Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study.

BACKGROUND: Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL) model for accurate detection of colorectal cancer, and evaluate whether it could improve the detection performance of radiologists. METHODS: We developed a DL model using a manually annotated dataset (1196 cancer vs 1034 normal). The DL model was tested using an internal test set (98 vs 115), two external test sets (202 vs 265 in 1, and 252 vs 481 in 2), and a real-world test set (53 vs 1524). We compared the detection performance of the DL model with radiologists, and evaluated its capacity to enhance radiologists' detection performance. FINDINGS: In the four test sets, the DL model had the area under the receiver operating characteristic curves (AUCs) ranging between 0.957 and 0.994. In both the internal test set and external test set 1, the DL model yielded higher accuracy than that of radiologists (97.2% vs 86.0%, p < 0.0001; 94.9% vs 85.3%, p < 0.0001), and significantly improved the accuracy of radiologists (93.4% vs 86.0%, p < 0.0001; 93.6% vs 85.3%, p < 0.0001). In the real-world test set, the DL model delivered sensitivity comparable to that of radiologists who had been informed about clinical indications for most cancer cases (94.3% vs 96.2%, p > 0.99), and it detected 2 cases that had been missed by radiologists. INTERPRETATION: The developed DL model can accurately detect colorectal cancer and improve radiologists' detection performance, showing its potential as an effective computer-aided detection tool. FUNDING: This study was supported by National Science Fund for Distinguished Young Scholars of China (No. 81925023); Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No. U22A20345); National Natural Science Foundation of China (No. 82072090 and No. 82371954); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); High-level Hospital Construction Project (No. DFJHBF202105).

Trends and hotspots in acupuncture treatment of rat models of stroke: a bibliometric analysis from 2004 to 2023.

Background: Acupuncture is a widely used clinical treatment method, and studies have confirmed its therapeutic effects on stroke patients. It can also reduce the burden on patients and society. Acupuncture treatment is a complementary and preventive treatment for stroke. However, there has yet to be a visual bibliometric analysis of the field of acupuncture for stroke rat models. This study explores future trends, research hotspots, and frontiers in acupuncture for stroke rat models over the past 20 years through investigation and visualization. Methods: We collected literature data on acupuncture treatment of stroke in rats from the Web of Science Core Collection (WOSCC) database from January 1, 2004, to December 31, 2023. Import into CiteSpace (version 6.2.R4) and RStudio for analysis by author, country/region, affiliation, annual publication, keywords, and journal visualization. Results: A total of 379 articles were retrieved, including articles from 16 countries, 258 research institutions, and 123 academic journals. The countries and institutions with the most publications were the People's Republic of China (338) and the Fujian University of Traditional Chinese Medicine (43). Tao, Jing had the highest number of co-citations (144). The keywords and co-citation clustering show the main research directions in the field, including "artery occlusion," "neural regeneration," "stimulation," "rapid tolerance," "receptor," "signaling pathway," "apoptosis," "oxidative stress," "inflammatory response," "endogenous neurogenesis," "tolerance of local cerebral ischemic tissues," "proliferation of reactive astrocytes" and "neuroprotective effect." The intervention combines classical acupuncture treatment and modern technology (electricity) with electroacupuncture as a new intervention modality. Conclusion: This study demonstrates the increasing research on acupuncture for treating stroke in rat models. The country/region with the most publications is the People's Republic of China. However, international cooperation still needs to be improved, and future researchers must strengthen international cooperation. In addition, in future studies, researchers should improve the overall quality of research results in this area and enhance research protocols.

A novel mutation in mitochondrial cytochrome b conferring resistance to bifenazate in two-spotted spider mite Tetranychus urticae Koch (Acarina: Tetranychidae).

BACKGROUND: The two-spotted spider mite Tetranychus urticae causes significant damage to ornamental, cotton, sugarcane and horticultural crops in Australia. It has a long history of developing resistance to many acaricides including bifenazate. A mutation in the conserved cd1- and ef-helices of the Qo pocket of cytochrome b is recognized as the primary mechanism of bifenazate resistance. To investigate the resistance mechanisms against bifenazate in Australian two-spotted spider mite, we sequenced the complete mitochondrion genome of five mite strains including a susceptible and bifenazate-resistant strain. RESULTS: We identified a novel mutation D252N in the G126S background at cytochrome b being the cause of bifenazate resistance in a bifenazate-resistant strain, Bram. We validated the role of this mutation combination by reciprocal crosses between a bifenazate resistant and susceptible strain. By doing these crosses we confirmed the pattern of inheritance was maternal. Additionally, mitochondrial heteroplasmy was not observed by single mite genotyping of the mutations in cytb in a known bifenazate-resistant strain Bram. The phylogenetic analysis with the complete mitochondrion genome sequences revealed that Australian two-spotted spider mite strains are closely related to the green form of T. urticae found in China. CONCLUSIONS: The novel mutation D252N found in the cytochrome b in the G126S background was revealed to be the main cause of bifenazate resistance in the Australian T. urticae strain Bram. © 2024 Society of Chemical Industry.

Self-Flipping Solar Seesaw Evaporators Leverage Scaling to De-Scale.

Salt scaling poses a significant obstacle to the practical implementation of solar-driven evaporation for desalination. Attempts to mitigate scaling by enhancing mass transfer often lead to a compromise in evaporation efficiency due to associated heat loss. In the present work, a novel seesaw evaporator with a Janus structure to harness scaling for periodic self-descaling is reported. The seesaw evaporators are facilely fabricated by delignifying balsa wood and subsequently single-sided spray-coating it with soot and polydimethylsiloxane (PDMS). This unique Janus structure enables the evaporator to float on the brine while ensuring an ample supply of solution for evaporation. During evaporation, salt ions are transported directionally toward the cocked end of the evaporator to form scaling, triggering the seesaw evaporator to flip once a threshold is reached. The accumulated salts re-dissolve back into the solution. By adjusting the tilt angle, the evaporator can achieve an impressive evaporation rate of up to 2.65 kg m-2  h-1 when evaporating an 8 wt.% NaCl solution. Remarkably, these evaporators maintain a stable evaporation rate during prolonged 120 h operation and produce ≈3.93-6.35 L m⁻2 ·day⁻¹ of freshwater from simulated brines when assembled into an evaporation device.

Predictive Value of CFIm25 Expression in Peripheral Blood Monocytes for Coronary Atherosclerosis.

Background: Cleavage factor Im25 (CFIm25) regulates cell function by affecting mRNA editing processes and plays diverse roles in various diseases. Studies have found that peripheral blood monocytes are valuable in diagnosing and prognosing coronary atherosclerosis. However, no studies have examined the predictive value of CFIm25 expression in peripheral blood monocytes for coronary atherosclerosis. Methods and Results: We collected the coronary angiography results of 267 patients and calculated the Gensini score to evaluate their degree of coronary atherosclerosis. We isolated peripheral blood monocytes and detected CFIm25 RNA expression. Based on their Gensini score, we divided the patients into negative (0, n = 46), mild lesion (≤ 8, n = 71), moderate lesion (8-23, n = 76), and severe lesion (≥ 23, n = 74) groups. Results showed that CFIm25 expression correlated negatively with the Gensini score and the number of involved coronary vessels. Univariate and multivariate binary logistic regression analyses showed that CFIm25 expression in peripheral blood monocytes was a protective factor for severe lesions, ≥ 50% stenosis, and three-vessel lesions. The areas under the receiver operating characteristic curve of CFIm25 expression for predicting lesions, severe lesions, ≥50% stenosis, and three-vessel lesions were 0.743, 0.735, 0.791, and 0.736, respectively. Conclusions: CFIm25 expression in peripheral blood monocytes correlates negatively with the degree of coronary atherosclerosis and helps predict the severity and number of coronary artery lesions.

A high-throughput multilocus-amplicon sequencing panel to monitor insecticide resistance in fall armyworm (FAW) Spodoptera frugiperda (Lepidoptera: Noctuidae).

BACKGROUND: Fall armyworm (FAW), Spodoptera frugiperda, is a highly polyphagous crop pest that has spread over the world rapidly and invaded Australia in 2020. Globally, FAW has been reported to be resistant to several insecticides permitted in Australia. Timely resistance diagnosis is critical for integrated pest management-based control of FAW in Australia. RESULTS: We developed a multi-amplicon panel by next-generation sequencing (multiamplicon-seq) to identify known insecticide resistance mutations in Australian FAW with high throughput and low cost. The panel included nine known mutations causing insecticide resistance in FAW and four gene mutations causing insecticide resistance in several insect species, not yet reported in FAW. We sequenced 36 plates (96-well) in one MiSeq flow cell with easy sequencing library preparation. We found that Australian FAW carried a very high proportion of the F290V mutation in the acetylcholinesterase (AChE) gene that causes resistance to organophosphate and carbamate insecticides. Furthermore, FAW has a GABA-activated chloride channel mutation, A301Q in the RDL gene. The sequencing-based platform provided evidence of a duplication in the AChE gene. Here several single nucleotide polymorphisms (SNPs) within the 476-bp amplicon of the AChE gene demonstrated 100% heterozygosity across samples and some individuals carried two haplotypes with the F290V mutation. CONCLUSION: Molecular surveillance by multiamplicon-seq will increase capacity for early detection and future resistance monitoring in highly dispersed Australian FAW. It can provide timely resistance information and has the potential to play an important role in the resistance management of FAW. © 2023 Society of Chemical Industry.

T-cell Immunoglobulin and Mucin Domain 3 in Circulating Monocytes as a Novel Biomarker for Coronary Artery Disease.

The diagnostic role of T-cell immunoglobulin and mucin domain 3 (Tim-3) expression levels in circulating monocytes in coronary artery disease (CAD) remains to be determined. Here, we enrolled of 265 patients and isolated circulating monocytes from the blood of all participants. We found that the Tim-3 expression levels in monocytes were lower in CAD patients than in the control group. Spearman correlation analysis verified that the Tim-3 levels in monocytes were negatively correlated with the Gensini score and the number of coronary vessels. Multivariate logistic regression analysis showed that the Tim-3 levels in circulating monocytes were negatively correlated with CAD, severe CAD, and three-vessel CAD. The ROC curve showed that Tim-3 possessed high diagnostic value for CAD, severe CAD, and three-vessel CAD, with CAD prediction being the most significant of these values. In conclusion, Tim-3 in circulating monocytes is a novel biomarker for CAD. T-cell immunoglobulin and mucin domain 3 (Tim-3) in circulating monocytes as a novel biomarker for coronary artery disease.

Survival and analysis of prognostic factors for primary malignant cardiac tumors based on the SEER database.

PURPOSE: The purpose of this study was to use the Surveillance, Epidemiology, and End Results (SEER) database to evaluate the survival rate of primary malignant cardiac tumors (PMCTs), assess the risk factors affecting survival, and calculate the number of PMCT cases in recent years. METHODS: SEER 22 registries were used to calculate the number of cases PMCT. Data on age, sex, race, marital status, tumor size, the American Joint Committee on Cancer (AJCC) stage, lymph node involvement, metastasis, treatment, and survival were collected to analyze the survival and prognostic factors of SEER 17 registries. Using the Kaplan-Meier estimation method, a survival curve was obtained according to the influencing factors, and a multivariable Cox regression model was established. RESULTS: In recent years, the average annual number of PMCT cases was 20.56 ± 7.12, significantly higher than the average before 2004 (P = 0.015; 95% CI 1.14-8.98). The 1-, 3-, and 5-year survival rates were 45.6%, 18.8%, and 11.2%, respectively. Multivariate analysis revealed that age (risk ratio [HR], 2.047; 95% CI 1.381-3.034), AJCC stage III (HR, 1.786; 95% CI 1.123-2.839), AJCC staging with distant metastasis (HR, 2.666; 95% CI 1.509-4.709), no chemotherapy (HR, 2.011; 95% CI 1.561-2.590), and tumor size larger than 99 mm (HR, 1.766; 95% CI 1.132-2.756) were independent risk factors for poor prognosis. Only age over 76 years and distant metastasis were independent risk factors for prognosis in the chemotherapy group. CONCLUSION: In recent years, the annual number of patients with PMCT has increased significantly. Due to developments in chemotherapy, we should re-evaluate the traditional tumor staging and prognostic risk indicators to improve clinical applications.

Red-Fleshed Apple Flavonoids Extract Alleviates Male Reproductive Injury Caused by Busulfan in Mice.

In this research, we analyzed the protective effects of red-fleshed apple flavonoid extracts (RAFEs) on male reproductive injury induced by busulfan, using both in vitro and in vivo models. In the cell-based experiments, RAFEs significantly improved cell viability and proliferation rates compared to control groups. Similarly, in vivo testing with male mice showed that RAFEs and whole apple flavonoid extracts (WAFEs) enhanced various biochemical and liver function-related indicators in the testes; however, RAFEs demonstrated superior efficacy in mitigating testicular damage. Through immunohistochemistry, qRT-PCR, and Western blotting, we found that RAFEs notably enhanced the expression of spermatogenesis-related genes. Moreover, RAFEs increased the expression of oxidative stress- and apoptosis-related genes, thereby effectively reducing oxidative damage in the testes. These findings highlight the potential of RAFEs as natural agents for the prevention and treatment of male reproductive injury, paving the way for future research and potential therapeutic applications.

Automatic 3D Teeth Reconstruction from Five Intra-oral Photos Using Parametric Teeth Model.

Orthodontic treatment is a lengthy process that requires regular in-person dental monitoring, making remote dental monitoring a viable alternative when face-to-face consultation is not possible. In this study, we propose an improved 3D teeth reconstruction framework that automatically restores the shape, arrangement, and dental occlusion of upper and lower teeth from five intra-oral photographs to aid orthodontists in visualizing the condition of patients in virtual consultations. The framework comprises a parametric model that leverages statistical shape modeling to describe the shape and arrangement of teeth, a modified U-net that extracts teeth contours from intra-oral images, and an iterative process that alternates between finding point correspondences and optimizing a compound loss function to fit the parametric teeth model to predicted teeth contours. We perform a five-fold cross-validation on a dataset of 95 orthodontic cases and report an average Chamfer distance of 1.0121 mm2 and an average Dice similarity coefficient of 0.7672 on all the test samples in the cross-validation, demonstrating a significant improvement compared with the previous work. Our teeth reconstruction framework provides a feasible solution for visualizing 3D teeth models in remote orthodontic consultations.

Dry eye syndrome model established in rabbits via mitomycin C injection in the lacrimal gland.

PURPOSE: To develop a new dry eye syndrome (DES) animal model by injecting mitomycin C (MMC) into the lacrimal glands (LGs) of rabbits evaluated by clinical examinations. MATERIALS AND METHODS: A volume of 0.1 mL of MMC solution was injected in the LG and the infraorbital lobe of the accessory LG of rabbits for DES induction. Twenty male rabbits were separated into three groups, the control group, and different concentration of MMC, (MMC 0.25: 0.25 mg/mL or MMC 0.50: 0.5 mg/mL) were tested. Both MMC-treated groups received MMC twice injection on day 0 and day 7. Assessment of DES included changes in tear production (Schirmer's test), fluorescein staining pattern, conjunctival impression cytology, and corneal histological examination. RESULTS: After MMC injection, no obvious changes in the rabbit's eyes were noted by slit-lamp examination. Both the MMC 0.25 and the MMC 0.5 groups revealed decreased tear secretion after injection, and the MMC 0.25 group showed a continuous decrease in tear secretion up to 14 days. Fluorescent staining showed punctate keratopathy in both MMC-treated groups. In addition, both MMC-treated groups demonstrated decreased numbers of conjunctival goblet cells after injection. CONCLUSION: This model induced decreased tear production, punctate keratopathy, and decreased numbers of goblet cells, which are consistent with the current understanding of DES. Therefore, injecting MMC (0.25 mg/mL) into the LGs is an easy and reliable method to establish a rabbit DES model which can apply in new drug screening.

Nonlinear Strength Reduction Method of Rock Mass in Slope Stability Evaluation.

As the strength parameters of rock mass degrade differently during slope instability, different factors should be considered in the strength reduction method. Previous nonlinear reduction methods were essentially implemented based on the Mohr-Coulomb criterion, which was reported not to reflect the nonlinear performance of rock mass. To address this deficiency, in this study, the Hoek-Brown criterion was combined with a nonlinear reduction technique for slope stability evaluation. Firstly, based on the classical definition of safety factors, the relationships that should be satisfied by each parameter of the critical slope were derived. The critical curve of the slope regarding the Hoek-Brown constant mb and the uniaxial compressive strength of rock mass σcmass was then obtained. On the assumption that the slope parameter deterioration conforms to the shortest path theory, the reduction ratio of σcmass to mb was determined. The more objective k-means algorithm was employed to automatically search the potential sliding surface, on which the slope safety factor was calculated as the ratio of sliding resistance to sliding force. Finally, the slopes in published literature were adopted for verification, and the calculated safety factors were compared with those by other methods, which showed better efficacy.

Multi-treatment Effect Estimation from Biomedical Data.

Several biomedical applications contain multiple treatments from which we want to estimate the causal effect on a given outcome. Most existing Causal Inference methods, however, focus on single treatments. In this work, we propose a neural network that adopts a multi-task learning approach to estimate the effect of multiple treatments. We validated M3E2 in three synthetic benchmark datasets that mimic biomedical datasets. Our analysis showed that our method makes more accurate estimations than existing baselines.

Short sleep duration associated with increased risk for new-onset cardiovascular diseases in individuals with metabolic syndromes: Evidence from the China Health and Retirement Longitudinal Study.

To explore the impact and risk of short sleep duration (sleep duration < 6 h/night) on new-onset cardiovascular and cerebrovascular diseases (CVDs) in people with metabolic syndromes (Mets), this study used the 2011 baseline and 2015 follow-up data from the China Longitudinal Study of Health and Retirement (CHARLS) to conduct a prospective study of people aged ≥ 45 years in China. A total of 5,530 individuals without pre-existing CVDs in baseline were included. Mets were defined according to the harmonized criteria. We applied the Logistic Regression (LR), the Deep Neural Networks (DNN), and the Adaptive Boosting (AdaBoost), to evaluate the association between Mets components, short sleep, and the risk of new-onset CVDs, and the importance of multiple variates for new-onset CVDs. During the 4-year follow-up period, 512 individuals developed CVDs, and short sleep increased the risk of CVD in individuals with Mets. The odds ratio for prevalent CVD in Mets with short sleep group was 3.73 (95%CI 2.95-4.71; P < 0.001) compared to the normal group, and 1.99 (95% CI 1.58-2.51; P < 0.001) compared to the Mets without short sleep group. The DNN method reached the highest precision of 92.24% and f1-score of 95.86%, and the Adaboost method reached the highest recall of 99.92%. Both DNN and Adaboost have better predictive performance than LR and revealed short sleep duration and components of Mets are all the strongest predictors of CVD onset.

Compatibility and function of human induced pluripotent stem cell derived cardiomyocytes on an electrospun nanofibrous scaffold, generated from an ionomeric polyurethane composite.

Synthetic scaffolds are needed for generating organized neo-myocardium constructs to promote functional tissue repair. This study investigated the biocompatibility of an elastomeric electrospun degradable polar/hydrophobic/ionic polyurethane (D-PHI) composite scaffold with human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). The composite material was electrospun to generate scaffolds, with nanofibres oriented in aligned or random directions. These features enabled the authors to evaluate the effect of characteristic elements which mimic that of the native extracellular matrix (alignment, chemical heterogeneity, and fiber topography) on hiPSC-CMs activity. The functional nature of the hiPSC-CM cultured on gelatin and Matrigel-coated scaffolds were assessed, investigating the influence of protein interactions with the synthetic substrate on subsequent cell phenotype. After 7 days of culture, high hiPSC-CM viability was observed on the scaffolds. The cells on the aligned scaffold were elongated and demonstrated aligned sarcomeres that oriented parallel to the direction of the fibers, while the cells on random scaffolds and a tissue culture polystyrene (TCPS) control did not exhibit such an organized morphology. The hiPSC-CMs cultured on the scaffolds and TCPS expressed similar levels of cardiac troponin-T, but there was a higher expression of ventricular myosin light chain-2 on the D-PHI composite scaffolds versus TCPS, indicating a higher proportion of hiPSC-CM exhibiting a ventricular cardiomyocyte like phenotype. Within 7 days, the hiPSC-CMs on aligned scaffolds and TCPS beat synchronously and had similar conductive velocities. These preliminary results show that aligned D-PHI elastomeric scaffolds allow hiPSC-CMs to demonstrate important cardiomyocytes characteristics, critical to enabling their future potential use for cardiac tissue regeneration.

Medical image augmentation for lesion detection using a texture-constrained multichannel progressive GAN.

Lesion detectors based on deep learning can assist doctors in diagnosing diseases. However, the performance of current detectors is likely to be unsatisfactory due to the scarcity of training samples. Therefore, it is beneficial to use image generation to augment the training set of a detector. However, when the imaging texture of the medical image is relatively delicate, the synthesized image generated by an existing method may be too poor in quality to meet the training requirements of the detectors. In this regard, a medical image augmentation method, namely, a texture-constrained multichannel progressive generative adversarial network (TMP-GAN), is proposed in this work. TMP-GAN uses joint training of multiple channels to effectively avoid the typical shortcomings of the current generation methods. It also uses an adversarial learning-based texture discrimination loss to further improve the fidelity of the synthesized images. In addition, TMP-GAN employs a progressive generation mechanism to steadily improve the accuracy of the medical image synthesizer. Experiments on the publicly available dataset CBIS-DDMS and our pancreatic tumor dataset show that the precision/recall/F1-score of the detector trained on the TMP-GAN augmented dataset improves by 2.59%/2.70%/2.77% and 2.44%/2.06%/2.36%, respectively, compared to the optimal results of other data augmentation methods. The FROC curve of the detector is also better than the curve from the contrast-augmented trained dataset. Therefore, we believe the proposed TMP-GAN is a practical technique to efficiently implement lesion detection case studies.

Generative Adversarial Networks in Medical Image augmentation: A review.

OBJECT: With the development of deep learning, the number of training samples for medical image-based diagnosis and treatment models is increasing. Generative Adversarial Networks (GANs) have attracted attention in medical image processing due to their excellent image generation capabilities and have been widely used in data augmentation. In this paper, a comprehensive and systematic review and analysis of medical image augmentation work are carried out, and its research status and development prospects are reviewed. METHOD: This paper reviews 105 medical image augmentation related papers, which mainly collected by ELSEVIER, IEEE Xplore, and Springer from 2018 to 2021. We counted these papers according to the parts of the organs corresponding to the images, and sorted out the medical image datasets that appeared in them, the loss function in model training, and the quantitative evaluation metrics of image augmentation. At the same time, we briefly introduce the literature collected in three journals and three conferences that have received attention in medical image processing. RESULT: First, we summarize the advantages of various augmentation models, loss functions, and evaluation metrics. Researchers can use this information as a reference when designing augmentation tasks. Second, we explore the relationship between augmented models and the amount of the training set, and tease out the role that augmented models may play when the quality of the training set is limited. Third, the statistical number of papers shows that the development momentum of this research field remains strong. Furthermore, we discuss the existing limitations of this type of model and suggest possible research directions. CONCLUSION: We discuss GAN-based medical image augmentation work in detail. This method effectively alleviates the challenge of limited training samples for medical image diagnosis and treatment models. It is hoped that this review will benefit researchers interested in this field.

CT classification model of pancreatic serous cystic neoplasms and mucinous cystic neoplasms based on a deep neural network.

BACKGROUND: At present, numerous challenges exist in the diagnosis of pancreatic SCNs and MCNs. After the emergence of artificial intelligence (AI), many radiomics research methods have been applied to the identification of pancreatic SCNs and MCNs. PURPOSE: A deep neural network (DNN) model termed Multi-channel-Multiclassifier-Random Forest-ResNet (MMRF-ResNet) was constructed to provide an objective CT imaging basis for differential diagnosis between pancreatic serous cystic neoplasms (SCNs) and mucinous cystic neoplasms (MCNs). MATERIALS AND METHODS: This study is a retrospective analysis of pancreatic unenhanced and enhanced CT images in 63 patients with pancreatic SCNs and 47 patients with MCNs (3 of which were mucinous cystadenocarcinoma) confirmed by pathology from December 2010 to August 2016. Different image segmented methods (single-channel manual outline ROI image and multi-channel image), feature extraction methods (wavelet, LBP, HOG, GLCM, Gabor, ResNet, and AlexNet) and classifiers (KNN, Softmax, Bayes, random forest classifier, and Majority Voting rule method) are used to classify the nature of the lesion in each CT image (SCNs/MCNs). Then, the comparisons of classification results were made based on sensitivity, specificity, precision, accuracy, F1 score, and area under the receiver operating characteristic curve (AUC), with pathological results serving as the gold standard. RESULTS: Multi-channel-ResNet (AUC 0.98) was superior to Manual-ResNet (AUC 0.91).CT image characteristics of lesions extracted by ResNet are more representative than wavelet, LBP, HOG, GLCM, Gabor, and AlexNet. Compared to the use of three classifiers alone and Majority Voting rule method, the use of the MMRF-ResNet model exhibits a better evaluation effect (AUC 0.96) for the classification of the pancreatic SCNs and MCNs. CONCLUSION: The CT image classification model MMRF-ResNet is an effective method to distinguish between pancreatic SCNs and MCNs.

Comparison of gastrojejunostomy to endoscopic stenting for gastric outlet obstruction: An updated Systematic Review and Meta-analysis.

BACKGROUND: This study aimed to determine the optimal intervention modality for malignant GOO by comparing clinical outcomes after Gastrojejunostomy and endoscopic stenting. METHODS: Two authors independently searched Web of Science, PubMed, Embase, and the Cochrane Library for articles before February 2021 to compare the clinical outcomes of GOO patients undergoing GJ or ES. RESULTS: This meta-analysis included 31 articles with 2444 GOO patients. Although the GJ group outperformed the ES group in technical success (OR,3.79; P = 0.003), clinical success was not significantly different between the two groups (OR,1.25; P = 0.50). The GJ group had a longer hospitalization, lower re-obstruction and lower reintervention. Moreover, GJ had a better survival than ES in the gastric cancer group (HR, 0.33; P = 0.009). However, no significant statistical difference was observed in the pancreatic cancer group (HR, 0.55; P = 0.159). CONCLUSIONS: Both GJ and ES are safe and effective intervention modalities for malignant GOO. GJ had significantly improved survival in gastric cancer patients with GOO, while no significant difference was observed between the two groups in pancreatic cancer patients with GOO.

Red-fleshed apple flavonoid extract alleviates CCl4-induced liver injury in mice.

In recent years, the global incidence of liver damage has increased. Despite the many known health benefits of red-fleshed apple flavonoids, their potential liver-protective effects have not yet been investigated. In this study, we analyzed the composition of red-fleshed apple flavonoid extract (RAFE) by high-performance liquid chromatography (HPLC). We then induced liver damage in mice with carbon tetrachloride (CCl4) and performed interventions with RAFE to analyze its effect on liver damage, using bifendate as a positive control. The results showed that catechin was the most abundant flavonoid in 'XJ4' RAFE (49.346 mg/100 g). In liver-injured mice, the liver coefficients converged to normal levels following RAFE intervention. Moreover, RAFE significantly reduced the enzymatic activity levels of glutamic oxaloacetic transaminase (ALT), glutamic alanine transaminase (AST), and alkaline phosphatase (ALP) in mouse serum. Furthermore, RAFE significantly increased the content or enzyme activity level of total glutathione, total antioxidant capacity, and superoxide dismutase, and significantly decreased the content of malondialdehyde in the liver of mice. In parallel, we performed histopathological observations of mouse livers for each group. The results showed that RAFE restored the pathological changes caused by CCl4 around the central hepatic vein in mice and resulted in tightly bound hepatocytes. The recovery effect of RAFE was dose-dependent in the liver tissue. Regarding intestinal microorganisms, we found that RAFE restored the microbial diversity in liver-injured mice, with a similar microbial composition in the RAFE intervention group and normal group. RAFE reduced the ratio of Firmicutes to Bacteroidetes, increased the levels of probiotic bacteria, such as Lactobacillus acidophilus, and Clostridium, and reduced the levels of harmful bacteria, such as Erysipelothrix Rosenbach. Therefore, RAFE ameliorated CCl4-induced liver damage by modulating the abundance and composition of intestinal microorganisms in mice. In conclusion, RAFE alleviated CCl4-induced liver damage in mice, with H-RAFE (5 mg kg-1) significantly improving liver damage in mice but M-RAFE (1 mg kg-1) significantly improving the imbalance of intestinal microorganisms in mice. Our research suggests that RAFE could be employed for the adjuvant treatment and prevention of liver damage, and may have important applications in food and medicine.