Glycoengineering was carried out in the mammalian cell line CHO for the production of pro-tein-based drugs.Firstly,the genome sequence of the Rosa26 locus of CHO cells was determined,the gRNA sequences were designed,and the landing pad was integrated into the Rosa26 locus of CHO cells by CRISPR/Cas9 technology.Three targeting vectors co-expressed by glycosyltransferases,which are β-1,4 galactosyltransferase(B4GALT1),α-2,6-sialyltransferase 1(ST6GAL1)and N-acetaminoglycosyl-transferase Ⅲ(GnT Ⅲ),were constructed by overlapping PCR and seamless ligation technology,and the three glycosyltransferase genes were integrated into the CHO Rosa26 locus by Cre enzyme-mediated cassette exchange technology.PCR confirmed that three glycosyltransferases had been successfully site-directed integrated into the Rosa26 site.The mRNA expression levels of the three glycosyltransferases were more than 50 000-fold by qRT-PCR,and the protein expression levels of the three glycosyltrans-ferases were more than 4-fold via western blotting(P＜0.001).A CHO-engineered cell line with three glycosyltransferases integrated into Rosa26 site was successfully constructed.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Mesenchymal stem cells(MSCs)play a crucial role in tissue repair and regeneration,and the extracellular vesicle(EV)released by them holds great promise for applications in clinical biomarkers,vaccines,and drug delivery.However,MSCs-derived EV(MSCs-EV)face challenges such as low pro-duction yield,poor retention,and targeted delivery issues.There-fore,engineering MSCs-EV to enhance their performance and en-able visual research has become a hot topic.Curcumin(CUR),an active component in traditional chinese medicine,exhibits pharmacological effects but has limited bioavailability.Using MSCs-EV as a carrier for CUR delivery can address its solubility and bioavailability challenges.This article reviews the drug loading methods,engineering strategies of MSCs-EV,and their important applications in the delivery and treatment of CUR for cartilage injury diseases.It provides a basis for the clinical ap-plication of engineered MSCs-EV in CUR delivery for cartilage repair,offering potential solutions to the challenges in cartilage tissue repair.

Aim To explore the effect of astragalosideⅣ(AS-Ⅳ)on lipopolysaccharide(LPS)-induced po-larization and migration of RAW 264.7 macrophages and the underlying mechanism.Methods 1 mg·L-1 LPS was used to construct cell migration model.Scratch assay was utilized to determine cell migration rate.Immunofluorescence staining was utilized to de-tect the expression and location of F4/80,iNOS and Arg-1.CCK-8 assay was used to determine the viabili-ty of RAW 264.7 cells.Griess assay was used to measure NO content.Molecular docking was used to analyze the interaction between AS-Ⅳ and the core tar-gets such as cGAS and STING protein.Western blot was employed to detect the expression of iNOS,Arg-1,cGAS,STING,NF-κB p65 and p-NF-κB p65 protein.Results AS-Ⅳ significantly inhibited the migration and M1 polarization of RAW 264.7 cells induced by LPS.Moreover,AS-Ⅳ could interact with cGAS and STING protein,especially cGAS.Further Western blot assay showed that AS-Ⅳ significantly downregulated the expression of iNOS,cGAS,STING and p-NF-κB p65 protein.Conclusions AS-Ⅳ could promote mac-rophage M1 to M2 polarization,thereby inhibited mac-rophage migration through restraining the cGAS/STING/NF-κB signaling pathway,which provides a new therapeutic target for AS-Ⅳ to improve the early inflammatory response of AS.

This study predicts the quality markers(Q-markers) for the cough-relieving and phlegm-expelling effects of Kening Granules based on pharmacodynamics, plasma drug chemistry, network pharmacology, and pharmacokinetics. Strong ammonia solution spray and phenol red secretion assays were employed to evaluate the cough-relieving and phlegm-expelling effects of Kening Granules. Twentysix absorbed prototype components of Kening Granules were identified by ultra high performance liquid chromatography coupled with QExactive Plus quadrupole/Orbitrap high resolution mass spectrometry(UHPLC-Q-Exactive Plus Orbitrap HRMS). Through network pharmacology, 11 potential active components were screened out for the cough-relieving and phlegm-expelling effects of Kening Granules. The 11 components acted on 40 common targets such as IL6, TLR4, and STAT3, which mainly participated in PI3K/Akt, HIF-1, and EGFR signaling pathways. Pharmacokinetic quantitative analysis was performed for 7 prototype components. Three compounds including azelaic acid, caffeic acid, and vanillin were identified as Q-markers for the cough-relieving and phlegm-expelling effects of Kening Granules based on their effectiveness, transmissibility, and measurability. The results of this study are of great significance for clarifying the pharmacological substance basis, optimizing the quality standards, and promoting the clinical application of Kening Granules.
Drugs, Chinese Herbal/administration & dosage* ; Network Pharmacology ; Cough/blood* ; Male ; Humans ; Animals ; Rats ; Rats, Sprague-Dawley ; Biomarkers/blood* ; Quality Control ; Chromatography, High Pressure Liquid ; Antitussive Agents/chemistry*

The gut microbiota regulates intestinal nutrient absorption, participates in modulating host glucolipid metabolism, and contributes to ameliorating glucolipid metabolism disorder. Dysbiosis of the gut microbiota can compromise the integrity of the intestinal mucosal barrier, induce inflammatory responses, and exacerbate insulin resistance and abnormal lipid metabolism in the host. Dangua Humai Oral Liquid, a hospital-developed formulation for regulating glucolipid metabolism, has been granted a national invention patent and demonstrates significant clinical efficacy. This study aimed to investigate the effects of Dangua Humai Oral Liquid on gut microbiota and the intestinal mucosal barrier in a mouse model with glucolipid metabolism disorder. A glucolipid metabolism disorder model was established by feeding mice a high-glucose and high-fat diet. The mice were divided into a normal group, a model group, and a treatment group, with eight mice in each group. The treatment group received a daily gavage of Dangua Humai Oral Liquid(20 g·kg~(-1)), while the normal group and model group were given an equivalent volume of sterile water. After 15 weeks of intervention, glucolipid metabolism, intestinal mucosal barrier function, and inflammatory responses were evaluated. Metagenomics and untargeted metabolomics were employed to analyze changes in gut microbiota and associated metabolic pathways. Significant differences were observed between the indicators of the normal group and the model group. Compared with the model group, the treatment group exhibited marked improvements in glucolipid metabolism disorder, alleviated pathological damage in the liver and small intestine tissue, elevated expression of recombinant claudin 1(CLDN1), occluding(OCLN), and zonula occludens 1(ZO-1) in the small intestine tissue, and reduced serum levels of inflammatory factors lipopolysaccharides(LPS), lipopolysaccharide-binding protein(LBP), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α). At the phylum level, the relative abundance of Bacteroidota decreased, while that of Firmicutes increased. Lipid-related metabolic pathways were significantly altered. In conclusion, based on the successful establishment of the mouse model of glucolipid metabolism disorder, this study confirmed that Dangua Humai Oral Liquid effectively modulates gut microbiota and mucosal barrier function, reduces serum inflammatory factor levels, and regulates lipid-related metabolic pathways, thereby ameliorating glucolipid metabolism disorder.
Animals ; Gastrointestinal Microbiome/drug effects* ; Mice ; Intestinal Mucosa/microbiology* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice, Inbred C57BL ; Humans ; Glycolipids/metabolism* ; Lipid Metabolism/drug effects* ; Administration, Oral ; Disease Models, Animal

The aim of this investigation was to determine the optimal storage medium for testicular hypothermic transportation and identify the ideal concentration for the application of the protective agent 5-aminolevulinic acid (5-ALA). Furthermore, this study aimed to explore the underlying mechanism of the protective effects of 5-ALA. First, we collected and stored mouse testicular fragments in different media, including Hank's balanced salt solution (HBSS; n = 5), Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F12; n = 5), and alpha-minimum essential medium (αMEM; n = 5). Storage of testicular tissue in HBSS preserved the integrity of testicular morphology better than that in the DMEM/F12 group ( P < 0.05) and the αMEM group ( P < 0.01). Testicular fragments were subsequently placed in HBSS with various concentrations of 5-ALA (0 [control], 1 mmol l -1 , 2 mmol l -1 , and 5 mmol l -1 ) to determine the most effective concentration of 5-ALA. The 2 mmol l -1 5-ALA group ( n = 3) presented the highest positive rate of spermatogonial stem cells compared with those in the control, 1 mmol l -1 , and 5 mmol l -1 5-ALA groups. Finally, the tissue fragments were preserved in HBSS with control ( n = 3) and 2 mmol l -1 5-ALA ( n = 3) under low-temperature conditions. A comparative analysis was performed against fresh testes ( n = 3) to elucidate the underlying mechanism of 5-ALA. Gene set enrichment analysis (GSEA) for WikiPathways revealed that the p38 mitogen-activated protein kinase (MAPK) signaling pathway was downregulated in the 2 mmol l -1 5-ALA group compared with that in the control group (normalized enrichment score [NES] = -1.57, false discovery rate [FDR] = 0.229, and P = 0.019). In conclusion, these data suggest that using 2 mmol l -1 5-ALA in HBSS effectively protected the viability of spermatogonial stem cells upon hypothermic transportation.
Male ; Animals ; Testis/cytology* ; Aminolevulinic Acid/pharmacology* ; Mice ; Organ Preservation/methods* ; Organ Preservation Solutions/pharmacology* ; Cryopreservation/methods*

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Mesenchymal stem cells(MSCs)play a crucial role in tissue repair and regeneration,and the extracellular vesicle(EV)released by them holds great promise for applications in clinical biomarkers,vaccines,and drug delivery.However,MSCs-derived EV(MSCs-EV)face challenges such as low pro-duction yield,poor retention,and targeted delivery issues.There-fore,engineering MSCs-EV to enhance their performance and en-able visual research has become a hot topic.Curcumin(CUR),an active component in traditional chinese medicine,exhibits pharmacological effects but has limited bioavailability.Using MSCs-EV as a carrier for CUR delivery can address its solubility and bioavailability challenges.This article reviews the drug loading methods,engineering strategies of MSCs-EV,and their important applications in the delivery and treatment of CUR for cartilage injury diseases.It provides a basis for the clinical ap-plication of engineered MSCs-EV in CUR delivery for cartilage repair,offering potential solutions to the challenges in cartilage tissue repair.

Aim To explore the effect of astragalosideⅣ(AS-Ⅳ)on lipopolysaccharide(LPS)-induced po-larization and migration of RAW 264.7 macrophages and the underlying mechanism.Methods 1 mg·L-1 LPS was used to construct cell migration model.Scratch assay was utilized to determine cell migration rate.Immunofluorescence staining was utilized to de-tect the expression and location of F4/80,iNOS and Arg-1.CCK-8 assay was used to determine the viabili-ty of RAW 264.7 cells.Griess assay was used to measure NO content.Molecular docking was used to analyze the interaction between AS-Ⅳ and the core tar-gets such as cGAS and STING protein.Western blot was employed to detect the expression of iNOS,Arg-1,cGAS,STING,NF-κB p65 and p-NF-κB p65 protein.Results AS-Ⅳ significantly inhibited the migration and M1 polarization of RAW 264.7 cells induced by LPS.Moreover,AS-Ⅳ could interact with cGAS and STING protein,especially cGAS.Further Western blot assay showed that AS-Ⅳ significantly downregulated the expression of iNOS,cGAS,STING and p-NF-κB p65 protein.Conclusions AS-Ⅳ could promote mac-rophage M1 to M2 polarization,thereby inhibited mac-rophage migration through restraining the cGAS/STING/NF-κB signaling pathway,which provides a new therapeutic target for AS-Ⅳ to improve the early inflammatory response of AS.