Objective To evaluate the gastric microbiome in patients with chronic superficial gastritis(CSG)and intestinal metaplasia(IM)and investigate the influence of Helicobacter pylori(H.pylori)on the gastric microbiome.Meth...Objective To evaluate the gastric microbiome in patients with chronic superficial gastritis(CSG)and intestinal metaplasia(IM)and investigate the influence of Helicobacter pylori(H.pylori)on the gastric microbiome.Methods Gastric mucosa tissue samples were collected from 54 patients with CSG and IM,and the patients were classified into the following four groups based on the state of H.pylori infection and histology:H.pylori-negative CSG(n=24),H.pylori-positive CSG(n=14),H.pylori-negative IM(n=11),and H.pylori-positive IM(n=5).The gastric microbiome was analyzed by 16S rRNA gene sequencing.Results H.pylori strongly influenced the bacterial abundance and diversity regardless of CSG and IM.In H.pylori-positive subjects,the bacterial abundance and diversity were significantly lower than in H.pylori-negative subjects.The H.pylori-negative groups had similar bacterial composition and bacterial abundance.The H.pylori-positive groups also had similar bacterial composition but different bacterial relative abundance.The relative abundance of Neisseria,Streptococcus,Rothia,and Veillonella were richer in the I-HP group than in G-HP group,especially Neisseria(t=175.1,P<0.001).Conclusions The gastric microbial abundance and diversity are lower in H.pylori-infected patients regardless of CSG and IM.Compared to H.pylori-positive CSG group and H.pylori-positive IM,the relative abundance of Neisseria,Streptococcus,Rothia,and Veillonella is higher in H.pylori-positive patients with IM than in H.pylori-positive patients with CSG,especially Neisseria.展开更多
Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images(WSIs).Methods We retrospectively collected 1,250 gastric biopsy ...Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images(WSIs).Methods We retrospectively collected 1,250 gastric biopsy specimens(1,128 gastritis,122 normal mucosa)from PLA General Hospital.The deep learning algorithm based on DeepLab v3(ResNet-50)architecture was trained and validated using 1,008 WSIs and 100 WSIs,respectively.The diagnostic performance of the algorithm was tested on an independent test set of 142 WSIs,with the pathologists’consensus diagnosis as the gold standard.Results The receiver operating characteristic(ROC)curves were generated for chronic superficial gastritis(CSuG),chronic active gastritis(CAcG),and chronic atrophic gastritis(CAtG)in the test set,respectively.The areas under the ROC curves(AUCs)of the algorithm for CSuG,CAcG,and CAtG were 0.882,0.905 and 0.910,respectively.The sensitivity and specificity of the deep learning algorithm for the classification of CSuG,CAcG,and CAtG were 0.790 and 1.000(accuracy 0.880),0.985 and 0.829(accuracy 0.901),0.952 and 0.992(accuracy 0.986),respectively.The overall predicted accuracy for three different types of gastritis was 0.867.By flagging the suspicious regions identified by the algorithm in WSI,a more transparent and interpretable diagnosis can be generated.Conclusion The deep learning algorithm achieved high accuracy for chronic gastritis classification using WSIs.By pre-highlighting the different gastritis regions,it might be used as an auxiliary diagnostic tool to improve the work efficiency of pathologists.展开更多
Ninety-two asymptomafic subjects were investigated to determine whether they were in-fected with Helicobacter pylori(HP)by means of fiber gastroscopy, urease test andWarthin-Starry silver stain.As a result of this wor...Ninety-two asymptomafic subjects were investigated to determine whether they were in-fected with Helicobacter pylori(HP)by means of fiber gastroscopy, urease test andWarthin-Starry silver stain.As a result of this work,49 subjects with HP infection were found.Under gastroscope,24 of 92 subjects had normal gastric mucosa 45 suffered frompiebaldism-like congestion of the gastric mucosa and 23 mucosal erosion,but the differencesamong the detectable rotes of them had no statistical significance(P】0.05).Forty-six of the subjects with HP infection were seen in the 67 patients with gastritis and only 3 in the subjectswith normal mucosa.The positive rates of HP infection in the patients with moderate and serfous gastritis were significant highly(P【0.01),as compared with that in mild gastritis.It could besuggested that HP infection and the gastritis associated with it may universally exist in“healthy persons”without symptom.展开更多
According to the basic theory of the tradi-tional Chinese medicine,we have composed aprescription called Shen Xiang Yang Wei San(SXYWS,a powder)to treat chronic gastritis.After intravenous injection,it can evidently i...According to the basic theory of the tradi-tional Chinese medicine,we have composed aprescription called Shen Xiang Yang Wei San(SXYWS,a powder)to treat chronic gastritis.After intravenous injection,it can evidently incr-展开更多
基金supported by the Medicine and Health,Science and Technology Plan Project of Zhejiang(2020KY1009).
文摘Objective To evaluate the gastric microbiome in patients with chronic superficial gastritis(CSG)and intestinal metaplasia(IM)and investigate the influence of Helicobacter pylori(H.pylori)on the gastric microbiome.Methods Gastric mucosa tissue samples were collected from 54 patients with CSG and IM,and the patients were classified into the following four groups based on the state of H.pylori infection and histology:H.pylori-negative CSG(n=24),H.pylori-positive CSG(n=14),H.pylori-negative IM(n=11),and H.pylori-positive IM(n=5).The gastric microbiome was analyzed by 16S rRNA gene sequencing.Results H.pylori strongly influenced the bacterial abundance and diversity regardless of CSG and IM.In H.pylori-positive subjects,the bacterial abundance and diversity were significantly lower than in H.pylori-negative subjects.The H.pylori-negative groups had similar bacterial composition and bacterial abundance.The H.pylori-positive groups also had similar bacterial composition but different bacterial relative abundance.The relative abundance of Neisseria,Streptococcus,Rothia,and Veillonella were richer in the I-HP group than in G-HP group,especially Neisseria(t=175.1,P<0.001).Conclusions The gastric microbial abundance and diversity are lower in H.pylori-infected patients regardless of CSG and IM.Compared to H.pylori-positive CSG group and H.pylori-positive IM,the relative abundance of Neisseria,Streptococcus,Rothia,and Veillonella is higher in H.pylori-positive patients with IM than in H.pylori-positive patients with CSG,especially Neisseria.
文摘Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images(WSIs).Methods We retrospectively collected 1,250 gastric biopsy specimens(1,128 gastritis,122 normal mucosa)from PLA General Hospital.The deep learning algorithm based on DeepLab v3(ResNet-50)architecture was trained and validated using 1,008 WSIs and 100 WSIs,respectively.The diagnostic performance of the algorithm was tested on an independent test set of 142 WSIs,with the pathologists’consensus diagnosis as the gold standard.Results The receiver operating characteristic(ROC)curves were generated for chronic superficial gastritis(CSuG),chronic active gastritis(CAcG),and chronic atrophic gastritis(CAtG)in the test set,respectively.The areas under the ROC curves(AUCs)of the algorithm for CSuG,CAcG,and CAtG were 0.882,0.905 and 0.910,respectively.The sensitivity and specificity of the deep learning algorithm for the classification of CSuG,CAcG,and CAtG were 0.790 and 1.000(accuracy 0.880),0.985 and 0.829(accuracy 0.901),0.952 and 0.992(accuracy 0.986),respectively.The overall predicted accuracy for three different types of gastritis was 0.867.By flagging the suspicious regions identified by the algorithm in WSI,a more transparent and interpretable diagnosis can be generated.Conclusion The deep learning algorithm achieved high accuracy for chronic gastritis classification using WSIs.By pre-highlighting the different gastritis regions,it might be used as an auxiliary diagnostic tool to improve the work efficiency of pathologists.
文摘Ninety-two asymptomafic subjects were investigated to determine whether they were in-fected with Helicobacter pylori(HP)by means of fiber gastroscopy, urease test andWarthin-Starry silver stain.As a result of this work,49 subjects with HP infection were found.Under gastroscope,24 of 92 subjects had normal gastric mucosa 45 suffered frompiebaldism-like congestion of the gastric mucosa and 23 mucosal erosion,but the differencesamong the detectable rotes of them had no statistical significance(P】0.05).Forty-six of the subjects with HP infection were seen in the 67 patients with gastritis and only 3 in the subjectswith normal mucosa.The positive rates of HP infection in the patients with moderate and serfous gastritis were significant highly(P【0.01),as compared with that in mild gastritis.It could besuggested that HP infection and the gastritis associated with it may universally exist in“healthy persons”without symptom.
文摘According to the basic theory of the tradi-tional Chinese medicine,we have composed aprescription called Shen Xiang Yang Wei San(SXYWS,a powder)to treat chronic gastritis.After intravenous injection,it can evidently incr-
