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Abstract Purpose To evaluate the value of computed tomography (CT)‐based radiomics combined with clinical‐genetic features in predicting brain metastasis in patients with stage III/IV epidermal growth factor receptor (EGFR)‐mutant non‐small‐cell lung cancer (NSCLC). Methods The study included 147 eligible patients treated at our institution between January 2018 and May 2021. Patients were randomly divided into two cohorts for model training (n = 102) and validation (n = 45). Radiomics features were extracted from the chest CT images before treatment, and a radiomics signature was constructed using the Least Absolute Shrinkage and Selection Operator regression. Kaplan–Meier survival analysis was used to describe the differences in brain metastasis‐free survival (BM‐FS) risk. A clinical‐genetic model was developed using Cox regression analysis. Radiomics, genetic, and combined prediction models were constructed, and their predictive performances were evaluated by the concordance index (C‐index). Results Patients with a low radiomics score had significantly longer BM‐FS than those with a high radiomics score in both the training (p

The power grid, as the hub connecting the power supply and consumption sides, plays an important role in achieving carbon neutrality in China. In emerging carbon markets, assessing the investment benefits of power-grid enterprises is essential. Thus, studying the impact of the carbon market on the investment and operation of power- grid enterprises is key to ensuring their efficient operation. Notably, few studies have examined the interaction between the carbon and electricity markets using system dynamics models, highlighting a research gap in this area. This study investigates the impact of the carbon market on the investment of power-grid enterprises using a novel evaluation system based on a system dynamics model that considers carbon-emissions from an established carbon-emission accounting model. First, an index system for benefit evaluation was constructed from six aspects: financing ability, economic benefit, reliability, social responsibility, user satisfaction, and carbon-emissions. A system dynamics model was then developed to reflect the causal feedback relationship between the impact of the carbon market on the investment and operation of power-grid enterprises. The simulation results of a provincial power-grid enterprise analyze comprehensive investment evaluation benefits over a 10-year period and the impact of carbon emissions on the investment and operation of power-grid enterprises. This study provides guidelines for the benign development of power-grid enterprises within the context of the carbon market.

Abstract Background To assess the clinical effects of hybrid surgery, which includes spinal angiography-assisted microsurgery, in the treatment of spinal dural arteriovenous fistulas (SDAVF). Methods We retrospectively reviewed 45 patients who underwent hybrid Spinal dural arteriovenous fistula (SDAVF) resection between September 2019 and June 2022. The hybrid surgery involved intraoperative digital subtraction angiography (DSA) of the spinal vessels to determine the source of the blood-supplying artery, location of the fistula and draining vein, indocyanine green fluorescence (ICG)-assisted microsurgical resection of the fistula, and postoperative DSA to verify therapeutic efficacy. The Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Visual Analog Scale (VAS), Barthel score, modified Rankin Scale (mRS) and modified Aminoff-Logue score (key indicator) were used to assess the clinical effects of SDAVF resection. Results A series of 45 patients with SDAVF were successfully treated with hybrid surgery without fistula recurrence. There were no intraoperative complications related to spinal angiography, and none of the patients died. Postoperatively, two patients experienced clinical deterioration of spinal cord function, which manifested as bilateral lower extremity paralysis and bladder sphincter dysfunction. Postoperatively, improvement in mALS scores was observed in 16 cases (35.6%) within 1–2 days, 12 cases (26.7%) at 1 week, and 7 cases (15.6%) at 6 months. No SDAVF recurrence was detected in the spinal MRA examination 6 months after surgery. When compared with preoperative mALS scores, 35 cases (77.8%) showed significant improvement in symptoms, 8 cases (17.8%), remained unchanged, and 2 cases (4.4%) deteriorated. Compared with the preoperative scores, the postoperative mALS score was significantly decreased [postoperative vs. preoperative: 2(1,3) vs. 3(2,4)], HAMD score [(12.2 ± 5.5) vs. (19.6 ± 6.3)], HAMA score [(15.6 ± 5.5) vs. (20.5 ± 6.5)], and VAS score [3(2,5) vs. 5(4,8)]. Conversely, Barthel scoresshowed significant increase [(74.6 ± 8.7) vs. (67.8 ± 9.2)] (P 0.05). There was a significant increase in “good” neurological outcomes at follow-up compared with preoperative function (62.2% vs. 33.3%) (P = 0.023). Conclusion Hybrid surgery is a safe and effective treatment for patients with SAVF, which is beneficial for improving anxiety, depression, spinal cord, and neurological function, and relieving pain. However, the treatment of patients with SDAVF is a complex, long-term process requiring further multidisciplinary interventions, including clinical care, psychosocial interventions, and neurorehabilitation.

Offshore wind farms are becoming increasingly distant from onshore centralized control centers, and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control. This causes a deterioration in the performance of the primary frequency control and, in some cases, may even result in frequency instability within the power system. Therefore, a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power. The Padé approximation was used to model the time delays, and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays. The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored. In addition, a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics. Finally, a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform. The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.

BackgroundHigh-risk double-expressor diffuse large B-cell lymphoma has an inferior prognosis following standard first-line therapy. After failure of second-line therapy, treatment options are limited if accompanied by localized compressive symptoms. Chimeric Antigen Receptor T cell (CAR-T) therapy preceded by bridging radiotherapy may be an effective emerging therapy.Case presentationWe report a 66-year-old female patient diagnosed with stage IV double-expressor diffuse large B-cell lymphoma. The patient achieved progressive disease after two cycles of rituximab, cyclophosphamide, liposomal doxorubicin, vincristine, and prednisone and continued to develop cervical lymph node recurrence after second-line therapy. The patient was infused with CAR-T cells after receiving focal bridging radiotherapy and remained in complete response more than 9 months after treatment. In addition, the patients did not experience serious adverse reactions related to radiotherapy as well as CAR-T cell therapy.ConclusionsIn this article, we describe a patient with double-expressor diffuse large B-cell lymphoma with localized compression symptoms after second-line treatment failure who benefited from CAR-T combined with focal bridging radiotherapy.

Abstract Background Predicting short-term efficacy and intracranial progression-free survival (iPFS) in epidermal growth factor receptor gene mutated (EGFR-mutated) lung adenocarcinoma patients with brain metastases who receive third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapy was of great significance for individualized treatment. We aimed to construct and validate nomograms based on clinical characteristics and magnetic resonance imaging (MRI) radiomics for predicting short-term efficacy and intracranial progression free survival (iPFS) of third-generation EGFR-TKI in EGFR-mutated lung adenocarcinoma patients with brain metastases. Methods One hundred ninety-four EGFR-mutated lung adenocarcinoma patients with brain metastases who received third-generation EGFR-TKI treatment were included in this study from January 1, 2017 to March 1, 2023. Patients were randomly divided into training cohort and validation cohort in a ratio of 5:3. Radiomics features extracted from brain MRI were screened by least absolute shrinkage and selection operator (LASSO) regression. Logistic regression analysis and Cox proportional hazards regression analysis were used to screen clinical risk factors. Single clinical (C), single radiomics (R), and combined (C + R) nomograms were constructed in short-term efficacy predicting model and iPFS predicting model, respectively. Prediction effectiveness of nomograms were evaluated by calibration curves, Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Kaplan-Meier analysis was used to compare the iPFS of high and low iPFS rad-score patients in the predictive iPFS R model and to compare the iPFS of high-risk and low-risk patients in the predictive iPFS C + R model. Results Overall response rate (ORR) was 71.1%, disease control rate (DCR) was 91.8% and median iPFS was 12.67 months (7.88–20.26, interquartile range [IQR]). There were significant differences in iPFS between patients with high and low iPFS rad-scores, as well as between high-risk and low-risk patients. In short-term efficacy model, the C-indexes of C + R nomograms in training cohort and validation cohort were 0.867 (0.835-0.900, 95%CI) and 0.803 (0.753–0.854, 95%CI), while in iPFS model, the C-indexes were 0.901 (0.874–0.929, 95%CI) and 0.753 (0.713–0.793, 95%CI). Conclusions The third-generation EGFR-TKI showed significant efficacy in EGFR-mutated lung adenocarcinoma patients with brain metastases, and the combined line plot of C + R can be utilized to predict short-term efficacy and iPFS.

Peanuts were susceptible to frost damage during harvesting, transportation, storage, and processing due to temperature and humidity changes, which could affect the quality of peanuts and their products. In order to explore the mechanism of peanut frost damage and improve the detection efficiency of frost-damaged peanuts, this study used near-infrared hyperspectral technology to study the feasibility of non-destructive detection of peanut frost damage, optimization methods based on feature variable screening discriminant models, and the mechanism of peanut frost damage. The effects of five preprocessing methods, including standard normalized variate (SNV), multiplicative scatter correction (MSC), Savizkg-Golag (SG) smoothing, SG smoothing-SNV, and SG smoothing-MSC, on the original data were experimentally studied. Then, eight variable selection methods, including competitive adaptive reweighted sampling (CARS), random frog (RF), variable importance in projection (VIP), successive projections algorithm (SPA), Monte Carlo uninformative variable elimination (MC-UVE), iteration retention information variable (IRIV), variable combination population analysis-iteration retention information variable (VCPA-IRIV), and variable combination population analysis-genetic algorithm (VCPA-GA), were used to screen the feature wavelengths related to peanut frost damage. Support vector machine (SVM) was used to select the feature wavelengths that reached the discrimination accuracy threshold of 90% as the feature wavelengths of peanut frost damage. The results showed that the detection of peanut frost damage based on near-infrared hyperspectral imaging technology was generally feasible and had high accuracy. All variable selection methods can effectively screen the feature wavelengths related to frost damage. Among them, the VCPA-GA algorithm selected the least 7 feature wavelengths, accounting for only 3.125% of all wavelengths in the dataset. The accuracy of the training set and the test set were 91.60% and 90.12%, respectively. The selected frostbite characteristic wavelength reflects information about oleic acid and protein, verifying that excessively low temperatures can lead to a decrease in oleic acid content and an increase in protein content in peanuts. This study provides a theoretical basis and technical support for the rapid non-destructive detection of peanut frost damage.

Abstract Background Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it. Methods Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). Results The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1−Tim-3−TRM), TRM2 (PD-1+Tim-3−TRM), TRM3 (PD-1−Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63–3.60), P

Sub-Saharan Africa (SSA) is experiencing rapid economic growth and rising demand for energy, accompanied by significant low energy access and sustainability challenges. Globally, to address similar issues and unlock a region's energy potential, regional integrated energy systems have gained traction, and initiatives such as establishing power pools for regional electricity markets, cross-border power exchanges, and integrating renewable energy resources are being promoted. This paper describes the status of regional integrated energy systems in Sub-Saharan Africa. We analyze the energy growth achieved through effective strategies and policies that support regional integrated energy systems in developed and developing regions (the United Kingdom and China). Our findings show that challenges, including limited access to financing, regulatory barriers, lack of effective energy planning model, inadequate supporting policies, and fragmented institutional frameworks, hinder the region's widespread deployment of regional integrated energy systems. Taking lessons from the case studies, addressing SSA's energy challenges requires concerted efforts from governments, international organizations, and the private sector to create enabling policy environments, mobilize investments, and build technical capacity and supporting infrastructures. Regional integrated energy systems can enhance energy security by diversifying energy sources, fostering economic development, and stimulating cross-border energy trade. In the United Kingdom, the implementation of integrated energy systems has contributed to a 25% reduction in carbon emissions and a 15% increase in energy efficiency over the past decade. Similarly, in China, the integration of renewable energy sources into regional energy systems has led to a 30% increase in renewable energy capacity and a 20% decrease in coal consumption since 2010. China owns 32% of global renewable energy market, alongside an installed capacity of about 1.26 TW in the first quarter of 2023. Our findings from the power pools indicate that three out of the four pools possess significant hydro energy resources. Specifically, within the CAPP region, 7 out of 10 countries heavily rely on hydro energy, while in EAPP, 6 out of 11 countries exhibit a similar dependency. Moreover, within SAPP, 9 out of 12 countries and within WAPP, 5 out of 14 countries rely significantly on hydro energy.

Abstract Background Open spina bifida is an uncommon malformation in animals, and there is a lack of imaging, clinical, and pathological characterisation of this condition in dogs. Objective Open spina bifida is rarely observed in animals due to high levels of perinatal mortality and frequent euthanasia. To the best of our knowledge, we present the first case of spina bifida in a dog was diagnosed in‐utero and then followed post‐partum. Methods A 3‐year‐old Poodle was presented with twin pregnancy. Radiographic and ultrasonographic findings were suggestive of vertebral malformation and open spina bifida with myelomeningocele in one foetus. Conservative treatment was given but the puppy died 3 days after birth. Thereafter, anatomical and histopathological analysis of several organs was performed to characterise the disease. Results When the twins were born, one puppy had a linear dorsal midline cutaneous defect extending from the level of vertebrae L2–L6. R Radiographic examination showed several congenital vertebral malformations involving the thoracic segment, lumbar segment, sacrum and scapula. Histopathological examinations confirmed the presence of open spina bifida and identified additional abnormalities in several internal organs. Conclusions This case presents a complete characterisation of open spina bifida, before birth and after death, using imaging and histopathology techniques.

In recent years, countries around the world have been placing increasing emphasis on energy saving and emission reduction. As part of the energy system, integrated energy stations play an important role in the low-carbon transition of the energy sector. However, most of the existing studies on carbon emissions from integrated energy stations focus on the operation phase or a single module within it and lack analysis and prediction of carbon emissions from all phases of the integrated energy station. In this paper, based on the perspective of life cycle assessment, system dynamics is used to establish a life cycle carbon emission model for integrated energy stations from four phases: production & materialization, construction, operation & maintenance, and disposal & recycling. This paper takes wind power integrated energy stations as an example, simulates the characteristics of the life cycle carbon emissions of integrated energy stations, and identifies the key factors affecting the carbon emissions. The simulation results show that the carbon emissions of the integrated energy station are mainly concentrated in the production and operation of the energy station, and the increase in the service life of the energy station will not have a significant impact on the total carbon emissions. This paper provides the theoretical guidance and decision-making basis for the formulation of low-carbon emission reduction measures for integrated energy stations.

Tea grade evaluation is an important technical method to test the quality of tea, and scientifically building the tea grade evaluation model has an important significance. This paper took 102 Oolong teas as research object and built the Oolong tea grade evaluation model based on interior quality parameters with various characteristic value screening methods in combination with support vector machine algorithm. Meanwhile, by combining hyperspectral technology with chemometrics, this paper built the quantitative forecast model of particle swarm optimization back propagation neural network (PSO-BP) based on characteristic wavelength and sparrow search algorithm optimization least squares support vector machine (SSA-LSSVM) for characteristic quality parameters, and finally verified the chemical value model of quantitative forecast. The results showed that in case of parameter combination of ester catechin, simple catechin, tea polyphenol, aqueous extract, caffeine and epigallocatechin gallate (EGCG), the Oolong tea judgement model had the highest accuracy, the accuracy of training set was 97.22%, and the accuracy of forecast set was 93.33%. The sparrow search algorithm optimization least squares support vector machine (SSA-LSSVM) quantitative forecast model had higher forecast accuracy and lower root mean square error, and the determination coefficient of forecast set R2 ranged from 0.93 to 0.99. By randomly selecting the optimal six forecasted chemical values of 30 Oolong tea samples, the judgement accuracy reached up to 90%. In conclusion, it was feasible to accurately judge different grades of Oolong tea based on interior quality parameter combination, the forecast model based on hyperspectral technology could rapidly and accurately obtain the chemical value, and the forecasted chemical value could accurately judge different Oolong tea grades, which would provide a new analysis method and application example for scientifically judging tea quality and grade.

Abstract Background Immune-related genes (IRGs) have been confirmed to play an important role in tumorigenesis and tumor microenvironment formation in hepatocellular carcinoma (HCC). We investigated how IRGs regulates the HCC immunophenotype and thus affects the prognosis and response to immunotherapy. Methods We investigated RNA expression of IRGs and developed an immune-related genes-based prognostic index (IRGPI) in HCC samples. Then, the influence of the IRGPI on the immune microenvironment was comprehensively analysed. Results According to IRGPI, HCC patients are divided into two immune subtypes. A high IRGPI was characterized by an increased tumor mutation burden (TMB) and a poor prognosis. More CD8 + tumor infiltrating cells and expression of PD-L1 were observed in low IRGPI subtypes. Two immunotherapy cohorts confirmed patients with low IRGPI demonstrated significant therapeutic benefits. Multiplex immunofluorescence staining determined that there were more CD8 + T cells infiltrating into tumor microenvironment in IRGPI-low groups, and the survival time of these patients was longer. Conclusions This study demonstrated that the IRGPI serve as a predictive prognostic biomarker and potential indicator for immunotherapy.

Tea polyphenol, a vital indicator used for the detection of tea quality, is of great significance to quickly detect the tea polyphenol content via near infrared spectroscopy. In this paper, the near infrared spectroscopy in combination with partial least squares (PLS) was adopted to establish the rapid analysis models by near infrared for tea polyphenol content of powdered and complete tea samples respectively, using 144 black tea samples as the study objects, revealing that the prediction model established by SNV+first derivative+Savitzky-Golay smoothing combined with PLS had the optimal effect in the results. The correlation coefficient (r) was 0.9990 and the root mean square error of calibration (RMSEC) was 0.165% of the training set, while the r was 0.9243 and the root mean square error of prediction (RMSEP) was 0.972% of the prediction set in powered tea samples. At the same time, the r was 0.9967 and the RMSEC was 0.310% of the training set, while the r was 0.9541 and the RMSEP was 0.870% of the prediction set in complete tea samples. The results showed that the PLS model for complete tea samples was better than that for powdered tea. Therefore, rapid and nondestructive detection of tea polyphenols in black tea can be achieved by near infrared spectroscopy.

Abstract Background Anti-PD-(L)1 immunotherapy has been recommended for non-small cell lung cancer (NSCLC) patients with lymph node metastases (LNM). However, the exact functional feature and spatial architecture of tumor-infiltrating CD8 + T cells remain unclear in these patients. Methods Tissue microarrays (TMAs) from 279 IA-IIIB NSCLC samples were stained by multiplex immunofluorescence (mIF) for 11 markers (CD8, CD103, PD-1, Tim3, GZMB, CD4, Foxp3, CD31, αSMA, Hif-1α, pan-CK). We evaluated the density of CD8 + T-cell functional subsets, the mean nearest neighbor distance (mNND) between CD8 + T cells and neighboring cells, and the cancer-cell proximity score (CCPS) in invasive margin (IM) as well as tumor center (TC) to investigate their relationships with LNM and prognosis. Results The densities of CD8 + T-cell functional subsets, including predysfunctional CD8 + T cells (Tpredys) and dysfunctional CD8 + T cells (Tdys), in IM predominated over those in TC (P

Due to the significant price differences among different types of edible oils, expensive oils like olive oil are often blended with cheaper edible oils. This practice of adulteration in edible oils, aimed at increasing profits for producers, poses a major concern for consumers. Furthermore, adulteration in edible oils can lead to various health issues impacting consumer well-being. In order to meet the requirements of fast, non-destructive, universal, accurate, and reliable quality testing for edible oil, the oblique-incidence reflectivity difference (OIRD) method combined with machine learning algorithms was introduced to detect a variety of edible oils. The prediction accuracy of Gradient Boosting, K-Nearest Neighbor, and Random Forest models all exceeded 95%. Moreover, the contribution rates of the OIRD signal, DC signal, and fundamental frequency signal to the classification results were 45.7%, 34.1%, and 20.2%, respectively. In a quality evaluation experiment on olive oil, the feature importance scores of three signals reached 63.4%, 18.9%, and 17.6%. The results suggested that the feature importance score of the OIRD signal was significantly higher than that of the DC and fundamental frequency signals. The experimental results indicate that the OIRD method can serve as a powerful tool for detecting edible oils.

Abstract Photovoltaic (PV) generation has high impact on the decarbonization pathways of power systems. Accuracy of day‐ahead PV power forecasting has become crucial in the operation and control of power system with high PV penetration. This paper develops a hybrid approach based on generative adversarial network (GAN) combined with convolutional autoencoder (CAE) to improve PV power forecasting accuracy. Self‐organizing map method is first utilized as data pre‐processing to classify target days into different weather types based on solar irradiance. With the ability of GAN to reduce the burden of loss and the advantages of CAE to extract multi‐scale effective features from the weather and PV power, PV power forecasting model consisting of GAN and CAE is proposed. The developed method has been tested on a real dataset in a Chinese PV station and compared with base reference PV forecasting methods. Numerical testing results demonstrate the effectiveness of our method with high accuracy.

This paper presents an online multi-level energy management system for local microgrids of commercial buildings that integrate roof-top photovoltaic sources, battery storage systems, utility grids, diesel generators, supercapacitors, and commercial buildings consisting of active orchestrated loads, to solve the uncertainty problem of sources and loads, while also optimizing the local microgrid operation cost of commercial buildings and the utilization rate of local renewable energy. The energy management system includes a long-term rolling optimization level, rule-based optimization level, and load demand optimization level. At the long-term rolling optimization level, an online rolling method of data restructuring is proposed, where measurement data, short-term prediction data, and day-ahead prediction data are reconstructed to reduce the uncertainty in photovoltaic source prediction and load demand prediction. Four methods are proposed for the energy management system and simulated in MATLAB/Simulink under three typical weather conditions, cloudy, sunny, and rainy. Simulation results show that the performance of Method 3 is closest to that of Method 4, whose data conditions are ideal; Method 3 reduces the operational cost of the commercial building microgrid and improves the utilization rate of photovoltaic sources, at the slight cost of non-critical load shedding.

ObjectiveTo explore a prediction model for lymphovascular invasion (LVI) on cT1–2N0M0 radiologic solid non-small cell lung cancer (NSCLC) based on a 2-deoxy-2[18F]fluoro-D-glucose ([18F]F-FDG) positron emission tomography-computed tomography (PET-CT) radiomics analysis.MethodsThe present work retrospectively included 148 patients receiving surgical resection and verified pathologically with cT1–2N0M0 radiologic solid NSCLC. The cases were randomized into training or validation sets in the ratio of 7:3. PET and CT images were used to select optimal radiomics features. Three radiomics predictive models incorporating CT, PET, as well as PET/CT images radiomics features (CT-RS, PET-RS, PET/CT-RS) were developed using logistic analyses. Furthermore, model performance was evaluated by ROC analysis for predicting LVI status. Model performance was evaluated in terms of discrimination, calibration along with clinical utility. Kaplan-Meier curves were employed to analyze the outcome of LVI.ResultsThe ROC analysis demonstrated that PET/CT-RS (AUCs were 0.773 and 0.774 for training and validation sets) outperformed both CT-RS(AUCs, 0.727 and 0.752) and PET-RS(AUCs, 0.715 and 0.733). A PET/CT radiology nomogram (PET/CT-model) was developed to estimate LVI; the model demonstrated conspicuous prediction performance for training (C-index, 0.766; 95%CI, 0.728–0.805) and validation sets (C-index, 0.774; 95%CI, 0.702–0.846). Besides, decision curve analysis and calibration curve showed that PET/CT-model provided clinically beneficial effects. Disease-free survival and overall survival varied significantly between LVI and non-LVI cases (P

Actinidia arguta is a berry fruit with high nutritional values. To evaluate the comprehensive quality, the fruit weight, titratable acid (TAC), soluble solids (SSC), vitamin C, mineral elements, and taste value of 67 accessions of A. arguta were measured, and sensory attributes including olfactive intensity, juiciness, sweetness, sourness, and astringency were assessed. Cluster analysis was carried out based on mineral elements, and principal component analysis (PCA) was used for comprehensive score ranking. The result demonstrated that fruit weight ranged from 3.5 g to 24.2 g, SSC ranged from 11.94% to 20.56%, TAC ranged from 0.15% to 1.20%, and vitamin C ranged from 3.51 g/kg to 230.76 g/kg (fresh weight) among the tested samples. There were significant differences in sourness, sweetness, bitterness, and umami among the 67 accessions based on electronic tongue analysis, and this result was rapidly and objectively characterized by the sensory assessment. The dendrogram was obtained and clustered the accessions into two major clusters, and five principal components were extracted by PCA. Overall, the information provided by this study identified the 10 best germplasm resources for fresh-eating and processing fruits. It can provide theoretical reference for nutritional efficacy evaluation and food development of A. arguta.

BackgroundThe anti-tumoral or pro-tumoral roles of CD4+ and CD8+ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis.MethodsWe performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman’s or Kruskal-Wallis tests.ResultsIn the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4+, and CD8+ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4+ and CD8+ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α+CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.sConclusionsIn locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8+ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.

Complexing self-assembled DNA nanostructures with various functional guest species is the key to unlocking new and exciting biomedical applications. Cationic guest species not only induce magnesium-free DNA to self-assemble into defined structures but also endow the final complex nanomaterials with new properties. Herein, we propose a novel strategy that employs naturally occurring cationic amino acids to induce DNA self-assembly into defined nanostructures. Natural l-arginine and l-lysine can readily induce the assembly of tile-based DNA nanotubes and DNA origami sheets in a magnesium-free manner. The self-assembly processes are demonstrated to be pH- and concentration-dependent and are achieved at constant temperatures. Moreover, the assembled DNA/amino acid complex nanomaterials are stable at a physiological temperature of 37 °C. Substituting l-arginine with its D form enhances its serum stability. Further preliminary examination of this complex nanomaterial platform for biomedical applications indicates that DNA/amino acids exhibit distinct cellular uptake behaviors compared with their magnesium-assembled counterparts. The nanomaterial mainly clusters around the cell membrane and might be utilized to manipulate molecular events on the membrane. Our study suggests that the properties of DNA nanostructures can be tuned by complexing them with customized guest molecules for a designed application. The strategy proposed herein might be promising to advance the biomedical applications of DNA nanostructures.

BackgroundFactors that may influence the recovery of patients with confirmed SARS-CoV-2 infection hospitalized in the Fangcang shelter were explored, and machine learning models were constructed to predict the duration of recovery during the Omicron BA. 2.2 pandemic.MethodsA retrospective study was conducted at Hongqiao National Exhibition and Convention Center Fangcang shelter (Shanghai, China) from April 9, 2022 to April 25, 2022. The demographics, clinical data, inoculation history, and recovery information of the 13,162 enrolled participants were collected. A multivariable logistic regression model was used to identify independent factors associated with 7-day recovery and 14-day recovery. Machine learning algorithms (DT, SVM, RF, DT/AdaBoost, AdaBoost, SMOTEENN/DT, SMOTEENN/SVM, SMOTEENN/RF, SMOTEENN+DT/AdaBoost, and SMOTEENN/AdaBoost) were used to build models for predicting 7-day and 14-day recovery.ResultsOf the 13,162 patients in the study, the median duration of recovery was 8 days (interquartile range IQR, 6–10 d), 41.31% recovered within 7 days, and 94.83% recovered within 14 days. Univariate analysis showed that the administrative region, age, cough medicine, comorbidities, diabetes, coronary artery disease (CAD), hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were associated with a duration of recovery within 7 days. Age, gender, vaccination dose, cough medicine, comorbidities, diabetes, CAD, hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were related to a duration of recovery within 14 days. In the multivariable analysis, the receipt of two doses of the vaccination vs. unvaccinated (OR = 1.118, 95% CI = 1.003–1.248; p = 0.045), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.114, 95% CI = 1.004–1.236; p = 0.043), diabetes (OR = 0.383, 95% CI = 0.194–0.749; p = 0.005), CAD (OR = 0.107, 95% CI = 0.016–0.421; p = 0.005), hypertension (OR = 0.371, 95% CI = 0.202–0.674; p = 0.001), and ratio of N/IC (OR = 3.686, 95% CI = 2.939–4.629; p < 0.001) were significantly and independently associated with a duration of recovery within 7 days. Gender (OR = 0.736, 95% CI = 0.63–0.861; p < 0.001), age (30–70) (OR = 0.738, 95% CI = 0.594–0.911; p < 0.001), age (>70) (OR = 0.38, 95% CI = 0292–0.494; p < 0.001), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.391, 95% CI = 1.12–1.719; p = 0.0033), cough medicine (OR = 1.509, 95% CI = 1.075–2.19; p = 0.023), and symptoms (OR = 1.619, 95% CI = 1.306–2.028; p < 0.001) were significantly and independently associated with a duration of recovery within 14 days. The SMOTEEN/RF algorithm performed best, with an accuracy of 90.32%, sensitivity of 92.22%, specificity of 88.31%, F1 score of 90.71%, and AUC of 89.75% for the 7-day recovery prediction; and an accuracy of 93.81%, sensitivity of 93.40%, specificity of 93.81%, F1 score of 93.42%, and AUC of 93.53% for the 14-day recovery prediction.ConclusionAge and vaccination dose were factors robustly associated with accelerated recovery both on day 7 and day 14 from the onset of disease during the Omicron BA. 2.2 wave. The results suggest that the SMOTEEN/RF-based model could be used to predict the probability of 7-day and 14-day recovery from the Omicron variant of SARS-CoV-2 infection for COVID-19 prevention and control policy in other regions or countries. This may also help to generate external validation for the model.

Dedifferentiated thyroid cancer is the major cause of mortality in thyroid cancer and is difficult to treat. Hence, the essential molecular mechanisms involved in dedifferentiation should be thoroughly investigated. Several studies have explored the biomolecular modifications of dedifferentiated thyroid cancer such as DNA methylation, protein phosphorylation, acetylation, ubiquitination, and glycosylation and the new targets for radiological imaging and therapy in recent years. Novel radionuclide tracers and drugs have shown attractive potential in the early diagnosis and treatment of dedifferentiated thyroid cancer. We summarized the updated molecular mechanisms of dedifferentiation combined with early detection by molecular modification-based imaging to provide more accurate diagnosis and novel therapeutics in the management of dedifferentiated thyroid cancer.

From the perspective of propagation dynamics in complex networks, failure propagation in cyber-physical power systems is analogous to the spread of diseases; subsequently, the cyber nodes and power nodes are regarded as individuals in each of their groups. In this study, a two-layer interdependent network model of the cyber-physical power system is proposed, where each subnetwork adopts the Susceptible-Infected-Susceptible (SIS) epidemic-spreading model. On this basis, we construct a failure cooperation propagation model of cyber-physical power systems. Furthermore, we introduce the node protection mechanism to ensure the normal operation of key nodes. The generated scale-free cyber network and IEEE118-bus power system are used for simulation to analyze the influence of the coupling effect between them on the final failure scale.

Brain metastases (BMs) in non-small-cell lung cancer (NSCLC) patients are associated with significant morbidity and poor prognosis. Immune checkpoint inhibitors (ICIs) have resulted in a paradigm shift in the management of advanced NSCLC. However, the value of ICIs in NSCLC patients with BMs remains unclear because patients with BMs are routinely excluded in numerous prospective trials on ICIs. Here, starting from the mechanisms of ICIs for BMs, we will reveal the value of ICIs by reviewing the efficacy and adverse effects of ICIs monotherapy as well as promising combination strategies, such as combinations with chemotherapy, radiotherapy, and anti-angiogenic drugs, etc. In addition, the methods of patient selection and response assessment will be summarized to assist clinical practice and further studies.

Abstract Background Adequate cytology is limited by insufficient cytologists in a large‐scale cervical cancer screening. We aimed to develop an artificial intelligence (AI)‐assisted cytology system in cervical cancer screening program. Methods We conducted a perspective cohort study within a population‐based cervical cancer screening program for 0.7 million women, using a validated AI‐assisted cytology system. For comparison, cytologists examined all slides classified by AI as abnormal and a randomly selected 10% of normal slides. Each woman with slides classified as abnormal by either AI‐assisted or manual reading was diagnosed by colposcopy and biopsy. The outcomes were histologically confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+). Results Finally, we recruited 703 103 women, of whom 98 549 were independently screened by AI and manual reading. The overall agreement rate between AI and manual reading was 94.7% (95% confidential interval [CI], 94.5%‐94.8%), and kappa was 0.92 (0.91‐0.92). The detection rates of CIN2+ increased with the severity of cytology abnormality performed by both AI and manual reading (Ptrend

Abstract Background Stereotactic body radiotherapy (SBRT) is the standard care for inoperable early stage non‐small cell lung cancer (NSCLC). The purpose of our study was to investigate whether a prediction model based on cone‐beam CT (CBCT) plus pretreatment CT radiomics features could improve the prediction of tumor control and lung toxicity after SBRT in comparison to a model based on pretreatment CT radiomics features alone. Methods A total of 34 cases of stage I NSCLC patients who received SBRT were included in the study. The pretreatment planning CT and serial CBCT radiomics features were analyzed using the imaging biomarker explorer (IBEX) software platform. Multivariate logistic regression was conducted for the association between progression‐free survival (PFS), lung toxicity and features. The predictive capabilities of the models based on CBCT and CT features were compared using receiver operating characteristic (ROC) curves. Results Five CBCT features and two planning CT features were correlated with disease progression. Six CBCT features and two planning CT features were related to lung injury. The ROC curves indicated that the model based on the CBCT plus planning CT features might be better than the model based on the planning CT features in predicting lung injury. The other ROC curves indicated that the model based on the planning CT features was similar to the model based on the CBCT plus planning CT features in predicting disease progression. Conclusions Both pretreatment CT and CBCT radiomics features could predict disease progression and lung injury. A model with CBCT plus pretreatment CT radiomics features might improve the prediction of lung toxicity in comparison with a model with pretreatment CT features alone. Key points Significant findings of the study: A model with cone‐beam CT radiomics features plus pre‐treatment CT radiomics features might improve the prediction of lung toxicity after SBRT in stage I NSCLC patients. What this study adds: In the prediction of PFS and lung toxicity in early‐stage NSCLC patients treated with SBRT, CBCT radiomics could be another effective method.

ObjectivesTo retrospectively observe the instantaneous changes in intratumor density heterogeneity after microwave ablation (MWA) of lung tumors and to determine their prognostic value in predicting treatment response and local tumor progression (LTP).MethodsPre- and post-MWA computed tomography (CT) images of 50 patients (37-males; 13-females; mean-age 65.9 ± 9.7y, 39 primary and 11 metastasis) were analyzed to evaluate changes in intratumor density. Global, regional, and local scale radiomics features were extracted to assess intratumor density heterogeneity. In four to six weeks, chest enhanced CT was used as the baseline evaluation of treatment response. The correlations between the parametric variation immediately after ablation and the visual score of ablation response (Rvisu) were analyzed by nonparametric Spearman correlation analysis. The 1-year LTP discrimination power was assessed using the area under the receiver operating characteristic (ROC) curves. A Cox proportional hazards regression model was used to identify the independent prognostic features.ResultsAlthough no significant volume changes were observed after ablation, the radiomics parameters changed in different directions and degrees. The mean intensity value from baseline CT image was 30.3 ± 23.2, and the post-MWA CT image was -60.9 ± 89.8. The ratio of values change was then calculated by a unified formulation. The largest increase (522.3%) was observed for cluster prominence, while the mean CT value showed the largest decline (321.4%). The pulmonary tumors had a mean diameter of 3.4 ± 0.8 cm. Complete ablation was documented in 36 patients. Significant correlations were observed between Rvisu and quantitative features. The highest correlations were observed for changes in local features after MWA, with r ranging from 0.594 to 0.782. LTP developed in 22 patients. The Cox regression model revealed Δcontrast% and response score as independent predictors (Δcontrast%: odds ratio [OR]=5.61, p=0.001; Rvisu: OR=1.73, p=0019). ROC curve analysis showed that Δcontrast% was a better predictor of 1-year LTP. with higher sensitivity (83.5% vs. 71.2%) and specificity (87.1% vs. 76.8%) than those for Rvisu.ConclusionsThe changes in intratumor density heterogeneity after MWA could be characterized by analysis of radiomics features. Real-time density changes could predict treatment response and LTP in patients with pulmonary tumors earlier, especially for tumors with larger diameters.

With a proliferation of diverse types of renewable distributed generation (DG) into the distribution network, an equivalent model of an active distribution network (ADN) is extremely important, since the detailed modeling of the whole ADN is much more complex and time consuming. However, different studies developed different model structures of ADNs, which are difficult to be applied in a power system simulation. At the same time, the DG’s low voltage ride through the (LVRT) control was not considered in the existing ADN model, which may lead to a large modelling error. In this paper, a general equivalent model is developed for the ADN with a significant amount of DGs, based on a two-step modelling method. Step one, motivated by the dynamic similarities between the doubly-fed induction generator (DFIG)-based wind turbines, direct drive permanent magnet synchronous generator (DDPMSG)-based wind turbines, and photovoltaic (PV) generation, a general model structure of a renewable DG is initially developed. Then, an aggregation method for the DG’s nonlinear subsystems of the low voltage ride through (LVRT) control and the converter’s current limits are presented. Step two, the ADN model is represented by a general renewable DG model paralleled with a composite load model, and the model is validated, based on an actual distribution network with different renewable DG penetrations and different disturbance degrees. The simulation results show that our model outperforms others with acceptable errors.

In the present study, we presented the complete mitochondrial genome of an entomophthoroid fungus Conidiobolus sp. The mitogenome of Conidiobolus sp. has a total length of 26,612 bp, with the base composition as follows: A (44.22%), T (27.10%), C (10.99%) and G (17.68%). The mitogenome contains 19 protein-coding genes, 2 ribosomal RNA genes (rRNA), and 23 transfer RNA (tRNA) genes. The taxonomic status of the Conidiobolus sp. mitogenome exhibited a close relationship with the mitogenome of Conidiobolus heterosporus.

In the present study, the complete mitogenome of Cryptococcus sp. were sequenced and assembled. The complete mitogenome of Cryptococcus sp. was composed of circular DNA molecules, with a total length of 30,029 bp. The base composition of this mitochondrial genome is as follows: A (31.94%), T (34.89%), G (15.97%), and C (17.21%). The mitogenome contains 20 protein-coding genes, 2 ribosomal RNA genes (rRNA), and 22 transfer RNA (tRNA) genes. Phylogenetic analysis showed that the mitogenome of the Cryptococcus sp. exhibited a closest relationship with Cryptococcus gattii.

Neoadjuvant chemotherapy has been established as standard treatments for advanced breast cancer among multidisciplinary therapies. A simple and instructive biomarker for the postoperative recurrence and metastasis is needed to evaluate the therapeutic effect. Plasma fibrinogen level has been shown to be associated with tumor progression and poor outcomes in breast cancer patients. This study aims to further evaluate the clinical and prognostic value of plasma fibrinogen level as a biomarker in breast cancer patients receiving neoadjuvant chemotherapy. In this study, data of 67 patients were retrospectively collected and analyzed to identify the relationship between the plasma fibrinogen level and the clinical progression and outcome of these patients. Patients with increased plasma fibrinogen level after neoadjuvant chemotherapy had significantly shorter disease-free survival and overall survival (p < 0.001 and p = 0.001, respectively). In a univariate survival analysis, molecular type (p = 0.0004/p = 0.005), clinical response (p = 0.008/p = 0.015), and changes in plasma fibrinogen level (p = 0.012/p = 0.007) were associated with disease-free survival and overall survival, and all of them, molecular type (p = 0.0003/p = 0.005), clinical response (p = 0.027/p = 0.021), and changes in plasma fibrinogen level (p = 0.035/p = 0.025), were associated with disease-free survival and overall survival in a multivariate survival analysis, respectively. The plasma fibrinogen level was found to be a possible biomarker for clinical response to chemotherapy and postoperative metastasis or death in advanced breast cancer patients who received neoadjuvant chemotherapy.

Polyploid plants often have higher biomass and superior crop qualities. Breeders therefore search for crop germplasm with higher ploidy levels; however, whether higher ploidy levels are associated with better performance remains unclear. Actinidia arguta and related species, whose commercialized fruit are referred to as kiwiberries, harbor a series of ploidy races in nature, offering an opportunity to determine the link between ploidy levels and agronomic traits. In the present study, we determined the ploidy levels of A. arguta var. arguta, A. arguta var. giraldii, and A. melanandra in 16 natural populations using flow cytometry, and examined 31 trait variations in fruits, leaves and flowers by field observations, microscopic examination and laboratory analyses. Our results showed that octaploid and decaploid A. arguta var. giraldii had larger dimension of leaves than tetraploid A. arguta var. arguta and A. melanandra, but their fruits were significantly smaller. In addition, A. arguta var. giraldii (8x and 10x) had higher contents of nutrients such as ascorbic acid and amino acids; however, some important agronomic traits, including the content of total sugar and total acid, were significantly lower in the octaploids and decaploids. Moreover, octaploids and decaploids did not result in greater ecological adaptability for the challenging environments and climates. In conclusion, the differentiation of ecological adaptability and traits among natural kiwiberries' cytotypes suggested that higher ploidy levels are not inevitably advantageous in plants. The findings of A. arguta and related taxa in geographical distribution and agronomic trait variations will facilitate their germplasm domestication.

There is an urgent need for rapid and accurate microbiological diagnostic assay for detection of Clostridium difficile infection (CDI). We assessed the diagnostic accuracy of the Xpert Clostridium difficile assay (Xpert CD) for the diagnosis of CDI.We searched PubMed, EMBASE, and Cochrane Library databases to identify studies according to predetermined criteria. STATA 13.0 software was used to analyze the tests for sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the summary receiver operating characteristic curves (AUC). QUADAS-2 was used to assess the quality of included studies with RevMan 5.2. Heterogeneity in accuracy measures was tested with Spearman correlation coefficient and Chi-square.A total of 22 studies were included in the meta-analysis. The pooled sensitivity (95% confidence intervals [CI]) was 0.97 (0.95-0.99) and specificity was 0.95 (0.94-0.96). The AUC was 0.99 (0.97-0.99). Significant heterogeneity was observed when we pooled most of the accuracy measures of selected studies.The Xpert CD assay is a useful diagnostic tool with high sensitivity and specificity in diagnosing toxigenic CDI, and this method has excellent usability due to its rapidity and simplicity.

The identification of surgical non-small cell lung cancer (NSCLC) patients with poor prognosis is a priority in clinical oncology because of their high 5-year mortality. This meta-analysis explored the prognostic value of maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) on disease-free survival (DFS) and overall survival (OS) in surgical NSCLC patients.MEDLINE, EMBASE and Cochrane Libraries were systematically searched until August 1, 2015. Prospective or retrospective studies that evaluated the prognostic roles of preoperative 18F-FDG PET/CT with complete DFS and OS data in surgical NSCLC patients were included. The impact of SUVmax, MTV or TLG on survival was measured using hazard ratios (HR). Sub-group analyses were performed based on disease stage, pathological classification, surgery only and cut-off values.Thirty-six studies comprised of 5807 patients were included. The combined HRs for DFS were 2.74 (95%CI 2.33-3.24, unadjusted) and 2.43 (95%CI: 1.76-3.36, adjusted) for SUVmax, 2.27 (95%CI 1.77-2.90, unadjusted) and 2.49 (95%CI 1.23-5.04, adjusted) for MTV, and 2.46 (95%CI 1.91-3.17, unadjusted) and 2.97 (95%CI 1.68-5.28, adjusted) for TLG. The pooled HRs for OS were 2.54 (95%CI 1.86-3.49, unadjusted) and 1.52 (95%CI 1.16-2.00, adjusted) for SUVmax, 2.07 (95%CI 1.16-3.69, unadjusted) and 1.91 (95%CI 1.13-3.22, adjusted) for MTV, and 2.47 (95%CI 1.38-4.43, unadjusted) and 1.94 (95%CI 1.12-3.33, adjusted) for TLG. Begg's test detected publication bias, the trim and fill procedure was performed, and similar HRs were obtained. The prognostic role of SUVmax, MTV and TLG remained similar in the sub-group analyses.High values of SUVmax, MTV and TLG predicted a higher risk of recurrence or death in patients with surgical NSCLC. We suggest the use of FDG PET/CT to select patients who are at high risk of disease recurrence or death and may benefit from aggressive treatments.

INTRODUCTION:To observe the early change of metabolic tumor heterogeneity during chemoradiotherapy and to determine its prognostic value for patients with locally advanced non-small cell lung cancer (NSCLC). METHODS:From January 2007 to March 2010, 58 patients with NSCLC were included who were received 18F-fluorodeoxyglucose (18F-FDG) PET/CT before and following 40 Gy radiotherapy with the concurrent cisplatin-based chemotherapy (CCRT). Primary tumor FDG uptake heterogeneity was determined using global and local scale textural features extracted from standardized uptake value (SUV) histogram analysis (coefficient of variation [COV], skewness, kurtosis, area under the curve of the cumulative SUV histogram [AUC-CSH]) and normalized gray-level co-occurrence matrix (contrast, dissimilarity, entropy, homogeneity). SUVmax and metabolic tumor volume (MTV) were also evaluated. Correlations were analyzed between parameters on baseline or during treatments with tumor response, progression-free survival (PFS), and overall survival (OS). RESULTS:Compared with non-responders, responders showed significantly greater pre-treatment COV, contrast and MTV (AUC = 0.781, 0.804, 0.686, respectively). Receiver-operating-characteristic curve analysis showed that early change of tumor textural analysis serves as a response predictor with higher sensitivity (73.2%~92.1%) and specificity (80.0%~83.6%) than baseline parameters. Change in AUC-CSH and dissimilarity during CCRT could also predict response with optimal cut-off values (33.0% and 28.7%, respectively). The patients with greater changes in contrast and AUC-CSH had significantly higher 5-year OS (P = 0.008, P = 0.034) and PFS (P = 0.007, P = 0.039). In multivariate analysis, only change in contrast was found as the independent prognostic factor of PFS (HR 0.476, P = 0.021) and OS (HR 0.519, P = 0.015). CONCLUSIONS:The metabolic tumor heterogeneity change during CCRT characterized by global and local scale textural features may be valuable for predicting treatment response and survival for patients with locally advanced NSCLC.

Clinical studies have demonstrated the predictive values of changes in electrocardiographic (ECG) parameters for the preexisting myocardial ischemic infarction. However, a simple and early predictor for the subsequent development of myocardial infarction during the ischemic phase is of significant value for the identification of ischemic patients at high risk. The present study was undertaken by using non-human primate model of myocardial ischemic infarction to fulfill this gap. Twenty male Rhesus monkeys at age of 2-3 years old were subjected to left anterior descending artery ligation. This ligation was performed at varying position along the artery so that it produced varying sizes of myocardial infarction at the late stage. The ECG recording was undertaken before the surgical procedure, at 2 h after the ligation, and 8 weeks after the surgery for each animal. The correlation of the changes in the ECG waves in the early or the late stage with the myocardial infarction size was analyzed. The R wave depression and the QT shortening in the early ischemic stage were found to have an inverse correlation with the myocardial infarction size. At the late stage, the R wave depression, the QT prolongation, the QRS score, and the ST segment elevation were all closely correlated with the developed infarction size. The poor R wave progression was identified at both the early ischemic and the late infarction stages. Therefore, the present study using non-human primate model of myocardial ischemic infarction identified the decreases in the R wave and the QT interval as early predictors of myocardial infarction. Validation of these parameters in clinical studies would greatly help identifying patients with myocardial ischemia at high risk for the subsequent development of myocardial infarction.

Background: High-risk double-expressor diffuse large B-cell lymphoma has an inferior prognosis following standard first-line therapy. After failure of secondline therapy, treatment options are limited if accompanied by localized compressive symptoms. Chimeric Antigen Receptor T cell (CAR-T) therapy preceded by bridging radiotherapy may be an effective emerging therapy. Case presentation: We report a 66-year-old female patient diagnosed with stage IV double-expressor diffuse large B-cell lymphoma. The patient achieved progressive disease after two cycles of rituximab, cyclophosphamide, liposomal doxorubicin, vincristine, and prednisone and continued to develop cervical lymph node recurrence after second-line therapy. The patient was infused with CAR-T cells after receiving focal bridging radiotherapy and remained in complete response more than 9 months after treatment. In addition, the patients did not experience serious adverse reactions related to radiotherapy as well as CAR-T cell therapy. Conclusions: In this article, we describe a patient with double-expressor diffuse large B-cell lymphoma with localized compression symptoms after second-line treatment failure who benefited from CAR-T combined with focal bridging radiotherapy. [ABSTRACT FROM AUTHOR]