The effect of pH shifting on the calcium-fortified milk analogue with chickpea protein.

Milk alternative attracts more attention due to nutrition benefits, but the low solubility and the calcium deficiency of plant protein hinder the development of milk alternatives. Therefore, pH shifting was optimized to improve chickpea protein solubility and calcium fortification while ensuring good digestibility. The results showed that pH shifting reduced the particle size from 2197.67 ± 178.2 nm to 80.2 ± 2 nm, and increased the net ζ potential from -0.48 ± 0.24 to -21.27 ± 0.65 due to the unfolding of secondary protein structure, by which chickpea protein bring better solution stability. Additionally, the whiteness of the solution with chickpea protein increased. The calcium addition kept the solution stable with small particle size despite a slight increase. The microstructure of chickpea protein during digestion was well disrupted even with fortifying calcium. This study provides proof of the positive effect of pH shifting on chickpea protein stability and calcium fortification.

Developing a Machine-Learning Prediction Model for Infliximab Response in Crohn's Disease: Integrating Clinical Characteristics and Longitudinal Laboratory Trends.

BACKGROUND: Achieving long-term clinical remission in Crohn's disease (CD) with antitumor necrosis factor α (anti-TNF-α) agents remains challenging. AIMS: This study aims to establish a prediction model based on patients' clinical characteristics using a machine-learning approach to predict the long-term efficacy of infliximab (IFX). METHODS: Three cohorts comprising 746 patients with CD were included from 3 inflammatory bowel disease (IBD) centers between June 2013 and January 2022. Clinical records were collected from baseline, 14-, 30-, and 52-week post-IFX treatment. Three machine-learning approaches were employed to develop predictive models based on 23 baseline predictors. The SHapley Additive exPlanations (SHAP) algorithm was used to dissect underlying predictors, and latent class mixed model (LCMM) was applied for trajectory analysis of the longitudinal change of blood routine tests along with long-term IFX therapy. RESULTS: The XGBoost model exhibited the best discrimination between long-term responders and nonresponders. In the internal training and testing set, the model achieved an AUC of 0.91 (95% CI, 0.86-0.95) and 0.71 (95% CI, 0.66-0.87), respectively. Moreover, it achieved a moderate predictive performance in the independent external cohort, with an AUC of 0.68 (95% CI, 0.59-0.77). The SHAP algorithm revealed disease-relevant laboratory measurements, notably hemoglobin (HB), white blood cells (WBC), erythrocyte sedimentation rate (ESR), albumin (ALB), and platelets (PLT), alongside age at diagnosis and the Montreal classification, as the most influential predictors. Furthermore, 2 distinct patient clusters based on dynamic laboratory tests were identified for monitoring the long-term remission. CONCLUSIONS: The established prediction model demonstrated remarkable discriminatory power in distinguishing long-term responders from nonresponders to IFX therapy. The identification of distinct patient clusters further emphasizes the need for tailored therapeutic approaches in CD management.

The study developed a machine-learning model using clinical data to predict long-term efficacy of IFX in Crohn's disease. The XGBoost model demonstrated strong discriminatory power, revealing influential predictors and distinct patient clusters, emphasizing the importance of tailored therapeutic approaches in CD management.

Calcium Oxide Adsorption of Gas Phase PCDD/Fs and Its Impact on the Adsorption Properties of Activated Carbon.

Calcium oxide (CaO), utilized in semi-dry/dry desulfurization systems at municipal solid waste incineration (MSWI) plants, demonstrates some capability to remove polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). This study assessed the gas-phase PCDD/F removal performance of CaO, activated carbon (AC) and CaO-AC mixtures. Alone, CaO achieved removal efficiencies of only 31.9% for mass and 50.8% for I-TEQ concentration. However, CaO-AC mixtures exhibited significantly higher efficiencies, reaching 96.0% and 92.5% for mass and I-TEQ concentrations, respectively, surpassing those of AC alone, which were 74.7% and 58.5%. BET analysis indicated that CaO's limited surface area and pore structure are major constraints on its adsorption performance. Density functional theory (DFT) calculations revealed that the π-π electron donor-acceptor (EDA) interaction enhances the adsorption between AC and PCDD/F, with adsorption energies ranging from -1.02 to -1.24 eV. Additionally, the induced dipole interactions between CaO and PCDD/F contribute to adsorption energies ranging from -1.13 to -1.43 eV. Moreover, with increasing chlorination levels, PCDD/F molecules are more predisposed to accept electron transfers from the surfaces of AC or CaO, thereby facilitating adsorption. The calculation for mixed AC and CaO showed that CaO modifies AC's properties, enhancing its ability to adsorb gas phase PCDD/Fs, with the higher adsorption energy and more electrons transfer, aligning with gas phase PCDD/Fs adsorption experiments. This study provides a comprehensive understanding of how CaO influences the PCDD/F adsorption performance of AC.

A clinical-radiomics nomogram based on automated segmentation of chest CT to discriminate PRISm and COPD patients.

Purpose: It is vital to develop noninvasive approaches with high accuracy to discriminate the preserved ratio impaired spirometry (PRISm) group from the chronic obstructive pulmonary disease (COPD) groups. Radiomics has emerged as an image analysis technique. This study aims to develop and confirm the new radiomics-based noninvasive approach to discriminate these two groups. Methods: Totally 1066 subjects from 4 centers were included in this retrospective research, and classified into training, internal validation or external validation sets. The chest computed tomography (CT) images were segmented by the fully automated deep learning segmentation algorithm (Unet231) for radiomics feature extraction. We established the radiomics signature (Rad-score) using the least absolute shrinkage and selection operator algorithm, then conducted ten-fold cross-validation using the training set. Last, we constructed a radiomics signature by incorporating independent risk factors using the multivariate logistic regression model. Model performance was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses (DCA). Results: The Rad-score, including 15 radiomic features in whole-lung region, which was suitable for diffuse lung diseases, was demonstrated to be effective for discriminating between PRISm and COPD. Its diagnostic accuracy was improved through integrating Rad-score with a clinical model, and the area under the ROC (AUC) were 0.82(95 %CI 0.79-0.86), 0.77(95 %CI 0.72-0.83) and 0.841(95 %CI 0.78-0.91) for training, internal validation and external validation sets, respectively. As revealed by analysis, radiomics nomogram showed good fit and superior clinical utility. Conclusions: The present work constructed the new radiomics-based nomogram and verified its reliability for discriminating between PRISm and COPD.

The different serum albumin assays influence the prescriptions in children with primary nephrotic syndrome.

The differences between the serum albumin determined by bromocresol green (BCG) and immunonephelometry (IN) were inconsistent in past studies, and the samples were all adults. We sought to determine the differences in children and reveal the impacts of these differences on the clinical diagnosis and treatments of primary nephrotic syndrome (PNS). Repeated measurements from 576 PNS children showed that albumin measured by BCG and IN (ALB-B and ALB-I) were 19.95 (11.15) g/L and 15.30 (11.05) g/L, respectively, and the mean difference was 4.68 g/L (P < 0.001). The cut-offs we calculated for hypoalbuminemia and severe hypoalbuminemia based on the IN were 25 and 15 g/L, which were 5 g/L lower than the cut-offs recommended by KIDGO, respectively. A pair of historical control samples (206 vs. 216) with ALB-B or ALB-I showed that the proportion of severe hypoalbuminemia was 14.60% greater in IN group (75.20% vs. 60.60%, P < 0.001). The misdiagnosis rate of severe hypoalbuminemia by IN was 33.77% when 20 g/L rather than 15 g/L was used as the cut-off. Furthermore, the proportion of patients receiving albumin injections increased by 10.20%, and the average consumption increased by 97.06% (P = 0.01) along with the use of IN. So, our results suggested that the difference between ALB-B and ALB-I led to misdiagnosis and prescription abuse in PNS children.

High expression of circulating exosomal PD-L1 contributes to immune escape of hepatocellular carcinoma and immune clearance of chronic hepatitis B.

OBJECTIVE: To investigate the expression of programmed death ligand-1 (PD-L1) in circulating exosomes, and to define the role of exosomal PD-L1 in promoting immune escape mechanism during chronic hepatitis B infection (CHB) and related liver diseases. METHODS: The levels of PD-L1 expressed in exosomes were detected by ELISA. CD8+T cells were sorted and cytotoxicity test was assessed by flow cytometry. PD-L1 protein expression in hepatocellular carcinoma (HCC) and normal adjacent tissues were detected by immunohistochemistry. RESULTS: Circulating exosomal PD-L1 levels were significantly higher in patients with CHB and HCC than in healthy controls (F =7.46, P=0.001). Levels of CD107a on CD8+T cells in patients with CHB receiving PD-L1 blocking antibody were significantly lower than in patients receiving isotype blocking antibody (t = 4.96, P < 0.01). Levels of TNF-α in cell culture supernatants of the PD-L1 blocking antibody group were significantly higher than in the isotype blocking antibody group (t =5.92, P < 0.01). Compared with patients receiving isotype blocking antibody, levels of CD107a on CD8+T cells significantly increased in patients with HCC receiving anti-PD-L1 antibody (t = 3.51, P<0.05). Compared with adjacent tissues, the levels of PD-L1 protein expression in HCC tissues were slightly higher; however, no significant difference between the two groups was observed. CONCLUSIONS: PD-L1 blockade in exosomes might promote the cytotoxic function of CD8+T cells and inhibit immune evasion during progression of HCC. Blocking PD-L1 in exosomes reduced the cytotoxic function of CD8+T cells in patients with CHB while enhancing the production of proinflammatory cytokines.

Effectiveness and safety of tripterygium wilfordii poly-glycosides on glomerulonephritis: a systematic review and meta-analysis.

Treatment of glomerulonephritis presents several challenges, including limited therapeutic options, high costs, and potential adverse reactions. As a recognized Chinese patent medicine, Tripterygium wilfordii poly-glycosides (TWP) have shown promising benefits in managing autoimmune diseases. To evaluate clinical effectiveness and safety of TWP in treating glomerulonephritis, we systematically searched PubMed, Cochrane Library, Web of Science, and Embase databases for controlled studies published up to 12 July 2023. We employed weighted mean difference and relative risk to analyze continuous and dichotomous outcomes. This meta-analysis included 16 studies that included primary membranous nephropathy (PMN), type 2 diabetic kidney disease (DKD), and Henoch-Schönlein purpura nephritis (HSPN). Analysis revealed that additional TWP administration improved patients' outcomes and total remission rates, reduced 24-h urine protein (24hUP) and decreased relapse events. The pooled results demonstrated the non-inferiority of TWP to glucocorticoids in achieving total remission, reducing 24hUP, and converting the phospholipase A2 receptor (PLA2R) status to negative. For DKD patients, TWP effectively reduced 24hUP levels, although it did not significantly improve the estimated glomerular filtration rate (eGFR). Compared to valsartan, TWP showed comparable improvements in 24hUP and eGFR levels. In severe cases of HSPN in children, significant clinical remission and a reduction in 24hUP levels were observed with the addition of TWP treatment. TWP did not significantly increase the incidence of adverse reactions. Therefore, TWP could offer therapeutic benefits to patients with PMN, DKD, and severe HSPN, with a minimal increase in the risk of side effects.

Aminophylline suppresses chronic renal failure progression by activating SIRT1/AMPK/mTOR-dependent autophagy.

Chronic renal failure (CRF) is a severe syndrome affecting the urinary system for which there are no effective therapeutics. In this study, we investigate the effects and mechanisms of aminophylline in preventing CRF development. A rat model of chronic renal failure is established by 5/6 nephrectomy. The levels of serum creatinine (SCR), urinary protein (UPR), and blood urea nitrogen (BUN) are detected by ELISA. Histological evaluations of renal tissues are performed by H&E, Masson staining, and PAS staining. Functional protein expression is detected by western blot analysis or immunofluorescence microscopy. Glomerular cell apoptosis is determined using the TUNEL method. Results show that Aminophylline significantly reduces the levels of SCR, UPR, and BUN in the CRF model rats. Histological analyses show that aminophylline effectively alleviates renal tissue injuries in CRF rats. The protein expression levels of nephrin, podocin, SIRT1, p-AMPK, and p-ULK1 are greatly increased, while p-mTOR protein expression is markedly decreased by aminophylline treatment. Additionally, the protein level of LC3B in CRF rats is significantly increased by aminophylline. Moreover, aminophylline alleviates apoptosis in the glomerular tissues of CRF rats. Furthermore, resveratrol promotes SIRT1, p-AMPK, and p-ULK1 protein expressions and reduces p-mTOR and LC3B protein expressions in CRF rats. Selisistat (a SIRT1 inhibitor) mitigates the changes in SIRT1, p-AMPK, p-ULK1, p-mTOR, and LC3B expressions induced by aminophylline. Finally, RAPA alleviates renal injury and apoptosis in CRF rats, and 3-MA eliminates the aminophylline-induced inhibition of renal injury and apoptosis in CRF rats. Aminophylline suppresses chronic renal failure progression by modulating the SIRT1/AMPK/mTOR-mediated autophagy process.

Identification and analysis of differently expressed transcription factors in aristolochic acid nephropathy.

BACKGROUND: Aristolochic acid nephropathy (AAN) is a rapidly progressive interstitial nephropathy caused by Aristolochic acid (AA). AAN is associated with the development of nephropathy and urothelial carcinoma. It is estimated that more than 100 million people worldwide are at risk of developing AAN. However, the underlying mechanisms driving renal deterioration in AAN remain poorly understood, and the treatment options are limited. METHODS: We obtained GSE27168 and GSE136276 series matrix data from the Gene Expression Omnibus (GEO) related to AAN. Using the R Studio environment, we applied the limma package and WGCNA package to identify co-differently expressed genes (co-DEGs). By GO/KEGG/GSVA analysis, we revealed common biological pathways. Subsequently, co-DEGs were subjected to the String database to construct a protein-protein interaction (PPI) network. The MCC algorithms implemented in the Cytohubba plugin were employed to identify hub genes. The hub genes were cross-referenced with the transcription factor (TF) database to identify hub TFs. Immune infiltration analysis was performed to identify key immune cell groups by utilizing CIBERSORT. The expressions of AAN-associated hub TFs were verified in vivo and in vitro. Finally, siRNA intervention was performed on the two TFs to verify their regulatory effect in AAN. RESULTS: Our analysis identified 88 co-DEGs through the "limma" and "WGCNA" R packages. A PPI network comprising 53 nodes and 34 edges was constructed with a confidence level >0.4. ATF3 and c-JUN were identified as hub TFs potentially linked to AAN. Additionally, expressions of ATF3 and c-JUN positively correlated with monocytes, basophils, and vessels, and negatively correlated with eosinophils and endothelial cells. We observed a significant increase in protein and mRNA levels of these two hub TFs. Furthermore, it was found that siRNA intervention targeting ATF3, but not c-JUN, alleviated cell damage induced by AA. The knockdown of ATF3 protects against oxidative stress and inflammation in the AAN cell model. CONCLUSION: This study provides novel insights into the role of ATF3 in AAN. The comprehensive analysis sheds light on the molecular mechanisms and identifies potential biomarkers and drug targets for AAN treatment.

Incineration-source fingerprints and emission spectrums of dioxins with diagnostic application.

Despite increasing waste-to-energy (WtE) capacities, there remain deficiencies in comprehension of 136 kinds of tetra- through octa-chlorinated dibenzo-p-dioxin and dibenzofurans (136 PCDD/Fs) originating from incineration sources. Samples from twenty typical WtE plants, encompassing coal-fired power plants (CPP), grate incinerators (GI), fluidized bed incinerators (FBI), and rotary kilns (RK), yielded extensive PCDD/F datasets. Research was conducted on fingerprint mapping, formation pathways, emission profiles, and diagnostic analysis of PCDD/Fs in WtE plants. Fingerprints revealed a prevalence of TCDF, followed by PeCDF, while CPP and RK respectively generated more PCDD and HxCDD. De novo synthesis was the predominant formation pathway except one plant, where CP-route dominated. DD/DF chlorination also facilitated PCDD/F formation, showing general trends of FBI > GI > CPP > RK. The PCDD/F emission intensities emitted in air pollution control system inlet (APCSI) and outlet (APCSO) followed the statistical sequence of RK > FBI > GI > CPP, with the average I-TEQ concentrations in APCSO reaching 0.18, 0.08, 0.11, and 0.04 ng I-TEQ·Nm-3. Emission spectrum were accordingly formed. Four clusters were segmented for diagnosis analysis, where PCDD/Fs in GI and FBI were similar, grouped as a single cluster. PCDD/Fs in CPP and RK demonstrated distinctive features in TCDD, HxCDD, and HxCDF. The WtE plants exceeding the limit value tended to generate and retain fewer TCDD and TCDF yet had higher fractions of HxCDD and HxCDF. The failure of APCS coupled with the intrinsic source strength of PCDD/Fs directly led to exceedance, highlighting safe operational practices. This study motivated source tracing and precise evaluation of 136 PCDD/Fs based on the revealed fingerprint profiles for WtE processes.

CTCOSY-JRES: A high-resolution three-dimensional NMR method for unveiling J-couplings.

Two-dimensional (2D) J-resolved spectroscopy provides valuable information on J-coupling constants for molecular structure analysis by resolving one-dimensional (1D) spectra. However, it is challenging to decipher the J-coupling connectivity in 2D J-resolved spectra because the J-coupling connectivity cannot be directly provided. In addition, 2D homonuclear correlation spectroscopy (COSY) can directly elucidate molecular structures by tracking the J-coupling connectivity between protons. However, this method is limited by the problem of spectral peak crowding and is only suitable for simple sample systems. To fully understand the intuitive coupling relationship and coupling constant information, we propose a three-dimensional (3D) COSY method called CTCOSY-JRES (Constant-Time COrrelation SpectroscopY and J-REsolved Spectroscopy) in this paper. By combining the J-resolved spectrum with the constant-time COSY technique, a doubly decoupled COSY spectrum can be provided while preserving the J-coupling constant along an additional dimension, ensuring high-resolution analysis of J-coupling connectivity and J-coupling information. Moreover, compression sensing and fold-over correction techniques are introduced to accelerate experimental acquisition. The CTCOSY-JRES method has been successfully validated in a variety of sample systems, including industrial, agricultural, and biopharmaceutical samples, revealing complex coupling interactions and providing deeper insights into the resolution of molecular structures.

Impact of obesity on outcomes of extracorporeal membrane oxygenation support: a systematic review and meta-analysis.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is used when standard methods of standard treatment methods are not successful. Obese patients present unique challenges during ECMO due to large body size hindering sufficient flows, difficulties with patient positioning and anatomical landmark identification, and restricted radiology scans. This meta-analysis aims to investigate the impact of obesity on the outcomes of patients undergoing ECMO. METHODS: Databases (PubMed, Embase, and Scopus databases) were searched to identify relevant studies published until July 2023. Data were reported as odds ratios (OR) with 95% confidence interval (CI), and the descriptive data were reported as standard difference of means (SDM) by a random effects model. RESULTS: A literature search identified 345 studies. Of them, 18 studies met the inclusion criteria. The findings from the meta-analysis revealed no significant association between obesity and survival outcomes after ECMO (odds ratio (OR): 0.91, 95% confidence interval (CI): 0.70-1.17, p: 0.46). Moreover, no comparative significant differences were found between obese and non-obese individuals on the duration of ECMO procedure (standardized mean difference (SMD): 0.07, -0.03-0.17), length of hospital stay (-0.03, -0.19 to 0.12), and duration of ventilation support (-0.10, -0.44 to 0.24). CONCLUSION: The meta-analysis findings suggest no significant impact of obesity on the survival outcomes after the ECMO procedure. There was no significant impact of obesity on the duration of ECMO procedures, length of hospital stay, and duration of ventilation support.

Facile synthesis of manganese-hafnium nanocomposites for multimodal MRI/CT imaging and in vitro photodynamic therapy of colon cancer.

Precise diagnosis of complex and soft tumors is challenging, which limits appropriate treatment options to achieve desired therapeutic outcomes. However, multifunctional nano-sized contrast enhancement agents based on nanoparticles improve the diagnosis accuracy of various diseases such as cancer. Herein, a facile manganese-hafnium nanocomposites (Mn3O4-HfO2 NCs) system was designed for bimodal magnetic resonance imaging (MRI)/computed tomography (CT) contrast enhancement with a complimentary function of photodynamic therapy. The solvothermal method was used to fabricate NCs, and the average size of Mn3O4 NPs and Mn3O4-HfO2 NCs was about 7 nm and 15 nm, respectively, as estimated by TEM. Dynamic light scattering results showed good dispersion and high negative (-33 eV) zeta potential, indicating excellent stability in an aqueous medium. Mn3O4-HfO2 NCs revealed negligible toxic effects on the NCTC clone 929 (L929) and mouse colon cancer cell line (CT26), demonstrating promising biocompatibility. The synthesized Mn3O4-HfO2 NCs exhibit significant enhancement in T1-weighted magnetic resonance imaging (MRI) and X-ray computed tomography (CT), indicating the appropriateness for dual-modal MRI/CT molecular imaging probes. Moreover, ultra-small Mn3O4-HfO2 NCs show good relaxivities for MRI/CT. These nanoprobes Mn3O4-HfO2 NCs further possessed outstanding reactive oxygen species (ROS) generation ability under minute ultraviolet light (6 mW·cm-2) to ablate the colon cancer cells in vitro. Therefore, the designed multifunctional Mn3O4-HfO2 NCs were ideal candidates for cancer diagnosis and photodynamic therapy.

Best practices for managing malodorous and infected wounds in advanced cervical cancer.

This cross-sectional study was conducted to examine the most effective strategies for managing malodorous and infected wounds in patients who have been diagnosed with advanced cervical cancer. The research was conducted in Liupanshui, China. The study specifically examined demographic profiles, wound characteristics and effectiveness of wound management approaches. The study incorporated the heterogeneous sample of 289 participants who fulfilled the inclusion criteria. Data collection was conducted via structured questionnaires and medical record evaluations. Descriptive statistics and statistical analyses, such as regression analysis, were utilized to evaluate demographic attributes, wound profiles and effects of different approaches to wound management. The findings unveiled the heterogeneous demographic composition of patients, encompassing differences in socioeconomic standing, educational attainment and age. A wide range of wound characteristics were observed, as 65.7% of lesions during the acute phase with diameter between 2 and 5 centimetres, while 41.5% of lesions had this range. The most prevalent types of infections were those caused by fungi (48.4%), followed by bacterial infections lacking resistance (38.1%). A moderate degree of odour intensity was prevalent, affecting 45.0% of the cases. With maximal odour reduction of 80%, a mean healing time of 25 days and patient satisfaction rating of 4.5 out of 5, Negative Pressure Wound Therapy demonstrated itself to be the most efficacious treatment method. Additional approaches, such as photodynamic therapy and topical antibiotic therapy, demonstrated significant effectiveness, as evidenced by odour reductions of 70% and 75%, respectively, and patient satisfaction ratings of 4.3 and 4.2. Thus, the study determined challenges associated with management of malodorous and infected lesions among patients with advanced cervical cancer. The results underscored the significance of individualized care approaches, drew attention to efficacious wound management techniques and identified critical determinants that impacted patient recuperation. The findings of this study hold potential for advancing palliative care for individuals diagnosed with advanced cervical cancer.

CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD.

BACKGROUND: Computed tomography (CT) plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease (COPD). This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients. METHODS: This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group. The radiomic features of the whole lung volume were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic signature construction. A radiomic nomogram was established by combining the radiomic score and clinical factors. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive performance of the radiomic nomogram in the training, internal validation, and independent external validation cohorts. RESULTS: Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model. The area under the curve (AUC) of the radiomic model in the training, internal, and independent external validation cohorts were 0.888 [95% confidence interval (CI) 0.869-0.906], 0.874 (95%CI 0.844-0.904) and 0.846 (95%CI 0.822-0.870), respectively. All were higher than the clinical model (AUC were 0.732, 0.714, and 0.777, respectively, P < 0.001). DCA demonstrated that the nomogram constructed by combining radiomic score, age, sex, height, and smoking status was superior to the clinical factor model. CONCLUSIONS: The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.

CT-based whole lung radiomics nomogram: a tool for identifying the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease.

OBJECTIVES: To evaluate the value of CT-based whole lung radiomics nomogram for identifying the risk of cardiovascular disease (CVD) in patients with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: A total of 974 patients with COPD were divided into a training cohort (n = 402), an internal validation cohort (n = 172), and an external validation cohort (n = 400) from three hospitals. Clinical data and CT findings were analyzed. Radiomics features of whole lung were extracted from the non-contrast chest CT images. A radiomics signature was constructed with algorithms. Combined with the radiomics score and independent clinical factors, multivariate logistic regression analysis was used to establish a radiomics nomogram. ROC curve was used to analyze the prediction performance of the model. RESULTS: Age, weight, and GOLD were the independent clinical factors. A total of 1218 features were extracted and reduced to 15 features to build the radiomics signature. In the training cohort, the combined model (area under the curve [AUC], 0.731) showed better discrimination capability (p < 0.001) than the clinical factors model (AUC, 0.605). In the internal validation cohort, the combined model (AUC, 0.727) performed better (p = 0.032) than the clinical factors model (AUC, 0.629). In the external validation cohort, the combined model (AUC, 0.725) performed better (p < 0.001) than the clinical factors model (AUC, 0.690). Decision curve analysis demonstrated the radiomics nomogram outperformed the clinical factors model. CONCLUSION: The CT-based whole lung radiomics nomogram has the potential to identify the risk of CVD in patients with COPD. CLINICAL RELEVANCE STATEMENT: This study helps to identify cardiovascular disease risk in patients with chronic obstructive pulmonary disease on chest CT scans. KEY POINTS: • To investigate the value of CT-based whole lung radiomics features in identifying the risk of cardiovascular disease in chronic obstructive pulmonary disease patients. • The radiomics nomogram showed better performance than the clinical factors model to identify the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease. • The radiomics nomogram demonstrated excellent performance in the training, internal validation, and external validation cohort (AUC, 0.731; AUC, 0.727; AUC, 0.725).

Distribution of PCDD/Fs and PCBs at different locations in a circulating fluidised bed municipal solid waste incinerator.

This study investigates a circulating fluidised bed (CFB) incineration plant to examine the concentrations and fingerprints of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), and biphenyls (PCBs) at five locations downstream of the post-combustion zone. Sampling encompassed both flue gas and ash, spanning from the high-temperature superheater to the outlet of the baghouse filter, thus covering a wide range of flue gas temperatures. The analysis reveals a continuous increase in PCDD/F and PCB concentrations in the flue gas from the superheater to the inlet of the air pollution control system (APCS). The maximum concentrations observed were 75.8 ng/Nm3 for PCDDs, 219 ng/Nm3 for PCDFs, and 763 ng/Nm3 for PCBs. These values represent 9.14, 11.5, and 6.37 times their respective concentrations at the outlet of the high-temperature superheater. Concurrently, the levels of PCDD/Fs and dioxin-like PCBs (dl-PCBs) in the ash steadily increased along the cooling path of the flue gas within the plant. Comparing dl-PCBs to the total amount of 209 PCB congeners, it was evident that dl-PCBs exhibited a trend more akin to that of PCDD/Fs. A robust linear correlation was observed between dl-PCBs and PCDD/Fs (R2 = 0.99, p < 0.001), surpassing that between PCBs and PCDD/Fs (R2 = 0.92, p < 0.01), suggesting that dl-PCBs share closer formation pathways with PCDD/Fs. Additionally, elemental composition analysis of fly ash samples aimed to explore potential links between fly ash characteristics and PCDD/F and PCB formation. The Cl/S ratio increased from 1.58 to 5.13 with decreasing flue gas temperature. Principal component analysis (PCA) was employed to visualise the concentrations of PCDD/Fs and PCBs in the flue gas alongside elemental contents in the fly ash. With the exception of PCBs in ash, all other PCDD/Fs and PCBs in fly ash exhibited positive correlations with both carbon (C) and chlorine (Cl). Furthermore, a positive relationship between C/Cl and PCDD/Fs-PCBs in fly ash implies that fly ash serves as the primary reaction surface for dioxin generation during low-temperature heterogeneous catalytic reactions.

Validation of disease severity index for predicting complicated disease in Crohn's disease: A comparison study with Lémann index.

BACKGROUND: Disease Severity Index (DSI) provides comprehensive assessment of bowel damage (BD). AIMS: To evaluate DSI in patients with Crohn's disease (CD) at high risk of disease progression, compared to Lémann Index (LI). METHODS: Patients with CD in our center were reviewed consecutively between 2017 and 2019. DSI, LI, and complicated CD course were analyzed. RESULTS: The median LI and DSI of included 300 patients were 1.63 (IQR 1.25-3.13) and 42 (IQR 32-51), respectively. 152 patients (50.7%) experienced a complicated disease course (median 5.1 months; IQR 1.1-20.2). DSI (AUC 0.66; 95% CI 0.60-0.72) better predicted a complicated course of CD over LI (AUC 0.56; 95% CI 0.50-0.63; P = 0.007). The cumulative probability of complicated CD course in severe patients was higher than those with 'mild CD' (P < 0.001). The Cox analysis identified DSI>43 (HR 2.18; 95% CI 1.54-3.09; P < 0.001), B2/3 vs. B1 (HR 2.80; 95% CI 1.99-3.94; P < 0.001), and a higher level of CRP (HR 1.01; 95% CI 1.00-1.02; P = 0.005) as independent prognostic factors for complicated CD. However, LI was not associated with complicated CD (P = 0.164). CONCLUSIONS: Higher DSI was associated with complicated disease outcomes. DSI might play a better role than LI in identifying patients at high risks of disease progression.

Extracellular volume fraction as a potential predictor to differentiate lung cancer from benign lung lesions with dual-layer detector spectral CT.

Background: Extracellular volume (ECV) fraction has been used in cardiovascular diseases, pancreatic fibrosis, and hepatic fibrosis. The diagnostic value of ECV for focal lung lesions remains to be explored. The aim of this study was to evaluate the feasibility of ECV derived from a dual-layer detector computed tomography (DLCT) to differentiate lung cancer (LC) from benign lung lesions (BLLs). Methods: Retrospectively, 128 consecutive patients with pathologically confirmed LC (n=86) or BLLs (n=42) were included. Conventional computed tomography (CT) characteristics and spectral CT parameters were assessed. All patients' hematocrits were measured to correct contrast volume distributions in blood while calculating ECV. After performing logistic regression analysis, a conventional CT-based model (Model A), DLCT-based model (Model B), combined diagnostic models (Model C), and an ECV-based model (Model D) were developed. The diagnostic effectiveness of each model was examined using the receiver operating characteristic (ROC) curve and their corresponding 95% confidence intervals (CIs). The area under the curve (AUC) of each model was compared using the DeLong test. Results: Certain conventional CT features (such as lesion size, lobulation, spiculation, pleural indentation, and enlarged lymph nodes) differed significantly between the LC and BLL groups (all P<0.05). Statistical differences were found in the following DLCT parameters (all P<0.05): effective atomic number (Zeff) (non-enhancement), electron density (ED) (non-enhancement), ECV, iodine concentration (IC), and normalized iodine concentration (NIC). Models A, B, C, and D had AUCs of 0.801 [95% confidence interval (CI): 0.721-0.866], 0.805 (95% CI: 0.726-0.870), 0.925 (95% CI: 0.865-0.964), and 0.754 (95% CI: 0.671-0.826), respectively. The AUC of Model D (ECV) showed no significant difference from that of Models A and B (DeLong test, P>0.05). Conclusions: The ECV derived from DLCT may be a potential new method to differentiate LC from BLLs, broadening the scope of ECV in clinical research.