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Stromal and immune cells are major components of tumor microenvironment (TME) and affect the growth and development of thyroid carcinoma (THCA). However, data on the exact mechanisms that define the relationship between the TME and THCA remain scant. We calculated stromal and immune cells scores and the proportion of tumor-infiltrating immune cells (TICs) by CIBERSORT and ESTIMATE based on the THCA gene expression data from the Cancer Genome Atlas (TCGA). In addition, we evaluated differentially expressed genes (DEGs) from high- and low-score groups and performed functional enrichment analysis. Furthermore, our data show a significant correlation between plasma complement factor B (CFB) and PTC development and prognosis. Gene Set Enrichment Analysis (GSEA) demonstrated that the CFB was mainly enriched in immune response pathways. The expression of CFB was positively correlated with T cells CD8, Macrophages M1, Plasma cells, T cells CD4 memory activated, T cells follicular helper and T cells regulatory (Tregs), whereas negatively correlated with Eosinophils, Macrophages M0, Macrophages M2, Mast cells resting, T cells CD4 memory resting in the TME. Finally, the expression level of CFB was verified by other cohorts from Gene Expression Omnibus (GEO) database and quantitative Real-Time PCR (qRT-PCR) analyses, which was consistent with the results of bioinformatic analysis. Taken together, our data demonstrated that the CFB could be a prognostic marker for THCA and its expression influences the infiltration of immune cells.

The unsupervised anomaly detection task based on high-dimensional or multidimensional data occupies a very important position in the field of machine learning and industrial applications; especially in the aspect of network security, the anomaly detection of network data is particularly important. The key to anomaly detection is density estimation. Although the methods of dimension reduction and density estimation have made great progress in recent years, most dimension reduction methods are difficult to retain the key information of original data or multidimensional data. Recent studies have shown that the deep autoencoder (DAE) can solve this problem well. In order to improve the performance of unsupervised anomaly detection, we propose an anomaly detection scheme based on a deep autoencoder (DAE) and clustering methods. The deep autoencoder is trained to learn the compressed representation of the input data and then feed it to clustering approach. This scheme makes full use of the advantages of the deep autoencoder (DAE) to generate low-dimensional representation and reconstruction errors for the input high-dimensional or multidimensional data and uses them to reconstruct the input samples. The proposed scheme could eliminate redundant information contained in the data, improve performance of clustering methods in identifying abnormal samples, and reduce the amount of calculation. To verify the effectiveness of the proposed scheme, massive comparison experiments have been conducted with traditional dimension reduction algorithms and clustering methods. The results of experiments demonstrate that, in most cases, the proposed scheme outperforms the traditional dimension reduction algorithms with different clustering methods.

Papillary thyroid microcarcinoma (PTMC) comprises more than 50% of all newly detected cases of papillary thyroid carcinoma (PTC). High-volume lymph node metastasis (involving5 lymph nodes) (hv-LNM) is associated with PTMC recurrence. In half of the clinically node-negative (cN0) PTMC patients, central lymph node metastasis (CLNM) is pathologically present. However, clinical risk factors for high-volume CLNM (hv-CLNM) in cN0 PTMC have not been defined well. Therefore, we aimed to obtain evidence for hv-CLNM risk factors in cN0 PTMC.Data on patients who visited our hospital between January 2020 and December 2021 were collected; a preoperative diagnosis of cN0 and a postoperative pathological confirmation of PTMC were obtained. After filtering by inclusion versus exclusion criteria, the obtained data (N = 2268) were included in the meta-analysis. Relevant studies published as of 10 April 2022, were identified from the Web of Science, PubMed, WANFANG, and CNKI databases. These eligible studies were included in the meta-analysis and the association between clinicopathological factors and hv-CLNM in cN0 PTMC was assessed. SPSS and MetaXL were used for statistical analyses.The meta-analysis included 10 previous studies (11,734 patients) and 2268 patients enroled in our hospital for a total of 14,002 subjects. The results of which suggested that younger age (40, odds ratio [OR] = 3.28, 95% confidence interval [CI] = 2.75-3.92, p .001 or45 odds ratio [OR] = 2.93, 95% CI = 2.31-3.72, p .001), male sex (OR = 2.81, 95% CI = 2.25-3.52, p .001), tumour size5 mm (OR = 1.85, 95% CI = 1.39-2.47, p .001), multifocality (OR = 1.88, 95% CI = 1.56-2.26, p .001), extrathyroidal extension (OR = 2.58, 95% CI = 2.02-3.30, p .001), capsule invasion (OR = 2.02, 95% CI = 1.46-2.78, p .001), microcalcification (OR = 3.25, 95% CI = 2.42-4.36, p .001) and rich blood flow (OR = 1.65, 95% CI = 1.21-2.25, p = .002) were the significant factors related to an elevated hv-CLNM risk in cN0 PTMC patients. Hashimoto thyroiditis (OR = 0.76, 95% CI = 0.55-1.07, p = .114), irregular margin (versus regular margin, OR = 0.96, 95% CI = 0.68-1.33, p = .787) and hypoechoic (versus nonhypoechoic, OR = 1.27, 95% CI = 0.84-1.92, p = .261) showed no significant association with hv-CLNM.Younger age, tumour size5 mm, males, extrathyroidal extension, multifocality, microcalcification, capsular invasion, and rich blood flow were the significant clinicopathological risk factors for hv-CLNM risk in cN0 PTMC patients. These predictors may compensate for the sensitivity of imaging diagnosis in the preoperative period, thus helping in the effective identification of PTMCs with an invasive phenotype.

Background: Necroptosis, a type of programmed cell death, has been implicated in a variety of cancer-related biological processes. However, the roles of necroptosis-related genes in thyroid cancer yet remain unknown.Methods: A necroptosis-related gene signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis. The predictive value of the prognostic signature was validated in an internal cohort. Additionally, the single-sample gene set enrichment analysis (ssGSEA) was used to examine the relationships between necroptosis and immune cells, immunological functions, and immune checkpoints. Finally, the modeled gene expression was validated in clinical tumor and normal tissue samples.Results: In this study, the risk signature of seven necroptosis-related genes was created to predict the prognosis of papillary thyroid cancer (PTC) patients, and all patients were divided into high- and low-risk groups. Patients in the high-risk group fared worse in terms of overall survival than those in the low-risk group. The area under the curve (AUC) of the receiver operator characteristic (ROC) curves proved the predictive capability of created signature. The risk score was found to be an independent risk factor for prognosis in multivariate Cox analysis. The low-risk group showed increased immune cell infiltration and immunological activity, implying that they might respond better to immune checkpoint inhibitor medication. Finally, GEO database and qRT-PCR were used to validate the expression of the seven modeled genes in PTCs, and the results were compatible with TCGA database.Conclusions: The created necroptosis-related risk signature may have an effective predictive in the and prognosis of PTC. The findings of this study could pave the way for further research into the link between necroptosis and tumor immunotherapy.

Background The functional alterations of eRNAs have been reported to be correlated with tumorigenesis. However, the roles of eRNAs in thyroid cancer (THCA) remain still unclear. This study aimed to construct an immune-related eRNA prognostic signature that could effectively predict the survival and prognosis for THCA. Methods The Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify THCA-specific immune-related hub genes and immune-related eRNAs were obtained using Pearson correlation analysis. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression were conducted to construct an immune-related eRNA prognostic signature in training cohort, and the predictive capability was verified in test cohort and entire cohort. Kaplan-Meier analysis, principal component analysis (PCA), receiver operating characteristic (ROC) curves, and nomogram were used to validate the risk signature. Furthermore, CIBERSORT, ESTIMATE and ssGSEA were analyzed to explore the tumor immune microenvironment (TIME) of the risk signature, and the response of potential immunotherapeutic were also discussed. Results A total of 125 immune-related eRNAs were obtained and 16 immune-related eRNAs were significantly correlated with overall survival (OS). A 9-immune-related eRNA prognostic signature was constructed, and the risk score was identified as an independent predictor. High-risk groups were associated with a poorer OS. Immune microenvironment analysis indicated that low risk score was correlated with higher immuneScore, high immune cell infiltration, and the better response of immunotherapy. Additionally, we also detected 9 immune-related eRNA expression levels in sixty-two matched tumorous and non-tumorous tissues using qRT-PCR analysis. Conclusion Our immune-related eRNA risk signature that was an independent prognostic factor was strongly correlated with the immune microenvironment and may be promising for the clinical prediction of prognosis and immunotherapeutic responses in THCA patients.

This study aimed to clarify whether the extent of thyroidectomy (total thyroidectomy vs thyroid lobectomy) influences survival in adults with localized medullary thyroid cancer.Patients with localized medullary thyroid cancer were identified using the Surveillance, Epidemiology, and End Results database (2000-2018). An independent cohort of patients with localized medullary thyroid cancer were retrospectively reviewed from three medical centers in China from 2010 to 2020. The patients were grouped by the extent of surgery (total thyroidectomy vs thyroid lobectomy). Primary end points were overall survival and disease-specific survival.From 1,686 patients with medullary thyroid cancer identified in SEER, 1,122 patients met inclusion for matching, with a median follow-up of 99 months. After propensity score matching, 122 patients underwent a total thyroidectomy and 122 patients underwent a thyroid lobectomy. The 10-year overall survival was 85.2% (77.9%-90.7%) and 83.1% (75.5%-90.7%) in total thyroidectomy group and in thyroid lobectomy group, respectively. The 10-year disease-specific survival was 100% and 96.8% (93.1%-100%) in total thyroidectomy group and in thyroid lobectomy group, respectively. There was no statistically significant difference in overall survival or disease-specific survival in patients with localized medullary thyroid cancer undergoing total thyroidectomy or thyroid lobectomy (hazard ratio = 0.83, 95% confidence interval 0.44-1.57, P = .57 and hazard ratio = 0.49, 95% confidence interval 0.10-2.41, P = .39, respectively). Forty-seven patients with localized medullary thyroid cancer were identified in an independent Chinese cohort (n = 29 in total thyroidectomy group vs n = 18 in thyroid lobectomy group). After a median follow-up of 47 months, there was no mortality observed in either group.This study suggests that the extent of thyroidectomy does not influence survival for patients with early-stage localized medullary thyroid cancer and that thyroid lobectomy might be adequate in this patient population.

With the proposal of “Double-Carbon” goal and the acceleration of energy transformation, a large number of distributed new energy sources such as photovoltaics and wind power, are connected to the power distribution system, the power distribution system has developed into a novel distribution system with the optimization and coordination of energy as its core, thus put forward higher requirements for the safety protection of distribution network. However, when the line of distribution network is repaired or faulty, the power distribution system is very easy to cause islanding effect. Measures of anti-islanding are still implemented based on the grid-connected inverter on the user’s side, and there may be dead zones for anti-islanding protection or other abnormal situations. From the perspective of a novel power distribution system, this paper proposes the method of anti-islanding in novel distribution system with distributed new energy access. The identification of islanding criterion signal, the determination of islanding operation’s area, the generation and execution of islanding processing strategy, the evaluation of islanding processing result and the display of anti-islanding function are elaborated in detail. By analyzing the scenarios of actual application of the anti-islanding processing method, the proposed method can accurately sense the state of islanding of the distribution network and quickly isolate the operating area of islanding through remote control, and the novel power distribution system with distributed new energy access can be prevented from running in islanding, which greatly improves the efficiency of anti-islanding processing for dispatchers, so as to ensure the safe, stable and reliable operation of the distribution network.

Background Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer (TC), accounting for more than 80% of all cases. Ferroptosis is a novel iron-dependent and Reactive oxygen species (ROS) reliant type of cell death which is distinct from the apoptosis, necroptosis and pyroptosis. Considerable studies have demonstrated that ferroptosis is involved in the biological process of various cancers. However, the role of ferroptosis in PTC remains unclear. This study aims at exploring the expression of ferroptosis-related genes (FRG) and their prognostic values in PTC. Methods A ferroptosis-related gene signature was constructed using lasso regression analysis through the PTC datasets of the Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the bioinformatics functions of significantly different genes (SDG) of ferroptosis. Additionally, the correlations of ferroptosis and immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT database. Finally, SDG were test in clinical PTC specimens and normal thyroid tissues. Results LASSO regression model was utilized to establish a novel FRG signature with 10 genes (ANGPTL7, CDKN2A, DPP4, DRD4, ISCU, PGD, SRXN1, TF, TFRC, TXNRD1) to predicts the prognosis of PTC, and the patients were separated into high-risk and low-risk groups by the risk score. The high-risk group had poorer survival than the low-risk group (p Conclusions We identified differently expressed FRG that may involve in PTC. A ferroptosis-related gene signature has significant values in predicting the patients’ prognoses and targeting ferroptosis may be an alternative for PTC’s therapy.

The general availability growth models for large scale complicated repairable system such as electric generating units, power station auxiliaries, and transmission and distribution installations are presented. The calculation formulas for the maintenance coefficient, mathematical expressions for general availability growth models, ways for estimating, and fitting on checking the parameters of the model are introduced. Availability growth models for electric generating units, power station auxiliaries, and transmission and distribution installations are given together with verification examples for availability growth models of 320–1000 MW nuclear power units and 1000 MW thermal power units, 200–1000 MW power station auxiliaries, and 220–500 kV transmission and distribution installations. The verification results for operation availability data show that the maintenance coefficients for electric generating units, power station auxiliaries, transmission and distribution installations conform to the power function, and general availability growth models conform to rules of availability growth tendency of power equipment.

Background Pyroptosis is a form of programmed cell death triggered by inflammasomes. However, the roles of pyroptosis-related genes in thyroid cancer (THCA) remain still unclear. Objective This study aimed to construct a pyroptosis-related signature that could effectively predict THCA prognosis and survival. Methods A LASSO Cox regression analysis was performed to build a prognostic model based on the expression profile of each pyroptosis-related gene. The predictive value of the prognostic model was validated in the internal cohort. Results A pyroptosis-related signature consisting of four genes was constructed to predict THCA prognosis and all patients were classified into high- and low-risk groups. Patients with a high-risk score had a poorer overall survival (OS) than those in the low-risk group. The area under the curve (AUC) of the receiver operator characteristic (ROC) curves assessed and verified the predictive performance of this signature. Multivariate analysis showed the risk score was an independent prognostic factor. Tumor immune cell infiltration and immune status were significantly higher in low-risk groups, which indicated a better response to immune checkpoint inhibitors (ICIs). Of the four pyroptosis-related genes in the prognostic signature, qRT-PCR detected three of them with significantly differential expression in THCA tissues. Conclusion In summary, our pyroptosis-related risk signature may have an effective predictive and prognostic capability in THCA. Our results provide a potential foundation for future studies of the relationship between pyroptosis and the immunotherapy response.

In this study, the antifatigue potential of two sea cucumber peptides (SCP), with low hydrolysis degree (SCP-1) and high hydrolysis degree (SCP-2) derived from Acaudina leucoprocta was investigated. SCP-2 had a lower molecular weight, shorter peptide length, and higher proportion of identified sequences related to branched chain amino acids than SCP-1. Both SCP-1 and SCP-2 significantly improved exercise performance and exerted antifatigue effects in comparison to the negative control group (NC). The mice group received SCP-2 treatment showed better antifatigue effects than that of SCP-1 by prolonging exhaustive swimming time, increasing forelimb grip strength, reducing metabolite accumulation, relieving muscle injury, enhancing muscle glycogen and energy metabolism. Besides, these two treatments significantly modulated the protein relative levels of oxidative stress and mitochondrial function by regulating the NRF2 and AMPK signaling pathways. Conclusively, the study’s findings suggested that SCP could possibly be used as a green functional ingredient to overcome fatigue.

Background: Optimal management for papillary thyroid microcarcinoma (PTMC) remains controversial. The purpose of this study was to explore risk factors predictive of cervical lymph node metastasis in conventional PTMCs. Methods: Conventional PTMC patients (n = 2,404) undergoing surgery between 2010 and 2017 were grouped and analyzed according to the positivity of cervical lymph node. Results: Central lymph node (CLN) metastases and lateral lymph node (LLN) metastases were observed in 915 (38.1%) and 184 (7.7%) cases, respectively. Multivariate analysis found that male (odds ratio [OR] = 1.974, p < 0.001), younger age (OR = 1.601, p < 0.001), tumor size (OR = 1.935, p < 0.001), extrathyroidal extension (ETE) (OR = 1.647, p < 0.001), multifocality (OR = 1.416, p < 0.001), and intrathyroidal spreading (OR = 3.355, p < 0.001) predicted increased CLN metastasis. In particular, younger age, multifocality, and intrathyroidal spreading were significantly associated with a high number of CLN metastases (n ≥ 5). The presence of CLN metastasis was strongly associated with LLN metastasis (OR = 5.426, p < 0.001). Conclusion: Male, younger age, tumor size, ETE, multifocality, and intrathyroidal spreading predict increased CLN metastasis in PTMCs. In patients with suspicious lateral lymphadenopathy, the presence of CLN metastasis is independently associated with LLN metastasis Refereed/Peer-reviewed

In this paper a novel method for reliability prediction and validation of nuclear power units in service is proposed. The equivalent availability factor is used to measure the reliability, and the equivalent availability factor deducting planed outage hours from period hours and maintenance factor are used for the measurement of inherent reliability. By statistical analysis of historical reliability data, the statistical maintenance factor and the undetermined parameter in its numerical model can be determined. The numerical model based on the maintenance factor predicts the equivalent availability factor deducting planed outage hours from period hours, and the planed outage factor can be obtained by using the planned maintenance days. Using these factors, the equivalent availability factor of nuclear power units in the following 3 years can be obtained. Besides, the equivalent availability factor can be predicted by using the historical statistics of planed outage factor and the predicted equivalent availability factor deducting planed outage hours from period hours. The accuracy of the reliability prediction can be evaluated according to the comparison between the predicted and statistical equivalent availability factors. Furthermore, the reliability prediction method is validated using the nuclear power units in North American Electric Reliability Council (NERC) and China. It is found that the relative errors of the predicted equivalent availability factors for nuclear power units of NERC and China are in the range of–2.16% to 5.23% and–2.15% to 3.71%, respectively. The method proposed can effectively predict the reliability index in the following 3 years, thus providing effective reliability management and maintenance optimization methods for nuclear power units.

In this study, lotus leaf flavonoids (LLF) were found to show a notable inhibition activity on α-amylase in a mixed-type manner with IC50 value of (5.58 ± 0.10) mg/mL. The intrinsic fluorescence of α-amylase was quenched by the interaction with LLF through a static quenching mechanism, and LLF-α-amylase complex was spontaneously formed mainly driven by the hydrophobic interaction and hydrogen bonding. Multispectroscopic analyses (synchronous fluorescence, three-dimensional fluorescence, circular dichroism (CD) and fourier transform infrared spectra (FT-IR)) comprehensively demonstrated that the binding of LLF to α-amylase would change the conformation and microenvironment of α-amylase, resulting in inhibiting the enzyme activity. The present study indicated that LLF had potential to be as an ingredient in functional food for the prevention of type-2 diabetes.

The optimized structure strength design and finite element analysis method for very high pressure (VHP) rotors of the 700°C ultra-super-critical (USC) steam turbine are presented. The main parameters of steam and the steam thermal parameters of blade stages of VHP welded rotors as well as the start and shutdown curves of the steam turbine are determined. The structure design feature, the mechanical models and the typical position of stress analysis of the VHP welded rotors are introduced. The steady and transient finite element analysis are implemented for steady condition, start and shutdown process, including steady rated condition, 110% rated speed, 120% rated speed, cold start, warm start, hot start, very hot start, sliding-pressure shutdown, normal shutdown and emergency shutdown, to obtain the temperature and stress distribution as well as the stress ratio of the welded rotor. The strength design criteria and strength analysis results of the welded rotor are given. The results show that the strength design of improved structure of the VHP welded rotor of the 700°C USC steam turbine is safe at the steady condition and during the transient start or shutdown process.

A reliability growth model for pumped-storage power units is presented. Ways for estimating and fitting on checking the model’s parameters are given together with analysis results concerning the reliability growth of 300MW pumped-storage power units. On site operation, reliability data show that the reliability growth model conforms to rules of reliability growth tendency. Analysisresults of reliability growth indicate that measures taken for improving maintenance and operation by the pumpedstorage power companies are effective and that the reliability of the 300MW pumped-storage power units exhibits a rising tendency.

Based on theories of probability and statistics, and taking static stresses, dynamic stresses, endurance strength, safety ratios, vibration frequencies and exciting force frequencies of blades as random variables, a reliability design method for steam turbine blades is presented. The purport and calculation method for blade reliability are expounded. The distribution parameters of random variables are determined after analysis and numerical calculation of test data. The fatigue strength and the vibration design reliability of turbine blades are determined with the aid of a probabilistic design method and by interference models for stress distribution and strength distribution. Some blade reliability design calculation formulas for a dynamic stress design method, a safety ratio design method for fatigue strength, and a vibration reliability design method for the first and second types of tuned blades and a packet of blades on a disk connected closely, are given together with some practical examples. With these methods, the design reliability of steam turbine blades can be guaranteed in the design stage. This research may provide some scientific basis for reliability design of steam turbine blades.

The mathematical model and the methodology of the reliability prediction of generating units are presented. Based on statistical analysis of operation reliability past data for generating units, statistical values of the repair factor and the mathematical model’s parameters of the repair factor are determined. According to plan repair outage days and the mathematical model for the repair factor of some generating unit, equivalent availability factor (EAF) of the generating unit can be predicted in future three years. The reliability prediction examples for sub-critical 300MW, supercritical 600MW and sub-critical 600MW fossil units are given together with reliability prediction results of 550MW hydro units and 984MW, 990MW nuclear units. The relative error’s range for equivalent availability factor prediction values of the generating units is between −1.48% and 2.69% which indicates that reliability prediction precision is higher. By using reliability prediction method, prediction values for the reliability indexes of generating units can be quantitatively calculated, which provides a basis for reliability objective management and optimization repair of generating units.Copyright © 2011 by ASME

A method for the reliability and the availability prediction of main stop valve and control valve systems of steam turbines is presented. The calculation models for the reliability and the availability of series, parallel and series-parallel systems of main stop valves and control valves are introduced. The reliability block diagrams, the availability block diagrams, formulas for the reliability prediction and the availability prediction of systems with 2 main stop valves and 2 control valves, 2 main stop valves and 4 control valves, 2 main stop valves and 6 control valves, 4 main stop valves and 4 control valves are given together with some examples. The mathematical model for the reliability and the availability prediction method of main stop valve and control valve systems of steam turbine is simple and the physical meaning is definite. The reliability and availability of main stop valve and control valve systems can be quantitatively already calculated and improved during the design stage. A basis is thus provided for the reliability and the availability design of main stop valve and control valve systems of steam turbines.Copyright © 2011 by ASME

An on-line calculation method, based on a neural network, for calculating the equivalent stress of steam turbine rotors, is being proposed. The method of expressing the equivalent stress in an steam turbine rotors, in terms of formulas applicable for solid cylindrical models of the same diameter, is being explained; together with the numerical finite element calculation method. A Method and calculation steps of on-line calculation by neural network are presented, accompanied by a practical example of calculating the equivalent stress in the high and intermediate pressure rotor (HP-IP rotor) of a 600MW steam turbine. The application of neural network technique, for obtaining the equivalent stress in on-line monitoring systems of steam turbine rotors, raises the calculation precision of the equivalent stress of steam turbine rotors; providing herewith a better basis for on-line monitoring the equivalent stress and life consumption management of steam turbine rotor’s.

Some life assessment methods for easily damaged power equipment components are being presented, together with methods of Statistical analysis, tests for determining the type of life data distribution, ways of parameter estimation and how to calculate the mean life as well as the reliable life. Classification of failure consequences and functions of a life management system of easily damaged power equipment components are explained. A method for determining the replacement period of easily damaged components is given, accompanied by some practical examples. With this life assessment method and life management system, the replacement period of the components can be determined during their service stage, and therewith a scientific basis provided for maintenance and replacement, and especially for optimized planning purposes.