The thought of the way of heaven is the core philosophy of the Book of Changes， aiming to achieve the “pursuing good fortune and avoiding disaster” of human affairs or “seeking benefits and avoiding harm” in technology. The embedded value orientations， such as “continuous life”， “utmost sincerity”， and “correct desire”， provide ethical considerations for “seeking benefits and avoiding harm” in human gene editing technology. Among them， the thought of “continuous life” affirms the potential value of gene editing technology for human reproduction， diagnosis and treatment， or prevention of diseases and disabilities from two aspects of human reproduction and individual body and mind， while adopting a cautious attitude towards the risks of technology. The thought of “utmost sincerity” advocates that gene editing should be studied and applied following objective laws. The thought of “correct desire” puts forward the norm of human desire in human gene editing. In terms of the issue of offspring autonomy， the thought of the way of heaven provides some ethical support for parents to implement gene editing for their offspring for the sake of the offspring’s physical and mental development. In conclusion， the application of the thought of the way of heaven in the Book of Changes hopes that human gene editing technology will benefit mankind and provide it with broader prospects and a better future.

Objective:To investigate the role of the IgG subtypes (IgG1 and IgG2a) in anti-glycoprotein (GP) Ⅰbα antibody-induced platelet clearance.Methods:Venous blood was collected from healthy volunteers, and platelets were separated. The phagocytosis of human platelets by human acute monocytic leukemia cells (THP-1 cells) induced by different anti-GPⅠbα antibodies (AN51, AK2, HIP1, TM60, VM16d, WM23, and SZ2) was detected by flow cytometry. The effects of the AN51 full-length antibody, F (ab') 2, and Fab fragments on platelet phagocytosis by THP-1 cells were detected by flow cytometry. Then, the Fc blocking antibody 2.4G2 and normal rat IgG2a or IgG1 were injected into C57BL/6J mice via the posterior ocular vein, and their effects on platelet reduction induced by R300 were detected by a hematology analyzer. Results:Compared with IgG1, the IgG2a subtype of anti-GPⅠbα antibodies induced the phagocytosis of platelets by THP-1 cells in vitro ( P<0.05). In contrast to the AN51 full-length antibody, neither AN51 F (ab') 2 nor the Fab fragment could induce THP-1 cells to phagocytose platelets ( P<0.05). Compared with the control group, anti-mouse GPⅠbα R300-induced thrombocytopenia in mice was reduced at 2, 4, and 6 h after the injection of Fc blocking antibody 2.4G2 ( P<0.05). Similarly, R300-induced thrombocytopenia in mice was reduced at 2, 4, and 6 h after the injection of rat IgG2a ( P<0.05) . Conclusion:IgG2a plays an important role in anti-GPⅠbα-induced clearance.

As a major global public health concern,cancer has witnessed a continues rise in both incidence and mortality rates.It pose not only a severe threat to human health but also a heavy burden on socioeconomic systems.Despite remarkable advancements in oncology research,critical challenges such as tumor heterogeneity,drug resistance,and limitations in early screening and diagnostic technologies remain to be addressed.Against this backdrop,artificial intelligence(AI),with its unique advantages in big data analysis,pattern recognition,and predictive modeling,has opened new avenues for cancer research.By integrating multi-modal data,including omics,imaging,and clinical information,AI not only accelerates investigations into fundamental tumor mechanisms but also demonstrates immense potential in areas such as early screening,biomarker discovery,and personalized treatment.These advancements have fostered a deeper integration of precision medicine and oncology.This review provides a comprehensive overview of the most recent progresses in the application of AI in cancer diagnosis and treatment research,with a focus on its practical value across diverse data types and clinical scenarios,as well as future directions for its development.

Alzheimer's disease (AD) is the leading cause of dementia, and no effective treatment has been developed for it thus far. Recently, the use of natural compounds in the treatment of neurodegenerative diseases has garnered significant attention owing to their minimal adverse reactions. Accordingly, the potential therapeutic effect of pterostilbene (PTS) on AD has been demonstrated in multiple in vivo and in vitro experiments. In this study, we systematically reviewed and summarized the results of these studies investigating the use of PTS for treating AD. Analysis of the literature revealed that PTS may play a role in AD treatment through various mechanisms, including anti-oxidative damage, anti-neuroinflammation, anti-apoptosis, cholinesterase activity inhibition, attenuation of β-amyloid deposition, and tau protein hyperphosphorylation. Moreover, PTS interferes with the progression of AD by regulating the activities of peroxisome proliferator-activated receptor alpha (PPAR-α), monoamine oxidase B (MAO-B), silent information regulator sirtuin 1 (SIRT1), and phosphodiesterase 4A (PDE4A). Furthermore, to further elucidate the potential therapeutic mechanisms of PTS in AD, we employed network pharmacology and molecular docking technology to perform molecular docking of related proteins, and the obtained binding energies ranged from -2.83 to -5.14 kJ/mol, indicating that these proteins exhibit good binding ability with PTS. Network pharmacology analysis revealed multiple potential mechanisms of action for PTS in AD. In summary, by systematically collating and summarizing the relevant studies on the role of PTS in treatment of AD, it is anticipated that this will serve as a reference for the precise targeted prevention and treatment of AD, either using PTS or other developed drug interventions.

Screening carbonyl reductases with the ability to catalyze the reduction of complex carbonyl compounds is of great significance for the biosynthesis of R-tolvaptan(R-TVP). In this study, the target carbonyl reductase in the crude enzyme extract of rabbit liver was separated, purified, and identified by ammonium sulfate precipitation, gel-filtration chromatography, ion exchange chromatography, affinity chromatography, and protein mass spectrometry. With the rabbit liver genome as the template, the gene encoding the carbonyl reductase rlsr5 was amplified by PCR and the recombinant strain was successfully constructed. After RLSR5 was purified by affinity chromatography, its enzymatic properties were characterized. The results indicated that the gene sequence of rlsr5 was 972 bp, encoding a protein with a molecular weight of 40 kDa. RLSR5 was a dimeric protein, and each monomer was composed of a (α/β)₈-barrel structure. RLSR5 could asymmetrically reduce 7-chloro-1-[2-methyl-4-[(2- methylbenzoyl)amino]benzoyl]-5-oxo-2,3,4,5-tetrahydro-1H-1-benzazepine (prochiral ketone, PK) to synthesize R-TVP. The specific activity of the enzyme was 36.64 U/mg, and the optical purity of the product was 99%. This enzyme showcased the optimal performance at pH 6.0 and 30 °C. It was independent of metal ions, with the activity enhanced by Mn²⁺. This study lays a foundation for the biosynthesis of tolvaptan of optical grade.
Animals ; Rabbits ; Alcohol Oxidoreductases/biosynthesis* ; Recombinant Proteins/metabolism* ; Escherichia coli/metabolism* ; Liver/enzymology*

Objective To analyze dynamic contrast-enhanced MRI (DCE-MRI) radiomic features using machine learning algorithms, and to develop and validate a predictive model for HER-2 status in breast cancer. Methods The DCE-MRI images of 272 treatment-naive female patients with breast cancer between 2020 and 2022 were included in this study. Regions of interest (ROIs) were manually segmented using 3d-Slicer software, and radiomic features were extracted. All patients were randomly divided into training sets or validation sets at a ratio of 4∶1. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening on the training set, followed by the development of predictive models using six machine learning algorithms. Internal cross-validation was performed to compare the performance differences between the models. The best-performing model was selected, trained on the training set, and evaluated on the validation set. Evaluation metrics included area under the curve (AUC), sensitivity, specificity, precision, and recall rate. Results The clinical data of patients in the training set and validation set showed no significant differences. Five features were identified by the LASSO algorithm. With these features, six machine learning models were developed on the training set, and their predictive performance was internally cross-validated using the bagging method. XGBoost model had the highest mean AUC (0.696), followed by RF model (0.690); XGBoost model had the highest mean precision (0.756), followed by LR and RF models. Therefore, XGBoost was the optimal model. An HER-2 predictive model was built using the XGBoost algorithm on the training set and applied to the validation set. The AUC, precision, sensitivity, and specificity of the predictive model on the validation set were calculated, and ROC curves, precision-recall curves, calibration curves, and decision-making curves were plotted. Conclusion This study constructed and evaluated different DCE-MRI radiomics-based machine learning models for predicting HER-2 status in breast cancer. Among them, XGBoost algorithm performed the best and has the potential to become a new non-invasive method for preoperative prediction of HER-2 status, providing reliable evidence for personalized clinical diagnosis and treatment.

With reference to the Information and Documentation-Resource Description (GB/T 3792-2021) and Bibliographical Description for Ancient Chinese Books (GB/T 3792.7-2008) and other cataloging standards and rules, drawing on the practical experience of cataloging ancient TCM books, Bibliographical Cataloging for Ancient TCM Books was formulated. This standard specifies the entry items and their order of ancient TCM books, cataloging identifier, cataloging text, cataloging information source, and cataloging item details. The standard can provide standardized and unified guiding principles and methods for the work of ancient TCM books, and promote the sharing and utilization of ancient TCM books.

Objective To explore the effects of plantamajoside on the proliferation and invasion of human gastric cancer cell line BGC823.Methods BGC823 cells were randomly separated into a control group,a plantamajoside group,an AAV-NC(transfection of empty plasmids packaged with lentivirus)group and a plantamajoside+AAV-HIF-1α(transfection of HIF-1α overexpression plasmid packaged with lentivirus)group.Cell proliferation,inva-sion,apoptosis,the numbers of vascular mimicry(VM)lumens and vascular branches,the expression of prolifera-tion,apoptosis,epithelial mesenchymal transition(EMT)related proteins,HIF-1α/VEGF pathway proteins of cells were all examined.Results Compared with control group,the BGC823 cell viability,colony formation num-ber,invasion number,VM lumen number,vascular branch number,and expression of Ki-67,PCNA,vimentin,MMP9,Snail,VEGFA,VE-cadhering,HIF-1α and VEGF protein were all lower in plantamajoside group(P＜0.05).The apoptosis rate,the cleaved Caspase-3,Bax,and E-cadherin protein expression were significantly increased(P＜0.05).Compared with plantamajoside group,the BGC823 cell viability,colony formation number,invasion number,VM lumen number,vascular branch number,and expression of Ki-67,PCNA,vimentin,MMP9,Snail,VEGFA,VE-cadherin,HIF-1α and VEGF protein were higher in the plantamajoside+AAV-HIF-1α group(P＜0.05).The apoptosis rate,the cleaved caspase-3,Bax,and E-cadherin protein expression were lower(P＜0.05).Conclusions Plantamajoside inhibits proliferation,EMT,invasion,and VM of human gastric cancer cell line and induce its apoptosis.

Alzheimer's disease(AD)is the leading cause of dementia,and no effective treatment has been devel-oped for it thus far.Recently,the use of natural compounds in the treatment of neurodegenerative diseases has garnered significant attention owing to their minimal adverse reactions.Accordingly,the potential therapeutic effect of pterostilbene(PTS)on AD has been demonstrated in multiple in vivo and in vitro experiments.In this study,we systematically reviewed and summarized the results of these studies investigating the use of PTS for treating AD.Analysis of the literature revealed that PTS may play a role in AD treatment through various mechanisms,including anti-oxidative damage,anti-neuroinflammation,anti-apoptosis,cholinesterase activity inhibition,attenuation of β-amyloid deposi-tion,and tau protein hyperphosphorylation.Moreover,PTS interferes with the progression of AD by regulating the activities of peroxisome proliferator-activated receptor alpha(PPAR-α),monoamine oxi-dase B(MAO-B),silent information regulator sirtuin 1(SIRT1),and phosphodiesterase 4A(PDE4A).Furthermore,to further elucidate the potential therapeutic mechanisms of PTS in AD,we employed network pharmacology and molecular docking technology to perform molecular docking of related proteins,and the obtained binding energies ranged from-2.83 to-5.14 kj/mol,indicating that these proteins exhibit good binding ability with PTS.Network pharmacology analysis revealed multiple po-tential mechanisms of action for PTS in AD.In summary,by systematically collating and summarizing the relevant studies on the role of PTS in treatment of AD,it is anticipated that this will serve as a reference for the precise targeted prevention and treatment of AD,either using PTS or other developed drug interventions.

The classical latent structure method does not consider the influence of primary and secondary symptoms,syndromes and symptoms in the analysis and modeling of syndromes.In this paper,based on the data of damp-heat in intestine and stomach syndrome involving 1087 diabetic patients,the classical latent structure analysis was used to obtain the quantitative syndrome diagnostic rules.Then,using Constrained Latent Tree Analysis(CLTA),the quantitative syndrome diagnostic rules containing primary and secondary symptoms were obtained as follows,primary symptoms include halitosis(2.3),yellow tongue coating(2),abdominal distension(2.3),greasy tongue coating(2.1),loose stool or loose stool(1.5),red tongue(1.3),smooth pulse(1.4).Secondary symptoms include epigastric distension(1.1).Compared with the traditional latent structure analysis method,the rules established by CLTA are more compatible with the concept of differentiating primary and secondary symptoms and the common practice of TCM.The quantitative syndrome diagnostic rules of damp-heat in intestine and stomach syndrome constructed by the CLTA method have considerable objectivity in the modeling process.The diagnostic rules established were also compatible with the qualitative concept of TCM theory in stratifying primary and secondary symptoms.Finally,the diagnostic rules are obtained by logistic regression analysis,and the accuracy of the three rules is compared.The results show that the rule recognition accuracy obtained by CLTA is the highest.Therefore,the syndrome diagnostic rules of damp-heat in intestine and stomach obtained from the analysis of CLTA are in line with the constraint semantics of primary and secondary diseases and the theory of traditional Chinese medicine.