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 influence of maternal autoimmune diseases and anticoagulants, including low-molecular-weight heparin (LMWH) and aspirin, on the fetal fraction of maternal plasma cell-free DNA of non-invasive prenatal testing (NIPT).Methods:A prospective cohort study was conducted on women with singleton pregnancies receiving NIPT in the Nanjing Drum Tower Hospital from March 2021 to July 2022. NIPT was carried out using a polymerase chain reaction (PCR)-free amplification platform. In this study, four types of maternal autoimmune diseases, which were antiphospholipid syndrome, undifferentiated connective tissue disease, Sj?gren's syndrome, and systemic lupus erythematosus (SLE), and two anticoagulants, LMWH and aspirin, were studied. Univariate and multivariate linear regression models were used to analyze the factors influencing fetal fraction of maternal plasma cell-free DNA.Results:A total of 4 102 singleton pregnant women were enrolled in the prospective cohort, and 3 948 were finally included after excluding the cases with unclear dosing time of LMWH or aspirin, other autoimmune diseases, conceiving through ovulation induction alone, and having true positive or failed NIPT result. There were 96 cases with antiphospholipid syndrome, 35 with undifferentiated connective tissue disease, 34 with Sj?gren's syndrome, and 18 with SLE. A total of 108 patients only received LMWH treatment, 121 only received aspirin treatment, and 113 received both LMWH and aspirin treatment. Univariate linear regression analysis showed that maternal body mass index at blood collection ( B=－0.423), conceived by assisted reproductive technology ( B=－0.803), male fetus ( B=－0.458), undifferentiated connective tissue disease ( B=1.774), and SLE ( B=3.467) had influence on the fetal fraction (all P<0.05). Multivariate linear regression analysis showed that maternal body mass index at blood collection ( B=－0.415), conceived by assisted reproductive technology ( B=－0.585), male fetus ( B=－0.322), SLE ( B=3.347) and undifferentiated connective tissue disease ( B=1.336) were factors influencing fetal fraction (all P<0.05). Conclusions:Maternal use of LMWH or aspirin does not affect fetal fraction when performing NIPT on a PCR-free amplification platform, but undifferentiated connective tissue disease and SLE are the influencing factors. Therefore, pregnant women should be informed before the NIPT that the fetal fraction of maternal plasma cell-free DNA may be affected by maternal autoimmune diseases.

Objective:To evaluate the relationship between preoperative free thyroxine (FT4) levels and the risk of new-onset atrial fibrillation (AF) after cardiac valve surgery in patients with normal thyroid function, and to identify high-risk individuals for postoperative AF among patients undergoing cardiac valve surgery.Methods:This retrospective study enrolled patients(≥18 years old)with valvular heart disease who underwent heart valve replacement or valvoplasty surgery from December 2019 to January 2023 in Beijing Anzhen Hospital. Patients with thyroid function tests exceeding the normal reference range(7.64-16.03 pmol/L) were excluded, resulting in a final cohort of 2 645 patients, including 1 597 males and 1 048 females; aged 18-83 years, with a median age of 56 (46, 64) years. Among them, 1 891 patients (71.5%) had hypertension, and 176 (6.7%) had type 2 diabetes. The patients were divided into four groups based on quartiles of FT4 levels: Group 1 (n=661) with FT4 levels of 7.64-10.33 pmol/L, Group 2 (n=661) with 10.33-11.36pmol/L, Group 3 (n=661) with 11.36-12.54 pmol/L, and Group 4(n=662) with 12.54-13.66pmol/L. The risk of postoperative AF was compared among the four groups, and logistic regression was used to adjust for relevant risk factors. The odds ratio ( OR) and 95% confidence interval( CI) for postoperative AF across different groups were analyzed. Subgroup analyses were performed based on age, gender, hypertension status, and B-type natriuretic peptide (BNP) levels to compare the association between FT4 levels and new-onset AF within different subgroups. Results:Statistically significant differences were observed among the four groups in terms of age, body mass index, hypertension, hyperlipidemia, BNP, glomerular filtration rate, triglyceride, and total cholesterol levels ( P<0.05), while no significant differences were found in other indicators( P<0.05). Using the lowest FT4 group as the baseline, a higher risk of postoperative new-onset AF was observed in groups with higher FT4 levels, with a significant trend of incremental increase in postoperative AF with rising FT4 levels. Similar trends were observed across subgroups stratified by age, gender, hypertension status, and BNP levels. The Youden index indicated a cut-off value of 11.485pmol/L for FT4. Conclusion:Among patients with normal thyroid function and valvular heart disease, preoperative higher FT4 levels are significantly associated with an increased risk of new-onset AF after cardiac valve surgery. Close monitoring for postoperative AF risk is recommended for patients with preoperative FT4 levels exceeding 11.485 pmol/L, even if the thyroid function is still within the normal.

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.

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.

Goiter is a kind of non-inflammatory and non-neoplastic hyperplasia and enlargement. Many studies have shown that substances such as thiocyanates and isothiocyanates can prevent the development of a variety of tumors. However, some studies have also found that such substances can lead to goiter. In this article, relevant information on common goitrogen in food are collected to explore their mechanism of action, laying a foundation for guiding residents to maintain a healthy and balanced diet.

Objectives:To analyze the risk factors related to infection after posterior lumbar interbody fusion(PLIF)by random forest algorithm and develop a prediction model,providing a certain reference for clinical prevention of surgical site infection(SSI)after PLIF.Methods:A retrospective study was conducted on the masked data of patients hospitalized for PLIF in the spinal surgery department of some third-level grade A hospitals in Beijing municipality and Hebei Province from June 2019 to June 2021 provided by Beijing Zhongwei Cloud Medical Data Analysis and Application Technology Research Institute through data processing and analysis.The classification data were analyzed and compared between SSI group and non-SSI group to obtain variables that significantly impacted the postoperative infection.SPSS Modeler 20 system was used as the tool for model development,and random forest algorithm was applied to analyze,obtaining the patient characteristics of postoperative infection,namely the infection model.Results:A total of 8,764 patients were included in study,and 373 patients were diagnosed with SSI,with an incidence rate of 4.4％(95％CI:2.2％to 6.5％).After statistical analysis,six variables,including obesity,ASA Ⅲ and above,prolonged operative time,chronic heart disease,diabetes and renal dysfunction,were independently associated with SSI.Classification with a random forest model yielded a high accuracy of 90.6％.The characteristics of patients prone to infection after PLIF(two models of infection)was:[(BMI=1)and(SD=1)and(ASA=1)and(RI=1)]or[(BMI=0)and(SD=1)and(DM=1)and(RI=1)].Conclusions:The random forest algorithm applied in this study could obtain an average accuracy of 90.6％,and two infection models were obtained as:(1)Patients with obesity,renal insufficiency,ASA grade Ⅲ or above,and operative time≥3h;(2)Patients who are not obese,but with diabetes,renal insufficiency,and the operative time ≥3h.

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.

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.

Objective:To develop and evaluate metal artifact removal systems (MARS) 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, 1.5, 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 MARS. 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.