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This study investigated the relationship between challenge-hindrance stressors and innovative behavior of medical postgraduates in China, examining the mediating role of academic engagement and the moderating effect of relaxation. Drawing from a sample of 437 medical postgraduates from three Chinese universities, our findings revealed that challenge stressors positively correlated with innovative behavior, while the direct relationship between hindrance stressors and innovative behavior was not statistically significant. Furthermore, academic engagement mediated the relationship between two types of stressors and innovative behavior. Challenge stressors enhanced academic engagement, which in turn fostered innovative behavior. Conversely, hindrance stressors were found to diminish academic engagement, which in turn indirectly limited innovative behavior. Additionally, relaxation was identified as a moderating factor that helped mitigate the negative effects of hindrance stressors on academic engagement and indirectly on innovative behavior. These results suggested that academic engagement as a mechanism played a pivotal role in determining how different stressors influenced innovative behavior, underscoring the need for stress management, particularly through relaxation techniques, to maintain high levels of academic engagement and innovative behavior. This study offers practical insights for medical education policymakers and educators in China, emphasizing the importance of balancing stressors and incorporating relaxation practices to enhance the innovative capabilities of medical postgraduates in demanding academic environments.

Abstract 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.

Key points Histogram parameters from pretreatment ADC maps are associated with RTLI in NPC. The ADC and combined models show better performance than the T stage alone. The combined model shows excellent performance in predicting RTLI in different subgroups.

When radar receivers adopt digital channelization, it is prone to generating a cross-channel split signal, the rabbit ear effect, and a transition band repeated signal, leading to errors in radar signal sorting or identification. The pulse-splitting model and detection method proposed in this paper can model split pulses and identify them in radar pulse streams, facilitating the merging of split pulses to enhance sorting and identification performance. Firstly, the mechanism of splitting pulse generation is deeply analyzed, and the splitting site theory is proposed. Then, the split pulse signal model and the split pulse number statistical model based on geometric distribution are constructed, which are used to guide the construction of simulation data of split pulse flow with different characteristics. Furthermore, a time-domain convergence degree (TCD) index is proposed to characterize the pulse split phenomenon. At the same time, in order to avoid a large number of threshold searching problems in pulse-splitting detection, an empirical formula for the pulse-splitting detection threshold based on the TCD is given to quickly determine whether there is a pulse train split problem. The selected measured radar pulse stream is verified to follow a geometric distribution at a significance level of 0.05. The proposed method achieved a detection accuracy of at least 99.55% on the simulation dataset and at least 95.68% on the experimental dataset, validating the rationality of pulse-splitting modeling and the effectiveness of the detection method.

Abstract 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 cross-linking point of a conventional chemical cross-linking agent is fixed. Therefore, gels that are prepared with a conventional cross-linking agent have poor deformability, strength, shear resistance, and further properties. Some researchers have prepared a new cross-linking agent using cyclodextrin (CD). In a polyrotaxane cross-linking agent, the cross-linking points can slide freely along the molecule chain. The special “slide ring” structure can provide better elongation, strength, and other properties to gels, which can effectively expand the application of the gel’s materials. This paper summarizes the preparation methods and applications from different types of CD and compares the improvements of properties (swelling, viscoelastic properties, etc.). In addition, the current results of our group are presented, and some ideas are provided for the development of polyrotaxane cross-linking agents.

Abstract 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

ObjectivesTo investigate the performance of a model in predicting carotid artery (CA) invasion in patients with head and neck masses using computed tomography (CT).MethodsThis 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.ResultsA 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

Lost circulation is a world-class problem, and the contradiction between plugging and unplugging in reservoirs is a problem that needs to be solved urgently. The traditional LCM is not suitable for reservoirs and the complex subsequent operations. Currently, a self-degrading plugging material is proposed. In this paper, a new self-degradation plugging material, CKS-DPPG, was prepared by AM, GG, nano silica, and PEGDA. The effects of reactant concentration, pH, mineralization, etc., on the swelling and degradation performance of CKS-DPPG were investigated. The plugging capacity was tested by fracture plugging equipment, and the mechanism of self-degradation was revealed. The results show that the CKS-DPPG reached a 50% degradation rate in 54 h and complete degradation in 106 h at 80 °C and pH = 8. Low temperatures, high mineralization, and weak alkaline conditions prolong the complete degradation time of CKS-DPPG, which facilitates subsequent operations. The simulation of the 3 mm opening fracture plugging experiment showed that the pressure-bearing capacity reached 6.85 MPa and that a 0.16 MPa pressure difference could unplug after degradation. The ester bond of PEGDA is hydrolyzed under high-temperature conditions, and the spatial three-dimensional structure of CKS-DPPG becomes linear. The CKS-DPPG can effectively reduce subsequent unplugging operations and lower production costs.

ObjectiveTo 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.MethodsThis 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.ResultsForty-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.ConclusionSintilimab 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 Registrationhttps://ClinicalTrials.gov, identifier NCT04411706.

This study examines the role of wisdom in the cross-cultural adaptation of Chinese visiting scholars in Canada, as mediated by different coping styles. Path analysis was used to for hypotheses testing. The findings suggest that (1) wisdom measured by 3D-WS and Adult Self-Transcendence Inventory (ASTI), independently had direct correlation with social and psychological adaptation, and positively associated with engaged coping (active coping and proactive–reflective coping); (2) the independent effects of 3D-WS and ASTI on social adaptation, psychological adaptation, and life satisfaction were mediated by proactive–reflective coping; (3) wisdom, when measured by 3D-WS, promoted positive psychological adaptation through decreasing passive coping. This study shows that wisdom is a critical factor affecting cross-cultural adaptation, and the use of proactive–reflective coping is a wise way of handling future life challenges.

AbstractLost circulation often occurs in fractured formations, which was a main technological problem during drilling. Conventional lost circulation material (LCM) was often used to form a plugging zone to prevent fluid loss during drilling. The formed seal was a granular material system composed of LCMs. This paper presented the physical mechanism of the force chain within the plugging zone. The seal performance is related to the properties of LCMs. A device for testing seal performance of LCMs with long fracture was developed. The effects of LCM performance on seal integrity were investigated using a plugging device with long fracture. The results showed that the wide particle size distribution (PSD) of LCMs tended to form a strong force chain network structure within the sealing zone. Increasing the stiffness and roughness of LCMs resulted in higher breaking pressure. The addition of fiber with high length-diameter ratio could improve the shear strength of the sealing zone and form a strong force chain network structure, and it can reduce fluid loss.

In this paper, a multiple-input multiple-output (MIMO) integrated radar and communication system based on orthogonal frequency division multiplexing (OFDM) signals is proposed. We consider a bistatic scenario. Exploiting superimposed pilots and orthogonal space-time block code (OSTBC) precoding, transmitted power can be effectively used in both information symbol sending and target sensing with little energy waste and performance degradation. The expectation maximization (EM) is employed to estimate unknown symbols and the channel jointly, which can take the place of matched filtering in traditional radar. In the EM algorithm, we propose to calculate the channel expectation by using Gaussian distribution of the symbol estimation, which can make full use of the OSTBC property of sensing spatial diversity with fast maximum likelihood decoding. The autocorrelation response, and the Doppler response of moving targets in slow time are verified by numerical experiments. Simulations also show superimposed pilot is suitable in the integrated radar and communication system, even when targets with large Doppler shift exist.

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.

Cardiac hypertrophy is associated with many forms of heart disease, and identifying important modifier genes involved in the pathogenesis of cardiac hypertrophy could lead to the development of new therapeutic strategies. Tomoregulin-1 is a growth factor that is primarily involved in embryonic development and adult central nervous system (CNS) function, and it is expressed abnormally in a variety of CNS pathologies. Tomoregulin-1 is also expressed in the myocardium. However, the effects of tomoregulin-1 on the heart, particularly on cardiac hypertrophy, remains unknown. The aim of the study is to examine whether and by what mechanism tomoregulin-1 regulates the development of cardiac hypertrophy induced by pressure overload. In this study, we found that tomoregulin-1 was significantly upregulated in two cardiac hypertrophy models: cTnTR92Q transgenic mice and thoracic aorta constriction (TAC)-induced cardiac hypertrophy mice. The transgenic overexpression of tomoregulin-1 increased the survival rate, improved the cardiac geometry and functional parameters of echocardiography, and decreased the degree of cardiac hypertrophy of the TAC mice, whereas knockdown of tomoregulin-1 expression resulted in an opposite phenotype and exacerbated phenotypes of cardiac hypertrophy induced by TAC. A possible mechanism by which tomoregulin-1 regulates the development of cardiac hypertrophy in TAC-induced cardiac hypertrophy is through inhibiting TGFβ non-canonical (TAK1-JNK) pathways in the myocardium. Tomoregulin-1 plays a protective role in the modulation of adverse cardiac remodeling from pressure overload in mice. Tomoregulin-1 could be a therapeutic target to control the development of cardiac hypertrophy.