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.

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.

Objective:To examine the impact of berberine on polycystic ovary syndrome (PCOS) in mice, and to investigate the effects of berberine on the intestinal flora and the intestinal flora on PCOS.Methods:A mouse model of PCOS was established by administering dehydroepiandrosterone in combination with high fat diet, and the mouse model was given a berberine treatment. The study consisted of a blank control group (C group), a PCOS model group (M group) and a berberine treatment group (T group). During the experiment, the mice were closely monitored through timed body weight measurements and estrous cycle monitoring; intraperitoneal glucose tolerance test and insulin tolerance test were done. Upon completion of the pharmacological intervention, the wet weights of liver, ovary and fat deposits of mice were assessed and subjected to HE staining to confirm the success of PCOS modeling and the efficacy of berberine. Additionally, fecal samples were analyzed for intestinal flora through 16S rRNA analysis.Results:The PCOS model was established successfully, berberine alleviated the disturbance of estrous cycle in mice, and significantly alleviated fat accumulation and metabolic abnormalities of glucose in mice. The cross-sectional area of fat pad cells in T group was (2 858±146) μm2, which was significantly lower than that in M group [(9 518±347) μm2], and the difference was statistically significant ( P<0.001). The blood glucose levels in T group were significantly lower than those in M group ( P<0.05). The composition and structure of intestinal flora in mice of M group with PCOS (compared with C group) and in mice of T group after berberine intervention (compared with M group) were significantly altered. However, alpha diversity did not change significantly among three groups ( P>0.05). Conclusion:Berberine could alleviate PCOS by intervening in the alterations of gut microbiota.

To promote the development of extracellular vesicles of herbal medicine especially the establishment of standardization, led by the National Expert Committee on Research and Application of Chinese Herbal Vesicles, research experts in the field of herbal medicine and extracellular vesicles were invited nationwide with the support of the Expert Committee on Research and Application of Chinese Herbal Vesicles, Professional Committee on Extracellular Vesicle Research and Application, Chinese Society of Research Hospitals and the Guangdong Engineering Research Center of Chinese Herbal Vesicles. Based on the collation of relevant literature, we have adopted the Delphi method, the consensus meeting method combined with the nominal group method to form a discussion draft of "Consensus statement on research and application of Chinese herbal medicine derived extracellular vesicles-like particles (2023)". The first draft was discussed in online and offline meetings on October 12, 14, November 2, 2022 and April and May 2023 on the current status of research, nomenclature, isolation methods, quality standards and research applications of extracellular vesicles of Chinese herbal medicines, and 13 consensus opinions were finally formed. At the Third Academic Conference on Research and Application of Chinese Herbal Vesicles, held on May 26, 2023, Kewei Zhao, convenor of the consensus, presented and read the consensus to the experts of the Expert Committee on Research and Application of Chinese Herbal Vesicles. The consensus highlights the characteristics and advantages of Chinese medicine, inherits the essence, and keeps the righteousness and innovation, aiming to provide a reference for colleagues engaged in research and application of Chinese herbal vesicles at home and abroad, decode the mystery behind Chinese herbal vesicles together, establish a safe, effective and controllable accurate Chinese herbal vesicle prevention and treatment system, and build a bridge for Chinese medicine to the world.

Objective:To study the diagnostic value of artificial intelligence B-ultrasound image computer-aided diagnosis system (hereinafter referred to as intelligent ultrasound system) in adult goiter.Methods:In June 2022 and March 2023, two phases of thyroid disease survey were carried out in 4 cities in Anhui Province. One village was selected in each city, and 250 adults were selected as survey subjects in each village. Adult bilateral thyroid area was scanned by both intelligent ultrasound system and conventional ultrasound scanning equipment, and the effectiveness of intelligent ultrasound system in the diagnosis of goiter was analyzed based on the results of conventional ultrasound examination. Receiver operating characteristic (ROC) curve was drawn, and Kappa test was used to analyze the consistency between intelligent ultrasound system and conventional ultrasound examination in the diagnosis of goiter. At the same time, Spearman correlation analysis and Bland-Altman method were used to evaluate the consistency of the two methods in measuring thyroid volume.Results:After screening and removing outliers and missing values, a total of 910 adults were included, including 253 males (27.80%) and 657 females (72.20%). The age was (45.92 ± 10.20) years old, ranging from 18 to 60 years old. The sensitivity, specificity, and accuracy of the intelligent ultrasound system for diagnosing adult goiter were 80.00%, 99.67%, and 99.56%, respectively. The area under the ROC curve (AUC) was 0.996, which was consistent with the results of conventional ultrasound examination for diagnosing goiter ( κ = 0.67, P < 0.001). After controlling for variables such as gender, thyroid function, and thyroid nodules, the intelligent ultrasound system showed good consistency with conventional ultrasound examination in the diagnosis of goiter in females, adults with thyroid dysfunction, and adults without thyroid nodules ( κ = 0.66, 0.80, 0.80, P < 0.001). The consistency in the diagnosis of goiter in adults with thyroid nodules was moderate ( κ = 0.56, P < 0.001). Spearman correlation analysis showed a highly positive correlation between the measurement results of adult thyroid volume by intelligent ultrasound system and conventional ultrasound examination ( r = 0.88, P < 0.001). The Bland-Altman method results showed that only 4.62% (42/910) of points in adults were outside the 95% consistency limit, indicating good consistency between intelligent ultrasound system and conventional ultrasound examination in measuring thyroid volume (< 5%). The proportion of points outside the 95% consistency limit in males, adults with thyroid dysfunction, and adults with thyroid nodules was 6.72% (17/253), 5.83% (12/206), and 6.45% (12/186), respectively. Conclusions:The intelligent ultrasound system has certain diagnostic value for adult goiter and has good consistency with conventional ultrasound examination for thyroid volume measurement. However, the accuracy of diagnosis for males and adults with thyroid nodules still needs to be improved.

Objective:To develop and evaluate metal artifact removal systems (MARSs) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images.Methods:A full-mouth standard model (60 mm×75 mm×110 mm) was three-dimensional (3D) printed using photosensitive resin. The model included a removable and replaceable target tooth position where cobalt-chromium alloy crowns with varying thicknesses were inserted to generate matched CBCT images. The artifacts resulting from cobalt-chromium alloys with different thicknesses were evaluated using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). CNN-MARS and U-net-MARS were developed using a convolutional neural network and U-net architecture, respectively. The effectiveness of both MARSs were assessed through visualization and by measuring SSIM and PSNR values. The SSIM and PSNR values were statistically analyzed using one-way analysis of variance (α=0.05).Results:Significant differences were observed in the range of artifacts produced by different thicknesses of cobalt-chromium alloys (all P<0.05), with 1 mm resulting in the least artifacts. The SSIM values for specimens with thicknesses of 1.0 mm, 1.5 mm, and 2.0 mm were 0.916±0.019, 0.873±0.010, and 0.833±0.010, respectively ( F=447.89, P<0.001). The corresponding PSNR values were 20.834±1.176, 17.002±0.427, and 14.673±0.429, respectively ( F=796.51, P<0.001). After applying CNN-MARS and U-net-MARS to artifact removal, the SSIM and PSNR values significantly increased for images with the same thickness of metal (both P<0.05). When using the CNN-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.938±0.023, 0.930±0.029, and 0.928±0.020 ( F=2.22, P=0.112), while the PSNR values were 30.938±1.495, 30.578±2.154 and 30.553±2.355 ( F=0.54, P=0.585). When using the U-net-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.930±0.024, 0.932±0.017 and 0.930±0.012 ( F=0.24, P=0.788), and the PSNR values were 30.291±0.934, 30.351±1.002 and 30.271±1.143 ( F=0.07, P=0.929). No significant differences were found in SSIM and PSNR values after artifact removal using CNN-MARS and U-net-MARS for different thicknesses of cobalt-chromium alloys (all P>0.05). Visualization demonstrated a high degree of similarity between the images before and after artifact removal using both MARSs. However, CNN-MARS displayed clearer metal edges and preserved more tissue details when compared with U-net-MARS. Conclusions:Both the CNN-MARS and U-net-MARS models developed in this study effectively remove the metal artifacts and enhance the image quality. CNN-MARS exhibited an advantage in restoring tissue structure information around the artifacts compared to U-net-MARS.