Indomethacin Does Not Reduce Post-ERCP Pancreatitis in High-Risk Patients Receiving Pancreatic Stenting.

BACKGROUND: Rectal indomethacin reduces pancreatitis following endoscopic retrograde cholangiopancreatography (ERCP). However, there is insufficient evidence regarding its added benefits in patients already receiving prophylactic pancreatic stenting. Our goal was to evaluate the impact of indomethacin in high-risk patients undergoing pancreatic stenting. METHODS: A cohort study was conducted on all patients who underwent the rescue cannulation technique for challenging bile duct cannulation (selected high-risk patients). Patients were split into two groups based on the prophylaxis method for post-ERCP pancreatitis (PEP): one receiving a combination of indomethacin and pancreatic stenting, while the other received pancreatic stenting alone. Comparative analyses were carried out on PEP, hyperamylasemia, gastrointestinal bleeding, and postoperative hospital stay among post-ERCP pancreatitis patients. RESULTS: Between November 2017 and May 2023, a total of 607 patients with native papillae were enrolled, with 140 grouped into the indomethacin plus stent group and 467 into the stent alone group. The overall PEP rate was 4.4% in the entire cohort, with no statistical differences observed between the groups in terms of PEP rates (P = 0.407), mild PEP (P = 0.340), moderate to severe PEP (P = 1.000), hyperamylasemia (P = 0.543), gastrointestinal bleeding (P = 0.392), and postoperative hospital stay (P = 0.521). Furthermore, sensitivity analysis using multivariable analysis also validated these findings. CONCLUSIONS: Indomethacin did not reduce the incidence or severity of PEP in high-risk patients who routinely received prophylactic pancreatic stent placement. Therefore, the additional administration of rectal indomethacin to further mitigate PEP appears to be not necessary.

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.

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.

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.

Knockdown of long non-coding RNA small nucleolar RNA host gene 9 or hexokinase 2 both suppress endometrial cancer cell proliferation and glycolysis.

AIM: Endometrial cancer (EC) is a common type of malignant gynecological cancer. Small nucleolar RNA host gene 9 (SNHG9) has been discovered to serve a role in several types of cancer; however, the role of SNHG9 in EC remains unclear. The present study aimed to investigate the effects of lncRNA SNHG9 on cell proliferation and glycolysis in EC cells. METHODS: SNHG9 and hexokinase 2 (HK2) mRNA expression levels were measured by reverse transcription-quantitative PCR. Glucose consumption and lactate production were detected by the glycolysis cell-based assay kit. Cell Counting Kit-8 and colony formation assays were conducted to detect cell proliferation. The knockdown experiments of SNHG9 and HK2 were carried out by transfection of corresponding small interference RNAs (siRNA). The SNHG9-overexpressed plasmid was transfected into the cells to upregulate SNHG9. HK2 protein levels were analyzed by western blotting assay. RESULTS: SNHG9 expression levels were significantly upregulated in EC tissues and cells. The knockdown of SNHG9 subsequently effectively attenuated cell proliferation and glycolysis in vitro, while SNHG9 overexpression reported the opposite effects. Notably, the transfection of 2-DG partially reversed the promoting effect of SNHG9 on glycolysis. Downregulation of HK2 markedly decreased cell proliferation and glycolysis in EC cells antagonized SNHG9. CONCLUSION: Either downregulation of SNHG9 or HK2 inhibits EC cell proliferation and glycolysis via repressing EC cell proliferation and glycolysis.

Characteristics and Therapeutic Potential of Human Amnion-Derived Stem Cells.

Stem cells including embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs) and adult stem cells (ASCs) are able to repair/replace damaged or degenerative tissues and improve functional recovery in experimental model and clinical trials. However, there are still many limitations and unresolved problems regarding stem cell therapy in terms of ethical barriers, immune rejection, tumorigenicity, and cell sources. By reviewing recent literatures and our related works, human amnion-derived stem cells (hADSCs) including human amniotic mesenchymal stem cells (hAMSCs) and human amniotic epithelial stem cells (hAESCs) have shown considerable advantages over other stem cells. In this review, we first described the biological characteristics and advantages of hADSCs, especially for their high pluripotency and immunomodulatory effects. Then, we summarized the therapeutic applications and recent progresses of hADSCs in treating various diseases for preclinical research and clinical trials. In addition, the possible mechanisms and the challenges of hADSCs applications have been also discussed. Finally, we highlighted the properties of hADSCs as a promising source of stem cells for cell therapy and regenerative medicine and pointed out the perspectives for the directions of hADSCs applications clinically.

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.

Exploring whether ChatGPT-4 with image analysis capabilities can diagnose osteosarcoma from X-ray images.

The generation of radiological results from image data represents a pivotal aspect of medical image analysis. The latest iteration of ChatGPT-4, a large multimodal model that integrates both text and image inputs, including dermatoscopy images, histology images, and X-ray images, has attracted considerable attention in the field of radiology. To further investigate the performance of ChatGPT-4 in medical image recognition, we examined the ability of ChatGPT-4 to recognize credible osteosarcoma X-ray images. The results demonstrated that ChatGPT-4 can more accurately diagnose bone with or without significant space-occupying lesions but has a limited ability to differentiate between malignant lesions in bone compared to adjacent normal tissue. Thus far, the current capabilities of ChatGPT-4 are insufficient to make a reliable imaging diagnosis of osteosarcoma. Therefore, users should be aware of the limitations of this technology.

Therapeutic effect of exosomes derived from Schwann cells in the repair of peripheral nerve injury.

Peripheral nerve injury (PNI) can cause nerve demyelination, neuronal apoptosis, axonal atrophy, inflammatory infiltration, glial scar formation, and other pathologies that can lead to sensory and motor dysfunction and seriously affect the psychosomatic health of patients. There is currently no effective treatment method, so exploring a promising treatment method is of great significance. Several studies have revealed the therapeutic roles of Schwann cells (SCs) and their exosomes in nerve injury repair. Exosomes are extracellular nanovesicles secreted by cells that act as key molecules in intercellular communication. Progress has been made in understanding the role of exosomes derived from SCs (SC-EXOs) in peripheral nerve regeneration, including the promotion of axonal regeneration and myelin formation, anti-inflammation, vascular regeneration, neuroprotection, and neuroregulation. Therefore, in this paper, we summarize the functional characteristics of SC-EXOs and discuss their potential therapeutic effects on PNI repair as well as some existing problems and future challenges.

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.

The anti-inflammatory and immunomodulatory effects of olfactory ensheathing cells transplantation in spinal cord injury and concomitant pathological pain.

Spinal cord injury (SCI) is a serious and disabling injury that is often accompanied by neuropathic pain (NeP), which severely affects patients' motor and sensory functions and reduces their quality of life. Currently, there is no specific treatment for treating SCI and relieving the accompanying pain, and we can only rely on medication and physical rehabilitation, both of which are ineffective. Researchers have recently identified a novel class of glial cells, olfactory ensheathing cells (OECs), which originate from the olfactory system. Transplantation of OECs into damaged spinal cords has demonstrated their capacity to repair damaged nerves, improve the microenvironment at the point of injury, and They can also restore neural connectivity and alleviate the patient's NeP to a certain extent. Although the effectiveness of OECs transplantation has been confirmed in experiments, the specific mechanisms by which it repairs the spinal cord and relieves pain have not been articulated. Through a review of the literature, it has been established that the ability of OECs to repair and relieve pain is inextricably linked to its anti-inflammatory and immunomodulatory effects. In this regard, it is imperative to gain a deeper understanding of how OECs exert their anti-inflammatory and immunomodulatory effects. The objective of this paper is to provide a comprehensive overview of the mechanisms by which OECs exert anti-inflammatory and immunomodulatory effects. We aim to manipulate the immune microenvironment at the transplantation site through the intervention of cytokines and immune cells, with the goal of enhancing OECs' function or creating a conducive microenvironment for OECs' survival. This approach is expected to improve the therapeutic efficacy of OECs in clinical settings. However, numerous fundamental and clinical challenges remain to be addressed if OEC transplantation therapy is to become a standardized treatment in clinical practice.

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.

Thermosensitive and injectable chitosan-based hydrogel embedding umbilical cord mesenchymal stem cells for ß-cell repairing in type 2 diabetes mellitus.

A thermosensitive and injectable hydrogel composed of chitosan (CS), chitosan biguanide hydrochloride (CSG) and collagen (CO) could embed umbilical cord mesenchymal stem cells (UC-MSCs), then was applied for the type 2 diabetes mellitus (T2DM) treatment in vivo. UC-MSCs could adhere well on CS/CSG/CO hydrogel surface and cell division could be clearly observed. Especially, UC-MSCs maintained alive till they grew in CS/CSG/CO hydrogel for 8 days, while the amount of UC-MSCs was limited due to the steric hindrance in hydrogel. To T2DM mice contrastive treatment by intraperitoneal injection for thirteen weeks, UC-MSCs + Hydrogel group could improve the impaired glucose tolerance, maintain glucose homeostasis in vivo, and restore islet morphology for T2DM mice. The immunofluorescence staining and western blot experiments further displayed that both the nuclear antigen Ki67 for cell proliferation and pancreatic duodenal homeobox-1 (Pdx1) expression in UC-MSCs + Hydrogel group were significantly higher than the expressions in untreated T2DM group and treated UC-MSCs + PBS group, which indicated that UC-MSCs + Hydrogel elevated ß cell transcriptional activity. Moreover, the positivity rates of iNOS and CD163 in UC-MSCs + Hydrogel group were generally decreased and increased, respectively, compared to those in untreated T2DM group and treated UC-MSCs + PBS group. It displayed that UC-MSCs + Hydrogel could reduce M1 macrophage expression and increase M2 macrophage polarization in T2DM mice.

Enhancing lymph node metastasis prediction in adenocarcinoma of the esophagogastric junction: A study combining radiomic with clinical features.

BACKGROUND: The incidence of adenocarcinoma of the esophagogastric junction (AEJ) is increasing, and with poor prognosis. Lymph node status (LNs) is particularly important for planning treatment and evaluating the prognosis of patients with AEJ. However, the use of radiomic based on enhanced computed tomography (CT) to predict the preoperative lymph node metastasis (PLNM) status of the AEJ has yet to be reported. PURPOSE: We sought to investigate the value of radiomic features based on enhanced CT in the accurate prediction of PLNM in patients with AEJ. METHODS: Clinical features and enhanced CT data of 235 patients with AEJ from October 2017 to May 2023 were retrospectively analyzed. The data were randomly assigned to the training cohort (n = 164) or the external testing cohort (n = 71) at a ratio of 7:3. A CT-report model, clinical model, radiomic model, and radiomic-clinical combined model were developed to predict PLNM in patients with AEJ. Univariate and multivariate logistic regression were used to screen for independent clinical risk factors. Least absolute shrinkage and selection operator (LASSO) regression was used to select the radiomic features. Finally, a nomogram for the preoperative prediction of PLNM in AEJ was constructed by combining Radiomics-score and clinical risk factors. The models were evaluated by area under the receiver operating characteristic curve (AUC-ROC), calibration curve, and decision curve analyses. RESULTS: A total of 181 patients (181/235, 77.02%) had LNM. In the testing cohort, the AUC of the radiomic-clinical model was 0.863 [95% confidence interval (CI) = 0.738-0.957], and the radiomic model (0.816; 95% CI = 0.681-0.929), clinical model (0.792; 95% CI = 0.677-0.888), and CT-report model (0.755; 95% CI = 0.647-0.840). CONCLUSION: The radiomic-clinical model is a feasible method for predicting PLNM in patients with AEJ, helping to guide clinical decision-making and personalized treatment planning.

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.

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.

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.

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.

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.