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The ability to predict tunnel deformation holds great significance for ensuring the reliability, safety, and sustainability of tunnel structures. However, existing deformation prediction models often simplify or overlook the impact of spatial characteristics on deformation by treating it as a time series prediction issue. This study utilizes monitoring data from the Grand Canyon Tunnel and introduces an effective data-driven method for predicting tunnel deformation based on the spatio-temporal characteristics of the historical deformation of adjacent sections. The proposed model, a combination of graph attention network (GAT) and bidirectional long and short-term memory network (Bi-LSTM), is equipped with robust spatio-temporal predictive capabilities. Additionally, the study explores other possible spatial connections and the scalability of the model. The results indicate that the proposed model outperforms other deep learning models, achieving favorable root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) values of 0.34 mm, 0.23 mm, and 0.94, respectively. The graph structure based on intuitive spatial connections proves more suitable for meeting the challenges of predicting deformation. Integrating GAT-LSTM with transfer learning technology, remains stable performance when extended to other tunnels with limited data.

Abstract Heterotopic brain tissue is rare and has not been reported. Our center made the first report. 4 years and 2 months old Girl presented with a cystic mass in the right adrenal gland 2 weeks after right upper abdominal pain. The operation was successful, and the diagnosis was confirmed by postoperative pathology. 6 months after the procedure, the incision healed well without recurrence. This case report has a detailed diagnosis and treatment process and satisfactory examination results. It can provide a reference for diagnosing and treating clinical HBT and reduce the risk of misdiagnosis and mistreatment.

Abstract Objective Prostate cancer (PC) is a significant disease affecting men’s health worldwide. More than 60% of patients over 65 years old and more than 80% are diagnosed with localized PC. The current choice of treatment modalities for localized PC and whether overtreatment is controversial. Therefore, we wanted to construct a nomogram to predict the risk factors associated with cancer-specific survival (CSS) and overall survival (OS) in elderly patients with localized PC while assessing the survival differences in surgery and radiotherapy for elderly patients with localized PC. Methods Data of patients with localized PC over 65 years were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to determine independent risk factors for CSS and OS. Nomograms predicting CSS and OS were built using multivariate Cox regression models. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to test the potential clinical value of this model. Results A total of 90,434 patients over 65 years and diagnosed with localized PC from 2010 to 2018 were included in the study. All patients were randomly assigned to the training set (n = 63,328) and the validation set (n = 27,106). Univariate and multivariate Cox regression model analysis showed that age, race, marriage, T stage, surgical, radiotherapy, prostate-specific antigen (PSA), and Gleason score (GS) were independent risk factors for predicting CSS in elderly patients with localized PC. Age, race, marriage, surgery, radiotherapy, PSA, and GS were independent risk factors for predicting OS in elderly patients with localized PC. The c-index of the training and validation sets for the predicted CSS is 0.802(95%CI:0.788–0.816) and 0.798(95%CI:0.776–0.820, respectively). The c-index of the training and validation sets for predicting OS is 0.712(95%:0.704–0.720) and 0.724(95%:0.714–0.734). It shows that the nomograms have excellent discriminatory ability. The AUC and the calibration curves also show good accuracy and discriminability. Conclusion We have developed new nomograms to predict CSS and OS in elderly patients with localized PC. After internal validation and external temporal validation with reasonable accuracy, reliability and potential clinical value, the model can be used for clinically assisted decision-making.

Background: Thyroid cancer (TC) is the most common malignant tumor in the endocrine system, is also one of the head and neck tumor. Follicular Thyroid Carcinoma (FTC) plays an important role in the pathological classification of thyroid cancer. This study aimed to develop an innovative predictive tool, a nomogram, for predicting cancer specific survival (CSS) in middle-aged FTC patients. Methods: We collected patient data from the Surveillance, Epidemiology, and End Results (SEER) database. The data from patients between 2004 and 2015 were used as the training set, and the data from patients between 2016 and 2018 were used as the validation set. To identify independent risk factors affecting patient survival, univariate and multivariate Cox regression analyses were performed. Based on this, we developed a nomogram model aimed at predicting CSS in middle-aged patients with FTC. The consistency index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration curve were used to evaluate the accuracy and confidence of the model. Results: A total of 2470 patients were enrolled in this study, in which patients from 2004 to 2015 were randomly assigned to the training cohort (N = 1437) and validation cohort (N = 598), and patients from 2016 to 2018 were assigned to the external validation cohort (N = 435) in terms of time. Univariate and multivariate Cox regression analysis showed that marriage, histological grade and TNM stage were independent risk factors for survival. The C-index for the training cohort was 0.866 (95 % CI: 0.805–0.927), for the validation cohort it was 0.944 (95 % CI: 0.903–0.985), and for the external validation cohort, it reached 0.999 (95 % CI: 0.997–1.001). Calibration curves and AUC suggest that the model has good accuracy. Conclusions: We developed an innovative nomogram to predict CSS in middle-aged patients with FTC. Our model after a rigorous internal validation and external validation process, based on the time proved that the high level of accuracy and reliability. This tool helps healthcare professionals and patients make informed clinical decisions.

Rockburst is a kind of common geological disaster in deep tunnel engineering. It has the characteristics of causing great harm and occurring at random locations and times. These characteristics seriously affect tunnel construction and threaten the physical and mental health and safety of workers. Therefore, it is of great significance to study the tendency of rockburst in the early stage of tunnel survey, design and construction. At present, there is no unified method and selected parameters for rockburst prediction. In view of the large difference of different rockburst criteria and the imbalance of rockburst database categories, this paper presents a two-step rockburst prediction method based on multiple factors and the stacking ensemble algorithm. Considering the influence of rock physical and mechanical parameters, tunnel face conditions and excavation disturbance, multiple rockburst criteria are predicted by integrating multiple machine learning algorithms. A combined prediction model of rockburst criteria is established, and the results of each rockburst criterion index are weighted and combined, with the weight updated using the field rockburst record. The dynamic weight is combined with the cloud model to comprehensively evaluate the regional rockburst risk. Field results from applying the model in the Grand Canyon tunnel show that the rockburst prediction method proposed in this paper has better applicability and higher accuracy than the single rockburst criterion.

Abstract Prostate Cancer (PC) is the most common male nonskin tumour in the world, and most diagnosed patients are over 65 years old. The main treatment for PC includes surgical treatment and nonsurgical treatment. Currently, for nonsurgically treated elderly patients, few studies have evaluated their prognostic factors. Our aim was to construct a nomogram that could predict cancer-specific survival (CSS) in nonsurgically treated elderly PC patients to assess their prognosis-related independent risk factors. Patient information was obtained from the Surveillance, Epidemiology and End Results (SEER) database, and our target population was nonsurgically treated PC patients who were over 65 years old. Independent risk factors were determined using both univariate and multivariate Cox regression models. A nomogram was built using a multivariate Cox regression model. The accuracy and discrimination of the prediction model were tested using the consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve. Decision curve analysis (DCA) was used to examine the potential clinical value of this model. A total of 87,831 elderly PC patients with nonsurgical treatment in 2010–2018 were included in the study and were randomly assigned to the training set (N = 61,595) and the validation set (N = 26,236). Univariate and multivariate Cox regression model analyses showed that age, race, marital status, TNM stage, chemotherapy, radiotherapy modality, PSA and GS were independent risk factors for predicting CSS in nonsurgically treated elderly PC patients. The C-index of the training set and the validation set was 0.894 (95% CI 0.888–0.900) and 0.897 (95% CI 0.887–0.907), respectively, indicating the good discrimination ability of the nomogram. The AUC and the calibration curves also show good accuracy and discriminability. We developed a new nomogram to predict CSS in elderly PC patients with nonsurgical treatment. The model is internally validated with good accuracy and reliability, as well as potential clinical value, and can be used for clinical aid in decision-making.

Due to its inherent advantages, shield tunnelling has become the primary construction method for urban tunnels, such as high-speed railway and metro tunnels. However, there are numerous technical challenges to shield tunnelling in complex geological conditions. Under the disturbance induced by shield tunnelling, sandy pebble soil is highly susceptible to ground loss and disturbance, which may subsequently lead to the risk of surface collapse. In this paper, large-diameter slurry shield tunnelling in sandy pebble soil is the engineering background. A combination of field monitoring and numerical simulation is employed to analyze tunnelling parameters, surface settlement, and deep soil horizontal displacement. The patterns of ground disturbance induced by shield tunnelling in sandy pebble soil are explored. The findings reveal that slurry pressure, shield thrust, and cutterhead torque exhibit a strong correlation during shield tunnelling. In silty clay sections, surface settlement values fluctuate significantly, while in sandy pebble soil, the settlement remains relatively stable. The longitudinal horizontal displacement of deep soil is significantly greater than the transverse horizontal displacement. In order to improve the surface settlement troughs obtained by numerical simulation, a cross-anisotropic constitutive model is used to account for the anisotropy of the soil. A sensitivity analysis of the cross-anisotropy parameter α was performed, revealing that as α increases, the maximum vertical displacement of the ground surface gradually decreases, but the rate of decrease slows down and tends to level off. Conversely, as the cross-anisotropy parameter α decreases, the width of the settlement trough narrows, improving the settlement trough profile.

Abstract Small cell carcinoma of the bladder (SCCB) is a rare urological tumor. The prognosis of SCCB is abysmal. Therefore, this study aimed to construct nomograms that predict overall survival (OS) and cancer-specific survival (CSS) in SCCB patients. Information on patients diagnosed with SCCB during 2004–2018 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models analyzed Independent risk factors affecting patients' OS and CSS. Nomograms predicting the OS and CSS were constructed based on the multivariate Cox regression model results. The calibration curve verified the accuracy and reliability of the nomograms, the concordance index (C-index), and the area under the curve (AUC). Decision curve analysis (DCA) assessed the potential clinical value. 975 patients were included in the training set (N = 687) and the validation set (N = 288). Multivariate COX regression models showed that age, marital status, AJCC stage, T stage, M stage, surgical approach, chemotherapy, tumor size, and lung metastasis were independent risk factors affecting the patients' OS. However, distant lymph node metastasis instead AJCC stage is the independent risk factor affecting the CSS in the patients. We successfully constructed nomograms that predict the OS and CSS for SCCB patients. The C index of the training set and the validation set of the OS were 0.747 (95% CI 0.725–0.769) and 0.765 (95% CI 0.736–0.794), respectively. The C index of the CSS were 0.749 (95% CI 0.710–0.773) and 0.786 (95% CI 0.755–0.817), respectively, indicating that the predictive models of the nomograms have excellent discriminative power. The calibration curve and the AUC also show good accuracy and discrimination of the nomograms. To sum up, We established nomograms to predict the OS and CSS of SCCB patients. The nomograms have undergone internal cross-validation and show good accuracy and reliability. The DCA shows that the nomograms have an excellent clinical value that can help doctors make clinical-assisted decision-making.

Pulmonary fibrosis (PF) is the pathological structure of incurable fibroproliferative lung diseases that are attributed to the repeated lung injury-caused failure of lung alveolar regeneration (LAR). Here, we report that repetitive lung damage results in a progressive accumulation of the transcriptional repressor SLUG in alveolar epithelial type II cells (AEC2s). The abnormal increased SLUG inhibits AEC2s from self-renewal and differentiation into alveolar epithelial type I cells (AEC1s). We found that the elevated SLUG represses the expression of the phosphate transporter SLC34A2 in AEC2s, which reduces intracellular phosphate and represses the phosphorylation of JNK and P38 MAPK, two critical kinases supporting LAR, leading to LAR failure. TRIB3, a stress sensor, interacts with the E3 ligase MDM2 to suppress SLUG degradation in AEC2s by impeding MDM2-catalyzed SLUG ubiquitination. Targeting SLUG degradation by disturbing the TRIB3/MDM2 interaction using a new synthetic staple peptide restores LAR capacity and exhibits potent therapeutic efficacy against experimental PF. Our study reveals a mechanism of the TRIB3–MDM2–SLUG–SLC34A2 axis causing the LAR failure in PF, which confers a potential strategy for treating patients with fibroproliferative lung diseases.

Giant fibroepithelial polyp (FP) of the scrotum in infants is a rare disease. We reported the first case of FP in China. The child was only 9 months and 12 days old and was admitted to the hospital due to rapid growth and rupture of the scrotal mass. The patient underwent scrotal exploration under general anesthesia, and the mass was cystic-solid with clear boundaries. The tumor did not invade the sarcolemma of the scrotum and testicular tissue. The intraoperative pathological frozen section tended to be benign, and the scrotum's tumor and subcutaneous pedicle tissue were removed entirely after 0.5 cm from the boundary of the mass. The operation was successful. The mass was confirmed as FP by postoperative pathology. 6 months after the operation, the incision healed well without recurrence. This case report has a detailed diagnosis and treatment process and adequate examination results. It can provide a reference for diagnosing and treating FP in infants and reduce the risk of misdiagnosis and mistreatment.

In order to solve the problems of poor hole-filling performance and the high seed-breakage rate of conventional rice bud seed precision hole direct seed-metering devices, a side-filled rice precision hole direct seed-metering device was developed, and the mechanism and force analyses for seeding operations were carried out. The key factors affecting seeding quality were determined: rotation speed, seeding angle and seeding height. By coupling the discrete element method (DEM) and multi-rigid body dynamics (MBD), the seed breakage rate and seeding performance at different rotation speeds were analyzed. Single-factor bench testing was used to analyze the effect of a duckbill unit on seeding performance under different factor levels. The three-factor and five-level quadratic regression orthogonal rotation center combination test methods were used to obtain the optimal working parameter combination. The test results showed that when the rotation speed was 47 r/min, the seeding angle was 19°, and the seeding height was 180 mm, the qualified index of seeding was 92.03%, the hole diameter qualified index was 91.62%, and the hole distance variation index was 7.17%. This study provides a reference for the research of mechanical rice sprouting seed-metering devices.

Geosynthetic reinforced and pile-supported (GRPS) provide an economic and effective solution for embankments. To investigate the load-bearing mechanism of the GRPS embankment in loess, experimental and numerical studies under static and dynamic loading are carried out. The characteristics of soil arch effect and tensile membrane effect of GPRS embankment under static and dynamic loading are revealed by analyzing pile–soil stress ratio, tension of geogrid, and stress distribution of pile. The test results show that the pile–soil stress ratio under dynamic loading is reduced by 2.3 compared with static loading. In comparison to static load, the soil arching effect is attenuated under dynamic load, and the stronger the static load soil arching effect, the greater the degree of weakening under dynamic load. In addition, under dynamic loading, the tensioned membrane effect is still effective, but its enhancement is not as pronounced as under static loading. Furthermore, by using the finite element software, the numerical model is developed and validated with the experimental results. The parameter analysis of the load-bearing performance of the GRPS embankment is accomplished using the finite element model as well.

Background: Gastric adenosquamous carcinoma with EBV-positive component of squamous cell carcinoma mixed with gastric carcinoma with lymphoid stroma are extremely unusual variants of gastric carcinoma. We herein reported such a case and summarized five related cases that have been reported previously.Case presentation: A 59-year-old man was admitted to our hospital with upper abdominal discomfort and acid reflux. Gastric endoscopic examination revealed an irregular ulcer in the gastric angle. Biopsy of the lesion revealed adenocarcinoma. The patient underwent laparoscopic distal gastrectomy with lymph node dissection subsequently. Histologically, the tumor showed coexistence of GASC and GCLS. SCC and GCLS were positive for EBER in situ hybridization, while adenocarcinoma component was negative. Accordingly, the present case was diagnosed as GASC with EBV-positive component of SCC mixed with GCLS.Conclusion: GASC with EBV-positive component of SCC mixed with GCLS is extremely rare. Although the pathogenesis of GASC and the role of EBV in the development of an ASC component have not been fully elucidated, this case will help clinicians and pathologists better understand this special subtype of gastric tumor.

Background: Thyroid cancer (TC) accounts for more than 90% of endocrine tumours and is a typical head and neck tumour in adults. The aim of this study was to develop a predictive tool to predict cancer-specific survival (CSS) in middle-aged patients with papillary thyroid carcinoma (PTC). Methods: The patients from 2004 to 2015 were randomly divided into a training cohort (n = 25,342) and a internal validation cohort (n = 10,725). The patients from 2016 to 2018 were treated as an external validation cohort (n = 11353). COX proportional hazard model was used to screen meaningful independent risk factors. These factors were constructed into a nomogram to predict CSS in middle-aged patients with PTC. The performance and accuracy of the nomogram were then evaluated using the concordance index (C-index), calibration curve and the area under the curve (AUC). The clinical value of nomogram was evaluated by decision curve analysis (DCA). Results: Age, gender, marriage, tumour grade, T stage, N stage, M stage, surgery, chemotherapy, and tumour size were independent prognostic factors. The C-indexes of the training, internal validation, and external validation cohorts were 0.906, 0.887, and 0.962, respectively. The AUC and calibration curves show good accuracy. DCA shows that the clinical value of the nomogram is higher than that of Tumour, Node and Metastasis (TNM) staging. Conclusion: We developed a new prediction tool to predict CSS in middle-aged patients with PTC. The model has good performance after internal and external validation, which can be friendly to help doctors and patients predict CSS.

Malignant triton tumor (MTT) is a rare kind of malignant peripheral nerve sheath tumors, histologically characterized by rhabdomyoblastic differentiation. There are limited reports of MTT occurring in the intracranial area. The treatment modality consisting of total surgical resection plus post-operative radiotherapy is generally accepted. However, even with optimal treatment, most patients will die within a few months. We report a 71-year-old man with a history of pituitary adenoma, who underwent surgical treatment and postoperative gamma knife therapy. Magnetic resonance imaging (MRI) of the brain revealed a mass with two distinctive components in the sellar area. Postoperative pathology found that the lesion consisted of a MTT and a relapsed pituitary adenoma. The present case is the first report of MTT that occurred in the sellar area. It is also the first case of intracranial MTT with other concurrent tumors (relapsed pituitary tumors). Meanwhile, this case has a clear history of radiation therapy, suggesting that the occurrence of MTT may be related to radiation.

BackgroundRenal cell carcinoma (RCC) is a common malignant tumor in the elderly, with an increasing trend in recent years. We aimed to construct a nomogram of cancer-specific survival (CSS) and overall survival (OS) in elderly patients with nonmetastatic renal cell carcinoma (nmRCC).MethodsClinicopathological information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program in elderly patients with nmRCC from 2010 to 2015. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression analyses were used to identify independent risk factors for patient outcomes in the training cohort. A nomogram was constructed based on these independent risk factors to predict the 1-, 3-, and 5-year CSS and OS in elderly patients with nmRCC. We used a range of methods to validate the accuracy and reliability of the model, including the calibration curve, consistency index (C-index), and the area under the receiver operating curve (AUC). Decision curve analysis (DCA) was used to test the clinical utility of the model.ResultsA total of 12,116 patients were enrolled in the study. Patients were randomly assigned to the training cohort (N = 8,514) and validation cohort (N = 3,602). In the training cohort, univariate and multivariate Cox regression analysis showed that age, marriage, tumor histological type, histological tumor grade, TN stage, tumor size, and surgery are independent risk factors for prognosis. A nomogram was constructed based on independent risk factors to predict CSS and OS at 1-, 3-, and 5- years in elderly patients with nmRCC. The C-index of the training and validation cohorts in CSS were 0.826 and 0.831; in OS, they were 0.733 and 0.734, respectively. The AUC results of the training and validation cohort were similar to the C-index. The calibration curve indicated that the observed value is highly consistent with the predicted value, meaning the model has good accuracy. DCA results suggest that the clinical significance of the nomogram is better than that of traditional TNM staging.ConclusionsWe built a nomogram prediction model to predict the 1-, 3- and 5-year CSS and OS of elderly nmRCC patients. This model has good accuracy and discrimination and can help doctors and patients make clinical decisions and active monitoring.

Abstract Due to surface emissivity, the retrieval accuracy of hyperspectral infrared temperature and humidity profiles is typically poor in the lower atmosphere. To solve this problem, we use the double channel differences method (DCDM) to retrieve the temperature and humidity profiles of the Infrared Atmospheric Sounding Interferometer (IASI) with different surfaces, zenith angles, and data sources. Results show that DCDM can effectively improve IASI retrieval performance. The root mean square error (RMSE) reductions are large and exhibit no marked change with the zenithal angle. Compared with prior profiles, prior near‐surface temperatures can markedly improve the retrieval performance of temperature profiles. Humidity profile retrieval using both humidity and temperature channels can reduce the RMSE and the dependence on the precision of the prior inputs. The DCDM can markedly reduce errors in temperature and relative humidity retrievals, and the retrievals agree with ERA‐Interim better than IASI L2. With the DCDM, the lower temperature and relative humidity RMSE can be ∼3.5 K/14% (land), ∼3 K/13% (coast), ∼1.4 K/7% (sea). Compared with radiosonde observations and ERA‐Interim, the DCDM can reduce errors in temperature and humidity retrievals, and the improvement in performance is equivalent.

AimTo explore the treatment experience of the duplex kidney.MethodA case of the complete bilateral duplex kidney with severe hydronephrosis and ureterectasis in the upper moiety of the kidney diagnosed in the Department of Urology of Kunming Children's Hospital from 2021 to 2022 was retrospectively analyzed and relevant literature was reviewed.ResultsA 2-month-old baby girl was admitted to the hospital because of hydronephrosis of bilateral kidneys found by prenatal ultrasound for 3 months and fever for 3 days. After being given the relevant examinations, the girl was diagnosed with complete bilateral duplex kidneys with severe hydronephrosis and ureterectasis in the upper moiety, and urinary tract infection. The patient's urinary tract infection was poorly controlled after positive anti-infective therapy, so a bilateral ureterostomy was performed. After the surgery, urinary tract infection was soon cured. A bilateral ureteroureterostomy was performed 13 months later, and the patient recovered after 7 days.ConclusionCutaneous ureterostomy combined with late ureteroureterostomy for children with complete bilateral duplex kidneys with severe hydronephrosis in the upper moiety and ureter are not only beneficial to caregivers’ nursing after the operation, but also have significance for salvaging renal function.

Quantitative estimation of growth patterns is important for diagnosis of lung adenocarcinoma and prediction of prognosis. However, the growth patterns of lung adenocarcinoma tissue are very dependent on the spatial organization of cells. Deep learning for lung tumor histopathological image analysis often uses convolutional neural networks to automatically extract features, ignoring this spatial relationship. In this paper, a novel fully automated framework is proposed for growth pattern evaluation in lung adenocarcinoma. Specifically, the proposed method uses graph convolutional networks to extract cell structural features; that is, cells are extracted and graph structures are constructed based on histopathological image data without graph structure. A deep neural network is then used to extract the global semantic features of histopathological images to complement the cell structural features obtained in the previous step. Finally, the structural features and semantic features are fused to achieve growth pattern prediction. Experimental studies on several datasets validate our design, demonstrating that methods based on the spatial organization of cells are appropriate for the analysis of growth patterns.

Concentric gravity waves (CGWs) in the middle and upper atmosphere show wave-coupling processes between the lower atmosphere and the middle and upper atmosphere. In this research, we analyzed a case of CGWs detected simultaneously by the AIRS (Atmospheric Infrared Sounder) and the VIIRS/DNB (Day/Night Band of the Visible Infrared Imager Radiometer Suite) in the stratosphere and mesosphere. Results showed that gravity waves (GWs) were generated by the collocated Hurricane Bejisa on the island of Mauritius. The AIRS data showed arc-like phase fronts of GWs with horizontal wavelengths of 190 and 150 km at 21:08 coordinated universal time (UTC) on 1 January 2014 and at 10:00 UTC on 2 January 2014, whereas the DNB observed arced GWs with horizontal wavelengths of 60 and 150 km in the same geographic regions at 22:24 UTC. The characteristics of CGW parameters in the stratosphere (~40 km) and the mesosphere (~87 km), such as the vertical wavelength, intrinsic frequency, and intrinsic horizontal phase speed, were first derived together with the background winds from ERA5 reanalysis data and Horizontal Wind Model data through the dispersion relationship of GWs and the wind-filtering theory.

Purpose Microwave ablation combined with concurrent biopsy has been used for lung cancer. Frozen section (FS) diagnosis is an important supplement for the final pathology (FP). Thus, a retrospective study was conducted to evaluate the concordance between FS examination and FP in the computed tomography (CT)-guided biopsy of lung cancer. Materials and methods Patients who underwent percutaneous transthoracic needle lung biopsies and were diagnosed using both intraoperative FS examination and FP were retrospectively enrolled. Concordance between FS findings and FP in the diagnosis of malignant lung cancer and the definitive histology types were recorded. Results Overall, 163 patients were enrolled. The concordance rate in the diagnosis of malignant tumors was 96.3%. The definitive histology types were concordant between FS examinations and FP in 112 patients (68.7%). Lung cancers undefined with FS but diagnosed as adenocarcinoma with FP were the most common type, observed in 18 patients. The concordance in the histology type was lower for those requiring immunohistochemistry for FP diagnoses (47.3 vs. 79.6%, p

Background: Malignant rhabdoid tumor of the kidney (MRTK) is an infrequent malignant tumor in childhood, accounting for approximately 2% of all childhood kidney tumors. Although the development of current treatments, the overall survival (OS) rate of MRTK patients is only 25%. The aim of this research was to explore the prognostic value of genes associated with the mTORC1 signaling pathway in MRTK.Methods: The transcriptome data of MRTK samples were downloaded from the TARGET database. The 200 genes of HALLMARK_MTORC1_SIGNALING were downloaded from the Molecular Signatures Database (MSigDB). Furthermore, we applied gene set variation analysis (GSVA) to screen differentially expressed gene sets between the MRTK and normal samples. The 200 genes were combined with differentially expressed genes (DEGs) identified from differentially expressed gene sets. Then, a gene signature of mTORC1 pathway-related genes (mTRGs) was constructed in MRTK. The molecular mechanism of prognostic factors in MRTK was further analyzed using gene set enrichment analysis (GSEA). The target drugs based on these prognostic factors were explored from The Comparative Toxicogenomics Database (CTD). Moreover, six paired fresh tumor tissues and paraneoplastic tissues from children with MRTK were collected to validate the expressions of P4HA1, MLLT11, AURKA, and GOT1 in clinical samples via real-time fluorescence quantitative PCR and Western blot.Results: A four-gene signature (P4HA1, MLLT11, AURKA, and GOT1) related to the mTORC1 pathway was developed in MRTK, which divided the MRTK patients into high-risk and low-risk groups. The patients with high-risk scores were strongly associated with reduced OS. Receiver operating characteristic (ROC) analysis indicated a good prediction performance of the four biomarker signatures. GSEA revealed that the mTOR signaling pathway was significantly enriched. The risk score was demonstrated to be an independent predictor for MRTK outcome. According to the correlation of tumor stem cell index and prognostic factors, the target drugs were obtained for the treatment of MRTK patients. Furthermore, the expressions of RT-qPCR and Western blot were consistent with RNA-sequencing data such that their expressions were significantly elevated in tumor tissues.Conclusion: A total of four genes (P4HA1, MLLT11, AURKA, and GOT1) were screened as prognostic markers, further providing a new understanding for the treatment of patients with MRTK.

BackgroundDesmoid fibromatosis (DF) is a rare clonal proliferation of fibroblasts and myofibroblasts. It develops in the connective tissues and does not metastasize but may infiltrate adjacent structures. Because of the rarity of these tumors and the unpredictable natural history of the disease, well-defined and precise guidelines of the optimal treatment for DF have not been formulated.Case PresentationHere, we present a giant abdominal DF that invaded the right spermatic cord and iliac vessels. The lesion was excised with external iliac artery dissection; however, the vein was sacrificed. The abdominal wall defect was then repaired with a polypropylene mesh. The lesional cells are positive for β-catenin.ConclusionsIn the past decades, there has been a change in the treatment of DF. The “wait and see” policy has been considered initially in most cases. Surgical intervention remains a valid option for symptomatic lesions. The optimal regimes of the tumor should not take the risk of making the patient more symptomatic than the lesion itself.

ObjectivePapillary renal cell carcinoma (pRCC) is the second most common type of renal cell carcinoma and an important disease affecting older patients. We aimed to establish a nomogram to predict cancer-specific survival (CSS) in elderly patients with pRCC.MethodsPatient information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) project, and we included all elderly patients with pRCC from 2004 to 2018. All patients were randomly divided into a training cohort and a validation cohort. Univariate and multivariate Cox proportional risk regression models were used to identify patient independent risk factors. We constructed a nomogram based on a multivariate Cox regression model to predict CSS for 1-, 3-, and 5- years in elderly patients with pRCC. A series of validation methods were used to validate the accuracy and reliability of the model, including consistency index (C-index), calibration curve, and area under the Subject operating curve (AUC).ResultsA total of 13,105 elderly patients with pRCC were enrolled. Univariate and multivariate Cox regression analysis suggested that age, tumor size, histological grade, TNM stage, surgery, radiotherapy and chemotherapy were independent risk factors for survival. We constructed a nomogram to predict patients' CSS. The training and validation cohort's C-index were 0.853 (95%CI: 0.859–0.847) and 0.855 (95%CI: 0.865–0.845), respectively, suggesting that the model had good discrimination ability. The AUC showed the same results. The calibration curve also indicates that the model has good accuracy.ConclusionsIn this study, we constructed a nomogram to predict the CSS of elderly pRCC patients, which has good accuracy and reliability and can help doctors and patients make clinical decisions.

Oral Submucous Fibrosis (OSMF) is an oral mucosal disease with lamina propria collagen hyperplasia as the main pathological change, which belongs to Oral Potentially Malignant Disorders (OPMDs). Areca nut is identified as a class I carcinogen with complex components. Arecoline is the main component of areca nut which plays an important role in the pathogenesis of OSMF. Through the review of literature, it is shown that arecoline can lead to the change in level of cytokines in oral mucosa, which further leads to the imbalance of collagen metabolism. This article reviews the molecular mechanism research progress of arecoline in promoting the pathogenesis of OSMF in recent years, including Transforming Growth Factor-β (TGF-β) and Reactive Oxygen Species (ROS) associated with increased collagen production, Matrix Metalloproteinase (MMP) and Tissue Inhibitor of Metalloproteinase (TIMP) associated with reduced collagen degradation, hypoxia and microvascular related factors and in order to provide reference for the treatment of the disease at the molecular level.

The obtainment of road condition information during driving is extremely important for a driver. However, drivers usually cannot notice multiple information at the same time, which definitely increases certain safety risks. Considering this problem, this paper designs a road information collection plus alarm system based on artificial intelligence to monitor road information. The underlying core algorithm of this system adopts the YOLO v3 network with the best comprehensive detection performance in the end-to-end network. We use this network's advantage of fast detection speed to optimize on its original basis, and propose to “copy” part of the backbone network to build an auxiliary network, which enhances its feature extraction capability. Further, we apply the attention mechanism to the feature information fusion of the auxiliary network and the backbone network, suppress the invalid information channel, and improve the network processing efficiency. Besides, the training part of the network is optimized, and the mAP (mean Average Precision) is improved by setting the scale that meets the target to be detected. Through the test, the average test accuracy of the optimized network model reaches 84.76%, and the real-time detection speed on the 2080Ti reaches 41FPS. Compared with the previous network, the detection accuracy increases by 5.43% after optimization.

Context Oral submucous fibrosis (OSF) is a chronic and progressive disease. Arecoline, present in betel nuts, has been proposed as a vital aetiological factor. However, the underlying mechanism remains unclear. Objectives This research elucidates the expression of tropomyosin-1 (TPM1) and its regulation mechanism in HaCaT cells treated with arecoline. Materials and methods HaCaT cells were assigned into three groups: (1) Control; (2) Treated with arecoline (0.16 mM) for 48 h (3) Treated with arecoline (0.16 mM) and transfected with small interfering RNA (siRNA) for TPM1 (50 nM) for 48 h. CCK8, cell cycle, and apoptosis phenotypic analyses were performed. PCR and western blot analyses were performed to detect the expression level of TPM1 and examine the related signalling pathway. Results The IC50 of arecoline was approximately 50 μg/mL (0.21 mM). The arecoline dose (0.16 mM) and time (48 h) markedly increased TPM1 expression at the mRNA and protein levels in HaCaT cells. Arecoline suppressed the cell growth, caused cell cycle arrest at the G1 phase, and induced cell apoptosis in HaCaT cells. siRNA-mediated knockdown of TPM1 attenuated the effect of arecoline on cell proliferation, apoptosis, and cell cycle arrest at the G1 phase. Furthermore, blocking of the transforming growth factor (TGF)-β receptor using SB431542 significantly suppressed TPM1 expression in the cells treated with arecoline. Discussion and conclusions Arecoline suppresses HaCaT cell viability by upregulating TPM1 through the TGF-β/Smad signalling pathway. This research provides a scientific basis for further study of arecoline and TPM1 in OSF and can be generalised to broader pharmacological studies. TPM1 may be a promising molecular target for treating OSF.

The tunnel face collapses easily during tunnel construction in weak surrounding rock under high geo-stress. Identifying the instability mechanism of the face and proposing targeted control measures are of great importance to prevent the collapse of the face. Using the setting of the carbonaceous phyllite stratum of the Baima tunnel, a FLAC3D-PFC3D coupled model is used to analyze the influential factors on the stability of the face and optimize the original support scheme. The results show that the instability of the face is rooted in the collapse of the rock above the face, and the bench method with short cycle footage is more conducive to the stability of the face. Compared with single support mode of advanced small pipes, the combined support scheme of long bolts and small pipes can better control the displacement of the surrounding rock and prevent the collapse of the tunnel face. The numerical simulation and field surrounding rock monitoring results verify the rationality of the excavation method, the cycle footage, and the support system. This finding will be of great significance to guide design and construction in weak surrounding rock.

To effectively optimize the mechanical behavior of a traditional anti-slide pile and reduce environmental destruction, a new method for slope reinforcement by a spatial arc crown beam composite supporting structure was proposed. First, a numerical model was validated through lab-scale model test data obtained herein, and then a full-scale numerical model was created for an in-depth understanding of the distribution regularity of displacement along the pile, the soil pressure, the crown beam stiffness, and so on. The results demonstrated that: (1) The spatial arc crown beam is simplified to a two-hinged arch, and the maximum value of the bending moment in the arc crown beam is about one-third of the straight crown beam through theoretical calculation. (2) The spatial arc crown beam redistributes the load sharing among different piles, and the extreme bending moment of other piles varies within 10% along the downhill direction except for the piles at the slope foot. (3) Bending moments are close to zero at the pile end, and the anti-slide pile can be simplified as a vertical beam with one end fixed and the other end hinged. (4) The axial force in the spatial arc crown beam is always presented as pressure, so the crown beam can make full utilization of the compression resistance of concrete. (5) The distribution characteristic of soil pressure in front of the pile at the arch foot is different from that in other positions, and the stable soil at the slope foot provides greater soil resistance for anti-piles. (6) As the crown beam stiffness is above five times the reference value, the axial force of the crown beam tends to be stable, and as the crown beam stiffness increases continually, the maximum value of My is −1013.13 kN·m, and the constraining effect of the crown beam is gradually weakened.

Forced ventilation is typically used in the construction of tunnels since it is an economical method to provide high amounts of fresh air. Air velocity and pollutant concentration near the work face are determined by the ventilation arrangement. In the study, field measurement of air velocity was performed, and computational fluid dynamics (CFD) models were constructed to investigate airflow near the work face and predict the gas distribution in a gas tunnel construction. The effects of the distance between the air duct exit and the work face (L1) were evaluated by analyzing the flow field and pollutant concentration. The evaluation shows that the ventilation efficiency improves if L1 does not exceed 15 m in a road tunnel with full-face excavation. With respect to a road tunnel with benching excavation, the effects of bench length (L2) are analyzed, and the results of the analysis indicate that ventilation efficiency is optimal when L2 = 5 m and L2 = 10 m and the air-duct diameter corresponds to 1.6 m. The CFD results fit the field measurement significantly well, and the current ventilation system in the construction exhibits a relatively high efficiency. The findings of the study aid practitioners in optimizing ventilation efficiency. Keywords: Tunnel construction, Forced ventilation, Ventilation arrangement, Fluid field, Hazardous gases, Numerical simulation

To obtain more accurate dynamics change law for asymmetric involute gear， dynamics model of asymmetric involute gear is established by introducing time-varying stiffness and gear backlash. The time history chart， phase diagram， Poincaré perception map and FFT spectrogram are obtained by Runge-Kutta method， then the dynamics behaviors of gear with time-varying stiffness and changing backlash are analyzed. The research result shows that the average meshing stiffness of asymmetric involute gears is greater than that of symmetrical involute gears， and the asymmetric involute gear has better dynamics performance. And the one-order harmonic component in the varying mesh stiffness has little effect on dynamics performance， but the average mesh stiffness has greater impact. Moreover， the relationship between the average mesh stiffness and dynamics performance are nonlinear. That is， with the increase of the average meshing stiffness， the dynamics characteristics becomes better from worse， but the average meshing stiffness continues to increase and then the dynamic characteristics become inferior， so the optimal value of the average meshing stiffness should be determined according to the actual working conditions. In addition， when the gear backlash adds， the dynamics performance drops， so as to the symmetrical involute gear. The research here provides a great theoretical significance and practical value for expanding the theoretical system of asymmetric involute gear dynamics and improving its transmission performances.

In this paper, we study a class of nonlinear space-time fractional stochastic kinetic equations in Rd with Gaussian noise which is white in time and homogeneous in space. This type of equation constitutes an extension of the nonlinear stochastic heat equation involving fractional derivatives in time and fractional Laplacian in space. We firstly give a necessary condition on the spatial covariance for the existence and uniqueness of the solution. Furthermore, we also study various properties of the solution, such as Hölder regularity, the upper bound of second moment, and the stationarity with respect to the spatial variable in the case of linear additive noise.

This paper aims to solve the problem of high reseeding rates and mis-seeding rates in the rice multi-grain hole direct seeding process. A multi grain cluster air suction type rice hill direct seed metering device was developed, and its seeding mechanism was analyzed. Based on CFD-DEM coupling simulation and bench tests, this study explored and optimized the performance of the seed metering device, and carried out the seeding adaptability test. The simulation results were as follows: when the negative pressure was −5 kPa, the static pressure, dynamic pressure and velocity of the flow field reached the maximum. When the negative pressure was −4 kPa, the qualification index was 89.62%, the reseeding index was 4.36%, and the mis-seeding index was 6.02%. The results of the orthogonal rotation combination test of three factors and five levels showed that when the rotation speed, negative pressure and the length of stirring brush were 20.70 rpm, −4.0 kPa and 10.50 mm respectively, the seed metering performance was the best, the qualification index was 90.85%, the reseeding index was 4.41% and the mis-seeding index was 4.74%. The seed metering device had strong adaptability to the sowing of different rice varieties, and met the agronomic requirements of direct seeding and seeding in rice holes.

Emergency scheduling of public resources on the cloud computing platform network can effectively improve the network emergency rescue capability of the cloud computing platform. To schedule the network common resources, it is necessary to generate the initial population through the Hamming distance constraint and improve the objective function as the fitness function to complete the emergency scheduling of the network common resources. The traditional method, from the perspective of public resource fairness and priority mapping, uses incremental optimization algorithm to realize emergency scheduling of public resources, neglecting the improvement process of the objective function, which leads to unsatisfactory scheduling effect. An emergency scheduling method of cloud computing platform network public resources based on genetic algorithm is proposed. With emergency public resource scheduling time cost and transportation cost minimizing target, initial population by Hamming distance constraints, emergency scheduling model, and the corresponding objective function improvement as the fitness function, the genetic algorithm to individual selection and crossover and mutation probability were optimized and complete the public emergency resources scheduling. Experimental results show that the proposed method can effectively improve the efficiency of emergency resource scheduling, and the reliability of emergency scheduling is better.

Based on the bilinear method, rational lump and mixed lump-solitary wave solutions to an extended (2+1)-dimensional KdV equation are constructed through the different assumptions of the auxiliary function in the trilinear form. It is found that the rational lump decays algebraically in all directions in the space plane and its amplitude possesses one maximum and two minima. One kind of the mixed solution describes the interaction between one lump and one line solitary wave, which exhibits fission and fusion phenomena under the different parameters. The other kind of the mixed solution shows one lump interacting with two paralleled line solitary waves, in which the evolution of the lump gives rise to a two-dimensional rogue wave. This shows that these three interesting phenomena exist in the corresponding physical model.

Background: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a widely used, safe, and accurate technique for obtaining pathological specimens to be used in the diagnosis of diseases involving lung hilar and mediastinal lymph node (LN) enlargement. However, application of the suction technique during EBUS-TBNA remains controversial. In addition, the effectiveness of the slow-pull capillary technique for the diagnosis of pancreatic masses was recently reported. The aim of this study was to compare the diagnostic accuracy of EBUS-TBNA using these two techniques. Methods: The accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and availability of tissue cores of the suction and slow-pull capillary techniques were studied retrospectively in patients who underwent EBUS-TBNA for the diagnosis of diseases involving lung hilar and mediastinal LN enlargement. Results: A total of 97 patients with hilar and mediastinal LN enlargement underwent EBUS-TBNA; 30 patients underwent the suction technique, 56 patients underwent the slow-pull capillary technique, 5 patients underwent both techniques, and 6 patients had failed operations. The accuracy, sensitivity, specificity, NPV, PPV, and the number of tissue cores obtained with the suction and slow-pull capillary techniques were 66.67% versus 85.71% ( p = 0.039), 43.75% versus 85.42% ( p 0.05), 59.09% versus 50% ( p > 0.05), 87.5% versus 97.62% ( p > 0.05), and 19 versus 50 ( p = 0.004), respectively. In both univariate and multivariate analyses, the acquisition of tissue core was significantly associated with the diagnostic accuracy of EBUS-TBNA. Moreover, the slow-pull capillary technique was significantly associated with the acquisition of tissue core in EBUS-TBNA. There were no significant differences between the two groups in the blood contamination of samples. Conclusions: Use of the slow-pull capillary technique in EBUS-TBNA can significantly increase the accuracy related to the diagnosis of diseases involving hilar and mediastinal LN enlargement by improving the acquisition of tissue core. The reviews of this paper are available via the supplemental material section.

Securinega suffruticosa (Pall.) Rehd is an excellent natural secondary shrub in the Shell Islands of Yellow River Delta. The roots of S. suffruticosa have high medicinal value and are used to treat diseases, such as neurasthenia and infant malnutrition. Any organism that is isolated from this species is of immense interest due to its potential novel bioactive compounds. In this research, the distribution and diversity of culturable endophytic fungi in S. suffruticosa were studied, and the endophytic fungi with antimicrobial activity were screened. A total of 420 endophytic fungi isolates were obtained from the S. suffruticosa grown in Shell Islands, from which 20 genera and 35 species were identified through morphological and internal transcribed spacer (ITS) sequence analyses. Chaetomium, Fusarium, Cladosporium, and Ceratobasidium were the dominant genera. The high species richness S (42), Margalef index D' (5.6289), Shannon-Wiener index H' (3.1000), Simpson diversity index Ds (0.9459), PIE index (0.8670), and evenness Pielou index J (0.8719) and a low dominant index λ (0.0541) indicated the high diversity of endophytic fungi in S. suffruticosa, the various species of endophytic fungi with obvious tissue specificity. The inhibition percentages of the 12 species of such endophytic fungi against Colletotrichum siamense were 3.6%-26.3%. C. globosum, Fusarium sp.3, and C. ramotenellum had a high antibacterial activity against Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus. The Minimum Inhibitory Concentration (MIC) and the Minimum Bactericidal Concentration (MBC) were between 0.5 mg/mL and 2 mg/mL. Alkaloid content detection indicated that endophytic fungi had a high alkaloid content, whereas the alkaloid contents of C. globosum and Fusarium sp.3 reached 0.231% and 0.170%, respectively. Members belonging to the endophytic fungal community in the S. suffruticosa of Shell Islands that may be used as antagonists and antibacterial agents for future biotechnology applications were identified for the first time.

The rock load acting on the lining of an underground excavation is influenced by multiple factors, including rock type, rock mass condition, depth, and construction method. This study focuses on quantifying the magnitude and distribution of the radial loads on the lining of a deep shaft constructed in hard rock by the so-called short-step method. The blasting-induced damage zone (BDZ) around the shaft was characterized using ultrasonic testing and incorporated into the convergence-confinement method (CCM) and 3D numerical analyses to assess the impact of BDZ on rock loading against the liner. The results show that excavation blasting of shafts is an important controlling factor for the degradation of the rock mass, while the orientation and magnitude of the principal stress had a minimal influence on the distribution of blast-induced damage. The analysis shows that increasing the depth of blast damage in the walls can increase the loads acting on the lining, and the shear loads acting on the liner could be significant for shafts sunk by the short-step method in an area with anisotropic in situ stresses.

Gliomas are the most common primary malignant brain tumors in adults. Accurate grading is crucial as therapeutic strategies are often disparate for different grades and may influence patient prognosis. This study aims to provide an automated glioma grading platform on the basis of machine learning models. In this paper, we investigate contributions of multi-parameters from multimodal data including imaging parameters or features from the Whole Slide images (WSI) and the proliferation marker Ki-67 for automated brain tumor grading. For each WSI, we extract both visual parameters such as morphology parameters and sub-visual parameters including first-order and second-order features. On the basis of machine learning models, our platform classifies gliomas into grades II, III, and IV. Furthermore, we quantitatively interpret and reveal the important parameters contributing to grading with the Local Interpretable Model-Agnostic Explanations (LIME) algorithm. The quantitative analysis and explanation may assist clinicians to better understand the disease and accordingly to choose optimal treatments for improving clinical outcomes. The performance of our grading model was evaluated with cross-validation, which randomly divided the patients into non-overlapping training and testing sets and repeatedly validated the model on the different testing sets. The primary results indicated that this modular platform approach achieved the highest grading accuracy of 0.90 ± 0.04 with support vector machine (SVM) algorithm, with grading accuracies of 0.91 ± 0.08, 0.90 ± 0.08, and 0.90 ± 0.07 for grade II, III, and IV gliomas, respectively.

Bacterial endophytes with the capacity to degrade petroleum hydrocarbons and promote plant growth may facilitate phytoremediation for the removal of petroleum hydrocarbons from contaminated soils. A hydrocarbon-degrading, biosurfactant-producing, and plant-growth-promoting endophytic bacterium, Pseudomonas aeruginosa L10, was isolated from the roots of a reed, Phragmites australis, in the Yellow River Delta, Shandong, China. P. aeruginosa L10 efficiently degraded C10–C26n-alkanes from diesel oil, as well as common polycyclic aromatic hydrocarbons (PAHs) such as naphthalene, phenanthrene, and pyrene. In addition, P. aeruginosa L10 could produce biosurfactant, which was confirmed by the oil spreading method, and surface tension determination of inocula. Moreover, P. aeruginosa L10 had plant growth-stimulating attributes, including siderophore and indole-3-acetic acid (IAA) release, along with 1-aminocyclopropane-1-carboxylic (ACC) deaminase activity. To explore the mechanisms underlying the phenotypic traits of endophytic P. aeruginosa L10, we sequenced its complete genome. From the genome, we identified genes related to petroleum hydrocarbon degradation, such as putative genes encoding monooxygenase, dioxygenase, alcohol dehydrogenase, and aldehyde dehydrogenase. Genome annotation revealed that P. aeruginosa L10 contained a gene cluster involved in the biosynthesis of rhamnolipids, rhlABRI, which should be responsible for the observed biosurfactant activity. We also identified two clusters of genes involved in the biosynthesis of siderophore (pvcABCD and pchABCDREFG). The genome also harbored tryptophan biosynthetic genes (trpAB, trpDC, trpE, trpF, and trpG) that are responsible for IAA synthesis. Moreover, the genome contained the ACC deaminase gene essential for ACC deaminase activity. This study will facilitate applications of endophytic P. aeruginosa L10 to phytoremediation by advancing the understanding of hydrocarbon degradation, biosurfactant synthesis, and mutualistic interactions between endophytes and host plants.

It is widely accepted that oral squamous cell carcinoma (OSCC) is a major contributor to the incidence and mortality of neck and head cancer. Tropomyosin-1 (TPM1), which is expressed at a low level, has been considered a prominent tumor-suppressing gene in a variety of solid tumors, although the precise mechanism of the TPM1 gene in OSCC progression remains unknown. We found that TPM1 expression levels decreased in OSCC patients and OSCC cell lines. The overall and cancer-specific survival of patients who exhibited low TPM1 levels were inferior to those of patients who had high TPM1 levels. It was also found that OSCC patients who suffered from disease stageⅠ-Ⅱ were more likely to have an up-regulated TPM1 expression level, and OSCC patients with lymph node metastasis had a higher probability of exhibiting reduced TPM1 expression. We show that overexpression of TPM1 can promote cell apoptosis and inhibit migration. Our results suggest that TPM1 can suppress tumors in OSCC, and the TPM1 expression level is related to OSCC patient prognosis.

A nonlinear dynamics model and qualitative analysis are presented to study the key effective factors for coupled axial/torsional vibrations of a drill string, which is described as a simplified, equivalent, flexible shell under axial rotation. Here, after dimensionless processing, the mathematical models are obtained accounting for the coupling of axial and torsional vibrations using the nonlinear dynamics qualitative method, in which excitation loads and boundary conditions of the drill string are simplified to a rotating, flexible shell. The analysis of dynamics responses is performed by means of the Runge-Kutta-Fehlberg method, in which the rules that govern the changing of the torsional and axial excitation are revealed, and suggestions for engineering applications are also given. The simulation analysis shows that when the drill string is in a lower-speed rotation zone, the torsional excitation is the key factor in the coupling vibration, and increasing the torsional stress of the drill string more easily leads to the coupling vibration; however, when the drill string is in a higher-speed rotating zone, the axial excitation is a key factor in the coupling vibration, and the axial stress in a particular interval more easily leads to the coupling vibration of the drill string.