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In this study, deer suet fat was used as a raw material to study the effects of aqueous enzymatic extraction of deer oil on its components, followed by studies into the potential protective activity, and related molecular mechanisms of deer oil on ethanol-induced acute gastric mucosal injury in rats. The results show that aqueous enzymatic extraction of deer oil not only has a high extraction yield and has a small effect on the content of active ingredients. Deer oil can reduce total stomach injury. Without affecting the blood lipid level, it can reduce the oxidative stress, which is manifested by reducing the content of myeloperoxidase (MPO) and enhancing the activity level of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px). It also enhances the expression of defense factors prostaglandin (E2), epidermal growth factor (EGF), and somatostatin (SS), it inhibits apoptosis evidenced by the enhanced of Bcl-2 and decreased expression of cleavage of caspase-3 and Bax. At the same time, it reduces inflammation, which is manifested by reducing the expression of IL-1β, interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α) gastric tissue pro-inflammatory cytokines, and enhancing the expression of anti-inflammatory factors IL-4 and IL-10, and inhibiting the mitogen-activated protein kinase/nuclear factor kappa B (MAPK/NF-κB) signaling pathway in gastric tissue.

In this study, deer suet fat was used as a raw material to study the effects of aqueous enzymatic extraction of deer oil on its components, followed by studies into the potential protective activity, and related molecular mechanisms of deer oil on ethanol-induced acute gastric mucosal injury in rats. The results show that aqueous enzymatic extraction of deer oil not only has a high extraction yield and has a small effect on the content of active ingredients. Deer oil can reduce total stomach injury. Without affecting the blood lipid level, it can reduce the oxidative stress, which is manifested by reducing the content of myeloperoxidase (MPO) and enhancing the activity level of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px). It also enhances the expression of defense factors prostaglandin (E2), epidermal growth factor (EGF), and somatostatin (SS), it inhibits apoptosis evidenced by the enhanced of Bcl-2 and decreased expression of cleavage of caspase-3 and Bax. At the same time, it reduces inflammation, which is manifested by reducing the expression of IL-1β, interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α) gastric tissue pro-inflammatory cytokines, and enhancing the expression of anti-inflammatory factors IL-4 and IL-10, and inhibiting the mitogen-activated protein kinase/nuclear factor kappa B (MAPK/NF-κB) signaling pathway in gastric tissue.

# Quantitative plant resistance enhances pathogen adaptation to ecological stresses [https://doi.org/10.5061/dryad.573n5tbh7](https://doi.org/10.5061/dryad.573n5tbh7) ## Description of the data and file structure Raw data belonging to: Li-Na Yang†, Zhe-Chao Pan†, Oswald Nkurikiyimfura†, Jianjun Lu, Yan-Ping Wang, Ying Wang, Abdul Waheed, Han-Mei Fang, Peter H. Thrall, Jeremy J. Burdon, Qi-Jun Sui*, Jiasui Zhan*. (2024), Quantitative plant resistance enhances pathogen adaptation to ecological stresses, Nature Communications### Files and variables #### File: NCOMMS\_Data.zip **Description:** | Metadata for file ‘1-Raw Data’ | | | | :---------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------- | | | | | | Numerical order of Raw data | Content | Abbreviations | | Raw data 1 | Resistance level of the 16 potato varities measured by AUDPC which is calculated from the visual estimate of disease severity in field | AUDPC = Area Under Disease Progress Curves | | Raw data 2 | Resistance level of the 16 potato varieties evaluated by greenhouse measurement of lesion size | n/a = not available | | Raw data 3 | Incubation period of Phytophthora infestans populations collected from the 16 potato varieties | n/a = not available | | Raw data 4 | Lesion size (aggressiveness cm2) of Phytophthora infestans isolates collected from the 16 potato varieties | | | Raw data 5 | Pathotype complexity of Phytophthora infestans strains collected from the 16 potato varieties (0= no infection, 1 = infection) | | | Raw data 6 | Colony size (cm2) used to calculate RGR of Mancozeb treatment | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Raw data 7 | Colony size (cm2) used to calculate EC50 of Mancozeb treatment | EC50 = Half maximum effective concentration, n/a = not available | | Raw data 8 | Colony size (cm2) used to calculate RGR of Azoxytrombin treatment | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Raw data 9 | Colony size (cm2) used to calculate EC50 of Azoxystrobin treatment | EC50 = Half maximum effective concentration, n/a = not available | | Raw data 10 | Colony size (cm2) used to calculate RGR at 25℃ | RGR = Relative growth rate of the pathogen with and without fungicide | | Raw data 11 | Colony size (cm2) used to calculate RGR at 13℃ | | | Raw data 12 | Colony size (cm2) used to calculate RGR for H2O2 treatment | | | Raw data 13 | Colony size (cm2) used to calculate RGR under UV treatment | | | Raw data 14 | Colony size (cm2) used to calculate RGR with NaCl treatment | n/a = not available | | Raw data 15 | Sporangium yield (per view) in the P. infestans populations collected from the 16 potato varieties | n/a = not available | | Raw data 16 | Mating types (+ = self-fertile, - = Non self-fertile) in the P. infestans isolates collected from the 16 potato varieties | | | Raw data 17 | Colony size (cm2) used to calculate growth rate of the isolates on agar | n/a = not available | | Raw data 18 | The gene expression level of Pinf\_014372, Pinf\_017755 and Pinf\_022024 | | | | | | | Metadata for file ‘2-Expanded data’ | | | | | | | | Numerical order of Expanded data | Content | Abbreviations | | Expanded data 1 | Mancozeb resistance measured by RGR in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Expanded data 2 | Mancozeb resistance measured by EC50 in the P. infestans populations collected from the 16 potato varieties | EC50 = Half maximum effective concentration | | Expanded data 3 | Azoxystrobin resistance measured by RGR in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Expanded data 4 | Azoxystrobin resistance measured by EC50 in the P. infestans populations collected from the 16 potato varieties | EC50 = Half maximum effective concentration | | Expanded data 5 | RGR under 25℃ (high temperature) of the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide | | Expanded data 6 | RGR under 13℃ (low temperature) of the P. infestans populations collected from the 16 potato varieties | | | Expanded data 7 | RGR under H2O2 treatment of the P. infestans populations collected from the 16 potato varieties | | | Expanded data 8 | RGR under UV treatment in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, UV = Ultraviolet | | Expanded data 9 | RGR under NaCl treatment in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, NaCl = Sodium Chloride | | Expanded data 10 | The linkage disequilibrium (LD) decay patterns in the P. infestans genomes (HQPR, LQPR and all combined) | HQPR = High Quantitative Plant Resistance, LQPR = Low Quantitative Plant Resistance | | Expanded data 11 | Pairwise differences in the number of SNPs and Indels between the genomes of HQPR- and LQPR-derived pathogens | SNPs = Single Nucleotide Polymorphism, HQPR = High Quantitative Plant Resistance, LQPR = Low Quantitative Plant Resistance | | Expanded data 12 | Differences of SNPs and Indels in the P. infestans genomes and differences in the resistance of potato varieties | SNPs = Single Nucleotide Polymorphism | | Expanded data 13 | Chromosome walking of genetic differentiation (Fst) between HQPR- and LQPR-derived pathogen genomes, ‘HQPR’ and ‘LQPR’ | HQPR = High Quantitative Plant Resistance, LQPR = Low Quantitative Plant Resistance | ## Code/software Zip and Excel Host-pathogen interactions play an important role in shaping ecosystems with many fundamental and applied implications. However, many aspects of the processes, consequences and mechanisms of these antagonistic interactions are still unknown. Evolutionary theory hypothesizes that quantitative plant resistance (QPR) enhances pathogen pathogenicity, therefore, threatening ecological function and sustainability but this hypothesis has rarely been tested empirically. Here, we present results from an eco-evolutionary study of a quantitative plant-pathogen interaction using 16 potato varieties and >2000 Phytophthora infestans strains. Twelve functional traits in a subset (>300 strains) of the P. infestans populations derived from these varieties were compared. Our results indicate that QPR enhances pathogen pathogenicity and facilitates pathogen adaptation to other disease management attempts including the deployment of qualitative plant resistance and the application of fungicides, and to environmental and chemical stresses including salinity, UV radiation, H2O2, heat and cold. QPR also increases pathogen spore production and potential of sexual recombination thereby enhancing the generation of new variation for adaptation. Genome-wide analyses indicate that the observed patterns of functional variation result from increased selection from potato varieties with higher QPR and that a substantial portion of genome are involved in the adaptation genetically and epigenetically. Our results highlight a potential risk to ecological function and resilience associated with continuing deployment of QPR, particularly under future climate conditions and are expected to stimulate further investigation into this important phenomenon with many host-pathogen systems.

# Quantitative plant resistance enhances pathogen adaptation to ecological stresses [https://doi.org/10.5061/dryad.573n5tbh7](https://doi.org/10.5061/dryad.573n5tbh7) ## Description of the data and file structure Raw data belonging to: Li-Na Yang†, Zhe-Chao Pan†, Oswald Nkurikiyimfura†, Jianjun Lu, Yan-Ping Wang, Ying Wang, Abdul Waheed, Han-Mei Fang, Peter H. Thrall, Jeremy J. Burdon, Qi-Jun Sui*, Jiasui Zhan*. (2024), Quantitative plant resistance enhances pathogen adaptation to ecological stresses, Nature Communications### Files and variables #### File: NCOMMS\_Data.zip **Description:** | Metadata for file ‘1-Raw Data’ | | | | :---------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------- | | | | | | Numerical order of Raw data | Content | Abbreviations | | Raw data 1 | Resistance level of the 16 potato varities measured by AUDPC which is calculated from the visual estimate of disease severity in field | AUDPC = Area Under Disease Progress Curves | | Raw data 2 | Resistance level of the 16 potato varieties evaluated by greenhouse measurement of lesion size | n/a = not available | | Raw data 3 | Incubation period of Phytophthora infestans populations collected from the 16 potato varieties | n/a = not available | | Raw data 4 | Lesion size (aggressiveness cm2) of Phytophthora infestans isolates collected from the 16 potato varieties | | | Raw data 5 | Pathotype complexity of Phytophthora infestans strains collected from the 16 potato varieties (0= no infection, 1 = infection) | | | Raw data 6 | Colony size (cm2) used to calculate RGR of Mancozeb treatment | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Raw data 7 | Colony size (cm2) used to calculate EC50 of Mancozeb treatment | EC50 = Half maximum effective concentration, n/a = not available | | Raw data 8 | Colony size (cm2) used to calculate RGR of Azoxytrombin treatment | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Raw data 9 | Colony size (cm2) used to calculate EC50 of Azoxystrobin treatment | EC50 = Half maximum effective concentration, n/a = not available | | Raw data 10 | Colony size (cm2) used to calculate RGR at 25℃ | RGR = Relative growth rate of the pathogen with and without fungicide | | Raw data 11 | Colony size (cm2) used to calculate RGR at 13℃ | | | Raw data 12 | Colony size (cm2) used to calculate RGR for H2O2 treatment | | | Raw data 13 | Colony size (cm2) used to calculate RGR under UV treatment | | | Raw data 14 | Colony size (cm2) used to calculate RGR with NaCl treatment | n/a = not available | | Raw data 15 | Sporangium yield (per view) in the P. infestans populations collected from the 16 potato varieties | n/a = not available | | Raw data 16 | Mating types (+ = self-fertile, - = Non self-fertile) in the P. infestans isolates collected from the 16 potato varieties | | | Raw data 17 | Colony size (cm2) used to calculate growth rate of the isolates on agar | n/a = not available | | Raw data 18 | The gene expression level of Pinf\_014372, Pinf\_017755 and Pinf\_022024 | | | | | | | Metadata for file ‘2-Expanded data’ | | | | | | | | Numerical order of Expanded data | Content | Abbreviations | | Expanded data 1 | Mancozeb resistance measured by RGR in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Expanded data 2 | Mancozeb resistance measured by EC50 in the P. infestans populations collected from the 16 potato varieties | EC50 = Half maximum effective concentration | | Expanded data 3 | Azoxystrobin resistance measured by RGR in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, n/a = not available | | Expanded data 4 | Azoxystrobin resistance measured by EC50 in the P. infestans populations collected from the 16 potato varieties | EC50 = Half maximum effective concentration | | Expanded data 5 | RGR under 25℃ (high temperature) of the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide | | Expanded data 6 | RGR under 13℃ (low temperature) of the P. infestans populations collected from the 16 potato varieties | | | Expanded data 7 | RGR under H2O2 treatment of the P. infestans populations collected from the 16 potato varieties | | | Expanded data 8 | RGR under UV treatment in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, UV = Ultraviolet | | Expanded data 9 | RGR under NaCl treatment in the P. infestans populations collected from the 16 potato varieties | RGR = Relative growth rate of the pathogen with and without fungicide, NaCl = Sodium Chloride | | Expanded data 10 | The linkage disequilibrium (LD) decay patterns in the P. infestans genomes (HQPR, LQPR and all combined) | HQPR = High Quantitative Plant Resistance, LQPR = Low Quantitative Plant Resistance | | Expanded data 11 | Pairwise differences in the number of SNPs and Indels between the genomes of HQPR- and LQPR-derived pathogens | SNPs = Single Nucleotide Polymorphism, HQPR = High Quantitative Plant Resistance, LQPR = Low Quantitative Plant Resistance | | Expanded data 12 | Differences of SNPs and Indels in the P. infestans genomes and differences in the resistance of potato varieties | SNPs = Single Nucleotide Polymorphism | | Expanded data 13 | Chromosome walking of genetic differentiation (Fst) between HQPR- and LQPR-derived pathogen genomes, ‘HQPR’ and ‘LQPR’ | HQPR = High Quantitative Plant Resistance, LQPR = Low Quantitative Plant Resistance | ## Code/software Zip and Excel Host-pathogen interactions play an important role in shaping ecosystems with many fundamental and applied implications. However, many aspects of the processes, consequences and mechanisms of these antagonistic interactions are still unknown. Evolutionary theory hypothesizes that quantitative plant resistance (QPR) enhances pathogen pathogenicity, therefore, threatening ecological function and sustainability but this hypothesis has rarely been tested empirically. Here, we present results from an eco-evolutionary study of a quantitative plant-pathogen interaction using 16 potato varieties and >2000 Phytophthora infestans strains. Twelve functional traits in a subset (>300 strains) of the P. infestans populations derived from these varieties were compared. Our results indicate that QPR enhances pathogen pathogenicity and facilitates pathogen adaptation to other disease management attempts including the deployment of qualitative plant resistance and the application of fungicides, and to environmental and chemical stresses including salinity, UV radiation, H2O2, heat and cold. QPR also increases pathogen spore production and potential of sexual recombination thereby enhancing the generation of new variation for adaptation. Genome-wide analyses indicate that the observed patterns of functional variation result from increased selection from potato varieties with higher QPR and that a substantial portion of genome are involved in the adaptation genetically and epigenetically. Our results highlight a potential risk to ecological function and resilience associated with continuing deployment of QPR, particularly under future climate conditions and are expected to stimulate further investigation into this important phenomenon with many host-pathogen systems.

Green consumption is an important component of environmental protection behavior. The behaviors of individual consumers are having unprecedented impacts on the sustainable development of a green society. Previous research has discussed how anthropomorphic beneficiaries of environmental behavior (e.g., nature/earth) impact green consumption behavior and compared the influence of anthropomorphic presence and absence on consumers. However, few have examined the impact of different types of anthropomorphic carriers with environmental benefits (e.g., green product/brand) on consumers. This research explores the matching effects on the willingness of consumers to buy green products between the anthropomorphic image of the brand (cute vs. cool) and advertising appeals (self-interest vs. altruism); in addition, the underlying mechanisms of matching effects are revealed. The results show that, under the self-interested advertising appeal, the cool anthropomorphic image can lead to higher purchase intention of green products due to the mediating role played by the brand capacity trust. However, when exposed to altruistic advertising appeal, the cute anthropomorphic image can enhance brand goodwill trust of consumers and make consumers more willing to buy green products. Finally, this paper discusses the contributions and limitations.

Green consumption is an important component of environmental protection behavior. The behaviors of individual consumers are having unprecedented impacts on the sustainable development of a green society. Previous research has discussed how anthropomorphic beneficiaries of environmental behavior (e.g., nature/earth) impact green consumption behavior and compared the influence of anthropomorphic presence and absence on consumers. However, few have examined the impact of different types of anthropomorphic carriers with environmental benefits (e.g., green product/brand) on consumers. This research explores the matching effects on the willingness of consumers to buy green products between the anthropomorphic image of the brand (cute vs. cool) and advertising appeals (self-interest vs. altruism); in addition, the underlying mechanisms of matching effects are revealed. The results show that, under the self-interested advertising appeal, the cool anthropomorphic image can lead to higher purchase intention of green products due to the mediating role played by the brand capacity trust. However, when exposed to altruistic advertising appeal, the cute anthropomorphic image can enhance brand goodwill trust of consumers and make consumers more willing to buy green products. Finally, this paper discusses the contributions and limitations.

Constructs tested for phosphatase secretion and activity.

Constructs tested for phosphatase secretion and activity.

Using 50% of castor oil with 50% cottonseed oil to use as additive in diesel of 99.75 to enhance lubrication.

Using 50% of castor oil with 50% cottonseed oil to use as additive in diesel of 99.75 to enhance lubrication.