A Mild PUM1 Mutation Is Associated with Adult-Onset Ataxia, whereas Haploinsufficiency Causes Developmental Delay and Seizures.

Certain mutations can cause proteins to accumulate in neurons, leading to neurodegeneration. We recently showed, however, that upregulation of a wild-type protein, Ataxin1, caused by haploinsufficiency of its repressor, the RNA-binding protein Pumilio1 (PUM1), also causes neurodegeneration in mice. We therefore searched for human patients with PUM1 mutations. We identified eleven individuals with either PUM1 deletions or de novo missense variants who suffer a developmental syndrome (Pumilio1-associated developmental disability, ataxia, and seizure; PADDAS). We also identified a milder missense mutation in a family with adult-onset ataxia with incomplete penetrance (Pumilio1-related cerebellar ataxia, PRCA). Studies in patient-derived cells revealed that the missense mutations reduced PUM1 protein levels by ∼25% in the adult-onset cases and by ∼50% in the infantile-onset cases; levels of known PUM1 targets increased accordingly. Changes in protein levels thus track with phenotypic severity, and identifying posttranscriptional modulators of protein expression should identify new candidate disease genes.

Predicting chronological age of 14 or 18 in adolescents: integrating dental assessments with machine learning.

AIM: Age estimation plays a critical role in personal identification, especially when determining compliance with the age of consent for adolescents. The age of consent refers to the minimum age at which an individual is legally considered capable of providing informed consent for sexual activities. The purpose of this study is to determine whether adolescents meet the age of 14 or 18 by using dental development combined with machine learning. METHODS: This study combines dental assessment and machine learning techniques to predict whether adolescents have reached the consent age of 14 or 18. Factors such as the staging of the third molar, the third molar index, and the visibility of the periodontal ligament of the second molar are evaluated. RESULTS: Differences in performance metrics indicate that the posterior probabilities achieved by machine learning exceed 93% for the age of 14 and slightly lower for the age of 18. CONCLUSION: This study provides valuable insights for forensic identification for adolescents in personal identification, emphasizing the potential to improve the accuracy of age determination within this population by combining traditional methods with machine learning. It underscores the importance of protecting and respecting the dignity of all individuals involved.

Adolescents and Children Age Estimation Using Machine Learning Based on Pulp and Tooth Volumes on CBCT Images.

OBJECTIVES: To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography (CBCT) images, and to compare and analyze the estimation results. METHODS: A total of 498 Shanghai Han adolescents and children CBCT images of the oral and maxillofacial regions were collected. The pulp and tooth volumes of the left maxillary central incisor and cuspid were measured and calculated. Three machine learning algorithms (K-nearest neighbor, ridge regression, and decision tree) and stepwise regression were used to establish four age estimation models. The coefficient of determination, mean error, root mean square error, mean square error and mean absolute error were computed and compared. A correlation heatmap was drawn to visualize and the monotonic relationship between parameters was visually analyzed. RESULTS: The K-nearest neighbor model (R2=0.779) and the ridge regression model (R2=0.729) outperformed stepwise regression (R2=0.617), while the decision tree model (R2=0.494) showed poor fitting. The correlation heatmap demonstrated a monotonically negative correlation between age and the parameters including pulp volume, the ratio of pulp volume to hard tissue volume, and the ratio of pulp volume to tooth volume. CONCLUSIONS: Pulp volume and pulp volume proportion are closely related to age. The application of CBCT-based machine learning methods can provide more accurate age estimation results, which lays a foundation for further CBCT-based deep learning dental age estimation research.

Applicability of the London Atlas method in the East China population.

BACKGROUND: Dental age estimation is important for developmental assessment and individual identification. The London Atlas, a recently proposed method for dental age estimation, has been reported to perform satisfactorily in various populations. OBJECTIVE: In this study, we assessed the reproducibility, repeatability and applicability of the London Atlas method in the East China population and compared it with the Demirjian method. MATERIALS AND METHODS: We assessed panoramic radiographs of 835 pediatric patients ages 6.0-19.9 years using the London Atlas and the Demirjian method. We employed the intraclass correlation coefficient and Bland-Altman analysis to evaluate reproducibility and repeatability, respectively. We assessed the agreement between dental age and chronological age and calculated 95% and 80% prediction intervals for each dental age stage. Sensitivity, specificity and predictive values were calculated to assess the performance of both methods for identifying threshold ages. RESULTS: The London Atlas has better reproducibility and repeatability (intraclass correlation coefficients: 0.98 and 0.99; 95% limits of agreement: - 1.34 to 1.56 and - 1.22 to 0.88, respectively). Dental age estimated using the London Atlas was closer to chronological age in both genders (median absolute error = 0.58). The 95% prediction intervals for chronological age were wide (0.99 to 9.89 years). CONCLUSION: The London Atlas has excellent reproducibility and repeatability. Thus, it might offer an alternative method for developmental assessment. We observed considerable variation in dental development in the East China population, which needs further research.

A population-based study to assess two convolutional neural networks for dental age estimation.

BACKGROUND: Dental age (DA) estimation using two convolutional neural networks (CNNs), VGG16 and ResNet101, remains unexplored. In this study, we aimed to investigate the possibility of using artificial intelligence-based methods in an eastern Chinese population. METHODS: A total of 9586 orthopantomograms (OPGs) (4054 boys and 5532 girls) of the Chinese Han population aged from 6 to 20 years were collected. DAs were automatically calculated using the two CNN model strategies. Accuracy, recall, precision, and F1 score of the models were used to evaluate VGG16 and ResNet101 for age estimation. An age threshold was also employed to evaluate the two CNN models. RESULTS: The VGG16 network outperformed the ResNet101 network in terms of prediction performance. However, the model effect of VGG16 was less favorable than that in other age ranges in the 15-17 age group. The VGG16 network model prediction results for the younger age groups were acceptable. In the 6-to 8-year-old group, the accuracy of the VGG16 model can reach up to 93.63%, which was higher than the 88.73% accuracy of the ResNet101 network. The age threshold also implies that VGG16 has a smaller age-difference error. CONCLUSIONS: This study demonstrated that VGG16 performed better when dealing with DA estimation via OPGs than the ResNet101 network on a wholescale. CNNs such as VGG16 hold great promise for future use in clinical practice and forensic sciences.

Using machine learning to determine age over 16 based on development of third molar and periodontal ligament of second molar.

BACKGROUND: Having a reliable and feasible method to estimate whether an individual has reached 16 years of age would greatly benefit forensic analysis. The study of age using dental information has matured recently. In addition, machine learning (ML) is gradually being applied for dental age estimation. AIM: The purpose of this study was to evaluate the development of the third molar using the Demirjian method (Demirjian3M), measure the development index of the third molar (I3M) using the method by Cameriere, and assess the periodontal ligament development of the second molar (PL2M). This study aimed to predict whether Chinese adolescents have reached the age of criminal responsibility (16 years) by combining the above measurements with ML techniques. SUBJECTS & METHODS: A total of 665 Chinese adolescents aged between 12 and 20 years were recruited for this study. The development of the second and third molars was evaluated by taking orthopantomographs. ML algorithms, including random forests (RF), decision trees (DT), support vector machines (SVM), K-nearest neighbours (KNN), Bernoulli Naive Bayes (BNB), and logistic regression (LR), were used for training and testing to determine the dental age. This is the first study to combine ML with an evaluation of periodontal ligament and tooth development to predict whether individuals are over 16 years of age. RESULTS AND CONCLUSIONS: The study showed that SVM had the highest Bayesian posterior probability at 0.917 and a Youden index of 0.752. This finding provides an important reference for forensic identification, and the combination of traditional methods and ML is expected to improve the accuracy of age determination for this population, which is of substantial significance for criminal litigation.

Assessment of oral emergency services during COVID-19: a retrospective study of 14,885 cases in Shanghai.

BACKGROUND: To assess the impact of coronavirus disease-2019 (COVID-19) in its outbreak stage (Spring Festival in 2020) on oral emergency services. METHODS: Oral emergency cases in Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, during the Spring Festival after the outbreak of the COVID-19 epidemic in 2020 were collected and compared with those in 2018 and 2019. Electronic medical records including the visited department, age, sex, time, date, region, and diagnosis were collected and analyzed. The results were statistically analyzed using Pearson's Chi-square test and one-way analysis of variance (ANOVA). RESULTS: Compared with that in 2018 and 2019, the total number of patients decreased during the Spring Festival in 2020 (p < 0.001), but the proportions of patients visiting Oral Surgery and Oral, Head, and Neck Oncology Emergency departments increased. The average age of patients increased, and the number of night visits decreased. Toothache diseases involving endodontic and periodontal diseases increased, while the proportion of maxillofacial trauma decreased. The wasn't a linear association between diagnosis or genders (P > 0.001) across years. However, a linear-by-linear association between age groups and years, visited departments and years were observed (P < 0.001). CONCLUSIONS: The study revealed that the transmission of COVID-19 affected the patient population and structure of disease types and oral services in 2020 during the Spring Festival, compared with those in the previous two years. The visits to oral emergency departments and the proportions of patients who were children and adolescents reduced; meanwhile, the percentage of the elderly people increased during the outbreak of COVID-19. The clear trend of age groups and visiting divisions could be used as a marker to reflect the severity of the COVID-19 pandemic. These results may serve as a reference for dental practitioners involved in oral emergency services and to allocate the limited emergency health resources.

Performance of the London Atlas, Willems, and a new quick method for dental age estimation in Chinese Uyghur children.

BACKGROUND: Numerous dental age estimation methods have been devised and practised for decades. Among these, the London Atlas and Willems methods were two of the most frequently adopted, however dependent on atlantes or tables. A new estimation method less reliant on external measurement could be efficient and economical. AIM: This study aimed to evaluate the utility and applicability of the dental age estimation methods of London Atlas, Willems, and a new quick method that subtracts the number of developing teeth from the universal root mature age of 16 years in one of the lower quadrants reported in this work among Chinese Uyghur children. METHODS: A comparative cross-sectional study was conducted. Subjects enrolled in the study were screened according to preset inclusion and exclusion criteria. The observer then obtained the dental age from the subjects' panoramic radiographs based on the estimated rules of the London Atlas, Willems, and a new quick method. Paired t-test was used to compare the accuracy and precision of the above three estimation methods. Independent-sample t-test was used to find the difference between gender. RESULTS: Totally, 831 radiographs entered the analyses of this study. Among the three methods evaluated, the Willems method, in particular, showed a distinct underestimated tendency. The mean error of the dental age predicted by the London Atlas, the Willems method, and the quick method was 0.06 ± 1.13 years, 0.44 ± 1.14 years, and 0.30 ± 0.63 years, respectively. The mean absolute error was 0.86 ± 0.75 years according to the London Atlas, 1.17 ± 0.89 years under the Willems method, and 0.70 ± 0.54 years under our quick method. No significant difference was found between the chronological age and dental age using the London Atlas, generally for the 10 to 15 years group (p > 0.05), but our quick method for the 15-16 years children (p < 0.05) and Willems method (p < 0.001). CONCLUSION: The London Atlas outperformed the Willems method with better accuracy and precision among 10-15 years Chinese Uyghur children. Our new quick method may be comparable to the London Atlas for children aged 10-14 and potentially become a more straightforward dental age prediction instrument.

Comparative assessment of the Willems dental age estimation methods: a Chinese population-based radiographic study.

BACKGROUND: The comparison of the two Willems dental age estimation methods (gender-specific (Willems I) and non-gender-specific (Willems II)) has not been fully investigated. Here we aimed to explore the applicability of the Willems dental age estimation in an Eastern Chinese population, which may cast light on the field of dental age estimation. METHODS: A total of 1211 oral panoramic radiographs (582 boys and 629 girls) of the Chinese Han population aged 11-16 years old were collected. Dental ages (DAs) were calculated using the Willems method. Statistical significance was set at a p-value < 0.05. Age differences between chronological age (CA) and dental age were analyzed by paired t-tests and mean absolute error (MAE). RESULTS: The differences between CA and DA determined by the Willems I method were + 0.44 and + 0.09 years for boys and girls, respectively. When using the Willems II method, these differences were + 0.57 and - 0.09. The MAEs of the Willems I method between DA and CA were 0.95 and 1.00 years in boys and girls, respectively. For Willems II, MAEs were 1.02 and 1.00 years in boys and girls. CONCLUSIONS: This study showed that the Willems I method was more accurate than the Willems II method in the boys' group for predicting age from a whole scale. In comparison, Willems II is more competitive in the girls' group. Neither method may be satisfactory for 11-to-16-year-old teenagers in Eastern China.

Correction: NocU is a cytochrome P450 oxygenase catalyzing N-hydroxylation of the indolic moiety during the maturation of the thiopeptide antibiotics nocathiacins.

Correction for 'NocU is a cytochrome P450 oxygenase catalyzing N-hydroxylation of the indolic moiety during the maturation of the thiopeptide antibiotics nocathiacins' by Heng Guo et al., Org. Biomol. Chem., 2021, DOI: 10.1039/d1ob01284c.

NocU is a cytochrome P450 oxygenase catalyzing N-hydroxylation of the indolic moiety during the maturation of the thiopeptide antibiotics nocathiacins.

The ribosomally synthesized and post-translationally modified peptide (RiPP) natural products include the family of thiopeptide antibiotics, where nocathiacins (NOCs) and nosiheptide (NOS) are structurally related bicyclic members featuring an indolic moiety within the side ring system. Compared with NOS, NOCs bear additional functionalities that lead to the improvement of water solubility and bioavailability, a problem inherent to most of the thiopeptide antibiotics, and thus hold potential for clinical use in anti-infective agent development. The process through which post-translational modifications (PTMs) occur to afford these functionalities remains unclear. In this study, an engineered NOS-producing strain is applied to study the function of NocU, a cytochrome P450 oxygenase unique during the PTMs in NOC biosynthesis. Benefiting from the isolation and structure characterization of nosiheptide U (NOS-U), a new NOS-type compound with an extra hydroxyl group at the indole nitrogen, we report that NocU is responsible for the N-hydroxylation of the indolic moiety during the maturation of NOCs. This finding reveals the cause of structural differences at the indole nitrogen of NOCs, which will not only accelerate the biosynthetic studies of NOCs, but also promote new analog development by utilizing the compatibility of the biosynthetic machinery of thiopeptide antibiotics.

Correction: Characterization of a carboxyl methyltransferase in Fusarium graminearum provides insights into the biosynthesis of fusarin A.

Correction for 'Characterization of a carboxyl methyltransferase in Fusarium graminearum provides insights into the biosynthesis of fusarin A' by Qian Yang et al., Org. Biomol. Chem., 2021, DOI: 10.1039/d1ob01010g.

Characterization of a carboxyl methyltransferase in Fusarium graminearum provides insights into the biosynthesis of fusarin A.

Fusarium graminearum is a major fungal pathogen that causes a series of devastating crop diseases by producing a variety of mycotoxins. Fusarins are a class of polyketide-nonribosomal peptide hybrids. In Fusarium mycotoxins, a variable 2-pyrrolidone ring conjugates with a polyene chain substituted with a methyl ester moiety. The enzymatic route through which fusarin A, a major member of the fusarin family with a characteristic tetrohydrofuran-coupled pyrrolidone ring, is formed in F. graminearum has not been established. By targeting the final step in the biosynthesis of fusarin A, we report here an S-adenosyl methionine-dependent carboxyl methyltransferase responsible for the formation of the methyl ester moiety by in vivo gene inactivation, isolation and characterization of a key fusarin intermediate, and in vitro biochemical characterization. Related findings provide insights into the poorly understood biosynthetic pathway of fusarin A. Additionally, bioactivity assays demonstrate that the methyl ester is necessary for fusarin cytotoxicity.

A modified dental age assessment method for 5- to 16-year-old eastern Chinese children.

OBJECTIVES: Age estimation is widely applied in the field of orthodontics, pediatric dentistry, and forensic science. Dental age estimation by the radiological method is frequently used because of its convenience and noninvasiveness. However, there are not enough suitable methods for eastern Chinese children. This study aimed to establish a modified formula for eastern Chinese children according to the Demirjian method and then compared the accuracy of the modified method with the Demirjian method and Willems method. MATERIALS AND METHODS: A total of 2367 dental panoramic radiographs from individuals aged 5-16 years of eastern China were collected as samples. Age estimation was conducted using the Demirjian and Willems methods. The polynomial curve fitting method was used to modify the Demirjian method to improve its application to the eastern Chinese children. The paired t test and accuracy ratio were used to compare the applicability of the modified methods with two commonly used methods. RESULTS: The mean chronological age (CA) of the subjects was 11.20 ± 3.29 years for boys and 10.99 ± 3.12 years for girls. The mean difference values between the CA and dental age (DA) (CA-DA) using the Demirjian and Willems methods were 0.73 and 0.7 for boys, respectively, and both 0.79 for girls. The modified method using the polynomial curve fitting presented a smaller underestimation compared with CA for both boys (0.04 years) and girls (0.09 years), which showed a high suitability to Chinese children to some extent. CONCLUSIONS: The Willems method was more accurate in estimating DA compared with the Demirjian method. However, the modified method was more accurate than the two methods; therefore, it can be used in eastern Chinese children. CLINICAL RELEVANCE: It was thought to be a non-invasive, convenient, and efficient method to connect DA and CA. By estimating dental age, pediatrist, and orthodontists can better understand the development of permanent teeth and provide a more accurate orthodontic treatment time and treatment plan to children patients.

Machine learning assisted Cameriere method for dental age estimation.

BACKGROUND: Recently, the dental age estimation method developed by Cameriere has been widely recognized and accepted. Although machine learning (ML) methods can improve the accuracy of dental age estimation, no machine learning research exists on the use of the Cameriere dental age estimation method, making this research innovative and meaningful. AIM: The purpose of this research is to use 7 lower left permanent teeth and three models [random forest (RF), support vector machine (SVM), and linear regression (LR)] based on the Cameriere method to predict children's dental age, and compare with the Cameriere age estimation. SUBJECTS AND METHODS: This was a retrospective study that collected and analyzed orthopantomograms of 748 children (356 females and 392 males) aged 5-13 years. Data were randomly divided into training and test datasets in an 80-20% proportion for the ML algorithms. The procedure, starting with randomly creating new training and test datasets, was repeated 20 times. 7 permanent developing teeth on the left mandible (except wisdom teeth) were recorded using the Cameriere method. Then, the traditional Cameriere formula and three models (RF, SVM, and LR) were used to estimate the dental age. The age prediction accuracy was measured by five indicators: the coefficient of determination (R2), mean error (ME), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). RESULTS: The research showed that the ML models have better accuracy than the traditional Cameriere formula. The ME, MAE, MSE, and RMSE values of the SVM model (0.004, 0.489, 0.392, and 0.625, respectively) and the RF model (- 0.004, 0.495, 0.389, and 0.623, respectively) were lower with the highest accuracy. In contrast, the ME, MAE, MSE and RMSE of the European Cameriere formula were 0.592, 0.846, 0.755, and 0.869, respectively, and those of the Chinese Cameriere formula were 0.748, 0.812, 0.890 and 0.943, respectively. CONCLUSIONS: Compared to the Cameriere formula, ML methods based on the Cameriere's maturation stages were more accurate in estimating dental age. These results support the use of ML algorithms instead of the traditional Cameriere formula.

Oxidative Indole Dearomatization for Asymmetric Furoindoline Synthesis by a Flavin-Dependent Monooxygenase Involved in the Biosynthesis of Bicyclic Thiopeptide Thiostrepton.

The interest in indole dearomatization, which serves as a useful tool in the total synthesis of related alkaloid natural products, has recently been renewed with the intention of developing new methods efficient in both yield and stereoselective control. Here, we report an enzymatic approach for the oxidative dearomatization of indoles in the asymmetric synthesis of a variety of furoindolines with a vicinal quaternary carbon stereogenic center. This approach depends on the activity of a flavin-dependent monooxygenase, TsrE, which is involved in the biosynthesis of bicyclic thiopeptide antibiotic thiostrepton. TsrE catalyzes 2,3-epoxidation and subsequent epoxide opening in a highly enantioselective manner during the conversion of 2-methyl-indole-3-acetic acid or 2-methyl-tryptophol to furoindoline, with up to >99 % conversion and >99 % ee under mild reaction conditions. Complementing current chemical methods for oxidative indole dearomatization, the TsrE activity-based approach enriches the toolbox in the asymmetric synthesis of products possessing a furoindoline skeleton.

A Heterotrimeric Dehydrogenase Complex Functions with 2 Distinct YcaO Proteins to Install 5 Azole Heterocycles into 35-Membered Sulfomycin Thiopeptides.

Sulfomycins are sulfur-rich, ribosomally synthesized, and post-translationally modified peptides (RiPPs) that are characterized by a 35-membered macrocyclic ring system with a pyridine domain central to five azoles and additional dehydroamino acids. The pathway through which these large thiopeptide antibiotics are formed in Streptomyces viridochromogene remains elusive. Starting with the cloning of the biosynthetic gene cluster of sulfomycins, we here dissect a two-stage process in which an unusual dehydrogenase heterotrimer functions with two distinct YcaO proteins to install five azole heterocycles into the core peptide sequence of the precursor peptide. The first stage involves the activity of a typical cyclodehydratase complex composed of a didomain E1-YcaO protein and an F-protein partner to heterocyclize distant residues l-Cys2 and l-Thr9 and then the activity of the heterotrimeric dehydrogenase complex that converts the resulting azolines to azoles. In the second stage, this dehydrogenase complex associates with a discrete YcaO protein to form an atypical, four-component azole synthase complex, which is capable of sequentially converting residues l-Cys7, l-Thr5, and l-Ser12 to azoles in a distinct manner. During this process, an E1-like partner protein plays a critical role and functions through the two stages to mediate a variety of specific protein-protein interactions. This partner protein participates in the formation of the active dehydrogenase heterotrimer and the engagement of discrete YcaO activity to form the azole synthase heterotetramer. The findings in this study advance the understanding in the biosynthesis of different azole-containing RiPPs and set the stage for the discovery, engineering, and creation of new thiopeptides using genome mining and synthetic biology approaches.

Applicability of 2 Dental Age Estimation Methods to Taiwanese Population.

The aim of this study is to assess the accuracy of Demirjian and Willems dental age estimation methods on a population of 8- to 15-year-old Taiwanese children. A total of 799 digital panoramic radiographs (404 boys, 395 girls) of children aged from 8.00 to 15.99 years are evaluated. All panoramic films are assessed by 2 examiners using Demirjian and Willems methods. We randomly select 48 panoramic films to evaluate the reproducibility of dental age measurements. The intraobserver and interobserver Cohen's kappa values are 0.733 and 0.762, respectively.The difference between chronological age and dental age is calculated for each individual using both methods. The result shows that Demirjian method slightly overestimates the chronological age of children. The mean age difference is 0.12 years for boys (standard deviation [SD], 0.80) and 0.21 years for girls (SD, 0.95). Willems method slightly underestimates the chronological age of children. The mean age difference is -0.22 years for boys (SD, 0.80) and -0.12 years for girls (SD, 0.92).In conclusion, Demirjian and Willems methods are both accurate for assessing dental age in the Taiwan region of China. The mean age differences of both methods are within ±1 year, which is acceptable at forensic odontology level. However, although the discrepancy between chronological age and dental age is frequently observed between -0.5 and 0.5 years in both methods, there is no guarantee it will be accurate for any particular individual, further modifications to both methods are suggested.

Downregulation of Nrf2 promotes autophagy-dependent osteoblastic differentiation of adipose-derived mesenchymal stem cells.

Adipose derived stem cells (ADSCs) are an important source of stem cells for tissue repair and regeneration; therefore, understanding the mechanisms that regulate stem cell differentiation into a specific lineage is critical. The NF-E2-related factor 2 (Nrf2) pathway and autophagy promote cell survival in response to oxidative stress. However, the roles of Nrf2 and autophagy in bone metabolism under oxidative stress are controversial. Here, we explored the involvement of Nrf2 signaling and autophagy on the differentiation of ADSCs under conditions of oxidative stress. Exposure of ADSCs to H2O2 promoted reactive oxygen species (ROS) accumulation concomitant with the reduction of cell viability, upregulation of Nrf2, the induction of apoptosis and autophagy, and the promotion of osteogenesis. Suppression of autophagic activity at particular stages resulted in the activation of the Nrf2 pathway, whereas osteoblastic differentiation of ADSCs was inhibited upon ROS stimulation. Silencing of Nrf2 promoted autophagy and osteoblastic differentiation upon ROS stimulation in vitro, and this effect was confirmed in vivo in a mouse model, in which bone formation was enhanced in mice receiving Nrf2-knockdown ADSCs. Taken together, these findings indicate that a negative interaction between the Nrf2 pathway and autophagy may modulate oxidative stress-induced ADSC osteogenesis, and suggest that Nrf2 is a potential target to regulate the differentiation of ADSCs into a specific lineage.