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Abstract Background The metabolic tumour area (MTA) was found to be a promising predictor of prostate cancer. However, the role of MTA based on 18F-FDG PET/CT in diffuse large B-cell lymphoma (DLBCL) prognosis remains unclear. This study aimed to elucidate the prognostic significance of MTA and evaluate its incremental value to the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) for DLBCL patients treated with first-line R-CHOP regimens. Methods A total of 280 consecutive patients with newly diagnosed DLBCL and baseline 18F-FDG PET/CT data were retrospectively evaluated. Lesions were delineated via a semiautomated segmentation method based on a 41% SUVmax threshold to estimate semiquantitative metabolic parameters such as total metabolic tumour volume (TMTV) and MTA. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off values. Progression-free survival (PFS) and overall survival (OS) were the endpoints that were used to evaluate the prognosis. PFS and OS were estimated via Kaplan‒Meier curves and compared via the log-rank test. Results Univariate analysis revealed that patients with high MTA, high TMTV and NCCN-IPI ≥ 4 were associated with inferior PFS and OS (P

Abstract Purpose Cancer survivors have a high risk of mortality, and vitamin D (VD) is associated with the risk of mortality. This study is aim to examine the impact of VD on mortality in cancer survivors. Methods A prospective study was conducted using data from the National Health and Nutrition Examination Survey. Participants were obtained information on their baseline characteristics, dietary habits, comorbidities, lifestyle, and serum 25-hydroxy VD [25(OH)D] concentrations. The weighted Cox proportional hazard and competing risk regression models were used to estimate the hazard ratio and 95% confidence intervals (HR, 95% CI) of mortality for different serum 25(OH)D concentrations. Restricted cubic spline (RCS) curves were utilized to illustrate the dose–response relationship between serum 25(OH)D concentrations and mortality. Results The study encompassed 2,495 participants with cancer diagnoses. Multivariate models indicated that, compared to serum 25(OH)D concentrations below 58.5 nmol/L, concentrations exceeding 81.6 nmol/L were associated with reduced HRs for all-cause mortality (HR = 0.70; 95% CI: 0.56–0.87), cardiovascular mortality (HR = 0.53; 95% CI: 0.32–0.86), and cancer-specific mortality (HR = 0.66; 95% CI: 0.45–0.99). RCS curves revealed “L-shaped” associations between serum 25(OH)D concentration and both all-cause and cancer-specific mortality, with threshold effects at 87.9 nmol/L and 84.6 nmol/L, respectively. Conversely, the relationship between serum 25(OH)D concentration and cardiovascular mortality exhibited a more linear pattern, with a threshold at 88.7 nmol/L. Subgroup analyses highlighted a gender-specific interaction that elevated serum 25(OH)D concentrations were significantly more protective against mortality in males than in females, especially regarding cancer-specific mortality (P-interaction = 0.009). Conclusion Elevated serum 25(OH)D concentrations were correlated with decreased risks of all-cause, cardiovascular, and cancer-specific mortality in cancer survivors, with benefit thresholds at 87.9, 88.7, and 84.6 nmol/L, respectively. These findings suggested that cancer survivors might benefit from higher vitamin D recommendations than the general population.

Abstract Background To introduce a three-dimensional convolutional neural network (3D CNN) leveraging transfer learning for fusing PET/CT images and clinical data to predict EGFR mutation status in lung adenocarcinoma (LADC). Methods Retrospective data from 516 LADC patients, encompassing preoperative PET/CT images, clinical information, and EGFR mutation status, were divided into training (n = 404) and test sets (n = 112). Several deep learning models were developed utilizing transfer learning, involving CT-only and PET-only models. A dual-stream model fusing PET and CT and a three-stream transfer learning model (TS_TL) integrating clinical data were also developed. Image preprocessing includes semi-automatic segmentation, resampling, and image cropping. Considering the impact of class imbalance, the performance of the model was evaluated using ROC curves and AUC values. Results TS_TL model demonstrated promising performance in predicting the EGFR mutation status, with an AUC of 0.883 (95%CI = 0.849–0.917) in the training set and 0.730 (95%CI = 0.629–0.830) in the independent test set. Particularly in advanced LADC, the model achieved an AUC of 0.871 (95%CI = 0.823–0.919) in the training set and 0.760 (95%CI = 0.638–0.881) in the test set. The model identified distinct activation areas in solid or subsolid lesions associated with wild and mutant types. Additionally, the patterns captured by the model were significantly altered by effective tyrosine kinase inhibitors treatment, leading to notable changes in predicted mutation probabilities. Conclusion PET/CT deep learning model can act as a tool for predicting EGFR mutation in LADC. Additionally, it offers clinicians insights for treatment decisions through evaluations both before and after treatment.

ObjectiveTo explore the association between the quantity of hibernating myocardium (HM) and collateral circulation in patients with coronary chronic total occlusion (CTO).Materials and methods88 CTO patients were retrospectively analyzed who underwent evaluation for HM using both 99mTc-sestamibi Single photon emission computed tomography (99mTc-MIBI SPECT) myocardial perfusion imaging (MPI) combined with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) myocardial metabolism imaging (MMI). They were divided into two groups according Rentrop grading: the poorly/well-developed collateral circulation group (PD/WD group, Rentrop grades 0–1/2–3). After adjusting for the potential confounding factors and conducting a stratified analysis, we explored the association between the HM index within CTO region and the grading of collateral circulation.ResultsIn the WD group, the HM index was notably higher than PD group (46.2 ± 15.7% vs. 20.9 ± 16.7%, P

An 8-week feeding trial was conducted to investigate the effects of dietary carbohydrate levels on growth performance, body composition, and plasma biochemical parameters, liver and gut histology, and intestinal microbiota of Takifugu rubripes. Five isonitrogenous and isolipidic experimental diets were formulated with graded levels of cassava starch: 0% (C0), 8% (C8), 16% (C16), 24% (C24), and 32% (C32). The results showed that weight gain rate, specific growth rate (SGR) and protein efficiency ratio significantly increased in C16 and C24 groups (P < 0.05), while the feed conversion ratio expressed an opposite trend. Feeding rate is decreased with the increasing of carbohydrate levels (P < 0.05). Liver lipid content was dramatically increased in C24 treatment (P < 0.05). The intestinal amylase activity and muscle glycogen content were higher than other groups (P < 0.05). Plasma glucose levels were increased in C24 and C32 groups (P < 0.05). In addition, the abundance of intestinal potentially pathogenic bacteria (Staphylococcus) decreased, and the intestinal probiotics (Lactobacillus) increased with the increasing of dietary carbohydrate level (P < 0.05). The intestinal bacteria, indicated by Sobs, Chao and Shannon indexes, were more diverse with the increasing of the carbohydrate level (P < 0.05), meanwhile the abundance of transport and metabolism of carbohydrate, lipid and amino acid were enhanced with the increasing of carbohydrate levels (P < 0.05). In conclusion, appropriate supplementation of carbohydrate in diet promoted growth performance and feed utilization of juvenile Takifugu rubripes, and increased the liver lipid and muscle glycogen content, as well as intestinal microbial diversity. Based on the quadratic regression between SGR and carbohydrate levels, the optimal dietary carbohydrate level of juvenile Takifugu rubripes is 21.6%.

Abstract Aim Atrial fibrillation (AF) is a progressive disease from paroxysmal to persistent, and persistent AF (PerAF) had worse prognosis. AF has potential link with inflammation, but it is not clear whether PerAF or paroxysmal AF (ParAF) is more closely related to inflammation. On the basis of inhibiting myocardial physiological uptake, 18F-fluorodeoxyglucosepositron emission tomography/computed tomography (18F-FDG PET/CT) is an established imaging modality to detect cardiac inflammation. We aimed to decipher the association between AF and atrial inflammatory activity by 18F-FDG PET/CT. Methods Thirty-five PerAF patients were compared to age and sex matched ParAF group with baseline 18F-FDG PET/CT scans prior to radiofrequency catheter ablation (RFCA) in the prospective case-control study. High-fat and low-carbohydrate diet and prolonged fast (HFLC+Fast) was applied to all AF patients before PET/CT. Then 22 AF patients with positive right atrial (RA) wall FDG uptake (HFLC+Fast) were randomly selected and underwent HFLC+Fast+heparin the next day. The CHA2DS2-VASc score was calculated to evaluate the risk of stroke. Clinical data, ECG, echocardiography, and atrial 18F-FDG uptake were compared. Results PerAF patients had significantly higher probability of RA wall positive FDG uptake and higher SUVmax than ParAF group [91.4% VS. 28.6%, P

Abstract Background 18F-FDG PET/CT provides precise information about dissemination of lymphoma lesions. Dmax, defined as distance between the two lesions that were farthest apart by PET/CT, was found to be a promising predictor of Diffuse large B-cell lymphoma (DLBCL) outcome in a small size of clinical trial data. We analyzed the impact of Dmax on the outcome of a large real-world DLBCL cohort. Methods Data of newly diagnosed DLBCL at the Third Affiliated Hospital of Soochow University were retrospectively collected. Baseline Dmax, clinical data and survival information were recorded. A metabolic parameter, metabolic bulk volume (MBV), was also measured to verify the independent impact of Dmax. Results Optimal cut-off values for Dmax and MBV were 45.34 cm and 21.65 cm3. With a median follow-up of 32 months, Dmax significantly impacted progression-free survival (PFS) and overall survival (OS) in 253 DLBCL patients. For Dmaxlow and Dmaxhigh groups, estimated 3-year OS were 87.0% and 53.8% (p

Abstract Background This study aims to construct radiomics models based on [18F]FDG PET/CT using multiple machine learning methods to predict the EGFR mutation status of lung adenocarcinoma and evaluate whether incorporating clinical parameters can improve the performance of radiomics models. Methods A total of 515 patients were retrospectively collected and divided into a training set (n = 404) and an independent testing set (n = 111) according to their examination time. After semi-automatic segmentation of PET/CT images, the radiomics features were extracted, and the best feature sets of CT, PET, and PET/CT modalities were screened out. Nine radiomics models were constructed using logistic regression (LR), random forest (RF), and support vector machine (SVM) methods. According to the performance in the testing set, the best model of the three modalities was kept, and its radiomics score (Rad-score) was calculated. Furthermore, combined with the valuable clinical parameters (gender, smoking history, nodule type, CEA, SCC-Ag), a joint radiomics model was built. Results Compared with LR and SVM, the RF Rad-score showed the best performance among the three radiomics models of CT, PET, and PET/CT (training and testing sets AUC: 0.688, 0.666, and 0.698 vs. 0.726, 0.678, and 0.704). Among the three joint models, the PET/CT joint model performed the best (training and testing sets AUC: 0.760 vs. 0.730). The further stratified analysis found that CT_RF had the best prediction effect for stage I–II lesions (training set and testing set AUC: 0.791 vs. 0.797), while PET/CT joint model had the best prediction effect for stage III–IV lesions (training and testing sets AUC: 0.722 vs. 0.723). Conclusions Combining with clinical parameters can improve the predictive performance of PET/CT radiomics model, especially for patients with advanced lung adenocarcinoma.

Abstract Purpose To use 18 F-FDG microPET dynamic imaging to preliminarily identify the changes of myocardial glucose metabolism corresponding to different functional phenotypes of diabetic cardiomyopathy (DCM) in mice and elucidate their relationships. Methods Left ventricular function was measured by echocardiography in C57BL/KsJ-db/db (db/db) mice and their controls at 8, 12, 16, and 20 weeks of age to divide DCM stages and functional phenotypes. Myocardial histopathology was used to verify the staging accuracy and list-mode microPET dynamic imaging was conducted. The myocardial metabolic rate of glucose (MRglu) and the glucose uptake rate constant (Ki) were derived via Patlak graphical analysis, and the differences in myocardial glucose metabolism levels in different DCM stages were compared. The key proteins involved in myocardial glucose metabolism signaling pathway were analyzed by Western blotting to elucidate the underlying mechanism of abnormal glucose metabolism in DCM. Results Compared with the controls, the ratio of early diastolic transmitral flow velocity to early diastolic mitral annular tissue velocity (E/e’) of db/db mice was significantly increased from the age of 12 weeks, while the left ventricular ejection fraction (LVEF) was significantly decreased from the age of 16 weeks (all P 0.05). MRglu and SUV were moderately negatively correlated with the E/e’ ratio (r=-0.539 and − 0.512, P = 0.007 and 0.011), which were not significantly correlated with LVEF (P > 0.05). Meanwhile, Ki was not significantly correlated with LVEF or E/e’ ratio. The decreased expression of glucose transporter (GLUT) -4 in db/db mice preceded GLUT-1 and was accompanied by decreased phosphorylated AMP-activated protein kinase (p-AMPK) expression. Myocardial MRglu, Ki and SUV were significantly positively correlated with the expression of GLUT-4 (MRglu: r = 0.537; Ki: r = 0.818; SUV: r = 0.491; P = 0.000 ~ 0.046), but there was no significant correlation with GLUT-1 expression (P = 0.238 ~ 0.780). Conclusions During the progression of DCM, with the changes of left ventricular functional phenotype, abnormal and dynamic changes of myocardial glucose metabolism can occur in the early stage.

Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of cancer-associated deaths. In recent years, significant progress has been achieved in basic and clinical research concerning the epidermal growth factor receptor (EGFR), and the treatment of lung adenocarcinoma has also entered a new era of individualized, targeted therapies. However, the detection of lung adenocarcinoma is usually invasive. 18F-FDG PET/CT can be used as a noninvasive molecular imaging approach, and radiomics can acquire high-throughput data from standard images. These methods play an increasingly prominent role in diagnosing and treating cancers. Herein, we reviewed the progress in applying 18F-FDG PET/CT and radiomics in lung adenocarcinoma clinical research and how these data are analyzed via traditional statistics, machine learning, and deep learning to predict EGFR mutation status, all of which achieved satisfactory results. Traditional statistics extract features effectively, machine learning achieves higher accuracy with complex algorithms, and deep learning obtains significant results through end-to-end methods. Future research should combine these methods to achieve more accurate predictions, providing reliable evidence for the precision treatment of lung adenocarcinoma. At the same time, facing challenges such as data insufficiency and high algorithm complexity, future researchers must continuously explore and optimize to better apply to clinical practice.

BackgroundMost coronary artery disease (CAD) patients with a normal left ventricular ejection fraction (LVEF) experience a poor prognosis. Single-photon emission computerized tomography (SPECT)–myocardial perfusion imaging (MPI), a routine examination, is useful in assessing risk and predicting major adverse cardiovascular events (MACEs) in populations with suspected or known CAD. SPECT/CT is a “one-stop shop” examination, which, through non-contrast CT, can produce attenuation correction for MPI and obtain information on coronary artery calcium (CAC) and epicardial fat volume (EFV) simultaneously. This study aims to investigate the predictive and incremental value of EFV to MPI for MACE in Chinese populations with suspected or known CAD with a normal LVEF.Methods and resultsWe retrospectively studied 290 suspected or known CAD inpatients with a normal LVEF who underwent SPECT/CT between February 2014 and December 2017. Abnormal MPI was defined as a summed stress score ≥4 or summed difference score ≥2. EFV and CAC were calculated using non-contrast CT. The end date of follow-ups was in February 2022. The follow-up information was obtained from the clinical case notes of the patients or reviews of telephone calls. MACE was defined as cardiac death, late coronary revascularization ≥3 months after MPI, non-fatal myocardial infarction, angina-related rehospitalization, heart failure, and stroke. During the 76-month follow-up, the event rate was 32.0% (93/290). Univariate and multivariate Cox regression analyses concluded that high EFV (>108.3 cm3) [hazard ratio (HR): 3.3, 95% CI: 2.1–5.2, P

Abstract Objective Previous studies have shown that global coronary artery calcium score (CACS) can improve single photon emission computerized tomography (SPECT) myocardial perfusion imaging (MPI) to detect obstructive coronary artery disease (CAD). Whether regional CACS can improve SPECT MPI to detect obstructive CAD remains unclear. The aim of this study was to verify whether regional CACS has additional diagnostic value for obstructive CAD in suspected patients, compared to SPECT MPI and global CACS. Methods The study included 321 suspected CAD patients who underwent one-stop rest-stress SPECT MPI and low-dose computed tomography (CT) scan. All patients underwent coronary angiography within one month after examination. MPI images were visually analyzed by 2 experienced nuclear cardiologists. The regional CACS of left anterior descending coronary artery (LAD), left circumflex coronary artery (LCX), right coronary artery (RCA) and global CACS were calculated. Obstructive CAD was defined as ≥ 70% narrowing of the inner diameter of the LAD, LCX, RCA or their main branches and ≥ 50% narrowing of the left main coronary artery (LM). Results Among the 321 patients, 86 (26.8%, 86/321) had obstructive CAD. With the increased in global and regional CACS, there was an increasing trend of patients with obstructive CAD (P for trend

Previous studies have indicated that 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in biochemical recurrence (BCR) patients with poorly differentiated prostate adenocarcinoma had higher diagnostic sensitivity than those with well differentiated adenocarcinoma, but whether the performance of FDG PET can achieve the effect of prostate-specific membrane antigen (PSMA) PET in BCR patients with a high Gleason score remains poorly understood. This study aimed to compare the efficacies of 18F-FDG PET/CT and 68Ga-PSMA PET/CT for BCR patients and evaluate whether 18F-FDG PET was not inferior to 68Ga-PSMA PET for detecting BCR with a high Gleason score. This was a retrospective, head-to-head comparative study completed at Ren Ji Hospital between May 2018 and June 2021. Patients underwent both 18F-FDG and 68Ga-PSMA PET/CT. The detection rate of BCR at the patient level and at the anatomical region level was evaluated. In total, 145 patients were enrolled in this study. 18F-FDG PET/CT (24.1%, 35/145) had lower detection rates than 68Ga-PSMA PET/CT (59.3%, 86/145; p < 0.001) at the patient level and at any anatomical region (p < 0.05). The PSA level (p < 0.001, OR = 11.026, 95% CI: 3.214–37.824) and the Gleason score (p < 0.001, OR = 20.227, 95% CI: 5.741–71.267) were independent predictive factors of the detection rate on 18F-FDG PET/CT, while the PSA level (p < 0.001, OR = 4.862, 95% CI: 2.338–10.110) was the only predictor of the detection rate on 68Ga-PSMA PET/CT. 18F-FDG PET/CT had a similar detection rate as 68Ga-PSMA PET/CT in patients with a Gleason score of 9 at the patient level (64.3% vs. 71.4%, p = 0.567) and any anatomical region (all p > 0.05), but 18F-FDG PET/CT had a lower detection rate than 68Ga-PSMA PET/CT in patients with a Gleason score of 6–8. 18F-FDG PET is not inferior to 68Ga-PSMA PET for detecting BCR with a Gleason score of 9; therefore, 18F-FDG PET/CT could be considered in BCR patients with a Gleason score of 9. However, 68Ga-PSMA is a better tracer than 18F-FDG in PET/CT for treatment decision making in BCR patients with a Gleason score of 6–8.

Abstract Objective The rest-only single photon emission computerized tomography (SPECT) myocardial perfusion imaging (MPI) had low sensitivity in diagnosing obstructive coronary artery disease (CAD). Improving the efficacy of resting MPI in diagnosing CAD has important clinical significance for patients with contraindications to stress. The purpose of this study was to develop and validate a model predicting obstructive CAD in suspected CAD patients, based on rest-only MPI and cardiovascular risk factors. Methods A consecutive retrospective cohort of 260 suspected CAD patients who underwent rest-only gated SPECT MPI and coronary angiography was constructed. All enrolled patients had stress MPI contraindications. Clinical data such as age and gender were collected. Automated quantitative analysis software QPS and QGS were used to evaluate myocardial perfusion and function parameters. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the variables and build the prediction model. Results Among the enrolled 260 patients with suspected CAD, there were 95 (36.5%, 95/260) patients with obstructive CAD. The prediction model was presented in the form of a nomogram and developed based on selected predictors, including age, sex, SRS ≥ 4, SMS ≥ 2, STS ≥ 2, hypertension, diabetes, and hyperlipidemia. The AUC of the prediction model was 0.795 (95% CI: 0.741–0.843), which was better than the traditional models. The AUC calculated by enhanced bootstrapping validation (500 bootstrap resamples) was 0.785. Subsequently, the calibration curve (intercept = − 0.106; slope = 0.843) showed a good calibration of the model. The decision curve analysis (DCA) shows that the constructed clinical prediction model had good clinical applications. Conclusions In patients with suspected CAD and contraindications to stress MPI, a prediction model based on rest-only ECG-gated SPECT MPI and cardiovascular risk factors have been developed and validated to predict obstructive CAD effectively.

Abstract Purpose This work aims to train, validate, and test a dual-stream three-dimensional convolutional neural network (3D-CNN) based on fluorine 18 (18F)-fluorodeoxyglucose (FDG) PET/CT to distinguish benign lesions and invasive adenocarcinoma (IAC) in ground-glass nodules (GGNs). Methods We retrospectively analyzed patients with suspicious GGNs who underwent 18F-FDG PET/CT in our hospital from November 2011 to November 2020. The patients with benign lesions or IAC were selected for this study. According to the ratio of 7:3, the data were randomly divided into training data and testing data. Partial image feature extraction software was used to segment PET and CT images, and the training data after using the data augmentation were used for the training and validation (fivefold cross-validation) of the three CNNs (PET, CT, and PET/CT networks). Results A total of 23 benign nodules and 92 IAC nodules from 106 patients were included in this study. In the training set, the performance of PET network (accuracy, sensitivity, and specificity of 0.92 ± 0.02, 0.97 ± 0.03, and 0.76 ± 0.15) was better than the CT network (accuracy, sensitivity, and specificity of 0.84 ± 0.03, 0.90 ± 0.07, and 0.62 ± 0.16) (especially accuracy was significant, P-value was 0.001); in the testing set, the performance of both networks declined. However, the accuracy and sensitivity of PET network were still higher than that of CT network (0.76 vs. 0.67; 0.85 vs. 0.70). For dual-stream PET/CT network, its performance was almost the same as PET network in the training set (P-value was 0.372–1.000), while in the testing set, although its performance decreased, the accuracy and sensitivity (0.85 and 0.96) were still higher than both CT and PET networks. Moreover, the accuracy of PET/CT network was higher than two nuclear medicine physicians [physician 1 (3-year experience): 0.70 and physician 2 (10-year experience): 0.73]. Conclusion The 3D-CNN based on 18F-FDG PET/CT can be used to distinguish benign lesions and IAC in GGNs, and the performance is better when both CT and PET images are used together.

BackgroundVitamin D (VD) plays an important role in decreasing the risk of adverse events for various metabolic diseases. However, for patients with hyperlipidemia, the relationship between the main VD storage within the body known as serum 25-hydroxy-VD [25(OH)VD] and the risk of all-cause, cardiovascular and malignancies-specific mortality is still unclear.Materials and methodsA total of 6740 participants above the age of 20 years with hyperlipidemia who completed the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2016 and were followed up until 2019 were included in the study. The weighted Cox proportional hazards regression model and weighted competing risk regression model were used to evaluate the risk for all-cause, cardiovascular and malignancy-related mortality in relation to the serum 25(OH)VD. The model was adjusted according to age, gender, race, body mass index, lipids status, medication usage, the Charlson comorbidity index and healthy eating index. The last restricted cubic spline (RCS) method was used to present the relationship between hazard ratios (HR) associated with diverse cause-specified modalities and the serum 25(OH)VD levels.ResultsSerum 25(OH)VD was identified as an independent factor for mortality. Lower serum 25(OH)VD under the threshold of 25.6 and 25.2 ng/ml were significantly associated with a higher risk for all-cause and cardiovascular mortalities, respectively. However, no association was found between malignancy-specific mortality and serum 25(OH)VD.ConclusionSerum 25(OH)VD were identified as an independent factor associated with risks of all-cause and cardiovascular mortalities in patient with hyperlipidemia. Moreover, lower serum 25(OH)VD than 25.6 and 25.2 ng/mL were, respectively, associated with a gradual increase in a risk for all-cause and cardiovascular mortality in patients with hyperlipidemia, and therefore regular monitoring of VD levels and correction of VD deficiency is recommended in those patients.

The low-carbon retrofitting of industrial heritage communities is an important issue for reducing urban carbon emissions. Previous research on the judgment of heritage elements and carbon emission factors of industrial heritage communities lacked the construction of elements within the space, and the value judgment of conservation and the determination of low-carbon factors lacked a systematic network analysis. Carbon spatial networks as a systematic approach can systematically harmonize the contradictions between “conservation–transformation–low carbon” while considering the spatial and temporal carbon emissions of nodes. This research uses hierarchical analysis to analyze the value of heritage elements and locate them in space, then combine the elements that affect carbon activities in space to form carbon space nodes integrated with heritage conservation elements, and analyze the links between nodes to form a carbon space network. Then, this research uses a carbon spatial network to dissect the structure of carbon emissions, calculate the carbon activity at nodes, and reflect it into a parameterized platform to guide designers. After that, this research selected 16 industrial heritage communities in the severe cold region for the carbon activity measurement of carbon spatial network node elements in the operation stage and conducted a correlation analysis to obtain a correlation matrix model of node elements and carbon activities. Within the constraints of heritage element protection, the results show that the volume ratio, green area ratio, and building density of the carbon spatial network model have the greatest influence on its carbon performance, followed by porosity and road density. Through case simulation verification, the floor area ratio of industrial heritage communities should be controlled between 2.1–2.5, the number of residential building floors should be 7–14, the road network density should be 4.16–4.50%, the green space ratio should be 20–35%, and the porosity should be 35–45%. Taking the three major power road communities in Harbin as an example, retrofit measures were decided by reference to relevant parameter control intervals, resulting in a 21.1% reduction in energy consumption, an approximate 32.7% reduction in carbon emissions, and a 7.3% reduction in the annual percentage of hours in extreme hot and cold environments.

The escalation of the urban population and energy demands has exacerbated the carbon emission intensity at the operational stage of urban old communities. The spatial elements of the built environments comprising building groups, roads and landscape, and the spatial morphology of these elements, are endowed not only with human activities but also impact local microclimates and overall carbon emissions. Nonetheless, little attention has been paid to the correlation mechanism between the spatial morphology of the urban built environments and carbon emissions. In this paper, the aim is to combine carbon emissions simulation and statistical analysis to find the correlation between the spatial morphological indices and carbon emissions and to bridge the gaps. Thus, guided by the principles of urban energy modeling, this research adopts a parametric process of “information model construction–carbon emission simulation–statistical analysis”. First, taking 60 typical samples of an old community in Jinan, China, as objects, morphological indices such as density, texture and layout are analyzed through regression analysis to highlight their impacts on carbon emissions. Then, a carbon emission prediction model based on spatial morphological indices is established and verified. The results show that the floor area ratio (FAR), building coverage ratio (BCR), enclosure degree (ED), shape factor (SF) and average road aspect ratio (AS) have significant impacts on carbon emissions during the operational stage. Among these indices, the FAR and the ED are identified as the pivotal influencers. The findings confirm the important role of spatial morphological design of old communities in cold regions in improving urban carbon reduction potential, and they provide theoretical underpinnings and empirical data as references for urban morphology design formulated within the context of low-carbon objectives.

Abstract Background Patients with prostate cancer (PC) are at a high risk of developing secondary hematologic malignancies (SHMs) after radiation therapy (RT), while no study has assessed the relationship of different treatment modalities with the occurrence of SHMs after PC at early stage. This study aimed to investigate the risks of developing SHMs in patients with T1/T2 PC undergoing different treatment modalities. Methods Patients with T1/T2 PC were identified from the Surveillance, Epidemiology, and End Results database. Competing risk regression (CRR) model was performed to evaluate the hazard ratios (HRs) of developing SHMs. As SHMs scarcely occur, the relative risk (RR) analysis was employed to compare the risks of different treatment modalities associating with the development of SHMs. Results The CRR analysis showed that undergoing RT was associated with a higher risk of developing SHMs (external beam radiation therapy [EBRT]: HR = 1.21, 95% confidence interval [CI]: 1.10–1.34; radioactive implant [RI]: HR = 1.20, 95% CI: 1.06–1.36). As for different types of SHMs, EBRT, and RI were correlated with decreased risks of developing CLL (RR = 0.67, 0.72; 95% CI: 0.53–0.85, 0.54–0.96, respectively), but with the increased risks of developing NHL (RR = 1.18, 1.23; 95% CI: 1.02–1.35, 1.05–1.44, respectively); EBRT also showed increased risks of developing acute/ chronic myeloid leukemia (AML/CML, RR = 1.54, 1.56; 95% CI: 1.16–2.03,1.05–2.33, respectively); No increased risk of developing SHMs was detected in patients who only underwent prostatectomy. Conclusions Although RT was found to be associated with the increased risks of developing SHMs in patients with T1/T2 PC, this finding cannot be extended to diverse types of SHMs. RT was correlated with the increased risks of the development of NHL, AML, and CML, but with the decreased risk of developing CLL. Prostatectomy did not increase the risk of developing SHMs.

BackgroundAtrial fibrillation (AF) is a common arrhythmia, and its most severe and dreaded complication is stroke. The CHA2DS2-VASc score is currently recommended for stroke risk assessment in AF. We aimed to explore the relationship between atrial FDG uptake and stroke and whether atrial FDG uptake could provide incremental value above the CHA2DS2-VAS score to predict stroke in AF by 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT).Materials and MethodsFrom September 2017 to December 2020, we retrospectively enrolled 230 patients (115 with AF and 115 without AF as the non-AF group, matched for the date of PET/CT examination and the basic characteristics of the patient) who underwent 18F-FDG PET/CT due to tumor screening or preoperative staging after prolonged fasting and followed up for at least 12 months from the date of PET/CT examination; the endpoint event is the occurrence of stroke. We visually and quantitatively analyzed 18F-FDG uptake in the right and left atria (RA/LA), right and left atrial appendage (RAA/LAA), right and left ventricle (RV/LV), and collected clinical features. In addition, according to the endpoint event (stroke), the enrolled population was divided into the stroke group and non-stroke group, and relevant clinical features and atrial FDG uptake indicators of the two groups were analyzed. Univariate and multivariate Cox regression analyzes were used to analyze the risk factors of stroke events. The Kaplan–Meier survival curve of atrial FDG uptake was drawn, and the log-rank method was used to compare the differences in the survival curves of the two groups. Receiver operating characteristic (ROC) curves were used to examine the discriminatory power of atrial FDG uptake in predicting stroke and determine whether the addition of atrial FDG uptake improves predictive value beyond the CHA2DS2-VASc score for stroke.ResultsIn the AF group, more than half of patients had RA FDG uptake and one-fifth had LA FDG uptake, while one patient had RA FDG uptake and two patients had LA FDG uptake in the non-AF group. In quantitative analysis, the maximum standardized uptake value (SUVmax) of the RA and LA in the AF group was significantly higher than that of the non-AF group (all P < 0.001). We followed up the patients for 28 ± 10 months, and finally, 31 patients had stroke. In the stroke group, atrial fibrillation, RA SUVmax, RAA SUVmax, LAA SUVmax, age ≥ 75 years, and left atrial dilation were significantly higher than those of the non-stroke group (all P < 0.05). Multivariate Cox regression analysis showed that high RA SUVmax (RA SUVmax ≥ 2.62) was an independent risk factor for stroke (HR = 4.264, 95% CI 1.368–13.293, P = 0.012). By using the log-rank test, patients with high RA SUVmax had a significantly higher incidence of stroke compared with patients with low RA SUVmax (P < 0.001). Addition of high RA SUVmax to the CHA2DS2-VASc score could predict stroke more effectively, with a larger AUC 0.790 (P < 0.001).ConclusionThis study found a significant correlation between atrial FDG uptake and AF, especially in RA. Meanwhile, RA FDG uptake is an independent risk factor for stroke, and patients with high RA SUVmax have a significantly higher risk of stroke. Moreover, RA FDG uptake improves prediction of stroke above the CHA2DS2-VASc score in patients with AF.

Abstract Background Kidney cancer (KC) is associated with cardiovascular regulation disorder and easily leads to cardiovascular and cerebrovascular death (CCD), which is one of the major causes of death in patients with KC, especially those with T1/2 status. However, few studies have treated CCD as an independent outcome for analysis. We aimed to identify and evaluate the key factors associated with CCD in patients with T1/2 KC by competing risk analysis and compared these risk factors with those associated with kidney cancer-specific death (KCD) to offer some information for clinical management. Methods A total of 45,117 patients diagnosed with first primary KC in T1/2 status were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were divided into the CCD group (n = 3087), KCD group (n = 3212), other events group (n = 6312) or alive group (n = 32,506). Patients’ characteristics were estimated for their association with CCD or KCD by a competing risk model. Pearson’s correlation coefficient and variance inflation factor (VIF) were used to detect collinearity between variables. Factors significantly correlated with CCD or KCD were used to create forest plots to compare their differences. Results The competing risk analysis showed that age at diagnosis, race, AJCC T/N status, radiation therapy, chemotherapy and scope of lymph node represented different relationships to CCD than to KCD. In detail, age at diagnosis (over 74/1–50: HR = 9.525, 95% CI: 8.049–11.273), race (white/black: HR = 1.475, 95% CI: 1.334–1.632), AJCC T status (T2/T1: HR = 0.847, 95% CI: 0.758–0.946) and chemotherapy (received/unreceived: HR = 0.574, 95% CI: 0.347–0.949) were correlated significantly with CCD; age at diagnosis (over 74/1–50: HR = 3.205, 95% CI: 2.814–3.650), AJCC T/N status (T2/T1: HR = 2.259, 95% CI: 2.081–2.451 and N1/N0:HR = 3.347, 95% CI: 2.698–4.152), radiation therapy (received/unreceived: HR = 2.552, 95% CI: 1.946–3.346), chemotherapy (received/unreceived: HR = 2.896, 95% CI: 2.342–3.581) and scope of lymph nodes (1–3 regional lymph nodes removed/none: HR = 1.378, 95% CI: 1.206–1.575) were correlated significantly with KCD. Conclusions We found that age at diagnosis, race, AJCC T status and chemotherapy as the independent risk factors associated with CCD were different from those associated with KCD.

Abstract Background To establish and validate 18F-fluorodeoxyglucose (18F-FDG) PET/CT-based radiomics model and use it to predict the intermediate-high risk growth patterns in early invasive adenocarcinoma (IAC). Methods Ninety-three ground-glass nodules (GGNs) from 91 patients with stage I who underwent a preoperative 18F-FDG PET/CT scan and histopathological examination were included in this study. The LIFEx software was used to extract 52 PET and 49 CT radiomic features. The least absolute shrinkage and selection operator (LASSO) algorithm was used to select radiomic features and develop radiomics signatures. We used the receiver operating characteristics curve (ROC) to compare the predictive performance of conventional CT parameters, radiomics signatures, and the combination of these two. Also, a nomogram based on conventional CT indicators and radiomics signature score (rad-score) was developed. Results GGNs were divided into lepidic group (n = 18) and acinar-papillary group (n = 75). Four radiomic features (2 for PET and 2 for CT) were selected to calculate the rad-score, and the area under the curve (AUC) of rad-score was 0.790, which was not significantly different as the attenuation value of the ground-glass opacity component on CT (CTGGO) (0.675). When rad-score was combined with edge (joint model), the AUC increased to 0.804 (95% CI [0.699–0.895]), but which was not significantly higher than CTGGO (P = 0.109). Furthermore, the decision curve of joint model showed higher clinical value than rad-score and CTGGO, especially under the purpose of screening for intermediate-high risk growth patterns. Conclusion PET/CT-based radiomics model shows good performance in predicting intermediate-high risk growth patterns in early IAC. This model provides a useful method for risk stratification, clinical management, and personalized treatment.

Abstract Background Nonalcoholic fatty liver disease (NAFLD) is a multisystem disease that affects the liver and a variety of extra-hepatic organ systems. This study aimed to investigate the relationship between hepatic steatosis and glucose metabolism in liver and extra-hepatic tissues and organs. Methods The whole body 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) images of 191 asymptomatic tumor screening patients were retrospectively analyzed. Patients with the ratio of spleen/liver CT densities > 1.1 were defined to have NAFLD, and their clinical symptoms, laboratory markers, FDG uptake in a variety of tissues and organs including heart, mediastinal blood pool, liver, spleen, pancreas, and skeletal muscle, as well as abdominal adipose tissue volumes including visceral adipose tissue (VAT) volume and subcutaneous adipose tissue (SAT) volume were compared with those of the non-NAFLD patients and used to analyze the independent correlation factors of NAFLD. Results Among the 191 patients, 33 (17.3%) were NAFLD, and 158 (82.7%) were non-NAFLD. There was no significant correlation between the mean standardized uptake value (SUVmean) and CT density of liver as well as the ratio of spleen/liver CT densities. Hepatic steatosis, but not FDG intake, was more significant in NAFLD patients with abnormal liver function than those with normal liver function. Compared with the non-NAFLD patients, NAFLD patients had significantly reduced myocardial glucose metabolism, but significantly increased mediastinal blood pool, spleen SUVmean and abdominal adipose tissue volumes (including VAT and SAT volumes) (P

To investigate whether the maximum standardized uptake value (SUVmax) of 18F-deoxyglucose (FDG) PET imaging can increase the diagnostic efficiency of CT radiomics-based prediction model in differentiating benign and malignant pulmonary ground-glass nodules (GGNs). We retrospectively collected 190 GGNs from 165 patients who underwent 18F-FDG PET/CT examination from January 2012 to March 2020. Propensity score matching (PSM) was performed to select GGNs with similar baseline characteristics. LIFEx software was used to extract 49 CT radiomic features, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to select parameters and establish the Rad-score. Logistic regression analysis was performed combined with semantic features to construct a CT radiomics model, which was combined with SUVmax to establish the PET + CT radiomics model. Receiver operating characteristic (ROC) was used to compare the diagnostic efficacy of different models. After PSM at 1:4, 190 GGNs were divided into benign group (n = 23) and adenocarcinoma group (n = 92). After texture analysis, the Rad-score with three CT texture features was constructed for each nodule. Compared with the Rad-score and CT radiomics model (AUC: 0.704 (95%CI: 0.562-0.845) and 0.908 (95%CI: 0.842-0.975), respectively), PET + CT radiomics model had the best diagnostic efficiency (AUC: 0.940, 95%CI: 0.889-0.990), and there was significant difference between each two of them (P = 0.001-0.030). SUVmax can effectively improve CT radiomics model performance in the differential diagnosis of benign and malignant GGNs. PET + CT radiomics might become a noninvasive and reliable method for differentiating of GGNs.

Currently, the mechanized harvesting method of Cyperus esculentus is mainly based on rotary excavation, but there are problems such as high working resistance, high damage rate, and high buried fruit rate in the working process. This paper focuses on the analysis of the movement trajectory of the positive-rotating and counter-rotating Cyperus esculentus excavation device, establishes a agglomerate model of soil-Cyperus esculentus tuber-Cyperus esculentus root system-mechanism, and conducts discrete element simulation tests on Cyperus esculentus agglomerates under different soil layers. According to Expert test optimization, the optimal structural parameters of the counter-rotating blade are determined: the radius of gyration is 151 mm, the inclination angle of the cutting edge is 42.5°, and the working width is 318 mm. The comparative test of the positive-rotating rotary tillage method under the optimal structural parameters shows that the working resistance is reduced by 11.25%, and the torque of the tool shaft is reduced by 16.11%, which proves that the designed anti-rotation excavation structure has the effect of reducing resistance. To further test the harvesting performance of the Cyperus esculentus excavation device, field harvesting tests were conducted, and the results showed that the buried fruit rate of the counter-rotating excavation device was reduced by 11.6%, and the damage rate was reduced by 6.1% year-on-year. This study shows that the design of the counter-rotating excavation device can further improve the harvesting performance of Cyperus esculentus based on reduced resistance harvesting and meet the requirements of Cyperus esculentus harvesting.

When peanuts are harvested, the high rate of pod crush and pods leakage are the main problems in the current peanut fruit picking process. Optimized peanut picking rollers help to improve peanut harvesting efficiency. This paper investigates the fruit picking system of a three-monopoly, six-row semi-feeding peanut combine harvester, in order to reduce the rate of crush and leakage of peanut pods during the picking process. Firstly, this article specifies the structure and basic parameters of peanut picking pairs of rollers. Secondly, this paper combines JKR (Johnson-Kendall-Roberts) model theory, crash model simulation analysis, a field test, and other methods. Motion and force analysis are presented in detail for the peanut picking mechanism and associated harvesting components. The optimum clamping chain speed, the angle of installation of the picking rollers to the clamping chain, and the picking rollers’ speed are determined. A three-factor, three-level regression orthogonal combination test was designed to obtain regression models for pod crushed and pods leakage rate. The regression model’s response surface analysis concluded that when the clamping chain speed is 0.84–1.2 m/s, the fruit picking roller angle is 10°–11.2° and the fruit picking roller speed is 442 r/min–500 r/min. It is the optimal working parameter for the three-monopoly six-row peanut combine harvester. At this point, the peanut harvesting requirements are met, and the overall performance is significantly improved. This paper lays the foundation for the development of the semi-feeding peanut picking system.

To explore the association between 18F-FDG PET/CT-based SUV index and malignant risk of persistent ground-glass nodules (GGNs). We retrospectively analyzed a total of 166 patients with GGN who underwent PET/CT examination from January 2012 to October 2019. There were 113 women and 53 men, with an average age of 60.8 ± 9.1 years old. A total of 192 GGNs were resected and confirmed by pathology, including 22 in benign group and 170 in adenocarcinoma group. They were divided into three groups according to SUV index tertiles: Tertile 1 (0.14–0.54), Tertile 2 (0.55–1.17), and Tertile 3 (1.19–6.78), with 64 GGNs in each group. The clinical and imaging data of all patients were collected and analyzed. After adjusting for the potential confounding factors, we found that the malignancy risk of GGN significantly decreased as the SUV index increased (OR, 0.245; 95%CI, 0.119–0.504; P

Background Epicardial adipose tissue may be associated with the pathogenesis of coronary artery disease (CAD), but its effect on obstructive CAD risk is uncertain. Therefore, we aimed to examine the relationship between epicardial adipose tissue and obstructive CAD in Chinese patients with suspected CAD. Methods and Results The present study enrolled 194 consecutive inpatients with suspected CAD who underwent both noncontrast computed tomography and coronary angiography. We measured epicardial fat volume (EFV) and evaluated its association with obstructive CAD, which was defined as coronary stenosis severity ≥70%. Overall, 44.3% patients had obstructive CAD and tend to have higher EFV. Age, body mass index, triglycerides, incidence of hypertension, and hyperlipidemia were higher across tertiles of EFV (P for trend

Leaf size is an important agronomic trait directly affecting yield in rice, and thus understanding the genes determining leaf size is important in breeding. In this study, one Leaf Mutant 7 (lm7) with small leaf size was isolated using ethyl methane sulphonate (EMS) mutagenesis from the japonica Zhenggeng 1925. MutMap by whole genome resequencing of phenotypic bulks revealed that LM7 is likely located in the 133 kb region on chromosome 7 using F2 population from a cross between lm7 and wild-type (WT) Zhenggeng 1925. The candidate gene encoding heat shock protein OsHSP40 for LM7 was functionally validated. Disruption of this gene in Oshsp40 mutants significantly reduced the leaf size compared with that of WT in rice. Microscopic examination showed that OsHSP40 modulated leaf size via regulating the veins formation and cell size/cell number. Nucleotide diversity analysis indicated that a single nucleotide polymorphism (SNP) variation of C to T in the coding region of OsHSP40 may cause small leaves among rice accessions. Therefore, the natural variation of OsHSP40 contributing to leaf size might be useful for rice breeding.

Background This study was performed to characterize the metabolic, functional, and structural cardiac changes in a canine model of radiation‐induced heart disease by serial in vivo imaging and ex vivo analyses. Methods and Results Thirty‐six dogs were randomly assigned to control or irradiated groups at 3 time points (months 3, 6, and 12 after radiation; each group comprised 6 dogs). The left anterior myocardium of dogs in irradiated groups was irradiated locally with a single dose of 20‐Gy X‐ray. The irradiated myocardial regions showed increased myocardial uptake of 18F‐FDG (18F‐fludeoxyglucose) in the irradiated beagles, but the increased uptake area decreased at months 6 and 12 compared with month 3 after radiation. Abnormality of myocardial perfusion and cardiac function were detected at month 6 after radiation. Compared with the control groups, the protein expression of GLUT4 (glucose transporter 4) was upregulated in the irradiated groups, correlating with significantly decreased CPT1 (carnitine acyltransferase 1) expression. Mitochondria degeneration, swelling, and count reduction in the irradiated groups were observed. The difference in CD68 of macrophage markers and the inflammatory cytokines (IL‐6 [interleukin 6], TNF‐α [tumor necrosis factor α]) between the irradiation and control groups was not significant. Furthermore, the progressive aggravation of apoptosis and fibrosis was displayed. Conclusions Elevated 18F‐FDG uptake occurred after irradiation and subsequently led to ventricular perfusion defects and dysfunction. The process was associated with myocardial metabolic substrate remodeling, cardiac muscle cell apoptosis, and myocardial fibrosis rather than inflammation.

Abstract Background In diabetes, dysregulated substrate utilization and energy metabolism of myocardium can lead to heart failure. To examine the dynamic changes of myocardium, most of the previous studies conducted dynamic myocardial PET imaging following euglycemic-hyperinsulinemic clamp, which involves complicated procedures. In comparison, the whole-body 18F-FDG PET/CT scan is a simple and widely used method. Therefore, we hope to use this method to observe abnormal myocardial glucose metabolism in diabetes and determine the influencing factors. Methods We retrospectively analyzed PET/CT images of 191 subjects from our medical examination center. The levels of FDG uptake in myocardium were visually divided into 4 grades (Grade 0–3, from low to high). The differences in clinical and metabolic parameters among diabetes mellitus (DM), impaired fasting glucose (IFG), and normal fasting glucose (NFG) groups were analyzed, as well as their associations with myocardial FDG uptake. Results Compared with NFG and IFG groups, DM group had more cardiovascular-related risk factors. The degree of myocardial FDG uptake was significantly decreased in DM group; when myocardial FDG uptake ≤ Grade 1, the sensitivity of DM prediction was 84.0%, and the specificity was 58.4%. Univariate analysis showed that the myocardial FDG uptake was weakly and negatively correlated with multiple metabolic-related parameters (r = − 0.173~ − 0.365, P