This study investigated the family structure, parent–child pair and inbreeding coefficient of a Tan sheep breeding farm in Ningxia, China. The results can be used as the theoretical basis for selecting excellent breeding stock and making an apposite mating plan; furthermore, it can provide an important scientific basis for the conservation and reproduction of Tan sheep germplasm resources.Tan sheep is a special breed of locally protected sheep in China, one of the best quality meat sheep in the world. Due to the unclear pedigree of the rams on the Ningxia Tan sheep breeding farm, we investigated 74 rams in the field and explored a new method for family division. Genomic DNA was extracted from the blood of breeding rams. Using Plink software, GCTA tools and R language, we analyzed the genetic structure, kinship, and inbreeding coefficient of the breeding sheep, which revealed the genetic relationship between the individuals. The results showed that there was no obvious clustering phenomenon in the PCA, and the genetic background of the samples was similar. The G matrix and IBS distance matrix indicated that most individuals were far away from each other. Paternity testing identified 24 pairs of unknown parent–child pairs, and all the Tan sheep could be divided into 12 families, which provided a reference for sheep breeding. The average inbreeding coefficient based on the ROH of this population was 0.049, so there was a low degree of inbreeding and the rams in the field were able to maintain high genetic diversity. Overall, we explored a more accurate method through paternity and kinship analysis; it provides a scientific basis for pedigree construction, which has an important application value for Tan sheep breeding. As one of the “five treasures” in Ningxia, China, the Tan sheep has tender meat, a very light taste, even fat distribution, rich nutrition, and is the top quality mutton favored by consumers; it is listed as a high-quality sheep breed under national and local protection. Since the 1950s, it has been introduced by more than a dozen other provinces in China, but all of them failed to maintain the original variety characteristics due to unsuitable ecological conditions. Later, due to various factors, the distribution range was significantly reduced; only Yanchi County is listed as a Tan sheep breeding conservation area by the Ningxia Hui Autonomous Region Government and the national Tan sheep breeding farm is also based in Yanchi County. At present, the excellent breeding rams are mainly provided by breeding farms, enterprises, and farmers. However, after long-term, enclosed breeding, decline is likely, due to the consequences of inbreeding.The wrong pedigree will slow down the breeding process and reduce the population’s genetic diversity and the effective populations in animal breeding . For breSingle nucleotide polymorphism (SNP), as the third-generation DNA molecular marker, has the advantages of dense distribution, low typing error, genetic stability and low cost. It is widely used in evolutionary research ,5,6,7,8 A total of 74 male Tan sheep, with complete ear numbers and birth dates, were selected from the Tan sheep breeding farm in Yanchi, Ningxia. Blood samples of 10 mL were collected from the jugular vein in EDTA anticoagulant tubes, upside down to prevent coagulation, brought back to the laboratory at low temperature, and stored in the refrigerator at −80 ℃ for future use.Genomic DNA was extracted from 3 mL blood samples using Promega Wizard Genomic Purification according to the manufacturer’s protocol Kits. Nanodrop 1000  was used to detect the purity and concentration of genomic DNA, and all DNA samples with a ratio of light absorption (A260/280) between 1.8 and 2.0 and a concentration > 50 ng/µL were eligible for genotyping. Individual genotyping was carried out using a 50 K SNP chip .−5. In addition, linkage disequilibrium should be removed when analyzing genetic structure. The window size was set as 1000, the number of moving steps was set as 5, and the r2 threshold  was set as 0.5, which was used to simplify SNPs.We used PLINK (V1.90)  softwarePrincipal component analysis (PCA) transforms multiple linearly correlated variables (SNPs) into a few linearly independent variables with a large explanatory degree of variation through a series of matrix transformations, so as to reveal the genetic background of samples and assist subsequent research. We used PLINK to calculate PCA (--pca 3) and visualized it by the ggplot2 package in Rstudio (V4.1.2) software.https://itol.embl.de/, accessed on 1 November, 2022) to beautify.To calculate the relatedness between pairwise samples, the study used GCTA  tool to Combining the analysis of genetic relationship and structure, we could roughly judge which Tan sheep were closely related and might come from the same family.The individual detection rate and call rate were more than 95%;Minimum allele frequency 0.4;All loci conform to Hardy–Weinberg equilibrium;Linkage disequilibrium was removed, and the spacing between adjacent SNPs on each chromosome was greater than 10 Mb.In order to verify the reliability of the family construction results, considering that paternity testing was used to correct the above grouping, the parent–child relationship was determined by the LOD value of the likelihood method, and the family grouping was determined by combining the aforementioned clustering results. PLINK software was used to specifically screen SNP loci that could be used for paternity testing in this population. The quality control standards were as follows:The genetic diversity parameters of all loci were calculated by Cervus (V3.0.7)  softwareRuns of homozygosity (ROHs), which are generated by the complete transmission of homologous haplotypes from parents to offspring, refer to the continuous segments of homozygous genotypes within an individual and are widely present in all populations . DetectRA total of 64734 SNPs were detected, and 41149 SNPs were left for subsequent analysis after quality control .PCA visualization results showed  that theWe measured the IBS genetic distance ranging from 0.188 to 0.329, with an average distance of 0.297 . In FiguThe relatability value based on the G matrix is shown in Corresponding to the G matrix, the NJ (neighbor-joining) tree showed several branches with 2–3 individuals clustered together, which were, respectively, defined as a family, including family groups 2, 4, 5, 9 and 12. Here, we classified individuals on the same branch as a single family, thus the sample was divided into 14 families . DiffereThrough the above screening, 76 SNPs were identified, and He was about 0.50, with an average of 0.5033. Ho ranged from 0.494 to 0.649, with an average Ho of 0.518 and PIC equal to 0.375, and the cumulative exclusion probability of candidate parents for this combination was greater than 99.99% . With coThe 24 pairs of individuals corresponded to our preliminary family division, and we found that most of the individuals with parent–child relationships were grouped into the same family on the evolutionary tree. In addition, 190351 and 180407 had a parent–child relationship, with an LOD of 2.38 and a confidence of more than 95%, but they were divided into different branches in the evolutionary tree. Therefore, we combined all the branches they were in, this is 12, 13 and 14 in the above The mean an 0.125 . The lowPedigree is crucial to animal genetics and breeding research. However, in the breeding process of individual investors and even farms, there will be inevitable mistakes, resulting in incomplete or incorrect pedigree records, particularly in developing countries . SeveralThe samples we collected were all from the same field, which has been closed breeding over a period of time, with some individuals inevitably having near or far relatives. Hence, no obvious grouping was found and the genetic background was similar in Tan sheep by PCA. The IBS distance matrix and G matrix indicated that some individuals were closely related to each other. Attention should be paid to the mating work between these rams and their female parents in the process of breeding conservation to prevent the risks caused by inbreeding. In addition, there were several individuals clustered separately on the diagonal, which could not be divided into families. Therefore, when constructing the NJ tree, we classified a single and the individual with the closest genetic distance on the tree as the same family, so as to preliminarily determine 14 family groups.Our criteria for screening SNPs refer to the Simmental cattle paternity test in China , except Then, we detected 24 pairs of paternity through paternity identification, with LOD values ranging from 0.28 to 15.63, with confidence higher than 95%, indicating high accuracy. Corresponding to the evolutionary tree, we found that most parent–child pairs belonged to the same branch, and only one parent–child pair (190351 and 180407) was located in different branches. Interestingly, there was a third family between the two, so we combined them to end up with 12 families. On the one hand, it verified the reliability of the family construction mentioned above; on the other hand, it supplemented some unknown parent–child relationships in the field and explored a new method for family division based on SNP markers, which is of great significance for the future breeding work of Tan sheep, by tapping the potential of breeds and protecting breed resources. Since the samples collected were all rams, there are some limitations in mating with ewes; we will add ewe samples to further clarify the individual relationships of Tan sheep and promote breeding efforts in future.Preventing the increase in inbreeding in livestock and poultry is an important issue to ensure the sustainable development of agricultural and animal husbandry production. The inbreeding coefficient is usually used to evaluate the degree of inbreeding of individuals. By comparing various methods for calculating the inbreeding coefficient, it was found that the ROH-based inbreeding coefficient ividuals ,33,34,35 in 2019 . The reaWe investigated the genetic background, family structure, parent–child relationship and the level of inbreeding using 50 K sheep chips on a survey of the Yanchi Tan sheep breeding farm in Ningxia, China. A more accurate method was explored through paternity and kinship analysis; it provides a scientific basis for future selection, breeding and pedigree construction. In addition, the degree of inbreeding in this population was low and the genetic diversity was high. This study is of great significance for the genetic evaluation, new breed selection and breed resource conservation of Tan sheep.


Candida (20.3%), Diutina (2.9%), Filobasidium (1.0%), Kazachstania (33.0%), Pichia (3.9%), Saccharomyces (1.0%), Starmerella (28.2%), Torulaspora (2.9%), and Yarrowia (6.8%). Based on probiotic characteristic analysis of ten selected yeast strains, Kazachstania bulderi KKKS4-1 showed the strongest probiotic characteristics in terms of hemolytic activity, antimicrobial activity against pathogenic bacteria, tolerance to low pH and bile salt and hydrophobicity. Isolated yeasts with probiotic characteristics may be useful in fermented food and animal feed production to improve their nutritional values.This research aimed to evaluate the diversity of yeasts recovered from fermented foods gathered from some areas of Northeastern Thailand. The fermented food items included Pla-som, Nham-pla, Kem-buknud, Isan-sausage, Pla-ra, Mhum-neu, Mhum-Khai-pla, Nham-neu, Nham-mu, Kung-joom, Som-pla-noi, and Poo-dong. Their probiotic characteristics were also investigated. A total of 103 yeast isolates of nine genera were identified using 28S rDNA sequencing. The yeast genera were  Additionally, the ability to use microorganisms to preserve food and create flavorful fermented foods is best reflected in human culinary innovation. This is why a wide variety of fermented foods are produced, consumed and found in almost every country around the world. In some countries, these fermented foods have had an integral role in the food culture for centuries. The method of producing fermented foods is part of the wisdom and culture of each country, which has been passed down from generation to generation for hundreds of years Thailand has a tropical climate because it is close to the equator. Its warm temperature, high humidity and a relatively long rainy season cause food raw materials like meat, fish, grains, fruits, and vegetables to be highly perishable. Preservation and storage of these foods and raw materials is important to extend their shelf-life, ensuring good quality and safety for consumption, especially in rural areas. Hence, fermentation is one of the methods used to preserve food and raw materials in various communities in Thailand Thai fermented foods are similar to other fermented foods because the positive organoleptic changes that occur are the result of an interaction of lactic acid bacteria (LAB) and yeasts. These two groups of microorganisms work synergistically and contribute a significant impact on taste, texture, and odor of foods Candida, Saccharomyces, Lachancea, Pichia, Zygosaccharomyces, Debaryomyces and HanseniasporaD. hansenii, Torulaspora delbrueckii, Kluyveromyces lactis, Yarrowia lipolytica, K. marxianus, and K. lodderae, can tolerate gastric juices, survive in the human intestine, and are highly antagonistic to gastrointestinal pathogens S. cerevisiae var. boulardii, is considered a probiotic strain in humans. This strain is also recommended for the prevention and treatment of various types of gastroenteritis in children and adults Yeasts are the second most important group of microorganisms in fermented foods. They have received less attention than lactic acid bacteria. Most research has reported the presence and role of yeasts in fermented beverages rather than in fermented foods. There are few research reports on the presence of yeasts in fermented foods. These reports discuss yeasts of the genera Nowadays, consumers demand chemical-free, natural and safe foods. Fermented foods with probiotic microorganisms have become foods of choice for health-conscious people To the best of our knowledge, there are few, if any studies, on probiotic yeast diversity in fermented foods, especially in Thai fermented foods. For this reason, the current research aimed to study yeast diversity in various types of Thai fermented foods, namely fermented fish, shrimp, crab, and shellfish products and to investigate their probiotic properties. Isolated yeasts with probiotic characteristics may be useful in fermented food and animal feed production to improve their nutritional values.2.2.1.Thirty-eight samples (n = 38) of various fermented food such as fermented shrimp (n = 5), fish (n = 29), meat (n = 2), pork (n = 1), and crab (n = 1) were collected around the northeastern region of Thailand , specifi2.2.Yeast was isolated from each sample using the spread plate technique of Limtong et al. 2.3.The selected yeast strains were categorized through morphological, physiological, and biochemical means following the methods of Limtong et al. 2.4.2.4.1.The selected yeast strains were determined harmless using the results of a hemolysis assay. Sheep's red blood agar plates were cross-streaked with one loopful of yeast colony and incubated at 35 °C for 48 h. The types of hemolysis were determined according to appearance of zones around colonies. β-hemolysis, γ-hemolysis and non-hemolysis were designated when there were clear zones, green-hued zones and no zone around colonies, respectively.2.4.2.Escherichia coli TISTR 073, Staphylococcus aureus TISTR 029, Enterobacter aerogenes TISTR 1540, and Bacillus cereus TISTR 678, were spread on YPD plates. Then, a sterile cork borer was used to cut 0.8 mm diameter holes into the YPD agar. Aliquots of 100 µL of supernatants were placed into the wells and the plates incubated at 35 °C for 48 h. The results were obtained by measuring the width of the inhibition zones surrounding the wells.The antimicrobial activity of selected yeast strains was assessed using an agar well diffusion method according Ragavan and Das 2.4.3.The acid resistance test was adapted from Aloğlu et al. 0) is the yeast cell count (log CFU/ml) at the initial time, and log CFU/ml (t3) is the yeast cell count (log CFU/ml) after a given incubation time.Where log CFU/ml  was measured using a microplate reader . For the adhesion test, the cell suspension used to obtain the A1 value was mixed well with xylene and incubated for 2 h. The absorbance of the upper phase, containing the cell suspension, was measured at 660 nm (A2). The % adhesion was determined as:Adhesion capability was determined using a modified method of Ragavan and Das 3.3.1.All 103 yeast isolates were from different fermented food products and sources . Pure cuCandida (20.3%), Diutina (2.9%), Filobasidium (1.0%), Kazachstania (33.0%), Pichia (3.9%), Saccharomyces (1.0%), Starmerella (28.2%), Torulaspora (2.9%), and Yarrowia (6.8%). These details are shown in Kazachstania (33.0%) and Starmerella (28.2%), namely Kazachstania sp., Kazachstania bulderi, Kazachstania exiqua, Kazachstania humili, Kazachstania servazzii, Kazachstania turicensis, Starmerella etchellsii and Starmerella roubikii.The 103 isolated yeasts were identified using 28S rDNA sequencing. They were of nine genera including Candida, Saccharomyces, Pichia, and some species in Zygosaccharomyces, Debaryomyces and HanseniasporaKazachstania (33.0%) and Starmerella (28.2%) are two dominant genera that are widely distributed in fermented food samples. Moreover, it is also the first report of Starmerella roubikii found in fish or meat-based fermented foods.Most research on fermented food has focused on the lactic acid bacteria rather than yeast. So, many genera and species of lactic acid bacteria in various types of fish or meat-based fermented foods were screened, isolated, identified and reported Kazachstania and Starmerella are osmophilic yeasts isolated from high salt or sugar food products such as kimchi, miso, soy sauce, jams and honey Kazachstania, and Starmerella, provide the desirable characteristics of yeasts in food and beverage fermentations such sourdough, miso, soy sauce, chili-paste and wine Yeasts of the genera Kazachstania, and Starmerella in flavor formation in fish or meat-based fermented foods remains to be determined.In traditional fermented foods, spontaneous fermentations often involve interactions between various microbial groups. Each of these interactions creates a group of heterogeneous microorganisms that work synergistically, producing a significant impact on taste, texture and odor 3.2.3.2.1.Several yeast strains have been reported to have hemolytic activity that can cause anemia and edema in a host 3.2.2.S. etchellsii SRKS4-12 exhibited antimicrobial activity against at least one tested pathogenic bacterial strain (K. bulderi KKKS4-1 and K. exigua KKFSP1-1 had the strongest antimicrobial activity, inhibiting three out of four pathogenic bacteria used in this study, including B. cereus TISTR 678, E. coli TISTR 073, and Ent. Aerogenes TISTR 1540. Additionally, Y. lipolytica KKFSC1-1, T. delbrueckii KKFSP2-3, P. kudriavzevii UBPS-1 and S. cerevisiae UBFS17-1 inhibited two bacterial strains while F. uniguttulatum KKFSP2-1, K. servazzii UBIF5-1 and K. turicensis UBFS11-1 inhibited only one bacterial strain (Kazachstania, Pichai and SaccharomycesStarmerella and Torulaspora yeasts, for which our results showed moderate inhibition against test bacteria, have been reported of having a good ability to inhibit the growth of yeasts and molds, while yeasts of the genus Yarrowia have not been reported to produce antimicrobial compounds Bacillus spp, E. coli, Staphylococcus, Pseudomonas and KlebsiellaOf the ten nonhemolytic yeast strains, all of them except l strain . Among tl strain . The res3.2.3.K. bulderi KKKS4-1 and F. uniguttulatum KKFSP2-1 were the most tolerant strains to these harsh conditions (For probiotic microorganisms to exert their health benefits in the human body, they have to pass through extreme conditions in the gastrointestinal tract, i.e., low pH in the stomach and high bile salt concentrations in the small intestine nditions . These rin vitro evaluations do not fully mimic the actual in situ conditions of the human gut ecosystem. Additionally, there are other conditions and physiological factors that can affect the survival rates of yeast strains. However, the in vitro acid and bile salt tolerance assays used in this study remain an effective tool for rapid screening of yeast strains Probiotic microorganisms need to be resistant to gastric acidity and tolerant to bile salts in the gastrointestinal tract. Therefore, acidity and bile tolerance are considered essential properties required for the survival of probiotic microorganisms. However, there is no clear consensus on the exact bile concentration that probiotic microorganisms should tolerate. This is because the concentration of bile and acids in the human gastrointestinal tract varies depending on the individual, as well as the type and amount of food ingested. Normally, the mean concentration of bile salts in the small intestine is about 0.2 to 0.3% 3.2.4.in-vitro model systems using a hydrophobicity assay. This assay determines the capability of microorganisms to adhere to surfaces having hydrophobic substances such as xylene and toluene K. bulberi KKKS4-1, S. cerevisiae UBFS17-1, P. kudriavzevii UBPS-1, and S. etchellsii SRKS4-12 had the highest adhesion to xylene, 65–70% after 2 h of incubation. The overall hydrophobicity of the yeast strains in this experiment was higher than that of yeast isolated from fermented foods and beverages in Taiwan, where the values ranged from 31–63% Saccharomyces cerevisiae strains from Brazilian kefir-fermented milk had moderate to high hydrophobicity. Moreover, yeasts with high hydrophobicity have been reported. For example, P. kudriavzevii ROM11 isolated from cereal-based Nigerian traditional fermented food products was reported to have high adhesion to n-hexadecane in vivo conditions in the laboratory. However, in vitro tests still provide useful information for primary screening The ability to adhere to mucus and epithelial cells is an important selection criterion for potential probiotic strains. Adhesion of probiotic strains is commonly studied with 4.S. etchellsii SRKS4-12, K. bulderi KKKS4-1, K. exigua KKFSP1-1, Y. lipolytica KKFSC1-1, F. uniguttulatum KKFSP2-1, K. servazzii UBIF5-1, K. turicensis UBFS11-1, P. kudriavzevii UBPS-1, and S. cerevisiae UBFS17-1. These findings are based on population studies of yeast strains originating from meat and fermented pork and meat, or aquatic sources such as shrimp, fish, and shellfish. The current study highlights the potential of various yeast strains in the development of probiotic foods.This study presents yeast diversity in Thai fermented foods. Some of the isolated yeasts exhibited good probiotic characteristics including


Fusarium graminearum Schwabe, is an emerging threat to wheat production in Korea under a changing climate. The disease occurrence and accumulation of associated trichothecene mycotoxins in wheat kernels strongly coincide with warm and wet environments during flowering. Recently, the International Panel for Climate Change released the 6th Coupled Model Intercomparison Project (CMIP6) climate change scenarios with shared socioeconomic pathways (SSPs). In this study, we adopted GIBSIM, an existing mechanistic model developed in Brazil to estimate the risk infection index of wheat FHB, to simulate the potential FHB epidemics in Korea using the SSP245 and SSP585 scenarios of CMIP6. The GIBSIM model simulates FHB infection risk from airborne inoculum density and infection frequency using temperature, precipitation, and relative humidity during the flowering period. First, wheat heading dates, during which GIBSIM runs, were predicted over suitable areas of winter wheat cultivation using a crop development rate model for wheat phenology and downscaled SSP scenarios. Second, an integrated model combining all results of wheat suitability, heading dates, and FHB infection risks from the SSP scenarios showed a gradual increase in FHB epidemics towards 2100, with different temporal and spatial patterns of varying magnitudes depending on the scenarios. These results indicate that proactive management strategies need to be seriously considered in the near future to minimize the potential impacts of the FHB epidemic under climate change in Korea. Therefore, available wheat cultivars with early or late heading dates were used in the model simulations as a realistic adaptation measure. As a result, wheat cultivars with early heading dates showed significant decreases in FHB epidemics in future periods, emphasizing the importance of effective adaptation measures against the projected increase in FHB epidemics in Korea under climate change.Fusarium head blight (FHB) of wheat, mainly caused by  Fusarium graminearum Schwabe and is a deadly fungal disease affecting staple crops, such as wheat, barley, and rice, in many countries (Fusarium head blight (FHB), also known as wheat scab, is mainly caused by ountries . Under fountries . Grains ountries . Therefoountries . Furtherountries . Fusariuountries .Fusarium head blight is a major wheat disease in Korea . In SoutThe wheat FHB causes distinct symptoms, such as premature bleaching of spikelets or blank heads and accumulation of mycotoxins, such as deoxynivalenol (DON), nivalenol (NIV), and zearalenone (ZEA), that have adverse effects on humans and animals. The FHB pathogen infects wheat anthers through wind dispersal or rain-splash during the flowering period from mid-April to mid-May. Since FHB is a monocyclic disease, the quantity of the primary inoculum is a key factor influencing its incidence. Overwintering pathogens on the crop residue are the main inoculum sources causing new infections during the following spring. Airborne ascospores, produced outside the field, could initiate disease by traveling long distances . The FHBA climate change impact assessment study of the FHB epidemic was conducted in Scotland . DecreasTo conduct a climate change impact assessment on FHB, an ecophysiological model that considers environmental conditions affecting FHB infection and transmission can be used. Several models simulating the epidemics of FHB have been developed for Argentina , BelgiumAmong existing FHB models, we used the GIBSIM to simulate the potential epidemics of FHB in wheat in Korea, as it better reflects the environmental conditions affecting the development of FHB during the flowering period . The GIBThe GIBSIM model requires information on the wheat heading date as a key input to simulate FHB infection risk. Since the heading date could change due to the increasing temperature under climate change, the potential FHB epidemic can be predicted realistically by integrating the simulation of wheat heading dates into the modeling process with the GIBSIM in this study. Many phenological models, including empirical models based on the accumulation of thermal time and mechanistic models simulating the emission of leaves and spike primordia at the shoot apex, have been used to predict wheat phenology . We adopWheat is not the main staple crop in Korea, and most of the wheat consumed in Korea is imported from the United States, Canada, and Australia . TherefoThe target area of this study was the entire Korean Peninsula , including both South and North Korea Figure 1-2), from 1981 to 2021, were obtained from 87 Automatic Synoptic Observation System (ASOS) stations. These stations are evenly distributed over the Korean Peninsula (https://data.kma.go.kr). In this study, the ASOS weather data for 1981–2010 were used as the observation weather data  for bias-correction of or comparison with climate change scenario data  from global climate models (GCM). Owing to considerable missing solar radiation data in the ASOS data, we used daily climatological averages of solar radiation from 1993 to 2021, obtained from the National Aeronautics and Space Administration–Prediction Of Worldwide Energy Resources (NASA–POWER), for each ASOS station , precipitation (mm), relative humidity (%), and solar radiation , the SSP245 scenario is highly likely to occur in the future. On the contrary, SSP585 corresponds to a nominal anthropogenic forcing of 8.5 W m-2 by 2100, assuming a continuously increasing trend of greenhouse gas emissions owing to limited global/national policy intervention in the future (The Shared Socioeconomic Pathways (SSP) scenario data from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) by the Intergovernmental Panel on Climate Change (IPCC) were used in this study. The SSP scenarios include new social and economic factors along with the Representative Concentration Pathway (RCP), thus allowing the projection of future changes in energy and land use based on adaptation and mitigation scenarios . The SSPe future .CMIP6 scenario data are available from the Earth System Grid Federation . In thisThe scenario data obtained from the GCMs deviated significantly from the observation data obtained from the ASOS stations. Therefore, using them directly as inputs in impact modeling is challenging. In particular, agricultural impact models, such as crop growth, phenology, and pest and disease models, are highly sensitive to systemic bias in scenario data from GCMs . The simThe reproducibility of the bias-corrected and downscaled CMIP6 scenarios from 18 GCMs was evaluated based on spatial comparisons between the observation and scenario weather data for the historical period (1981–2010). The reproducibility test was conducted for three weather variables  in April and May because the flowering of wheat—corresponding to the simulation period of the FHB epidemic—took place during these months of the historical period (1981–2010). Solar radiation was omitted because the NASA–POWER averages were used in the ASOS data. The monthly average values of the corresponding weather variables were compared, and the percentage differences between the scenario and observation data were visualized to examine the reproducibility of the scenario data from the GCMs. Reasonably good agreement for the percent difference maps of all three weather variables is shown in The developmental rate (DVR) model, introduced by nDVI is the developmental index on day n, and iDVR is the developmental rate on day i.where T) and daily photoperiod (L), and five parameters, including the minimum number of days from emergence to heading (vG), temperature when the DVR value becomes half of the maximum rate (hvT), critical photoperiod (cL), temperature parameter (vA), and photoperiod parameter (B). Further information on the definition and response of the model parameters is described in detail by The DVR values were calculated using Eq. (2), which requires two weather variables, the daily mean air temperature (T) was obtained either from the ASOS data or from the CMIP6 scenario data of the 18 GCMs used in the study, and the photoperiod variable (L) was estimated using Eq. (3) (The air temperature variable ( Eq. (3) ϕ is the latitude, and δ is the declination of the sun.where 2) = 0.56. In the study, with the DVR model, heading dates of the Geumgang cultivar were estimated for all 87 ASOS stations using either the observation data from the ASOS stations or scenario data from the 18 GCMs.The average prediction errors for the estimated heading date using the DVR model were as follows: ME = 0.9, RMSE = 5.1 (day), and the coefficient of determination  and two future periods (2041–2070 and 2071–2100) using the ASOS observation data and the scenario data of two SSP245 and SSP585 scenarios from 18 GCMs. Using the same weather input data and DVR model , heading dates were predicted from the estimated sowing dates.The GIBSIM, an FHB infection risk model , was useThe GIBSIM was first developed and successfully used for FHB early warning and climate variability studies in Brazil . The mody = 4.06 x + 1.19  and an R2 of 0.55 (in situ observations (the observation data) from 87 ASOS stations and climate change scenarios (the scenario data) from 18 GCMs of the CMIP6. Daily weather variables, such as maximum air temperature, minimum air temperature, total precipitation, average relative humidity, and average solar radiation, were used as input data for the model simulation. The predicted heading dates from the DVR model were used to initiate the GIBSIM simulations for each individual season. All GIBSIM simulations were run from the initial heading date (five days before the predicted heading date) to the date when susceptible tissues no longer existed, indicating that the simulation duration for each year was automatically determined in the model. The average duration of the model simulation was very similar for all periods: for example, 38.7, 38.3, and 39.4 days for the historical, near future, and distant future periods, respectively, in the SSP585 scenario.We used the GIBSIM to simulate FHB epidemics in the Korean Peninsula using To assess the climate change impact on FHB epidemics in Korea, GIBSIM was simulated for 87 ASOS stations based on two emission scenarios (SSP245 and SSP585) of CMIP6. Scenario data from 18 GCMs of the CMIP6 that were bias-corrected using the SQM were used as input data for the model simulation. The resulting simulation results were divided into three periods . To visualize the results on the map, we created a multi-model ensemble (MME) using 30-year simulations for each period. Briefly, for a given GCM at each ASOS station, the average FHB risk indices over the 30-year GIBSIM simulations were calculated. The resultant one average value per GCM was then averaged for the 18 GCMs for each emission scenario (SSP245 or SSP585) to calculate the MME means. The MMEs of the FHB risk index were then converted into FHB incidences using the regression equation between the simulated FHB risk indices and the actual FHB incidences, shown in the 2.2.2 section. These were then visualized on the maps by spatially interpolating the 87 ASOS point values over the Korean Peninsula using the kriging method .Based on the GIBSIM simulations, we also proposed a possible adaptation strategy using wheat cultivars with different heading dates. The underlying assumption of using alternative cultivars with different heading dates is that early or late heading dates will avoid environmental conditions conducive to FHB infection. Changing planting dates or using cultivars of different maturity to avoid high disease pressure periods is a popular adaptation strategy to mitigate the projected impacts of climate change on plant diseases . A serieTo investigate whether the differences in the simulated risks from changing heading dates with different wheat cultivars were related to projected changes in each weather variable under climate change, we calculated the mean temperature, total precipitation, number of rainy days with more than 0.3 mm precipitation, and mean relative humidity for the simulation duration of the GIBSIM for each run. The number of rainy days over 0.3 mm was selected as it was used to determine the GZ (the daily relative density of an airborne FHB spore cloud) in the model. We conducted this analysis using only the SSP585 scenario data for the distant future period, as it showed the most considerable differences between different heading dates. The results were plotted using a box plot to compare the distribution of the projected changes in each weather variable, representing non-adaptation (using heading dates of the Geumgang) versus the early (−10 days) and the late (+10 days) heading dates, representing adaptation using different cultivars. In addition, a regression analysis with FHB incidences as a dependent variable and four weather variables as an explanatory variable was conducted to statistically understand the relative contribution of individual weather variables to the simulated FHB incidences.Prior to the impact assessment of future changes in FHB epidemics, the reproducibility of the essential weather variables  from the CMIP6 scenario data was evaluated for April and May, corresponding to the duration of the GIBSIM simulations for the historical period (http://kosis.kr). Despite numerous factors, such as crop rotation, abiotic and biotic stresses, and socioeconomic factors, that affect actual areas for wheat cultivation, these results indicate that the climatic conditions used in this study can be used as a representative of the actual wheat cultivation conditions.Climatic suitability maps for wheat cultivation in the Korean Peninsula were generated based on the climatic conditions of the SSP245 and SSP585 scenarios for three periods . The projected spatiotemporal changes in the suitable areas for wheat cultivation (uncolored area indicates ‘Not suitable’ and colored area indicates ‘Suitable’) for each administrative area are indicated in With climate change, the geographical areas that can support wheat cultivation will gradually expand from the present coastal and southern areas to higher inland and northern areas by 2100. In the historical period, more than 50% of the Korean Peninsula appears to be ‘Not suitable’ for wheat cultivation. However, in the distant future, more than 80% of the areas can be marked as ‘Suitable’ Figure 2For areas suitable for wheat cultivation, the heading dates of the Geumgang cultivar were predicted using the DVR model. The day of year (DOY) of the predicted heading dates shown on the maps indicate that the heading dates occur earlier in the south and later in the north, primarily because of the temperature-dependent development rate in phenology development. The average heading date for the historical period is 116 DOY, which, in the distant future period (2071–2100), advances to 108 DOY and 102 DOY in the SSP245 and SSP585 scenarios, respectively. This result suggests that increasing temperatures due to climate change significantly affect the phenological development of wheat in Korea.On suitable wheat cultivation areas and using the predicted heading dates Figure 2Comparing South and North Korea, the incidence of FHB is projected to be relatively higher in North Korea than in South Korea; the average incidences of FHB in South and North Korea in the SSP585 scenario are 6.9% and 7.7%, respectively, for the near future, and 9.0% and 9.5% for the distant future period. These differences indicate that climate conditions in North Korea will become more conducive to FHB epidemics due to climate change. In particular, Hamgyeongbuk-do, the mountainous province in North Korea, showed the highest incidence of FHB, up to 21.8% in the distant future period. In most areas, the FHB incidence was relatively higher in SSP585 than in SSP245. Notably, in the distant future, the incidence of FHB will significantly increase in the coastal areas of the Korean Peninsula.A possible adaptation strategy to the projected FHB epidemics was suggested using currently available wheat cultivars, either with earlier or later heading dates than the Geumgang cultivar. The underlying assumption is that advancing or delaying the timing of susceptible stages of wheat may help avoid environmental conditions conducive to FHB infection. Indeed, changing heading dates from −10 to +10 days at 5-day intervals compared to those of the Geumgang cultivar resulted in significant changes in FHB incidences Table 2.To understand the key weather variables affecting the projected changes in FHB incidences with varying heading dates, we extracted and analyzed the weather data used to simulate the GIBSIM Figure 42), the average air temperature had a relatively pronounced positive effect (coefficient: +1.28) with a confidence level of 99%, followed by the average relative humidity with a positive effect (coefficient: +0.30) with a confidence level of 99%, and the number of rainy days with a positive effect (coefficients: +0.22) with a confidence level of 99%. In contrast, total precipitation showed a very minimal positive effect (coefficient: +0.004) with no statistical significance in the regression result. These results indicated that the changes in air temperature, relative humidity, and rainy days significantly affected the resulting FHB incidences when the heading date was changed. Overall, our findings suggest that adopting alternatives or breeding new cultivars with early heading dates can be an effective adaptation strategy to manage the FHB epidemics better under climate change conditions in the Korean Peninsula.Therefore, to further understand the relative contribution of individual weather variables, a regression analysis was conducted with FHB incidence as a dependent variable and four weather variables as an explanatory variable  level. Lastly, the corresponding weather data to run GIBSIM were obtained from the nearest ASOS weather station; thus, they might not represent the local weather conditions where the FHB incidence data were collected. To support the calibration study of GIBSIM in a future study, the corresponding metadata, such as coordinates and data collection dates, should be collected and used with the FHB incidence data (https://data.kma.go.kr), need to be evaluated for the accuracy of the weather variables needed for the GIBSIM simulation. Although weather conditions largely determine the occurrence of FHB, agronomic factors also significantly influence FHB. Potential factors to be considered in future modeling efforts with GIBSIM include fungicide treatment, crop rotation system (with rice), weed management, and host plant resistance in Korea  in North Korea  to mid-term (7–15 days) weather forecasts and an FHB infection model would be useful for wheat growers to implement timely preventive controls of FHB. As this type of integrated modeling platform is developed and continuously improved with more quality-controlled data and more reliable modeling algorithms, policymakers and agricultural stakeholders will be able to prepare more realistic, rational adaptation strategies to deal with the upcoming climate change threat based on evidence-based scientific results. Many follow-up studies are needed in the near future, as indicated by the findings of this study.The original contributions presented in the study are included in the article/J-YJ, J-HK, K-HK conceived and initiated the study and led the manuscript preparation. CC, JC collected and managed the required data for the analysis. J-YJ, J-HK, MB, JK conducted modelling and analysed the results. WP sourced the GIBSIM and provided advice and guidance for the study. All authors contributed to the article and approved the submitted version.


Reproductive genetic carrier screening provides individuals and couples with information regarding their risk of having a child affected by an autosomal recessive or X-linked recessive genetic condition. This information allows them the opportunity to make reproductive decisions in line with their own beliefs and values. Traditionally, carrier screening has been accessed by family members of affected individuals. In recent years, improvements to accessibility and updates to recommendations suggest that all women planning or in early pregnancy should be offered reproductive genetic carrier screening. As uptake moves towards the population scale, how can the genetic counselling needs of such large-scale screening be met? A scoping review of the literature was performed to ascertain what the genetic counselling needs of reproductive genetic carrier screening are, and what future research is needed. Four broad themes were identified in the existing literature: (1) The offer—when and in what context to offer screening; (2) Information—the importance of and what to include in education, and pre- and post-test counselling; (3) Who and how—who the genetic counselling is performed by and how; (4) Personalization—how do we find the balance between standardized and individualized approaches? Based on the existing literature, we present a set of recommendations for consideration in implementing population-scale reproductive genetic carrier screening as well as suggested areas for future research. Research suggests that 300 million people worldwide are affected by rare diseases . GeneticCarrier testing has been used for many years by family members of individuals affected by a recessive genetic condition such as cystic fibrosis (CF), spinal muscular atrophy (SMA), or fragile X syndrome (FRAX) to determine their carrier status ,4,5. In Population-based carrier screening was first performed for genetic conditions with high carrier frequencies, particularly in ethnic populations, such as sickle cell anaemia or thalassaemia in Mediterranean populations, or Tay Sachs disease in the Ashkenazi Jewish population . Single It has been possible in Australia to access a basic reproductive genetic carrier screening (RGCS) panel inclusive of CF, SMA and FRAX since 2012 on a user-pays basis [More recently, the advances in genomic sequencing technology and its increasing affordability have made it possible to offer the large panel screening of 100 s to 1000 s of genes at once ,11. ThesOver recent years, professional bodies in a number of countries have released recommendations advising that all women should be offered genetic carrier screening when planning a pregnancy or in early pregnancy ,16,17,18In 2021 the American College of Medical Genetics (ACMG)  releasedThe increasing push to offer RGCS programs at the population scale raises questions relating to how the substantial genetic counselling requirements for such programs can be adequately met. What are the genetic counselling requirements specifically? Who should be involved in providing genetic counselling for RGCS programs and at which stages in the process? Are there alternative methods for performing genetic counselling? Where should the specialist skills and experience of genetic counsellors be focussed within the scope of RGCS service delivery at scale? To answer these questions the genetic counselling requirements of genetic carrier screening must be explored and understood. This scoping review was conducted based on the Arksey and O’Malley  frameworThis review was guided by the question, ‘What are the genetic counselling requirements for RGCS?’ where ‘RGCS’ refers to expanded gene panels and whole exome sequencing with targeted computational analysis  for autoA search was conducted in three electronic databases; MEDLINE/PubMed, EMBASE and CINAHL/EBSCO. The databases were selected to be comprehensive and to cover the relevant disciplines. No limits on date, language, or type were placed on the database search. The search query consisted of terms relating to three key areas: genetic counselling, carrier screening and reproductive health/behaviour. The search query tailored these three subject areas to the specific requirements of each database . UnpubliA two-stage screening process was used to assess the relevance of studies identified in the search. All citations were imported into the web-based bibliographic manager Mendeley Reference Manager for the subsequent title and abstract relevance screening. The first level of screening involved a review of only the title and abstract of citations to identify those studies that met the minimum inclusion criteria. Exclusion criteria included duplicate articles, unpublished articles or grey literature, ineligible article type , references to screening unrelated to RGCS , etc.), or where there were no genetic counselling outcomes. The second level of screening involved a full review of the article for exclusion or inclusion in the data characterisation phase. All citations deemed relevant after the title and abstract screening were obtained for subsequent review of the full-text article. Study characteristics such as publication year, research characteristics, participant type, and carrier screening type were extracted into a single spreadsheet for descriptive statistical analyses. The researcher adopted a narrative synthesis approach due to methodological heterogeneity across the reviewed studies. This allowed for the organisation, description, exploration and interpretation of the study findings relating to genetic counselling outcomes , each ofhttps://doi.org/10.17605/OSF.IO/MR8ZK, accessed on 21 June 2022) along with the protocol . Specific ethics approval for this scoping review was not required.The database search, article review, data characterisation and evidence synthesis were conducted by a single researcher. The scoping review was registered on Open Science Framework  adequate and consistent genetic counselling is provided, (2) the burden on genetic counselling resources is minimized, and (3) genetic counsellor skills are utilized for maximum effect:This scoping review was conducted by a single researcher and may thus be limited by a subjective interpretation of the data. The nature of a scoping review means that the available literature was not screened to exhaustion as a systematic review would have been. Thus, it is possible that potentially valuable studies may have been omitted by chance. Finally, the reviewed studies were conducted within varying politico-legal and cultural contexts, the specifics of which were not stated and thus assumptions may have influenced the formation of the recommendations. Implementing generalised recommendations into each specific regional context may be challenging but would offer a starting point on a potentially global journey to offering RGCS at scale.The review of the literature identified a distinct dearth of insight into pathology provider and policymaker views on genetic counselling requirements for RGCS. Pathology providers represent an important stakeholder group given that they perform the screening, variant curation and reporting of results. How does genetic counselling impact their processes? What are the roles of laboratory-based genetic counsellors? Similarly, standardized practices might be mandated by government regulatory bodies as they have been in Germany with the German Genetic Diagnostics Act , yet theWhilst it is recognized that RGCS offers based on positive family history result in the under-identification of carrier individuals and at-risk couples , family Further research is also needed into standardising and streamlining RGCS education for both the public and healthcare professionals. Evidence would suggest that healthcare professionals access RGCS education from a number of different sources, including local and regional conferences, commercial provider representatives, journal articles and colleagues. The provision of standardized RGCS education for the public would likely reduce the time burden on genetic counselling resources, as individuals would enter the pre-test counselling process with a greater knowledge base . SimilarThis scoping review of the literature identified the need for consistent standardized information during pre- and post-test counselling for RGCS and also highlighted the importance of personalized genetic counselling when necessary. Finding the right balance between standardisation and personalisation will be extremely important when implementing RGCS programs at scale. Further research into how this balance might be achieved is needed. One possibility may be integrating genetic counsellor support for both healthcare professionals and individuals/couples throughout the RGCS process, enabling the genetic counsellors to provide personalisation within a standardized system. Another area for investigation is interactive pre- and post-test counselling methods that provide an alternative to, and minimize the need for, traditional genetic counselling, e.g., decision aids, chatbots, online education, etc.The genetic counselling requirements for RGCS are not novel but are significantly more complex when implemented at scale. The genetic counselling requirements of smaller RGCS programs are evident and can provide insight. Yet the specific complexities of RGCS at scale appear under-researched and should be explored further in future studies. With the push for RGCS to be offered at scale and the potential conflict between commercial and patient agendas, it is imperative for a consensus of recommendations for the implementation of RGCS programs at scale from the wider genetics community in each country. The researchers put forward the recommendations set out in this scoping review as a starting point for developing consensus.


Akkermansia muciniphila has potential as a next-generation probiotic, but few previous studies attempted to analyze its intraspecies population diversity. In this study, we performed a comparative genomic analysis of 112 filtered genomes from the NCBI database. The populations formed three clades (A-C) on the phylogenetic tree, suggesting the existence of three genetic lineages though clades B and C were phylogenetically closer than clade A. The three clades also showed geographic-based clustering, different genetic characteristics, and clade-specific genes. Two putative functional genes (RecD2 and xerD) were specific to clade C due to genomic islands. These lineage-specific genes might be associated with differences in genomic features  between genetic lineages. The carbohydrate utilization gene profile (particularly for glycolytic hydrolases and carbohydrate esterases) also varied between clades, suggesting different carbohydrate metabolism potential/requirements between genetic lineages. Our findings provide important implications for future research on A. muciniphila.IMPORTANCEAkkermansia muciniphila has been widely accepted as part of the next generation of probiotics. However, most current studies on A. muciniphila have focused on the application of type strain BAA835T in the treatment of diseases, while few studies have reported on the genomic specificity, population structure, and functional characteristics of A. muciniphila species. By comparing the genomes of 112 strains from NCBI which met the quality control conditions, we found that the A. muciniphila population could be divided into three main clades (clades A to C) and presented a certain regional aggregation. There are significant differences among the three clades in their genetic characteristics and functional genes (the type strain BAA835T was located in clade A), especially in genes related to carbohydrate metabolism. It should be mentioned that probiotics should be a concept at the strain level rather than at the gut species level, so the probiotic properties of A. muciniphila need to be carefully interpreted. Akkermansia muciniphila has attracted much attention due to its unique characteristics  employed in the study was lower than the standard species-level cutoff of 95% , and functional genomic characteristics . The RecD2 (ATP-dependent RecD-like DNA helicase) and xerD (tyrosine recombinase) genes, which are unique to clade C, led to a high proportion of core genes in the branch and a recombination rate of approximately zero, a low genetic diversity, and a greater number of phages. Insights into the evolutionary history, population structures, gene clusters, and carbohydrate-related genes of A. muciniphila provide more information about the possible physiological and probiotic mechanisms of A. muciniphila strains. This manuscript provides some instructions for in-depth research into the use of A. muciniphila as a gut probiotic in the future.ANI has been widely accepted as a classical species classification method , and twoA. muciniphila, we performed paired ANI analysis on the 130 strains, which consisted of four species groupings . The results of phylogenetic analysis based on the core genes were consistent with the results of paired ANI analysis : 18 isolates showed interspecies differences with the other 112 isolates (including the type strain ATCC BAA-835T). Due to the large differences between different species, 18 strains which might have incorrect taxonomic status were removed from this study and 112 strains which shared more than 95% ANI with the type strain ATCC BAA-835T were further analyzed.As of September 2020, NCBI’s Refseq database contains genomic data for 130 strains . To confirm the genomic taxonomic status of A. muciniphila genome is 2.65 ± 0.08 Mb in size and its GC content is 55.29% ± 0.37%. There were 2,234 ± 93 coding sequences (CDS) in A. muciniphila. Further analysis showed a significant linear relationship between genome size and the number of CDS , but no significant linear relationship between genome size and GC content  or between GC content and CDS . According to the fitted linear function, the average genome length of CDS was about 896.87 bp.Of the 112 fecal isolates, 44 human isolates were from America (39.28%), 29 were from China (25.89%), 20 were from South Korea (17.86%), and 8 isolates were from other non-human mammals (7.14%). At the species level, the A. muciniphila species, we obtained a pan-core gene set of 9,419 genes , including the 1,132 core genes present in all strains, 401 soft-core genes (95% ≤ strains < 100%), 1,201 shell genes (15% ≤ strains < 95%) and 6,685 cloud genes (0% ≤ strains < 15%). The results showed that the pan-genome was open, indicating that the A. muciniphila strain had strong adaptability. In addition, cloud genes occupy a large proportion of the pan-genome of A. muciniphila and are the most important component of the pan-genome.In order to facilitate in-depth evolutionary and population genetics analyses of these genomes, we initially annotated these 112 genomes. By constructing the pan-core gene set of A. muciniphila strains are divided into three genetic lineages (A to C) by two main branches in the phylogenetic tree  and not of mammalian isolates other than Homo sapiens . South Korean  and Chinese human fecal isolates  were the main components of genetic lineage B. Forty-four American (88.00%), four Korean (8.00%), and two Chinese intestinal isolates (4.00%) constituted genetic lineage C. In addition, genetic lineages B and C are parallel lineage groups which may share an ancestor, but both of them are distantly related to genetic lineage A.Based on the 1,132 core genes, we constructed a phylogenetic tree of the strains. The results of phylogenetic analysis showed that the 112 tic tree . The reses level . It is wA. muciniphila genetic lineages, we used ANI and total nucleotide identity (TNI) to describe the genetic diversity and differences of the three genetic lineages. The ANI and TNI results . In contrast, genetic lineages B and C are relatively closely related (ANI > 98%). It is worth noting that genetic lineage C showed low genetic diversity in both ANI and TNI results .In order to analyze the genetic diversity and differences of different A. muciniphila genetic lineages, we compared their genome sizes, GC content, and numbers of CDS. The results showed that genome size . Genetic lineage A had the smallest genome and the lowest number of CDS, but the highest GC content. Genetic lineage C had the largest genome, the greatest number of coding sequences, and medium GC content. This is consistent with the good linear relationship between GC content and genome size found in this study.In order to analyze the genetic characteristic differences of different ome size , GC contome size , and theome size  were sigFurthermore, we constructed pan-core gene sets of the three different genetic lineages. Genetic lineage A has 5,149 pan-genome genes and 1,576 core genome genes . GeneticA. muciniphila strains showed that genetic lineages B and C shared the most genes, and that lineage C had few lineage-specific genes. The three lineages possessed different spectra of lineage-specific core genes. Lineage C was the least diverse lineage, containing the highest number of core genes  among the three lineages. Two interesting core putative proteins detected among lineage C isolates were the methyltransferase paeR7IM (a recombinant DNA repair enzyme of DNA helicase RecD2), which was specific to this lineage, as well as the tyrosine recombinase XerD, which exhibited a higher number of copies in lineage C than in other genetic lineages. Notably, the isolates in genetic lineage C did not contain the RecBC gene. The presence and enrichment of these two enzymes in genetic lineage C might result in the unique recombination characteristics and relatively low genomic diversity within this lineage. Eighteen lineage A-specific genes were identified, including 1 peptidyl-lysine N-acetyltransferase (yajB) and 17 hypothetical proteins. N-epsilon-lysine acetyltransferase participates in protein acetylation . The r/m rates of most strains were less than 1, indicating that mutation was the main evolutionary driving force in A. muciniphila strains. The different ratios of different genetic lineages indicate that different genetic lineages experienced different evolutionary events. Genetic lineage C had the highest recombination rate among the three genetic lineages, while genetic lineage B exhibited a much lower recombination rate. The recombination rate in genetic lineage B was close to zero  and phages  . These results suggested that different numbers and frequencies of horizontal gene transfer events occurred in the three lineages, and, generally, more of these events happened for the genetic lineage C isolates. Interestingly, RecD2 and more copies of XerD were found on genomic islands in genetic lineage C, suggesting that genomic islands confer genes which are specific to genetic lineages and aid in lineage evolution.Horizontal gene transfer is an important mechanism of nonhomologous recombination and one of the main driving forces of bacterial evolution. The presence of phage/prophage-containing genomic islands is indicative of horizontal gene transfer. Thus, the number of genomic islands and phages in the genomes of different genetic lineages were analyzed. The results showed that genetic lineage C had a significantly higher number of genomic islands  . In contA. muciniphila could be divided into four groups according to the distribution and types of CRISPR-Cas systems present in their genomes, including no CRISPR-Cas, Type I-C, Type II-C, and Type I-C and II-C   . In geneA. muciniphila isolates of different genetic lineages . The isolates in genetic lineages C had the highest number of spaces (100.1 ± 19.3), followed by genetic lineages B (55.0 ± 27.9) and A (22.8 ± 27.5), respectively.Meanwhile, there was a significant difference in the number of CRISPR-Cas system spacers among A. muciniphila in the gut can be increased through the intake of cranberry extract (A. muciniphila. Carbohydrate-active enzymes (CAZymes) play key roles in energy acquisition and utilization and growth in bacteria. Thus, the genomic profiles of A. muciniphila from different genetic lineages were compared. The results of PCA and permutational multivariate analysis of variance (PERMANOVA) revealed significant differences in the profiles of CAZyme-encoding genes between the three different genetic lineages . Particularly, significant difference was observed between genetic lineage A and genetic lineages B and C based on pairwise adonis analysis .The abundance of  extract  or FODMA extract , suggestP = 5.3 × e−15, Kruskal-Wallis test) and carbohydrate esterases  but a significantly lower number of glycosyl transferases  compared with lineages B and C. These results indicate that carbohydrate metabolism capacity varied between genetic lineages. Then, significant interlineage differences in the genomic contents of CAZymes were analyzed on a finer level. The results showed that the number of copies of CAZyme-encoding genes also varied between genetic lineages. Isolates in genetic lineage A had more copies of genes in the GH33, GH43_24, and GT11 families , while genetic lineage B had fewer genes in the CE6 family . In addition, the GH18, CBM78, and GH141 gene families were unique to genetic lineage A, while the carbohydrate metabolite families of CBM56, GT5, and GT101 were common to genetic lineages B and C but not present in lineage A. These results together suggested that there were significant differences in carbohydrate metabolism capacity between the genetic lineages of A. muciniphila. The different carbohydrate metabolism capacities between genetic lineages and isolates could be related to their niches and the environmental selection forces that drive adaptation, particularly the dietary habits of the host, as A. muciniphila were mainly isolated the from mammalian gut.Further analysis revealed significantly different makeup of CAZymes between the three separate lineages. Lineage A had a significantly higher number of glucoside hydrolases , CBM78, and GH18 families  were specific to isolates of genetic lineage A.Research on glucose metabolism in cosamine . Ploviercosamine  successfA. muciniphila strains/isolates; in particular, specific culture conditions and methods should be tailored for laboratory cultivation of isolates of interest. Moreover, it is worth mentioning that A. muciniphila is recognized as a keystone species in the human microbiome and a potential next-generation probiotic. Because most previous physiological and functional studies of A. muciniphila have been established from the type strain BAA-835T, knowledge and understanding of this species is limited  and xerD (a tyrosine recombinase). These lineage-specific genes might be associated with genomic features, such as the number of phages and genomic islands, the pan-core genome, the recombination rate, and genetic diversity. The profiles of carbohydrate metabolism/utilization genes (particularly the glycolytic hydrolase and carbohydrate esterase families) also varied between genetic lineages, suggesting different carbohydrate metabolism potential/requirements. Our findings provide important and practical implications for future research on A. muciniphila, especially for laboratory isolation/cultivation of strains of interest, selection of candidate strains for functional studies, and design and application of A. muciniphila-containing synbiotic formulations.By comparative genomics analyses, our study showed that the 112 A. muciniphila were retrieved from the NCBI RefSeq database  and were included in further analysis. The information of the downloaded genome sequences is presented in Table S1 in the supplemental material.In September 2020, 130 sequenced genomes that were reported to be database . PairwisA. muciniphila genomes was predicted using Prokka (v1.11)   using thsoftware  with thesoftware  with defhttp://treesoft.sourceforge.net/treebest.shtml).TreeBest software was used to construct a phylogenetic tree of single-copy tandem sequences of core genes generated by Roary based on gene adjacencies  were calculated using R software.Statistical analyses were implemented via the R platform. Heatmaps were generated using the pheatmap package, and PCA was performed using the psych package and visualized using the ggplot2 package. ANOSIM and adonis analysis (999 permutations) of PERMANOVA were performed using the vegan package in R software. Pairwise Adonis analysis  of PERMANOVA was performed using the pairwiseAdonis package in R software. All genomic data used in this study are stored in NCBI. Information on the genome sequences is presented in Table S1 in the supplemental material.


An important drug used in the treatment of Parkinson’s disease is amantadine. We are the first to perform a comprehensive study based on various glycation and oxidation factors, determining the impact of amantadine on protein glycoxidation. Sugars  and aldehydes  were used as glycation agents, and chloramine T was used as an oxidant. Glycoxidation biomarkers in albumin treated with amantadine were generally not different from the control group (glycation/oxidation factors), indicating that the drug did not affect oxidation and glycation processes. Molecular docking analysis did not reveal strong binding sites of amantadine on the bovine serum albumin structure. Although amantadine poorly scavenged hydroxyl radical and hydrogen peroxide, it had significantly lower antioxidant and antiglycation effect than all protein oxidation and glycation inhibitors. In some cases, amantadine even demonstrated glycoxidant, proglycation, and prooxidant properties. In summary, amantadine exhibited weak antioxidant properties and a lack of antiglycation activity.  Increased ROS/RNS formation occurs under the influence of external factors  as well as cellular metabolic disorders 10H17N; 1-adamantanamine; Amantadine  glutamate receptor subtype. Amantadine inhibits the release of acetylcholine through NMDA receptors, exhibiting anticholinergic effect,On the other hand, amantadine has a virostatic effect, inhibiting the early stages of viral replication by blocking the proton pump of viral M2 protein, stopping the removal of the viral envelope, and inactivating newly synthesised viral haemagglutinin,2•−) and hydroxyl radical (HO•) generation in in vitro modelsNot all mechanisms of the pharmacological action of amantadine are well understood. Since amantadine has been successfully used in oxidative stress-related Parkinson’s disease, its therapeutic activity may be based on preventing protein glycoxidationThe review of the literature was conducted between 1995 and May 2022 on Medline (PubMed) database. The accessible bibliography was searched using keywords: [amantadine and antiglycoxidative properties], [amantadine and antiglycation properties] [amantadine and antioxidative properties], [amantadine and oxidative stress], [amantadine and carbonyl stress], [amantadine and protein glycation], [amantadine and nitrosative stress], and [amantadine and ROS scavenging]. Inclusion and exclusion criteria are presented in The initial data was explored by evaluating titles and abstracts of publications independently by two investigators . Next, the other two authors scrutinised all previously extracted manuscripts . The papers compliant with the inclusion and exclusion criteria were utilised for the final analysis. The researchers’ level of reliability was evaluated with Cohen’s kappa coefficient (κ) which equalled κ = 0.94. All articles were assessed methodologically, and the following factors were analysed: authors, year of publication, study design, size of the experiment population, inclusion and exclusion criteria, research length, and endpoints.All chemicals  were purchased from Sigma-Aldrich . Directly before use, solutions were sterilised by filtration through 0.2-mm-membrane filters. The absorbance and fluorescence were assessed with an Infinite M200 PRO multimode microplate reader .A1 – A2)/A0}] × 100%, where A0 represents the absorbance of the control (without additives), A1 – after the addition of the drugs, and A2 – without sodium salicylateThe scavenging activity of HO• was measured via the modified assay described by Su et al.2O2 scavenging activity was performed in compliance with the method by Kwon et al.2SO4) (10 μL), xylenol orange (7.6 mg) and ferrous ammonium sulphate (10 mg) were mixed in 100 mL of 90% methanol-water solution in order to obtain ferrous ion oxidation-xylenol orange (FOX). Then, 50 mM of H2O2 and the samples  were mixed  and incubated at room temperature for 30 min. Next, 10 μL of high-performance liquid chromatography (HPLC)-grade methanol was added to 90 μL of the sample solution in H2O2. After that, 0.9 mL of the FOX reagent was added to the above mixture and it was then vortexed and incubated at room temperature for 30 min. The absorbance of the reaction product, ferric-xylenol orange complex, was assayed spectrophotometrically at 560 nm wavelength. The scavenged H2O2 (%) was calculated according to the formula: [1 – {(A1 – A2)/A0}] × 100%, where A0 is the absorbance of the control (without additives), A1 – after the addition of the drugs, and A2 – without the FOX reagentThe assessment of HAblank – Asample)/Ablank] × 100%, where Ablank is the absorbance of the blank DPPH solution, and Asample – DPPH solution after the addition of the sampleThe determination of free radical scavenging activity was performed based on the decolourisation of the DPPH radical according to Kwon et al.TAC assessment was performed with the Erel’s methodo-dianisidine complex into the ferric ion. The ferric ion in an acidic medium forms a coloured complex with xylenol orange. 35 μL of the sample, 225 μL of reagent 1  as well as 11 μL of reagent 2 (5 mM ferrous ion with 10 mM o-dianisidine in 25 mM H2SO4 solution), were mixed. The wavelength of 560/800 nm was used to measure the absorbance. The TOS level was read from H2O2 standard curveThe Erel’s method was used to calculate TOS,,,,The glycation and/or oxidation of BSA was conducted in compliance with a previously published method,,,,,,Glycation agent concentrations and the optimal incubation conditions for studies on the modification of the glycoxidation rate by additives were assayed and validated according to the previous kinetic studiesin vitro studies, proportionally to the high concentrations of glycation agents,,,To compare the results obtained for amantadine, aminoguanidine was used as a known protein oxidation inhibitor, and α-lipoic acid (ALA), N-acetylcysteine (NAC), and ascorbic acid (AA) – as antioxidants2SO4 . Results were standardised based on fluorescence of 0.1 mg/mL quinine sulphate in 0.1 M H2SO4,.Tryptophan (TRY), kynurenine (KN), N-formylkynurenine (NFK), and dityrosine (DT) were assessed using fluorescence emission and excitation at 95/340, 365/480, 325/434, and 330/415 nm wavelengths, respectively. Before the measurement, the investigated solutions were diluted with 0.1 M H−1cm−1)The total amount of AP was assessed by means of a colourimetric Nitro Blue Tetrazolium (NBT) assay. The absorbance was estimated at 525 nm wavelength with the use of monoformazan extinction coefficient  was used as a standardAssessment of PC concentration was conducted with the use of the reaction of carbonyls with 2,4-dinitrophenylhydrazine (DNPH) in proteins damaged by oxidation. Reaction product absorbance was marked colourimetrically at 355 nm wavelength. The absorption coefficient for 2,4-DNPH , the standard solutions (0–100 μmol/L), and 200 μL of blank PBS solution were placed on a 96-well microplate. Then, 10 μL of 1.16 M potassium iodide and 20 μL of acetic acid were added to the wells. The absorbance was determined instantly in a microplate reader at 340 nm wavelength in comparison with the blank solution . ChT solutions showed linear absorbance in the range of 0–100 μmol/Lhttps://www.rcsb.org/) in the .pdb format. It was the crystal structure established with the X-ray diffraction method at a 2.47 Å resolution valuehttps://pubchem.ncbi.nlm.nih.gov/) as a .sdf file. The BSA molecule was processed using AutoDock MGL ToolsMolecular docking is used in the in silico method of predicting the preferred position of a ligand after binding to a macromolecule (e.g. protein). BSA was used as a receptor in an interaction study with the amantadine molecule. Possible attachment of the drug to BSA could suggest a mechanism of protective action against carbonyl stress. A three-dimensional structure of BSA (PDB ID: 4F5S)post hoc test for multiple comparisons, and p < 0.05 was allowed to be statistically significant. Multiplicity adjusted p values was also evaluated. The statistical analysis was performed with GraphPad Prism 9 .The results were shown as a percentage of the respective control values /oxidising agent [ChT]). Differences between groups were assayed using the one-way analysis of variance (ANOVA) followed by Tukey’s Our systematic review of the bibliography identified 144 publications from the Medline (PubMed) database, from which 113 were excepted because of the title. Out of 31 read abstracts, 18 complied with the inclusion and exclusion criteria. Out of the eligible works, eight were found not to be related to the subject of our research. However, 10 papers were finally included , ALA , NAC , as well as AA  was significantly higher than the inhibition rate of amantadine , NAC , and AA  in comparison with amantadine , NAC , and AA  , ALA , NAC , as well as AA  was significantly higher than its level of amantadine  and TRY are amino acids highly susceptible to glycoxidative damage. The product of the breakdown of TRY in the kynurenine pathway is NFK, which is converted to KN. The cross-linking of two glycoxidised TYR results in DTThe fluorescence of TRY was significantly lower in Glc + amantadine (−15.0%), Glc + ALA (−7.9%), Glc + NAC (−13.4%), and Glc + AA (−16.7%) than in Glc. The parameter was effectively reduced in Glc (−40.8%), Glc + amantadine (−34.7%), Glc + aminoguanidine (−41.8%), Glc + ALA (−37.6%), Glc + NAC (−35.3%), as well as Glc + AA (−34%) in comparison with BSA. TRY content was markedly decreased in Fru + amantadine (−12%) and Fru + AA (−17.8%) versus Fru. This biomarker was substantially enhanced in Fru + NAC (+13.6%) compared to Fru alone. TRY fluorescence was effectively reduced in Fru (−29.4%), Fru + amantadine (−25.8%), Fru + aminoguanidine (−30.4%), Fru + ALA (−31%), Fru + NAC (−33.4%), and Fru + AA (−24.1%) in comparison with BSA. The content of TRY was considerably suppressed in Gal + amantadine (−14.3%) and Gal + AA (−36.7%) versus Gal. This parameter was relevantly lower in Gal (−39.9%), Gal + amantadine (−34.2%), Gal + aminoguanidine (−26.4%), Gal + ALA (−38.1%), Gal + NAC (−39.1%), and Gal + AA (−25.2%) than in BSA. The fluorescence of TRY was significantly attenuated in GO + amantadine (−24.5%) and also GO + AA (−26.9%)compared with GO. The marker was efficiently decreased in GO (−42%), GO + amantadine (−31.7%), GO + aminoguanidine (−42.4%), GO + ALA (−50.3%), GO + NAC (−41.6%), as well as GO + AA (−30.7%) compared to BSA. TRY content was markedly reduced in MGO + amantadine (−70.6%) in comparison with MGO. This biomarker was significantly decreased in MGO (−34.9%), MGO + amantadine (−10.3%), MGO + aminoguanidine (−35.9%), MGO + ALA (−35.6%), MGO + NAC (−29.8%), as well as MGO + AA (−32.6%) when compared to BSA. TRY fluorescence was markedly inhibited in ChT + amantadine (−26.7%) versus ChT. The parameter was relevantly higher in ChT + NAC (+153.9%) than in ChT alone. TRY content was significantly diminished in ChT (−66.7%), ChT + amantadine (−48.9%), ChT + aminoguanidine (−69.2%), ChT + ALA (−81.8%), and ChT + AA (−63.8%) in comparison with BSA (The content of KN was significantly elevated in Glc + amantadine (+4.8%) and Glc + AA (+81.5%) compared to Glc. The biomarker was effectively reduced in Glc + aminoguanidine (−17.6%) and Glc + NAC (−13.7%) versus Glc. The fluorescence of KN was markedly higher in Glc (+34.6%), Glc + amantadine (+36.3%), Glc + ALA (+33.7%), Glc + NAC (+29.9%), as well as Glc + AA (+62.8%) in comparison with BSA. The parameter was substantially decreased in Fru + aminoguanidine (−38.5%) and Fru + NAC (−8.9%) when compared to Fru. KN fluorescence was effectively increased in Fru + AA (+68.2%) versus Fru alone. The marker was relevantly enhanced in Fru (+106.3%), Fru + amantadine (+106.6%), Fru + aminoguanidine (+65.4%), Fru + ALA (+105%), Fru + NAC (+96.9%), as well as Fru + AA (+178.8%) compared to BSA. KN content was notedly attenuated in Gal + aminoguanidine (−33%) and Gal + NAC (−27.1%) versus Gal. The biomarker was significantly higher in Gal + AA (+111%) than in Gal alone. The fluorescence of KN was effectively intensified in Gal (+103.6%), Gal + amantadine (+113.6%), Gal + aminoguanidine (+69.4%), Gal + ALA (+111%), Gal + NAC (+75.6%), and Gal + AA (+218.6%) compared with BSA. The parameter was markedly lower in GO + aminoguanidine (−40.7%) and GO + NAC (−47.8%) than in GO. KN fluorescence was substantially increased in GO (+677.6%), GO + amantadine (+710.1%), GO + aminoguanidine (+402.1%), GO + ALA (+708.8%), GO + NAC (+353.6%), as well as GO + AA (+655.1%) in comparison with BSA. The marker was significantly reduced in MGO + amantadine (−11.2%), MGO + aminoguanidine (−33.3%), and MGO + NAC (−17%) versus MGO. KN content was notedly increased in MGO + AA (+20%) compared to MGO alone. The biomarker was substantially elevated in MGO (+1148.1%), MGO + amantadine (+1019.5%), MGO + aminoguanidine (+766.1%), MGO + ALA (+1085.1%), MGO + NAC (+953.4%), as well as MGO + AA (+1377.8%) versus BSA. The fluorescence of KN was considerably lower in ChT + aminoguanidine (−39.4%), ChT + NAC (−33.7%), and ChT + AA (−35.4%) than in ChT. The content of KN was relevantly elevated in ChT (+56.3%), ChT + amantadine (+64.7%), and ChT + ALA (+58.8%) in comparison with BSA (The fluorescence of NFK was significantly elevated in Glc + amantadine (+3.4%) and Glc + AA (+92.6%) compared to Glc. The biomarker was effectively reduced in Glc + NAC (−8.7%) versus Glc. The content of NFK was markedly higher in Glc (+37.1%), Glc + amantadine (+38.3%), Glc + ALA (+36.8%), Glc + NAC (+33.8%), as well as Glc + AA (+71.4%) in comparison to BSA. The parameter was substantially decreased in Fru + aminoguanidine (−30.2%) and Fru + NAC (−8.1%) when compared to Fru. NFK content was effectively increased in Fru + AA (+79%) versus Fru alone. The marker was relevantly enhanced in Fru (+96.9%), Fru + amantadine (+96.5%), Fru + aminoguanidine (+67.6%), Fru + ALA (+94.3%), Fru + NAC (+89%), as well as Fru + AA (+173.4%) compared to BSA. NFK fluorescence was meaningfully attenuated in Gal + aminoguanidine (−29.4%) and Gal + NAC (−16%) versus Gal. The content of NFK was significantly higher in Gal + AA (+137%) than in Gal alone. The parameter was effectively intensified in Gal (+88%), Gal + amantadine (+93.2%), Gal + aminoguanidine (+62.1%), Gal + ALA (+93.8%), Gal + NAC (+73.9%), as well as Gal + AA (+208.5%) compared to BSA. NFK content was markedly lower in GO + aminoguanidine (−50.4%), GO + ALA (−6%), GO + NAC (−55.2%), and also GO + AA (−21.1%) than in GO. The marker was substantially increased in GO (+578.4%), GO + amantadine (+608.5%), GO + aminoguanidine (+287%), GO + ALA (+613.1%), GO + NAC (+259.2%), as well as GO + AA (+456.6%) in comparison with BSA. The fluorescence of NFK was efficiently reduced in MGO + amantadine (−8.2%) and MGO + aminoguanidine (−40.2%) versus MGO. The biomarker was substantially elevated in MGO (+739.6%), MGO + amantadine (+679.2%), MGO + aminoguanidine (+442.7%), MGO + ALA (+708.3%), MGO + NAC (+733.9%), and MGO + AA (+826.2%) compared to BSA. The biomarker was considerably lower in ChT + aminoguanidine (−33.9%), ChT + NAC (−29.2%), and ChT + AA (−30%) than in ChT. NFK fluorescence was relevantly elevated in ChT (+42.7%), ChT + amantadine (+45.5%), as well as ChT + ALA (+43%) in comparison with BSA (The content of DT was significantly reduced in Glc + aminoguanidine (−14.6%) and Glc + NAC (−8.3%) compared to Glc. The biomarker was effectively elevated in Glc + AA (+32%) versus Glc. The fluorescence of DT was markedly higher in Glc (+51.1%), Glc + amantadine (+51.9%), Glc + aminoguanidine (+43.6%), Glc + ALA (+52.3%), Glc + NAC (+46.9%), as well as Glc + AA (+67.4%) in comparison with BSA. The parameter was substantially decreased in Fru + aminoguanidine (−30%) when compared to Fru. DT fluorescence was efficiently increased in Fru + AA (+28.4%) versus Fru alone. The marker was relevantly enhanced in Fru (+59.9%), Fru + amantadine (+59.6%), Fru + aminoguanidine (+42%), Fru + ALA (+60.7%), Fru + NAC (+59.4%), as well as Fru + AA (+77%) compared to BSA. DT content was markedly attenuated in Gal + aminoguanidine (−23.5%) versus Gal. The fluorescence of DT was significantly higher in Gal + AA (+49%) than in Gal alone. The parameter was effectively increased in Gal (+80.4%), Gal + amantadine (+83.4%), Gal + aminoguanidine (+61.5%), Gal + ALA (+86.4%), Gal + NAC (+75.5%), as well as Gal + AA (+119.8%) compared to BSA. DT fluorescence was markedly lower in GO + aminoguanidine (−50.8%), GO + NAC (−54.9%), and also GO + AA (−23.6%) than in GO. DT content was significantly increased in GO + ALA (+8.6%) versus GO alone. The marker was substantially elevated in GO (+148.7%), GO + amantadine (+155.7%), GO + aminoguanidine (+73.1%), GO + ALA (+161.5%), as well as GO + AA (+113.7%) in comparison with BSA. DT content was effectively reduced in MGO + amantadine (−4.8%) and MGO + aminoguanidine (−54.3%) versus MGO. The biomarker was substantially raised in MGO (+291.8%), MGO + amantadine (+277.9%), MGO + aminoguanidine (+133.5%), MGO + ALA (+283.2%), MGO + NAC (+273.2%), as well as MGO + AA (+319.3%) compared to BSA. The biomarker was significantly lower in ChT + aminoguanidine (−37.2%), ChT + NAC (−13.6%), and also ChT + AA (−25.7%) than in ChT. DT content was relevantly elevated in ChT (+10.1%), ChT + amantadine (+11.4%), ChT + aminoguanidine (+6.4%), ChT + ALA (+10.4%), as well as ChT + AA (+7.5%) in comparison with BSA (ϵ-carboxymethyl-lysine (CML) and Nϵ-carboxyethyl-lysine (CEL). Prolonged exposure of proteins to Glc and other sugars causes the α-helix transition to a linear structure, triggering the formation of βAThe Maillard reaction is a series of chemical transformations that occur between amino acids and reducing sugars. Glycation is initiated by the covalent attachment of reducing sugars to the amino groups of proteins to produce a reversible and unstable Schiff base. The Schiff base can be converted into more stable AP which undergo dehydration and rearrangement accompanied by the formation of AGE, such as NThe concentration of AP was significantly lower in Glc + aminoguanidine (−19.9%), Glc + ALA (−12.5%), Glc + NAC (−21.9%), and Glc + AA (−11.4%) than in Glc. The biomarker was effectively elevated in Glc (+39.5%), Glc + amantadine (+40%), Glc + ALA (+34.6%), as well as Glc + AA (+35%) in comparison with BSA. AP level was markedly decreased in Fru + NAC (−19.2%) and also Fru + AA (−35.1%) versus Fru. The parameter was effectively elevated in Fru (+82.4%), Fru + amantadine (+90.2%), Fru + aminoguanidine (+80.2%), Fru + ALA (+78.1%), and Fru + NAC (+66.6%) in comparison with BSA. The concentration of AP was markedly enhanced in Gal + amantadine (+6.3%) versus Gal. The marker was significantly reduced in Gal + aminoguanidine (−8.5%) and Gal + NAC (−5.6%) compared to Gal alone. The level of AP was relevantly higher in Gal (+57.5%), Gal + amantadine (+61.2%), Gal + aminoguanidine (+52.7%), Gal + ALA (+57.7%), Gal + NAC (+54.3%), and Gal + AA (+55.8%) than in BSA. This parameter was markedly raised in MGO + NAC (+26.7%) and MGO + AA (+15%) in comparison with MGO. The concentration of AP was considerably increased in MGO (+96%), MGO + amantadine (+95.6%), MGO + aminoguanidine (+98.2%), MGO + ALA (+95.4%), MGO + NAC (+121.6%), as well as MGO + AA (+110.4%) when compared to BSA. AP formation was markedly inhibited in ChT + aminoguanidine (−56.2%) and ChT + ALA (−25.4%) versus ChT. AP level was relevantly higher in ChT + NAC (+22.7%) and ChT + AA (+82.3%) than in ChT alone. The parameter was significantly enhanced in ChT + aminoguanidine (+5.2%), as well as ChT + AA (+21.8%) in comparison with BSA (βA fluorescence was effectively elevated in Glc + AA (+259%%) versus Glc. The biomarker was markedly higher in Glc (+302.1%), Glc + amantadine (+286%), Glc + aminoguanidine (+271.5%), Glc + ALA (+300%), Glc + NAC (+355%), as well as Glc + AA (+1086.9%) in comparison with BSA. The content of βA was substantially decreased in Fru + ALA (−7.6%) and Fru + NAC (−14.5%) compared to Fru. This parameter was markedly increased in Fru + AA (+17.7%) versus Fru alone. The marker was relevantly enhanced in Fru (+283.7%), Fru + amantadine (+394.4%), Fru + aminoguanidine (+301.3%), Fru + ALA (+262.1%), Fru + NAC (+242.5%), as well as Fru + AA (+334%) compared to BSA. The fluorescence of βA was significantly higher in Gal + NAC (+40.3%) and Gal + AA (+74%) than in Gal. The parameter was effectively elevated in Gal (+326.6%), Gal + amantadine (+296.9%), Gal + aminoguanidine (+254.5%), Gal + ALA (+391.9%), Gal + NAC (+457.9%), and Gal + AA (+568.3%) when compared to BSA. βA content was markedly lower in GO + aminoguanidine (−57.9%), GO + NAC (−22%), and GO + AA (−21.8%) than in GO. The production of βA was substantially increased in GO (+363.6%), GO + amantadine (+417.8%), GO + aminoguanidine (+153%), GO + ALA (+338.4%), GO + NAC (+283.7%), as well as GO + AA (+284.3%) in comparison with BSA. βA fluorescence was efficiently reduced in MGO + aminoguanidine (−19%) and MGO + NAC (−20.2%) versus MGO. This parameter was meaningfully higher in MGO + AA (+27.2%) than in MGO alone. The content of βA was substantially raised in MGO (+190.4%), MGO + amantadine (+193.4%), MGO + aminoguanidine (+154.2%), MGO + ALA (+191.3%), MGO + NAC (+151.9%), and MGO + AA (+242.1%) versus BSA. The marker was efficiently lower in ChT + aminoguanidine (−60.2%), ChT + NAC (−63.8%), and ChT + AA (−57%) than in ChT. βA fluorescence was relevantly elevated in ChT (+322.8%), ChT + amantadine (+348.3%), ChT + aminoguanidine (+128.5%), ChT + ALA (+306.4%), ChT + NAC (+116.9%), as well as ChT + AA (+138.8%) in comparison with BSA (The content of AGE was significantly reduced in Glc + aminoguanidine (−15.2%) and Glc + NAC (−10%) compared to Glc. AGE production was effectively elevated in Glc + AA (+55.5%) versus Glc alone. AGE fluorescence was markedly higher in Glc (+100.2%), Glc + amantadine (+101.4%), Glc + aminoguanidine (+85%), Glc + ALA (+101%), Glc + NAC (+90.1%), as well as Glc + AA (+155.7%) in comparison with BSA. The parameter was substantially decreased in Fru + aminoguanidine (−31.9%) than in Fru. AGE content was significantly increased in Fru + AA (+49.7%) versus Fru alone. The marker was relevantly enhanced in Fru (+144.4%), Fru + amantadine (+140.2%), Fru + aminoguanidine (+98.3%), Fru + ALA (+144%), Fru + NAC (+139.3%), and Fru + AA (+216.1%) compared to BSA. The fluorescence of AGE was considerably attenuated in Gal + aminoguanidine (−27.3%) and Gal + NAC (−10.8%) versus Gal. This parameter of AGE was significantly higher in Gal + AA (+82.6%) than in Gal alone. The content of AGE was effectively increased in Gal (+163.9%), Gal + amantadine (+170.6%), Gal + aminoguanidine (+119.2%), Gal + ALA (+176.2%), Gal + NAC (+146.3%), as well as Gal + AA (+299.3%) compared to BSA. AGE fluorescence was markedly lower in GO + aminoguanidine (−50.5%), GO + NAC (−59.9%), and GO + AA (−22.4%) than in GO. The biomarker was substantially enhanced in GO + ALA (+7.5%) versus GO alone. AGE content efficiently increased in GO (+333.5%), GO + amantadine (+351.1%), GO + aminoguanidine (+165%), GO + ALA (+358.5%), GO + NAC (+133.8%), and GO + AA (+258.7%) in comparison with BSA. The parameter was relevantly reduced in MGO + amantadine (−5.1%) and MGO + aminoguanidine (−50.5%) versus MGO. The generation of AGE was significantly raised in MGO (+471.4%), MGO + amantadine (+447.5%), MGO + aminoguanidine (+233.4%), MGO + ALA (+450.5%), MGO + NAC (+437.5%), as well as MGO + AA (+514.8%) compared to BSA. The fluorescence of AGE was significantly lower in ChT + aminoguanidine (−35.7%), ChT + NAC (−16.4%), and ChT + AA (−25.7%) than in ChT. This parameter was effectively elevated in ChT (+13.5%), ChT + amantadine (+15%), ChT + aminoguanidine (+8.7%), ChT + ALA (+13.9%), as well as ChT + AA (+10.1%) in comparison with BSA .Since fluorometric measurements of BSA glycoxidation can be interfered by additives, AGE content was also determined by ELISA. We showed that AGE evaluation by the fluorometric technique is consistent with the results of the reference method (ELISA) , lysine (LYS) and TRY). AOPP are the end products of the complex process of protein oxidation. They are aggregates, fragments or derivatives of oxidatively altered albumin, fibrinogen or lipoproteins. It is known that AOPP molecules contain DT, PC, and modified residues of TRY, TYR, ARG, LYS and sulphur-containing amino acidsPC concentration was significantly improved in Glc (+104.8%) in comparison to BSA. The biomarker was effectively increased in Fru + amantadine (+123.9%) and Fru + aminoguanidine (+45.8%) versus Fru. The level of PC was markedly decreased in Fru + NAC (−30.5%) and Fru + AA (−43.8%) compared to Fru alone. The parameter was substantially elevated in Fru + amantadine (+77.5%), as well as Fru + aminoguanidine (+50.5%) versus BSA. PC level was considerably higher in Gal (+71.4%) than in BSA. The marker was relevantly reduced in GO + NAC (−63.6%) in comparison with GO. The content of PC was markedly increased in GO (+142.3%) and GO + amantadine (+136.5%) compared to BSA. This parameter was significantly elevated in ChT (+136.9%), ChT + amantadine (+146.8%), ChT + aminoguanidine (+147.1%), ChT + ALA (+135.3%), ChT + NAC (+165.2%), as well as ChT + AA (+140.8%) versus ChT. PC concentration was substantially lower in ChT + aminoguanidine (−58.7%), ChT + ALA (−17.4%), ChT + NAC (−28.7%), and ChT + AA (−47.4%) than in ChT alone. The level of PC was markedly enhanced in ChT (+128.3%), ChT + aminoguanidine (+129.6%), ChT + ALA (+106%), as well as ChT + NAC (+91.5%) in comparison with BSA (The level of AOPP was significantly lower in Glc + aminoguanidine (−15.5%), Glc + NAC (−47.8%), and Glc + AA (−48.3%) than in Glc. The biomarker was effectively improved in Glc (+48.5%), Glc + amantadine (+48%), as well as Glc + aminoguanidine (+41%) in comparison with BSA. AOPP concentration was markedly decreased in Fru + aminoguanidine (−51.5%) versus Fru. The parameter was significantly increased in Fru + NAC (+47.9%) compared to Fru alone. AOPP level was markedly elevated in Fru (+45.4%), Fru + amantadine (+55.2%), Fru + aminoguanidine (+22%), Fru + NAC (+67.1%), as well as Fru + AA (+49.1%) in comparison with BSA. The concentration of AOPP was considerably enhanced in Gal + amantadine (+424.8%) and Gal + NAC (+118.5%) versus Gal. The level of AOPP was significantly reduced in Gal + aminoguanidine (−75.8%) when compared to Gal alone. AOPP were relevantly higher in Gal (+67%), Gal + amantadine (+351.5%), Gal + aminoguanidine (+16.2%), and Gal + ALA (+146.3%) than in BSA. The parameter was markedly diminished in GO + NAC (−21.7%) in comparison with GO. The marker was significantly elevated in GO (+166.9%), GO + amantadine (+167.2%), and GO + aminoguanidine (+151.5%), GO + ALA (+190.7%), GO + NAC (+130.6%), as well as GO + AA (+161.1%) compared to BSA. AOPP concentration was notedly boosted in MGO + aminoguanidine (+115.8%) in comparison with MGO. This parameter was substantially increased in MGO (+249.8%), MGO + amantadine (+245.5%), MGO + aminoguanidine (+539%), MGO + ALA (+298.5%), MGO + NAC (+260.8%), as well as MGO + AA (+291%) when compared to BSA. AOPP level was markedly inhibited in ChT + amantadine (−10.2%), ChT + aminoguanidine (−82.6%), ChT + ALA (−11.9%), ChT + NAC (−98.4%), and ChT + AA (−98.1%) versus ChT. The concentration of AOPP was significantly enhanced in ChT (+4201.1%), ChT + amantadine (+3773.4%), ChT + aminoguanidine (+732.7%), ChT + ALA (+3701.1%), as well as ChT + NAC (+68.1%) in comparison with BSA  below 3 , but non,in vitro study determining the impact of amantadine on protein glycoxidation. We used the BSA model for this purpose.Amantadine is a drug used in the prevention/treatment of influenza A, but primarily in Parkinson’s disease and parkinsonian syndromes,Albumin is the major plasma protein,,,in vitro BSA model. Two LYS residues (LYS-524 and LYS-232) were found to be the main sites of Glc-induced glycation of BSA responsible for about 30% of total albumin glycation,,,,,,,In the present study, we used various glycation  and oxidation (ChT) factors to determine the impact of amantadine on glycoxidation, glycation, and oxidation protein products. Glycation is a non-enzymatic reaction that occurs between the carbonyl group of reducing sugars and proteins with high levels of free amino groupsMolecular docking analysis did not reveal strong binding sites of amantadine on the BSA structure, which can be a probable reason for the lack of protective effect against protein oxidation/glycation. The source of amantadine’s ability to promote oxidative and carbonyl stress may be another feature of its structure. The amino group attached to the cyclic ring is an activating substituent that may be the reason of prooxidant properties of the compound2O2 at the level of about 50–65%. Amantadine can therefore exhibit antioxidant activity, although it is weaker than the commonly used antioxidants. Moreover, our study confirms previous reports on the proglycation properties of AA,Well-known glycation inhibitors and antioxidants were used to compare amantadine’s ability to protect against carbonyl stress. Aminoguanidine prevents glycation through competition, dicarbonyl scavenging, as well as antioxidant activity due to the occurrence of a guanidinium group2•− in in vitro models, as well as reduced oxidative damage in 2-deoxyribose- and dopamine-secreting neuronsb]furan derivatives of amantadine inhibited lipid peroxidation in vitroin vitro inhibition of ROS production and lipid peroxidation; in vivo enhancement of the antioxidant barrier and reduction of protein and lipid oxidation),The effects of other adamantane derivatives on carbonyl stress have never been comprehensively studied. The literature provides only isolated papers examining the antioxidant potential of these drugs. Nitroxyl radical derivatives of amantadine diminished the content of HO• and O2O2, it has significantly lower antioxidant and antiglycation effect than all ROS scavengers and protein glycation inhibitors. Data from the literature review indicate that the protective effect of amantadine is more likely due to improved neuronal metabolism, which is secondarily responsible for reduced protein oxidation and glycation,,,,,In summary, amantadine exerted poor antioxidant properties and a lack of antiglycation activity per se. Although amantadine poorly scavenged HO• and HClick here for additional data file.