Effect of Resin Content on the Structure, Water Resistance and Mechanical Properties of High-Density Bamboo Scrimbers.

Bamboo scrimber is acknowledged for its eco-friendly potential as a structural material. Its properties are significantly affected by both its density and resin content, but the effect of resin content on the properties under high density is not yet known. In this study, the microstructure, water resistance, mechanical properties, and thermal stability of bamboo scrimbers with varying resin content at a density of 1.30 g/cm3 were investigated. The results unearthed that phenolic resin assisted in the densification of bamboo cells during hot pressing, and a higher resin content could effectively reduce the cracks in the scrimber. The inherent cellulose I structure remained unaffected, but an increase in resin content led to a noticeable decline in crystallinity. Additionally, an increase in resin content pronouncedly improved the water resistance and dimensional stability of bamboo scrimbers. The water absorption and thickness swelling were as low as 9.67% and 7.62%, respectively. The modulus of rupture (MOR) exhibited a marginal increase with the amount of resin, whereas the compressive strength and short-beam shearing strength first increased and then decreased. Their peak strengths were 327.87 MPa at a resin content of 15 wt.%, and 168.85 MPa and 25.96 MPa at 11 wt.%, respectively. However, phenolic resin accelerated the thermal decomposition of bamboo scrimbers, and more resin worsened the thermal stability. These research outcomes offer a dual advantage, providing both a theoretical foundation and concrete data that can inform the production and practical application of high-density bamboo scrimbers.

Association of epicardial fat volume with subclinical myocardial damage in patients with type 2 diabetes mellitus.

Background: In type 2 diabetes mellitus (T2DM) patients, left ventricular systolic dyssynchrony (LVSD) with normal left ventricular ejection fraction (LVEF) and normal myocardial perfusion could referred to as subclinical myocardial damage, which is difficult to diagnose at an early stage. Epicardial adipose tissue, a distinctive heart-specific visceral fat, is closely related to various cardiovascular diseases. The objective of this study was to investigate the correlation between epicardial fat volume (EFV) and subclinical myocardial damage in T2DM patients. Methods: This retrospective cross-sectional study included 117 T2DM patients with normal myocardial perfusion by single photon emission computed tomography-computed tomography (SPECT-CT) and normal LVEF by echocardiography. The study was conducted from January 2018 to December 2022. Patient data were collected through electronic medical records including basic patient information, medical history, laboratory tests, and medication data. The EFV was quantified through a non-contrast CT scan. Quantitative indicators of LVSD including phase standard deviation (PSD) and phase histogram bandwidth (PBW) were obtained through phase analysis of the gated rest myocardial perfusion imaging (MPI). Additionally, 83 healthy individuals at the same time were selected to gain the reference threshold of LVSD indicators (13.1° for PSD and 37.6° for PBW). Univariate and multivariable logistic regression models were performed to analyze factors influencing LVSD. A generalized additive model (GAM) was applied to explore the relationship between EFV and LVSD. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of EFV for LVSD. Results: Among all patients, 32 (27.4%) patients had LVSD. Compared with the non-LVSD group, the body mass index (BMI) and EFV were higher in the LVSD group (25.83±2.66 vs. 23.94±3.13 kg/m2; 142.41±44.17 vs. 108.01±38.24 cm3, respectively, both P<0.05). Multivariate regression analysis revealed that EFV was independently associated with LVSD [odds ratio (OR) =1.19; 95% confidence interval (CI): 1.06-1.34; P=0.003]. Age, BMI, incidence of hypertension, and LVSD were increased with tertiles of EFV (all P<0.05). The GAM indicated a linear association between EFV and LVSD. The ROC curve analysis concluded that the area under the curve (AUC) of EFV for predicting subclinical myocardial damage in T2DM patients was 0.732 (95% CI: 0.633-0.831, P<0.001), with the optimal threshold of 122.26 cm3, sensitivity of 71.9%, and specificity of 69.4%. Conclusions: EFV is an independent risk factor for LVSD in T2DM patients with normal LVEF and normal MPI, which could potentially serve as a novel imaging marker and a potential therapeutic target for subclinical myocardial damage.

Effect of tannic/gallic acid-iron dyeing treatment on surface color and light fastness of bamboo veneer.

Currently, the quest for bamboo materials with high color fastness, rich colors and environmental friendliness is rapidly rising due to its potential applications in construction, furniture and decoration. However, finding an easy-to-operate and environmentally friendly dye for bamboo is a necessary task because of the difficulty in treating the dyeing waste liquid of acid dyes and the complexity of the production process of reactive dyes.Five formulations involving metal polyphenol complexes were employed to straightforwardly produce eco-friendly dyed bamboo and the impact of various formulations on the light aging resistance of the dyed veneers was examined. The results indicated that the light resistance of bamboo veneer dyed with the solution containing only FeSO4·7H2O and tannic acid reached level 4, surpassing the undyed bamboo veneer by three levels. The mechanism of enhanced lightfastness of dyed bamboo veneer was elucidated by XPS analysis. The polyphenol iron complex serves a dual purpose: it absorbs ultraviolet rays and scavenges free radicals within the system. Additionally, it reduced the oxidation of phenolics in the substrate, transforming them into dark-colored quinone structures. This process enhanced the light-aging resistance of the finishing materials. Therefore, this work provides a simple and environmentally friendly method for changing the color of bamboo and provides a new idea for the selection of dyes for bamboo dyeing in actual production.

The relationship between right atrial wall inflammation and poor prognosis of atrial fibrillation based on 18F-FDG positron emission tomography/computed tomography.

Background: Atrial fibrillation (AF) has been identified to increase stroke risk, even after oral anticoagulants (OACs), and the recurrence rate is high after radiofrequency catheter ablation (RFCA). Inflammation is an essential factor in the occurrence and persistence of AF. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) is an established molecular imaging modality to detect local inflammation. We aimed to investigate the relationship between atrial inflammatory activity and poor prognosis of AF based on 18F-FDG PET/CT. Methods: A total of 204 AF patients including 75 with paroxysmal AF (ParAF) and 129 with persistent AF (PerAF) who underwent PET/CT before treatment were enrolled in this prospective cohort study. Clinical data, electrocardiograph (ECG), echocardiography, and cardiac 18F-FDG uptake were collected. Follow-up information was obtained from patient clinical case notes or telephone reviews, with the starting point being the time of PET/CT scan. The follow-up deadline was either the date of AF recurrence after RFCA, new-onset stroke, or May 2023. Cox proportional hazards regression models were used to identify predictors of poor prognosis and hazard ratios (HRs) with 95% confidence intervals (CIs) was calculated. Results: Median follow-up time was 29 months [interquartile range (IQR), 22-36 months]. Poor prognosis occurred in 52 patients (25.5%), including 34 new-onset stroke patients and 18 recrudescence after RFCA. The poor prognosis group had higher congestive heart failure, hypertension, age ≥75 years (doubled), diabetes mellitus, prior stroke or transient ischemic attack (TIA) or thromboembolism (doubled), vascular disease, age 65-74 years, sex category (female) (CHA2DS2-VASc) score [3.0 (IQR, 1.0-3.75) vs. 2.0 (IQR, 1.0-3.0), P=0.01], right atrial (RA) wall maximum standardized uptake value (SUVmax) (4.13±1.82 vs. 3.74±1.58, P=0.04), higher percentage of PerAF [39 (75.0%) vs. 90 (59.2%), P=0.04], left atrial (LA) enlargement [45 (86.5%) vs. 104 (68.4%), P=0.01], and RA wall positive FDG uptake [40 (76.9%) vs. 79 (52.0%), P=0.002] compared with the non-poor prognosis group. Univariate and multivariate Cox proportional hazard regression analysis concluded that only CHA2DS2-VASc score (HR, 1.29; 95% CI: 1.06-1.57; P=0.01) and RA wall positive FDG uptake (HR, 2.68; 95% CI: 1.10-6.50; P=0.03) were significantly associated with poor prognosis. Conclusions: RA wall FDG positive uptake based on PET/CT is tightly related to AF recurrence after RFCA or new-onset stroke after antiarrhythmic and anticoagulation treatment.

Right atrial wall inflammation detected by 18F-FDG PET/CT may be significantly associated with persistent atrial fibrillation: a prospective case-control study.

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 < 0.001; SUVmax: 4.10(3.20-4.90) VS. 2.60(2.40-3.10), P < 0.001]. Multivariate logistic regression analyses demonstrated that RA wall SUVmax was the independent influencing factor of PerAF (OR = 1.80, 95%CI 1.02-3.18, P = 0.04). In 22 AF patients with RA wall positive FDG uptake (HFLC+Fast), the "HFLC+Fast+Heparin" method did not significantly change RA wall FDG uptake evaluated by either quantitative analysis or visual analysis. High CHA2DS2-VASc score group had higher RA wall 18F-FDG uptake [3.35 (2.70, 4.50) vs, 2.8 (2.4, 3.1) P = 0.01]. CONCLUSIONS: RA wall FDG positive uptake was present mainly in PerAF. A higher RA wall 18F-FDG uptake was an independent influencing factor of PerAF. RA wall FDG uptake based on 18F-FDG PET/CT may indicate pathological inflammation. TRIAL REGISTRATION: http://www.chictr.org.cn , ChiCTR2000038288.

Full-Wood Utilization Strategy toward a Directional Luminescent Solar Concentrator.

Luminescent solar concentrators (LSCs) have proven to be highly effective in enhancing the conversion efficiency of photovoltaic (PV) cells. However, the traditional LSCs always suffer from self-absorption and escape the losses of luminescence. To these challenges, this study presents an ingenious all-wood-based LSC (W-LSC) with directional light-concentrating capabilities. By converting lignin into fluorescent carbon quantum dots (CQDs) and integrating them into transparent cellulose channels in delignified wood, we achieved efficient directional luminescence transmission in the W-LSC is achieved. The synthesized lignin-based CQDs (L-CQDs) exhibited a large Stokes shift (0.63 eV) and a bright yellow emission (540 nm). The prepared W-LSC possessed an external optical efficiency (ηopt) along the longitudinal (L) direction of 4.60% under a low irradiation intensity (40 mW·cm-2). Besides, contributed to the low thermal conductivity (0.300 W·m-1·K-1) of wood, the W-LSC maintained an ηopt of 4.03% at a temperature of 65 °C. Furthermore, the W-LSC demonstrated high tensile strength (424 MPa) and light transmission (85%). By leveraging the advantages of wood, this approach provides a different solution for enhancing solar energy utilization and advancing sustainable building.

Epicardial fat volume, an independent risk factor for major adverse cardiovascular events, had an incremental prognostic value to myocardial perfusion imaging in Chinese populations with suspected or known coronary artery disease with a normal left ventricular ejection fraction.

Background: Most 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 results: We 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 < 0.000] and abnormal MPI (HR: 1.8, 95% CI: 1.1-2.8, P = 0.010) were independent risk factors for MACE. The event-free survival of patients with high EFV was significantly lower than that of the low EFV group (log-rank test P < 0.001). In the subgroup with normal MPI, high EFV was associated with reduced event-free survival (log-rank P < 0.01), with a higher annualized event rate (8.3% vs. 1.9%). Adding high EFV to MPI could predict MACEs more effectively, with a higher concordance index (0.56-0.69, P < 0.01), higher global chi square (7.2-41.4, P < 0.01), positive integrated discrimination improvement (0.10, P < 0.01), and net reclassification index (0.37, P < 0.01). Conclusions: In Chinese populations with suspected or known CAD with normal LVEF, high EFV was an independent risk factor for MACE after adjusting for traditional risk factors, CAC and MPI. In subgroups with normal MPI, EFV could also improve risk stratification. Adding EFV to MPI had an incremental value for predicting MACE.

Lignocellulosic Biomass-Based Carbon Dots: Synthesis Processes, Properties, and Applications.

Carbon dots (CDs), a new type of carbon-based fluorescent nanomaterial, have attracted widespread attention because of their numerous excellent properties. Lignocellulosic biomass is the most abundant renewable natural resource and possesses broad potential to manufacture different composite and smart materials. Numerous studies have explored the potential of using the components (such as cellulose, hemicellulose, and lignin) in lignocellulosic biomass to produce CDs. There are few papers systemically aiming in the review of the state-of-the-art works related to lignocellulosic biomass-derived CDs. In this review, the significant advances in synthesis processes, formation mechanisms, structural characteristics, optical properties, and applications of lignocellulosic biomass-based CDs such as cellulose-based CDs, hemicellulose-based CDs and lignin-based CDs in latest research are reviewed. In addition, future research directions on the improvement of the synthesis technology of CDs using lignocellulosic biomass as raw materials to enhance the properties of CDs are proposed. This review will serve as a road map for scientists engaged in research and exploring more applications of CDs in different science fields to achieve the highest material performance goals of CDs.

Machine learning to predict hemodynamically significant CAD based on traditional risk factors, coronary artery calcium and epicardial fat volume.

We sought to establish an explainable machine learning (ML) model to screen for hemodynamically significant coronary artery disease (CAD) based on traditional risk factors, coronary artery calcium (CAC) and epicardial fat volume (EFV) measured from non-contrast CT scans. 184 symptomatic inpatients who underwent Single Photon Emission Computed Tomography/Myocardial Perfusion Imaging (SPECT/MPI) and Invasive Coronary Angiography (ICA) were enrolled. Clinical and imaging features (CAC and EFV) were collected. Hemodynamically significant CAD was defined when coronary stenosis severity ≥ 50% with a matched reversible perfusion defect in SPECT/MPI. Data was randomly split into a training cohort (70%) on which five-fold cross-validation was done and a test cohort (30%). The normalized training phase was preceded by the selection of features using recursive feature elimination (RFE). Three ML classifiers (LR, SVM, and XGBoost) were used to construct and choose the best predictive model for hemodynamically significant CAD. An explainable approach based on ML and the SHapley Additive exPlanations (SHAP) method was deployed to generate individual explanation of the model's decision. In the training cohort, hemodynamically significant CAD patients had significantly higher age, BMI and EFV, higher proportions of hypertension and CAC comparing with controls (P all < .05). In the test cohorts, hemodynamically significant CAD had significantly higher EFV and higher proportion of CAC. EFV, CAC, diabetes mellitus (DM), hypertension, and hyperlipidemia were the highest ranking features by RFE. XGBoost produced better performance (AUC of 0.88) compared with traditional LR model (AUC of 0.82) and SVM (AUC of 0.82) in the training cohort. Decision Curve Analysis (DCA) demonstrated that XGBoost model had the highest Net Benefit index. Validation of the model also yielded a favorable discriminatory ability with the AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of 0.89, 68.0%, 96.8%, 94.4%, 79.0% and 83.9% in the XGBoost model. A XGBoost model based on EFV, CAC, hypertension, DM and hyperlipidemia to assess hemodynamically significant CAD was constructed and validated, which showed favorable predictive value. ML combined with SHAP can offer a transparent explanation of personalized risk prediction, enabling physicians to gain an intuitive understanding of the impact of key features in the model.

18F-FDG PET-CT for the prediction of mortality in patients with dermatomyositis and without malignant tumors: a pilot study.

Background: 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) is typically used to screen malignancy in patients with dermatomyositis (DM). The aim of this study was to investigate the value of using PET-CT in assessing the prognosis of patients with DM and without malignant tumors. Methods: A total of 62 patients with DM who underwent 18F-FDG PET-CT were enrolled in the retrospective cohort study. Clinical data and laboratory indicators were obtained. The muscle max standardized uptake value (SUVmax), splenic SUVmax, target-to-background ratio (TBR) of the aorta, pulmonary highest value (hv)/SUVmax, epicardial fat volume (EFV), and coronary artery calcium (CAC) were measured using 18F-FDG PET-CT. The follow-up was conducted until March 2021, and the endpoint was death from any cause. Univariable and multivariable Cox regression analyses were used to analyze prognostic factors. The survival curves were produced with the Kaplan-Meier method. Results: The median duration of follow-up was 36 [interquartile range (IQR), 14-53] months. The survival rates were 85.2% and 73.4% for 1 and 5 years, respectively. A total of 13 (21.0%) patients died during a median follow-up of 7 (IQR, 4-15.5) months. Compared with the survival group, the death group had significantly higher levels of C-reactive protein [CRP; median (IQR), 4.2 (3.0, 6.0) vs. 6.30 (3.7, 22.8)], hypertension [7 (14.3%) vs. 6 (46.2%)], interstitial lung disease [ILD; 26 (53.1%) vs. 12 (92.3%)], positive anti-Ro52 antibody [19 (38.8%) vs. 10 (76.9%)], pulmonary FDG uptake [median (IQR), 1.8 (1.5, 2.9) vs. 3.5 (2.0, 5.8)], CAC [1 (2.0%) vs. 4 (30.8%)], and EFV [median (IQR), 74.1 (44.8, 92.1) vs. 106.5 (75.0, 128.5)] (all P values <0.001). Univariable and multivariable Cox analyses identified high pulmonary FDG uptake [hazard ratio (HR), 7.59; 95% confidence interval (CI), 2.08-27.76; P=0.002] and high EFV (HR, 5.86; 95% CI, 1.77-19.42; P=0.004) as independent risk factors for mortality. The survival rate was significantly lower in patients with the concurrent presence of high pulmonary FDG uptake and high EFV. Conclusions: Pulmonary FDG uptake and EFV detected with PET-CT were independent risk factors for death in patients with DM and without malignant tumors. Patients with the concurrent presence of high pulmonary FDG uptake and high EFV had a worse prognosis compared with patients with 1 or neither of these two risk factors. Early treatment should be applied in patients with concurrent presence of high pulmonary FDG uptake and high EFV to improve the survival rate.

Association of epicardial adipose tissue volume with increased risk of hemodynamically significant coronary artery disease.

Background: Epicardial adipose tissue (EAT) is closely related to coronary artery disease (CAD). Hemodynamically significant CAD has a worse prognosis and is more likely to benefit from revascularization. However, the specific relationship between EAT and hemodynamically significant CAD remains unclear. Methods: A total of 164 inpatients received single-photon emission computerized tomography-myocardial perfusion imaging (SPECT/MPI) and coronary angiography (CAG) between March 2018 and October 2019 at the Third Affiliated Hospital of Soochow University were enrolled in the retrospective cross-sectional study. Data on body mass index (BMI), hypertension, hyperlipidemia, diabetes mellitus (DM), active smoking, and symptoms were gathered. Epicardial fat volume (EFV) and coronary artery calcium (CAC) were quantified by noncontrast computed tomography (CT). Hemodynamically significant CAD was defined by coronary stenosis severity ≥50% with reversible perfusion defects in the corresponding areas of SPECT/MPI. Results: A total of 37.8% of patients had hemodynamically significant CAD. Age and BMI increased with tertiles of EFV (P for trend =0.009 and P<0.001). The ratios of hemodynamically significant CAD in EFV from low to high were 16.4%, 37.0%, and 60.0%, respectively (P for the trend <0.001). In univariate regression analysis, EFV was associated with hemodynamically significant CAD [odds ratio (OR) per 10 cm3 =1.36; 95% confidence interval (CI): 1.20-1.55; P<0.001]. After correcting for traditional risk factors and CAC, EFV was firmly linked to hemodynamically significant CAD (OR per 10 cm3 =1.53; 95% CI: 1.25-1.88; P<0.001). With an increasing trend in EFV for the tripartite groups, the likelihood of hemodynamically significant CAD increased significantly (P for trend <0.001). There was a saturation effect between EFV and hemodynamically significant CAD according to the generalized additive model (GAM). When EFV <134.43 cm3, EFV was linearly correlated with hemodynamically significant CAD (OR per 10 cm3 =2.06; 95% CI: 1.45-2.94; P<0.001). When EFV ≥134.43 cm3, the hemodynamically significant CAD risk was steeper and gradually reached saturation. Hypertension affected the relationship between EFV and hemodynamically significant CAD (P for the interaction =0.02) with an interaction effect. Conclusions: There was a robust relationship between EFV and hemodynamically significant CAD. After adjustment for confounders, we found that the risk of hemodynamically significant CAD onset increased nonlinearly for EFV above 134.4 cm3. This refined understanding of the relationship is helpful for the accurate clinical prediction of hemodynamically significant CAD.

Detecting obstructive coronary artery disease with machine learning: rest-only gated single photon emission computed tomography myocardial perfusion imaging combined with coronary artery calcium score and cardiovascular risk factors.

Background: The rest-only single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has low diagnostic performance for obstructive coronary artery disease (CAD). Coronary artery calcium score (CACS) is strongly associated with obstructive CAD. The aim of this study was to investigate the performance of rest-only gated SPECT MPI combined with CACS and cardiovascular risk factors in diagnosing obstructive CAD through machine learning (ML). Methods: We enrolled 253 suspected CAD patients who underwent the 1-stop rest-only SPECT MPI and computed tomography (CT) scan due to stress test-related contraindications. Myocardial perfusion and wall motion were assessed using quantitative perfusion SPECT + quantitative gated SPECT (QPS + QGS) automated quantification software. The Agatston algorithm was used to calculate CACS. The clinical data of patients, including cardiovascular risk factors, were collected. Based on feature selection and clinical experience, 8 factors were identified as modeling variables. Subsequently, patients were divided randomly into 2 groups: the training (70%) and test (30%) groups. The performance of 8 supervised ML algorithms was evaluated in the training and test groups. Results: Obstructive CAD was diagnosed by coronary angiography in 94 (37.2%, 94/253) patients. In the training group, the area under the receiver operator characteristic (ROC) curve (AUC) of the random forest was the highest, and the AUCs of Logistic, extreme gradient boosting (XGBoost), support vector machine (SVM), and adaptive boosting (AdaBoost) were all above 0.9. In the test group, the AUC of recursive partitioning and regression trees (Rpart) was the highest (0.911). Rpart and Naïve Bayes had the highest accuracy (0.840). Rpart had a sensitivity and specificity of 0.851 and 0.821, respectively; Naïve Bayes had a sensitivity and specificity of 0.809 and 0.893, respectively. Next was Logistic, with an accuracy of 0.827, a sensitivity of 0.872, and a specificity of 0.750. The random forest and XGBoost algorithms also had high accuracy, which was 0.813 for each algorithm. Conclusions: Rest-only SPECT MPI combined with CACS and cardiovascular risk factors using an ML algorithm to detect obstructive CAD is feasible. Among the algorithms validated in the test group, Rpart, Naïve Bayes, XGBoost, Logistic, and random forest are all highly accurate for diagnosing obstructive CAD. The application of ML in resting MPI and CACS may be used for screening obstructive CAD.

Left ventricular systolic dyssynchrony: a novel imaging marker for early assessment of myocardial damage in Chinese type 2 diabetes mellitus patients with normal left ventricular ejection fraction and normal myocardial perfusion.

OBJECTIVES: Myocardial damage is the important cause of heart failure (HF) in type 2 diabetes mellitus (T2DM), which is difficult to early diagnose, especially in T2DM with normal left ventricular ejection fraction (LVEF) and normal myocardial perfusion. The goal was to evaluate myocardial damage in T2DM with normal LVEF and normal myocardial perfusion by detecting left ventricular systolic dyssynchrony (LVSD), and find out the risk factors associated with LVSD. METHODS: This study included 95 T2DM with normal LVEF, normal myocardial perfusion. 69 consecutive individuals without T2DM and CAD were enrolled as the control group with age-, sex- and BMI-matched. All participants underwent stress/rest 99mtechnetium-sestamibi (99mTc-MIBI) gated myocardial perfusion imaging (GMPI) and two-dimensional echocardiography within 1 week. Clinical data including age, gender, BMI, duration of diabetes, chronic diabetic complications, glycated haemoglobin A1c (HbA1c), fast blood glucose (FBG) and Brain Natriuretic Peptide (BNP) were collected from medical records. Left ventricular synchrony parameters were acquired, including phase standard deviation (PSD) and phase histogram bandwidth (PBW) by rest GMPI. RESULTS: PSD and PBW in T2DM group were significantly higher than control group (P < .05). LVSD was detected in 20 (21%) T2DM patients. Compared to non-LVSD T2DM group, LVSD T2DM group had higher BMI, higher prevalence of BNP [Formula: see text] 35 pg/mL and chronic diabetic complications (P < .05). BNP [Formula: see text] 35 pg/mL had mild positive association with LVSD (r = 0.318, P = .004). In multivariate logistic regression, chronic diabetic complications and high BMI (> 23.4 kg/m2) were independent risk factors of LVSD (OR 5.64, 95% CI 1.58-20.16, P = .008; OR 6.77, 95% CI 1.59-28.89, P = .010). CONCLUSIONS: LVSD existed in T2DM patients with normal LVEF and normal myocardial perfusion. Chronic diabetic complications and high BMI (> 23.4 kg/m2) were the independent risk factors of LVSD. LVSD based on GMPI can be the novel imaging marker to early assess myocardial damage in T2DM patients.

The value of regional and global CACS combined with SPECT MPI in detecting obstructive CAD: a retrospective real-world comparative study.

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 < 0.001). Regional CACS had a better diagnostic performance in RCA territories (AUC 0.856, P < 0.001) compared with LAD, LCX territories (AUC 0.690, 0.674, respectively). The AUC of combined regional CACS and MPI was significantly higher than that of MPI alone (0.735 vs. 0.600, P < 0.001). However, based on MPI, the AUC of combined regional CACS was not significantly higher than that of global CACS (0.735 vs. 0.732, P = 0.898). The sensitivity and specificity of regional CACS combined with MPI for detecting obstructive CAD were 64.0% and 72.8%, respectively. CONCLUSIONS: Regional CACS was effective in detecting obstructive CAD in RCA territory. Based on SPECT MPI, regional CACS improved the detection of obstructive CAD, but was not superior to global CACS.

Incremental value of PET primary lesion-based radiomics signature to conventional metabolic parameters and traditional risk factors for preoperative prediction of lymph node metastases in gastric cancer.

BACKGROUND: Precise preoperative prediction of lymph node metastasis (LNM) is crucial for optimal diagnosis and treatment in patients with gastric cancer (GC), in which existing imaging methods have certain limitations. We hypothesized that PET primary lesion-based radiomics signature could provide incremental value to conventional metabolic parameters and traditional risk indicators in predicting LNM in patients with GC. METHODS: This retrospective study was performed in 127 patients with GC who underwent preoperative PET/CT. Basic clinical data and PET conventional metabolic parameters were collected. Radiomics signature was constructed by the least absolute shrinkage and selection operator algorithm (LASSO) logistic regression. Based on the postoperative histological results, the patients were divided into LNM group and non-lymph node metastasis (NLNM) group. Receiver-operating characteristic (ROC) was used to evaluate the discriminatory ability of Radiomics score (Rad-score) for predicting LNM and determine whether adding Rad-score to PET conventional metabolic parameters and traditional risk factors could improve the predictive value in LNM. The Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were calculated to further confirm the incremental value of Rad-score for predicting LNM in GC. RESULTS: The LNM group had higher Rad-score than NLNM group [(0.35 (-0.13-0.85) vs. -0.61 (-1.92-0.18), P < 0 .001)]. After adjusted for gender, age, BMI, and FBG, multivariable logistic regression analysis illustrated that Rad-score (OR: 6.38, 95% CI: 2.73-14.91, P < 0.0001) was independent risk factors for LNM in GC. Adding PET conventional parameters to traditional risk factors increased the predictive value of LNM in GC (AUC 0.751 vs 0.651, P = 0.02). Additional inclusion of Rad-score to conventional metabolic parameters and traditional risk indicators significantly improved the AUC (0.882 vs 0.751; P = 0.006). Bootstrap resampling (times = 500) was used for internal verification, 95% confidence interval (CI) was 0.802-0.948, with the sensitivity equaled to 89.5%, and positive predictive value (PPV) was 93.5%. When Rad-score was added to conventional metabolic parameters and traditional risk indicators, net reclassification improvement (NRI) was 0.293 (P = 0.0040) and integrated discrimination improvement (IDI) was 0.293 (P = 0.0045). CONCLUSION: In GC patients, PET Radiomics signature of the primary lesion-based was significantly associated with LNM and could improve the prediction of LNM above PET conventional metabolic parameters and traditional risk factors, which could provide incremental value for individual diagnosis and treatment of GC.

Preparation and Characterization of Wood Scrimber Based on Eucalyptus Veneers Complexed with Ferrous Ions.

Wood-based products manufactured from fast-growing wood species such as eucalyptus have gained increasing attraction with the demand of using wood in architecture, furniture, and decoration. In this paper, a new type of wood scrimber based on eucalyptus veneers complexed with ferrous ions was prepared and its properties were characterized. The results showed that the presence of complexes did not affect the mechanical properties of eucalyptus wood scrimber, but made its surface more hydrophobic (contact angle increased by 38.48% and dimensional stability improved (thickness swelling rate decreased by 32.26%). Most importantly, the color of eucalyptus wood scrimber changed significantly, from the original brown to dark blue, and its anti-photoaging property also greatly improved. These advantages would make this type of wood scrimber based on the eucalyptus veneer complexes with ferrous ions more widely applicable in decorations and buildings.

Thermophysical Molding Treatments on Thick Wood Veneer.

Thermophysical molding (TPM) treatments can significantly improve the surface properties of thick wood veneer. To understand the effects of TPM treatments on the surface properties of thick veneer, the roughness, contact angles, and chemical changes were determined. The results indicated that the roughness of the thick veneer decreased when the temperature and the duration increased. The contact angles decreased when the temperature increased, resulting in better wettability. X-ray photoelectron spectroscopic (XPS) results provided information about the significant chemical changes in the surface with different TPM temperatures of 160-190 °C and durations of 5-11 min. Increases in temperature and duration increased the C content and decreased the O content during the treatment process. The most significant changes in the thick veneer that resulted from increasing the temperature and the duration were the increase in the C1 component and the decrease in the C2 component. Thus, the oxygen to carbon (O/C) ratio decreased and the ratio of aromatic carbon to aliphatic carbon (C1/C2) notably increased with the increasing TPM temperature. The TPM duration slightly affected the O/C ratio, but it had a stronger linear relation with the C1/C2 ratio. Additionally, the C1/C2 ratio and the O/C ratio had a linear statistical relationship with the initial wettability. These findings could provide useful information for the future utilization of thick veneers treated with TPM.

Bamboo cellulose fibers prepared by different drying methods: Structure-property relationships.

Bamboo cellulose fibers (BCFs) has attracted increasing attention in many fields due to its high mechanical strength and interconnected porous structure. Drying is a key factor that determines the final structure and properties of BCFs. In this work, three kinds of BCFs, i.e., conventional-dried (CD-BCFs), freeze-dried (FD-BCFs), and supercritical CO2-dried (SD-BCFs), were prepared via different drying methods. The effects of drying methods on their supramolecular structure, porosity, and mechanical properties were studied, and the structure-property relationships were proposed. The CD-BCFs composed of well-aligned crystalline nanofibrils with a dense structure exhibited the best mechanical properties (tensile strength of 854.54 MPa). The SD-BCFs featured with interconnected 3D microfibril networks give a highly porous structure and the highest surface area of 9.162 m2/g. The FD-BCFs showed medium mechanical properties and surface area owing to the stacked lamellar microfibril network. This work provides guidelines for designing BCFs with proper structure for various end-use applications.

18F-FDG PET/CT-based radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer.

Objective: Lymph node metastasis (LNM) is not only one of the important factors affecting the prognosis of gastric cancer but also an important basis for treatment decisions. The purpose of this study was to investigate the value of the radiomics nomogram based on preoperative 18F-deoxyglucose (FDG) PET/CT primary lesions and clinical risk factors for predicting LNM in gastric cancer (GC). Methods: We retrospectively analyzed radiomics features of preoperative 18F-FDG PET/CT images in 224 gastric cancer patients from two centers. The prediction model was developed in the training cohort (n = 134) and validated in the internal (n = 59) and external validation cohorts (n = 31). The least absolute shrinkage and selection operator (LASSO) regression was used to select features and build radiomics signatures. The radiomics feature score (Rad-score) was calculated and established a radiomics signature. Multivariate logistic regression analysis was used to screen independent risk factors for LNM. The minimum Akaike's information criterion (AIC) was used to select the optimal model parameters to construct a radiomics nomogram. The performance of the nomogram was assessed with calibration, discrimination, and clinical usefulness. Results: There was no significant difference between the internal verification and external verification of the clinical data of patients (all p > 0.05). The areas under the curve (AUCs) (95% CI) for predicting LNM based on the 18F-FDG PET/CT radiomics signature in the training cohort, internal validation cohort, and external validation cohort were 0.792 (95% CI: 0.712-0.870), 0.803 (95% CI: 0.681-0.924), and 0.762 (95% CI: 0.579-0.945), respectively. Multivariate logistic regression showed that carbohydrate antigen (CA) 19-9 [OR (95% CI): 10.180 (1.267-81.831)], PET/CT diagnosis of LNM [OR (95% CI): 6.370 (2.256-17.984)], PET/CT Rad-score [OR (95% CI): 16.536 (5.506-49.660)] were independent influencing factors of LNM (all p < 0.05), and a radiomics nomogram was established based on those factors. The AUCs (95% CI) for predicting LNM were 0.861 (95% CI: 0.799-0.924), 0.889 (95% CI: 0.800-0.976), and 0.897 (95% CI: 0.683-0.948) in the training cohort, the internal validation cohort, and the external validation cohort, respectively. Decision curve analysis (DCA) indicated that the 18F-FDG PET/CT-based radiomics nomogram has good clinical utility. Conclusions: Radiomics nomogram based on the primary tumor of 18F-FDG PET/CT could facilitate the preoperative individualized prediction of LNM, which is helpful for risk stratification in GC patients.

A model combining rest-only ECG-gated SPECT myocardial perfusion imaging and cardiovascular risk factors can effectively predict obstructive coronary artery disease.

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.