Resting-State Brain Function Alteration in Colorectal Cancer Patients.

BACKGROUND AND PURPOSE: To investigate the abnormal pattern of altered functional activity in the brain and the neuroimaging mechanisms underlying the cognitive impairment of patients with colorectal cancer (CRC) via resting-state functional magnetic resonance imaging (rs-fMRI). MATERIALS AND METHODS: CRC patients (n = 56) and healthy controls (HCs) (n = 50) were studied. The participants underwent rs-fMRI scans and the Montreal Cognitive Assessment (MoCA). The amplitude of low-frequency fluctuations (ALFF), degree centrality (DC), regional homogeneity (ReHo), and MoCA scores, were calculated for participants. RESULTS: The scores of executives, visuospatial, memory, language and attention were lower in CRC patients. ReHo and ALFF values in the left postcentral gyrus, ReHo values in the right postcentral gyrus, ALFF and DC values in the left middle occipital gyrus, ReHo and DC values in the right lingual gyrus, DC values in the right angular gyrus and precuneus, and ALFF values in the left middle temporal gyrus decreased conspicuously in the CRC patients. CONCLUSION: CRC patients have abnormal resting state function, mainly in the brain areas involved in cognitive function. The overlapping brain regions with abnormal functional indicators are in the middle occipital gyrus, postcentral gyrus, and lingual gyrus. This study reveals the potential biological pathways involved in brain impairment and neurocognitive decline in patients with CRC.

Gut microbiota dysbiosis in hyperuricaemia promotes renal injury through the activation of NLRP3 inflammasome.

BACKGROUND: The prevalence of hyperuricaemia (HUA), a metabolic disorder characterized by elevated levels of uric acid, is on the rise and is frequently associated with renal injury. Gut microbiota and gut-derived uremic toxins are critical mediators in the gut-kidney axis that can cause damage to kidney function. Gut dysbiosis has been implicated in various kidney diseases. However, the role and underlying mechanism of the gut microbiota in HUA-induced renal injury remain unknown. RESULTS: A HUA rat model was first established by knocking out the uricase (UOX). HUA rats exhibited apparent renal dysfunction, renal tubular injury, fibrosis, NLRP3 inflammasome activation, and impaired intestinal barrier functions. Analysis of 16S rRNA sequencing and functional prediction data revealed an abnormal gut microbiota profile and activation of pathways associated with uremic toxin production. A metabolomic analysis showed evident accumulation of gut-derived uremic toxins in the kidneys of HUA rats. Furthermore, faecal microbiota transplantation (FMT) was performed to confirm the effects of HUA-induced gut dysbiosis on renal injury. Mice recolonized with HUA microbiota exhibited severe renal injury and impaired intestinal barrier functions following renal ischemia/reperfusion (I/R) surgery. Notably, in NLRP3-knockout (NLRP3-/-) I/R mice, the deleterious effects of the HUA microbiota on renal injury and the intestinal barrier were eliminated. CONCLUSION: Our results demonstrate that HUA-induced gut dysbiosis contributes to the development of renal injury, possibly by promoting the production of gut-derived uremic toxins and subsequently activating the NLRP3 inflammasome. Our data suggest a potential therapeutic strategy for the treatment of renal diseases by targeting the gut microbiota and the NLRP3 inflammasome. Video Abstract.

Two-Photon Nanoparticle Probe for Formaldehyde Detection via the AILE Luminescence Mechanism.

A two-photon nanoparticle probe was designed and developed based on the principle of intermolecular interaction of the aggregation-induced locally excited emission luminescence mechanism. The probe has the advantages of simple synthesis, convenient use, strong atomic economy, good biocompatibility, and photobleaching resistance. It can produce a specific and sensitive response to formaldehyde, help detect FA in normal cells and cancer cells, and is expected to become a specific detection probe for FA in vitro and in vivo.

Clinicopathologic and Molecular Characterization of Xanthomatous Giant Cell Renal Cell Carcinomas: Further Support for a Close Morphologic Spectrum to Eosinophilic Solid and Cystic Renal Cell Carcinomas.

A recent study described a rare subtype of tuberous sclerosis complex ( TSC )-mutated renal cell carcinoma primarily characterized by Xanthomatous giant cell morphology. Only 2 cases in young individuals have been reported so far, making the correct diagnosis challenging from a pathological perspective. It remains unknown whether this tumor represents an independent subtype or belongs to other TSC -mutated tumors. We conducted a clinicopathologic evaluation and immunohistochemical profiling of 5 cases of Xanthomatous Giant Cell Renal Cell Carcinoma (XGC RCC) with confirmed TSC2 mutations through targeted DNA sequencing. In addition, we analyzed transcriptomic profiles using RNA-seq for the following samples: XGC RCC, Low-grade Oncocytic tumors (LOT), High-grade Oncocytic tumors/Eosinophilic Vacuolar Tumors (HOT/EVT), Eosinophilic Solid and Cystic Renal Cell Carcinomas (ESC RCC), Chromophobe cell Renal Cell Carcinomas (ChRCC), Renal Oncocytomas (RO), clear cell Renal Cell Carcinomas (ccRCC), and normal renal tissues. There were 2 female and 3 male patients, aged 22 to 58 years, who underwent radical nephrectomy for tumor removal. The tumor sizes ranged from 4.7 to 9.5 cm in diameter. These tumors exhibited ill-defined boundaries, showed an expansive growth pattern, and featured distinctive tumor giant cells with abundant eosinophilic to Xanthomatous cytoplasm and prominent nucleoli. All tumors had low Ki-67 proliferation indices (<1%) and demonstrated immune reactivity for CD10, PAX8, CK20, CathepsinK, and GPNMB. Next-generation sequencing confirmed TSC2 mutations in all cases. RNA sequencing-based clustering indicated a close similarity between the tumor and ESC RCC. One patient (1/5) died of an accident 63 months later, while the remaining patients (4/5) were alive without tumor recurrences or metastases at the time of analysis, with a mean follow-up duration of 43.4 months. Our research supports the concept that Xanthomatous giant cell renal cell carcinoma (XGC RCC) shares clinicopathological and molecular characteristics with ESC RCC and shows a relatively positive prognosis, providing further support for a close morphologic spectrum between the two. We propose considering XGC RCC as a distinct subtype of ESC RCC.

Clinical and CT Quantitative Features for Predicting Liver Metastases in Patients with Pancreatic Neuroendocrine Tumors: A Study with Prospective/External Validation.

RATIONALE AND OBJECTIVES: We aimed to evaluate clinical characteristics and quantitative CT imaging features for the prediction of liver metastases (LMs) in patients with pancreatic neuroendocrine tumors (PNETs). METHODS: Patients diagnosed with pathologically confirmed PNETs were included, 133 patients were in the training group, 22 patients in the prospective internal validation group, and 28 patients in the external validation group. Clinical information and quantitative features were collected. The independent variables for predicting LMs were confirmed through the implementation of univariate and multivariate logistic analyses. The diagnostic performance was evaluated by conducting receiver operating characteristic curves for predicting LMs in the training and validation groups. RESULTS: PNETs with LMs demonstrated significantly larger diameter and lower arterial/portal tumor-parenchymal enhancement ratio, arterial/portal absolute enhancement value (AAE/PAE value) (p < 0.05). After multivariate analyses, A high level of tumor marker (odds ratio (OR): 5.32; 95% CI, 1.54-18.35), maximum diameter larger than 24.6 mm (OR: 7.46; 95% CI, 1.70-32.72), and AAE value ≤ 51 HU (OR: 4.99; 95% CI, 0.93-26.95) were independent positive predictors of LMs in patients with PNETs, with area under curve (AUC) of 0.852 (95%CI, 0.781-0.907). The AUCs for prospective internal and external validation groups were 0.883 (95% CI, 0.686-0.977) and 0.789 (95% CI, 0.602-0.916), respectively. CONCLUSION: Tumor marker, maximum diameter and absolute enhancement value in arterial phase were independent predictors with good predictive performance for the prediction of LMs in patients with PNETs. Combining clinical and quantitative features may facilitate the attainment of good predictive precision in predicting LMs.

Qi-dan-dihuang decoction ameliorates renal fibrosis in diabetic rats via p38MAPK/AKT/mTOR signaling pathway.

CONTEXT: Qi-dan-dihuang decoction (QDD) has been used to treat diabetic kidney disease (DKD), but the underlying mechanisms are poorly understood. OBJECTIVE: This study reveals the mechanism by which QDD ameliorates DKD. MATERIALS AND METHODS: The compounds in QDD were identified by high-performance liquid chromatography and quadrupole-time-of-flight tandem mass spectrometry (HPLC-Q-TOF-MS). Key targets and signaling pathways were screened through bioinformatics. Nondiabetic Lepr db/m mice were used as control group, while Lepr db/db mice were divided into model group, dapagliflozin group, 1% QDD-low (QDD-L), and 2% QDD-high (QDD-H) group. After 12 weeks of administration, 24 h urinary protein, serum creatinine, and blood urea nitrogen levels were detected. Kidney tissues damage and fibrosis were evaluated by pathological staining. In addition, 30 mmol/L glucose-treated HK-2 and NRK-52E cells to induce DKD model. Cell activity and migration capacity as well as protein expression levels were evaluated. RESULTS: A total of 46 key target genes were identified. Functional enrichment analyses showed that key target genes were significantly enriched in the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) and mitogen-activated protein kinase (MAPK) signaling pathways. In addition, in vivo and in vitro experiments confirmed that QDD ameliorated renal fibrosis in diabetic mice by resolving inflammation and inhibiting the epithelial-mesenchymal transition (EMT) via the p38MAPK and AKT-mammalian target of rapamycin (mTOR) pathways. DISCUSSION AND CONCLUSION: QDD inhibits EMT and the inflammatory response through the p38MAPK and AKT/mTOR signaling pathways, thereby playing a protective role in renal fibrosis in DKD.

Peripheral T cell lymphoma initially presenting in lung biopsies: A diagnostic challenge.

BACKGROUND: Primary or secondary pulmonary involvement by peripheral T cell lymphoma (PTCL) is rare and difficult to diagnose particularly via lung biopsies. METHODS: 22 cases of PTCL diagnosed initially in lung biopsies between January 2006 and November 2020 were retrospectively reviewed followed at Nanjing Drum Tower Hospital and the First Affiliated Hospital of Zhengzhou University, respectively, including clinical manifestations, baseline biochemical indexes, images, histological findings and other available ancillary studies such as immunostaining, Epstein-Barr virus encoded RNA (EBER) in situ hybridization and T-cell receptor rearrangement analysis upon diagnosis. RESULTS: The median age of these patients was 59 years old (range: 29-82 years) at diagnosis. The majority of them complained of fever, cough and fatigue. Computed tomography scans mainly revealed multiple ill-defined nodules/masses of various sizes and densities with or without air bronchogram. Microscopically, most lesions showed lymphoid cells with clear cytoplasm and irregular nuclear contours diffusely infiltrating alveolar septa or alveolar spaces in an inflammatory background. Several cases had a predominance of small neoplastic cells (n = 4) with atypical, irregular nuclei. One case showed a diffuse monotonous pattern of growth. Angioinvasion and necrosis were not uncommon findings. The neoplastic cells in all cases were positive for one or more T-cell markers, and negative for B-cell-lineage antigens and EBER. 19 out of 22 patients had complete follow-up information, and 17 patients were dead at the last follow-up. CONCLUSIONS: Pulmonary involvement by PTCL is rare with dismal outcome. Aggressive clinical course and several clinicopathologic clues, albeit unspecific, may alert the pathologists of the possibilities of pulmonary PTCLs.

Functional analyses of TRAF6 gene in Argopecten scallops.

The tumor necrosis factor (TNF) receptor-associated factor (TRAF) family has been reported to be involved in many immune pathways. In a previous study, we identified 5 TRAF genes, including TRAF2, 3, 4, 6, and 7, in the bay scallop (Argopecten irradians, Air) and the Peruvian scallop (Argopecten purpuratus, Apu). Since TRAF6 is a key molecular link in the TNF superfamily, we conducted a series of studies targeting the TRAF6 gene in the Air and Apu scallops as well as their hybrid progeny, Aip (Air ♀ × Apu ♂) and Api (Apu ♀ × Air ♂). Subcellular localization assay showed that the Air-, Aip-, and Api-TRAF6 were widely distributed in the cytoplasm of the human embryonic kidney cell line (HEK293T). Additionally, dual-luciferase reporter assay revealed that among TRAF3, TRAF4, and TRAF6, only the overexpression of TRAF6 significantly activated NF-κB activity in the HEK293T cells in a dose-dependent manner. These results suggest a crucial role of TRAF6 in the immune response in Argopecten scallops. To investigate the specific immune mechanism of TRAF6 in Argopecten scallops, we conducted TRAF6 knockdown using RNA interference. Transcriptomic analyses of the TRAF6 RNAi and control groups identified 1194, 2403, and 1099 differentially expressed genes (DEGs) in the Air, Aip, and Api scallops, respectively. KEGG enrichment analyses revealed that these DEGs were primarily enriched in transport and catabolism, amino acid metabolism, peroxisome, lysosome, and phagosome pathways. Expression profiles of 28 key DEGs were confirmed by qRT-PCR assays. The results of this study may provide insights into the immune mechanisms of TRAF in Argopecten scallops and ultimately benefit scallop breeding.

Acacetin protects against sepsis-induced acute lung injury by facilitating M2 macrophage polarization via TRAF6/NF-κB/COX2 axis.

Acute lung injury (ALI) is the leading cause of death in patients with sepsis syndrome and without effective protective or therapeutic treatments. Acacetin, a natural dietary flavonoid, reportedly exerts several biological effects, such as anti-tumor, anti-inflammatory, and anti-oxidative effects. However, acacetin's effect and underlying mechanism on sepsis-induced ALI remain unclear. Here, the mouse model was established to explore the impact of acacetin on sepsis-induced ALI. Acacetin significantly increased ALI murine survival and attenuated lung injury in histological examinations. Additionally, acacetin down-regulated myeloperoxidase activity, protein concentration, and number of neutrophils and macrophages in bronchoalveolar lavage fluid. Subsequently, inflammatory cytokines, including TNF-α, IL-1ß, and IL-6, were examined. Results showed that acacetin dramatically suppressed the production of TNF-α, IL-1ß, and IL-6. These above results indicated that acacetin attenuated sepsis-induced ALI by inhibiting the inflammatory response. Moreover, acacetin inhibited the expression of markers for M1-type (iNOS, CD86) macrophages and promoted the expression of markers for M2-type (CD206, Arg1) macrophages by western blot. In addition, acacetin down-regulated the expression TRAF6, NF-κB, and Cyclooxygenase-2 (COX2) by western blot. The high concentration of acacetin had a better effect than the low concentration. Besides, over-expression of TRAF6 up-regulated the expression of COX2, CD86, and iNOS, and the ratio of p-NF-κB to NF-κB increased the mRNA levels of TNF-α, IL-1ß, and IL-6, down-regulated the expression of CD206 and Arg1. The effects of TRAF6 were the opposite of acacetin. And TRAF6 could offset the impact of acacetin. This study demonstrated that acacetin could prevent sepsis-induced ALI by facilitating M2 macrophage polarization via TRAF6/NF-κB/COX2 axis.

Machine Learning Methods Based on CT Features Differentiate G1/G2 From G3 Pancreatic Neuroendocrine Tumors.

RATIONALE AND OBJECTIVES: To identify CT features for distinguishing grade 1 (G1)/grade 2 (G2) from grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) using different machine learning (ML) methods. MATERIALS AND METHODS: A total of 147 patients with 155 lesions confirmed by pathology were retrospectively included. Clinical-demographic and radiological CT features was collected. The entire cohort was separated into training and validation groups at a 7:3 ratio. Least absolute shrinkage and selection operator (LASSO) algorithm and principal component analysis (PCA) were used to select features. Three ML methods, namely logistic regression (LR), support vector machine (SVM), and K-nearest neighbor (KNN) were used to build a differential model. Receiver operating characteristic (ROC) curves and precision-recall curves for each ML method were generated. The area under the curve (AUC), accuracy rate, sensitivity, and specificity were calculated. RESULTS: G3 PNETs were more likely to present with invasive behaviors and lower enhancement than G1/G2 PNETs. The LR classifier yielded the highest AUC of 0.964 (95% confidence interval [CI]: 0.930, 0.972), with 95.4% accuracy rate, 95.7% sensitivity, and 92.9% specificity, followed by SVM (AUC: 0.957) and KNN (AUC: 0.893) in the training group. In the validation group, the SVM classier reached the highest AUC of 0.952 (95% CI: 0.860, 0.981), with 91.5% accuracy rate, 97.3% sensitivity, and 70% specificity, followed by LR (AUC: 0.949) and KNN (AUC: 0.923). CONCLUSIONS: The LR and SVM classifiers had the best performance in the training group and validation group, respectively. ML method could be helpful in differentiating between G1/G2 and G3 PNETs.

A noninvasive nomogram model based on CT features to predict DNA mismatch repair deficiency in gastric cancer.

Objectives: DNA mismatch repair deficiency (dMMR) status has served as a positive predictive biomarker for immunotherapy and long-term prognosis in gastric cancer (GC). The aim of the present study was to develop a computed tomography (CT)-based nomogram for preoperatively predicting mismatch repair (MMR) status in GC. Methods: Data from a total of 159 GC patients between January 2020 and July 2021 with dMMR GC (n=53) and MMR-proficient (pMMR) GC (n=106) confirmed by postoperative immunohistochemistry (IHC) staining were retrospectively analyzed. All patients underwent abdominal contrast-enhanced CT. Significant clinical and CT imaging features associated with dMMR GC were extracted through univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) and internal validation of the cohort data were performed. Results: The nomogram contained four potential predictors of dMMR GC, including gender (odds ratio [OR] 9.83, 95% confidence interval [CI] 3.78-28.20, P < 0.001), age (OR 3.32, 95% CI 1.36-8.50, P = 0.010), tumor size (OR 5.66, 95% CI 2.12-16.27, P < 0.001) and normalized tumor enhancement ratio (NTER) (OR 0.15, 95% CI 0.06-0.38, P < 0.001). Using an optimal cutoff value of 6.6 points, the nomogram provided an area under the curve (AUC) of 0.895 and an accuracy of 82.39% in predicting dMMR GC. The calibration curve demonstrated a strong consistency between the predicted risk and observed dMMR GC. The DCA justified the relatively good performance of the nomogram model. Conclusion: The CT-based nomogram holds promise as a noninvasive, concise and accurate tool to predict MMR status in GC patients, which can assist in clinical decision-making.

Comparison of the preoperative diagnostic accuracy of BIPSS versus MRI for Cushing disease: a single-centre experience.

BACKGROUND: Cushing disease (CD) arises due to a pituitary corticotroph adenoma, which is the most common cause of Cushing syndrome (CS). Bilateral inferior petrosal sinus sampling (BIPSS) is a safe method for differentiating CD from ectopic adrenocorticotropic hormone (ACTH)-dependent CS. Enhanced high-resolution magnetic resonance imaging (MRI) can localize tiny pituitary lesions. The aim of this study was to compare the preoperative diagnostic accuracy of BIPSS versus MRI for CD in CS patients. We performed a retrospective study of patients who underwent BIPSS and MRI between 2017 and 2021. Low- and high-dose dexamethasone suppression tests were performed. Blood samples were collected simultaneously from the right and left catheter and femoral vein before and after desmopressin stimulation. MRI images were obtained, and endoscopic endonasal transsphenoidal surgery (EETS) was performed in confirmed CD patients. Dominant sides of ACTH secretion during BIPSS and MRI were compared with surgical findings. RESULTS: Twenty-nine patients underwent BIPSS and MRI. CD was diagnosed in 28 patients, 27 of whom received EETS. Localizations of microadenomas by MRI and BIPSS agreed with the EETS findings in 96% and 93% of the cases, respectively. BIPSS and EETS were successfully performed on all patients. CONCLUSION: BIPSS was the most accurate method (gold standard) for establishing a preoperative diagnosis of pituitary-dependent CD and was more sensitive than MRI in diagnosing microadenoma. High-resolution MRI with enhancement had an advantage over BIPSS in microadenoma lateralization diagnostics. The combined use of MRI and BIPSS could improve the preoperative diagnosis accuracy in ACTH-dependent CS patients.

Quality Change in Camellia Oil during Intermittent Frying.

Camellia oil with a high oleic acid content is widely used for frying. To comprehensively describe the quality change in camellia oil during frying, the changes in composition, deterioration indicators, and volatile profiles were investigated. The results showed that tocopherols mainly degraded in the early stage of frying, followed by unsaturated fatty acids (UFA). This caused the carbonyl value and total polar compounds level to significantly increase. Moreover, frying promoted the accumulation of volatile compounds in terms of type and abundance, especially aldehydes, which are related to the degradation of UFA. Principal component analysis showed that the frying of camellia oil was divided into three stages. First, the camellia oil with a heating time of 2.5-7.5 h showed excellent quality, where tocopherol played a major role in preventing the loss of UFA and was in the degradation acceleration stage. Subsequently, as tocopherol entered the degradation deceleration stage, the quality of camellia oil heated for 10.0-15.0 h presented a transition from good to deteriorated. Finally, tocopherol entered the degradation stagnation stage, and the quality of camellia oil heated for 17.5-25.0 h gradually deteriorated, accompanied by a high level of volatile compounds and deterioration indicators. Overall, this work comprehensively determined the deterioration of camellia oil during intermittent frying and offered valuable insights for its quality evaluation.

Clinical value of serum sTREM-1 and HBP levels in combination with traditional inflammatory markers in diagnosing hospital-acquired pneumonia in elderly.

BACKGROUND: The clinical presentation of hospital-acquired pneumonia (HAP) in older patients is often complex and non-specific, posing a diagnostic challenge. This study evaluates the value of serum soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) and heparin-binding protein (HBP) in combination with traditional inflammatory markers procalcitonin (PCT) and C-reactive protein (CRP) in diagnosing HAP in older patients. METHODS: Thirty-eight elderly male patients with HAP (≥ 80 years old) and 46 age-matched controls, who were hospitalized for other reasons than HAP, were enrolled. The serum sTREM-1, HBP, PCT and CRP levels were measured by ELISA on the first day after enrollment. In addition, routine blood test, blood gas, sputum analysis, clinical pulmonary infection score (CPIS) assessment, and chest X-ray were performed, and the correlations with HAP were analyzed. RESULTS: The serum sTREM-1 (n = 38, 170.75 ± 158.33 pg/ml), HBP (2.08 ± 0.50), PCT (9.44 ± 17.73) and CRP (79.63 ± 71.37) were all significantly higher in the HAP group, when compared to the control group (P < 0.05). Furthermore, the values were positively correlated with the CPIS. The ROC curve analysis revealed that the AUC for sTREM-1 (0.667) and HBP (0.711) were lower, when compared to that for PCT (AUC = 0.839) and CRP (AUC = 0.840). The combination of PCT and CRP with sTREM-1 (AUC = 0.927) or HBP (AUC = 0.930) had the highest AUC values. CONCLUSION: Serum sTREM-1, HBP, PCT and CRP can all be used as diagnostic markers for HAP in the elderly. The combination of traditional inflammatory markers PCT and CRP with novel inflammatory marker sTREM-1 or HBP further improves the diagnostic performance.

A Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperative Prediction of DNA Mismatch Repair Deficiency in Gastric Adenocarcinoma.

Purpose: To develop and validate a radiomics nomogram integrated with clinic-radiological features for preoperative prediction of DNA mismatch repair deficiency (dMMR) in gastric adenocarcinoma. Materials and Methods: From March 2014 to August 2020, 161 patients with pathologically confirmed gastric adenocarcinoma were included from two centers (center 1 as the training and internal testing sets, n = 101; center 2 as the external testing sets, n = 60). All patients underwent preoperative contrast-enhanced computerized tomography (CT) examination. Radiomics features were extracted from portal-venous phase CT images. Max-relevance and min-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) methods were used to select features, and then radiomics signature was constructed using logistic regression analysis. A radiomics nomogram was built incorporating the radiomics signature and independent clinical predictors. The model performance was assessed using receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA). Results: The radiomics signature, which was constructed using two selected features, was significantly associated with dMMR gastric adenocarcinoma in the training and internal testing sets (P < 0.05). The radiomics signature model showed a moderate discrimination ability with an area under the ROC curve (AUC) of 0.81 in the training set, which was confirmed with an AUC of 0.78 in the internal testing set. The radiomics nomogram consisting of the radiomics signature and clinical factors (age, sex, and location) showed excellent discrimination in the training, internal testing, and external testing sets with AUCs of 0.93, 0.82, and 0.83, respectively. Further, calibration curves and DCA analysis demonstrated good fit and clinical utility of the radiomics nomogram. Conclusions: The radiomics nomogram combining radiomics signature and clinical characteristics (age, sex, and location) may be used to individually predict dMMR of gastric adenocarcinoma.

An Evaluation Model for the Quality of Frying Oil Using Key Aldehyde Detected by HS-GC/MS.

To establish a practical model for evaluating the oxidation of frying oil using aldehydes, the aldehydes of 10 commercial oils during frying at 180 °C were identified using headspace-gas chromatography/mass spectrometry, and the changes of common aldehydes and their correlation with carbonyl values (CV) were analyzed. The results showed that the total peak area of aldehydes increased significantly with heating time, which was related to the fatty acid and tocopherol contents of the oils. There were four common aldehydes with different trends during frying, namely, pentanal, hexanal, (E)-hept-2-enal, and nonanal. Moreover, pentanal with a high correlation with CV was selected as the quality evaluating index of frying oil due to its stable accumulation over time. Based on the linear fitting relationships between CV and pentanal, as well as the initial content ratio of linoleic acid to palmitic acid and total tocopherols in oils, a predictive model was established for evaluating the quality of frying oils with high precision and non-reagent by using mass spectrometry. In summary, this work provides theoretical support for using aldehyde as the quality evaluation index of frying oil and provides a new idea for evaluating oil deterioration from the perspective of volatile compounds.

Quantitative analysis of enhanced CT in differentiating well-differentiated pancreatic neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas.

OBJECTIVE: To identify quantitative CT features for distinguishing well-differentiated pancreatic neuroendocrine tumors (PNETs) from poorly differentiated pancreatic neuroendocrine carcinomas (PNECs). MATERIALS AND METHODS: Seventeen patients with PNECs and 131 patients with PNETs confirmed by biopsy or surgery were retrospectively included. General demographic (sex, age) and CT quantitative parameters (arterial/portal absolute enhancement, arterial/portal relative enhancement ratio, arterial/portal enhancement ratio) were collected. Univariate and multivariate logistic regression analyses were performed to confirm independent variables for differentiating PNECs from PNETs. Receiver operating characteristic (ROC) curves for each quantitative parameter were generated to determine their diagnostic ability. RESULTS: PNECs had a much lower mean arterial/portal absolute enhancement value (19.5 ± 11.0 vs. 78.8 ± 47.2; 28.1 ± 15.8 vs. 77.0 ± 39.4), arterial/portal relative enhancement ratio (0.57 ± 0.36 vs. 2.03 ± 1.31; 0.80 ± 0.52 vs. 1.99 ± 1.13), and arterial/portal enhancement ratio (0.62 ± 0.27 vs. 1.22 ± 0.49; 0.74 ± 0.19 vs. 1.21 ± 0.36) than PNETs (all p < 0.001). After multivariable analysis, arterial absolute enhancement (odds ratio [OR]: 0.96, 95% confidence interval [CI]: 0.93, 0.99) and portal absolute enhancement (OR: 0.96, 95% CI: 0.92, 0.99) were independent factors for differentiating PNECs from PNETs. For each quantitative parameter, arterial lesion enhancement yielded the highest diagnostic performance, with an area under the curve (AUC) of 0.922 (95% CI: 0.867-0.960), followed by portal absolute enhancement. CONCLUSIONS: Arterial/portal absolute enhancements were independent predictors with good diagnostic accuracy for differentiating between PNETs and PNECs. Quantitative parameters of enhanced CT can distinguish PNECs from PNETs. KEY POINTS: • PNECs were hypovascular and had a much lower enhanced CT attenuation in both arterial and portal phases than well-differentiated PNETs. • Quantitative parameters derived from enhanced CT can be used to distinguish PNECs from PNETs. • Arterial absolute enhancement and portal absolute enhancement were independent predictive factors for differentiating between PNETs and PNECs.

Combined assessment of tumour cell nest size and desmoplastic reaction as an excellent prognostic predictor in oesophageal squamous cell carcinoma.

AIMS: Tumour budding (TB) activity, cell nest size (CNS), and desmoplastic reaction (DR) have been confirmed to be significantly correlated with prognosis in oesophageal squamous cell cancer (ESCC) recently. However, there are limited data on the prognostic significance of combined assessment of cellular dissociation and tumour stroma in ESCC. METHODS: In all, 265 cases with resected ESCCs diagnosed between January 2018 and August 2019 were retrospectively reviewed. All slides were reviewed for assessing TB, CNS, and DR. The Cellular Dissociation Grading and our Combined CNS and DR (CNS/DR) Grading systems were adopted to re-grade ESCCs. RESULTS: High TB activity, small CNS, and immature DR had a strong association with shorter overall survival (OS) and progression-free survival (PFS) (P < 0.001, respectively) in ESCC. Combined assessment of CNS and DR in a 4-tiered grading system displayed a prognostic excellence for survival (P < 0.001), and outperformed the Cellular Dissociation Grading for both OS (area under the curve [AUC], 0.728 versus 0.644, P = 0.043) and PFS (AUC, 0.763 versus 0.667, P = 0.018) by receiver operator characteristic curves. Also, Combined CNS/DR Grading showed superiority in recognizing a G4 subgroup with the worst outcome in our cohort, to whom the most urgent attention needs to be called. CONCLUSIONS: This is the first study to propose a novel Combined Grading system based on CNS and DR in ESCC, which has been demonstrated to be relatively superior to Cellular Dissociation Grading in predicting prognosis. The findings shed new light on the histopathological grading of ESCC and facilitates identifying biologically aggressive ESCCs.

Diagnostic Value of CT- and MRI-Based Texture Analysis and Imaging Findings for Grading Cartilaginous Tumors in Long Bones.

OBJECTIVE: To confirm the diagnostic performance of computed tomography (CT)-based texture analysis (CTTA) and magnetic resonance imaging (MRI)-based texture analysis for grading cartilaginous tumors in long bones and to compare these findings to radiological features. MATERIALS AND METHODS: Twenty-nine patients with enchondromas, 20 with low-grade chondrosarcomas and 16 with high-grade chondrosarcomas were included retrospectively. Clinical and radiological information and 9 histogram features extracted from CT, T1WI, and T2WI were evaluated. Binary logistic regression analysis was performed to determine predictive factors for grading cartilaginous tumors and to establish diagnostic models. Another 26 patients were included to validate each model. Receiver operating characteristic (ROC) curves were generated, and accuracy rate, sensitivity, specificity and positive/negative predictive values (PPV/NPV) were calculated. RESULTS: On imaging, endosteal scalloping, cortical destruction and calcification shape were predictive for grading cartilaginous tumors. For texture analysis, variance, mean, perc.01%, perc.10%, perc.99% and kurtosis were extracted after multivariate analysis. To differentiate benign cartilaginous tumors from low-grade chondrosarcomas, the imaging features model reached the highest accuracy rate (83.7%) and AUC (0.841), with a sensitivity of 75% and specificity of 93.1%. The CTTA feature model best distinguished low-grade and high-grade chondrosarcomas, with accuracies of 71.9%, and 80% in the training and validation groups, respectively; T1-TA and T2-TA could not distinguish them well. We found that the imaging feature model best differentiated benign and malignant cartilaginous tumors, with an accuracy rate of 89.2%, followed by the T1-TA feature model (80.4%). CONCLUSIONS: The imaging feature model and CTTA- or MRI-based texture analysis have the potential to differentiate cartilaginous tumors in long bones by grade. MRI-based texture analysis failed to grade chondrosarcomas.