Background. Dendrobium genus has been used in traditional medicine to treat various illnesses. The study aims at examining the phytochemical, antioxidant, anti-inflammatory, and thrombolytic properties of the leaf, stem, and root of Dendrobium lindleyi Steud, and the relationship between phytochemicals and bioactivities is determined. Results. The qualitative screening found a variety of bioactive compounds, including alkaloids, coumarins, cardiac glycosides, glycosides, flavonoids, proteins, phenols, quinines, resins, steroids, saponins, tannins, and terpenoids, in varying amounts. The quantitative screening showed the highest concentration of alkaloids in the leaves (172.15 ± 1.22 mg/g), phenols in the root (203.55 ± 0.75 mg/g), flavonoids in the root (24.35 ± 0.42 mg/g), tannins in the leaves (105.06 ± 0.55 mg/g), and proteins in the root (194.12 ± 0.65 µg/ml). The root extract showed the highest antioxidant activity (IC50 = 58.24 µg/mL), the stem extract had the most increased thrombolytic activity (IC50 = 242.74 µg/mL), and the leaf extract had the most potent anti-inflammatory activity (IC50 = 61.79 µg/mL). Statistical analysis revealed a significant positive relationship (p = 0.05) between alkaloids (r = 0.96) and tannins (r = 0.9) with antioxidant, anti-inflammatory, and thrombolytic properties. Conclusion. The bioactivities of D. lindleyi, including antioxidant (root), thrombolytic (stem), and anti-inflammatory (leaf) activities, are linked to the phytochemicals detected in the screening. Dendrobium species as medicine has a long history, as it was mentioned in the Chinese pharmacopeia “The Sang Nung Pen Tsao Ching” as early as 200 B.C. as a tonic, astringent, analgesic, and anti-inflammatory substance [Dendrobium in his “Materia medica.” Modern research has confirmed the anti-inflammatory, antifungal, antibacterial, and other pharmacological properties of Dendrobium species [Dendrobium lindleyi Steud. It is one of the orchid species found in Bangladesh. Although its traditional use or therapeutic benefits are unknown, fresh and dried stems of D. lindleyi are used in traditional Chinese medicine to treat dehydration, fever, and eye health [D. lindleyi is being conducted. The study aims at validating its traditional uses and creating a foundation for further research towards developing new drugs from this species.The traditional medical systems of Ayurvedic, Siddha, and Unani have documented the use of orchids as medicine, as recorded by Charaka, Sushruta, and Vagbhata. With the growing demand for natural remedies, there is an increased interest in the medicinal use of orchids in traditional medicine . The use species , 4. Bang species –9. Dendre health . Previoue health ; however4, bovine serum albumin, 1,1-diphenyl-2-picrylhydrazyl, ascorbic acid, egg albumin, iso-saline, acetyl salicylic acid, streptokinase vial , and blood sample.Dragendroff's reagent, Hager's reagent, Wagner's reagent, Tannic acid reagent, Mayer's reagent, Folin–Ciocalteau reagent, 10% NaOH, glacial acetic acid, ferric chloride, conc. sulphuric acid, ethyl acetate, dilute ammonia solution, methanol, 50% HCL, Fehling's solution, acetic acid anhydride, chloroform, ethanol, potassium hydroxide pellets, ammonium hydroxide, sodium nitrite, aluminum chloride, sodium hydroxide, quercetin, sodium carbonate, gallic acid, tannic acid, NaOH solutions, NaK tartrate, CuSOPlants were collected from Bandarban (Keokradong hill), Chittagong, in the southeast region of Bangladesh, in April 2019. The area lies within latitude 22°11′43″ North and longitude 92°13′10″ East and runs along the border of Bangladesh. The plant was identified in the Chittagong University Herbarium (CTGUH), Department of Botany, University of Chittagong, where a voucher specimen (Accession no: KB_05/2019) was deposited for future reference.Fresh leaves, stems, and roots were harvested and thoroughly washed with water, room dried, and sun-dried. Then, the samples were dried in an oven at 60° for 72 hours. It was then ground into a coarse powder using a grinding machine and stored in an air-tight container for further investigation. 25 gm of sample from each plant part were taken for further analysis. 150 ml of methanol was added to each sample in a conical flask. It was then shaken well for 30 minutes, kept overnight, shaken again, and sonicated for 10 minutes. It was then filtered using the Whatman No. 1 filter paper. The process was repeated thrice with methanol; then, the extract was evaporated below 51° and dried. The dried sample was kept as a crude sample for each part.D. lindleyi using standard procedures [Qualitative tests were carried out on the crude and powdered extracts of leaves, stems, and roots of ocedures –14 to idQuantitative phytochemical tests were performed using the following standard procedures.(1) Total Alkaloid Determination. For determining the total alkaloid content, fresh samples of leaves, roots, and stems (5 g each) were placed in 250 mL beakers and a mixture of 200 mL 20% acetic acid in ethanol was added. After 4 hours, the mixture was filtered and the extract was concentrated in a water bath to a quarter of its original volume. Concentrated ammonium hydroxide was gradually added until precipitation was complete. After settling, the precipitate was washed, filtered, dried, and weighed with the weight expressed as mg/g extract [ extract .(2) Total Flavonoid Determination. For total flavonoid estimation, standard solutions of quercetin were prepared and plant extracts were treated similarly. After incubation and spectral measurement at 510 nm, the flavonoid content was expressed in mg quercetin equivalents (QE)/g of the dried plant extract [ extract , 17.(3) Total Phenol Determination. Methanol extracts (1 mg/ml) were analyzed to determine the total phenol concentration. A mixture of methanol extract, 10% Folin–Ciocalteu's reagent, and 7.5% sodium carbonate solution was prepared and incubated. Absorbance was measured at 760 nm using a UV spectrophotometer. The total phenol concentration was determined from a calibration curve of gallic acid equivalents (GAE) and expressed as mg GAE/g of the extract [ extract , 19.(4) Total Tannin Determination. For total tannin determination, extracts (1 mg/ml) were mixed with water, Folin–Ciocalteu reagent, sodium carbonate solution, and distilled water. After incubation, absorbance at 700 nm was measured using a UV spectrophotometer. Tannin content was expressed in mg of tannic acid equivalents/g of the dried sample [d sample .(5) Total Protein Determination. A phenolic complex with the maximum absorption at 660 nm was formed for total protein determination. Bovine serum albumin (BSA) was used as a standard protein. Samples were mixed with reagents and incubated. Then, absorbance was measured at 660 nm using a UV spectrophotometer. The protein content was expressed in mg/g of dried plant extract [ extract .D. lindleyi and the standard antioxidant ascorbic acid were assessed based on the free radical scavenging effect of the stable 2, 2-diphenyl-1-picrylhydrazyl  free radical activity with slight modification [D. lindleyi was conducted to prepare a range of concentrations  in methanol. Ascorbic acid (Positive control) with similar concentrations was also prepared in methanol. 0.004% DPPH solution was prepared in methanol. The absorbance was measured at 517 nm using a UV-visible spectrophotometer. The experiment was performed thrice. The scavenging activity against DPPH was calculated using the following equation:A = Absorbance of DPPH solution (negative control) and B = Absorbance of DPPH solution (extracts/ascorbic acid).The antioxidant activities of the methanolic crude extracts of the leaves, stems, and roots of fication . PreparaD. lindleyi and the standard anti-inflammatory agent acetyl salicylic acid were assessed based on inhibition of the albumin denaturation technique of the stable egg albumin denaturation inhibition activity with slight modification [D. lindleyi was carried out to prepare a range of concentrations  in methanol and 1% aqueous solution of egg albumin, and the pH values (5.6 ± 0.2) of all mixtures were adjusted by 1N HCl. Acetylsalicylic acid with different concentrations  was also prepared. The absorbance was measured at 660 nm using a UV-visible spectrophotometer. The experiment was performed thrice. The anti-inflammatory activity was calculated by using the following equation:A = absorbance of egg albumin solution + methanol (negative control) and B = absorbance of egg albumin solution + extract/standard (positive control).The anti-inflammatory activities of the methanolic crude extracts of the leaf, stem, and root of fication , 24. PreμL/tube) and incubated at 37°C for 45 minutes. After clot formation, the serum is completely removed (aspirated out without disturbing the clot formed). Each tube having a clot is again weighed to determine the clot weight. Each Eppendorf tube containing the clot is labelled correctly, and 100 μL of plant extract is added to the tubes. All the tubes are then incubated at 37°C for 90 minutes and observed for clot lysis. After incubation, the fluid obtained is removed and tubes are again weighed to keep the difference in weight after clot disruption. Streptokinase and water are positive and negative (nonthrombolytic) controls, respectively. The experiment is repeated three times with the blood samples of different volunteers. The difference obtained in weight taken before and after clot lysis is expressed as a percentage of clot lysis as follows:A clot lysis experiment was carried out to check the thrombolytic properties of the plant extract. In this method , venous Finally, the study statistically examined total phytochemicals  for their effect on bioactivity . For this, regression analysis and Pearson's correlation coefficient analysis were performed by Microsoft Excel 2010.The responses of the plant extracts to various reagents provide valuable insights into their chemical composition and the presence of specific alkaloid groups in different parts of the plant . When teMoreover, coumarins, cardiac glycosides, flavonoids, proteins, phenols, quinines, resins, steroids, saponins, tannins, and terpenoids were detected in varied amounts during the qualitative screening . The lea(1) Total Alkaloid. Total alkaloid contents of D. lindleyi leaf, root, and stem recorded were 172.15 ± 1.22, 109.47 ± 0.93, and 148.4 ± 1.00 mg/g, respectively. Leaf exhibited the highest alkaloid contents of 172.15 ± 1.22 mg/g.(2) Total Flavonoid. In the present work, 13.86 ± 0.20, 1.63 ± 0.66, and 24.35 ± 0.42 mg·g−1 of flavonoids were found in D. lindleyi in the leaf, stem, and root, respectively. The highest amount of flavonoid found in the root extract was 24.35 ± 0.42 mg/g.(3) Total Phenol. Total phenol concentrations of D. lindleyi leaf, root, and stem were 176.47 ± 1.05 mg/g, 148.22 ± 0.82 mg/g, and 203.55 ± 0.75 mg/g, respectively, in quantitative evaluations. The root has the highest phenol concentration, measuring 203.55 ± 0.75 mg/g.(4) Total Protein. The highest amount of protein content detected in the root methanolic extracts was 194.12 ± 0.65 µg/ml, equivalent to BSA, whereas the leaf and stem methanolic crude extracts of D. lindleyi contain (178.97 ± 0.41 and 131.61 ± 0.49) BSA identical µg/ml plant extract, respectively.(5) Total Tannin. The total tannin contents of the leaf, stem, and root of D. lindleyi were found to be  mg·g−1 respectively. The highest amount of tannin in the leaf extract was 105.06 ± 0.55 mg/g compared to the extracts of the stem and the root.µg/mL proteins (root) in quantitative screening , 203.55 ± 0.75 mg/g phenols (root), 24.35 ± 0.42 mg/g flavonoids (root), 105.06 ± 0.55 mg/g tannins (leaf), and 194.12 ± 0.65 creening .50 values of 111.79, 82.24, and 58.24 µg/mL, respectively. Compared to the standard (26.08 µg/mL), the root extract showed the most potent antioxidant activity, the stem extract displayed intermediate potency, and the leaf extract exhibited minor antioxidant potency among the tested plant parts . The IC50 values from the albumin denaturation assay measured the ability of the tested substances  to prevent the denaturation of albumin. A lower IC50 value indicates more potent anti-inflammatory activity. The standard had the most powerful protective effect, followed by the root extract, the leaf extract, and the stem extract  of albumin, a protein. The ICectively , with th extract . These f50 values of 275.06, 242.74, and 319.62 µg/mL, respectively, as compared to the standard (100 µL)  . The peractivity . The IC5r) were calculated as 0.96 for alkaloids, 0.9 for tannins, 0.7 for proteins, 0.51 for phenols, and 0.54 for flavonoids which indicated a strong positive correlation for alkaloids as well as tannins, whereas they indicated moderate positive correlation for proteins, flavonoids, and phenols. Statistical analysis showed that alkaloids (r = 0.96) and tannin (r = 0.9) have a substantial positive connection with antioxidant, anti-inflammatory, and thrombolytic activities at a significance level of p < 0.05 significantly.In this analysis , correlaD. lindleyi were studied, a variety of bioactive compounds, including coumarins, cardiac glycosides, flavonoids, proteins, phenols, quinines, resins, steroids, saponins, tannins, and terpenoids, were discovered. The highest concentration of alkaloids was found in the leaves, while the root contained the highest levels of phenols and flavonoids. Traces of glycosides and saponins were found in the leaves, stems, and roots, and resin was only present in the root. These findings are consistent with the previous studies [D. lindleyi suggests that it may have a wide range of therapeutic properties [In the phytochemical investigation, five reagents tested alkaloids. When tested with Dragendorff's reagent, the leaf extract displayed a “++” response, the stem extracted a “+++” reply, and the root extracted a “++” response. This variation in responses suggests that the stem extract likely contains a higher concentration of alkaloids with secondary amine groups than the leaf and root extracts, which showed more moderate responses. Similarly, when exposed to Hager's reagent, all parts of the plant—the leaf, stem, and root—demonstrated a “+++” response. This collective strong response strongly indicates the presence of alkaloids containing methoxy or catechol groups in substantial quantities across the entire plant. Mayer's reagent produced distinct responses as well. The leaf extract exhibited a “+++” response, the stem extracts a “+” reply, and the root extract a “+++” response. Here, the leaf and root extracts demonstrated a high response, suggesting the significant presence of alkaloids containing hydroxyl or amino groups. In contrast, the stem extract yielded a lower response to Mayer's reagent. Furthermore, against Wagner's reagent, the leaf extract showcased a “+++” response, the stem extract showcased a “++” response, and the root extract showcased a “++” reply. Notably, the leaf extract displayed the highest response, indicating the likely presence of alkaloids characterized by tertiary amines and phenolic hydroxyl groups. While the stem and root extracts showed moderate responses, they target different alkaloid characteristics. Lastly, the tannic acid reagent elicited “++,” “+,” and “-” responses from the leaf, stem, and root extracts. The leaf extract's “++” response suggests the likely presence of alkaloids that can react with tannic acid. Comparatively, the stem extract's lower “+” response suggests a lower quantity of these alkaloids, and the root extract's “-” response indicates an absence of reaction to this particular reagent. When the other phytochemical components of  studies –30. The operties .50 value of 111.79 µg/mL was obtained for the leaf extract, indicating that it has comparatively lower antioxidant potency than the stem and root extracts. This means that a higher concentration of the leaf extract is required to achieve the same level of antioxidant protection as the other extracts. In contrast, the stem extract demonstrated greater antioxidant potency than the leaf extract. Its IC50 value was 82.24 µg/mL, suggesting that it can achieve a 50% reduction in oxidative damage at a lower concentration than the leaf extract. The most robust antioxidant activity was observed in the root extract, which exhibited the lowest IC50 value of 58.24 µg/mL among the three extracts. This signifies that the root extract possesses the highest antioxidant potency. The antioxidant effects are thought to be due to flavonoids, saponins, and phenolic substances [The antioxidant activity was assessed using a free radical scavenging assay. An ICbstances , 33.50 value of 22.69 µg/mL. This means a standard substance concentration of 22.69 µg/mL effectively prevents albumin denaturation by 50%. The lower the IC50 value, the more potent the substance is in preserving the native structure of albumin. The leaf extract had an IC50 value of 61.79 µg/mL. At a 61.79 µg/mL concentration, the leaf extract can protect albumin from denaturation by 50%. The stem extract showed an IC50 value of 112.11 µg/mL. At a 112.11 µg/mL concentration, the stem extract can inhibit albumin denaturation by 50%. The root extract displayed an IC50 value of 70.76 µg/mL. At a 70.76 µg/mL concentration, the root extract can protect albumin from denaturation by 50%. This value positions the root extract as relatively more effective in preserving the native structure of albumin than the stem extract but still less effective than the standard. The anti-inflammatory properties may be due to saponins, terpenoids, alkaloids, glycosides, and tannins [The anti-inflammatory efficacy was determined using the heat-induced albumin denaturation assay. The standard substance demonstrated an IC tannins , 35.µL, could cause a 52.1% dissolution of the blood clot. The standard likely represents a positive control with known thrombolytic activity. The leaf extract showed a range of clot lysis percentages between 30.2% and 47.1%. This suggests that the leaf extract has varying degrees of thrombolytic activity within this range. The IC50 value for the leaf extract was measured as 275.06 µg/mL. This IC50 value indicates that the leaf extract achieves a 50% reduction in clot formation at a concentration of 275.06 µg/mL. The stem extract also displayed a range of clot lysis percentages, ranging from 31.8% to 49.6%. The IC50 value for the stem extract was 242.74 µg/mL. This value indicates that the stem extract effectively reduces clot formation by 50% at a 242.74 µg/mL concentration. The root extract demonstrated a range of clot lysis percentages from 9.6% to 39.8%. The IC50 value for the root extract was 319.62 µg/mL. This indicates that the root extract achieves a 50% reduction in clot formation at a concentration of 319.62 µg/mL. The thrombolytic activity may be due to alkaloids and tannins [D. lindleyi may be due to its alkaloids, phenolic compounds, and other phytocompounds [The thrombolytic activity was measured using the blood clotting inhibition assay. The standard exhibited a clot lysis percentage of 52.1%. This means that the standard, when used at a volume of 100  tannins , 37. Thuompounds . Statistompounds .D. lindleyi  have varying levels of effectiveness in their antioxidant, thrombolytic, and anti-inflammatory activities. The root extract is the most effective as an antioxidant, the stem extract has the highest thrombolytic activity, and the leaf extract is the most potent in anti-inflammatory activity. These findings can have implications for potential applications of these plant extracts in health and medicine. However, further research is usually necessary to fully understand their mechanisms of action and potential benefits.In summary, the results indicate that the different parts of D. lindleyi, a high-altitude plant with no recorded medicinal use, aimed at examining its phytochemical properties and evaluating its potential as an antioxidant, anti-inflammatory, and thrombolytic agent during the COVID-19 pandemic. However, the study was limited by the need for in vivo testing, which could not be conducted due to time constraints.The research on


The obtained data on the count of individual groups of microorganisms were subjected to analysis of variance (ANOVA) and statistically tested (Student’s t-test with the Bonferroni correction); for temperatures at which there were statistically significant differences and high numerical variability, the trend of changes in bacterial counts were visualised using mathematical modelling. The results show that the optimal storage conditions are refrigerated temperatures (up to 8 °C) for two weeks. At higher temperatures, food spoilage occurred due to the growth of aerobic bacteria, lactic acid bacteria, yeast, and mould. The MAP packaging method was more conducive to spoilage of the bars, especially in temperatures over 8 °C.Food business operators must include the results of shelf life testing in their HACCP plan. Ready-to-eat preservative-free meat products enriched with blood plasma are an unfathomable area of research in food safety. We tested modified atmosphere (80% N The increased demand for ready-to-eat (RTE) food caused the need to research  food chaOften, during the slaughter of animals, blood is classified as an animal by-product under Regulation (EU) No. 1069/2009 of the Parliament and the Council due to the lack of appropriate technology to obtain it in a possibly sterile manner, avoiding contact between the plasma and the surface of the animal’s skin . ApproprDue to the growing trend for the production of RTE food with dietary features  and low-processed food , it is necessary to analyse the microbiological safety of newly created products. The scientific evidence gathered from successful experimental trials validates the HACCP system. Each food business operator (FBO) is obliged to ensure the compliance of the product with the microbiological criteria set out in the Regulation of the European Parliament and of the Council No. 2073/2005 and provide scientific evidence during storage, confirming the safety of products placed on the domestic and international market under the Regulation of the European Parliament and of the Council No. 852/2004 ,7.S. aureus, Enterobacteriaceae) and pathogens  considering different packaging technologies and storage temperatures.The RTE, high-protein, preservative-free meat bar with dried plasma considered in this study is an innovative new product. There is no literature on the shelf life and durability of this type of food. For this reason, it was necessary to undertake a wide range of microbiological studies, taking into account food spoilage bacteria , under aerobic and anaerobic conditions and in MAP (modified atmosphere packaging) products, make them a significant concern for the food industry. They necessitate control measures along the food chain to prevent listeriosis, a severe disease which, according to EFSA reports, is responsible for 1900 hospitalisations per year [n = 334) of RTE pork products in China showed the presence of L. monocytogenes [L. monocytogenes in 25 g of product [RTE foods pose a particular hazard due to per year ,9,10. A ytogenes . Other s product .L. monocytogenes infection for a healthy population (risk level 10−6) and high-risk groups (risk level 10−4) by 80% [L. monocytogenes. They reported the most frequent presence in products packed in atmospheric air , less in vacuum-packed products , and least often in MAP products  [In addition, it has been confirmed that the storage temperature is paramount to maintaining the appropriate biological quality of food until shelf life . Another) by 80% . Other wn = 820) .Enterococcus, Lactococcus, Lactobacillus, Leuconostoc, Pediococcus); however, we are referring to products cured, i.e., those with the addition of preservatives in the form of sodium nitrite [Aeromonas spp. was mentioned. Still, the main reinforcing factors were the permeability of the packaging material to atmospheric oxygen, the initial level of contamination, pH, and storage temperature.Furthermore, it has been described that meat products packaged with access to atmospheric air spoiled mainly due to the growth of yeast and mould, and vacuum-packed products spoiled due to the growth of LAB , pH, storage conditions, temperature, and relative humidity, on microbial growth in food [The presence of microorganisms in food is essential for the quality and durability of the food. Using mathematical modelling obtained from quantitative studies on microbial populations, FBO may predict the effect of food factors, such as water activity . Primary growth models for both strains in the egg yolk were developed based on the Baranyi model. Secondary models were developed as a function of temperature for lag phase duration (LPD) and maximum specific growth rate (μmax) using Davey polynomial, secondary polynomial, and square root models, respectively [A basic simulation model estimated zero probability of ectively .2 with a prediction error of 0.752 log cfu/cm2 based on the results of fluorescent fingerprint spectrophotometry of 30 lean beef meat slices each of Australian and Japanese cattle stored aerobically at 15 °C [The researchers, using mathematical modelling, were able to predict an APC count in the bacterial contamination load range from 1.7 to 7.8 log cfu/cmat 15 °C .Staphylococcus aureus, lactic acid bacteria (LAB), and food safety criteria (FSC), such as E. coli, Salmonella spp., Campylobacter spp., and L. monocytogenes. Based on the collected data, four-parameter mathematical models were used to describe the trend of changes in microbial abundance over time in tested temperature ranges, paralleling the Baranyi and Gompertz growth models.Considering all these reports, we evaluated the effect of two different reduced oxygen packaging (ROP) methods and various storage temperatures on the durability (use-by date) of preservative-free RTE pork bars with porcine blood plasma. We assessed product durability by testing microorganisms according to Process Hygiene Criteria (PHC) such as Aerobic Plate Count (APC), Enterobacteriaceae, yeast and mould, We used 246 RTE meat bars from 3 independent production batches throughout the study. All bars were manufactured in one medium-sized facility  located east of the Masovian district.mm. semimembranosus, quadriceps, biceps, semitendinosus, and gluteus) obtained six hours after the slaughter of large white pigs from Polish farms. Other supplementary raw materials were table salt (sodium chloride), ground black pepper (Piper nigrum), Combivit at a concentration of 5 g/kg of the meat filling , and dried pork plasma.The main meat raw material for the RTE preservative-free meat bars with pork plasma production was chilled boneless pork ham  was 1364 kJ in 100 g and was composed of fat 2% (including saturated fatty acids 0.8%), carbohydrates 2% (including sugars 1%), protein 74.9%, and salt 11.9%. The mineral components of the dried plasma were (in 100 g of the product) calcium (108 mg), phosphorus (1530 mg), sodium (4750 mg), potassium (651 mg), magnesium (24 mg), and chlorides (3220 mg). The amino acid composition of dried plasma was as follows (in 100 g of product): alanine (4.19 g), arginine (4.57 g), aspartic acid (6.97 g), cystine (1.72 g), glutamic acid (10.04 g), glycine (2.92 g), histidine (2.7 g), isoleucine (2.85 g), leucine (6.44 g), lysine (6.82 g), methionine (0.75 g), phenylalanine (2.7 g), proline (3.6 g), serine (4.27 g), threonine (4.49 g), tryptophan (1.05 g), tyrosine (3.22 g), and valine (5.62 g).A complete flowchart of the meat bar’s production and the technological parameters at the control points are shown in On the day the product was delivered to the laboratory , the bars were separated into control and test samples and tested or placed in incubators, respectively.E. coli, Enterobacteriaceae, S. aureus, Campylobacter spp., and yeast and mould. The presence of Salmonella spp. and L. monocytogenes in 25 g of the sample was also determined. Moreover, physicochemical parameters, such as aw and pH, were measured.Control samples constituted the samples tested on day zero . The microbiological tests of the control group included determining the total count of APC, LAB, Test samples were classified as MAP or VP according to the reduced oxygen packing technology. After giving each bar a unique code, an equal number of bars were placed in thermal incubators with different target temperatures for the MAP group  and VP group . The measurement points during storage of the MAP bars were days 1, 3, 7, 10, 14, 17, 21, 24, 28, and 35, whereas the measurement points during the storage of VP bars were days 3, 7, 12, 14, 16, and 21. Definitions of treatments and sampling schemes are shown in S. aureus) and FSC . In addition, on days 7, 14, 21, 28, and 35 for the MAP group and 3, 7, 12, 14, 16, and 21 for the VP group, the pH and aw of RTE meat bars were measured. A simplified diagram of the laboratory experiment is shown in On measurement point, two samples of each MAP and VP group for every researched temperature were removed from each incubator and used for the assessment of the count or presence of examined microorganisms, which included PHC  according to validation standard with reference number ISO 18787:2017 [We determine the a787:2017 .The prepared 1/10 dilutions were tested in a SevenCompact™ pH meter S210 .E. coli, Campylobacter spp., and S. aureus in RTE meat bars after storage on measurement days is presented in ® Automatic System for Counting Quality Indicators .The assessment of the total count of APC, Enterobacteriaceae, yeast and mould, ® bottles with a dried culture medium and filled with 3 mL of sterile water to create a 1/40 concentration. In order to dissolve the culture medium and homogenate thoroughly, it was vortexed for 10 s . For results that fell outside the 1:40 dilution cutoff, further dilutions of 1/400, 1/4000, 1/40,000, 1/400,000, and 1/4,000,000 were prepared.On subsequent measurement days, bars were aseptically opened and homogenised . Next, 1 mL of the sample was added to TEMPO2 incubator type CB-150, Binder GmbH, Tuttlingen, Germany) to determine the count of LAB (30 °C/48 h), APC (30 °C/24 h), Enterobacteriaceae (35 °C/24 h), yeast and mould (25 °C/72 h), E. coli (37 °C/24 h), S. aureus (37 °C/24 h), and (Campylobacter spp. (42 °C/48 h).After hermetically filling, cards were incubated (COAfter a defined incubation period (measurement days), the cards were read, and the count of specific microbes was calculated based on the number and size of the positive microtubes (fluorescence or lack of fluorescence) and the statistical method of analysis (Bernoulli diagram to estimate the most probable number). Results were presented as the logarithm of the number of colony-forming units per gram of product (log cfu/g). The arithmetic mean with the standard deviation from three repetitions was calculated and thus presented. For data for which the numerical variability was sufficiently high (α = 0.05), we developed mathematical models of microbial growth/survival.L. monocytogenes and Salmonella spp. in a meat bar after the incubation period in question at nine various storage temperatures , we used a mini VIDAS® Compact Immunoassay Analyzer  [To assess the presence of  France) ,29.L. monocytogenes and the second for Salmonella spp. identification. Next, 225 mL of Half-Fraser Broth and 0.5 mL of LMX Supplement were added to 25 g of the bar prior to 2 min homogenisation. The exact amount of Buffered Peptone Water and one tablet of Salmonella Supplement was added to the sample before homogenisation for Salmonella spp. identification.On each measurement day, the meat bars were opened aseptically, and 25 g samples of each were placed in two bags: the first for L. monocytogenes identification were incubated at 37 °C for 26 h, and samples intended for Salmonella spp. identification were incubated at 42 °C for 24 h. Next, 2 mL of each test sample were transferred to microtubes to heat at 95–100 °C for 5 min in a water bath.After homogenisation, samples intended for L. monocytogenes identification suspension was overlaid on the sump of the LMX strap previously put in the analyser with a pipette internally coated with specific antibodies against L. monocytogenes. The same operation applies to the sample for Salmonella spp. identification, differing in volume (0.5 mL of suspension) and the types of straps (SPT straps).After the heating stage, 0.25 mL of ® analyser delivers the sample examination results after 50 min for Salmonella spp. and 60 min for L. monocytogenes identification using the enzyme immunofluorescence ELFA technique (Enzyme-Linked Fluorescent Assay).The mini VIDASw is water activity; X is the population of microorganisms (log cfu/g); r is the growth constant (1/h); γwa is the coefficient describing the effect of water activity on bacterial growth; and γpH is the coefficient describing the effect of pH on bacterial growth:We assumed that the bacterial kinetics model proposed to explain the investigated growth/survival processes carried out during storage at temperatures of 4, 8, 12, 16, 20, 24, 30, and 34 °C is described by a two-term functional relationship in Equation (1), where A, B, and K are the constants in the model; pH is the reaction of the environment; apH coefficients (Equation (3)) in the model, taking into account the influence of pH on the count of microorganisms, and γwa (Equation (2)). Reckoning with the impact of aw on the count of microorganisms ensures its best fit to the experimental data. The form of the γpH and γwa coefficients is analogous to what was proposed when determining the influence of temperature on the biotechnological processes studied [w and pH are 0.87, 0.95, and 0.99 and 4.2, 6.7, and 9, respectively.We examined the location of the γ studied . The minw(t) were determined by searching based on experimental data for unknown values of the coefficients rpH, KpH, and rwa and Kwa, respectively, in differential Equations (4) and (5):The instantaneous values of pH(t) and apH and γwa coefficients to speed up the numerical solution of the model equation.The appropriate algebraic Equations (6) and (7) describing the instantaneous values of pH(t) and wa(t) were used to determine the values of the γpH, γwa, K, A, and B in the model consisting of Equations (1)–(3) and (6)–(7). This package was used in the MATLAB 2021a environment . The objective function, Jc, was in the following form:The optimisation procedure, knitro_nlp, implemented in the Knitro 12.4 package , was used to determine the values of the searched coefficients r, γThe values of the coefficients sought were determined as a solution to the optimisation problem. Likewise, the same procedure, with the appropriate form of the objective function, was used to determine the unknown values of the coefficients in Equations (4) and (5).Statistical analysis was performed using Microsoft Excel 2019  using a one-way analysis of variance (ANOVA).t-test with the Bonferroni correction at a significance level of α = 0.05.Multiple means repetitions were performed using the Student’s S. aureus, and yeast and mould) in the samples of RTE meat bars from VP_C and MAP_C groups are presented in The raw experimental data of the microbial group counts .The APC values in the MAP_C bars remained practically the same throughout the entire storage period; they reached 4.23 log cfu/g at 4 °C and 4.43 log cfu/g at 8 °C. VP_C bars showed a similar tendency for the count of aerobic microorganisms to MAP_C bars. However, their values were slightly higher than half a log unit at 5.17, 5.16, and 5.30 log cfu/g at 4 °C, 6 °C, and 8 °C, respectively. ANOVA showed that the effect of storage time on the count of aerobic microorganisms in RTE bars stored at 4, 6, and 8 °C for both MAP_C and VP_C groups was not statistically significant (p < 0.01) in LAB count was observed on day 10 (Δ = 1.61 log cfu/g). In the MAP_C bar at 8 °C, the maximum LAB count was reached on day 35 (3.94 log cfu/g), and the most significant increase in LAB count was on day 10 (Δ = 1.80 log cfu/g). The VP_C bars had a higher initial LAB count on day 0 (3.76 log cfu/g) than the MAP_C bars; however, unlike the MAP_C bars, LAB count in the VP_C bars tended to decrease from day 0, except on day 12, when the maximum LAB count reached 2.92 log cfu/g, 3.07 log cfu/g and 3.83 log cfu/g at 4 °C, 6 °C, and 8 °C, respectively.LAB count in MAP_C bars showed low numerical variation during storage at 4 °C. The initial value on day 0 was 2.02 log cfu/g, with a maximum on day 17 (2.75 log cfu/g). The largest statistically significant increase  and a minimum on day 10 (0.77 log cfu/g). Statistically significant (p < 0.01) increases occurred on day 7 (Δ = 1.04 log cfu/g), 14 (Δ = 0.78 log cfu/g), and 21 (Δ = 1.10 log cfu/g). A similar increase of approximately one log unit was observed in the MAP_C bars at 8 °C on days 7 (Δ = 0.98 log cfu/g), 14 (Δ = 1.93 log cfu/g), and 21 (Δ = 1.01 log cfu/g).S. aureus count was less dispersed, with 1.12 log cfu/g of the initial count on day 0. At 4 °C, the count of S. aureus peaked on day 21 (2.00 log cfu/g), with significant increases recorded on day 12 (Δ = 0.95 log cfu/g) and day 21 (Δ = 0.98 log cfu/g). Similar S. aureus behaviour in VP_C bars could be observed during storage at 8 °C; maximum S. aureus count on day 21 (2.16 log cfu/g) and significant increases of 1 log unit on day 21 (Δ = 1.05 log cfu/g). S. aureus counts in the VP_C bars stored at 6 °C reached their maximum on day 14 (2.20 log cfu/g) and a significant increase (over 0.5 log units) on day 21 (Δ = 0.84 log cfu/g).In the VP_C bars, the numerical variability of In the VP_C and MAP_C bars, the growth of yeast and mould was rarely detected. In MAP_C bars stored at 4 °C and 8 °C, it was detected only on 4 out of 11 measurement days  and exceeded 1 log cfu/g only once (MAP_C bars at 8 °C on day 28). The presence of yeast and mould on day 0 was 0.33 log cfu/g in the VP_C bars.E. coli and Campylobacter spp. counts in the refrigerated meat bars (VP_C and MAP_C) compared to the initial counts on day 0 (0 log cfu/g). Also, no change in the Enterobacteriaceae count was observed in the VP_C and MAP_C meat bars. The exceptions were results obtained for samples stored at 4 °C , 6 °C , and 8 °C , for which the values were 0.80 ± 1.13 log cfu/g, 0.77 ± 1.08 log cfu/g, and 0.33 ± 0.47 log cfu/g, respectively.There was no change in the Salmonella spp. and L. monocytogenes were not found (not detected in 25 g) in VP_C and MAP_C bars during every measurement day of the storage test.S. aureus, and yeast and mould in the VP_NC and MAP_NC RTE meat bars are shown in The raw experimental data of APC, LAB, p < 0.01) increase in APC values in the MAP_NC bars stored above day 17 at 12 °C (Δ = 1.63 log cfu/g) and at 16 °C (Δ = 1.76 log cfu/g). During storage at higher temperatures, the increase in APC values in the MAP_NC bars was observed much earlier: above day 10 at 20 °C (Δ = 1.01 log cfu/g), above day 3 at 24 °C (Δ = 1.30 log cfu/g), above day 1 at 30 °C (Δ = 1.56 log cfu/g), and above day 7 at 34 °C (Δ = 1.33 log cfu/g). Maximum APC values in the MAP_NC bars were reached at the latest on day 28 at 12 °C (6.34 log cfu/g), while at the earliest on day 10 at 30 °C (8.84 log cfu/g) and 34 °C (8.85 log cfu/g). The decrease in the APC value for the MAP_NC bars at 34 °C stored above 10 days (Δ = −1.70 log cfu/g) was statistically significant (p < 0.01).The initial (measured at “Day 0”) APC value in the MAP_NC bars was lower (4.43 log cfu/g) than the initial APC value in the VP_NC bars (5.12 log cfu/g). At non-refrigeration temperatures, there was a statistically significant  and 12 (Δ = 0.66 log cfu/g). At other non-refrigeration temperatures, the fluctuations of the APC value relative to the initial value remained below half a log unit, reaching a maximum APC value on day 16 at 12 °C (5.58 log cfu/g) and 16 °C (5.50 log cfu/g), day 12 at 20 °C (5.62 log cfu/g), and day 7 at 24 °C (5.84 log cfu/g).The initial count of LAB in the MAP_NC bars (2.02 log cfu/g) was lower than in the VP_NC bars (3.76 log cfu/g); however, it should be noted that the wide standard deviation of the count of LAB in the VP_NC bars showed the resultant variability. LAB surge in the MAP_NC bars occurs at the latest after 7 days of storage at 12 °C (Δ = 1.08 log cfu/g) and at the earliest on day 1 at 20 °C (Δ = 1.74 log cfu/g), at 24 °C (Δ = 1.55 log cfu/g), at 30 °C (Δ = 2.97 log cfu/g), and at 34 °C (Δ = 2.92 log cfu/g). The lowest peak of LAB count in the MAP_NC bars was on day 35 at 12 °C (5.43 log cfu/g), and the highest peak was on day 24 at 30 °C (8.70 log cfu/g).The count of LAB in the VP_NC bars was numerically less diversified than in the MAP_NC bars. The increase in LAB count above the initial value was recorded only twice on day 16 at 20 °C and 24 °C, reaching 4.10 log cfu/g and 4.28 log cfu/g, respectively. Statistically significant increases in LAB count (above 1 log unit) were recorded on day 7 at 12 °C (Δ = 1.07 log cfu/g) and 24 °C (Δ = 1.68 log cfu/g), on day 16 at 16 °C (Δ = 1.96 log cfu/g) and 24 °C (Δ = 1.06 log cfu/g) g), and on day 12 at 20 °C (Δ = 1.55 log cfu/g).S. aureus was 2.44 log cfu/g. Its number showed a downward trend at 12 °C and 16 °C and never exceeded the initial value. At 20 °C, an increase of 2.29 log cfu/g was observed on the third day of storage (reaching a maximum of 3.47 log cfu/g), and then from day ten onwards, the count of staphylococci gradually decreased. Also, at 24 °C, the count of S. aureus significantly increased by 1.54 log cfu/g on day 10 (reaching a maximum of 3.31 log cfu/g), subsequently decreasing. At 30 °C, three significant (p < 0.01) increase peaks have been seen: on day 3 (Δ = 1.98 log cfu/g), 10 (Δ = 3.08 log cfu/g), and 17 (Δ = 1.90 log cfu/g). A similar trend has been observed in S. aureus growth when stored at 34 °C in the MAP_NC bar; the bacteria count increased significantly on day 3 (Δ = 1.88 log cfu/g), day 10 (Δ = 1.10 log cfu/g), and day 17 (Δ = 1.25 log cfu/g).The MAP_NC bars initial count of S. aureus count in the VP_NC bars (1.12 log cfu/g) was lower than in the MAP_NC bars (2.44 log cfu/g). The trend in the count of S. aureus in the VP_NC bars was essentially constant and exceeded 2 log cfu/g only on day 12 at 12 °C (2.02 log cfu/g), 16 °C (2.01 log cfu/g), and 20 °C (2.18 log cfu/g), and on day 14 at 12 °C (2.19 log cfu/g).The initial There was no evidence of yeast and mould growth in the MAP_NC bars directly after production (when tested on day 0). The VP_NC bars on day 0 were characterised by a low yeast and mould presence at a level equal to 0.33 log cfu/g. No yeast or mould was found in the VP_NC bars at 16 °C and 24 °C on the measurement days during storage for three weeks. In the VP_NC bars at 12 °C, the only growth was observed on day 14 (1.26 log cfu/g). At 20 °C, yeast and mould were present on days 12, 16, and 21, reaching 1.55 log cfu/g, 1.22 log cfu/g, and 1.47 log cfu/g, respectively.Different yeast and mould growth dynamics were observed in the MAP_NC bars. The growth started the latest on day 10 at 12 °C (1.00 log cfu/g) and the earliest on day 1 at 24 °C (2.52 log cfu/g) and 30 °C (0.58 log cfu/g). Maximum values of yeast and mould count in the MAP_NC bars were reached on day 17 at 30 °C (5.88 log cfu/g) and 34 °C (6.03 log cfu/g), showing a statistically significant upward trend.E. coli and Campylobacter spp. were not found in any MAP_NC and VP_NC bar samples.n = 198): on day 3 at 16 °C, 24 °C, and 34 °C, with an average count of 1.16 ± 1.65 log cfu/g, 1.12 ± 1.58 log cfu/g, and 1.04 ± 1.47 log cfu/g, respectively, and on day 7 at 16 °C, with an average of 0.43 ± 0.61 log cfu/g.The lack of growth throughout the storage test was also shown for the Enterobacteriaceae in the VP_NC bars. In the MAP_NC bars, intermittent growth of Enterobacteriaceae occurred only for 2% of bars  changes in pH and aw occurred only for the MAP_NC bars at temperatures as low as 24 °C. However, the most noticeable pH and aw decrease between day zero and the end of the experiment occurred in bars stored at 30 °C and 34 °C. The initial and final pH values were 0.68 and 0.83, respectively, and the difference between those values for aw was 0.037 and 0.049, respectively.The sensitivity analysis showed no statistically significant changes in pH and apH and γwa coefficients were tested in the AC model (Equation (1)). The best fit, measured by the value of the coefficient of determination R2 .pHγ and waγ coefficients were also tested, i.e., these coefficients and their product separately. After analysing the value of the coefficient of determination R2 calculated for all temperatures, it was found that the introduction of the pHγ and waγ coefficients into the model did not significantly improve its fit; therefore, the final form of the AC bacterial colony behaviour model is in the form of Equation (11):For this form of the model, all possible combinations of 2 value as a function of the r parameter, as presented in Small changes in the RCampylobacter spp., Enterobacteriaceae, and E. coli in the MAP_C and MAP_NC bars was practically not found; therefore, the process of determining the coefficients in the model was not carried out for them. The VP_NC and VP_C bars also showed no increase in Campylobacter spp., Enterobacteriaceae, and E. coli count above the minimum detectable value (10 cfu/g). Moreover, occasional results above 10 cfu/g in the yeast and mould count in the MAP_C, VP_NC, and VP_C bars also provided too little of an elemental database for determining reliable mathematical models.In the tests, the presence of S. aureus in the MAP_NC and MAP_C bars, as well as the count of APC, LAB, S. aureus, and yeast and mould in the MAP_C, VP_C, and VP_NC bars, causes the curves of the mathematical models to not show fundamental differences between changes in the four theoretical growth/death phases of microorganisms. The nature of the model lines for the microorganisms mentioned above is relatively constant, which means that particular storage conditions  do not significantly affect their growth. Therefore, they were not included in this publication.Low numerical variability of changes in the count of We carried out statistical analysis for all the experimental results obtained; nevertheless, for the data on lower storage temperatures, we did not observe statistically significant differences and large variability in the abundance of individual microorganisms or groups of microorganisms, in contrast to the data on higher (but still non-refrigerated) temperatures. As a result of these observations, we applied a mathematical modelling tool to illustrate the nature of the observed phenomena more clearly. The use of statistical analysis and mathematical modelling of some of the experimental data is not contradictory but complementary; ANOVA showed whether there were statistical differences between the results, and mathematical modelling was used to describe the trend of microbial counts in RTE meat bars where the differences are high and significant. Model curves showing the growth phases for APC, yeast/mould, and LAB in the MAP_NC bars are shown in Using modelling, the predicted lag phase for APC in the MAP_NC bars at 12 °C A lasts uThe growth curve for LAB in the MAP_NC bars at 16 °C is similar B. A logaThe APC growth curve modelled for the MAP_NC bar stored at 20 °C C does noIn general, the course of the growth curves for microorganisms in the MAP_NC bars stored at 24 °C D is simiNoticeable changes compared to the previous measurement temperature (30 °C) occur in the models of APC and yeast and mould counts for the MAP_NC bar at 34 °C F. In thew was 0.95, which means that the product tested is a food matrix, supporting the growth of L. monocytogenes [w changes in the MAP bars during storage at temperatures higher than 30 °C, which argues in favour of vacuum packaging of the bars due to a more physicochemically stable environment for background microflora [The premise of not using preservatives in the production of RTE meat bars with dried blood plasma is a significant challenge for food operators to ensure the product’s safety, especially if FBOs want to store it outside refrigerated counters. Our research has shown that the product tested as a preservative-free RTE meat bar is safer and lasts longer for human consumption during vacuum packaging than modified atmosphere packaging. The average pH of the RTE no-preservative meat bars was 6.1, and the acroflora .In our study, organoleptic signs of spoilage occurred as early as the seventh day after production when the MAP bars were stored under unrefrigerated conditions. Organoleptic changes included an exacerbated sour smell, a change in the bar’s texture from elastic to soggy, and the appearance of a yellow and cloudy discharge of meat juice, which was caused mainly by the growth of LAB, mesophilic aerobic bacteria, and yeast and mould, as shown by the results obtained. The most noticeable growths of mould thallus were in the MAP_NC bars at 24 °C and 30 °C, starting from day 7 of storage. The maximum yeast and mould count was detected in the MAP_NC bars stored at 24 °C (4.68 log cfu/g on day 14) and 30 °C (5.88 log cfu/g on day 17).Aerobic mesophilic microorganisms generally remained at the same level in the VP_C and MAP_C bars. Their initial count was relatively high (approx. 4.5–5 log cfu/g) compared to most RTE products on the market (approx. 3 log cfu/g) . On day LAB count in the MAP_C bars stored at 4 °C remained similar throughout the entire storage period; packing in MAP technology and storage in refrigeration conditions did not support LAB growth. In comparison, clear upward trends were seen when the bars were stored at 8 °C and above. The temperature most conducive to LAB growth in the MAP_NC bars was 30 °C. LAB population in the MAP_NC bars stored at 34 °C reached the death phase on day 14 of storage, as shown in The VP technology did not significantly affect LAB count. Moreover, our research confirms the theory that claims that the growth of LAB in VP products had little impact on the deterioration of the product’s organoleptic characteristics . It was Lactobacillus plantarum in cooked chopped vacuum-packed RTE pork stored at various temperatures. It has been shown that the phase of the rapid growth of L. plantarum as an exponential function began on day 0 when stored at 16 °C and on day 4 at 10 °C. When storing the product at 4 °C, the growth of L. plantarum started on the 24th day. Nevertheless, it has not reached an exceeding value, which causes deterioration of product quality and risk to consumer health. The results obtained regarding the count of LAB during the storage of RTE meat bars are also in line with the conclusions [However, the LAB results presented are consistent with the findings of other authors  who modeclusions ; howeverclusions ,38 that S. aureus; its number remained at a similar level as the initial count (shortly after production) or had slight numerical fluctuations. In our opinion, the initial number of S. aureus in the meat bars, despite implementing good production practices and procedures based on HACCP principles at the production facility, was relatively high (approx. 2 log cfu/g). We recorded high levels of S. aureus at the production stage, indicating that the product was intraoperatively contaminated. Our conclusions align with the results of other researchers [S. aureus in dry cured meat products and found S. aureus in 13.4% (n = 83) of the products. S. aureus was also more prevalent on food contact surfaces during production than immediately after cleaning procedures. Since the food safety criterion is not S. aureus but the toxins produced by it, in further research, the sequencing of genes encoding enterotoxins  from isolates we obtained from stored RTE bars are considered.The storage of bars packed in ROP technology (VP and MAP) did not significantly support the growth of earchers  who inveThe yeast and mould count in the MAP_NC bars increased as the storage temperature increased, reaching a maximum growth rate at 24 °C and 30 °C. We found the presence of yeast and mould in the VP_C and MAP_C bars very rarely. This is consistent with studies of cooked RTE ham , during Our study experienced high standard deviations, often due to detecting yeast and mould in one of three replicates. An explanation for this phenomenon could be the survival of yeast and mould cells present in the product due to contamination; for example, at the packaging stage. These results lead to the need to extend research to all stages of the production process, which may result in new solutions to reduce yeast and mould contamination after heat treatment.E. coli, L. monocytogenes, Salmonella spp., Campylobacter spp., and Enterobacteriaceae; we draw this conclusion based on storage tests, which do not indicate the presence or growth of these pathogens during shelf life testing, regardless of employing the ROP technology that the bar was packaged. Nevertheless, to be completely certain of this conclusion, we plan to extend the research presented with a challenge test involving artificial contamination to determine the growth potential of individual pathogens.The results indicate that RTE bars produced without preservatives with the addition of dried plasma do not pose a risk to consumers regarding infection with L. monocytogenes results are consistent with some reports [E. coli, the first group of microorganisms in their research initially obtained a count of 1.25 log cfu/g with max. 5.57 log cfu/g on day 21 (VP group) and 1.4 log cfu/g with max. 3.09 log cfu/g on day 30 (MAP group), while the latter was initially not detected but reached the maximum on day 30 at 4.04 log cfu/g (VP group) and 2.94 log cfu/g (MAP group); no common point can be found compared to our results.The  reports ; howeverThe presented results of Enterobacteriaceae counts align with the previous research , where iL. monocytogenes in the 25 g MAP_NC bars, which may be related to the high count of background microflora, especially LAB. Similarly [L. monocytogenes at different temperatures in the RTE-cooked ham packed in a modified atmosphere was observed, depending on the count of LAB.We did not detect any imilarly , a noticPrevious researchers  successfMany authors use the Gompertz model to calculate the use-by date of food products. The modified Gompertz function (after re-parameterisation) is a commonly used empirical one. Despite its widespread use, the Gompertz model has weaknesses, which include non-horizontal course and estimation of the negative lag value of the phase or imprecise expression of the maximum growth rate of the population by the inflexion point of the curve, which suggests that the maximum growth rate may be higher than the estimated growth rate .2 permeability film at three different temperatures , 14 (at 8 °C), and 30 (at 0 °C).Based on mathematical modelling, we reached similar conclusions to previous researchers  on the cAdhering to the criteria proposed for RTE food products  for deteTo produce the RTE high-protein meat bars with blood plasma, which will be stable at non-refrigerated temperatures, FBOs must abandon the premise of producing preservative-free products or use alternative methods of microbial reduction, such as physical , chemical , and biological (bacteriophages) methods ,57,58,592 and 20% N2 used in the research is the most commonly used MAP gas mixture in the USA [2 share from 100%, the count of Enterobacteriaceae, Pseudomonas spp. and, above all, LAB, increased. Similar conclusions were reached [2 than 30% CO2 MAP technology; however, no significant differences in LAB counts were observed.The next point of consideration is adjusting the optimal gas mixture in MAP. The mixture of 80% CO the USA . A study the USA  proved t reached , where l2 level among the tested groups (40% CO2 and 60% N2).Congenial research was carried out , where tThe success of active packaging in microbial control may vary depending on other external factors . Consequently, intelligent packaging devices that detect microbial loads and species prevalence can be cost effective for producers. These indicators can also inform industry stakeholders of the need to take action on microbial levels; this means that it is not right to expect microbial levels to remain below the threshold of acceptability indefinitely; an acceptable level of safety should also be maintained between processing and consumption, and it is up to the food manufacturer to assess the safety of the solutions used .RTE preservative-free meat bars with blood plasma are undoubtedly an innovative product newly created due to consumer demand. Their high protein content, the absence of chemical food preservatives, low production processing, and intention for readiness to eat (without the need for heat treatment before consumption) increase the likelihood of the product spoiling sooner than expected. Therefore, all newly created alternative products require precise shelf life testing under adequate temperature stress.2 concentrations above 20%.Our research concludes that packaging methods and storage conditions are critical to meeting the food safety criterion (FSC) and ensuring pork meat bars’ expected shelf life (FSC and PHC). Considering the results we obtained for all tested groups of microorganisms, the preferred reduced oxygen packaging (ROP) for ready-to-eat preservative-free meat bars with dried plasma is vacuum packing followed by refrigeration storage, optimally at 4 °C (max. 8 °C). The consideration of packaging RTE bars using MAP technology is warranted if the tests are extended to individual gas mixture compositions, assuming the use of COAs the durability tests showed, the optimal shelf life for VP bars is 14 days when stored at 4 °C, 12 days at 6 °C, or 10 days at 8 °C. Extending the shelf life of vacuum-packed and refrigerated bars is only possible if additional hurdles  are implemented and scientific evidence of their effectiveness is provided.The production of additive-free bars requires the implementation of good hygiene practices at the plant to the highest level. Consideration should be given to isolating a microbiological high-risk zone in the production area, which includes the packaging stage, as a control measure for the microbiological hazard of recontamination of the product.L. monocytogenes in any 25 g sample, there is no clear evidence if the pork meat bar with dried plasma is a food that does or does not support the growth of L. monocytogenes. Taking into account the average pH and aw values of the bars, we assess that this product should be classified, according to Regulation 2073/2005, as food category 1.2 ready-to-eat foods able to support the growth of L. monocytogenes, other than those intended for infants and special medical purposes [Although we did not detect the presence of purposes , unless


BackgroundAsthma is a chronic inflammatory disease with its control being affected by underlying oxidative stress. Trace elements, along with vitamin D3, play an important role in immune alterations leading to an imbalance of Th1/Th2 helper cells. However, their role in asthma pathogenesis and control is inconsistent and inconclusive. The objective of our study was to assess levels of serum trace elements like zinc, copper, selenium, iron, magnesium, vitamin D3 levels, IgE, and HsCRP in asthmatic children, compare with healthy controls, and assess their association with the level of asthma control.MethodsA cross-sectional study was conducted from 2019 to 2021 enrolling 100 asthmatic children and 75 healthy controls. The level of asthma control was assessed as uncontrolled, partly controlled, and controlled asthma as per GINA Guidelines. Mean and standard deviation were calculated for each element and mean differences between groups were analyzed by student t-test. A p-value of <0.05 was considered significant.ResultsThe mean age was 8.75±2.89 yrs in cases and 9.04±2.79 in controls. A total of 57.6% of cases had atopic comorbidities. The mean serum zinc levels were 51±12.8 mg/dl, which was very low in asthmatic children as compared to 60±18.2mg/dl  in healthy controls. Serum selenium was 13±3 µg/dl in asthmatics vs. 15±4 µg/dl  in healthy controls. Serum copper was 115.2±21.92µg/dl vs. 125.3±31.99µg/dl , Serum vitamin D3 levels were 13.07±7.82ng/ml vs. 17.82±14.62 ng/ml in both groups, respectively. SIgE and HsCRP were high in asthmatic children suggestive of eosinophilic inflammation. Serum zinc was 49±5.45 mg/dl in the uncontrolled group, 53±6.1 in the partly controlled, and 58±8.0 in the well-controlled group (p<0.0001). Serum selenium was 10± 3.0 µg/dl in the uncontrolled group vs. 13± 2.0 and 14± 2.0 µg/dl in the partly controlled and well-controlled groups, respectively . Vitamin D3 was significantly low (9.32±5.95ng/dl) in the uncontrolled group vs. 12.99±4.97 and 13.40±5.92 ng/dl(p<0.005) in the partly controlled and well-controlled groups respectively. Vitamin D3 showed a strong positive correlation with zinc  and a negative correlation with inflammatory markers like SIgE and HsCRP.ConclusionChildren with asthma had low zinc, selenium, and vitamin D3 levels, and were associated with airway inflammation and poor asthma control. Asthma is a chronic inflammatory disorder of the airways characterized by variable bronchial obstruction and hyper-responsiveness . It is aSerum IgE and HsCRP are known to be involved in the inflammatory cascade in asthma ,7. StudiSelection of participantsA cross-sectional intramural-funded, two-center study was conducted from 2019 to 2021. Dr. Ram Manohar Lohia Institute of Medical Sciences (RMLIMS), a tertiary referral center, conducted the study by recruiting subjects referred from the Sanjay Gandhi Post Graduate Institute of Medical Sciences hospital with asthma. All the biochemical tests were done at the Department of Biochemistry RMLIMS after taking ethical consent from the Institutional research committee dated 15.10.2019, IEC NO 23/19.Newly diagnosed patients with asthma aged 5 -15 yrs were enrolled as cases, and age and sex-matched individuals were included as healthy controls. Asthma was diagnosed based on history, examination, and spirometry findings. The control level was assessed as uncontrolled, partly controlled, and controlled asthma as per GINA Guidelines . Simple With a 5% possibility of drop out of samples, a total of 175 subjects were enrolled. One hundred cases with bronchial asthma were enrolled from the asthma clinic and 75 healthy age and sex-matched children were enrolled as controls after taking parental consent. Children with severe malnutrition, refusal of consent, and a history of zinc, vitamin D, iron, oral or inhaled steroid intake in the past two weeks were excluded from the study. Baseline data like age, gender, anthropometric parameters, comorbidities, and parental history of asthma and allergy were collected. A total of 5 ml of venous blood samples were obtained for biochemical estimation. Zinc, selenium, and copper were estimated by using Inductively Coupled Plasma Mass Spectrophotometry (ICPMS) . Serum mData analysisStatistical Package for the Social Sciences SPSS  was used to analyze all data. Mean and standard deviation (SD) were calculated for each element. Frequencies in categorical data were assessed by the Chi-square test. The differences between the asthma group and the control group were compared with an independent t-test mean differences between the two groups. ANOVA test was used to analyze the correlation between serum trace element and level of asthma control and to ascertain whether the difference between these groups was statistically significant (P < 0.05).One hundred asthmatic cases and 75 healthy controls were enrolled in the study. Among the cases, 39(39.0%) were with uncontrolled asthma, 53(53.0%) were with partly-controlled asthma, and 8(8.0%) were with well-controlled asthma. Baseline characteristics like age, gender, and Body mass index were comparable in both groups, as shown in Table The mean age among both groups was 8.75 ± 2.89 years vs. 9.04 ± 2.79 years (p=0.113). Mean weight, height, and body mass index were comparable in both groups. The male:female ratio was 2:1 in both groups. Family history of asthma was present in 26(26.0%) in the case group vs. 7(9.3%)  in the control group. Atopic comorbidities were present in 64 (57.6%) asthmatic cases, out of which 48 (48%) had allergic rhinitis, 12(12%)had allergic conjunctivitis, and 12(12%) had atopic dermatitis.Trace elements and vitamin D levels in the asthma case group and healthy controls are shown in Table Table As shown in Table In our study, the levels of the trace elements zinc and selenium were significantly low in asthmatic children as compared to healthy controls. Asthma is an airway inflammatory disease; trace elements may have a role in the inflammatory process.Similar studies -16 have A recent review states overproduction of reactive oxygen species (ROS) has been implicated in the development of asthma  . Thus, Monitoring and managing zinc levels may be a new therapeutic modality in asthmatic patients with low vitamin D3. Selenium acts by inhibiting reactive oxygen species (ROS) production and chronic inflammation. We found that asthma cases had a lower level of selenium than controls, which may be because it increased the immune response to allergens by increasing T-helper responses . Low selOn the other hand, iron is a critical element in many oxidative reactions. Only free iron takes part in the inflammatory process producing free radicals. Our findings showed that asthmatic patients had serum iron levels on the lower side of the normal range as in other studies ,25. We dSerum IgE levels were higher in asthmatic vs. healthy controls. Vitamin D insufficiency correlated to higher s IgE and Hs-CRP levels which are markers of eosinophilic inflammation. Vitamin D, a member of the secosteroid family known to play a role in calcium or phosphate homeostasis and bone mineralization, is a potent immunological modulator, and is known to regulate cell proliferation and differentiation . AccordiThe limitations of the study were that we only analyzed serum levels of trace elements and not other tissues like hair and nail, which may reflect the long-term status of the trace elements. Confounders like eating habits and distribution of trace elements sources affecting their absorption would have affected the blood levels. We also did not do an intracellular magnesium assessment, which could be the reason for normal magnesium levels. Since asthma is a clinical diagnosis with multifactorial etiology, levels of trace elements and vitamin D3 can serve as a biomarker for the assessment of asthma. In conclusion, serum analysis of trace elements, zinc, selenium, and vitamin D3 should be considered in the workup of asthma. Low serum zinc and selenium were associated with poor asthma control in our study. An association exists between serum zinc and vitamin D3 levels, thus signifying their role in airway inflammation. Further studies on intervention to change the levels of trace elements underlying the structure-function changes in asthma, particularly in poor asthma control, are needed.Serum zinc, selenium, and vitamin D3 levels were very low in asthmatic children and were significantly low in the uncontrolled group. Since asthma is a clinical diagnosis with multifactorial etiology, trace elements levels, and vitamin D3 can add value and serve as a biomarker for their assessment. Inflammatory markers like HsCRP and serum IgE were also correlated with low vitamin D3 and zinc. We could confer our findings not on the mechanistic approach of each trace element, which was our limitation, but on the clinical data and asthma control in children, which has a translational value. Hence, further studies on intervention to change trace element levels underlying structure-function changes in asthma, particularly in poor asthma control, are needed.


R-squared (R2) shrinkage estimators]. Results showed that the Olkin–Pratt extended adjusted R2 estimator had the least bias and the smallest MSE in estimating υ across conditions. We also applied different estimators of υ in a real data example. Recommendations and guidelines were provided about the use of this estimator.Many currently available effect size measures for mediation have limitations when the predictor is nominal with three or more categories. The mediation effect size measure υ was adopted for this situation. A simulation study was conducted to investigate the performance of its estimators. We manipulated several factors in data generation  and effect size estimation [different  M) that account for the relation between a predictor variable  and an outcome variable . A variety of effect size measures have been developed for mediation analysis. However, most of these effect size measures have limitations, including non-monotonicity and spurious inflation. Lachowicz et al. , which, in turn, causally affects outcome Y (b path). X can have a direct effect on and Y (c′ path), in which X directly influences Y.A simple mediation model shown in M and Y are treated as continuous. Equations 1, 2 are required to estimate the effects of the a path and b path, respectively. The indirect effect of X on Y is the product of a and b. The direct effect is c′ (Eq 2). The total effect is c in X's direct and indirect effects on Y (Eq 4).This model can be estimated by a set of regression models or by structural equation modeling when the effects are linear and X can be dichotomous, or it can be treated as continuous. However, mediation analysis with a multicategorical predictor is common  coded variables are computed to represent each group. Different coding strategies are available, and the choice of strategy depends on the research question. Hayes and Preacher  dummy variables  are constructed, where Di is set to 1 to represent the cases in group i; otherwise, it is set to 0. The kth group is the reference group and is coded 0 in all Dis th group to the kth group . The effects are “relative” because they are based on comparisons between the group i and the other group (s), depending on the coding strategy of Di.Hayes termed X on Y through M. They suggest using R-squared (R2) to capture the overall effect of X on M from Equation 5 and construct the confidence interval for the product of this R2 and b to provide an omnibus test of the indirect effect. They tested the performance of this method using Smith, Wherry-1, Wherry-2, Olkin–Pratt, Pratt, and Claudy R2 shrinkage estimators for R2 . While there is no mathematical proof that the product of R2 and b quantifies the overall mediation effect properly, this method has shown satisfactory results in maintaining the type I error rate at a set level . The zero-order correlation between M and Y has two components: (a) the conditional correlation between M and Y independent of X, and (b) the correlation due to the mutual dependence of Y and M on X. The first component is often referred to as true correlation, and the latter component is considered spuriously inflated. A true correlation between M and Y is needed to create a mediation effect size without spurious inflation :Among the three effect size measures mentioned previously, Lachowicz et al.  modifiedwhere βa is the standardized a path. c′ path. βb is the standardized b path, which captures the true correlation between M and Y in the mediation model. Lachowicz et al. pointed out that b is zero . If there is no direct effect, the spuriously inflated term is zero . As a result, rYM cannot distinguish whether an indirect effect is present. Lachowicz et al. . The term M and Y. Y explained by M and X  is the expectation function, B is the unstandardized regression coefficient, and According to Lachowicz et al., υ has numerous desirable properties as an effect size measure of the indirect effect: (a) It is standardized , (b) it is independent of sample size, (c) its function in the absolute value of the indirect effect is monotonic, and (d) its confidence interval can be constructed. Using Equation 15, Lachowicz et al. proposed sample estimators of υ for the simple mediation model . The firX and Y. The confidence interval of υ can be calculated via non-parametric bootstrapping. Their simulation study found that this estimator had an acceptable bias with only four experimental conditions resulting in percent relative biases > 5% at N = 100. The confidence interval of υ can be constructed using this estimator via non-parametric bootstrapping; their simulation showed that the bootstrapped confidence interval had an acceptable coverage rate  at N = 250.where aib equals ai is the standardized ai path and βai = ai(σDi/σM). In addition, we believe that researchers would be interested in calculating υ for the overall indirect effect of X on Y through M. Equation 15 and its sample estimators are difficult to apply in this situation because of multiple ai paths; thus, we chose Equation 14 and proposed an estimator of υ:Because of the desirable properties of υ, we applied it in a simple mediation model with a multicategorical predictor . We condFollowing Equation 16, we chose n et al. , we hopeR2 and r2 . Based on the results from previous simulation studies on the performance of the shrinkage estimators  A number of groups in n et al. .n = 10, 20, 25, 50, 100. The range of n covered small-to-large sample sizes across groups.(2) Sample size per group, ai paths were manipulated as the mean difference between adjacent groups on M. The mean difference was set in terms of Cohen's d = 0, 0.2, 0.5, 0.8, representing null, small, medium, and large effects, respectively  Effect size of y Cohen, .b path, b = 0, 0.15, 0.39, 0.59. The conditions followed those in Lachowicz et al. ((4) Size of z et al. .Y. The mean difference was set in terms of Cohen's d = 0.1, 0.2, 0.3.(5) Effect size of M, eM, was a normal variable with variance determined by Y, eY, was a standard normal variable. The simulation used a full factorial design with a total of 720 conditions (3 × 5 × 4 × 4 × 3). For each condition, 10,000 replications were created. For each condition and replication, nine b, R , and the packages boot 1.3–20 , and coverage rate. For any parameter θ, bias is the difference between the expectation of the sample estimates In each condition, the population value of υ was calculated using Equation 14. The online Standardized bias is the bias divided by the standard deviation of the sample estimates Mean squared error is the expected squared difference between the sample estimates and the parameter. It is equal to the sum of the variance of sample estimates and squared bias (Equation 20). An unbiased sample estimator would produce an MSE equal to the variance of the estimator.Coverage rate is the proportion of the sample in which the population parameter is contained within the 95% confidence interval across replications in a condition. An acceptable coverage rate is between 92.5 and 97.5% Bradley, .N) and small effect size conditions. The bias of unadjusted N and effect size. For the shrinkage adjusted N would not change the bias. We expected that the MSE of the unadjusted N increased since larger sample sizes decrease both sampling error and bias. For the same reason, we expected that the MSE of the shrinkage adjusted N increased. Finally, for both unadjusted N increased.We expected that the unadjusted ai paths, size of b path, and effect size of post-hoc pairwise comparisons with Tukey's HSD tests and produced boxplots by different conditions within the factor.We conducted one-way analyses of variance (ANOVAs) to study the effects of each manipulated factor . None of the estimators produced satisfactory coverage rates (>0.9) across conditions. The unadjusted post hoc pairwise comparisons of each manipulated factor on the bias, standardized bias, MSE, and coverage rate of z et al. . Based ob path had the strongest effect on the bias of F = 448.22, p < 0.0001; η2 = 0.65. b path conditions. The bias of b = 0.59 was significantly higher than all the other b path conditions. The bias at b = 0.39 was also significantly higher than the b = 0.15 and b = 0 conditions. A higher effect of b path was associated with a more positive bias The size of the ai paths had the second strongest effect on the bias of F = 39.13, p < 0.0001, η2 = 0.14. ai paths. All pairwise comparisons were significant (ps < 0.05) except (d = 0.2 vs. d = 0). The bias of d = 0.8 was significantly lower than d = 0.5, 0.2, and 0. Bias of d = 0.5. The effect size of F = 8.26, p < 0.001 η2 = 0.02. F = 3.20, p < 0.05, η2 = 0.009  = 0.57, p = 0.69, η2 = 0.003.The effect size of  = 0.009 . The biab path had an effect on the standardized bias of F = 25.73, p < 0.0001, η2 = 0.10. b = 0.59 with  = 19.98, p < 0.0001, η2 = 0.08. ai paths increased. When d = 0 and 0.2, the standardized bias of d = 0.5, the median standardized bias was < 0.4. When d = 0.8, the standardized bias of F = 0.25, p = 0.78, η2 = 0.001.The size of the .59 with . When b F = 2.84, p = 0.06, η2 = 0.008. Group size had a significant effect on the standardized bias of F = 7.66, p < 0.0001, η2 = 0.04. n= 10 (median > 0.4), and its standardized bias was significantly more positive than those in other conditions (ps < 0.05). The median standardized bias was >0.4 when group size = 25 and 100. When group size = 100 and 200, the median standardized bias was < 0.4.The number of groups had no significant effect on the standardized bias of b path had a significant and large effect on the MSE of F = 301.85, p < 0.0001, η2 = 0.56. MSE of b increased , and the MSE at b = 0.39 was significantly higher than those at b = 0.15 and 0 (ps < 0.05). When b = 0 and 0.15, the MSE were close to zero. The effect sizes of ai and ai: F = 0.90, p = 0.44, η2 = 0.004; F = 2.29, p = 0.10, η2 = 0.006].The size of the ncreased . The MSEF = 1.11, p = 0.33, η2 = 0.003. Group size had a significant effect on the MSE of F = 23.18, p < 0.0001, η2 = 0.12. ps < 0.05). When group size = 25, 50, and 100, the median MSEs were close to zero.The number of groups had no significant effect on the MSE of b path had a significant effect on the coverage rate of F = 99.18, p < 0.0001, η2 = 0.29. All pairwise comparisons were significant (ps < 0.05). b increased, and only when b = 0 did ai paths had a significant effect on the coverage rate of F = 2.24, p < 0.0001, η2 = 0.08. d = 0 had a significantly lower coverage rate than all other conditions . For d = 0.2, 0.5, and 0.8 conditions, F = 0.01, p = 0.99, η2 < 0.0001. None of the conditions for The size of the F = 1.83, p = 0.16, η2 = 0.005. Group size had a significant effect on the coverage rate of F = 36.26, p < 0.0001, η2 = 0.17. ps < 0.05). Group size = 10 reached the satisfactory cutoff with a mean coverage rate of 0.91. The coverage was the lowest at group size = 200.The number of groups had no significant effect on the coverage rate of b path. According to Equation 16, the finite sample adjustment of b and (2) adjusting b path. Therefore, we conducted additional analyses which estimated υ using Equation 14 without finite sample adjustment to βb and with the Olkin–Pratt extended shrinkage method for b (Equation 16), the size of the b path had significant effects on the bias, standardized bias, and MSE of this estimator. We conclude that this estimator did not further improve Results suggest that the performance of via perceived racial and ethnic discrimination. There were 90 participants with completed measures. Race/ethnicity was a multicategorical variable with four groups: non-Hispanic white , Hispanic , Afro-Hispanic , and others (group 4: n4 = 15). Dummy coding was used and non-Hispanic white was the reference group. The mediator, perceived discrimination , was measured by the Perceived Ethnic Discrimination Questionnaire—Community Version Brief , was calculated as the percentage (0 to 100%) of doses taken on schedule as assessed by the Medication Event Monitoring System  Medication Adherence Study at the Icahn School of Medicine at Mount Sinai (ISMMS) in New York City. We were interested in the mediation process between race/ethnicity and antiretroviral medication adherence R2 shrinkage methods. Similar to simulation results, all R2 shrinkage methods were performed equally, with via perceived discrimination was equal to 0.15. All adjusted b path was the most important factor that negatively influenced the accuracy of the sample estimator of υ. In our data generation process, there were no large differences between the effect sizes of the a path and those of the b path. On further scrutiny, the performance of the sample estimator with uncorrected b path remained undiscovered. R2 shrinkage methods produced slightly less biased υ estimates. The R2 shrinkage methods performed similarly on adjusting R2 shrinkage methods might not be the source of high values of bias, standardized bias, and MSE.The goal of this study was to extend the mediation effect size υ developed by Lachowicz et al.  to mediaSince b path reaches 0.39–0.59, b path  could also result in a large value of MSE in (1) When the size of ai paths have small effects .(2) n = 10.(3) Researchers should pay attention to small group sizes. b path and the bias of the sample estimator of υ. Second, since this effect size measure is appropriate for the mediation model specified in this study, future studies should further develop this effect size measure to be suitable for more complex mediation models, such as models with multicategorical mediators or outcomes, models with moderations or latent variables, and models with multilevel or longitudinal data structures. Finally, since there are more rigorous assumptions that need to be made to justify an indirect effect as a causal effect, it is possible for researchers to introduce unknown bias into the estimation of υ. Future studies should investigate the performance of the estimator when such moderate violations of assumptions occur.There are several limitations to this study. First, further analyses should be conducted on the relationship between the effect of the size of The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.https://reporter.nih.gov/search/XK3XEZYfbEuZQESg5r-YNA/project-details/7681039. The patients/participants provided their written informed consent to participate in this study.The studies involving human participants were reviewed and approved by NIMH-funded study  at the Icahn School of Medicine at Mount Sinai (ISMMS) All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Although indexing effective orifice area (EOA) by body surface area (BSA) is recommended, this method has several disadvantages, since it corrects by acquired fatty tissue. Our aim was to analyze the value of EOA normalized by height for predicting cardiovascular outcome in patients with aortic stenosis (AS).Patients with AS (peak velocity > 2 m/s) evaluated in our echocardiography laboratory between January 2015 and June 2018 were prospectively enrolled. EOA was indexed by BSA and height. A composite primary endpoint was defined as cardiac death or aortic valve replacement. A receiver operating characteristic curve was plotted to determine the best cutoff value of EOA/height for predicting cardiovascular events.p < 0.001) and EOA/height . A cutoff value of 0.60 cm2/m for EOA/height had a sensitivity of 84%, specificity of 61%, positive predictive value of 60% and negative predictive value of 84%. One-year survival from primary endpoint was significantly lower in patients with EOA/height ≤ 0.60 cm2/m  than EOA/height > 0.60 cm2/m. The excess of risk of cardiovascular events seen in univariate analysis persists even after adjustment for other demonstrated adverse prognostic variables . In obese patients, there was an excess of risk in patients with EOA/height < 0.60 cm2/m , but not in EOA/BSA < 0.60 cm2/m2 .Four-hundred and fifteen patients were included . Area under the curve was similar for EOA/BSA (AUC 0.75, We could identify a subgroup of patients with AS at high risk of cardiovascular events. Consequently, we recommend using EOA/height as a method of indexation in AS, especially in obese patients, with a cutoff of 0.60 cm2/m for identifying patients with higher cardiovascular risk. Aortic stenosis (AS) is the most common primary valve lesion in Europe and North America, and its prevalence continues rising as a consequence of the ageing population . EchocarIndexing EOA by body surface area (BSA) represents an intuitively convincing and widely adopted method to adjust for differences in body size. However, normalization for BSA has been criticized in patients with obesity where it corrects not only by body size but also for the acquired fatty tissue , 6. In aOur aim was to analyze the value of EOA normalized by height for predicting cardiovascular outcome in patients with AS, and to identify the best EOA/height cutoff for prediction of high risk of cardiovascular events during follow-up.We prospectively included 415 patients between January 2015 and June 2018 with valvular native AS (peak velocity > 2 m/s). The exclusion criteria were: age under 18 years old, suboptimal acoustic window, concomitant moderate or severe aortic regurgitation, moderate or severe mitral or tricuspid valvular disease, subvalvular o supravalvular aortic stenosis (defined as velocity higher than 1.5 m/s), ascending thoracic aorta diameter less than 25 mm, congenital heart disease  and previous aortic valve surgery. We also enrolled prospectively 66 patients between January 2019 and September 2019 to create a validation group.The study protocol was approved by the Ethics Committee of our center. All the participants gave their consent to participate in the study.2) was calculated using the Dubois formula [Clinical data included age, sex, hypertension, diabetes, history of smoking, hypercholesterolemia, height, weight, chronic renal failure and coronary heart disease. Patients were carefully screened for the presence of symptoms attributable to AS: angina, syncope or dyspnoea using the New York Heart Association functional classification. Body surface area . All tests were conducted by two experienced sonographers. Blood pressure was measured at the time of the echocardiographic evaluation.Parasternal long axis view with zoom was used for measuring the aortic annulus diameter in early systole. Using the pulsed Doppler in the left ventricular outflow tract, placing the sample volume 1 cm below the aortic valve, the time-velocity integral (TVI) was obtained. Stroke volume was then calculated assuming a circular shape of the left ventricular outflow tract. Continuous wave Doppler recording of flow through the valve was performed from the 5-chambers and right parasternal windows to record maximal instantaneous and mean pressure gradients across the aortic valve.2/m2). EOA was also normalized by height .EOA was calculated using the continuity equation. An indexed EOA was estimated as EOA/body surface area , a simplification of the continuity equation, was calculated as TVI of left ventricular outflow tract/TVI of aortic jet.All measurements represent an average of 3 cardiac cycles for patients in sinus rhythm and at least 6 cycles if the patient was in a different rhythm than sinus one. In any case, the estimation of extrasystolic beat was always avoided. Doppler recordings were performed at a sweep speed of 150 mm/s.2, aortic transvalvular mean gradient inferior than 40 mmHg and left ventricular ejection fraction less than 40% [Dobutamine stress echocardiogram was performed when EOA calculated by continuity equation was less than 1.0 cmthan 40% . A low-dthan 40% . DopplerThe systolic time intervals of flow through the aortic valve were measured using the velocity curve from the continuous wave Doppler recording in apical view: ejection time (ET), acceleration time (AT) and AT/ET ratio, as we described previously .2 after stress echocardiography. A “paradoxical” low flow-low gradient severe AS was defined as an EOA smaller than 1.0 cm2, mean gradient less than 40 mmHg, left ventricular ejection fraction above 50% and stroke volume index ≤ 35 ml/m2.For classification purpose, in patients with left ventricular ejection fraction above 50%, mild AS was defined as a peak velocity below 3.0 m/s; moderate AS whether peak velocity was between 3.0 and 4.0 m/s; whilst severe AS was defined when peak velocity was greater than 4.0 m/s. In patients with left ventricular dysfunction, “classical” low-flow low gradient severe AS was defined by a peak velocity > 4 m/s or a mean gradient > 40 mmHg and an aortic valve area that not exceed 1.0 cmThe primary endpoint was a combined endpoint of cardiovascular death and aortic valve replacement. In patients who underwent aortic valve implantation, we used the implantation date to compute the length of follow-up. We also recorded cardiac death, percutaneous and surgical aortic valve replacement. Cardiac death includes death resulting from sudden cardiac death, death due to heart failure, stroke or cardiovascular procedures. Outcome data were retrospectively obtained from patient visits or records, telephone interview, or death certificates when applicable.t test. Categorical variables were expressed as percentages and were compared using chi-square analysis or the Fisher exact test. A receiver-operating characteristic curve was plotted to determine the optimal cutoff value of EOA/height for predicting one-year primary endpoint in patients with AS. The best cutoff value was determined as the value providing a balance between sensitivity and specificity. A receiver-operating characteristic curve of EOA/BSA was also plotted. The area under the curve (AUC) was calculated. The calculated cut-off was then tested in the validation cohort.Continuous variables were tested for normality using the Shapiro–Wilk test. Data were expressed as mean ± standard deviation for continuous variables, and were compared using the unpaired Kaplan–Meier analysis were performed by using the log-rank test to compare survival rates between the groups. Univariate and multivariable analyses of time to events were performed using Cox proportional hazard models. The variables entered into the model were sex, age, left ventricular ejection fraction, peak aortic velocity, indexed left ventricular mass, symptomatic status and EOA/height, based on their demonstrated prognostic value in AS.2/m and EOA/BSA ≤ 0.60 cm2/m2 on primary endpoint in patients with obesity (BMI ≥ 30 kg/m2).To study the predictive value of EOA/height AND EOA/BSA in obese patients, univariable Cox model testing the impact of EOA/height ≤ 0.6 cm2/m in subgroups of patients. Hence, a first-order interaction term (the product of EOA/height ≤ or > 0.6 cm2/m and different categories of subgroups) was systematically included in a Cox multivariable model including EOA/height ≤ or > 0.6 cm2/m and the categories of each subgroup of patients in the whole cohort of patients. A significant interaction was considered in case of a p value for the interaction variable < 0.05. Univariable Cox model testing the impact of EOA/height ≤ or > 0.6 cm2/m on primary endpoint were obtained thereafter in each category of the subgroup of patients.We aimed also at identifying if there was a difference in the prognostic value of EOA/height ≤ 0.6 cmp values < 0.05. For data analysis, the statistical program SPSS version 19.0  was used.Differences were considered significant at 2. Diabetes prevalence was 44%, arterial hypertension 80%, obesity (BMI ≥ 30 kg/m2) 42% and coronary artery disease 42%. Degenerative calcification was the most common cause of AS (92%), followed by bicuspid aortic valve (6%) and rheumatic disease (2%). Overall, aortic peak velocity was 3.77 ± 0.77 m/s, mean gradient 36.3 ± 15.5 mmHg, EOA 1.01 ± 0.35 cm2 and left ventricular ejection fraction 61.1 ± 10.7%.A final sample of 415 patients were enrolled, of which 45 (11%) had mild AS, 181 (44%) moderate AS, 162 (39%) severe AS, 20 (5%) classical low flow-low gradient severe AS and 7 (2%) “paradoxical” low-flow low gradient severe AS. Mean age was 74.8 ± 11.6 years, with 52% women and a body mass index of 29.4 ± 5.0 kg/mValidation group was composed of 4 patients (6%) with mild AS, 25 (53%) moderate AS, 36 (29%) severe AS and 1 (1%) patient with “classical” low flow-low gradient severe AS.p < 0.001) and EOA/BSA . AUC was also similar for predicting 6-month cardiovascular events in EOA/height  and EOA/BSA , and two-year outcomes .Receiver operating characteristics curves Fig.  showed t2/m, EOA/height had a sensitivity of 84% , specificity of 61% , positive predictive value of 60%  and negative of 84% (CI 95% from 78 to 92%), whilst using the guideline-recommended cutoff value of 0.60 cm2/m2, EOA/BSA had a sensitivity of 92% (CI 95% from 84 to 98%), specificity of 38% (CI 95% from 30 to 46%), positive predictive value of 51% (CI 95% from 43 to 51%) and negative predictive value of 87% (CI 95% from 80 to 94%).Table 2/m, EOA/height had a sensitivity of 77%, a specificity of 70%, a positive predictive value of 62% and negative predictive value of 82% for severe AS. However, the cutoff of 0.60 cm2/m2 for EOA/BSA had a sensitivity of 88%, specificity of 50%, positive predictive value of 53% and negative predictive value of 87%.In the validation group, using a cut-off of 0.60 cm2/m and 203 patients with EOA/height higher than 0.60 cm2/m. Baseline characteristics of patients are compared in Table 2/m showed more severe echocardiographic parameters .Complete follow-up was achieved in 100% of the sample. Median follow-up was 322 days (from 1 to 1538 days), without significant differences according to EOA/height group , more cardiovascular deaths , although global mortality did not reach statistical differences .Primary endpoint was reached in 116 patients 28%) during follow-up. There were 57 deaths, of which 33 were from cardiovascular causes. Aortic valve replacement was performed in 86 patients during follow-up. Survival from primary endpoint is presented in Fig. 8% duringp < 0.001), although cardiovascular death did not reach statistical difference . Global mortality did not reach significant differences either .Similarly, there were more combined cardiovascular events in patients with EOA/BSA ≤ 0.60 cm2/m2 . Moreover, two-year survival was 85 ± 6% in EOA/height > 0.60 cm2/m and 27 ± 5% in EOA/height ≤ 0.60 cm2/m (log-rank p < 0.001).One-year survival was 91 ± 4% in patients with EOA/height > 0.60 cm2) in our sample (42% of the patients), of which 54% were women, 21% had mild, 45% moderate and 34% severe AS. Mean age was 75.1 ± 8.3 years and BMI was 34.1 ± 3.4 kg/m2. There was an excess of risk in patients with EOA/height < 0.60 cm2/m , but not in EOA/BSA < 0.60 cm2/m2 .One-hundred and seventy-five patients had obesity .Sensitivity of EOA/height < 0.60 cmp < 0.001).In obese patients with EOA/BSA < 0.60 cm2/m2, sensitivity was 95%, specificity 32%, negative predictive value 92% and positive predictive value of 45%. Youden Index was 27%. AUC of EOA/BSA in obese patients was 0.69  was also observed after adjustment by age, sex, left ventricular ejection fraction, symptomatic status, indexed left ventricular mass and peak aortic velocity  (Table p = 0.24).The excess of risk of cardiovascular events in univariate analysis in patients with EOA/height ≤ 0.60 cm2/m  2.66–7.98, The impact of EOA/height ≤ 0.60 cm2/m was consistent in different subgroups, except for left ventricular ejection fraction where a significant interaction was found  incorporates an EOA < 1 cmis value –16. It cis value , outcomeis value , 19, andradients –23. Thisradients , where eIn contrast, height may be considered a better parameter for adjusting EOA as it is not altered by excessive adipose tissue, remains practically unchanged during adulthood, and allows adjustment for body size differences between different nationalities .Indeed, our data showed that outcome in patients with EOA was not influenced by BMI, that is, in our opinion, one of the strengths of the study.Vulesevic et al. [2. However, we preferred to use clinical outcome because it is recognized as the only endpoint available for defining severity [c et al.  showed tseverity . Tribouilloy et al. [The good predictive capacity for cardiovascular events of EOA/height was also shown by y et al. , with exAlthough it is not the objective of the study, we failed to demonstrate a higher predictive accuracy of EOA/height compared to EOA/BSA, with similar area under the curve for predicting cardiovascular events. Nevertheless, we believe that EOA/height has several advantages over EOA/BSA: 1) EOA/BSA may overestimate the severity of AS in obese patients , whilst The main limitation of our study is, in our opinion, the small sample size, which could make it difficult to obtain statistically significant differences in some results. Secondly, sample data were obtained from a single hospital. Although it may be argued that valve replacement is an end point that is arbitrarily determined during the natural history of the disease, it is noteworthy that referring physicians based their decisions on EOA, peak velocity, mean gradients and symptomatic status, being unaware of EOA/height values. Another probable limitation is the high prevalence of obese patients in our sample, that could influence the results, especially in EOA/BSA. Besides, validation group sample was small. Finally, it would have been interesting to analyze cardiovascular events in asymptomatic patients, but we did not have an adequate sample size to obtain significant results.2/m provides a predictive accuracy for the occurrence of AS-related events.In conclusion, the present study shows that normalization of EOA for height is useful for risk stratification, since we could identify a subgroup of patients at high risk of cardiovascular events. Therefore, EOA/height represents a variable that provides additional information to EOA/BSA in AS, and the cut-off of 0.6 cm