Radiomics nomogram for preoperative differentiation of pulmonary mucinous adenocarcinoma from tuberculoma in solitary pulmonary solid nodules.

OBJECTIVE: To develop and validate predictive models using clinical parameters, radiomic features and a combination of both for preoperative differentiation of pulmonary nodular mucinous adenocarcinoma (PNMA) from pulmonary tuberculoma (PTB). METHOD: A total of 124 and 53 patients with PNMA and PTB, respectively, were retrospectively analyzed from January 2017 to November 2022 in The Fourth Affiliated Hospital of Hebei Medical University (Ligang et al., A machine learning model based on CT and clinical features to distinguish pulmonary nodular mucinous adenocarcinoma from tuberculoma, 2023). A total of 1037 radiomic features were extracted from contrast-enhanced computed tomography (CT). The patients were randomly divided into a training group and a test group at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was used for radiomic feature selection. Three radiomics prediction models were applied: logistic regression (LR), support vector machine (SVM) and random forest (RF). The best performing model was adopted, and the radiomics score (Radscore) was then computed. The clinical model was developed using logistic regression. Finally, a combined model was established based on clinical factors and radiomics features. We externally validated the three models in a group of 68 patients (46 and 22 patients with PNMA and PTB, respectively) from Xing Tai People's Hospital (30 and 14 patients with PNMA and PTB, respectively) and The First Hospital of Xing Tai (16 and 8 patients with PNMA and PTB, respectively). The area under the receiver operating characteristic (ROC) curve (AUC) value and decision curve analysis were used to evaluate the predictive value of the developed models. RESULTS: The combined model established by the logistic regression method had the best performance. The ROC-AUC (also a decision curve analysis) of the combined model was 0.940, 0.990 and 0.960 in the training group, test group and external validation group, respectively, and the combined model showed good predictive performance for the differentiation of PNMA from PTB. The Brier scores of the combined model were 0.132 and 0.068 in the training group and test group, respectively. CONCLUSION: The combined model incorporating radiomics features and clinical parameters may have potential value for the preoperative differentiation of PNMA from PTB.

Preoperative assessment of high-grade endometrial cancer using a radiomic signature and clinical indicators.

Aim: To develop and validate a radiomics-based combined model (ModelRC) to predict the pathological grade of endometrial cancer. Methods: A total of 403 endometrial cancer patients from two independent centers were enrolled as training, internal validation and external validation sets. Radiomic features were extracted from T2-weighted images, apparent diffusion coefficient map and contrast-enhanced 3D volumetric interpolated breath-hold examination images. Results: Compared with the clinical model and radiomics model, ModelRC showed superior performance; the areas under the receiver operating characteristic curves were 0.920 (95% CI: 0.864-0.962), 0.882 (95% CI: 0.779-0.955) and 0.881 (95% CI: 0.815-0.939) for the training, internal validation and external validation sets, respectively. Conclusion: ModelRC, which incorporated clinical and radiomic features, exhibited excellent performance in the prediction of high-grade endometrial cancer.

Accurate preoperative evaluation of the pathological grade of endometrial carcinoma is very important for the selection of treatment and prognosis. This study tried to develop a simple combined model based on radiomic features from endometrial carcinoma MRI and clinical features of patients. Compared with the clinical model and the radiomic model, the combined model showed superior performance. Therefore, this combined model would help patients and clinicians to make more rational decisions when choosing treatment strategies.

Fabrication of biologically inspired electrospun collagen/silk fibroin/bioactive glass composited nanofibrous to accelerate the treatment efficiency of wound repair.

A triple-layer matrix Collagen/Silk fibroin/Bioactive glass composited Nanofibrous was fabricated by linking electrospinning and freeze-drying systems, this typical three layered composite with a nanofibrous fragment as the key (top) layer, middle portion as inferior, and a spongy porous fragment as the third (bottom) deposit to develop the synergistic effect of composite materials resultant to physical and biological performances. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy were used to assess the final material's physicochemical properties (SEM). The triple-layer matrix had a nanofibrous and porous structure, which has qualities including high porosity, swelling, and stability, which are important in soft-tissue engineering. NIH 3 T3 fibroblast and humanoid keratinocyte (HaCaT) cell lines were also used to investigate the matrix's in vitro biological and fluorescent capabilities, which showed excellent cell adherence and proliferation across the composite layers. The synergistic arrangement of nanofibrous substantial deposition onto collagenous with silk fibroin candidates has therefore proven effective in the construction of a tri-layer matrix for skin-tissue-engineering applications.

Early top-down modulation in visual word form processing: Evidence from an intracranial SEEG study.

Visual word recognition, at a minimum, involves the processing of word form and lexical information. Opinions diverge on the spatiotemporal distribution of and interaction between the two types of information. Feedforward theory argues that they are processed sequentially, while interactive theory advocates that lexical information is processed fast and modulates early word form processing. To distinguish the two theories, we applied stereoelectroencephalography (SEEG) to 33 human adults with epilepsy (25 males and 8 females) during visual lexical decisions. The stimuli included real words (RWs), pseudowords (PWs) with legal radical positions, nonwords (NWs) with illegal radical positions, and stroked-changed words (SWs) in Chinese. Word form and lexical processing were measured by the word form effect (PW vs. NW) and lexical effect (RW vs. PW), respectively. Gamma-band (60 ∼ 140 Hz) SEEG activity was treated as an electrophysiological measure. A word form effect was found in eight left brain regions (i.e., the inferior parietal lobe, insula, fusiform, inferior temporal, middle temporal, middle occipital, precentral and postcentral gyri) from 50 ms poststimulus onset, while a lexical effect was observed in five left brain regions (i.e., the calcarine, middle temporal, superior temporal, precentral and postcentral gyri) from 100 ms poststimulus onset. The two effects overlapped in the precentral (300 ∼ 500 ms) and postcentral (100 ∼ 200 ms and 250 ∼ 600 ms) gyri. Moreover, high-level regions provide early feedback to word form regions. These results demonstrate that lexical processing occurs early and modulates word form recognition, providing vital supportive evidence for interactive theory.SIGNIFICANCE STATEMENTA pivotal unresolved dispute in the field of word processing is whether word form recognition is obligatorily modulated by high-level lexical top-down information. To address this issue, we applied intracranial stereoelectroencephalography (SEEG) to 33 adults with epilepsy, to precisely delineate the spatiotemporal dynamics between processing word form and lexical information during visual word recognition. We observed that lexical processing occurred from 100 ms poststimulus presentation and even spatiotemporally overlapped with word form processing. Moreover, the high-order regions provided feedback to the word form regions in the early stage of word recognition. These results revealed the crucial role of high-level lexical information in word form recognition, deepening our understanding of the functional coupling among brain regions in word processing networks.

Value of contrast-enhanced mammography combined with the Kaiser score for clinical decision-making regarding tomosynthesis BI-RADS 4A lesions.

OBJECTIVES: To investigate the diagnostic performance of contrast-enhanced mammography (CEM) combined with the Kaiser score (KS) in digital breast tomosynthesis (DBT) BI-RADS 4A lesions to potentially reduce unnecessary breast biopsies. METHODS: This retrospective study evaluated 106 patients with 109 DBT BI-RADS 4A lesions from June 2019 to June 2021. For the absence of enhancement on CEM, the lesions were downgraded to BI-RADS 3. For lesions with enhancement, the readers were asked to classify all enhancing lesions referring to the KS for breast MRI. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance. Two readers rated all cases and interreader agreement was assessed by Cohen's kappa coefficients. RESULTS: There were ninety-five benign lesions and 14 malignant lesions. CEM combined with KS's accuracy, represented by the area under the curve (AUC), ranged between 0.880 and 0.906. The use of the KS improved the performance, with a significant difference relative to a single BI-RADS reading or US (p < 0.001). CEM with KS had higher specificity than CEM with BI-RADS or US (p < 0.001), without difference in sensitivity (p > 0.05). CEM combined with KS could have potentially obviated 72 (75.8%) to 78 (82.1%) unnecessary benign biopsies in 95 benign lesions previously DBT classified as BI-RADS 4A. The interreader agreement was substantial (kappa: 0.727) for KS. CONCLUSIONS: CEM combined with KS may be used in DBT BI-RADS 4A lesions to substantially reduce unnecessary benign biopsies. KEY POINTS: • CEM combined with the Kaiser scoring system shows high diagnostic performance for DBT BI-RADS 4A lesions. • The application of CEM combined with the Kaiser scoring system may avoid 75.8% to 82.1% of unnecessary benign breast biopsies. • CEM combined with the KS aids clinical decision-making in DBT BI-RADS 4A lesions.

Gray matter volume reduction with different disease duration in trigeminal neuralgia.

PURPOSE: Structural magnetic resonance imaging is widely used to explore brain gray and white matter structure in trigeminal neuralgia (TN) but has yielded conflicting findings. This study investigated the relationship between disease duration as a clinical feature of TN and changes in brain structure. METHODS: We divided 49 TN patients into three groups (TN1-TN3) based on disease duration (TN1 = 1.1 ± 0.7 (0-2) years, TN2 = 4.8 ± 1.5 (3-7) years, TN3 = 15.1 ± 5.5 (10-30) years). We used voxel-based morphometry (VBM) to compare the gray matter volume (GMV) across groups and between TN patients and 18 matched healthy control subjects. RESULTS: The TN1 group showed reduced GMV of pain-related regions in the cerebellum; the TN2 group showed reduced GMV in the thalamus and the motor/sensory cortex; and the TN3 group showed reduced GMV in the emotional and reward circuits compared with healthy controls. Similar brain regions, including bilateral hippocampi, caudate, left insular cortex, and medial superior frontal cortex, were affected in TN2 and TN3 compared with TN1. CONCLUSION: Disease duration can explain differences in structural alterations-especially in pain-related brain regions-in TN. These results highlight the advanced structural neuroimaging method that are valuable tools to assess the trigeminal system in TN and may further our current understanding of TN pathology.

Can lymphovascular invasion be predicted by contrast-enhanced CT imaging features in patients with esophageal squamous cell carcinoma? A preliminary retrospective study.

BACKGROUND: To investigate the value of contrast-enhanced CT (CECT)-derived imaging features in predicting lymphovascular invasion (LVI) status in esophageal squamous cell carcinoma (ESCC) patients. METHODS: One hundred and ninety-seven patients with postoperative pathologically confirmed esophageal squamous cell carcinoma treated in our hospital between January 2017 and January 2019 were enrolled in our study, including fifty-nine patients with LVI and one hundred and thirty-eight patients without LVI. The CECT-derived imaging features of all patients were analyzed. The CECT-derived imaging features were divided into quantitative features and qualitative features. The quantitative features consisted of the CT attenuation value of the tumor (CTVTumor), the CT attenuation value of the normal esophageal wall (CTVNormal), the CT attenuation value ratio of the tumor-to-normal esophageal wall (TNR), the CT attenuation value difference between the tumor and normal esophageal wall (ΔTN), the maximum thickness of the tumor measured by CECT (Thickness), the maximum length of the tumor measured by CECT (Length), and the gross tumor volume measured by CECT (GTV). The qualitative features consisted of an enhancement pattern, tumor margin, enlarged blood supply or drainage vessels to the tumor (EVFDT), and tumor necrosis. For the clinicopathological characteristics and CECT-derived imaging feature analysis, the chi-squared test was used for categorical variables, the Mann-Whitney U test was used for continuous variables with a nonnormal distribution, and the independent sample t-test was used for the continuous variables with a normal distribution. The trend test was used for ordinal variables. The association between LVI status and CECT-derived imaging features was analyzed by univariable logistic analysis, followed by multivariable logistic regression and receiver operating characteristic (ROC) curve analysis. RESULTS: The CTVTumor, TNR, ΔTN, Thickness, Length, and GTV in the group with LVI were higher than those in the group without LVI (P < 0.05). A higher proportion of patients with heterogeneous enhancement pattern, irregular tumor margin, EVFDT, and tumor necrosis were present in the group with LVI (P < 0.05). As revealed by the univariable logistic analysis, the CECT-derived imaging features, including CTVTumor, TNR, ΔTN and enhancement pattern, Thickness, Length, GTV, tumor margin, EVFDT, and tumor necrosis were associated with LVI status (P < 0.05). Only the TNR (OR 8.655; 95% CI 2.125-37.776), Thickness (OR 6.531; 95% CI 2.410-20.608), and tumor margin (OR 4.384; 95% CI 2.004-9.717) were independent risk factors for LVI in the multivariable logistic regression analysis. The ROC curve analysis incorporating the above three CECT-derived imaging features showed that the area under the curve obtained by the multivariable logistic regression model was 0.820 (95% CI 0.754-0.885). CONCLUSION: The CECT-derived imaging features, including TNR, Thickness, tumor margin, and their combination, can be used as predictors of LVI status for patients with ESCC.

Barrierless HONO and HOS(O)2-NO2 Formation via NH3-Promoted Oxidation of SO2 by NO2.

In the troposphere, the knowledge about nitrous acid (HONO) sources is incomplete. The missing source of sulfate and fine particles cannot be explained during haze events. Air quality models cannot predict high levels of secondary fine-particle pollution. Despite extensive studies, one challenging issue in atmospheric chemistry is identifying the source of HONO. Here, we present direct ab initio molecular dynamics simulation evidence and typical air pollution events of the formation of gaseous HONO, nitrogen dioxide/hydrogen sulfite (HOS(O)2-NO2 or NO2-HSO3) from nitrogen dioxide (NO2), sulfur dioxide (SO2), water (H2O), and ammonia (NH3) molecules in a proportion of 2:1:3:3. The reactions show a new mechanism for the formation of HONO and NO2-HSO3 in the troposphere, especially when the concentration of NO2, SO2, H2O, and NH3 is high (e.g., 2:1:3:3 or higher) in the air. Contrary to the proportion NO2, SO2, H2O, and NH3 equaling to 1:1:3:1 and 1:1:3:2, the proportion (2:1:3:3) enables barrierless reactions and weak interactions between molecules via the formation of HONO, NO2-HSO3, and NH3/H2O. In addition, field observations are carried out, and the measured data are summarized. Correlation analysis supported the conversion of NO2 to HONO during observational studies. The weak interactions promote proton transfer, resulting in the generation of HONO, NO2-HSO3, and NH3/H2O pairs.

A preliminary evaluation study of applying a deep learning image reconstruction algorithm in low-kilovolt scanning of upper abdomen.

OBJECTIVE: To investigate feasibility of applying deep learning image reconstruction (DLIR) algorithm in a low-kilovolt enhanced scan of the upper abdomen. METHODS: A total of 64 patients (BMI<28) are selected for the enhanced upper abdomen scan and divided evenly into two groups. The tube voltages in Group A are 100kV in arterial phase and 80kV in venous phase, while tube voltages are 120kV during two phases in Group B. Image reconstruction algorithms used in Group A include the filtered back projection (FBP) algorithm, the adaptive statistical iterative reconstruction-Veo (ASIR-V 40% and 80%) algorithm, and the DLIR algorithm (DL-L, DL-M, DL-H). Image reconstruction algorithm used in Group B is ASIR-V40%. The different reconstruction algorithm images are used to measure the common hepatic artery, liver, renal cortex, erector spinae, and subcutaneous adipose in the arterial phase and the average CT value and standard deviation of the portal vein, liver, spleen, erector spinae, and subcutaneous adipose in the portal phase. The signal-to-noise ratio (SNR) is calculated, and the images are also scored subjectively. RESULTS: In Group A, noise in the aorta, liver, portal vein (the portal phase), spleen (the portal phase), renal cortex, retroperitoneal adipose, and muscle is significantly lower in both the DL-H and ASIR-V80% images, and the SNR is significantly higher than those in the remaining groups (P<0.05). The SNR of each tissue and organ in Group B is not significantly different from that in DL-M, DL-L, and ASIR-V40% in Group A (P>0.05). The subjective image quality scores in the DL-H and B groups are higher than those in the other groups, and the FBP group has significantly lower image quality than the remaining groups (P<0.05). CONCLUSION: For upper abdominal low-kilovolt enhanced scan data, the DLIR-H gear yields a more satisfactory image quality than the FBP and ASIR-V.

Hydroxyl, hydroperoxyl free radicals determination methods in atmosphere and troposphere.

The hydroxyl radical (•OH) has a crucial function in the oxidation and removal of many atmospheric compounds that are harmful to health. Nevertheless, high reactivity, low atmospheric abundance, determination of hydroxyl, and hydroperoxyl radical's quantity is very difficult. In the atmosphere and troposphere, hydroperoxyl radicals (HO2) are closely demanded in the chemical oxidation of the troposphere. But advances in technology have allowed researchers to improve the determination methods on the research of free radicals through some spectroscopic techniques. So far, several methods such as laser-induced fluorescence (LIF), high-performance liquid chromatography (HPLC), and chemical ionization mass spectroscopy have been identified and mostly used in determining the quantity of hydroxyl and hydroperoxyl radicals. In this systematic review, we have advised the use of scavenger as an advance for further researchers to circumvent some of these problems caused by free radicals. The primary goal of this review is to deepen our understanding of the functions of the most critical free radical (•OH, HO2) and also understand the currently used methods to quantify them in the atmosphere and troposphere.

Repeatability of small lung nodule measurement in low-dose lung screening: a phantom study.

BACKGROUND: Lung cancer screening revealed that people with small pulmonary nodules are mostly asymptomatic and that some of these people are at risk of developing lung cancer, so we intended to explore the repeatability of small lung nodule measurement in low-dose lung screening. METHODS: We scanned eight ground-glass nodules (GGNs) and solid nodules, with diameters of 3, 5, 8, and 10 mm. They were divided according to the different combination schemes of tube voltage (KV) and tube current (mA) as 70, 80, 100, and 120 KV, and currents of nine tubes were divided as 20, 30, 40, 50, 60, 70, 80, 90, and 100 mAs. RESULTS: Compared with the conventional dose group (120 kVp, 100 mAs), the nodule diameter and solid nodule volume measured by all scanning combinations were more consistent (P > 0.05), the volumes of 10 mm GGNs combinations were consistent (P > 0.05), the volumes of 8 mm GGNs were consistent (P > 0.05), the volumes of 5 mm GGNs combinations were consistent (P > 0.05), and the volumes of 3 mm were consistent (P > 0.05). CONCLUSION: In lung cancer screening, CT parameters should be as follows: tube voltage is more than 80 kVp, and tube current is 80 mAs in order to meet the requirements for the accurate measurement of the diameter and volume of pulmonary nodules.

Seasonal variation characteristics of hydroxyl radical pollution and its potential formation mechanism during the daytime in Lanzhou.

Hydroxyl free radicals (OH radicals) play the main role in atmospheric chemistry and their involving reactions are the dominant rate determining step in the formation of secondary fine particulate matter and in the removal of air pollutants from the atmosphere. In this paper, we studied the seasonal variation characteristics of OH radicals during the daytime in Lanzhou and explored the potential formation mechanism of high concentration OH radicals. We found that the OH radicals in four seasons was 2.7 × 106, 2.6 × 106, 3.1 × 106, and 2.2 × 106 cm-3, respectively. Since the rainfall was concentrated in summer, the wet deposition had a significant effect on removing OH radicals. Among the four pollutants (including ozone (O3), volatile organic compounds (VOCs), nitrogen dioxide (NO2) and fine particulate matter (PM2.5)), the variation of OH radicals were closely related to ozone concentration especially in spring and summer. In autumn, the correlation between PM2.5 and OH radicals were the closest among the observing pollutants and its formation mechanism was different conventional regeneration pathway. In Event 1, high concentration of ozone was the main source of OH radicals; under the high humidity condition, except for ozone, the multiple factors including VOCs, NO2 and PM2.5 interplayed and leaded to the Event 2.

Preparation of Electrospun Active Molecular Membrane and Atmospheric Free Radicals Capture.

We load the natural active molecules onto the spin film in an array using electrospinning techniques. The electrospun active molecular membranes we obtain in optimal parameters exhibit excellent capacity for scavenging radical. The reaction capacity of three different membranes for free radicals are shown as follow, glycyrrhizin acid membrane > quercetin membrane > α-mangostin membrane. The prepared active molecular electrospun membranes with a large specific surface area and high porosity could increase the interaction area between active molecules and free radicals. Additionally, it also has improved anti-airflow impact strength, anti-contaminant air molecular interference ability, and the ability to capture free radicals.

Potential factors and mechanism of particulate matters explosive increase induced by free radicals oxidation.

Atmospheric particulate pollution in China has attracted much public attention. Occasionally, the particle number concentration increases sharply in a short time period, which is defined as a "particulate matter explosive increase". Heavy particulate matter pollution not only reduces visibility but also has an adverse effect on human health. Hence, there is an urgent need to discover the causes of particulate matter explosive increase. During this campaign, the particle number concentration and free radicals were measured at a tall building on the campus of Lanzhou University of Technology. Additionally, we examined a series of chemicals to reproduce the observed particulate matter explosive increase in a smog chamber to determine its potential factors. Then, we analyzed the mechanism of particulate matter explosive increase in the presence of free radicals. We found that, among the potential inorganic and organic sources analyzed, a mixture of organic and SO2 in the research region had a major effect on particulate matter explosive increase. Moreover, free radical oxidation has a large effect, especially in the formation of organic particulates.

The Concentration of Iodine in Perigastric Adipose Tissue: A Novel Index for the Assessment of Serosal Invasion in Patients with Gastric Cancer after Neoadjuvant Chemotherapy.

OBJECTIVE: This study aims to explore the association between iodine concentration (IC) in perigastric adipose tissue (PAT), quantified by dual-energy computed tomography (DECT) and serosal invasion (SI) in patients with gastric cancer post-neoadjuvant chemotherapy (NAC). METHODS: Forty-three patients with T4-staged gastric cancer were enrolled. IC and standardized IC in PAT (ICPAT and SICPAT) were quantified by DECT pre and post NAC. A postoperative pathologic examination was performed to stage gastric cancer. RESULTS: After NAC, a total of 43 participants were assigned to group A with 13 patients and group B with 30 patients according to the results of the postoperative pathologic examination. The accuracy of conventional CT in identifying SI was 74.42%. Differences of variations between pre- and post- NAC ICPAT, SICPAT, ∆ICPAT, and ∆SICPAT were observed respectively (p < 0.05). Intragroup ICPAT and SICPAT also changed significantly after NAC (p < 0.05). The area under the ROC curve was 0.929, with the threshold of ∆SICPAT reaching 0.095. The sensitivity, specificity, and accuracy of SICPAT in identifying post-NAC SI were 92.30, 86.70, and 88.37% respectively. Moreover, the 2 measurements in the same patient maintain a high level of consistency. CONCLUSION: These results showed that SICPAT is a reliable index for identifying post-NAC SI.

Detection of peroxyl radicals from polluted air by free radical reaction combined with liquid chromatography signal amplification technique.

Free radicals play an important role in the oxidizing power of polluted air, the development of aging-related diseases, the formation of ozone, and the production of secondary particulate matter. The high variability of peroxyl radical concentration has prevented the detection of possible trends or distributions in the concentration of free radicals. We present a new method, free radical reaction combined with liquid chromatography photodiode array detection, for identifying and quantifying peroxyl radicals in polluted air. Functionalized graphene was used for loading peroxyl radicals and reactive molecules in air sampling system, which can facilitate reaction kinetics (charge transfers) between peroxyl radicals and reaction molecules. Separation was performed with and without a preliminary exposure of the polluted air sample to reactive molecule(s) system. The integral chromatographic peak areas before and after air sampling are used to quantify the atmospheric peroxyl radicals in polluted air. The utility of the new technique was tested with measurements carried out in the field.

Biomass-Based Carbon Nanofibers Prepared by Electrospinning for Supercapacitor.

Biomass-based carbon nanofibers were prepared by double-nozzle electrospinning the aqueous solution of acid treated the waste medicine Aconitum sinomontanum Nakai extraction and poly-acrylonitrile followed by thermal treatment in an inert atmosphere. The structural, constituent and surface properties of biomass-based carbon nanofibers were investigated by means of spectroscopic, microscopy, energy spectrometer and Brunauer-Emmet-Teller (BET) techniques. The results showed that the biomass-based carbon nanofibers had abundant pore structure and large specific surface area. The electrochemical performance of supercapacitor electrodes with the nanofibers was studied. This electrode showed a capacitance of 295 F/g at the current density of 1 A/g in 6 mol/L aqueous KOH electrolyte, and 98.5% capacity retention after 1000 charge/discharge cycles at the current density of 2 A/g. This indicate that the activate biomass-based carbon nanofibers have a good electrochemical stability.

Functionalized graphene quantum dots loaded with free radicals combined with liquid chromatography and tandem mass spectrometry to screen radical scavenging natural antioxidants from Licorice and Scutellariae.

A novel screening method was developed for the detection and identification of radical scavenging natural antioxidants based on a free radical reaction combined with liquid chromatography with tandem mass spectrometry. Functionalized graphene quantum dots were prepared for loading free radicals in the complex screening system. The detection was performed with and without a preliminary exposure of the samples to specific free radicals on the functionalized graphene quantum dots, which can facilitate charge transfer between free radicals and antioxidants. The difference in chromatographic peak areas was used to identify potential antioxidants. This is a novel approach to simultaneously evaluate the antioxidant power of a component versus a free radical, and to identify it in a vegetal matrix. The structures of the antioxidants in the samples were identified using tandem mass spectrometry and comparison with standards. Fourteen compounds were found to possess potential antioxidant activity, and their free radical scavenging capacities were investigated. The order of scavenging capacity of 14 compounds was compared according to their free radical scavenging rate. 4',5,6,7-Tetrahydroxyflavone (radical scavenging rate: 0.05253 mL mg(-1) s(-1) ) showed the strongest capability for scavenging free radicals.

Deep learning nomogram for predicting neoadjuvant chemotherapy response in locally advanced gastric cancer patients.

PURPOSE: Developed and validated a deep learning radiomics nomogram using multi-phase contrast-enhanced computed tomography (CECT) images to predict neoadjuvant chemotherapy (NAC) response in locally advanced gastric cancer (LAGC) patients. METHODS: This multi-center study retrospectively included 322 patients diagnosed with gastric cancer from January 2013 to June 2023 at two hospitals. Handcrafted radiomics technique and the EfficientNet V2 neural network were applied to arterial, portal venous, and delayed phase CT images to extract two-dimensional handcrafted and deep learning features. A nomogram model was built by integrating the handcrafted signature, the deep learning signature, with clinical features. Discriminative ability was assessed using the receiver operating characteristics (ROC) curve and the precision-recall (P-R) curve. Model fitting was evaluated using calibration curves, and clinical utility was assessed through decision curve analysis (DCA). RESULTS: The nomogram exhibited excellent performance. The area under the ROC curve (AUC) was 0.848 [95% confidence interval (CI), 0.793-0.893)], 0.802 (95% CI 0.688-0.889), and 0.751 (95% CI 0.652-0.833) for the training, internal validation, and external validation sets, respectively. The AUCs of the P-R curves were 0.838 (95% CI 0.756-0.895), 0.541 (95% CI 0.329-0.740), and 0.556 (95% CI 0.376-0.722) for the corresponding sets. The nomogram outperformed the clinical model and handcrafted signature across all sets (all P < 0.05). The nomogram model demonstrated good calibration and provided greater net benefit within the relevant threshold range compared to other models. CONCLUSION: This study created a deep learning nomogram using CECT images and clinical data to predict NAC response in LAGC patients undergoing surgical resection, offering personalized treatment insights.