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Abstract Objectives This study aims to retrospectively analyze the clinical features of Stanford type A acute aortic dissection (TAAAD) based on Sun’s modified classification, and to investigate whether the Sun’s modified classification can be used to assess the risk of preoperative rupture. Methods Clinical data was collected between January 2018 and June 2019. Data included patient demographics, history of disease, type of dissection according to the Sun’s modified classification, time of onset, biochemical tests, and preoperative rupture. Results A total of 387 patients with TAAAD who met the inclusion criteria of Sun’s modified classification were included. There were more complex types, with 75, 151 and 140 patients in the type A1C, A2C and A3C groups, respectively. The age of the entire group of patients was 51.46 ± 12.65 years and 283 (73.1%) were male. The time from onset to the emergency room was 25.37 ± 30.78 h. There were a few cases of TAAAD combined with stroke, pericardial effusion, pleural effusion, and lower extremity and organ ischemia in the complex type group. The white blood cell count (WBC), neutrophil count (NEC) and blood amylase differed significantly between the groups. Three independent risk factors for preoperative rupture were identified: neutrophil count, blood potassium ion level, and platelet count. Binary logistic regression analysis showed that the Sun’s modified classification could not be used to assess the risk of preoperative rupture in TAAAD. Conclusion TAAAD was classified as the complex type in most patients. WBC, NEC and blood amylase were significantly different between the groups. NEC and serum potassium ion level were independent risk factors for preoperative rupture of TAAAD, while platelet count was its protective factor. More samples are needed to determine whether Sun’s modified classification can be used to evaluate the risk of preoperative rupture.

The βʹ-Cu4Ti phase is the major strengthening precipitate in Cu–Ti alloys. Previous research indicates that destabilization of the βʹ-Cu4Ti phase leads to dissolution of Ti atom from precipitates into the Cu matrix. In the present work, Sc was chosen to be alloying elements in Cu–Ti alloys, since stabilization of the βʹ-Cu4Ti phase could be enhanced by formation of βʹ-Cu4(Ti,Sc) phase. Experimental characterization combined with first-principles calculations were used to evaluate the effect of Sc addition. It was found that the bonding between Ti and Sc atoms in the same sublattice of βʹ-Cu4Ti phase increases the diffusion barrier of Ti atoms, and thus dissolution of the βʹ-Cu4Ti phase and further nucleation of the β-Cu4Ti phase were hindered.

Abstract Accurate estimations of carbon (C), nitrogen (N), and phosphorus (P) densities in shrublands are pivotal for assessing terrestrial ecosystem carbon sequestration. Combining in‐situ investigations and machine learning facilitates large‐scale patterns mapping, however, which often overlooks underlying ecological regulations. Here we utilize data from 1,122 survey plots across China's shrublands and develop a novel knowledge‐based deep learning framework that integrates a structural equation model (SEM) to elucidate mechanisms and construct an artificial neural network (ANN) based on these causal relationships. Results show that biomass allocation to different organs follows allometric regulations and that N and P concentrations maintain a degree of stoichiometric homeostasis following biological stoichiometry theory. This insight guides the construction of our ANN, which outperforms both SEM and other prevalent machine learning methods. By leveraging ecological theories to inform model construction, our framework not only enhances prediction accuracy and explainability but also provides a methodological blueprint for ecological research.

Coal is one of the world's most important energy substances. China is rich in coal resources, accounting for more than 90 % of all ascertained fossil energy reserves. The consumption share of coal energy reaches 56.5 % in 2021. Due to the high moisture content of low-rank coal, it is easy to cause equipment blockage in the dry sorting process. This paper considers low-rank coal coming from Inner Mongolia (NM samples) and Yunnan (YN samples). The weight loss performance of the samples was analyzed using thermogravimetric experiments to determine the appropriate temperature for drying experiments. Thin-layer drying experiments were carried out at different temperature conditions. The drying characteristics of low-rank coal were that the higher the drying temperature, the shorter the drying completion time; the smaller the particle size, the shorter the drying completion time. The effective moisture diffusion coefficient was fitted using the Arrhenius equation. The effective water diffusion coefficient of NM samples was 5.07·10–11 - 9.58·10–11 m2/s. The effective water diffusion coefficients of the three different particle sizes of YN samples were 1.89·10–11 - 4.92·10–11 (–1 mm), 1.38·10–10 - 4.13·10–10 (1-3 mm), 5.26·10–10 - 1.49·10–9 (3-6 mm). The activation energy of Inner Mongolia lignite was 10.97 kJ/mol (–1 mm). The activation energies of Yunnan lignite with different particle sizes were 17.97 kJ/mol (–1 mm), 33.52 kJ/mol (1-3 mm), and 38.64 kJ/mol (3-6 mm). The drying process was simulated using empirical and semi-empirical formulas. The optimal model for Inner Mongolia samples was the Two-term diffusion model, and Yunnan samples were the Hii equation was used.

Postoperative tumor recurrence remains a predominant cause of treatment failure. In this study, we developed an in situ injectable hydrogel, termed MPB-NO@DOX + ATRA gel, which was locally formed within the tumor resection cavity. The MPB-NO@DOX + ATRA gel was fabricated by mixing a thrombin solution, a fibrinogen solution containing all-trans retinoic acid (ATRA), and a Mn/NO-based immune nano-activator termed MPB-NO@DOX. ATRA promoted the differentiation of cancer stem cells, inhibited cancer cell migration, and affected the polarization of tumor-associated macrophages. The outer MnO2 shell disintegrated due to its reaction with glutathione and hydrogen peroxide in the cytoplasm to release Mn2+ and produce O2, resulting in the release of doxorubicin (DOX). The released DOX entered the nucleus and destroyed DNA, and the fragmented DNA cooperated with Mn2+ to activate the cGAS-STING pathway and stimulate an anti-tumor immune response. In addition, when MPB-NO@DOX was exposed to 808 nm laser irradiation, the Fe-NO bond was broken to release NO, which downregulated the expression of PD-L1 on the surface of tumor cells and reversed the immunosuppressive tumor microenvironment. In conclusion, the MPB-NO@DOX + ATRA gel exhibited excellent anti-tumor efficacy. The results of this study demonstrated the great potential of in situ injectable hydrogels in preventing postoperative tumor recurrence.

BackgroundAccurately differentiating between ovarian endometrioma and ovarian dermoid cyst is of clinical significance. However, the ultrasound appearance of these two diseases is variable, occasionally causing confusion and overlap with each other. This study aimed to develop a diagnostic classification model based on ultrasound radiomics to intelligently distinguish and diagnose the two diseases.MethodsWe collected ovarian ultrasound images from participants diagnosed as patients with ovarian endometrioma or ovarian dermoid cyst. Feature extraction and selection were performed using the Mann-Whitney U-test, Spearman correlation analysis, and the least absolute shrinkage and selection operator (LASSO) regression. We then input the final features into the machine learning classifiers for model construction. A nomogram was established by combining the radiomic signature and clinical signature.ResultsA total of 407 participants with 407 lesions were included and categorized into the ovarian endometriomas group (n = 200) and the dermoid cyst group (n = 207). In the test cohort, Logistic Regression (LR) achieved the highest area under curve (AUC) value (0.981, 95% CI: 0.963−1.000), the highest accuracy (94.8%), and the highest sensitivity (95.5%), while LightGBM achieved the highest specificity (97.1%). A nomogram incorporating both clinical features and radiomic features achieved the highest level of performance (AUC: 0.987, 95% CI: 0.967−1.000, accuracy: 95.1%, sensitivity: 88.0%, specificity: 100.0%, PPV: 100.0%, NPV: 88.0%, precision: 93.6%). No statistical difference in diagnostic performance was observed between the radiomic model and the nomogram (P > 0.05). The diagnostic indexes of radiomic model were comparable to that of senior radiologists and superior to that of junior radiologist. The diagnostic performance of junior radiologists significantly improved with the assistance of the model.ConclusionThis ultrasound radiomics-based model demonstrated superior diagnostic performance compared to those of junior radiologists and comparable diagnostic performance to those of senior radiologists, and it has the potential to enhance the diagnostic performance of junior radiologists.

The spleen is the largest peripheral immune organ of the organism, accounting for 25% of the total lymphoid tissue of the body. During HS, the spleen is damaged due to the elevated environment, which seriously affects life performance and broilers’ health. This study aimed to investigate the mechanism of chronic HS damage to broiler spleen tissues. The broilers were typically raised until they reached 21 days of age, after which they were arbitrarily allocated into two groups: an HS group and a cntrol group. The HS group was subjected to a temperature of 35 °C for 10 h each day, starting at 21 days of age. At 35 and 42 days of age, spleen and serum samples were obtained from the broilers. The results showed that after HS, a significant decrease in productive performance was observed at 42 days of age (p < 0.01), and the spleen index, and bursa index were significantly decreased (p < 0.01). T-AOC of the organism was significantly decreased (p < 0.05), GSH-PX, SOD, and CAT antioxidant factors were significantly decreased (p < 0.01), and MDA was significantly elevated (p < 0.01). HS also led to a significant increase in cytokines IL-6, TNF-α, and INF-γ and a significant decrease in IL-4 in the spleen. The histopathologic results showed that the spleen’s red-white medulla was poorly demarcated. The cells were sparsely arranged after HS. After HS, the expression of TLRs, MYD88, and NF-κB genes increased significantly. The expression of HSP70 increased significantly, suggesting that HS may induces an inflammatory response in broiler spleens through this signaling pathway, which may cause pathological damage to broiler spleens, leading to a decrease in immune function and progressively aggravating HS-induced damage with the prolongation of HS.

In the continuous scaling-up process of the separating system, a mechanism exists that transforms the behavior of the flow field, resulting in deviations from the original model and conclusions. The paper examined the effects of the scale up of a fluidized bed by CFD. It was observed that increasing the diameter reduces the amplitude of axial density fluctuations. Similarly, increasing the static height increases the amplitude. Moreover, increasing the static bed height enhances the visibility of the cyclic flow structure of gas and solid phases. The flow structure in large bed diameters is disrupted. The impact of changing the bed diameter on bed density is more significant than the static height. As the bed diameter increases, the bubble disturbance decreases and the aggregation phase gradually disappears while the proportion of the emulsified phase keeps increasing. This study will guide and assist in the future application of separated fluidized beds in industry.

Coal beneficiation is the source technology of clean processing and utilization of coal. Dry coal beneficiation is an important way for efficient separation and upgrading of easily sliming coal in arid area. Dry dense medium fluidized bed forms a certain density of gas-solid fluidized bed by updraft-driven heavy medium particles fluidization, thus achieving coal separation according to bed density. The uniformity and stability of bed density, namely the bed fluidization quality, is the key to determine the separation accuracy. Due to the disturbance of airflow, bubbles, moving internals, feeding and other factors, the fluidization behavior of the bed is complex and changeable, and the pressure signal shows non-uniformity, non-linearity and multi-scale characteristics. Based on the characteristics of axial differential transmission and lateral equivalent diffusion of pressure signal in dry dense medium fluidized bed, the fluctuation characteristics of axial differential pressure were studied emphatically, and a quantitative characterization method of fluidization quality was proposed. The results show that: Based on time domain analysis, the probability density distribution of total pressure drop in Geldart A type separation fluidized bed is close to normal distribution. When the bed is in the particulate expansion, due to the uneven distribution of contact force between particles, the probability density shows the right deviation and the peak, deviating from the normal distribution. Through frequency domain analysis, it is found that the dominant frequency of bubbles dominates the whole axial interval of fluidized bed at the later stage of bed expansion. After complete fluidization, the dominant frequency of bubbles only controls the central region of the bed. The dominant frequency of bed concentration signal changes obviously along the bed axial distribution. Combined with the results of time-domain and frequency-domain signal analysis, a fluidization quality characterization model was proposed, where the standard deviation of axial fluctuation is weighted and averaged, and the dominant frequency of sub-bed concentration is taken as the weight value. This model can comprehensively evaluate the uniformity and stability of density distribution of dry dense medium fluidized bed, and provide strong support for the steady-state control and accurate separation of dry dense medium fluidized bed.

Abstract Background This study explored the diagnostic power of preoperative circulating tumor cells (CTCs) for the presence of microvascular invasion (MVI) and the relationship between dynamic changes in postoperative CTCs and prognosis. Methods A total of 137 patients were recruited for the study. Preoperative blood samples were collected from all patients to detect CTCs. The time points for blood collection were before the operation, during the operation, and at 1 week, 1 month, 2 months, 3 months, 6 months, and 1 year after surgery. The predictive power of CTC count for the presence of MVI was analyzed by receiver operating characteristic (ROC) curve analysis. According to recurrence status, 137 patients were divided into three groups: no recurrence, early recurrence, and non-early recurrence groups. Results A threshold CTC count of 5 showed the most significant power for predicting the existence of MVI. In multivariate analysis, the parameters of preoperative CTC count, alpha-fetoprotein (AFP) and tumor diameter were independent predictors of MVI (P 400 μg/L and tumor diameter > 5 cm. The number of intraoperative CTCs in the three groups did not increase compared to that before surgery (P > 0.05). The number of CTCs in the nonrecurrence group and the non-early recurrence group decreased significantly 1 week after surgery compared with the intraoperative values (P

Objective: We sought to evaluate the outcomes of integrated aortic-valve and ascending-aortic replacement (IR) vs. partial replacement (PR) in patients with bicuspid aortic valve (BAV)-related aortopathy.Methods: We compared long-term mortality, reoperation incidence, and the cumulative incidence of stroke, bleeding, significant native valve or prosthetic valve dysfunction, and the New York Heart Association (NYHA) functional classes II-IV between inverse probability-weighted cohorts of patients who underwent IR or PR for BAV-related aortopathy in a single center from 2002 to 2019. Patients were stratified into different aortic diameter groups (“valve type” vs. “aorta type”).Results: Among patients with “valve type,” aortic valve replacement in patients with an aortic diameter > 40 mm was associated with significantly higher 10-year mortality than IR compared with diameter 35–40 mm [17.49 vs. 5.28% at 10 years; hazard ratio (HR), 3.22; 95% CI, 1.52 to 6.85; p = 0.002]. Among patients with “aorta type,” ascending aortic replacement in patients with an aortic diameter 52–60 mm was associated with significantly higher 10-year mortality than IR compared with diameter 45–52 mm (14.49 vs. 1.85% at 10 years; HR, 0.04; 95% CI, 1.06 to 85.24; p = 0.03).Conclusion: The long-term mortality and reoperation benefit that were associated with IR, as compared with PR, minimizing to 40 mm of the aortic diameter among patients with “valve type” and minimizing to 52 mm of the aortic diameter among patients with “aorta type.”Trial Registration: Treatment to Bicuspid Aortic Valve Related Aortopathy (BAVAo Registry): ChiCTR.org.cn no: ChiCTR2000039867.

When the wind power system is working in the maximum wind energy tracking area, or when its mechanical drivetrain system vibrates and the vibration frequency is relatively high, the system cannot suppress the speed vibration of the generator in the drivetrain system by adjusting the pitch angle. In this paper, a generator speed control system based on the three degrees of freedom internal model control (3-DOF-IMC) is established to control the generator speed. Thus, a scheme of using the feedback filter in the 3-DOF-IMC to suppress generator speed vibration caused by drivetrain shaft elasticity and gear clearance in the drivetrain system is proposed. Firstly, the vibration problem and waveform of the two-mass wind power drivetrain systems are discussed, and the generator’s vector control and speed control systems are analyzed. Secondly, the principle of the 3-DOF-IMC is described, and the influence of the three controllers on the speed tracking performance and anti-interference performance of the generator is discussed. The suppression ability of the feedback filter for different forms of disturbance signals is emphasized. Finally, the feedback filter controls the generator speed and eliminates the influence of drivetrain vibration on the generator speed. To verify the superiority of the proposed method, the vibration suppression effect, tracking performance and anti-interference performance of the proposed method are compared with the engineering design method (EDM) and conventional IMC (1-DOF-IMC) method. When the parameter α/β = 0.66, the generator speed amplitude overshoot of the proposed method is the same as the EDM. When α/β = 1, it is only 4% of the amplitude overshoot of the EDM. In addition, the tracking performance and anti-interference performance of the proposed method can be adjusted independently, and it is better than the EDM and the 1-DOF-IMC method.

Network data analysis is a crucial method for mining complicated object interactions. In recent years, random walk and neural-language-model-based network representation learning (NRL) approaches have been widely used for network data analysis. However, these NRL approaches suffer from the following deficiencies: firstly, because the random walk procedure is based on symmetric node similarity and fixed probability distribution, the sampled vertices’ sequences may lose local community structure information; secondly, because the feature extraction capacity of the shallow neural language model is limited, they can only extract the local structural features of networks; and thirdly, these approaches require specially designed mechanisms for different downstream tasks to integrate vertex attributes of various types. We conducted an in-depth investigation to address the aforementioned issues and propose a novel general NRL framework called dynamic structure and vertex attribute fusion network embedding, which firstly defines an asymmetric similarity and h-hop dynamic random walk strategy to guide the random walk process to preserve the network’s local community structure in walked vertex sequences. Next, we train a self-attention-based sequence prediction model on the walked vertex sequences to simultaneously learn the vertices’ local and global structural features. Finally, we introduce an attributes-driven Laplacian space optimization to converge the process of structural feature extraction and attribute feature extraction. The proposed approach is exhaustively evaluated by means of node visualization and classification on multiple benchmark datasets, and achieves superior results compared to baseline approaches.

Vibrations occur in the wind turbine drivetrain due to the drivetrain’s elasticity and gear clearance. Typically, the PID control method is used to suppress elastic vibration, while the method with the disturbance suppression function is used to suppress nonlinear gear clearance vibration. The purpose of this paper is to propose an equivalent PID control method based on the internal model control (IMC) for suppressing vibration caused by the wind turbine drivetrain’s elasticity and gear clearance. The equivalent PID controller can suppresses elastic vibration; the IMC controller can suppresses gear clearance vibration. First, the vibration principle of the two-mass wind turbine drivetrain with clearance is discussed. After analyzing the nonlinear characteristics of the gear clearance, the nonlinear clearance system is decomposed into a linear unit and a nonlinear bounded disturbance unit. To suppress nonlinear bounded disturbances, a disturbance suppression method based on IMC is proposed; simultaneously, an equivalent PID controller based on IMC is designed to resolve the vibration issue caused by the wind turbine drivetrain’s elasticity. The simulation experimental results show that the clearance vibration is suppressed by the original IMC method. The PID controller obtained by the IMC equivalent transformation can suppress the elastic vibration.

Point defects are crucial in determining the quality of germanium crystals. A quantitative understanding of the thermodynamic formation properties of the point defects is necessary for the subsequent control of the defect formation during crystal growth. Here, molecular dynamics simulations were employed to investigate the formation energies, total formation free energies and formation entropies of the point defects in a germanium crystal. As far as we know, this is the first time that the total formation free energies of point defects in a germanium crystal have been reported in the literature. We found that the formation energies increased slightly with temperature. The formation free energies decreased significantly with an increase in temperature due to the increase in entropy. The estimated total formation free energies at the melting temperature are ~1.3 eV for self-interstitial and ~0.75 eV for vacancy, corresponding to a formation entropy of ~15 kB for both types of point defects.

Hepatocellular carcinoma (HCC) has been recognized as the third leading cause of cancer-related deaths worldwide. There is increasing evidence that the abnormal expression of autophagy-related genes plays an important role in the occurrence and development of HCC. Therefore, the study of autophagy-related genes can further elucidate the genetic drivers of cancer and provide valuable therapeutic targets for clinical treatment. In this study, we used 232 autophagy-related genes extracted from the Human Autophagy Database (HADb) and Molecular Signatures Database (MSigDB) to construct 1884 autophagy-related gene pairs. On this basis, we developed a prognostic model based on autophagy-related gene pairs using least absolute shrinkage and selection operator (LASSO) Cox regression to evaluate the prognosis of patients after liver cancer resection. We then used 845 liver cancer samples from three different databases to test the reliability of the risk signature through survival analysis, receiver operating characteristic (ROC) curve analysis, univariate and multivariate analysis. To further explore the underlying biological mechanisms, we conducted an enrichment analysis of autophagy-related genes. Finally, we combined the signature with independent prognostic factors to construct a nomogram. Based on the autophagy-related gene pair (ARGP) signature, we can divide patients into high- or low-risk groups. Survival analysis and ROC curve analysis verified the validity of the signature (AUC: 0.786—0.828). Multivariate Cox regression showed that the risk score can be used as an independent predictor of the clinical outcomes of liver cancer patients. Notably, this model has a more accurate predictive effect than most prognostic models for hepatocellular carcinoma. Moreover, our model is a powerful supplement to the HCC staging indicator, and a nomogram comprising both indicators can provide a better prognostic effect. Based on pairs of multiple autophagy-related genes, we proposed a prognostic model for predicting the overall survival rate of HCC patients after surgery, which is a promising prognostic indicator. This study confirms the importance of autophagy in the occurrence and development of HCC, and also provides potential biomarkers for targeted treatments.

Lead zirconate titanate (PZT) piezoelectric composites used in transducers were fabricated via direct ink writing (DIW) combined with furnace sintering and resin impregnation. A ceramic slurry with a volume fraction of 52 vol% and suitable viscoelasticity was prepared. After post-process, the PZT ceramic specimens showed a nanoscale grain size with a density of 7.63 g/cm3, accounting for 97.8% of the theoretical density. The effects of different printing rod spacing on the electrical properties of composites were evaluated and lucubrated. Finally, an underwater acoustic transducer was assembled by using the PZT piezoelectric composites fabricated by the above method. The electrical signal generated by the underwater acoustic transducer changed autonomously with the acoustic stimulation, which indicated the application mode of 4D printing in functional devices in the future.

Nasal breathing is a dynamic cortical organizer involved in various behaviors and states, such as locomotion, exploration, memory, emotion, introspection. However, the effect of sensory deprivation of nasal respiratory breath (NRD) on behavior remain poorly understood. Herein, general locomotor activity, emotion, learning and memory, social interaction, and mechanical pain were evaluated using a zinc sulfate nasal irrigation induced nasal respiratory sensory deprivation animal model (ZnSO4-induced mouse model). In the open field test, the elevated O-maze test, and forced swim test, NRD mice exhibited depressive and anxiety-like behaviors. In memory-associated tests, NRD mice showed cognitive impairments in the hippocampal-dependent memory (Y maze, object recognition task, and contextual fear conditioning (CFC)) and amygdala-dependent memory (the tone-cued fear conditioning test (TFC)). Surprisingly, NRD mice did not display deficits in the acquisition of conditional fear in both CFC and TFC tests. Still, they showed significant memory retrieval impairment in TFC and enhanced memory retrieval in CFC. At the same time, in the social novelty test using a three-chamber setting, NRD mice showed impaired social and social novelty behavior. Lastly, in the von Frey filaments test, we found that the pain sensitivity of NRD mice was reduced. In conclusion, this NRD mouse model showed a variety of behavioral phenotypic changes, which could offer an important insight into the behavioral impacts of patients with anosmia or those with an impaired olfactory bulb (OB) (e.g., in COVID-19, Alzheimer’s disease, Parkinson’s disease, etc.).

Coal is the dominant energy resource in China. With the Chinese policy of committing to reducing peak carbon dioxide emissions and achieving carbon neutrality, coal separation has recently become a hot topic, especially the fluidized separation of fine particles. In this study, micron-sized particles were introduced to ameliorate the properties of the traditional fluidized bed. The expansion characteristics of the micron-sized-particle-dense medium were explored. A bed expansion prediction model of the micron-sized-particle-dense medium was established, and the prediction error was about 10%, providing a theoretical basis for understanding the distribution characteristics of the bed. This model also helped predict the bed density in the presence of a micron-sized-particle-dense medium, and the prediction accuracy was between 85% and 92%, providing a theoretical basis for selecting and popularizing fluidized beds for industrial separation.

Multicycle repeated utilization of reclaimed asphalt pavement (RAP) is a quite recent development of sustainable pavement materials technology. To investigate ageing rules and recycling possibility of asphalt binders in repeatedly used asphalt mixture, virgin asphalt AH-70 samples were heated by the rolling thin film oven test (RTFOT) at 163°C, respectively, for 40, 85, 180, 240, and 300 minutes to simulate different ageing degrees, and then the aged ones were rejuvenated by adding a self-made rejuvenator. This ageing and recycling process was repeated altogether for 5 cycles to simulate repeated use of RAP binders. In repeated recycling, rejuvenator contents for different cycle numbers or ageing durations were not the same, and the optimum ones were initially estimated by an empirical formula and finally obtained by comparative tests. Empirical rheological tests and the infrared spectral (IR) analysis were done before and after each cycle of recycling. Results indicate that for impact on deterioration of asphalt binders, ageing time is more important than cycle number. Meanwhile, the asphalt after multicycle repeated ageing and recycling can be restored to the empirical rheological indices level of the virgin asphalt and meet specifications requirements.

Developing drugs that can effectively block STAT3 activation may serve as one of the most promising strategy for cancer treatment. Currently, there is no putative STAT3 inhibitor that can be safely and effectively used in clinic. In the present study, we investigated the potential of dihydroartemisinin (DHA) as a putative STAT3 inhibitor and its antitumor activities in head and neck squamous cell carcinoma (HNSCC). The inhibitory effects of DHA on STAT3 activation along with its underlying mechanisms were studied in HNSCC cells. The antitumor effects of DHA against HNSCC cells were explored both in vitro and in vivo. An investigation on cooperative effects of DHA with cisplatin in killing HNSCC cells was also implemented. DHA exhibited remarkable and specific inhibitory effects on STAT3 activation via selectively blocking Jak2/STAT3 signaling. Besides, DHA significantly inhibited HNSCC growth both in vitro and in vivo possibly through induction of apoptosis and attenuation of cell migration. DHA also synergized with cisplatin in tumor inhibition in HNSCC cells. Our findings demonstrate that DHA is a putative STAT3 inhibitor that may represent a new and effective drug for cancer treatment and therapeutic sensitization in HNSCC patients.