Analysis of preoperative computed tomography radiomics and clinical factors for predicting postsurgical recurrence of papillary thyroid carcinoma.

BACKGROUND: Postsurgical recurrence is of great concern for papillary thyroid carcinoma (PTC). We aim to investigate the value of computed tomography (CT)-based radiomics features and conventional clinical factors in predicting the recurrence of PTC. METHODS: Two-hundred and eighty patients with PTC were retrospectively enrolled and divided into training and validation cohorts at a 6:4 ratio. Recurrence was defined as cytology/pathology-proven disease or morphological evidence of lesions on imaging examinations within 5 years after surgery. Radiomics features were extracted from manually segmented tumor on CT images and were then selected using four different feature selection methods sequentially. Multivariate logistic regression analysis was conducted to identify clinical features associated with recurrence. Radiomics, clinical, and combined models were constructed separately using logistic regression (LR), support vector machine (SVM), k-nearest neighbor (KNN), and neural network (NN), respectively. Receiver operating characteristic analysis was performed to evaluate the model performance in predicting recurrence. A nomogram was established based on all relevant features, with its reliability and reproducibility verified using calibration curves and decision curve analysis (DCA). RESULTS: Eighty-nine patients with PTC experienced recurrence. A total of 1218 radiomics features were extracted from each segmentation. Five radiomics and six clinical features were related to recurrence. Among the 4 radiomics models, the LR-based and SVM-based radiomics models outperformed the NN-based radiomics model (P = 0.032 and 0.026, respectively). Among the 4 clinical models, only the difference between the area under the curve (AUC) of the LR-based and NN-based clinical model was statistically significant (P = 0.035). The combined models had higher AUCs than the corresponding radiomics and clinical models based on the same classifier, although most differences were not statistically significant. In the validation cohort, the combined models based on the LR, SVM, KNN, and NN classifiers had AUCs of 0.746, 0.754, 0.669, and 0.711, respectively. However, the AUCs of these combined models had no significant differences (all P > 0.05). Calibration curves and DCA indicated that the nomogram have potential clinical utility. CONCLUSIONS: The combined model may have potential for better prediction of PTC recurrence than radiomics and clinical models alone. Further testing with larger cohort may help reach statistical significance.

Development and validation of a prediction model of pneumothorax after CT-guided coaxial core needle lung biopsy.

Background: Pneumothorax is the most common complication of computed tomography-guided coaxial core needle biopsy (CCNB) and may be life-threatening. We aimed to evaluate the risk factors and develop a model for predicting pneumothorax in patients undergoing computed tomography-guided CCNB, and to further determine its clinical utility. Methods: Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for pneumothorax from 18 variables. A predictive model was established using multivariable logistic regression and presented as a nomogram based on a training cohort of 690 patients who underwent computed tomography-guided CCNB. The model was validated in 253 consecutive patients in the validation cohort and 250 patients in the test cohort. The area under the curve was used to determine the predictive accuracy of the proposed model. Results: The risk factors associated with pneumothorax after computed tomography-guided CCNB were sex, patient position, lung field, lesion contact with the pleura, lesion size, distance from the pleura to the lesion, presence of emphysema adjacent to the biopsy tract, and crossing fissures. The predictive model that incorporated these predictors showed good predictive performance in the training cohort [area under the curve, 0.71 (95% confidence interval: 0.67-0.75)], validation cohort [0.71 (0.64-0.78)], and internal test cohort [0.68 (0.60-0.75)]. The nomogram also provided excellent calibration and discrimination, and decision curve analysis (DCA) demonstrated its clinical utility. Conclusions: The predictive model showed good performance for pneumothorax after computed tomography-guided CCNB and may help improve individualized preoperative prediction.

Added value of histogram analysis of ADC in predicting radiation-induced temporal lobe injury of patients with nasopharyngeal carcinoma treated by intensity-modulated radiotherapy.

BACKGROUND: This study evaluated the predictive potential of histogram analysis derived from apparent diffusion coefficient (ADC) maps in radiation-induced temporal lobe injury (RTLI) of nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT). RESULTS: Pretreatment diffusion-weighted imaging (DWI) of the temporal lobes of 214 patients with NPC was retrospectively analyzed to obtain ADC histogram parameters. Of the 18 histogram parameters derived from ADC maps, 7 statistically significant variables in the univariate analysis were included in the multivariate logistic regression analysis. The final best prediction model selected by backward stepwise elimination with Akaike information criteria as the stopping rule included kurtosis, maximum energy, range, and total energy. A Rad-score was established by combining the four variables, and it provided areas under the curve (AUCs) of 0.95 (95% confidence interval [CI] 0.91-0.98) and 0.89 (95% CI 0.81-0.97) in the training and validation cohorts, respectively. The combined model, integrating the Rad-score with the T stage (p = 0.02), showed a favorable prediction performance in the training and validation cohorts (AUC = 0.96 and 0.87, respectively). The calibration curves showed a good agreement between the predicted and actual RTLI occurrences. CONCLUSIONS: Pretreatment histogram analysis of ADC maps and their combination with the T stage showed a satisfactory ability to predict RTLI in NPC after IMRT.

Recombinant human endostatin injection (Endostar) combined with PF chemotherapy and sequential intensity-modulated radiotherapy is tolerable and improves prognosis of locally advanced nasopharyngeal carcinoma: a randomized, open, multicenter phase II clinical study.

Nasopharyngeal carcinoma (NPC) is not only a common malignant disease of the head and neck, but also presented as locoregionally advanced NPC at diagnosis with poor prognosis. The efficacy of current chemoradiotherapy is unsatisfactory; therefore, in this study, we evaluated the safety and efficacy of treating locally advanced NPC using recombinant human endostatin injection (Endostar), combined with a cisplatin plus 5-fluorouracil (PF) regimen and sequential intensity-modulated radiotherapy (IMRT), and compared it with PF plus IMRT regimen. This phase II study included 83 eligible patients with stages III-IVa NPC (8th AJCC/UICC) who were randomized 1:1 into control (n = 42) and experimental (n = 41) groups. The control group received PF chemotherapy and IMRT for locally advanced NPC; One cycle of induction chemotherapy (IC) was administered before IMRT, and three cycles of adjuvant chemotherapy (AC) were administered four weeks post-radiotherapy. The experimental group received additional Endostar therapy. All patients were followed up for at least 5 years. The primary endpoints were progression-free survival (PFS) and the objective response rate. The secondary endpoints included overall survival and treatment-related toxicities. The short-term efficacy was evaluated at the end of the fourth chemotherapy cycle. Our results showed that the complete response rate of nasopharyngeal lesions was not significantly different between the experimental and control groups (80.5 vs. 71.4%, P = 0.335); however, there were significant differences in the complete response rates of cervical metastatic lymph nodes (75.6 vs. 40.5%, P = 0.001), especially for cervical N3 lymph nodes in the experimental group (55.6 vs. 9.5%, P = 0.004). The overall median follow-up time was 69.7 months. Patients in the experimental group showed significantly prolonged PFS by about four months (hazard ratio [HR] = 0.64, 95% CI: 0.41-0.99, P = 0.045). There was no significant difference in the median overall survival (P = 0.374). Furthermore, subgroup analysis indicated that the risk of death in patients with cervical N3 lymph nodes in the experimental group was reduced by 52% (HR = 0.48, 95% CI: 0.23-0.99, P = 0.046). Moreover, the incidence of radiation-induced grades 3-4 oral mucositis was significantly lower in the experimental group (29.3% vs. 54.8%, P = 0.019), while no significant differences in other severe adverse reactions were observed between the two groups (P>0.05). Taken together, our study indicated that, in patients with locally advanced NPC, Endostar in combination with PF chemotherapy and sequential IMRT significantly improved PFS, had tolerable treatment-related toxicities, improved the prognoses of patients with cervical N3 lymph nodes, and reduced the incidence of radiation-related oral mucositis.

Prediction model based on preoperative CT findings for carotid artery invasion in patients with head and neck masses.

Objectives: To investigate the performance of a model in predicting carotid artery (CA) invasion in patients with head and neck masses using computed tomography (CT). Methods: This retrospective study included patients with head and neck masses who underwent CT and surgery between January 2013 and July 2021. Patient characteristics and ten CT features were assessed by two radiologists. The patients were randomly allocated to a training cohort (n=106) and a validation cohort (n=109). Independent risk factors for CA invasion were assessed by univariate and multivariate logistic regression analyses. The predictive model was established as a nomogram using the training cohort. In addition, the calibration, discrimination, reclassification, and clinical application of the model were assessed in the validation cohort. Results: A total of 215 patients were evaluated, including 54 patients with CA invasion. Vascular wall deformation (odds ratio [OR], 7.17; p=0.02) and the extent of encasement to the CA (OR, 1.02; p<0.001) were independent predictors of CA invasion in the multivariable analysis in the training cohort. The performance of the model was similar between the training and validation cohort, with an area under the receiver operating characteristic curve of 0.93 (95% confidence intervals [CI], 0.88-0.98) and 0.88 (95% CI, 0.80-0.96) (p=0.07), respectively. The calibration curve showed a good agreement between the predicted and actual probabilities. Conclusion: A predictive model for carotid artery invasion can be defined based on features that come from patient characteristics and CT data to help in improve surgical planning and invasion evaluation.

Sintilimab combined with apatinib plus capecitabine in the treatment of unresectable hepatocellular carcinoma: A prospective, open-label, single-arm, phase II clinical study.

Objective: To evaluate the efficacy and safety of sintilimab combined with apatinib plus capecitabine in the treatment of unresectable hepatocellular carcinoma (HCC) to provide a more effective first-line treatment for patients with advanced HCC. Methods: This open-label, prospective, phase II study included patients with unresectable HCC who did not receive systematic treatment. The patients were treated with sintilimab (200 mg, intravenous drip, once every 3 weeks) combined with apatinib (250 mg, oral administration, once a day) plus capecitabine (1000 mg/m2, twice a day; after 2 weeks of oral administration, the drug was stopped for 1 week; course of treatment, 3 weeks). The primary endpoint was the objective response rate (ORR). The secondary endpoints included disease control rate (DCR), progression-free survival (PFS), duration of response (DoR), overall survival (OS), and safety. Results: Forty-seven patients (1 lost to follow-up) were enrolled in the study. As of March 1, 2022, the ORR and DCR were 50.0% (95% CI: 34.9-65.1%) and 91.3% (95% CI: 79.2-97.6%), respectively, after blind, independent imaging evaluation. The median follow-up time was 18.7 months (95% CI: 17.2-20.2 months). The median PFS was 9.0 months (95% CI: 7.1-10.9 months). The median DoR was 10.8 months (95% CI: 4.8-16.8 months). The median OS was not reached, and the 1-year OS rate was 71.7% (95% CI: 56.5-84.0%). Only 28.3% (13/46) of patients had grade 3/4 treatment-related adverse events. Conclusion: Sintilimab combined with apatinib plus capecitabine has good safety and anti-tumor activity as a first-line treatment for unresectable HCC. This is worthy of further multi-center, prospective, randomized, large-sample clinical studies. Clinical Trial Registration: https://ClinicalTrials.gov, identifier NCT04411706.

Magnetic resonance imaging-based radiomics model for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma after intensity-modulated radiotherapy.

BACKGROUND: To develop a model based on magnetic resonance imaging (MRI) radiomics and clinical features for predicting radiation-induced temporal lobe injury (RTLI) in patients with nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT). METHODS: Two hundred and sixteen patients with NPC were retrospectively included. Radiomics features were extracted and selected. The logistic regression analysis was performed for prediction models construction. The area under the receiver operating characteristic curve (AUC) was calculated for performance evaluation. RESULTS: Three radiomics features were selected to construct the radiomics signature (AUC of 0.94 and 0.92). The clinical-radiomics model, integrating radiomics signature with T classification, achieved higher predictive performance in the training and validation cohorts (AUC of 0.95 and 0.93), as well as improved accuracy of the classification of RTLI outcomes (net reclassification improvement: 0.711; 95% CI: 0.57-0.86; p < 0.001). CONCLUSIONS: The clinical-radiomics model and radiomics signature both showed great performance in predicting RTLI in patients with NPC.

[Clinical Analysis of Gene Mutation and Vascular Events in Patients with BCR/ABL Negative Myeloproliferative Neoplasms].

OBJECTIVE: To explore the relationship between clinical features, peripheral blood cell count, coagulation function, gene mutation and hemorrhagic events and thrombotic events in essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis(PMF) patients. METHODS: Clinical data of 78 patients with ET, PV, and PMF who were admitted to the Second Affiliated Hospital of Chongqing Medical University between September 2019 and August 2020 were retrospectively analyzed. Information about sex, age, gene mutation, peripheral blood cell count, coagulation function, and hemorrhagic and thrombotic events was included, and the influence of these data on the occurrence of hemorrhagic and thrombotic events was estimated. RESULTS: Among the 78 patients with myeloproliferative neoplasms, there were 47 cases of ET, 15 cases of PV, and 16 cases of PMF.A total of 10 patients (12.82%) experienced hemorrhagic events and 27 (34.62%) experienced thrombotic events. Male,patients aged ≥ 60 years, and patients with a JAK2V617F mutation were more likely to experience thrombotic events (P<0.05). Patients with thrombotic events had higher platelet (PLT) counts and fibrinogen (FIB) levels than patients without hemorrhagic-thrombotic events (P<0.05).White blood cell (WBC) count, red blood cell (RBC) count, hemoglobin (HGB) level, prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT) and international normalized ratio (INR) showed no statistical difference between patients with thrombotic events and patients without hemorrhagic-thrombotic events (P>0.05). There was also no significant difference in the above-mentioned indexes between patients with hemorrhagic events and patients without hemorrhagic-thrombotic events (P>0.05). Among JAK2V617F positive myeloproliferative neoplasm patients, male patients were more likely to have thrombotic events (P<0.05), and patients with thrombotic events had higher platelet counts than those without hemorrhagic-thrombotic events (P<0.05). There was no significant difference in age, white blood cell count, red blood cell count, hemoglobin level, PT, APTT, FIB, TT or INR between patients with thrombotic events and patients without hemorrhagic-thrombotic events (P>0.05). CONCLUSION: Sex, age, JAK2V617F mutation and platelet count have a certain value for predicting thrombosis in patients with myeloproliferative neoplasms.

A MRI-based radiomics model predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

OBJECTIVES: To develop and validate a radiomics-based model for predicting radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) by pretreatment MRI of the temporal lobe. METHODS: A total of 216 patients with diagnosed NPC were retrospectively reviewed. Patients were randomly allocated to the training (n = 136) and the validation cohort (n = 80). Radiomics features were extracted from pretreatment contrast-enhanced T1- or fat-suppressed T2 weighted MRI. A radiomics signature was generated by the least absolute shrinkage and selection operator (LASSO) regression algorithm, Pearson correlation analysis, and univariable logistic analysis. Clinical features were selected with logistic regression analysis. Multivariable logistic regression analysis was conducted to develop three models for RTLI prediction in the training cohort: namely radiomics signature, clinical variables, and clinical-radiomics parameters. A radiomics nomogram was used and assessed with respect to calibration, discrimination, reclassification, and clinical application. RESULTS: The radiomics signature, composed of two radiomics features, was significantly associated with RTLI. The proposed radiomics model demonstrated favorable discrimination in both the training (AUC, 0.89) and the validation cohort (AUC, 0.92), outperforming the clinical prediction model (p < 0.05). Combining radiomics and clinical features, higher AUCs were achieved (AUC, 0.93 and 0.95), as well as a better calibration and improved accuracy of the prediction of RTLI. The clinical-radiomics model showed also excellent performance in predicting RTLI in different clinical-pathologic subgroups. CONCLUSION: A radiomics model derived from pretreatment MRI of the temporal lobe showed persuasive performance for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma. KEY POINTS: • Radiomics features from pretreatment MRI are associated with radiation-induced temporal lobe injury in nasopharyngeal carcinoma. • The radiomics model shows better predictive performance than a clinical model and was similar to a clinical-radiomics model. • A clinical-radiomics model shows excellent performance in the prediction of radiation-induced temporal lobe injury in different clinical-pathologic subgroups.

Baseline MRI-based radiomics model assisted predicting disease progression in nasopharyngeal carcinoma patients with complete response after treatment.

BACKGROUND: Accurate pretreatment prediction for disease progression of nasopharyngeal carcinoma is key to intensify therapeutic strategies to high-risk individuals. Our aim was to evaluate the value of baseline MRI-based radiomics machine-learning models in predicting the disease progression in nasopharyngeal carcinoma patients who achieved complete response after treatment. METHODS: In this retrospective study, 171 patients with pathologically confirmed nasopharyngeal carcinoma were included. Using hold-out cross validation scheme (7:3), relevant radiomic features were selected with the least absolute shrinkage and selection operator method based on baseline T2-weighted fat suppression and contrast-enhanced T1-weighted images in the training cohort. After Pearson's correlation analysis of selected radiomic features, multivariate logistic regression analysis was applied to radiomic features and clinical characteristics selection. Logistic regression analysis and support vector machine classifier were utilized to build the predictive model respectively. The predictive accuracy of the model was evaluated by ROC analysis along with sensitivity, specificity and AUC calculated in the validation cohort. RESULTS: A prediction model using logistic regression analysis comprising 4 radiomics features (HGLZE_T2H, HGLZE_T1, LDLGLE_T1, and GLNU_T1) and 5 clinical features (histology, T stage, N stage, smoking history, and age) showed the best performance with an AUC of 0.75 in the training cohort (95% CI: 0.66-0.83) and 0.77 in the validation cohort (95% CI: 0.64-0.90). The nine independent impact factors were entered into the nomogram. The calibration curves for probability of 3-year disease progression showed good agreement. The features of this prediction model showed satisfactory clinical utility with decision curve analysis. CONCLUSIONS: A radiomics model derived from pretreatment MR showed good performance for predicting disease progression in nasopharyngeal carcinoma and may help to improve clinical decision making.

The Silence of PSMC6 Inhibits Cell Growth and Metastasis in Lung Adenocarcinoma.

The proteasome has been validated as an anticancer drug target, while the role of a subunit of proteasome, PSMC6, in lung adenocarcinoma (LUAD) has not been fully unveiled. In this study, we observed that both the RNA and protein of PSMC6 were highly upregulated in LUAD compared with the adjacent normal tissues. Moreover, a high PSMC6 expression was associated with poor prognosis. In accordance with this finding, PSMC6 was associated with poor tumor differentiation. Furthermore, the silence of PSMC6 by small interference RNAs (siRNAs) could significantly inhibit cell growth, migration, and invasion in lung cancer cell lines, suggesting that PSMC6 might serve as a promising therapeutic target in LUAD. To further explore the molecular mechanism of PSMC6 in LUAD, we observed that the proteasome subunits, such as PSMD10, PSMD6, PSMD9, PSMD13, PSMB3, PSMB1, PSMA4, PSMC1, PSMC2, PSMD7, and PSMD14, were highly correlated with PSMC6 expression. Based on the gene set enrichment analysis, we observed that these proteasome subunits were involved in the degradation of AXIN protein. The correlation analysis revealed that the positively correlated genes with PSMC6 were highly enriched in WNT signaling-related pathways, demonstrating that the PSMC6 overexpression may activate WNT signaling via degrading the AXIN protein, thereby promoting tumor progression. In summary, we systematically evaluated the differential expression levels and prognostic values of PSMC6 and predicted its biological function in LUAD, which suggested that PSMC6 might act as a promising therapeutic target in LUAD.

Prognostic and predictive value of radiomics features at MRI in nasopharyngeal carcinoma.

PURPOSE: To explore the value of MRI-based radiomics features in predicting risk in disease progression for nasopharyngeal carcinoma (NPC). METHODS: 199 patients confirmed with NPC were retrospectively included and then divided into training and validation set using a hold-out validation (159: 40). Discriminative radiomic features were selected with a Wilcoxon signed-rank test from tumors and normal masticatory muscles of 37 NPC patients. LASSO Cox regression and Pearson correlation analysis were applied to further confirm the differential expression of the radiomic features in the training set. Using the multiple Cox regression model, we built a radiomic feature-based classifier, Rad-Score. The prognostic and predictive performance of Rad-Score was validated in the validation cohort and illustrated in all included 199 patients. RESULTS: We identified 1832 differentially expressed radiomic features between tumors and normal tissue. Rad-Score was built based on one radiomic feature: CET1-w_wavelet.LLH_GLDM_Dependence-Entropy. Rad-Score showed a satisfactory performance to predict disease progression in NPC with an area under the curve (AUC) of 0.604, 0.732, 0.626 in the training, validation, and the combined cohort (all 199 patients included) respectively. Rad-Score improved risk stratification, and disease progression-free survival was significantly different between these groups in every cohort of patients (p = 0.044 or p < 0.01). Combining radiomics and clinical features, higher AUC was achieved of the prediction of 3-year disease progression-free survival (PFS) (AUC, 0.78) and 5-year disease PFS (AUC, 0.73), although there was no statistical difference. CONCLUSION: The radiomics classifier, Rad-Score, was proven useful for pretreatment prognosis prediction and showed potential in risk stratification for NPC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-021-00460-3.

Maternal anti-tumour necrosis factor-α drug use during pregnancy and risk of infection in the offspring: A systematic review and meta-analysis.

BACKGROUND: Anti-tumour necrosis factor (TNF)-α drugs are used by increasing numbers of reproductive-age women. Although the neonatal outcomes have been described, there are concerns regarding the risk of infection in offspring following exposure to anti-TNF-α. METHODS: A literature search was conducted using Pubmed, EMBASE, and the Cochrane Database, from inception through August 2020. We evaluated the risk of infection in autoimmune disease (AID) offspring unexposed to anti-TNF-α compared to AID offspring exposed to anti-TNF-α, as well as to unexposed non-AID offspring. RESULTS: Our primary analysis showed that both AID offspring unexposed to anti-TNF-α [risk ratio (RR) 1.09; 95% confidence interval (CI), 1.03-1.16; I2=0%] and AID offspring exposed to anti-TNF-α (RR 1.39; 95% CI, 1.2-1.61; I2=0%] was associated with an increased risk of infection during the first year of life compared with the unexposed non-AID offspring. However, our secondary analysis demonstrated that AID offspring exposed to anti-TNF-α was not associated with an increased risk of infection when compared with AID offspring unexposed to anti-TNF-α (RR=1.1; 95% CI, 0.86-1.4). CONCLUSION: Our results suggest that in utero exposure to anti-TNF-α does not appear to increase the risk of infection during the first year of life in the offspring; however, AID itself was associated with a marked excess risk of infection in the children.

Establishment of a Mouse Model of Premature Ovarian Failure Using Consecutive Superovulation.

BACKGROUND/AIMS: This study investigated the effect of consecutive superovulation on the ovaries and established a premature ovarian failure (POF) model in mice. METHODS: The mouse POF model was induced by 5-15 consecutive superovulation treatments with pregnant mare serum gonadotropin (PMSG), human chorionic gonadotropin (HCG) and prostaglandin F2α (PGF2α). Normal adult mice were compared with mice displaying natural ovarian aging. The following serum biochemical parameters were measured: including follicle-stimulating hormone (FSH), luteinizing hormone (LH), progesterone (P), estradiol (E2), inhibin B (INH B), malondialdehyde (MDA), total superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) levels. Follicles were counted using H&E staining. Levels of 8-hydroxyguanosine (8-OhdG), 4-hydroxynonenal (4-HNE), nitrotyrosine (NTY), anti-Mullerian hormone (AMH) and CDKN2A/ p16 (p16) were detected using immunohistochemical staining. Reactive oxygen species (ROS) levels were measured using dihydroethidium (DHE) staining. Cell apoptosis was detected using an in situ TUNEL fluorescence staining assay. Levels of proteins involved in ROS-related pathways and the p16 protein were detected using Western blotting. Sod1, Sod2 and Sod3 mRNA levels were detected using quantitative polymerase chain reaction (Q-PCR). Oocyte quality was evaluated using in vitro fertilization (IVF) and zygote culture. RESULTS: Consecutive superovulation groups presented lower P, E2, SOD, GSH-Px and INH B levels, significantly higher FSH, LH, MDA and ROS levels, and significantly fewer primordial follicles compared with the control group. Consecutive superovulation groups presented significantly increased levels of Sod2, 8-OhdG, 4-HNE, NTY, significantly increased levels of the SIRT1 and FOXO1 proteins, significantly increased levels of the senescence-associated protein p16, as well as decreased AMH, Sod1 and Sod3 levels and increased granulosa cell apoptosis compared with the control group. CONCLUSION: Consecutive superovulation significantly decreased ovarian function and oocyte quality and increased oxidative stress and apoptosis in the ovary via a mechanism involving the p16 and SIRT1/FOXO1 signaling pathways. These findings suggest that consecutive superovulation may be used to establish a mouse model of ovarian aging.

[Changes of T Cell Subsets and Their Relationship with Clinical Features and Prognosis in Patients with Acute Leukemia].

OBJECTIVE: To analyze the relationship between T cell subsets and clinical data. METHODS: mononuclear cells were collected from 103 patients with acute leukemia (AL) and 28 healthy volunteers, and percentage changes of CD3+CD4+, CD3+CD8+ and CD4+ CD25+ Foxp3+ cell subsets were assayed by flow cytometory. Relationship between the T subsets and clinical features of the patients was analyzed. RESULTS: Ratio of CD3+ T cells decreased more significantly in patients with >50% blast cells than that in patients with <50% blast cells, while the ratio of Treg between the 2 groups was not significantly different. Treg increased more statistically significantly in the patients with CD34+ leukemia cell than that with CD34- leukemia cells. In constrast to the relationship between prognosis and immune cells in the patients from 3 groups (low, intermediate and high-risk group) it was found that Treg cells increased more significantly in high-risk group than that in low-risk group. By continuously monitoring immune cells in 18 patients, it was found that Treg cells gradually increased during the first 3 courses of chemotherapy, then began to decreased in the 4th course, finally approached gradually to the normal value in the 6th course, and this change correlated with the clinical remission after chemotherapy. Treg cell number in the patients with AL was significantly higher than that in healthy controls, and Treg cell number during the onset and recurrence was significantly higher than that in the period of complete remission (continuous remission for over 6 months). Compared with the changes of immune cell number between different types of disease, it was found that Treg cells were increased more significantly in acute myeloid leukemia (AML) than that in acute lymphoblastic leukemia (ALL). Proportion of Treg cells, Treg/CD4 decreased more significantly after the 1st course of chemotherapy in the group with complete remission (CR) than that in the group without CR. The complete remission rate and recurrence rate were 68.9% and 20% respectively in the group with >10% Treg cells, while the complete remission rate and recurrence rate were 85.7% and 7.69% respectively in the group with.<10% Treg cells. In comparison of the 6 recurrent patients with 32 patients with sustained CR, it was found that the ratio of Treg cells and Treg/CD4 was increased more significantly in the patients with relapse than that with CR and in control group. CONCLUSION: Dynamic change of Treg cells in the peripheral blood was closely related with clinical feature, recurrence and prognosis in the patients with acute leukemia.

Curcumin exerts a protective effect against premature ovarian failure in mice.

This study was designed to investigate the protective effect of curcumin against d-galactose (d-gal)-induced premature ovarian failure (POF) in mice. A mouse POF model was induced by subcutaneous injection of d-gal (200 mg/kg/day) daily for 42 days. Mice in the curcumin group received both d-gal treatment and intraperitoneal injection of curcumin (100 mg/kg/day) for 42 days. Ovarian function, oxidative stress and apoptosis were evaluated. The P, E2 and SOD levels were higher, and the FSH, LH and MDA levels were significantly lower in the curcumin group than those in the d-gal group. The proportion of primordial follicles was also significantly higher in the curcumin group than that in the d-gal group. In addition, curcumin treatment after d-gal administration resulted in significantly lower Sod2, Cat, 8-OhdG, 4-HNE, NTY and senescence-associated protein P16 expression levels, higher Amh expression levels and less apoptosis in granulosa cells than was observed in the d-gal group. Moreover, the p-Akt, Nrf2 and HO-1 protein expression levels were significantly higher and the apoptosis-related cleaved caspase-3 and -9 protein expression levels were markedly lower in the curcumin group than in the d-gal group. In conclusion, curcumin effectively inhibited d-gal-induced oxidative stress, apoptosis and ovarian injury via a mechanism involving the Nrf2/HO-1 and PI3K/Akt signaling pathways, suggesting that curcumin is a potential protective agent against POF.

Effect of curcumin on glycerol-induced acute kidney injury in rats.

The aim of this study was to investigate the protective role and underlying mechanisms of curcumin on glycerol-induced acute kidney injury (AKI) in rats. Glycerol (10 ml/kg BW, 50% v/v in sterile saline, i.m.) was used to induce AKI, followed by curcumin (200 mg/kg/day, p.o.) administration for 3 days. To confirm renal damage and the effects of curcumin on AKI, serum BUN, Scr, and CK as well as renal SOD, MDA, GSH-Px were measured. Additionally, morphological changes were identified by H&E staining and transmission electron microscopy. The expression of several factors including chemotactic factor MCP-1, proinflammatory cytokines including TNF-α and IL-6, as well as the kidney injury markers, as Kim-1 and Lipocalin-2 were also assessed using q-PCR. Finally, cell apoptosis in renal tissue was detected using in situ TUNEL apoptosis fluorescence staining and expression of proteins associated with apoptotic, oxidative stress and lipid oxidative related signaling pathways were detected using immunohistochemical staining and western blot. The results showed that curcumin exerts renoprotective effects by inhibiting oxidative stress in rhabdomyolysis-induced AKI through regulation of the AMPK and Nrf2/HO-1 signaling pathways, and also ameliorated RM-associated renal injury and cell apoptosis by activating the PI3K/Akt pathway.

Effect of shRNA-Mediated Gene Silencing of Bmi-1 Expression on Chemosensitivity of CD44+ Nasopharyngeal Carcinoma Cancer Stem-Like Cells.

In this study, we investigate the effect of short hairpin RNA-mediated gene silencing of Bmi-1 expression on chemosensitivity of CD44(+) nasopharyngeal carcinoma cancer stem-like cells. The sequence-specific short hairpin RNA lentivirus targeting at human Bmi-1 was synthesized and used to infect CD44(+) nasopharyngeal cells that were sorted by flow cytometry. We also employed flow cytometry to detect transfection efficiency. Real-time polymerase chain reaction was used to detect Bmi-1 and its downstream repressor genes p16(INK4a) and p14(ARF) messenger RNA, while each protein expression level of Bmi-1, p16(INK4a), p14(ARF), and p53 was confirmed by Western blotting protocol. Tumor spheroid assay was used to evaluate the self-renewal capacity. 3-(4,5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide assay and colony formation assay were applied to detect proliferation capacity and colony-forming capacity under different concentrations of chemotherapeutic drugs 5-fluorouracil or cisplatin. Transwell cell migration and invasion assay were employed to observe migration and invasion capacity after cells were exposed to cisplatin for 24 hours. The constructed short hairpin RNA lentivirus targeting Bmi-1 gene successfully infected into the CD44(+) nasopharyngeal carcinoma cells and effectively inhibited the Bmi-1 messenger RNA and protein expression level, while the expression level of Bim-1 target genes, p16(INK4a), p14(ARF), and p53 was significantly increased (P < .05). Notably, the proliferation, colony formation, migration, and invasion capabilities of the sequence-specific short hairpin RNA lentivirus-infected CD44(+) nasopharyngeal carcinoma cells reduced significantly under chemotherapeutic treatments (P < .05). Our results indicated that Bmi-1 may play an important role in the chemosensitivity of CD44(+) nasopharyngeal carcinoma cancer stem-like cells. Bmi-1 may be a potential new target for the treatment of nasopharyngeal carcinoma displaying chemotherapy resistance.

Preliminary Characterization of a Leptin Receptor Knockout Rat Created by CRISPR/Cas9 System.

Leptin receptor, which is encoded by the diabetes (db) gene and is highly expressed in the choroid plexus, regulatesenergy homeostasis, the balance between food intake and energy expenditure, fertility and bone mass. Here, using CRISPR/Cas9 technology, we created the leptin receptor knockout rat. Homozygous leptin receptor null rats are characterized by obesity, hyperphagia, hyperglycemia, glucose intolerance, hyperinsulinemia and dyslipidemia. Due to long-term poor glycemic control, the leptin receptor knockout rats also develop some diabetic complications such as pancreatic, hepatic and renal lesions. In addition, the leptin receptor knockout rats show a significant decrease in bone volume and bone mineral density of the femur compared with their wild-type littermates. Our model has rescued some deficiency of the existing rodent models, such as the transient hyperglycemia of db/db mice in the C57BL/6J genetic background and the delayed onset of glucose intolerance in the Zucker rats, and it is proven to be a useful animal model for biomedical and pharmacological research on obesity and diabetes.