Transpancreatic Sphincterotomy After Double Guidewire Technique Was Noninferior to Primary Transpancreatic Sphincterotomy in Difficult Biliary Cannulation.

BACKGROUND: When unintentional pancreatic duct access occurs during difficult biliary cannulation, the double guidewire (DGW) or transpancreatic sphincterotomy (TPS) may be utilized. DGW can be easily switched to TPS due to the existing guidewire in the pancreatic duct. However, the efficacy of TPS after DGW, named sequential DGW-TPS technique, versus primary TPS has not been assessed. AIMS: Our aim was to compare the benefits and adverse events of sequential DGW-TPS technique and primary TPS. METHODS: We performed a comparative retrospective cohort study that enrolled a total of 117 patients with native papillae. The patients were divided into one of 2 groups according to the primary bile duct access technique (sequential DGW-TPS or primary TPS), both with pancreatic stenting. RESULTS: Between November 2017 and May 2023, a total of 84 patients were grouped into sequential DGW-TPS and 33 into primary TPS. The overall post-ERCP pancreatitis (PEP) rate was 4.3% in the entire cohort, with no statistical differences were observed between the groups in terms of PEP rates (P = 0.927), PEP severity (P = 1.000), first biliary cannulation success (P = 0.621), overall cannulation success (P = 1.000), hyperamylasemia incidence (P = 0.241), elevated amylase levels (P = 0.881), and postoperative hospital stay (P = 0.185). Furthermore, these results remained consistent in multivariable regression analysis. CONCLUSIONS: The sequential DGW-TPS technique showed a comparable safety and biliary cannulation success rate to primary TPS in difficult biliary cannulation. Given the potential long-term complications associated with TPS, DGW should be first if inadvertent pancreatic access occurs, with TPS serving as second only if DGW fails.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma.

BACKGROUND: The study on predicting the differentiation grade of colorectal cancer (CRC) based on magnetic resonance imaging (MRI) has not been reported yet. Developing a non-invasive model to predict the differentiation grade of CRC is of great value. AIM: To develop and validate machine learning-based models for predicting the differentiation grade of CRC based on T2-weighted images (T2WI). METHODS: We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023. Patients were randomly assigned to a training cohort (n = 220) or a validation cohort (n = 95) at a 7:3 ratio. Lesions were delineated layer by layer on high-resolution T2WI. Least absolute shrinkage and selection operator regression was applied to screen for radiomic features. Radiomics and clinical models were constructed using the multilayer perceptron (MLP) algorithm. These radiomic features and clinically relevant variables (selected based on a significance level of P < 0.05 in the training set) were used to construct radiomics-clinical models. The performance of the three models (clinical, radiomic, and radiomic-clinical model) were evaluated using the area under the curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: After feature selection, eight radiomic features were retained from the initial 1781 features to construct the radiomic model. Eight different classifiers, including logistic regression, support vector machine, k-nearest neighbours, random forest, extreme trees, extreme gradient boosting, light gradient boosting machine, and MLP, were used to construct the model, with MLP demonstrating the best diagnostic performance. The AUC of the radiomic-clinical model was 0.862 (95%CI: 0.796-0.927) in the training cohort and 0.761 (95%CI: 0.635-0.887) in the validation cohort. The AUC for the radiomic model was 0.796 (95%CI: 0.723-0.869) in the training cohort and 0.735 (95%CI: 0.604-0.866) in the validation cohort. The clinical model achieved an AUC of 0.751 (95%CI: 0.661-0.842) in the training cohort and 0.676 (95%CI: 0.525-0.827) in the validation cohort. All three models demonstrated good accuracy. In the training cohort, the AUC of the radiomic-clinical model was significantly greater than that of the clinical model (P = 0.005) and the radiomic model (P = 0.016). DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process. CONCLUSION: In this study, we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC. This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Incidence and risk factors for pulmonary hemorrhage after percutaneous CT-guided pulmonary nodule biopsy: an observational study.

To evaluate the current incidence of pulmonary hemorrhage and the potential factors contributing to its increased risk after percutaneous CT-guided pulmonary nodule biopsy and to summarize the technical recommendations for its treatment. In this observational study, patient data were collected from ten medical centers from April 2021 to April 2022. The incidence of pulmonary hemorrhage was as follows: grade 0, 36.1% (214/593); grade 1, 36.8% (218/593); grade 2, 18.9% (112/593); grade 3, 3.5% (21/593); and grade 4, 4.7% (28/593). High-grade hemorrhage (HGH) occurred in 27.2% (161/593) of the patients. The use of preoperative breathing exercises (PBE, p =0.000), semiautomatic cutting needles (SCN, p = 0.004), immediate contrast enhancement (ICE, p =0.021), and the coaxial technique (CoT, p = 0.000) were found to be protective factors for HGH. A greater length of puncture (p =0.021), the presence of hilar nodules (p = 0.001), the presence of intermediate nodules (p = 0.026), a main pulmonary artery diameter (mPAD) larger than 29 mm (p = 0.015), and a small nodule size (p = 0.014) were risk factors for high-grade hemorrhage. The area under the curve (AUC) was 0.783. These findings contribute to a deeper understanding of the risks associated with percutaneous CT-guided pulmonary nodule biopsy and provide valuable insights for developing strategies to minimize pulmonary hemorrhage.

Multi-objective pedestrian tracking method based on YOLOv8 and improved DeepSORT.

A multi-objective pedestrian tracking method based on you only look once-v8 (YOLOv8) and the improved simple online and real time tracking with a deep association metric (DeepSORT) was proposed with the purpose of coping with the issues of local occlusion and ID dynamic transformation that frequently arise when tracking target pedestrians in real complex traffic scenarios. To begin with, in order to enhance the feature extraction network's capacity to learn target feature information in busy traffic situations, the detector implemented the YOLOv8 method with a high level of small-scale feature expression. In addition, the omni-scale network (OSNet) feature extraction network was then put on top of DeepSORT in order to accomplish real-time synchronized target tracking. This increases the effectiveness of picture edge recognition by dynamically fusing the collected feature information at various scales. Furthermore, a new adaptive forgetting smoothing Kalman filtering algorithm (FSA) was created to adapt to the nonlinear condition of the pedestrian trajectory in the traffic scene in order to address the issue of poor prediction attributed to the linear state equation of Kalman filtering once more. Afterward, the original intersection over union (IOU) association matching algorithm of DeepSORT was replaced by the complete-intersection over union (CIOU) association matching algorithm to fundamentally reduce the target pedestrians' omission and misdetection situation and to improve the accuracy of data matching. Eventually, the generalized trajectory feature extractor model (GFModel) was developed to tightly merge the local and global information through the average pooling operation in order to get precise tracking results and further decrease the impact of numerous disturbances on target tracking. The fusion algorithm of YOLOv8 and improved DeepSORT method based on OSNet, FSA and GFModel was named YOFGD. According to the experimental findings, YOFGD's ultimate accuracy can reach 77.9% and its speed can reach 55.8 frames per second (FPS), which is more than enough to fulfill the demands of real-world scenarios.

Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning.

Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemodynamics and cardiac function, and is an effective method for atrial septal defect (ASD) examination. This paper aims to study a deep learning method based on cardiac ultrasound video to assist in ASD diagnosis. We chose four standard views in pediatric cardiac ultrasound to identify atrial septal defects; the four standard views were as follows: subcostal sagittal view of the atrium septum (subSAS), apical four-chamber view (A4C), the low parasternal four-chamber view (LPS4C), and parasternal short-axis view of large artery (PSAX). We enlist data from 300 children patients as part of a double-blind experiment for five-fold cross-validation to verify the performance of our model. In addition, data from 30 children patients (15 positives and 15 negatives) are collected for clinician testing and compared to our model test results (these 30 samples do not participate in model training). In our model, we present a block random selection, maximal agreement decision, and frame sampling strategy for training and testing respectively, resNet18 and r3D networks are used to extract the frame features and aggregate them to build a rich video-level representation. We validate our model using our private dataset by five cross-validation. For ASD detection, we achieve 89.33 ± 3.13 AUC, 84.95 ± 3.88 accuracy, 85.70 ± 4.91 sensitivity, 81.51 ± 8.15 specificity, and 81.99 ± 5.30 F1 score. The proposed model is a multiple instances learning-based deep learning model for video atrial septal defect detection which effectively improves ASD detection accuracy when compared to the performances of previous networks and clinical doctors.

Human amniotic MSCs-mediated anti-inflammation of CD206hiIL-10hi macrophages alleviates isoproterenol-induced ventricular remodeling in mice.

BACKGROUND: Human amniotic mesenchymal stem cells (hAMSCs) derived from amniotic membrane have multilineage differentiation, immunosuppressive, and anti-inflammation which makes them suitable for the treatment of various diseases. OBJECTIVE: This study aimed to explore the therapeutic effect and molecular mechanism of hAMSCs in ventricular remodeling (VR). METHODS: hAMSCs were characterized by a series of experiments such as flow cytometric analysis, immunofluorescence, differentiative induction and tumorigenicity. Mouse VR model was induced by isoproterenol (ISO) peritoneally, and the therapeutic effects and the potential mechanisms of hAMSCs transplantation were evaluated by echocardiography, carboxy fluorescein diacetate succinimidyl ester (CFSE) labeled cell tracing, histochemistry, qRT-PCR and western blot analysis. The co-culturing experiments were carried out for further exploring the mechanisms of hAMSCs-derived conditioned medium (CM) on macrophage polarization and fibroblast fibrosis in vitro. RESULTS: hAMSCs transplantation significantly alleviated ISO-induced VR including cardiac hypertrophy and fibrosis with the improvements of cardiac functions. CFSE labeled hAMSCs kept an undifferentiated state in heart, indicating that hAMSCs-mediated the improvement of ISO-induced VR might be related to their paracrine effects. hAMSCs markedly inhibited ISO-induced inflammation and fibrosis, seen as the increase of M2 macrophage infiltration and the expressions of CD206 and IL-10, and the decreases of CD86, iNOS, COL3 and αSMA expressions in heart, suggesting that hAMSCs transplantation promoted the polarization of M2 macrophages and inhibited the polarization of M1 macrophages. Mechanically, hAMSCs-derived CM significantly increased the expressions of CD206, IL-10, Arg-1 and reduced the expressions of iNOS and IL-6 in RAW264.7 macrophages in vitro. Interestingly, RAW264.7-CM remarkably promoted the expressions of anti-inflammatory factors such as IL-10, IDO, and COX2 in hAMSCs. Furthermore, the CM derived from hAMSCs pretreated with RAW264.7-CM markedly inhibited the expressions of fibrogenesis genes such as αSMA and COL3 in 3T3 cells. CONCLUSION: Our results demonstrated that hAMSCs effectively alleviated ISO-induced cardiac hypertrophy and fibrosis, and improved the cardiac functions in mice, and the underlying mechanisms might be related to inhibiting the inflammation and fibrosis during the ventricular remodeling through promoting the polarization of CD206hiIL-10hi macrophages in heart tissues. Our study strongly suggested that by taking the advantages of the potent immunosuppressive and anti-inflammatory effects, hAMSCs may provide an alternative therapeutic approach for prevention and treatment of VR clinically.

Dysregulated lncRNAs regulate human umbilical cord mesenchymal stem cell differentiation into insulin-producing cells by forming a regulatory network with mRNAs.

OBJECTIVE: In recent years, cell therapy has emerged as a new research direction in the treatment of diabetes. However, the underlying molecular mechanisms of mesenchymal stem cell (MSC) differentiation necessary to form such treatment have not been clarified. METHODS: In this study, human umbilical cord mesenchymal stem cells (HUC-MSCs) isolated from newborns were progressively induced into insulin-producing cells (IPCs) using small molecules. HUC-MSC (S0) and four induced stage (S1-S4) samples were prepared. We then performed transcriptome sequencing experiments to obtain the dynamic expression profiles of both mRNAs and long noncoding RNAs (lncRNAs). RESULTS: We found that the number of differentially expressed lncRNAs and mRNAs trended downwards during differentiation. Gene Ontology (GO) analysis showed that the target genes of differentially expressed lncRNAs were associated with translation, cell adhesion, and cell connection. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the NF-KB signalling pathway, MAPK signalling pathway, HIPPO signalling pathway, PI3K-Akt signalling pathway, and p53 signalling pathway were enriched in these differentially expressed lncRNA-targeting genes. We also found that the coexpression of the lncRNA CTBP1-AS2 with PROX1 and the lncRNAs AC009014.3 and GS1-72M22.1 with JARID2 mRNA was related to the development of pancreatic beta cells. Moreover, the coexpression of the lncRNAs: XLOC_ 050969, LINC00883, XLOC_050981, XLOC_050925, MAP3K14- AS1, RP11-148K1.12, and CTD2020K17.3 with p53, regulated insulin secretion by pancreatic beta cells. CONCLUSION: In this study, HUC-MSCs combined with small molecule compounds were successfully induced into IPCs. Differentially expressed lncRNAs may regulate the insulin secretion of pancreatic beta cells by regulating multiple signalling pathways. The lncRNAs AC009014.3, Gs1-72m21.1, and CTBP1-AS2 may be involved in the development of pancreatic beta cells, and the lncRNAs: XLOC_050969, LINC00883, XLOC_050981, XLOC_050925, MAP3K14-AS1, RP11-148K1.12, and CTD2020K17.3 may be involved in regulating the insulin secretion of pancreatic beta cells, thus providing a lncRNA catalogue for future research regarding the mechanism of the transdifferentiation of HUC-MSCs into IPCs. It also provides a new theoretical basis for the transplantation of insulin-producing cells into diabetic patients in the future.

Pneumothorax after percutaneous CT-guided lung nodule biopsy: a prospective, multicenter study.

Background: Pneumothorax is a common complication induced by computed tomography (CT)-guided percutaneous needle biopsy, with a frequency of 17-40.4%. It remains debatable how to predict and prevent the occurrence of post-biopsy pneumothorax. In a real-world setting, we investigated the characteristics associated with pneumothorax in primary lung nodule biopsy. Methods: This clinical registry cohort study recorded patients with newly diagnosed pulmonary nodules from 10 medical centers from April 2021 to April 2022, and the data were input into the electronic data capture (EDC) system. The eligibility criteria for participants included being within the age range of 18 to 80 years and expressing a willingness to undergo percutaneous puncture biopsy, among other requirements. Conversely, the exclusion criteria included an inability to cooperate throughout the biopsy process and the emergence of new health issues during the study duration resulting in attendance delays, among other factors. This study collected data from 924 patients, out of which 593 were included after exclusion. The essential characteristics, imaging features of pulmonary nodules, and technical factors associated with percutaneous biopsy were recorded. T-tests or one-way analysis of variance (ANOVA) were performed for continuous variables and Pearson's χ2 test, likelihood ratio, or Fisher's exact test were applied for categorical variables for comparison as appropriate, followed by multivariate logistic regression. Results: The overall incidence of pneumothorax was 13.0% (77/593), among which timely pneumothorax was 10.3% (61/593), delayed pneumothorax was 2.7% (16/593), and the rate of chest tube placement was 3.4% (20/593). There was no significant difference in the incidence of pneumothorax in a needle size range of 16-19 G (P=0.129), but the incidence of pneumothorax was lower with 17 G needles than with 18 G. An increased morbidity of pneumothorax was correlated with age (P=0.003), emphysema (P=0.006), and operation time (P=0.002). There was no significant increase in the incidence of pneumothorax between 1 or 2 passes through the pleura (P=0.062). However, multiple pleural passes (3 times) increased the chances of pneumothorax significantly (P=0.022). These risk factors have a certain clinical value in predicting the incidence of post-biopsy pneumothorax, and the area under the curve (AUC) was 0.749. Conclusions: The most common post-biopsy complication, pneumothorax, was managed conservatively in most cases. A maximum of two pleural passes does not increase the incidence of pneumothorax, and the 17 G needle is more suitable for percutaneous biopsy of pulmonary nodules in the real world.

Nondimensional analysis and application of gas desorption and diffusion driven by density gradient in coal particles.

An in-depth understanding of gas diffusion characteristics in coal is of great value to coalbed methane (CBM) production planning and coal mine safety management. However, the mechanism and model of gas diffusion is still unclear, and some methods for determining diffusion coefficients are not accurate enough. Accordingly, a free gas density gradient (FGDG)-driven coal particle gas desorption and diffusion model was established in this work, and numerical solutions were performed via finite difference method (FDM) and dimensionless method. The variation rules of dimensionless gas pressure, gas content, desorption capacity, and desorption rate were obtained. Finally, the application of the dimensionless method in diffusion modeling and diffusion coefficient inversion was discussed. The results show that the dimensionless method can simplify mathematical equation processing and analyze the common phenomena of desorption and diffusion under different parameters. The gas desorption diffusion in coal particles is from the surface to the inside, and there is obvious desorption hysteresis effect. The larger the dimensionless radius or dimensionless time, the smaller the dimensionless gas pressure, gas content, and dimensionless desorption rate. The dimensionless cumulative gas desorption amount increased rapidly first and then tended to flat with dimensionless time. The simulated curve can be easily converted into the variation curves of several different measured parameters, and the diffusion coefficient can be calculated accurately. The prediction curve of the FGDG diffusion model is in good agreement with the experimentally measured data, which verifies its reasonableness. The research content aims to provide some ideas for modeling gas desorption and diffusion behavior.

Prompt-enhanced hierarchical transformer elevating cardiopulmonary resuscitation instruction via temporal action segmentation.

The vast majority of people who suffer unexpected cardiac arrest are performed cardiopulmonary resuscitation (CPR) by passersby in a desperate attempt to restore life, but endeavors turn out to be fruitless on account of disqualification. Fortunately, many pieces of research manifest that disciplined training will help to elevate the success rate of resuscitation, which constantly desires a seamless combination of novel techniques to yield further advancement. To this end, we collect a specialized CPR video dataset in which trainees make efforts to behave resuscitation on mannequins independently in adherence to approved guidelines, promoting an auxiliary toolbox to assist supervision and rectification of intermediate potential issues via modern deep learning methodologies. Our research empirically views this problem as a temporal action segmentation (TAS) task in computer vision, which aims to segment an untrimmed video at a frame-wise level. Here, we propose a Prompt-enhanced hierarchical Transformer (PhiTrans) that integrates three indispensable modules, including a textual prompt-based Video Features Extractor (VFE), a transformer-based Action Segmentation Executor (ASE), and a regression-based Prediction Refinement Calibrator (PRC). The backbone preferentially derives from applications in three approved public datasets (GTEA, 50Salads, and Breakfast) collected for TAS tasks, which experimentally facilitates the model excavation on the CPR dataset. In general, we probe into a feasible pipeline that elevates the CPR instruction qualification via action segmentation equipped with novel deep learning techniques. Associated experiments on the CPR dataset advocate our resolution with surpassing 91.0% on Accuracy, Edit score, and F1 score.

Long-term hypoxic hUCMSCs-derived extracellular vesicles alleviates allergic rhinitis through triggering immunotolerance of their VEGF-mediated inhibition of dendritic cells maturation.

BACKGROUND: Extensions of mesenchymal stem cells (MSCs) in vitro may lead to the loss of their biological functions. However, hypoxic culturation has been shown to enhance the proliferation, survival, and immunomodulatory capacity of MSCs. OBJECTIVE: We aimed to investigate the effects of long-term hypoxic cultivation on the properties of human umbilical cord-derived MSCs (hUCMSCs) and the therapeutic effects of their extracellular vesicles (EVs) in allergic rhinitis (AR). METHODS: Proliferation, senescence, telomerase activity and multipotent properties of hUCMSCs were analyzed under long-term culturation of hypoxia (1%) or normoxia (21%), and the therapeutic effects of their conditional medium (CM) and EVs were evaluated in OVA-induced AR mice. Effects of hypoxia-EVs (Hy-EVs) or normoxia-EVs (No-EVs) on human monocyte-derived dendritic cells (DCs) were investigated, and the possible mechanisms of Hy-EVs in induction of immunotolerance were further explored. RESULTS: Long-term hypoxia significantly promoted the proliferation, inhibited cell senescence, maintained the multipotent status of hUCMSCs. Hy-CM and Hy-EVs showed better therapeutic effects in AR mice compared to No-EVs, seen as improvement of AR-related behaviors such as rubbing and sneezing, and attenuation of inflammation in nasal tissues. In addition, Hy-EVs significantly reduced the expressions of HLA-DR, CD80, CD40, and CD83 induced by OVA plus LPS in DCs, inhibiting the maturation of DCs. Furthermore, we observed that VEGF was remarkably enriched in Hy-EVs, but not in No-EVs, and the inhibition of DCs maturation was markedly neutralized by VEGF antibodies, suggesting that VEGF derived from Hy-EVs was responsible for the inhibition of DCs maturation. CONCLUSION: Our results demonstrated that long-term hypoxia significantly promoted the proliferation, inhibited cell senescence, maintained the multipotent status of hUCMSCs, and hypoxia treated hUCMSCs-derived EVs enhanced their therapeutic effects in AR mice through VEGF-mediated inhibition of DCs maturation.

A mosquito population suppression model with a saturated Wolbachia release strategy in seasonal succession.

Releasing Wolbachia-infected male mosquitoes to suppress wild female mosquitoes through cytoplasmic incompatibility has shown great promise in controlling and preventing mosquito-borne diseases. To make the release logistically and economically feasible, we propose a saturated release strategy, which is only implemented during the epidemic season of mosquito-borne diseases. Under this assumption, the model becomes a seasonally switching ordinary differential equation model. The seasonal switch brings rich dynamics, including the existence of a unique periodic solution or exactly two periodic solutions, which are proved by using the qualitative property of the Poincaré map. Sufficient conditions are also obtained for determining the stability of the periodic solutions.

Monacolin K Induces Apoptosis of Human Glioma U251 Cells by Triggering ROS-Mediated Oxidative Damage and Regulating MAPKs and NF-κB Pathways.

Monacolin K (MK), a polyketo secondary metabolic compound of the mold genus Monascus, can promote the apoptosis of malignant cancer cells, possessing potential antitumor properties. However, its mechanism of action on gliomas remains unclear. Here, we explored and investigated the potential of the monacolin K's antitumor effect on human glioma U251 cells and its possible molecular mechanism. Results showed that the application of 10 µM monacolin K inhibited the proliferation of U251 cells, with an inhibitory rate of up to 53.4%. Additionally, monacolin K induced the generation of reactive oxygen species and activated mitochondria-mediated pathways, including decreased MMP, activation of caspase3/caspase9, decreased Na+/K+-ATPase and Ca2+-ATPase activities, and disruption of the antioxidant system, resulting in the disruption of intracellular reduction-oxidation homeostasis. Monacolin K also activated MAPK and NF-κB pathways, upregulating P38 activity and downregulating JNK/ERK/P65/IκBα expression, ultimately leading to apoptosis of U251 cells. Importantly, monacolin K was not cytotoxic to normal human cells, hUC-MSCs. We concluded that monacolin K can induce apoptosis in U251 cells by triggering ROS-mediated oxidative damage and regulating MAPKs and NF-κB pathways.

A novel prognostic system combining carbonic anhydrase II and preoperative CA19-9 for intrahepatic cholangiocarcinoma after curative resection.

BACKGROUND: The role of carbonic anhydrase II (CAII) in intrahepatic cholangiocarcinoma (ICC) was investigated and a novel prognostic system combining CAII and preoperative carbohydrate antigen 19-9 (CA19-9) was established to predict the survival of patients with ICC after curative resection. METHODS: A total of 110 patients who underwent curative-intent resection for ICC between 2012 and 2020 were retrospectively analyzed. CAII in tumor and peritumor regions was examined by immunohistochemistry, and the relationships between clinicopathological factors and the prognostic value of CAII and CA19-9 were analyzed. RESULTS: CAII was frequently downregulated in ICC tissues (p < .001). Multivariate analyses indicated that showed that both low CAII expression level and preoperative CA19-9 ≥236 U/ml were independent risk factors for overall survival (OS) and recurrence-free survival (RFS) in patients with ICC after radical resection. Survival analysis revealed that patients with high CAII and low CA19-9 were significantly associated with a better OS and RFS (p < .001). The time-dependent receiver operating characteristic curves showed that CAII + CA19-9 had better prognostic predictive ability than CAII or CA19-9 alone. The nomogram constructed on independent factors including T stage, lymph node metastasis, CA19-9 (continuous variable), and CAII achieved C-indexes of 0.754 (95% CI, 0.701-0.807) and 0.730 (0.674-0.785) for OS and RFS, respectively. The calibration curve revealed acceptable agreement between actual and predicted OS and RFS. CONCLUSIONS: The combination of CAII and preoperative CA19-9 is a novel and useful prognostic tool for predicting the survival of patients with ICC after curative resection and guiding clinical decisions. PLAIN LANGUAGE SUMMARY: Carbonic anhydrase II (CAII) was frequently downregulated in intrahepatic cholangiocarcinoma (ICC) tissues. Survival analysis revealed that CAII is a novel independent factor for prognosis in patients with ICC after curative resection. CAII could be a useful prognostic marker for patients with ICC after surgery. The combination of CAII and preoperative carbohydrate antigen 19-9 is a novel and useful prognostic tool for predicting the survival of patients with ICC after curative resection and guiding clinical decisions.

Automatic detection of A-line in lung ultrasound images using deep learning and image processing.

BACKGROUND: Auxiliary diagnosis and monitoring of lung diseases based on lung ultrasound (LUS) images is important clinical research. A-line is one of the most common indicators of LUS that can offer support for the assessment of lung diseases. A traditional A-line detection method mainly relies on experienced clinicians, which is inefficient and cannot meet the needs of these areas with backward medical level. Therefore, how to realize the automatic detection of A-line in LUS image is important. PURPOSE: In order to solve the disadvantages of traditional A-line detection methods, realize automatic and accurate detection, and provide theoretical support for clinical application, we proposed a novel A-line detection method for LUS images with different probe types in this paper. METHODS: First, the improved Faster R-CNN model with a selection strategy of localization box was designed to accurately locate the pleural line. Then, the LUS image below the pleural line was segmented for independent analysis excluding the influence of other similar structures. Next, image-processing methods based on total variation, matched filter, and gray difference were applied to achieve the automatic A-line detection. Finally, the "depth" index was designed to verify the accuracy by judging whether the automatic measurement results belong to corresponding manual results (±5%). In experiments, 3000 convex array LUS images were used for training and validating the improved pleural line localization model by five-fold cross validation. 850 convex array LUS images and 1080 linear array LUS images were used for testing the trained pleural line localization model and the proposed image-processing-based A-line detection method. The accuracy analysis, error statistics, and Harsdorff distance were employed to evaluate the experimental results. RESULTS: After 100 epochs, the mean loss value of training and validation set of improved Faster R-CNN model reached 0.6540 and 0.7882, with the validation accuracy of 98.70%. The trained pleural line localization model was applied in the testing set of convex and linear probes and reached the accuracy of 97.88% and 97.11%, respectively, which were 3.83% and 8.70% higher than the original Faster R-CNN model. The accuracy, sensitivity, and specificity of A-line detection reached 95.41%, 0.9244%, 0.9875%, and 94.63%, 0.9230%, and 0.9766% for convex and linear probes, respectively. Compared to the experienced clinicians' results, the mean value and p value of depth error were 1.5342 ± 1.2097 and 0.9021, respectively, and the Harsdorff distance was 5.7305 ± 1.8311. In addition, the accumulated accuracy of the two-stage experiment (pleural line localization and A-line detection) was calculated as the final accuracy of the whole A-line detection system. They were 93.39% and 91.90% for convex and linear probes, respectively, which were higher than these previous methods. CONCLUSIONS: The proposed method combining image processing and deep learning can automatically and accurately detect A-line in LUS images with different probe types, which has important application value for clinical diagnosis.

Experimental study on uniaxial creep characteristics of sandstone with pre-peak unloading damage.

Deep resource extraction has been affected by the complex geological environment of "three highs and one disturbance" for a long time. The surrounding rocks experience strong unloading stress disturbance during the underground resource extraction. The creep characteristics of the perimeter rocks are of great theoretical and practical value. Firstly, the triaxial pre-peak loading and unloading tests on the prepared samples are conducted on the intact rock samples using the TAW-200 rock mechanics test system. Then the rock samples with different degrees of pre-peak unloading damage were prepared under the condition of pre-peak yield. Finally, the uniaxial creep tests were carried out to study the uniaxial creep mechanical properties. The results show that the wave velocities of the damaged rock samples are reduced to different degrees compared with those of the intact rock samples, the creep of the pre-peak unloading damaged rock has a time-dependent damage effect, and the study results are similar to those of the conventional uniaxial creep test of the white sandstone. The instantaneous strain at all stress levels of the damaged rock samples increased gradually with the stress level, which is consistent with the non-linear functional relationship; Based on the time-dependent damage effect, the two-parameter Weibull distribution function was introduced into the West Plains viscoelasticity model, and a creep damage model for white sandstone was proposed. The improved Nishihara model can simulate the uniaxial creep characteristics of each damaged rock sample at various stress levels.

Experimental Study on the Influence of Coal Fracture Surface Roughness on Water Injection Seepage.

Coal seam water injection has a significant effect on downhole dust resistance. However, during the operation of coal seam water injection, the seepage of the solution in the coal fractures is impacted by the roughness of coal fractures. Therefore, in this study, distilled water and a sodium lauryl sulfate surfactant were used as seepage solutions, kennel coal was used as the research subject, and four coal samples with different roughness coefficients were prepared for seepage experiments. After the analysis and discussion of the experimental results, it is found that the surface roughness of coal fractures hinders the seepage effect of coal seam water injection. The greater the surface roughness of coal fractures, the smaller the permeability coefficient. Furthermore, increasing the injection pressure and fracture aperture can reduce the influence of coal fracture surface roughness on the permeability coefficient. In addition, after sodium lauryl sulfate is added, the permeability coefficient of the coal sample is reduced. This further reveals the seepage of water injection into coal seams and provides certain guidance for the development of coal seam water injection technology.

TRIM65 Promotes Cervical Cancer Through Selectively Degrading p53-Mediated Inhibition of Autophagy and Apoptosis.

Tripartite motif containing 65 (TRIM65) is an E3 ubiquitin ligase that has been implicated in a variety of cellular processes as well as tumor progression, but its biological role and the underlying mechanism in cervical cancer is unclear. Here, we reported that TRIM65 expression in human cervical cancer tissues was significantly higher than that in the adjacent normal cervical tissues, and TRIM65 knockdown enhanced autophagic flux and cell apoptosis, but not cell cycle, to dramatically inhibit the proliferation and migration of cervical cancer cells. Furthermore, our experiments showed that TRIM65 exhibited oncogenic activities via directly targeting p53, a tumor suppressor and a common upsteam regulator between autophagy and apoptosis, promoting ubiquitination and proteasomal degradation of p53. Taken together, our studies demonstrated that TRIM65 knockdown promotes cervical cancer cell death through enhancing autophagy and apoptosis, suggesting that TRIM65 may be a potential therapeutic target for cervical cancer clinically.

Human amniotic stem cells-derived exosmal miR-181a-5p and miR-199a inhibit melanogenesis and promote melanosome degradation in skin hyperpigmentation, respectively.

BACKGROUND: Hyperpigmentation of skin is caused by an imbalance between the melanosome/melanin synthesis in melanocytes and the melanosome/melanin degradation in keratinocytes. Although studies showed that stem cells play a role in hypopigmentation, the underlying mechanisms are far not elucidated. Human amniotic stem cells (hASCs) including human amniotic mesenchymal stem cells (hAMSCs) and human amniotic epithelial stem cells (hAESCs) were considered to be a promising cell source for stem cells-based therapy of many diseases clinically due to their pluripotent potential, no tumorigenesis and immunogenicity, no ethical issues, and potent paracrine effects. Here, we reported that both hASCs and their conditional medium (CM) had a potent anti-hyperpigmentation in skin in vivo and in vitro. METHODS: hAESCs and hAMSCs were identified by RT-PCR, flow cytometric analysis and immunofluorescence. Effects of hASCs and hASC-CM on pigmentation were evaluated in B16F10 cells stimulated with α-melanocyte-stimulating hormone (α-MSH), and mouse ears or human skin substitutes treated with ultraviolet radiation B (UVB). Expressions of the key proteins related with melanogenesis and autophagic flux were detected by western blot in B16F10 cells for further exploring the effects and the underlying mechanisms of hAESC-CM and hAMSC-CM on melanogenesis and melanosome degradation. The hAMSCs exosomes-derived miRNAs were determined by sequencing. RT-PCR, western blot, melanin content analysis and luciferase activity assay were used to determine the hypopigmentation of miR-181a-5p and miR-199a. RESULTS: In our study, we observed that both hASCs and their CM significantly alleviated the α-MSH in B16F10 cells or UVB-induced hyperpigmentation in mouse ears or human skin substitutes by suppressing melanin synthesis and promoting melanosome degradation in vivo and in vitro. Furthermore, we demonstrated that miR-181a-5p and miR-199a derived from hASCs exosomes remarkably inhibited melanogenesis by suppressing MITF (microphthalmia-associated transcription factor) which is a master regulator for governing melanogenesis and promoting melanosome degradation through activating autophagy, respectively. CONCLUSIONS: Our studies provided strong evidence that the conditional medium and exosomes derived from hAMSCs inhibit skin hyperpigmentation by suppressing melanogenesis and promoting melanosome degradation, indicating that the hASCs exosomes or their released microRNAs might be as reagents for cell-free therapy in hyperpigmented disorders clinically.