A real-world analysis of stereotactic body radiotherapy combined with immunotherapy in advanced or recurrent non-small cell lung cancer (NSCLC): A single-center experience.

Background: We aimed to assess the value of stereotactic body radiotherapy (SBRT) delivered under the situation of controlled or progressed disease during ICI therapy in advanced or recurrent NSCLC. Methods: We retrospectively collected patients with advanced or recurrent NSCLC who received SBRT concurrently with ICI in our institution between January 2017 and December 2021. Patients were divided into two groups, including those for whom SBRT was delivered initially or to the residual tumors during the first- or later-line ICI treatment (Group 1), and those for whom SBRT was given to the progressed tumors irrespective of first- or later-line ICI treatment (Group 2). Results: A total of 144 patients were included. With median follow-up duration of 25.6 (range: 3.6 to 56.2) months, median progression-free survival (PFS) was 13.7 (95 % CI: 10.4 to 17.1) months and median overall survival (OS) was 52.8 [95 % CI: 30.6 to not available (NA)] months. In Group 1 (n = 78), median PFS was 17.9 (95 % CI: 14.5 to 29.8) months while median OS was not reached and 5-year OS rate was 61.2 %. In Group 2 (n = 66), median PFS was 8.0 (95 % CI: 6.0 to 13.1) months and median OS was 30.6 (95 % CI: 21.5 to NA) months. Conclusions: SBRT combined with ICI demonstrated favorable survival for advanced or recurrent NSCLC, delivered in a controlled-disease situation as well as to progressed diseases with salvage-intent. Future prospective studies are warranted to investigate the optimal SBRT dose regimen and appropriate combination strategy to synergize ICI.

Effects of Voltage and Treatment Time of Pulsed Electric Field on Electroporation in Rhizoctonia solani.

The pulsed electric field (PEF) of µs duration can induce electroporation by causing permanent damage to the membrane, leading to cell death. The microbe was treated by a homemade PEF generator instrument. The sterilization effect of PEF on the Rhizoctonia solani was observed by scanning electron microscope (SEM) and transmission electron microscope (TEM), and the leakage of the intracellular contents was measured with a conductometer and an ultraviolet spectrophotometer. The increases in the electrical conductivity and the optical density (OD) value indicated that the cell membrane was damaged, and the intracellular contents overflowed. As a result, according to our experimental conditions, the optimum condition was the high-pulsed electric voltage of 26 kV, and the treatment time was 4 min. It could be concluded that the PEF could damage the cell membrane, and the ratio of electroporation reached 100%, which provides a new method of killing R. solani efficiently.

Utilising standard samples instead of randomly collected food waste in composting: Implementation strategy and feasibility evaluation.

Randomly collected food waste results in inaccurate experimental data with poor reproducibility for composting. This study investigated standard food waste samples as replacements for randomly collected food waste. A response surface methodology was utilised to analyse data from a 28-day compost process optimisation experiment using collected food waste, and the optimal combination of composting parameters was derived. Experiments using different standard food waste samples (high oil and salt, high oil and sugar, balanced diet, and vegetarian) were conducted for 28 days under optimal conditions. The ranking of differences between the standard samples and collected food waste was vegetarian > balanced diet > high oil and sugar > high oil and salt. Statistical analysis indicated t-tests for increased oil and salt samples and collected food waste were not significant, and Cohen's d effect values were minimal. High oil and salt samples can be used as replacements for collected food waste in composting experiments.

Dosiomics and radiomics improve the prediction of post-radiotherapy neutrophil-lymphocyte ratio in locally advanced non-small cell lung cancer.

PURPOSE: To develop and validate a dosiomics and radiomics model based on three-dimensional (3D) dose distribution map and computed tomography (CT) images for the prediction of the post-radiotherapy (post-RT) neutrophil-to-lymphocyte ratio (NLR). METHODS: This work retrospectively collected 242 locally advanced non-small cell lung cancer (LA-NSCLC) patients who were treated with definitive radiotherapy from 2012 to 2016. The NLR collected one month after the completion of RT was defined as the primary outcome. Clinical characteristics and two-dimensional dosimetric factors calculated from the dose-volume histogram (DVH) were included. A total of 4165 dosiomics and radiomics features were extracted from the 3D dose maps and CT images within five different anatomical regions of interest (ROIs), respectively. Then, a three-step feature selection method was proposed to progressively filter features from coarse to fine: (i) model-based ranking according to individual feature's performance, (ii) maximum relevance and minimum redundancy (mRMR), (iii) select from model based on feature importance calculated with an ensemble of several decision trees. The selected feature subsets were utilized to develop the prediction model with GBDT. All patients were divided into a development set and an independent testing set (2:1). Five-fold cross-validation was applied to the development set for both feature selection and model training procedure. Finally, a fusion model combining dosiomics, radiomics and clinical features was constructed to further improve the prediction results. The area under receiver operating characteristic curve (ROC) were used to evaluate the model performance. RESULTS: The clinical-based and DVH-based models showed limited predictive power with AUCs of 0.632 (95% CI: 0.490-0.773) and 0.634 (95% CI: 0.497-0.771), respectively, in the independent testing set. The 9 feature-based dosiomics and 3 feature-based radiomics models showed improved AUCs of 0.738 (95% CI: 0.628-0.849) and 0.689 (95% CI: 0.566-0.813), respectively. The dosiomics & radiomics & clinical fusion model further improved the model's generalization ability with an AUC of 0.765 (95% CI: 0.656-0.874). CONCLUSIONS: Dosiomics and radiomics can benefit the prediction of post-RT NLR of LA-NSCLC patients. This can provide a reference for evaluating radiotherapy-related inflammation.

Boron nitride nanotube-salt-water hybrid:crystalline precipitation.

Molecular dynamics simulation is used to study the transport characteristics of NaCl solution in boron nitride nanotubes (BNNTs). It presents an interesting and well-supported MD study of the crystallization of NaCl from its water solution under the confinement of a 3 nm thick boron nitride nanotube with varied surface charging conditions. The results of the molecular dynamics simulation indicate that NaCl crystallization occurs in charged BNNTs at room temperature when the concentration of NaCl solution reaches about 1.2 M. The reason for this phenomenon is as follows: when the number of ions in the nanotubes is high, the double electric layer that forms at the nanoscale near the charged wall surface, the hydrophobicity of BNNTs, and the interaction among ions cause ions to aggregate in the nanotubes. As the concentration of NaCl solution increases, the concentration of ions when they aggregate in the nanotubes reaches the saturation concentration of the NaCl solution, resulting in the crystalline precipitation phenomenon.

Prediction of cooling effect of constant temperature community bin based on BP neural network.

In order to explore the influence of outdoor microclimate on the cooling effect of constant temperature community bin, the temperature prediction model was predicted. The temperature and microclimate data sets of the community bin were collected in summer from May 2021 to September 2021. The climatic characteristics included cloudy and sunny conditions, and the environmental factors included outdoor temperature, air speed, air relative humidity, and solar radiation intensity. Stepwise regression method was used to test the significance of environmental factors, and the corresponding regression equation was obtained. BP neural network was used to establish temperature prediction models under cloudy and sunny conditions, respectively. The results showed that the coefficient of determination (R2) of the two models was above 0.8, and the environmental factors with significant influence were screened out. The root mean square error (RMSE) between the training value and the actual value established by BP neural network was 0.83 °C, and the determination coefficient (R2) was 0.968. Under sunny conditions, the root mean square error (RMSE) of predicted value and measured value was 0.65 °C, and the determination coefficient (R2) was 0.982. According to the analysis of the sample data, it showed that the BP neural network was more accurate than stepwise regression, and could be used to predict the temperature of community bin, which provided model basis for the practical application of intelligent temperature control community bin in summer.

Design and parameter optimization of community bins based on evaporative cooling.

Aiming at the challenge of bad odors emanating from rotting perishable kitchen waste in summer within the garbage collection chain, the fan-pad system, which is widely used in agricultural facility systems, was applied to the design of community bins. In this regard, a community bin based on a fan-pad operating mechanism was developed. Computational fluid dynamics (CFD) was then used to numerically analyze the cooling effect of the community bin. Under conditions comprising of an outdoor temperature of 35 °C, an installation height of the wet curtain of the cooling system h1, an installation height of the fan h2, and varying distance d between the trash can and the wet curtain, and the average temperature T of 16 temperature measurement points was analyzed. Design-Expert software was used to design the Box-Behnken Design (BBD) experiment, and regression analysis was carried out. Under the optimized parameter combination, the average temperature T of the temperature measurement point was 24.82 °C by simulation. Through field test verification, it was established that the maximum relative error between the temperature of each measuring point and the simulation result was 1.54%, and the average temperature T fluctuated within the range of 0.5 °C of the simulation value.Implications Statement: By creatively integrating the agricultural apparatus with our daily community bin, our research presents great interdisciplinary originality and potential in wide application. Meanwhile, our research also gives a new solution to saving the energy wasted by community dust room based on air conditioner cooling. We hold the believe that our research can arrest great attention of scholars, managers, and people interested in sanitation apparatus. Additionally, our research also provides more theoretical and technical support for the design and application of sanitation collecting apparatus.

Radiosensitivity-Specific Proteomic and Signaling Pathway Network of Non-Small Cell Lung Cancer (NSCLC).

PURPOSE: An unmet clinical need in non-small cell lung cancer (NSCLC) management is the accurate prediction of radiation response in patients receiving radical radiation therapy. We explored the intrinsic radiosensitivity of NSCLC from the proteomic profiles of NSCLC cell lines and paraffin-embedded human samples. METHODS AND MATERIALS: To uncover radiosensitivity-specific proteomic and signaling pathways, we performed quantitative proteomics by data-independent acquisition mass spectrometry assay on 29 human NSCLC cell lines and 13 paraffin-embedded human NSCLC samples. We validated closely interacting radioresistant proteins by western blotting, immunofluorescence, real-time quantitative polymerase chain reaction in NSCLC cell lines, and immunohistochemistry in paraffin-embedded human samples. We validated the functions of 3 key hub proteins by lentivirus transfection, clonogenic survival assay, and flow cytometry. RESULTS: The proteomic profiling of NSCLC showed that the intrinsic radiosensitivity of NSCLC is mainly modulated by signaling pathways of proteoglycans in cancer, focal adhesion, and regulation of the actin cytoskeleton. We identified 71 differentially expressed proteins and validated 8 closely interacting proteins as radioresistant proteins of NSCLC. Moreover, we also validated the functionality of integrin-linked protein kinase, p21-activated kinase 1, and Ras GTPase-activating-like protein IQGAP1 in the radiation response of NSCLC cell lines. Finally, with the NSCLC radiosensitivity-specific proteins, we delineated the atlas network of NSCLC radiosensitivity-related signaling pathways. CONCLUSIONS: Radiosensitivity-specific proteins could guide individualized radiation therapy in clinical practice by predicting the radiation response of patients with NSCLC. Moreover, the NSCLC radiosensitivity-related signaling pathway atlas could guide further exploration of the underlying mechanism.

Detailed Analysis and Radiomic Prediction of First Progression Sites of First-Line Targeted Therapy for EGFR-Mutant Lung Adenocarcinoma Patients With Systemic Metastasis.

BACKGROUND: We aimed to analyze the first progression sites of first-line tyrosine kinase inhibitor (TKI) treatment for EGFR-mutant lung adenocarcinoma patients with systemic metastasis to recognize the potential candidates who might benefit from radiotherapy and establish a radiomic-based model to predict the first progression sites. MATERIALS AND METHODS: We retrospectively collected the clinical information and pre-treatment chest CT images of patients in Shanghai Chest Hospital from 2013 to 2017. All patients were diagnosed with stage IV EGFR-mutant lung adenocarcinoma and received TKI as first-line treatment. The first progression sites and survival were analyzed. The pre-treatment chest non-contrast CT images were utilized to establish a radiomic-based model to predict the first progression sites. RESULTS: We totally collected 233 patients with systemic metastasis, among whom, there were 84 (36.1%) and 149 (63.9%) patients developing first progression in original lesions (OP) and new lesions (NP), respectively. The PFS and OS of patients with OP were longer than those with NP (PFS 11 months vs. 8 months, p = 0.03, OS 50 months vs. 35 months, p = 0.046). For 67.9% of the patients with OF, disease progressed within five sites (oligoprogression). The radiomic-based model could predict the progression sites with an AUC value of 0.736, a specificity of 0.60, and a sensitivity of 0.750 in the independent validation set. CONCLUSION: Among patients with systemic metastasis, there were 36.1% of patients developing OP at first progression who had a better prognosis than those developing NP. Patients with OP may be potential candidates who might benefit from radiotherapy. Radiomics is a useful method to distinguish patients developing OP and could provide some indications for radiotherapy.

The Plasma Levels and Polymorphisms of Vitronectin Predict Radiation Pneumonitis in Patients With Lung Cancer Receiving Thoracic Radiation Therapy.

PURPOSE: Our previous findings have identified vitronectin (VTN) as a potential biomarker for radiation pneumonitis (RP) through proteomics and molecular mechanism studies. In a recent study, we further explored associations of plasma level and single nucleotide polymorphisms of VTN with the risk of RP in patients with lung cancer receiving radiation therapy. METHODS AND MATERIALS: A total of 165 patients with lung cancer were prospectively enrolled with detection of VTN concentration before radiation therapy. VTN reference single nucleotide polymorphisms, rs704 and rs2227721, were genotyped by Taqman probe method. Cox proportional hazard models were performed to identify clinical variables and genotypes associated with the risk of RP on univariate and multivariate analyses, and t tests and analysis of variance were conducted to evaluate the expression level of VTN. RESULTS: The baseline secretion level of VTN in patients with grade ≥3 RP was significantly higher than that in grade <3 RP patients (P < .0001), and elevated levels were observed in patients having the AA genotype compared with GA/GG genotypes of rs704. The VTN rs704 GA/GG and rs2227721 AA/AC genotypes had a significantly lower risk of RP (hazard ratio [HR], 0.448, P = .005; HR, 0.419, P = .008, respectively). In addition, combining cut-off values of mean lung dose (MLD) and VTN plasma level, grade ≥3 RP risk groupings were as follows: high risk: MLD ≥12 Gy and VTN level ≥132 µg/mL (RP rate, 10 of 16 patients, 62.5%); intermediate risk: MLD ≥12 Gy and VTN level <132 µg/mL or MLD <12 Gy and VTN level ≥132 µg/mL (8 of 70 patients, 11.4%); and low risk: MLD <12 Gy and VTN level <132 µg/mL (1 of 79 patients, 1.3%) (P < .0001). CONCLUSIONS: Among patients receiving radiation therapy, relatively high plasma levels of VTN before radiation therapy were associated with the higher incidence of RP, and VTN rs704 and rs2227721 each had a significant effect on predicting RP risk. Combining VTN concentration with MLD appeared to facilitate stratification of patients with lung cancer who received radiation therapy into low-, intermediate-, and high-risk RP groups. This study indicated that VTN may serve as a blood biomarker for susceptibility to RP in patients with lung cancer.

Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio associations with heart and body dose and their effects on patient outcomes in locally advanced non-small cell lung cancer treated with definitive radiotherapy.

BACKGROUND: Inflammation plays a vital role in tumor growth and progression and can be affected by radiotherapy (RT) and chemotherapy. We sought to investigate the prognostic significance of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), and their associations with dosimetric factors in locally advanced non-small cell lung cancer (LA-NSCLC). METHODS: In this retrospective study, subjects consisted of 244 patients who had received definitive RT ± chemotherapy for LA-NSCLC between 2012 and 2016. Absolute lymphocyte count (ALC), NLR and PLR recorded at pretreatment, during RT and post-RT were analyzed. Multivariable analysis (MVA) was performed to correlate clinical factors and inflammatory biomarkers with progression-free survival (PFS) and overall survival (OS) using a Cox regression model. Relationships between NLR or PLR with OS and PFS were evaluated with Kaplan-Meier analysis and compared with log-rank test results. Multiple stepwise linear regression was used to assess the associations between dosimetric factors and NLR or PLR. RESULTS: The median PFS and OS for all patients were 8.6 and 15.8 months, respectively. On MVA for PFS and OS, higher 1-month post-RT start NLR [hazard ratio (HR) 1.049; 95% CI: 1.018-1.080; P=0.001] or higher 1-month post-RT start PLR (HR 1.001; 95% CI: 1.000-1.002; P<0.001) was associated with inferior PFS. Higher 1-month post-RT start NLR (HR 1.040; 95% CI: 1.013-1.069; P=0.004) or PLR (HR 1.001; 95% CI: 1.001-1.002; P<0.001) was also an independent predictor of OS. ALCmin, baseline NLR and PLR were not associated with treatment outcomes. Multiple stepwise linear regression analysis confirmed that baseline NLR (P<0.001), heart V20 (P<0.001), heart V40 (P<0.001), and mean body dose (MBD) were significantly associated with 1-month post-RT start NLR. Also, baseline PLR (P<0.001) and MBD (P<0.001) were significantly associated with 1-month post-RT start PLR. CONCLUSIONS: Higher NLR and PLR during treatment were associated with worse patient outcomes, and heart dose or body dose was correlated with NLR or PLR in advanced NSCLC patients treated with definitive RT.

Analysis of Progression Patterns and Failure Sites of Patients With Metastatic Lung Adenocarcinoma With EGFR Mutations Receiving First-line Treatment of Tyrosine Kinase Inhibitors.

BACKGROUND: Reliable prediction of progression patterns and failure sites for patients with stage IV lung adenocarcinoma is valuable for physicians to deliver personalized tyrosine kinase inhibitor (TKI) treatment. PATIENTS AND METHODS: We retrospectively enrolled 266 patients who had stage IV lung adenocarcinoma and received first-line TKI treatment from 2013 to 2017 in Shanghai Chest Hospital. The clinical characteristics at initial diagnosis, progression patterns, and failure sites were analyzed with the attempt to identify some predictive factors for progression patterns and failure sites. RESULTS: Among all patients, 62.4% developed systemic progression, and 37.6% developed oligoprogression. Both cohorts had a median progression-free survival (PFS) of 9 months. The percentage of patients who developed original and distant failure was 39.1% and 60.9%, respectively. Patients with oligometastasis at initial diagnosis were more prone to develop oligoprogression (odds ratio [OR], 4.370; 95% confidence interval [CI], 1.881-10.151; P = .001), whereas pulmonary metastasis was negatively correlated with oligoprogression (OR, 0.567; 95% CI, 0.330-0.974; P = .04). Both oligometastasis diagnosis (OR, 2.959; 95% CI, 1.347-6.500; P = .007) and the maximum diameter of the primary lung lesion (threshold 3.25 cm: OR, 3.646; 95% CI, 2.041-6.515; P = .0001) were strong predictive factors for original failures. Osseous metastasis at initial diagnosis might be an indication for distant failure (OR, 0.536; 95% CI, 0.316-0.909; P = .021). CONCLUSION: Over one-half of patients with stage IV lung adenocarcinoma receiving first-line TKI treatment developed systemic progression and distant failure. Metastasis patterns at initial diagnosis was the most important predictive factor for progression patterns and failure sites. The maximum diameter of the primary lung lesion and evidence of osseous metastasis were also found to be significant indicative factors for failure sites.

Predictive model of the first failure pattern in patients receiving definitive chemoradiotherapy for inoperable locally advanced non-small cell lung cancer (LA-NSCLC).

PURPOSE: To analyze patterns of failure in patients with LA-NSCLC who received definitive chemoradiotherapy (CRT) and to build a nomogram for predicting the failure patterns in this population of patients. MATERIALS AND METHODS: Clinicopathological data of patients with LA-NSCLC who received definitive chemoradiotherapy and follow-up between 2013 and 2016 in our hospital were collected. The endpoint was the first failure after definitive chemoradiotherapy. With using elastic net regression and 5-fold nested cross-validation, the optimal model with better generalization ability was selected. Based on the selected model and corresponding features, a nomogram prediction model was built. This model was also validated by ROC curves, calibration curve and decision curve analysis (DCA). RESULTS: With a median follow-up of 28 months, 100 patients experienced failure. There were 46 and 54 patients who experience local failure and distant failure, respectively. Predictive model including 9 factors (smoking, pathology, location, EGFR mutation, age, tumor diameter, clinical N stage, consolidation chemotherapy and radiation dose) was finally built with the best performance. The average area under the ROC curve (AUC) with 5-fold nested cross-validation was 0.719, which was better than any factors alone. The calibration curve revealed a satisfactory consistency between the predicted distant failure rates and the actual observations. DCA showed most of the threshold probabilities in this model were with good net benefits. CONCLUSION: Clinicopathological factors could collaboratively predict failure patterns in patients with LA-NSCLC who are receiving definitive chemoradiotherapy. A nomogram was built and validated based on these factors, showing a potential predictive value in clinical practice.

Radiation-induced lung injury patterns and the misdiagnosis after SBRT of lung cancer.

PURPOSE: To analyze radiation-induced lung injury (RIL) after stereotactic body radiotherapy (SBRT) of lung cancer and the subsequent clinical problems. METHODS: 106 lung cancer patients treated with SBRT were included, their computed tomography (CT) scans were reviewed. Late injury pattern was classified by Koening's, radiologist' diagnosis reports for RIL was reviewed. Logistic regression was used to analyze the predictive model of injury pattern, which was also validated by ROC curve. RESULTS: Radiographic late injury within at least 6 months after SBRT was concluded. The majority of late RIL was mass-like pattern, not the modified conventional pattern. 36.8% patients showed acute injury, which trend to occur late lung injury earlier than patients who were not found acute injury (p = 0.0185). 24.5% RIL cases were misdiagnosed to tumor progression by radiologists. Most misdiagnosis occurred among mass-like pattern. Per fraction dose (p < 0.0001), prescription isodose line (p = 0.027) and age (p = 0.089) trend to associate with the occurrence of mass-like injury pattern. Nomogram was established based on these parameters, ROC curve showed that area under the ROC curve (AUC) of the nomogram was 0.767 (95% CI = 0.677-0.857), which was better than any factors along. CONCLUSION: SBRT for lung cancer patients was safe, the majority of late RIL was mass-like pattern. This injury was difficult to be distinguished from tumor progression, which leaded to misdiagnosis of 24.5% patients receiving SBRT. A nomogram based on age, per fraction dose and the prescription isodose line may assist the diagnosis in clinical practice.

Prognostic value and association of Lauren classification with VEGF and VEGFR-2 expression in gastric cancer.

Gastric cancer (GC) is one of the most common malignant tumors in the world. As anti-angiogenic therapy shows efficacy in the treatment of GC, but only works in certain patients, the identification of potential beneficiaries are urgently required in order to apply appropriate treatments. The Lauren classification demonstrates numerous differences in etiology, epidemiology and pathology; however, the association between Lauren classification and pro-angiogenic factors remains unclear. The present study aimed to investigate the clinicopathological factors associated with Lauren classification and the prognostic significance of Lauren classification and vascular endothelial growth factor (VEGF) and VEGF receptor-2 (VEGFR-2) expression in GC. Paraffin-embedded GC tissues and clinical information of 255 patients with GC were collected. The clinicopathological factors associated with Lauren classification were evaluated by Logistic regression analysis. Kaplan-Meier survival and Cox regression analyses were used to examine the prognostic significance of Lauren classification and of VEGF and VEGFR-2 expression in patients with GC. The results demonstrated that there was no association between Lauren classification and VEGF and VEGFR-2 expression. Furthermore, results from survival analysis demonstrated that Lauren classification (P=0.001) and Tumor-Node-Metastasis stage (stage II, P=0.002; stage III, P<0.001) were independent prognostic factors in GC. Following subgroup analysis based on Tumor-Node-Metastasis stage, Lauren classification was demonstrated to be an independent prognostic factor in patients with stage III GC (P=0.010) but not in patients with stage I or II GC. Furthermore, VEGFR-2 overexpression was an independent predictor of survival in intestinal-type GC (P=0.040) but not in diffuse-type GC. Taken together, these results indicate that Lauren classification may serve as an independent prognostic factor for patients with GC. In addition, although the expression of VEGF and VEGFR-2 was not associated with Lauren classification, VEGFR-2 overexpression may be considered as an independent prognostic factor in intestinal-type GC.

The VEGFR-2 protein and the VEGFR-2 rs1870377 A>T genetic polymorphism are prognostic factors for gastric cancer.

OBJECTIVE: Angiogenesis is one of the key processes in the development of malignant tumors. The vascular endothelial growth factor (VEGF) and VEGF receptor-2 (VEGFR-2) signaling pathway regulates branching angiogenesis in cancer. In this study, we analyzed the associations of VEGF/VEGFR-2 proteins and VEGFR-2 genetic variations with the prognosis of gastric cancer (GC). METHOD: We collected the clinical information of patients with GC and extracted genomic DNA from paraffin-embedded tissues. Immunohistochemical methods were used to detect the expression of VEGF and VEGFR-2 in GC tissues. Four single nucleotide polymorphisms of VEGFR-2 were detected by the TaqMan assay. The Kaplan-Meier method and Cox regression model were applied to analyze the associations between clinicopathological characteristics, VEGFR-2 polymorphisms and GC prognosis. RESULTS: A total of 256 cases of GC were included in our study. VEGFR-2 (+) and VEGFR-2 (++/+++) protein expression levels were detected in 83 and 135 cases, respectively. High expression of the VEGFR-2 protein was associated with the poor prognosis of GC (log-rank test P = 0.026). No statistical significance was observed for the association between VEGF and the prognosis of GC. The VEGFR-2 rs1870377 A > T genetic polymorphism was discovered to be associated with the prognosis of GC (AA vs. AT, HR = 1.69, 95% CI = 1.06-2.68, P = 0.027). CONCLUSION: Our study suggested that the high expression of VEGFR-2, as well as the VEGFR-2 rs1870377 A > T genetic polymorphism, may be prognostic markers for GC.

The pivotal role of DNA methylation in the radio-sensitivity of tumor radiotherapy.

Radiotherapy is an important modality for treatment of carcinomas; however, radio-resistance is still a difficult problem. Aberrant epigenetic alterations play an important role in cancer development. Among epigenetic parameters, DNA methylation has arguably attracted the most attention in the radio-resistance process. To determine the role of DNA methylation in radiation resistance, several studies were conducted. We summarized previous studies on the role of DNA methylation in radiotherapy. We observed this significant role of DNA methylation in genes related to DNA repair, cell proliferation, cell cycle process, and re-oxygenation. Furtherly, we also conclude the predictive effect of DNA methylation on tumor radio-sensitivity and the using of DNA methyltransferase inhibitors in clinical practice. DNA methylation plays a pivotal role in the radio-sensitivity of tumor radio-therapy. While hyper-methylation or hypo-methylation of genes is related to gene functions.

Genetic Variants Within MTORC1 Genes Predict Gastric Cancer Prognosis in Chinese Populations.

Objective: Mammalian target of rapamycin complex 1 (mTORC1) plays an important role in maintaining proper cellular functions in gastric cancer (GC). Previous studies demonstrated genetic variants within mTORC1 genes were associated with GC risk. However, no studies reported the associations between genetic variants within mTORC1 genes and GC prognosis. Herein, we firstly assessed the associations of genetic variants of mTORC1 genes with overall survival (OS) of GC in Chinese populations. Methods: We genotyped eight single nucleotide polymorphisms (SNPs) in mTORC1 genes (i.e., rs2536 T>C and rs1883965 G>A for mTOR, rs3160 T>C and rs26865 A>G for MLST8, rs3751934 C>A, rs1062935 T>C, rs3751932 T>C and rs12602885 G>A for RPTOR) by the TaqMan method in 197 Chinese GC patients who had surgical resection in Xinhua Hospital. We conducted Kaplan-Meier survival plots and Cox hazards regression analysis to explore the associations of these SNPs with OS. Results: The single-locus analysis indicated that RPTOR rs1062935 T>C was associated with an increased risk of poor GC prognosis (CC vs. TT/TC: adjusted Hazard ratio (HR) = 1.71, 95% confidence interval (CI) = 1.04-2.82). The combined analysis of all eight SNPs showed that patients with more than three risk genotypes significantly increased risk of death (adjusted HR = 2.44, 95% CI = 1.30-4.58), when compared to those with three or less risk genotypes. Conclusions: Our findings indicated that genetic variants within mTORC1 genes may predict GC prognosis in Chinese populations. The results need to be validated in future studies with larger sample sizes.

Deficiency of hMLH1 and hMSH2 expression is a poor prognostic factor in Early Gastric Cancer (EGC).

Purpose: The aim of the study was to investigate the effect of deficiency of hMLH1 and hMSH2 expression on the prognosis of early gastric cancer (EGC) in Chinese populations. Methods: A total of 160 EGC patients who underwent curative gastrectomy with lymphadenectomy from January 2011 to July 2014 at Xinhua Hospital were evaluated. The expression rates of hMLH1 and hMSH2 were examined using tissues preserved in paraffin blocks by immunohistochemical staining. The clinicopathological characteristics and prognosis of EGC with deficient hMLH1 and hMSH2 were analyzed. Results: On immunohistochemical staining, the loss expression of hMLH1 and hMSH2 were observed in 89 (55.6%) and 45 (28.1%), respectively. The hMLH1 deficiency was associated with the middle third of tumor location (P = 0.041). According to Kaplan-Meier survival analysis and Log-Rank test, the loss expression of hMLH1 and hMSH2 were associated with worse survival than positive hMLH1 (HR = 0.247, 95% CI = 0.078-0.781, P = 0.017) and hMSH2 (HR = 0.174, 95% CI = 0.051-0.601, P = 0.006) in EGC. Conclusion: The main conclusions were as follows: The hMLH1 deficiency was preferred to the middle third of EGC. Lymph node metastasis (LNM) was a prognostic factor of EGC. And the prognosis of EGC patients with deficient mismatch repair (dMMR, mainly including deficient hMLH1 and hMSH2) was obviously worse than proficient mismatch repair (pMMR).

[Detection algorithm of amyloid ß-protein deposition in magnetic resonance image based on pixel feature learning method].

Amyloid ß-protein (Aß) deposition is an important prevention and treatment target for Alzheimer's disease (AD), and early detection of Aß deposition in the brain is the key to early diagnosis of AD. Magnetic resonance imaging (MRI) is the perfect imaging technology for the clinical diagnosis of AD, but it cannot display the plaque deposition directly. In this paper, based on two feature selection modes-filter and wrapper, chain-like agent genetic algorithm (CAGA), principal component analysis (PCA), support vector machine (SVM) and random forest (RF), we designed six kinds of feature learning classification algorithms to detect the information (distribution) of Aß deposition through magnetic resonance image pixels selection. Firstly, we segmented the brain region from brain MR images. Secondly, we extracted the pixels in the segmented brain region as a feature vector (features) according to rows. Thirdly, we conducted feature learning on the extracted features, and obtained the final optimal feature subset by voting mechanism. Finally, using the final optimal selected features, we could find and mark the corresponding pixels on the MR images to show the information about Aß plaque deposition by elastic mapping. According to the experimental results, the proposed pixel features learning methods in this paper could extract and reflect Aß plaque deposition, and the best classification accuracy could be as high as 80%, thereby showing the effectiveness of the methods. The proposed methods can precisely detect the information of the Aß plaque deposition, thereby being helpful for improving classification accuracy of diagnosis of AD.