Age-based factors modulating the required thyroxine dose to achieve thyrotropin suppression in intermediate-and high-risk papillary thyroid cancer.

Background: Guidelines widely recommend thyrotropin suppression to reduce the risk of recurrence in intermediate- and high-risk papillary thyroid cancer (PTC) after total thyroidectomy. However, an insufficient or excessive dosage may result in a number of symptoms/complications especially in older patients. Patients and methods: We constructed a retrospective cohort including 551 PTC patient encounters. Using propensity score matching and logistic regression models, we determined the independent risk factors affecting levothyroxine therapy at different ages. Our outcomes included: expected TSH level and an unexpected TSH level, which was based on the initial thyroid-stimulating hormone (TSH) goal< 0.1 mIU/L with usual dosage of L-T4 (1.6 µg/kg/day). Results: From our analysis, more than 70% of patients undergoing total thyroidectomy did not achieve the expected TSH level using an empirical medication regimen, and the effect of the drug was affected by age (odds ratio [OR], 1.063; 95% CI, 1.032-1.094), preoperative TSH level (OR, 0.554; 95% CI, 0.436-0.704) and preoperative fT3 level (OR, 0.820; 95% CI, 0.727-0.925). In patients with age < 55 years old, preoperative TSH level (OR, 0.588; 95% CI, 0.459-0.753), and preoperative fT3 level (OR, 0.859; 95% CI, 0.746-0.990) were two independent protective factors, while, in patients with age ≥ 55 years old, only preoperative TSH level (OR, 0.490; 95% CI, 0.278-0.861) was the independent protective factors to achieve expected TSH level. Conclusion: Our retrospective analysis suggested the following significant risk factors of getting TSH suppression in PTC patients: age (≥55 years), lower preoperative TSH and fT3 levels.

Improved YOLOv7 Network Model for Gangue Selection Robot for Gangue and Foreign Matter Detection in Coal.

Coal production often involves a substantial presence of gangue and foreign matter, which not only impacts the thermal properties of coal and but also leads to damage to transportation equipment. Selection robots for gangue removal have garnered attention in research. However, existing methods suffer from limitations, including slow selection speed and low recognition accuracy. To address these issues, this study proposes an improved method for detecting gangue and foreign matter in coal, utilizing a gangue selection robot with an enhanced YOLOv7 network model. The proposed approach entails the collection of coal, gangue, and foreign matter images using an industrial camera, which are then utilized to create an image dataset. The method involves reducing the number of convolution layers of the backbone, adding a small size detection layer to the head to enhance the small target detection, introducing a contextual transformer networks (COTN) module, employing a distance intersection over union (DIoU) loss border regression loss function to calculate the overlap between predicted and real frames, and incorporating a dual path attention mechanism. These enhancements culminate in the development of a novel YOLOv71 + COTN network model. Subsequently, the YOLOv71 + COTN network model was trained and evaluated using the prepared dataset. Experimental results demonstrated the superior performance of the proposed method compared to the original YOLOv7 network model. Specifically, the method exhibits a 3.97% increase in precision, a 4.4% increase in recall, and a 4.5% increase in mAP0.5. Additionally, the method reduced GPU memory consumption during runtime, enabling fast and accurate detection of gangue and foreign matter.

Hazard source detection of longitudinal tearing of conveyor belt based on deep learning.

Belt tearing is the main safety accident of belt conveyor. The main cause of tearing is the doped bolt and steel in the conveying belt. In this paper, the bolt and steel are identified as the Hazard source of tear. In this paper, bolt and steel are defined as the risk sources of tearing. Effective detection of the source of danger can effectively prevent the occurrence of conveyor belt tearing accidents. Here we use deep learning to detect the hazard source image. We improved on the SSD(Single Shot MultiBox Detector) model. Replace the original backbone network with an improved Shufflenet_V2, and replace the original position loss function with the CIoU loss function. Additionally, it compares this new approach to previous methods. The proposed model has surpassed other state-of-art methods with more than 94% accuracy. In addition, when deployed without GPU acceleration, the detection speed can reach 20fps. It can meet the requirements of real-time detection. The experimental results show that the proposed model can realize the online detection of hazard sources, so as to prevent longitudinal tearing of conveyor belt.

A Prognostic Model of Differentiated Thyroid Cancer Based on Up-Regulated Glycolysis-Related Genes.

Objective: This study aims to identify reliable prognostic biomarkers for differentiated thyroid cancer (DTC) based on glycolysis-related genes (GRGs), and to construct a glycolysis-related gene model for predicting the prognosis of DTC patients. Methods: We retrospectively analyzed the transcriptomic profiles and clinical parameters of 838 thyroid cancer patients from 6 public datasets. Single factor Cox proportional risk regression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) were applied to screen genes related to prognosis based on 2528 GRGs. Then, an optimal prognostic model was developed as well as evaluated by Kaplan-Meier and ROC curves. In addition, the underlying molecular mechanisms in different risk subgroups were also explored via The Cancer Genome Atlas (TCGA) Pan-Cancer study. Results: The glycolysis risk score (GRS) outperformed conventional clinicopathological features for recurrence-free survival prediction. The GRS model identified four candidate genes (ADM, MKI67, CD44 and TYMS), and an accurate predictive model of relapse in DTC patients was established that was highly correlated with prognosis (AUC of 0.767). In vitro assays revealed that high expression of those genes increased DTC cancer cell viability and invasion. Functional enrichment analysis indicated that these signature GRGs are involved in remodelling the tumour microenvironment, which has been demonstrated in pan-cancers. Finally, we generated an integrated decision tree and nomogram based on the GRS model and clinicopathological features to optimize risk stratification (AUC of the composite model was 0.815). Conclusions: The GRG signature-based predictive model may help clinicians provide a prognosis for DTC patients with a high risk of recurrence after surgery and provide further personalized treatment to decrease the chance of relapse.

Insights into the Association Between QSER1 and M2 Macrophages and Remarkable Malignancy Characteristics in Hepatocellular Carcinoma.

PURPOSE: Glutamine and serine rich 1 (QSER1), as a DNA methylation modulator, play a crucial role in transforming tumor cells. Previous studies have shown that QSER1 plays a role in regulating the progression of various malignancies and that QSER1 dysfunction is connected with precancerous lesions of hepatocellular carcinoma (HCC) as well as HCC prognosis. However, little is known about the detailed contribution of QSER1 in HCC. PATIENTS AND METHODS: Various statistical methods such as Kaplan-Meier method, AUC analysis, GSEA, and immune-infiltration analysis were used to evaluate the relationship between QSER1 expression and clinical features, prognostic factors, and potential functional mechanisms of QSER1. RESULTS: QSER1 expression was negatively correlated with clinicopathological features (clinical stage, pathological grade, TP53 mutation, lymph node metastasis) and clinical outcome (overall survival versus recurrence). Functional enrichment analysis further suggested that QSER1 is involved in multiple pathways related to DNA replication and tumor immunity. TIMER analysis indicated that high QSER1 expression was significantly associated with higher macrophage infiltration and poorer macrophage-related outcomes. In particular, QSER1 was significantly more associated with M2 macrophages than M1 macrophages. CONCLUSION: Overall, elevated QSER1 is a potential prognostic marker for HCC and is associated with immune infiltration in HCC.

Methylation-Driven Gene PLAU as a Potential Prognostic Marker for Differential Thyroid Carcinoma.

Purpose: Aberrant DNA methylation plays a crucial role in the tumorigenesis of differentiated thyroid cancer (DTC); nevertheless, the factors leading to the local and regional recurrence of DTC are not well understood. This study aimed to establish the connection between DNA methylation-driven genes and the recurrence of DTC. Methods: RNA sequencing profiles and DNA methylation profiles of DTC were downloaded from The Cancer Genome Atlas (TCGA) database. Combined application of the methylmix R package and univariate Cox regression analyses were used to screen and distinguish prognosis-related methylation-driven genes. Multivariate Cox regression analyses were utilized to identify the target genes that were closely associated with the recurrence of DTC. Then, correlations between the expression levels of the target genes and the clinicopathological features were verified, as well as their potential biological functions. Results: A total of 168 Methylation-driven genes were differentially expressed in thyroid cancer, among which 10 genes (GSTO2, GSTM5, GSTM1, GPX7, FGF2, LIF, PLAU, BCL10, SHARPIN and TNFRSF1A) were identified as Hub genes. We selected PLAU for further analysis because PLAU was most strongly correlated with DTC recurrence and the DNA methylation levels of PLAU were closely associated with multiple clinicopathological features of DTC. PLAU was significantly upregulated in DTC, and patients with a high expression level of PLAU had a higher risk of recurrence (p < 0.05). Functional predictions suggested that PLAU-related genes were mainly involved in the regulation of immune-related signaling pathways. Moreover, the mRNA level of PLAU was found to be positively correlated with the cell markers of neutrophils and dendritic cells. In addition, we found that two DNA methylation sites (cg06829584, cg19399285) were associated with abnormal expression of PLAU in DTC. Conclusion: The methylation-driven gene PLAU is an independent risk factor for the recurrence of DTC and it functions as an oncogene through the regulation of immune-related signaling pathways, which offers new insight into the molecular mechanisms of thyroid cancer and provides new possibilities for individualized treatment of thyroid cancer patients.

Comprehensive Analysis of Prognostic Alternative Splicing Signature Reveals Recurrence Predictor for Papillary Thyroid Cancer.

BACKGROUND: Alternative splicing (AS) plays a key role in the diversity of proteins and is closely associated with tumorigenicity. The aim of this study was to systemically analyze RNA alternative splicing (AS) and identify its prognostic value for papillary thyroid cancer (PTC). METHODS: AS percent-splice-in (PSI) data of 430 patients with PTC were downloaded from the TCGA SpliceSeq database. We successfully identified recurrence-free survival (RFS)-associated AS events through univariate Cox regression, LASSO regression and multivariate regression and then constructed different types of prognostic prediction models. Gene function enrichment analysis revealed the relevant signaling pathways involved in RFS-related AS events. Simultaneously, a regulatory network diagram of AS and splicing factors (SFs) was established. RESULTS: We identified 1397 RFS-related AS events which could be used as the potential prognostic biomarkers for PTC. Based on these RFS-related AS events, we constructed a ten-AS event prognostic prediction signature that could distinguish high-and low-risk patients and was highly capable of predicting PTC patient prognosis. ROC curve analysis revealed the excellent predictive ability of the ten-AS events model, with an area under the curve (AUC) value of 0.889; the highest prediction intensity for one-year RFS was 0.923, indicating that the model could be used as a prognostic biomarker for PTC. In addition, the nomogram constructed by the risk score of the ten-AS model also showed high predictive efficiency for the prognosis of PTC patients. Finally, the constructed SF-AS network diagram revealed the regulatory role of SFs in PTC. CONCLUSION: Through the limited analysis, AS events could be regarded as reliable prognostic biomarkers for PTC. The splicing correlation network also provided new insight into the potential molecular mechanisms of PTC.

Effects of marital status on survival of medullary thyroid cancer stratified by age.

PURPOSE: Marital status has emerged as an important influence on several cancer outcomes, but its role in medullary thyroid cancer (MTC) remains unclear. This study was to explore the effects of marital status on the prognosis of MTC patients and to determine whether its effects vary by age. PATIENTS AND METHODS: We retrospectively extracted 1344 eligible patients diagnosed with MTC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Based on the marital status, we divided those patients into married and unmarried groups. We compared the difference in overall survival (OS) and cancer-specific survival (CSS) between married and unmarried via the Kaplan-Meier analysis. Univariate and multivariate Cox proportional models were performed to identify the prognostic factors of OS and CSS. RESULTS: There were 1344 MTC eligible patients in a total of which 883 (65.7%) were married and 461 (34.3%) were unmarried. The comparison observed between married and unmarried patients was as follows: male (45.2% vs. 28.0%), age (≥52 years) (55.9% vs. 44.6%), White (86.7% vs. 78.7%), and undergo surgery (97.7% vs. 93.3%). Multivariate analysis revealed unmarried status as a risk factor independently associated with worse OS (HR: 2.15, 95% CI: 1.59-2.92) rate and CSS (HR: 1.70, 95% CI: 1.17-2.47) rate. In a further analysis stratified by age, there was no significant difference in OS and CSS between married and unmarried patients younger than 52 years. For the remaining group with 52 years old and higher, unmarried patients showed significantly higher risk of OS and CSS than married patients at all stages of the pathology except M1 stage. CONCLUSION: Married patients with MTC have a better prognosis than unmarried ones. Age can affect the association between marital status and the survival of MTC, and married elders may benefit more than youngers.

A Prediction Model for Contralateral Central Neck Lymph Node Metastases in Unilateral Papillary Thyroid Cancer.

The health problems caused by the frequent relapse of papillary thyroid carcinoma (PTC) remain a worldwide concern since the morbidity rate of PTC ranks the highest among thyroid cancers. Residues from contralateral central lymph node metastases (con-CLNM) are the key reason for persistence or recurrence of unilateral papillary thyroid carcinoma (uni-PTC); however, the ability to assess the status of con-CLNM in uni-PTC patients is limited. To clarify the risk factors of con-CLNM, a total of 250 patients with uni-PTC who underwent total thyroidectomy and bilateral central lymph node dissection were recruited in this study. We compared the clinical, sonographic, and pathological characteristics of patients with con-CLNM to those without con-CLNM and established a nomogram for con-CLNM in uni-PTC. We found that male sex, without Hashimoto's thyroiditis, present capsular invasion, with ipsilateral lateral lymph node metastases, and the ratio of ipsilateral central lymph node metastases ≥0.16 were independent con-CLNM predictors of uni-PTC (ORs: 2.797, 0.430, 2.538, 2.202, and 26.588; 95% CIs: 1.182-6.617, 0.211-0.876, 1.223-5.267, 1.064-4.557, and 7.596-93.069, respectively). Additionally, a preoperative nomogram for the prediction of con-CLNM based on these risk factors showed good discrimination (C-index 0.881; 95% CI: 0.840-0.923; sensitivity 85.3%; specificity 76.0%) and good agreement via the calibration plot. Our study provided a way to quantitatively and accurately predict whether con-CLNM occurred in patients with uni-PTC, which may guide surgeons to evaluate the nodal status and perform tailored therapeutic central lymph node dissection.

Kinase gene fusions: roles and therapeutic value in progressive and refractory papillary thyroid cancer.

The incidence of papillary thyroid cancer (PTC), the major type of thyroid cancer, is increasing rapidly around the world, and its pathogenesis is still unclear. There is poor prognosis for PTC involved in rapidly progressive tumors and resistance to radioiodine therapy. Kinase gene fusions have been discovered to be present in a wide variety of malignant tumors, and an increasing number of novel types have been detected in PTC, especially progressive tumors. As a tumor-driving event, kinase fusions are constitutively activated or overexpress their kinase function, conferring oncogenic potential, and their frequency is second only to BRAFV600E mutation in PTC. Diverse forms of kinase fusions have been observed and are associated with specific pathological features of PTC (usually at an advanced stage), and clinical trials of therapeutic strategies targeting kinase gene fusions are feasible for radioiodine-resistant PTC. This review summarizes the roles of kinase gene fusions in PTC and the value of clinical therapy of targeting fusions in progressive or refractory PTC, and discusses the future perspectives and challenges related to kinase gene fusions in PTC patients.

Predictive Factors for Level V Lymph Node Metastases in Papillary Thyroid Carcinoma with BRAFV600E Mutation and Clinicopathological Features.

BACKGROUND: Therapeutic lateral neck dissection (LND) is recommended in papillary thyroid carcinoma (PTC) patients with clinically lateral lymph node metastasis (LLNM), whether underwent level V LND remains controversial for lacking of sensitive predicting system. BRAFV600E mutation is associated with aggressive tumor behavior, recurrence, and disease-specific mortality of PTC. However, the relationship between BRAFV600E mutation and level V LNM is unclear. METHODS: Univariate and multivariate analyses were retrospectively conducted on the potential predictive factors of 252 PTC patients who underwent initial treatment of neck lymph node dissection from September 2015 to October 2018 in our institute. BRAFV600E mutation and the clinicopathological characteristics of the two groups were compared. RESULTS: LLNM was presented in 208 (82.5%) patients and level II-V LNM was present in 42.8%, 71.2%, 85.1%, 17.8% patients, respectively. BRAFV600E mutation was observed in 188 (74.6%) patients and was significantly associated with patients' age, lymphocytic thyroiditis, capsule invasion, bilateral central lymph node metastasis (CLNM) and level V LNM in PTC. Univariate analysis revealed that lymphocytic thyroiditis, tumor size, number of CLNM, Level II LNM, Level III LNM, simultaneous Level II+III, simultaneous Level III+IV and simultaneous Level II+III+IV were significantly correlated with Level V LNM. In addition, multivariate analysis revealed that tumor size ≥2.5 cm, number of CLNM≥3, level II metastases and BRAFV600E mutation were independent Level V LNM predictors (odds ratio 3.910, 3.660, 8.410, 0.439; 95% CI 1.737-10.135, 1.054-12.713, 1.233-57.355, 0.280-0.827, respectively). CONCLUSION: In summary, we presented several independent predictive factors for level V LNM in PTC patients. We constructed a risk prediction model consisting of tumor size ≥2.5 cm, number of CLNM≥3 and level II metastases and BRAFV600E mutation that may guide surgeons to evaluate the nodal status in PTC and perform tailored therapeutic LND.

Preoperative Sonographic and Clinicopathological Predictors for Solitary Lateral Neck Node Metastasis in Papillary Thyroid Carcinoma: A Retrospective Study.

BACKGROUND: Cervical lymph node metastasis (LNM) is an independent risk factor for poor prognosis of papillary thyroid carcinoma (PTC), but the scope of PTC lateral neck dissection (LND) is controversial. Solitary lateral lymph node metastasis (SLNM) is a special type of PTC with lateral LNM. Currently, study on the preoperative clinical characteristics of SLNM has been seldomly reported. This study evaluated the preoperative characteristics for predicting the SLNM of PTC. METHODS: We included 391 patients diagnosed with PTC between May 2011 and July 2017. Among those patients, 44 had SLNM and 347 had multiple lateral neck node metastasis (MLNM). The clinicopathologic characteristics and other central lymph node metastasis risk factors were retrospectively analyzed. RESULTS: Univariate analysis revealed that age and tumor size (≤1 cm) were significantly correlated with SLNM. In ROC curve analysis, the optimal cutoff age of preoperative predictors for the prediction of SLNM was 46.5 years (AUC=0.623, 0.536-0.710). Besides, the frequency and mean number of CLNM was significantly less in the SLNM than MLNM group. The oval and round tumor shape and well-defined margin of the tumor were more common in the SLNM group (p =0.001; p=0.024, respectively). In addition, multivariate analysis revealed that age ≥47, capsular invasion, no extrathyroidal extension, with central lymph node metastases and irregular shape were independent SLNM predictors of PTCs (odds ratio 2.386, 0.173, 0.284, 0.239, 0.188; 95% CI 1.07-5.140, 0.058-0.840, 0.066-0.926, 0.091-0.437, 0.167-0.864, respectively). CONCLUSION: This study supported that SLNM is more likely to happen in PTC patients with age ≥47 years, capsular invasion, no extrathyroidal extension, with central lymph node metastases and irregular shape. That denotes, selective single level neck dissection can be considered as an alternative to systemic lateral neck dissection in those patients.