of surface groups. The second carbonization step is associated with the reduction of phosphate groups by the organic cellulose, which increases the cellulose gasification in this temperature range. The char residue amount of TP, TPZ, and TPNZ were 6.96, 11.04, and 25.79%, respectively, which meant TPNZ is the highest thermal stability attributable for the phosphate groups. The maximum decomposition temperature of TP, TPZ, and TPNZ was 344, 361, and 299 °C, respectively. The Tmax is related to the degradation of glucose rings. The Tmax of TPNZ is lower than that of TP and TPZ, which means that the thermal stability of TPNZ was inferior to that of TP and TPZ as a result of the introduction of phosphate groups, lower crystallinity, higher cellulose content, and lower lignin content [Due to the significant physico-chemical properties and subsequent enzymatic hydrolysis of TP samples when compared to C samples, we aimed to study the stability and organic polymer decomposition of TP, TPZ, and TPNZ, to assess the possibility for various applications; this was explored using the thermogravimetric analysis (TGA) technique, as shown in perature a. This lw 300 °C . After c2+) in the pretreatment of CS and TP elucidate that Zn ions have been dissolved as Lewis acid, resulting in stronger interaction between the good electron acceptors, Zn2+, and the electron donor sites of oxygen parts of TP or CS and their derivatives, without loss of protons from hydroxyl groups of the ligand, leading to the significant weakening or rupture of C-O-C, C-O, and CH2OH bonds in the polymeric components of TP and CS, facilitating their breakage, consequently reducing the recalcitrance of CS and TP by fragmentation of lignin [2 participate as nucleophiles, yielding D-glucose [2SO4 under the same conditions and same pH [As observed in SEM , after pf lignin . In deta-glucose . Kim et -glucose . The act same pH .2 and its combination with Na2HPO4 on the pretreatment of CS and TP, the respective experiments were carried out under the same conditions. NZ leads to a better effect of total glucose content than that of Z  were collected from the local farms in Beheira Governorate, Egypt, while Tetra Pak (TP) packages were collected from milk and juice sources, obtained from local companies in Egypt. Then, CS was chopped into small pieces and TP was cut into approximately 10 mm × 10 mm pieces, washed with distilled water to remove dust, and dried at 60 °C for two days until a constant weight was obtained.The dried samples were then milled in a ball mill  at 400 rpm speed for 20 min with a 95:1 ball to powder mass ratio. The produced powder was screened using  and the particles size < 250 μm was selected. The screened CS and TP were kept in tightly closed plastic bags at room temperature till usage.2  solution with a 3% (w/v) solid to liquid concentration ratio. These mixtures were autoclaved under the pressure of 310 kPa at 120 °C for 60 min using a Tuttnaur autoclave-steam sterilizer . After pretreatment, the mixtures were filtered, washed with hot distilled water till neutralization, and dried at 50 °C for 12 h till a constant weight was obtained. These neutralized powders were kept in tightly sealed plastic bags for characterization, enzymatic hydrolysis, and further processing, and labeled as CSZ and TPZ for corn stover and Tetra Pak, respectively.Ten grams of CS and TP each were suspended in ZnCl2 method, through a two-stage process. The first stage is the same as that previously mentioned in 2HPO4 instead of ZnCl2. Then, the produced pretreated dried powder was subjected to pretreatment using ZnCl2  with an enzyme dosage of 0.4 gm/gm substrate. The enzymatic hydrolysis was performed in 50 mL flasks covered by aluminum foil, incubated at 50 °C and 100 rpm for four days, the period in which a stable concentration of glucose was reached. The liberated glucose was estimated every day using a glucose kit . The optimum enzyme dosage was subjected to CS, TP, and their pretreated samples, CSZ, TPZ, CSNZ, and TPNZ to compare the glucose yield produced after and before the pretreatment, to estimate the enzymatic hydrolysis enhancement before the pretreatment process. The released glucose yield was estimated spectrophotometrically 2SO4, 0.5 gm MgSO4, and 1 gm yeast extract containing 4% glucose by utilizing 5% yeast inoculum. Then the cultures were anaerobically fermented in tightly sealed flasks; the residual glucose was determined by using the Miller DNS method [After yeast isolation  value of the yeast suspension was measured at 600 nm with a spectrophotometer.2 (Z) and combined Na2HPO4 and ZnCl2 (NZ) as catalysts were evaluated for improving enzymatic saccharification and consequently boosting the bioethanol production. Compositional analysis, FT-IR, SEM, XRD, and TGA revealed major structural changes after pretreatment. A combined pretreatment was systematically explored with respect to the impact of NZ pretreatment on glucose yield. The functionalization of cellulose with phosphorus and/or oxygen-containing surface groups leads to the boosting of sequential pretreatment for enhancing enzymatic saccharification of TPZ, TPNZ, CSZ, and CSNZ, and subsequently improving bioethanol production. It was also shown that the thermal stability of the pretreated TPNZ was largely improved compared to that of unmodified TP or pretreated TPZ. The outstanding enzymatic hydrolysis can be attributed to the heterogeneous surface chemistry composed mainly of oxygenated and phosphate functional groups. These findings are of great importance and clearly indicate that pretreated TPNZ represents the excellent adaptability for the pretreatment of lignocellulosic materials.This current research investigates renewable energy production for solving the problems of energy shortage that meet the United Nations Sustainable Development Goals (UNSDGs). For the first time, to the best knowledge of the authors, this effort offers a new method to produce the functionalized cellulosic materials by pretreatment of Corn Stover (CS), as agricultural waste, and Tetra Pak (TP), as an agro-industrial sustainable waste. The novel sequential pretreatment using ZnCl


Mathematical models of lactation curves are functions that describe milk production on each day of lactation. These models are able to predict milk yields as well as provide valuable information applicable in breeding and management decisions. The aim of the present study was to examine different shapes of lactation curves for milk traits  modelled by the Wilmink function and by linear or squared functions between 306 and 400 days in milk (DIM). The results suggested that the course of extended lactations could be modelled by a nonlinear model, for example, the Wilmink function, for up to 305 DIM, and the linear or squared function could be more appropriate afterwards.The objectives of this study were (1) to examine different shapes of lactation curves for milk, fat, protein and lactose yields and urea content in milk fitted by the Wilmink function using the test-day (TD) records and (2) to find the function that best describes test-day records beyond 305 days in milk (DIM) for Polish Holstein–Friesian cows. The data were 6,955,768 TD records from the 702,830 first six lactations of 284,193 Polish Holstein–Friesian cows. Cows calved in 19,102 herds between 2001 and 2018. The following functions were fitted to TD data from each lactation: (1) Wilmink model fitted to the whole lactation, (2) Wilmink model fitted to TD records from 5 to 305 DIM and linear function fitted to TD records from 306 to 400 DIM, (3) Wilmink model fitted to TD records from 5 to 305 DIM and squared function fitted to TD records from 306 to 400 DIM. The present study showed that urea content in milk was modelled slightly worse than other milk traits. The results suggested that the course of lactation could be successfully modelled by a nonlinear model, for example, the Wilmink function, for up to 305 DIM, and by the linear or squared function afterwards. Mathematical models of lactation curves are functions that describe milk production on each day of lactation. These models are able to predict milk yields as well as provide valuable information that is applicable in breeding and management decisions. They could be used for many practical purposes such as health monitoring, individual feeding, genetic evaluation, determining optimum strategies for artificial insemination and replacement of dairy cows ,2.Mathematical modelling has been often used in the analyses of test-day data in dairy cattle ,5,6,7,8.The functions used for modelling milk yield during lactation can also be applied to illustrate changes of fat and protein yields or other milk constituents across lactation ,15. QuinIn the last two decades, a tendency for extending the length of lactations of dairy cows beyond 305 days in milk has been observed in many countries ,7,19,20.We hypothesize that the course of lactation, both for milk yield and milk constituents, can be modelled by nonlinear models until 305 DIM, and the linear or quadratic (squared) functions might be used for modelling lactation shape beyond 305 DIM. Therefore, the objectives of this study were (1) to examine different shapes of whole lactation curves in Polish Holstein–Friesian cows when the Wilmink function was fitted to test-day milk, fat, protein and lactose yields and urea content in milk, and (2) to find the function that best describes test-day records beyond 305 days in milk.The data were 6,955,768 test-day (TD) records from the 702,830 first six lactations of 284,193 Polish Holstein–Friesian cows registered in the Polish national recording system (SYMLEK). The data were made available by the Polish Federation of Cattle Breeders and Dairy Farmers. Records included five traits, i.e., TD milk, fat, protein and lactose yield, and milk urea content. There were less than 1% TD records in which only milk yield was available. There were 4–16 TD records per lactation per cow in the data file. Cows were calved in 19,102 herds in the years from 2001 to 2018. The following restrictions on data were imposed: TD yields between 5 and 400 DIM, lactations lasting at least 200 days, daily milk yields between 1 and 85 kg, fat content from 1.5 to 9.0%, protein content from 1 to 7% and lactose content from 1.00 to 9.99%.1.The Wilmink  model (Wt   —day in milk (DIM);t.2.Wilmink model (WIL305) fitted to TD records from 5 to 305 DIM in lactation and:(a)Linear function (LIN) fitted to TD records from 306 to 400 DIM in lactation, assuming that at least one TD record beyond 305 DIM occurred. To fit LIN, the last TD record before 305 DIM and all TD records beyond 305 DIM were used;(b)Squared function (SQRT) fitted to TD records from 306 to 400 DIM in lactation. In this case, at least two TD records beyond 305 DIM were required. To fit SQRT, the last TD record before 305 DIM and all TD records beyond 305 DIM were used.Lactation curves were modelled separately for each cow in each of first six lactations. To fit the functions a nonlinear least squares method with the Levenberg–Marquardt algorithm was used. Lactation curves were modelled in Python  with Numa, b, c) of the Wilmink function have biological interpretations related to the shape of the lactation curve: parameter a is associated with the level of production, b with production decrease after peak yield, and c with production increase towards the peak [c) and decreasing (parameter b) phases of lactation. The different shapes of lactation curves were tested based on the information given in The parameters (the peak . The cou1.Mean Error (ME 2.Mean Squared Error (MSE 3.Mean Absolute Error (MAE 4.Pearson’s correlation (R) between the measured  have jointly undertaken a study on the shapes of lactation curves for different milk traits . They found that the lactation curve could be described as a cluster of five curves fitted by one single model. In 19.3% of lactations, the curves for milk, fat and protein yields followed the standard shape, while for fat and protein contents in milk, they had the reversed standard shape . This coNumerous studies indicated that the models suitable to describe standard 305 d lactations were often not adequate to describe extended lactations ,7,31. AlAs expected, the Wilmink function (WIL) used for all TD records available during lactation gave the worse fit than LIN or SQRT functions. According to Druet et al. (2003), the Wilmink model, as a three parametric curve, was not a very flexible function and could give atypical curves when some yields at the end of lactation were particularly high, i.e., outliers . Thus, tThe physiological processes of extended lactations seemed to be different from those of standard, i.e., 305 d lactations. A considerable extension of average lactation length was usually associated with an increased milk yield, greater peak and persistency ,32. AccoAs can be seen from the above, the replacement of many short lactations with fewer longer ones in high-yielding cows may improve the reproduction efficiency, reduce artificial insemination cost, disease incidence and the total number of parturitions. This, in turn, results in lower exposure to a high-risk period associated with calving and may contribute to higher cow longevity ,34,38,39Thus, the knowledge on lactations extended beyond 305 days and ability to model them are indispensable for optimal dairy herd management, especially for making well-informed decisions on cow feeding, health, breeding and replacement ,13,31,32As pointed out by many researchers, the choice of the best lactation model was always a kind of compromise between goodness of fit and other function properties, such as flexibility or robustness as well as computational considerations ,5,13. ThThree mathematical models were compared for accuracy of predicting milk, fat, protein and lactose yields, as well as urea content in milk based on TD records. Milk and lactose yields were best fitted by the used functions. Urea content in milk was modelled with a lower accuracy than other milk traits.The results suggested that the course of lactation could be modelled by a nonlinear model—for example, the Wilmink function, up to 305 DIM, and the linear or squared function were more appropriate afterwards.


High saturated fat diets have been associated with the development of obesity and hypertension, along with other pathologies related to the metabolic syndrome. In contrast, the Mediterranean diet, characterized by its high content of monounsaturated fatty acids, has been proposed as a dietary factor capable of positively regulating cardiovascular function. These effects have been linked to changes in the local renal renin angiotensin system (RAS) and the activity of the sympathetic nervous system. The main goal of this study was to analyze the role of two dietary fat sources on aminopeptidases activities involved in local kidney RAS. Male Wistar rats (six months old) were fed during 24 weeks with three different diets: the standard diet (S), the standard diet supplemented with virgin olive oil (20%) (VOO), or the standard diet enriched with butter (20%) plus cholesterol (0.1%) (Bch). Kidney samples were separated in medulla and cortex for aminopeptidase activities (AP) assay. Urine samples were collected for routine analysis by chemical tests. Aminopeptidase activities were determined by fluorometric methods in soluble (sol) and membrane-bound (mb) fractions of renal tissue, using arylamide derivatives as substrates. After the experimental period, the systolic blood pressure (SBP) values were similar in standard and VOO animals, and significantly lower than in the Bch group. At the same time, a significant increase in GluAP and IRAP activities were found in renal medulla of Bch animals. However, in VOO group the increase of GluAP activity in renal medulla was lower, while AspAP activity decreased in the renal cortex. Furthermore, the VOO diet also affected other aminopeptidase activities, such as TyrAP and pGluAP, related to the regulation of the sympathetic nervous system and the metabolic rate. These results support the beneficial effect of VOO in the regulation of SBP through changes in local AP activities of the kidney. High-fat diets (HFDs) are related to factors that condition the metabolic syndrome, such as the development of obesity and various pathologies such as hypertension, heart disease, stroke, atherosclerosis, diabetes, dyslipidemia, cancer and infertility ,2,3,4,5.Almost all the scientific evidence about a negative effect of fat on health refers to the source of saturated fatty acids and cholesterol. However, these results are not extensive to other types of lipid sources . PreviouRenin angiotensin system is one of the most important hormonal mechanisms involved in hemodynamic stability by regulating blood pressure, fluid balance, and electrolyte concentration. Until relatively recently, angiotensin II (Ang II) was considered the main peptide in the RAS. However, some of its metabolic derivatives, such as angiotensin III (Ang III), angiotensin IV (Ang IV) and angiotensin 2–10 (Ang 2–10), have also been shown to have important physiological functions ,20. The Different local RASs could be affected by changes in the degree of saturation of fat consumed in the diet. Within these local systems, angiotensin peptides are metabolized by various enzymes of the aminopeptidase (AP) family, also called angiotensinases, and previous results of our research group have shown that the activities of these peptidases are affected by the type of fatty acids consumed with the diet ,14,25,26Obesity-related kidney disease is linked to caloric excess promoting deleterious cellular responses. Accumulation of saturated free fatty acids in tubular cells produces lipotoxicity involving significant cellular dysfunction and injury . DietaryStructural changes within the kidney, secondary to obesity, are important since fat deposition around the kidneys, together with increased abdominal pressure secondary to central obesity, has been suggested as an additional cause of disorder in the reabsorption of sodium . SpecifiCatecholamines or adrenergic nerves innervating the kidney directly influence renal tubular function and, therefore, might participate in the regulation of sodium . In the In addition, these kidney disorders can cause internal and external effects that can be reflected in alterations of the levels of thyrotropin-releasing hormone, pGlu-His-Pro-NH2 (TRH). Similar to the liver , the kidThe Mediterranean diet (MD) is characterized by its main fat, virgin olive oil , a natural oil with a high monounsaturated fatty acid (MUFA) content and a lot of bioactive components in its minor fractions. Virgin olive oil has demonstrated an important cardioprotective and antihypertensive role ,46,47,48The results obtained from SBP values indicated that during the first two months no significant differences were observed between the three groups of animals. However, from the third month to the end of the experimental period, a marked increase was observed for the animals that were consuming the Bch diet. Interestingly, there were no differences between the animals fed with S and VOO diets, even when the VOO diet contained a percentage of fat similar to Bch diet. No significant differences were observed for the data of water intake, diuresis and the relation between both values, despite a slight but nonsignificant decrease in the urine excretion (mL/100 g body weight) in the group of rats fed VOO diet . AlthougThe striated texture of the medullary parenchyma is due to the predominance of collecting tubules and uriniferous ducts in the pyramids . The graThe mean values of TyrAP activity in the soluble fraction of the renal medulla were lower with the VOO diet compared to the Bch diet A. In theThe degrading activity of TRH was decreased significantly by the HFDs in the membrane fraction of the renal cortex. However, the VOO diet significantly reduced this activity in the soluble fraction of the renal medulla, achieved statistical significance only compared to Bch diet B.The test strip for urinalysis are in vitro diagnostic dipsticks to determine different parameters allocated in urine, among them: glucose, nitrite, protein, bilirubin, ketone, pH, density, and leukocytes. The results obtained on these test strips were read visually and can supply both semiquantitative and qualitative determination . For nepUrinalysis showed no glucose signal in the samples (data not shown). The determination of protein in urine detected traces within the normal range of albuminuria in both HFDs than in S diet. However, there was a significant interaction in nitrite levels by the dominant diet effect, but there were no differences in nitrite levels between the experimental diets. Compared to control animals, VOO and Bch groups showed a lower ketone and pH value in urine, but within the reference range. The densities (specific gravity) were significantly higher in both HFDs. Bilirubin and leukocytes were significantly lower for VOO diet compared to S diet.A local renin angiotensin system (RAS) has been widely characterized in the kidney. This system acts locally as a paracrine mechanism, regulating both the glomerular flow rate and the excretion of water and electrolytes. Moreover, the components of local RAS are able to reach the peripheral circulation and act as an endocrine system . Renal dTubular epithelial cells synthesize metabolites able to attract inflammatory cells into the renal interstitium ,60. NitrUrine levels of bilirubin were lower in the VOO group, indicative of a decrease in liver heme oxygenase activity (HO). SHR fed an HFD also decreased the bilirubin in urine . The hemHypertensive models fed an HFD increase macrophage infiltration in kidney . Our aniAs indicated previously, the source of fat in the diet has demonstrated to be decisive in the development of metabolic syndrome, obesity and hypertension ,63,64. CThe decrease of AspAP activity in the renal cortex of animals fed with VOO diet could be related to lower levels of Ang 2–10, a vasodilator peptide. However, the GluAP activity is higher in the renal medulla of these animals compared to controls, indicating upper metabolism of Ang II to Ang III, a vasodilator peptide. Taken together, this result indicates a higher flow in the renal medulla, which can have an effect on sodium and water excretion, with a long-term influence on arterial blood pressure regulation. Conversely, in Bch animals the changes in aminopeptidase activity were located only at renal medulla level. The GluAP activity was higher than in control animals, even higher than in the VOO group, indicating a rapid metabolism of Ang II to Ang III. The high metabolism of Ang II to Ang III in renal medulla is consistent with previous studies that showed the importance of this peptide in the physiology of renal medulla . The intThe increase in the activity of GluAP in renal medulla of Bch animals was parallel with an increase in IRAP activity. The insulin regulated aminopeptidase (IRAP) is also the AT4 receptor, which bonds to Ang IV, a peptide release by the metabolism of Ang III. IRAP colocalizes with GLUT4 in specialized vesicles, where it plays a tethering role. In the cells of the inner medulla, IRAP plays a localized role in the regulation of vasopressin bioactivity, and the AQP-2 levels are two-fold higher in IRAP knockout mice .It is well known that during hypertension, Ang II send signals to sympathetic excitatory centers ,79. On tThe dopaminergic system is important in the control of renal function and homeostasis, adapting kidneys to the different physiological or pathological situations, and maintaining the sodium homeostasis, the extracellular volume, and blood pressure values. On the other hand, several strategies for the treatment of hypertension blocked this system that led to renal vasoconstriction . A closeThe enzyme pGluAP is involved in the inactivation of GnRH and TRH . ThyrotrAt present, the possible mechanism that explains the protective role of virgin olive oil on hypertension and renal damage it is not totally explained. This effect could be related to the special fatty acid composition of virgin olive oil (rich in monounsaturated fatty acid) and changes in the cellular membranes composition that could lead to modifications in fluidity and enzyme activities. On the other hand, it is also possible that the protective role could be related to the antioxidant and anti-inflammatory components of the virgin olive oil . Indeed,These results are clinically relevant, because they demonstrated that the inclusion of virgin olive oil in the diet is able to prevent the development of arterial hypertension compared to a source of saturated fatty acids and cholesterol. This effect implicates mechanisms that modify the metabolism of renal angiotensin peptides, and the decrease of the catecholamine-forming precursors.n = 6) group, rats were fed with a commercial chow for laboratory rodents  whose nutritional composition was 16.5% protein, 3% total fat, 60% carbohydrates (nitrogen-free extract (NFE)), 5% minerals, and 4% fiber. The other two diets were HFDs. One group of rats was fed with the S diet supplemented with 20% of virgin olive oil , composed of a total fat content (%) of ω-9-monounsaturated fatty acid  75.5%, saturated fatty acid  11.5%, and ω-6-polyunsaturated fatty acid  7.5%). The second group of rats was fed with the S diet supplemented with 20% butter plus cholesterol (0.1%) , composed of a total fat content (%) of monounsaturated fatty acid (C18:1) 29%, saturated fatty acid (C16:0 y C18:0) 62%, polyunsaturated fatty acid (C16:0) 4%, and short and medium chain fatty acids (C4–C14). The Bch diet was supplemented with cholesterol (0.1%), in order to reach the average cholesterol content of the Western diet. The HFD diets were isocaloric, 1848 KJ/100 g and 1827 KJ/100 g for EVOO and Bch diets, respectively, compared to 1392 KJ/100 g S diet. The water and food intake of each group were measured during the balance periods.Adult male Wistar rats were purchased from Harlan Interfauna Ibérica S.A. . The experiments were approved according to the Institutional Animal Care and Use Committee of the University of Jaén, with code project number P.I.UJA_2005_acción 14 (1 January 2006). Rats had free access to experimental diets and water during 24 weeks, and they were maintained under a controlled temperature (20–25 °C) and humidity (50 ± 5%) environment, in a 12 h light/dark cycle. At the beginning of the study, the mean body weight and age of animals were ±495 g and six months old, respectively. Experimental procedures for animal use and care were in accordance with European Communities Council Directive 2010/63/UE and Spanish regulation RD 53/2013, and the study was approved by the Institutional Animal Care and Use Committee of the University of Jaén. Rats were randomly assigned into three groups: in the standard diet  through the left cardiac ventricle under Equithensin anesthesia (2 mL/kg body weight). The left kidney was dissected, and the samples were immediately placed in liquid nitrogen to separate into two parts , as previously described , and werThe systolic blood pressure (SBP) measurement was performed with the Letica-5000 measurer in unanesthetized animals, using the “tail-cuff” pneumatic plethysmography method as previously described ,90. The Individual metabolism cages were used at the second and sixth experimental month, in order to obtain values of food and water intake, as well as urine excretion for each group. Urine samples were analyzed using a colorimetric reagent strip  for the detection of leukocytes, nitrites, pH, protein, density, glucose, ketones, bilirubin.g for 30 min at 4 °C. The resulting supernatants were used to measure the enzymatic activities corresponding to the soluble fraction, and the protein content. To solubilize the membrane proteins, the pellets were rehomogenized in 10 mM Tris-HCl buffer (pH 7.4) with 1% Triton-X-100, and ultracentrifuged at 100,000× g for 30 min at 4 °C. The supernatants were kept for at least 4 h at 4 °C and shaken with SM-2 biobeads, in order to remove the detergent used to solubilize the membrane proteins. The resulting samples were used to measure the enzymatic activities of the membrane-bound fraction, and the protein content.In order to obtain the soluble fraction, the tissue samples were homogenized with 0.5 mL of 10 mM Tris-HCl buffer (pH 7.4) and ultracentrifuged at 100,000× The enzymatic activities of soluble and membrane-bound fractions of AlaAP, ArgAP, AspAP, IRAP, GluAP, pGluAP and TyrAP, were measured by a fluorimetry assay using as substrates aminoacyl-β-Naphthylamides (aa-β-NA): L-Ala-β-NA, L-Arg-β-NA, L-Asp-β-NA, L-Cys-β-NA, L-Glu-β-NA, L-pGlu-β-NA, and L-Tyr-β-NA, respectively, according to the methods of different authors ,92,93 moFor the quantification of proteins, the method of Bradford , based op-values below 0.05 (p < 0. 05) were considered statistically significant. All data are presented as mean ± standard error of the mean (SEM). Quantitative variables that were meant to be nonparametric univariate statistics, median and interquartile range (IQR) were used.Statistical analysis was performed using one-way ANOVA, followed by Tukey’s post-hoc test for multiple comparisons. When the normality test failed, Kruskal–Wallis One Way Analysis of Variance on Ranks was performed. Significant differences were estimated with Sigmaplot v11.0 software , and In conclusion, this study presents new data regarding the aminopeptidases’ regulation on blood pressure control and local renal RAS. The intake of saturated fat raised systolic blood pressure related to an increase of GluAP, and IRAP activity in renal medulla. However, extra virgin olive oil presents a protective effect on systolic blood pressure, showing a slight increase in GluAP activity in the renal medulla, lower than in Bch diet. Virgin olive oil seems present an indirect effect on the sympathetic system and the metabolic activity in kidney through changes on the TyrAP and pGluAP activities, reducing the release of tyrosine residues necessary for the formation of new catecholamines and the degradation of TRH.


The number of deaths from COVID-19 continues to surge worldwide. In particular, if a patient’s condition is sufficiently severe to require invasive ventilation, it is more likely to lead to death than to recovery.The goal of our study was to analyze the factors related to COVID-19 severity in patients and to develop an artificial intelligence (AI) model to predict the severity of COVID-19 at an early stage.We developed an AI model that predicts severity based on data from 5601 COVID-19 patients from all national and regional hospitals across South Korea as of April 2020. The clinical severity of COVID-19 was divided into two categories: low and high severity. The condition of patients in the low-severity group corresponded to no limit of activity, oxygen support with nasal prong or facial mask, and noninvasive ventilation. The condition of patients in the high-severity group corresponded to invasive ventilation, multi-organ failure with extracorporeal membrane oxygenation required, and death. For the AI model input, we used 37 variables from the medical records, including basic patient information, a physical index, initial examination findings, clinical findings, comorbid diseases, and general blood test results at an early stage. Feature importance analysis was performed with AdaBoost, random forest, and eXtreme Gradient Boosting (XGBoost); the AI model for predicting COVID-19 severity among patients was developed with a 5-layer deep neural network (DNN) with the 20 most important features, which were selected based on ranked feature importance analysis of 37 features from the comprehensive data set. The selection procedure was performed using sensitivity, specificity, accuracy, balanced accuracy, and area under the curve (AUC).We found that age was the most important factor for predicting disease severity, followed by lymphocyte level, platelet count, and shortness of breath or dyspnea. Our proposed 5-layer DNN with the 20 most important features provided high sensitivity (90.2%), specificity (90.4%), accuracy (90.4%), balanced accuracy (90.3%), and AUC (0.96).Our proposed AI model with the selected features was able to predict the severity of COVID-19 accurately. We also made a web application so that anyone can access the model. We believe that sharing the AI model with the public will be helpful in validating and improving its performance. The COVID-19 pandemic has had a major impact on health care systems globally. Since early 2020, COVID-19 has spread rapidly around the world, exceeding 100 million cases and 2 million deaths [Several models have been proposed to predict the severity or mortality of COVID-19 patients using artificial intelligence (AI) techniques. The majority of them have been developed based on limited information or variables, such as medical images -7, bloodTo overcome the generalization issue, we aimed to develop an AI prediction model based on confirmed nationwide patient data obtained from the South Korean government, which included 5601 patients from more than 100 hospitals. In this model, we used comprehensive data sets composed of 37 factors, including basic demographic information, vital signs, physical examination results, clinical symptoms and severity, comorbid diseases, and general blood test results. To the best of our knowledge, this is the first attempt to develop an AI model to predict the severity of COVID-19 based on a nationwide cohort and comprehensive data set in South Korea.This study was approved by the Korea Disease Control and Prevention Agency (KDCA) in South Korea. Informed consent was waived. The KDCA has been managing comprehensive data from COVID-19–confirmed patients in Korea obtained from approximately 100 hospitals. The KDCA discloses this data to few selected researchers during a specific study period. Thus, we investigated this data between September 15 and October 5, 2020, under the approval of the KDCA.Out of 5628 COVID-19 patient records, the clinical severity information was missing in 27 patient records, so we excluded them from our study. Thus, we used 5601 patient data records to develop the AI prediction model for clinical severity. For each patient data record, we used 37 variables as model inputs; these variables are summarized in In the data set, some features were missing (Table S1 in mean(train) and SD(train) are the mean and standard deviation values, respectively, for each feature from the training data set. We applied the standardization to both the training and testing data sets.where For the feature importance analysis and the AI prediction model development, we performed a grid search with a 5-fold cross-validation and 10-time repetition. For that, we divided the 5601 records into training  and testing  data sets in a stratified fashion . We usedThe training data set (n=4480) was randomly shuffled and partitioned into 5 equal folds in a stratified manner: each fold included 433 low-severity records and 15 high-severity records. Of the 5 folds, a single fold was retained as the validation data set for testing the model, and the remaining 4 folds were used as the training data. We repeated the process 10 times, with each of the 10 folds used exactly once as the validation data. Here, since the number of low-severity records was much higher than the number of high-severity records, we up-sampled the high-severity data by randomly copying the data to prevent the model’s bias toward the low-severity data by balancing the amount of data in the two groups.In order to select important features that influence clinical severity, we first investigated the contribution of each of the 37 input variables on severity via feature importance analysis using AdaBoost ,20, randBy repeating the 5-fold cross-validation 10 times, we found the best hyperparameters. For AdaBoost, we set the hyperparameters as follows: the number of tree estimators was set to 50 and the learning rate was set to 0.4. For random forest, we set the number of tree estimators to 100, the maximum depth to 4, and the maximum features to 5. For XGBoost, we set the maximum depth to 2, the learning rate to 0.2, the number of tree estimators to 100, the value of the regularization parameter α to 1.0, the fraction of observations to 0.9, and the fraction of columns to 0.9.The 10-time repeated 5-fold cross-validation provided 50 sets of feature importance values for each classifier . We then averaged the 50 sets of importance values and normalized them so that the importance values from each classifier were in the range from 0 to 1. Finally, we averaged the importance values for the final ranked feature importance value. Moreover, we determined the optimal number of top features to incorporate into the AI prediction model based on the cross-validation results.To develop the final AI model for severity prediction, we used a deep neural network (DNN). In the DNN approach, we investigated up to 5 hidden layers and each layer depth  up to the previous layer depth . For the input layer, we first ranked the features according to their importance and increased the number of top features used in the input layer from 1 to 37. For the fully connected (FC) layers as hidden layers, we applied dropouts by changing the dropout rate from 0 to 0.5 with 0.1 increments. The last FC layer was fed into a sigmoid layer, which is an output layer providing the probabilities for the patient severity. We trained the models with the Adam optimizer and binary cross-entropy cost function with a learning rate of 0.0001 and batch size of 64. We implemented the models using R, version 4.0.2 (The R Foundation), with TensorFlow, version 1.13.1, for DNN; scikit-learn, version 0.22.1, for machine learning algorithms; and xgboost, version 0.6.4, for the XGBoost algorithm.For each set of top features, we found the best cross-validation accuracy using the metrics of area under the curve (AUC) and balanced accuracy:Given the cross-validation accuracy analysis, we finally modeled with the 5-layer DNN using the top 20 features. The 5-layer DNN comprised an input layer, 3 FC layers as hidden layers, and an output layer. The input layer was fed into a series of 3 FC layers consisting of 20, 16, and 8 nodes, respectively. In the first 2 FC layers, we used a dropout rate of 0.5. Then, the last FC layer was fed into a sigmoid layer.We evaluated the prediction performance of our proposed 5-layer DNN model with the isolated testing data set (n=1121). To compare the prediction performance of the DNN model with those of other external AI models, we separately trained the following models: logistic regression, decision tree, random forest, support vector machine, XGBoost, AdaBoost, GradBoost, and HistBoost. We evaluated the prediction performance of these AI models as single models as well as ensemble models.We investigated the cross-validation performance with the metrics of AUC and balanced accuracy . The resWith the isolated testing data set (n=1121), our proposed 5-layer DNN showed a sensitivity of 90.20%, specificity of 90.37%, accuracy of 90.37%, balanced accuracy of 90.28%, and AUC of 0.96. Furthermore, we investigated the prediction performance of ensemble AI models ; none of the ensemble AI models outperformed our proposed 5-layer DNN model .Our proposed AI model, the 5-layer DNN using the selected top 20 features, was able to predict the severity of COVID-19 patients at the hospital admission stage with excellent prediction performance: 90.2% sensitivity, 90.4% specificity, and 90.4% accuracy. The model has several unique characteristics. First, it was developed based on nationwide confirmed COVID-19 patient data obtained from the KDCA. In South Korea, all confirmed cases must be reported to the KDCA; thus, the KDCA data are very accurate and updated on a daily basis [Second, our AI prediction model development started with feature importance analysis of the 37 features in the comprehensive data set. Of these, 20 were selected based on ranked feature importance analysis results in order to develop an accurate AI prediction model. The cross-validation demonstrated that the AI prediction model showed higher accuracy using the selected 20 features compared to using all 37 features. In addition, the selected 20 features  can be easily acquired from patient history, basic physical examinations, and routine laboratory tests. Thus, our AI prediction model can be easily incorporated into routine clinical practice. Furthermore, we observed that PCA-based feature selection also provided as good of a performance as did the feature importance analysis. In particular, we expect that many researchers will be able to flexibly diversify the model for predicting the severity of COVID-19 patients, in that a similar level of accuracy could be obtained with only eight features.In terms of our feature selection process, we combined AdaBoost, random forest, and XGBoost machine learning algorithms to rank the important features. The AdaBoost algorithm is part of the family of boosting algorithms and sequentially growing decision trees as weak learners . It is wWe named our proposed AI prediction model KOVIDnet, indicating the deep learning algorithm for Korean COVID-19 patients. Owing to its high accuracy and generalizability in Korea, we expect that KOVIDnet will be able to provide treatment priority guidance at the time of admission regarding who should be treated intensively. Although most patients with COVID-19 showed mild and self-limiting illness, some patients became severely and critically ill, showing the rapid progression to acute respiratory failure, sepsis, septic shock, multi-organ failure, and eventual death -32. The In our earlier study, we grouped the patients into eight subgroups. Subgroup 1 patients had no limits to their activity. Subgroup 2 patients had limits to their activity, but did not need oxygen. Subgroup 3 patients needed oxygen with a nasal prong. Subgroup 4 patients needed oxygen with a facial mask. Subgroup 5 patients needed noninvasive ventilation. Subgroup 6 patients needed invasive ventilation. Subgroup 7 patients had multi-organ failure or underwent extracorporeal membrane oxygenation. Subgroup 8 patients died. For the multiclass classification, we also trained the model through the same procedure as mentioned above, but the accuracy when using the testing data was not satisfactory , which was a data set that was split from the entire data set. It may be necessary to validate our AI model with external data sets, such as prospectively collected data. To validate and update KOVIDnet, we made a web application  so that In conclusion, we developed our AI model with 20 selected features based on a large nationwide data set, and it was able to predict the severity of COVID-19 accurately. We believe that our model can help health care providers to effectively treat COVID-19 patients at an early stage and ultimately reduce deaths.


Sociodemographic information, racing experience, and patterns of supplement intake, including type, frequency, dosage, etc., were collected using a questionnaire. Macronutrient intake was assessed using a food frequency questionnaire. ANOVA and logistic regression were used for data analysis. The prevalence of supplement intake was 51% for total runners and 72% among vegan runners. Age, sex, and race distance had no significant effect on the type of supplement intake (p > 0.05). Compared to omnivores and vegetarians, vegan runners reported consuming more vitamin  supplements (p < 0.05). Vitamin B12, magnesium, and multivitamin had the most prevalent use amongst micronutrient supplements. This study points to a central role for supplementary nutritional strategies in different groups of distance runners. The present findings may help future investigations by design to identify specific requirements of endurance runners when adhering to specific kinds of diet particularly plant-based diets.Nutrient deficiency is a common cause of underperformance in endurance athletes, and supplement intake is frequently considered compensatory for vegan and vegetarian athletes specifically. This study aimed to investigate the patterns of supplement intake among vegan, vegetarian, and omnivorous distance (>10 km) runners and its association with age, sex, and race distance. From a total of 317 runners who participated in an online survey, 220 distance runners (mean age: 38.5 years; mean BMI: 21.75 kg/m While sources , it has  sources , which c sources . 2max has been well-established in the literature [Irrespective of diet type, there is scientific evidence that indicates endurance runners may not be consuming sufficient nutrients through daily foods to support their athletic needs , and thiterature , currentterature  and recrterature  endurancterature .As a commonly used approach amongst many athletes, dietary supplements are frequently consumed to fulfill the nutrient needs and enhance physical performance and/or appearance . Althoug12, vitamin D, and iron [Although numerous studies demonstrate that the nutrient deficiencies in plant-based diets are generally due to poor planning of regime ,18, evidand iron ,20. It hTo date, few studies have assessed the nutritional patterns and supplement intake in vegan and vegetarian athletes ,22. DespThe present study was designed as descriptive and cross-sectional and is part of the NURMI (Nutrition and Running High Mileage) study step 2 . Enduranwww.nurmi-study.com, accessed on 6 August 2021. Before completing the questionnaire, participants were provided with a written description of the procedures and gave their informed consent to participate in the study. The questionnaire consisted of several parts, e.g., running training and racing behavior, quality of life, food frequency [2 [Participants completed an online survey within step 2 of the NURMI study, which was available in German and English at requency , as welluency [2 ,28, and From a total number of 317 endurance runners, the initial sample of the survey, 72 participants who did not meet the aforementioned general inclusion criteria  were excluded from the study. As a consequence of the specific exclusion criteria for the present study, an additional 25 runners were recognized for consuming less than 50% carbohydrates in their dietary intake, which is lower than the minimum amount of recommended level , and werThe participants were asked to report their regular supplement intake, in addition to food frequency ” with friendly permission of the Robert Koch Institute, Berlin, Germany) . MacronuThe latent factors “running experience”  and “racing experience”  were derived by using both pooled items defined by specific items based on manifest variables. Since the running experience  depends on age, the respective items were operationalized with age . With this, the respective items  were centered by the median and were z-transformed to a new scale by summarizing the respective items . Based on this, the values were categorized considering the two latent factors “running experience” and “racing experience” as low , medium , and high .2, nominal scale) was used to examine the association between dietary subgroups and age, sex, race distance. Kruskal-Wallis tests  were approximated by using the t or F distributions or using ordinary least squares and standard errors (SE), and R2. Logistic regression analysis ) was used to determine the effect size of the variables  on intake from kind of supplements  and is displayed as effect plots ). The level of statistical significance was set at p ≤ 0.05.The statistical software R version 4.0.0  was used to perform all statistical analyses. Exploratory analysis was performed by descriptive statistics (median and interquartile range (IQR), mean and standard deviation (SD)). Significant differences between the types of supplement intake and dietary subgroups, age, sex, and race distance were calculated by ANOVA. Logistic regression analysis ) was used to determine the effect size of the variables  on intake from kind of supplements  and is displayed as effect plots. Chi-square test  with a mean age of 38.5 (IQR 18.0) years remained for statistical analysis after a multi-stage data clearance. Germany, Austria, and Switzerland had the majority of endurance runners with 161, 39, and 11 participants, respectively, while 9 participants were from other countries . Based on their race distance, there were a total of 79 10-km runners, 84 half marathoners, and 57 (ultra-)marathoners. = 6.99, p = 0.001) and BMI  = 7.32, p < 0.001) but not in body height. In addition, both vegans and vegetarians were significantly younger  = 3.17, p = 0.041) than omnivores. Moreover, there was a significant difference between sex and diet type (χ2(2) = 8.71, p = 0.013), with the majority of vegans and vegetarians being female. No significant association was found between the kind of diet and academic qualification, marital status, country of residence, and race distance  and vegetarian (38%) runners, the consumption of a multivitamin (30%) and vitamin D (18%) was higher than other vitamin supplements in the omnivorous group /protein, minerals, vitamins, and other supplements were 20%, 33%, 42%, and 6%, respectively. No difference between vegans (20%), vegetarians (18%), and omnivores (20%) was found regarding the consumption of CHO/protein supplements. The prevalence of mineral supplement intake was lower among vegetarians (22%) compared to vegans (33%) and omnivores (36%). It was found that 66% of vegans consumed vitamin supplements, while only 25% of vegetarians and 30% of omnivores reported consuming vitamin supplements. Results from analysis of open questions showed that amongst mineral supplements, magnesium had the most prevalence of use in all three groups of omnivorous (45%), vegetarian (25%), and vegan (18%) runners. Amongst vitamin supplements, while vitamin Bus group . Concerning the frequency of supplement intake, 58% of the participants reported consuming supplements regularly in their daily diet, while the remaining 42% mentioned either less than once per week (6%), 1–2 times per week (15%), 3–4 times per week (12%), or 5–6 times per week (9%) as the frequency of supplement consumption. When comparing the dietary groups, we found that 61% of the omnivores, 36% of the vegetarians, and 62% of the vegans reported consuming a supplement on a daily basis. Analysis of the self-reported distribution of macronutrients showed that 58.2%, 24.5%, and 17.4% of the total energy intake of participants derived from CHO, protein, and fat, respectively. 2(2) = 27.38, p < 0.001) with the kind of the diet (particularly the greater intake of vitamin supplements by vegan group), and no significant effects were observed for CHO/protein (χ2(2) = 0.10, p = 0.951) and minerals (χ2(2) = 2.65, p = 0.266) across vegan, vegetarian, and omnivorous runners . There was also no significant association between supplement intake and race distance, running experience , and racing experience  (p > 0.05) (p > 0.05).It was found that neither age nor sex has a significant effect on the type of supplement intake in vegan, vegetarian, and omnivorous runners ( > 0.05) . No sign12 and magnesium had the most prevalence for use amongst vitamin and mineral supplements, respectively; (3) there was no association between type of supplement and age, sex, and race distance; and (4) higher CHO and lower protein and fat intakes were observed in macronutrient distribution considering the total daily energy intake of vegans compared to vegetarians and omnivorous endurance runners. Additionally, vegan and vegetarian distance runners had significantly lower body weight and BMI than omnivores that might be associated with the unbalanced sex and age distribution between dietary groups in the present study, as well as a more pronounced health-consciousness of vegetarians but especially vegans compared to omnivores, in general [The purpose of this study was to investigate supplement intake among vegan, vegetarian, and omnivorous distance runners and its relation to age, sex, and race distance. As the main finding, we observed a higher prevalence use of vitamin supplements use in vegan endurance runners (66%) compared to vegetarian (25%) and omnivorous (30%) counterparts. Further significant findings were: (1) irrespective of diet type, 51% of the distance runners reported consuming a supplement regularly; (2) vitamin B general .Detailed characteristics of dietary, sports nutrition, and performance-enhancing supplements and the scenarios in which they contribute to the nutritional demands of endurance athletes were presented recently by Maughan et al.  and Peel12, with a markedly higher consumption by vegan runners [12 by vegan runners was noticeably higher than omnivorous and vegetarian runners in the present study, and recent evidence indicates that micronutrient deficiency can occur with any diet type [12–regardless of kind of diet–should be recommended for all groups of the public and athletic populations, and daily meals should be planned and composed appropriately [When comparing vegan and non-vegan runners, a higher prevalence of supplement intake (irrespective of supplement type) was detected in vegans in the present study. While 72% of vegan runners reported consuming supplements, non-vegans reported consuming markedly fewer supplements (41% of omnivores and 35% of vegetarians). This occurrence might be directly linked to the increased consumption of vitamin supplements in vegans (66%), which was over two times higher than in omnivores and vegetarians . However, this pronounced difference did not occur in either intake of CHO/protein or mineral supplements. The higher intake of vitamin supplements by vegan runners seems to be characterized by an increased health-consciousness of individuals who follow plant-based diets ,21 and t runners . The coniet type . TherefoThe present study showed that the prevalence of CHO/protein supplement intake was found to be similar among vegan (20%), vegetarian 18%), and omnivorous (20%) runners. While proteins and carbohydrates can play critical roles in health and performance separately, co-ingestion of carbohydrates and protein can result in positive effects on post-exercise recovery in endurance athletes, compared to carbohydrates alone , and par8%, and oSex-related differences in supplement intake have been investigated widely in athletes and sedentary individuals. Consistent with the previous literature, the results of the present study found no general difference between male and female athletes considering supplement intakes ,41. HoweAge is generally an important modulator of the decision to use supplements and the strongest predictor of dietary supplement intake ,49. The In the present study, no significant difference was observed between 10-km runners, half-marathoners, (ultra-)marathoners, and the intakes of either CHO/protein, mineral, or vitamin supplements. Although no study has yet compared different groups of distance runners regarding the patterns of supplement intake, it has been well-documented that endurance athletes use supplements to a greater extent than non-endurance athletes ,53, probThe primary nutritional challenge that marathoners face is to meet the high exercise-induced requirements of daily energy and macronutrients necessary to optimize performance and recovery of prolonged training sessions ,59. In tAlthough it is well-accepted that individualized macronutrients distribution depends on different training, individual, nutritional, and environmental characteristics, macronutrient distribution of 60% from CHO, 15% from protein, and 25% from fat have been recommended in general to support repeated bouts of endurance training and to meet recommendations for health concerns ,54. The In the present study, protein intakes of vegan, vegetarian, and omnivorous runners were higher than the recommended range for endurance athletes , which wThere are some limitations to this study to be mentioned. In addition to the relatively small sample size, the study was conducted following a cross-sectional design, and the findings are based on self-reported data. Therefore, the results have to be interpreted with caution. In order to minimize the effect and to control for inconsistent and contradictory statements, control questions were implemented in different sections of the questionnaire. Moreover, despite the higher proportion of vegan/vegetarian populations in DACH countries (10–14%) compared to other Western nations, this might have affected the present results to some extent as 55% of participants in the present study stated following a vegan or vegetarian diet, which is markedly higher than the worldwide numbers, as well as for German-speaking countries . Another limitation of the present study could be the impossibility of conducting statistical analysis for inconsistent and incomplete open comments provided by runners, which compelled the authors to report the relevant findings inclusively. However, self-reports for this type of variable are valid if they are collected immediately or shortly after an event . In thisNevertheless, the authors are convinced that the present findings contribute to adding a valuable and novel body of evidence considering patterns of dietary supplement intake among endurance runners with a critical focus on runners who follow plant-based diets. Additionally, the present findings may help future investigations by design to identify specific requirements of endurance runners when adhering to specific kinds of diet. Future research with large randomized samples of distance runners can add support in providing comparable data on patterns of supplement intakes to help meet the macronutrient and micronutrient intake guidelines, which would especially contribute to a better understanding of supplement intake in distance runners following plant-based dietary patterns.12, vitamin D, calcium, iron, iodine, zinc) for vegan athletes. No difference between 10-km runners, half-marathoners, and (ultra-)marathoners in the type of consumed supplements were observed, indicating the null effects of the race distance on supplement choice among long-distance runners. Overall, the findings from the present study point to an important contribution of supplement strategies in endurance runners, particularly those who follow a vegan diet, and might be helpful when applying personalized nutritional strategies for optimized individual health status, performance, and recovery.In summary, the present comparison of vegan, vegetarian, and omnivorous distance runners shows a more than two-fold higher intake of vitamin supplements, but not of mineral and CHO/protein supplements, among vegan versus non-vegan runners. This finding might be associated with the existing dietary guidelines that highly recommend the supplementary intake of critical micronutrients (e.g., vitamin B


Computer simulations have been widely applied in population genetics and evolutionary studies. A great deal of effort has been made over the past two decades in developing simulation tools. However, there are not many simulation tools suitable for studying population admixture.AdmixSim 2, an individual-based tool that can flexibly and efficiently simulate population genomics data under complex evolutionary scenarios. Unlike its previous version, AdmixSim 2 is based on the extended Wright-Fisher model, and it implements many common evolutionary parameters to involve gene flow, natural selection, recombination, and mutation, which allow users to freely design and simulate any complex scenario involving population admixture. AdmixSim 2 can be used to simulate data of dioecious or monoecious populations, autosomes, or sex chromosomes. To our best knowledge, there are no similar tools available for the purpose of simulation of complex population admixture. Using empirical or previously simulated genomic data as input, AdmixSim 2 provides phased haplotype data for the convenience of further admixture-related analyses such as local ancestry inference, association studies, and other applications. We here evaluate the performance of AdmixSim 2 based on simulated data and validated functions via comparative analysis of simulated data and empirical data of African American, Mexican, and Uyghur populations.We here developed a forward-time simulator, AdmixSim 2 is a flexible simulation tool expected to facilitate the study of complex population admixture in various situations.The online version contains supplementary material available at 10.1186/s12859-021-04415-x. These tools were initially designed for various modeling emphases and objectives, so that they have been widely applied to different genetics studies, such as the human epidemiology , and thenomeSIM , genomeSomeSIMLA ). Among admix’em , SELAM [m [SELAM , SLiM [1AM [SLiM –16, simup [forqs . They arneEvolve , simuPOPAdmixSim  also supAdmixSim 2 can be mainly divided into five layers: segment, chromosome, individual, single-generation population, and multiple-generation population. AdmixSim 2 begins with a set of individuals from ancestral populations, corresponding sex settings, chromosome information, and a user-defined demographic model. Each Individual is a diploid and constituted by two chromosomes. In the founding generation, each chromosome of ancestral individuals is assigned with a unique integer-type label ranging from 0 to ith ancestral population, i = 1, 2, …, k). Chromosomes of a certain population take consecutive labels. Following the demographic model settings, for each population, the probability of being sampled to be a parent of newly generated individuals is proportional to the corresponding admixture proportion. More specifically, when there are three ancestral populations, i.e., pop1, pop2, and pop3, their admixture proportions are 0.2, 0.1, and 0.7 respectively. To make new individual data, we first generate a random number between 0 and 1. One individual of pop1 is selected if the random number is less than 0.2, while one individual of pop2 is selected if the random number is larger than 0.2 and less than 0.3, otherwise, one individual of pop3 is selected. Within each population, the probability of being sampled for each individual is proportional to the corresponding fitness. Each chromosome of newly generated individuals consists of a list of segments. Each segment is identified by the start physical position, the end physical position, and the label it originates from. The new generated individual inherits corresponding segments from parents with additional segments resulted from recombination. Asides from the ancestral segments, each chromosome has two additional lists recording the recombination breakpoints and de novo mutation points, respectively, and one map recording the physical positions under selection and corresponding states of the allele. The generation of new recombination and mutation points can be modeled as the Poisson process and assigned along the chromosome based on the user-defined recombination rate and mutation rate, respectively. Each population in AdmixSim 2 is constituted by individuals spreading several generations specified in the demographic model.The data structure of AdmixSim 2. Detailed information can be found in the user’s manual. AdmixSim 2 follows the extended Wright-Fisher (WF) model, which includes diploid individuals and non-overlapping, discrete generations. Unlike the strict WF model, the population size over generations can fluctuate and can be defined by users. Figure AdmixSim 2. Briefly, four input files are required for ancestral haplotype data, individual information, single nucleotide variation (SNV) information, and model description. The model description file defines the overall simulation processes by combining a series of modules of a standard format for every single process. Even though it is possible to use models in combination for extensive admixture scenarios, modifications of a single model are also applicable and flexible. With the input of these four files, AdmixSim 2 implements the whole simulation process defined in the model description file across generations. At the end of the simulation, haplotype data of individuals of specified populations are provided, and users can flexibly sample a certain number of individual data for output. Output data of any generation are available for all of the simulated populations. The output individual information file, haplotype data file, and updated SNV information file are in a similar format as the input file, which provides convenience and flexibility for subsequent simulations across different demographic models. Moreover, the haplotype data as provided by AdmixSim 2 are helpful for follow-up analysis and revealing the properties of real genomic data, which are not available in many other simulation tools. In addition to the aforementioned output files, AdmixSim 2 also generates three additional outputs, frequency of alleles under selection, ancestral track information, and a log file.Next, we provide a brief description of the workflow of AdmixSim 2. Corresponding parameters can be set in input files or using the command-line interface. Initial settings for sex in the individual information file define monoecious and dioecious individuals for simulation. In the case of monoecious individuals, we logically sample two different individuals as parents of each offspring in the next generation. The probability that samples an individual out is proportional to the individual’s fitness. The fitness of an individual is calculated as one plus the sum of selection coefficients of all selection conditions satisfied. The negative value is rescaled to zero. Each parent contributes one gamete to the offspring with mutations and recombination. The recombination rate and mutation rate can be set as uniform or nonuniform (locus-specific) in either the command line or the SNV information file. For selection, AdmixSim 2 can simulate the case of a single locus, multi-locus (continuous or discrete), population-specific, and sex-specific selection. Here, the sex-specific selection is incorporated by assigning different selection coefficients for two sexes. Sex-specific population sizes and sex-specific admixture proportions are supported as well. The selection coefficients are allowed to change over generations. Users can also simplify the simulation by using a single parameter setting to avoid complex evolutionary processes with recombination, de novo mutation, and natural selection, respectively.Admixture, de novo mutation, and natural selection are the evolutionary events that we mainly considered in forqs. The time consuming is insensitive to the number of simulated SNVs and remains relatively small even with a large recombination rate and mutation rate. Second, we discard the population information of the previous generation after simulating the current generation unless it is specified to be output. Generally speaking, there are data of two generations existing simultaneously in the simulation process. Finally, we record the haplotype data of ancestral populations into memory after simulating all the generations instead of at the beginning. The ancestral haplotype data are used to extract the segmental sequence based on the segment information carried by each output haplotype. We compared the basic features and abilities of AdmixSim 2 with QuantiNemo 2 [SLiM 3.3, simuPOP, GeneEvolve, SELAM, forqs, and admix’em . These results further demonstrated the simulated data by AdmixSim 2 are a satisfactory alternative on the level of local genomic regions. For the other two admixed populations, Mexicans and Uyghurs, the aforementioned features of simulated data were confirmed  which are of 2, 3, and 4 distinct ancestral originations, respectively  model with the initial ancestral contribution of 4:1 for two ancestral populations  and ended at generation 50. The recombination rate was set as 10ltiWaver . The stas, and 1 + 2 s for individuals carrying 0, 1, and 2 selected haplotypes, respectively, where s denotes the selection coefficient. During each simulation of 500 repeats, we recorded the selection frequency at each generation. Using xt to denote allele frequency at generation t, we have the theoretical frequency at generation t + 1 asTo verify the frequency variation tendency of alleles under selection, we simulated a two-locus segment under a selection amenable to the additive model with an initial freqncy of 5% and a selection coefficient of 0.1. Under the additive model, the fitness is 1, 1 + p = 0.999, Kolmogorov–Smirnov test).Given the condition of ion Fig. A. The re–8. We considered four distinct initial frequencies of the segment under selection, 5%, 10%, 15%, and 20%. The selection coefficient varied in the change of 0.01–0.1, taking 0.01 as a step  and mutation rate (per generation per site) were both set as 10AdmixSim 2 using a HI model with equal contribution from the two ancestral populations. Six distinct factors were considered in the evaluation by varying values of one and holding the rest constant, including chromosome length, recombination rate, mutation rate, admixed population size in simulation, end generation, and a number of loci under selection  and simulated generation . All tests were conducted on 96-core Intel Xeon Platinum 9242 CPU 2.30 GHz computer servers. SLiM 3.3 was compiled under the release build. The runtime and memory cost for both simulators are approximately linear functions of generations or population size. Notably, the memory cost of AdmixSim 2 is almost constant, while for SLiM 3.3, it is much higher and growing faster. These results indicate that AdmixSim 2 is feasible and efficient in massive simulations.Further, we evaluated the time cost of SLiM 3.3  using thAdmixSim 2 was designed to focus on simulating the admixture process, the pre-admixture data can be generated from different strategies. In human genetics, users can use the genetic data from public data sets like the KGP, the Estonian Biocentre Human Genome Diversity Panel (EGDP), the Simons Genome Diversity Project (SGDP), and the International HapMap Project. Since AdmixSim 2 can simulate the scenario that the ancestral populations evolve same generations as the admixed population, it is practical to use the populations from these public datasets as ancestral populations. Besides, populations from these datasets could be used as proxy populations in local ancestry inference. With the advance of genotyping and technologies, the ability to generate large amounts of sequence data in a relatively short amount of time is helping to enable a wide range of genetic analysis applications. Therefore, the pre-admixture genetic data can be more easily obtained in the future owing to advanced sequencing technologies. More generally, users can use coalescent approaches like msprime [SLiM 3.3 to simulate the pre-admixture data. This approach can be applied to both human and non-human species. For instance, the documentation of msprime (https://tskit.dev/msprime/docs/stable/demography.html) gave the code to simulate African, European, and East Asian individuals based on the Out of Africa model developed by Gutenkunst et al. [SLiM 3.3 (page 99) implemented a model of human evolution presented by Gravel et al. in 2011 [AdmixSim 2 can also be used as the input of further simulations. The first three output files  of AdmixSim 2 take the same format as the corresponding input, and they can be used for subsequent simulations with a new demographic model.Since  msprime  or forwat et al.  from the in 2011  based onAdmixSim 2 record the recombination segments rather than the whole haplotype data, which brings a proportion of efficiency for the simulation. The way of segment representation in AdmixSim 2 is similar to that implemented in forqs, but there is some slight difference. Each haplotype chunk in forqs is represented by two numbers : the position where it begins, and the identifier of the founding haplotype from which it is derived. For AdmixSim 2, each segment is identified by the start physical position, the end physical position, and the ancestral label it originates from. Despite this difference is not seemly substantial, we believe specify an ending physical position is more convenient to calculate the selection fitness and extract segmental sequence data without indexing the next segment. Besides, we noticed that forqs is mainly used to simulate the scenarios that recombination and/or natural selection on polygenic quantitative traits within a relatively small number of generations, while the emphasis of AdmixSim 2 is on simulating complex population admixture events more flexibly. Previous studies have demonstrated that a segment-based simulator is not as efficient as array-based simulators (like SLiM) when involving demographic events taking place over thousands of generations [erations . NeverthAdmixSim, has been used in many evolutionary and population genetic studies, including those exploring the genetic history of Xinjiang’s Uyghurs [CAMer [MultiWaver series software [Libgdrift [AdmixSim and AdmixSim 2  algorithm [SLiM 3.3 provides the necessary information to detect coalescence events and construct the genealogical tree at each chromosome position, although applying the TSR algorithm has a large impact on the performance of models, in terms of both runtime and memory usage . The TSR algorithm has also been applied into many other simulators like msprime and inference methods like tsinfer [SLiM 3.3, SELAM, and admix’em consider the cases including phenotypic selection, epistatic selection, or balancing selection. Although AdmixSim 2 does not cover the comprehensive scenarios of mate choice as some other simulators, it implements sex-biased admixture (different admixture proportions for two sexes) and sex-specific selection (different selection coefficients for two sexes).Nevertheless, there is still room for improvement in lgorithm  implemen tsinfer . NonetheAdmixSim 2 is an individual-based, forward-time simulator based on the extended WF model, which can be used to efficiently simulate one or more admixed populations under complex demographic scenarios. AdmixSim 2 is highly flexible and it can implement combinations of multiple parameter settings to simulate admixture, recombination, mutation, and natural selection. Furthermore, AdmixSim 2 can be used to simulate admixture scenarios for sex chromosomes and non-human species.In summary, Additional file 1: Figure S1. Admixture models of population (A) African America (B) Mexican and (C) Uyghur. The numbers on the arrows represent the corresponding admixture proportions. The time on the left of each model represent the admixture generationsAdditional file 2: Figure S2. Simulation of Mexican admixture pattern. (A) PCA results. The left is the result of empirical data and the right is the result of simulated data. The patterns of two results are quite similar. (B) Segment length proportion. The proportion of each ancestry was calculated based on the sum of the corresponding segment length. The average proportion of European, African, and Native American were 0.506, 0.054, and 0.440, which is consistent with proportions set in the admixture model . (C) Supervised admixture analysis results at K = 3. The left is the result of empirical data and the right is the result of simulated data. There is no marked difference between these two results. (D) Mutation number counts. The green histogram represents the simulation value and the red curve is derived from the theoretical Poisson distribution. The p-value was calculated using the chi-square goodness of fit test. The chromosome length was approximate 2.48 Morgan and the mutation rate was set as 10-8 per generation per site. As a result, after simulating 18 generations, the average mutation number of each haplotype is about 45Additional file 3: Figure S3. Simulation of Uyghur admixture pattern. (A) PCA results. The left is the result of empirical data and the right is the result of simulated data. The patterns of two results are quite similar. (B) Segment length proportion. The proportion of each ancestry was calculated based on the sum of the corresponding segment length. The average proportion of East Asian, Siberian, West Eurasian, and South Asian were 0.33, 0.17, 0.36, and 0.14, which is consistent with proportions in the admixture model . (C) Supervised admixture analysis results at K = 4. The left is the result of empirical data and the right is the result of simulated data. There is no marked difference between these two results. (D) Mutation number counts. The green histogram represents the simulation value and the red curve is the Poisson distribution, theoretically. The p-value was calculated using the chi-square goodness of fit. The chromosome length was about 2.48 Morgan and the mutation rate was set as 10-8 per generation per site. Therefore, after simulating 150 generations, the average mutation number of each haplotype is about 372Additional file 4: Table S1. Parameter settings of typical admixture patternAdditional file 5: Table S2. Parameter settings of selection fixation testAdditional file 6: Table S3. Parameter settings of performance evaluation