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According to medical research, colorectal polyps are considered typical precancerous lesions, making colonoscopic polyp images crucial for the early diagnosis of rectal cancer. However, variations in polyp size and shape, texture inconsistencies, and boundary ambiguities often pose significant challenges for polyp segmentation. To address these issues, we propose a multi-scale feature fusion network based on edge enhancement. Specifically, we utilize multi-scale feature fusion in each feature layer, where the extracted features are fused. From these extracted features, we generate a global mapping graph as a bootstrap region. Additionally, we introduce Spatial Channel Convolution (SCEConv) and Reverse Gated Channel Transformer (RGCT) to incorporate boundary information into the segmentation network. This approach enhances the layered features and produces a more refined segmentation map. Extensive qualitative and quantitative experiments on five benchmark datasets and two private datasets demonstrate that the EMFF-Net proposed in this paper significantly improves segmentation accuracy across six metrics. This represents a clear advantage over traditional CNNs and existing SOTA techniques, Especially, we achieved 81% mDice and 74% mIoU on the CVC-ColonDB dataset.

Abstract Background The aim is to develop and validate radiomics based on 2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) parameters for predicting the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade of clear cell renal cell carcinoma (ccRCC). Methods A total of 209 patients with 214 lesions, who underwent 2-[18F]FDG PET/CT scans between December 2016 to December 2023, were included in our study. All ccRCC lesions were categorized into low grade (WHO/ISUP grade I-II) and high grade (WHO/ISUP grade III-IV). The lesions were allocated into a training group and a testing group in a ratio of 7:3. The radiomics features were extracted by a serious of maximum standardized uptake value (SUVmax) thresholds (0,2.5%,25%,40%) with the utilization of the minimum redundancy and maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) regression algorithm. The clinical, radiomics and combined models were constructed. The receiver operating characteristic (ROC) curve, decision curve and calibration curves were plotted to assess the predicting performance. Results The area under curve (AUC) of PET-0, PET-2.5%, PET-25%, PET-40% model in the training group were 0.881(95% CI: 0.822–0.940),0.883(95% CI: 0.825–0.942),0.889(95% CI: 0.831–0.946),0.887(95% CI: 0.826–0.948); and 0.878(95% CI: 0.777–0.978),0.876(95% CI: 0.776–0.977),0.871(95% CI: 0.769–0.972),0.882(95% CI: 0.786–0.979) in the testing group. Due to perfect prediction and verification performance, the volume of interest (VOI) from PET images with SUVmax threshold of 40% were selected to construct the radiomics model and combined model. The AUC of the clinical model and radiomics model was 0.859 (sensitivity = 0.846, specificity = 0.747) and 0.909 (sensitivity = 0.808, specificity = 0.751) in the training group, respectively; 0.882 (sensitivity = 0.857, specificity = 0.857) and 0.901 (sensitivity = 0.905, specificity = 0.833) in the testing group, respectively. In combined models, the AUC was 0.916, the sensitivity was 0.923 and the specificity was 0.808 in the training group; the AUC was 0.916, the sensitivity was 0.881 and the specificity was 0.792 in the training group. Conclusion Radiomics based on 2-[18F]FDG PET/CT can be helpful to predict WHO/ISUP grade of ccRCC.

Abstract Background Although capsule endoscopy (CE) is a crucial tool for diagnosing small bowel diseases, the need to process a vast number of images imposes a significant workload on physicians, leading to a high risk of missed diagnoses. This study aims to develop an artificial intelligence (AI) model and application based on convolutional neural networks that can automatically recognize various lesions in small bowel capsule endoscopy. Methods Three small bowel capsule endoscopy datasets were used for AI model training, validation, and testing, encompassing 12 categories of images. The model’s performance was evaluated using metrics such as AUC, sensitivity, specificity, precision, accuracy, and F1 score to select the best model. A human-machine comparison experiment was conducted using the best model and endoscopists with varying levels of experience. Model interpretability was analyzed using Grad-CAM and SHAP techniques. Finally, a clinical application was developed based on the best model using PyQt5 technology. Results A total of 34,303 images were included in this study. The best model, MobileNetv3-large, achieved a weighted average sensitivity of 87.17%, specificity of 98.77%, and an AUC of 0.9897 across all categories. The application developed based on this model performed exceptionally well in comparison with endoscopists, achieving an accuracy of 87.17% and a processing speed of 75.04 frames per second, surpassing endoscopists of varying experience levels. Conclusion The AI model and application developed based on convolutional neural networks can quickly and accurately identify 12 types of small bowel lesions. With its high sensitivity, this system can effectively assist physicians in interpreting small bowel capsule endoscopy images.Future studies will validate the AI system for video evaluations and real-world clinical integration.

Abstract Background Apnea is common in preterm infants and can be accompanied with severe hypoxic damage. Early assessment of apnea risk can impact the prognosis of preterm infants. We constructed a prediction model to assess apnea risk in premature infants for identifying high-risk groups. Methods A total of 162 and 324 preterm infants with and without apnea who were admitted to the neonatal intensive care unit of Xiamen University between January 2018 and December 2021 were selected as the case and control groups, respectively. Demographic characteristics, laboratory indicators, complications of the patients, pregnancy-related factors, and perinatal risk factors of the mother were collected retrospectively. The participants were randomly divided into modeling (n = 388) and validation (n = 98) sets in an 8:2 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate logistic regression analyses were used to independently filter variables from the modeling set and build a model. A nomogram was used to visualize models. The calibration and clinical utility of the model was evaluated using consistency index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve, and the model was verified using the validation set. Results Results of LASSO combined with multivariate logistic regression analysis showed that gestational age at birth, birth length, Apgar score, and neonatal respiratory distress syndrome were predictors of apnea development in preterm infants. The model was presented as a nomogram and the Hosmer-Lemeshow goodness of fit test showed a good model fit (χ 2 =5.192, df=8, P=0.737), with Nagelkerke R 2 of 0.410 and C-index of 0.831. The area under the ROC curve and 95% CI were 0.831 (0.787-0.874) and 0.829 (0.722-0.935), respectively. Delong's test comparing the AUC of the two data sets showed no significant difference (P=0.976). The calibration curve showed good agreement between the predicted and actual observations. The decision curve results showed that the threshold probability range of the model was 0.07-1.00, the net benefit was high, and the constructed clinical prediction model had clinical utility. Conclusions Our risk prediction model based on gestational age, birth length, Apgar score 10 min post-birth, and neonatal respiratory distress syndrome was validated in many aspects and had good predictive efficacy and clinical utility.

Abstract It is a consensus in the international manned space field that factors such as microgravity during the space flight can cause anxiety, depression and other important brain function abnormalities in astronauts. However, the neural mechanism at the molecular level is still unclear. Due to the limitations of research conditions, studies of biological changes in the primate brain have been comparatively few. We took advantage of -6° head-down bed rest (HDBR), one of the most implemented space analogues on the ground, to investigate the effects of simulated weightlessness on non-human primate brain metabolites. The Rhesus Macaque monkeys in the experiment were divided into three groups: the control group, the 42-day simulated weightlessness group with HDBR, and the recovery group, which had 28 days of free activity in the home cage after the HDBR. Liquid chromatography-mass spectrometry (LC-MS) was used to perform metabolomics analysis on specific brain areas of the monkeys under three experimental conditions. Our results show that simulated weightlessness can cause neurotransmitter imbalances, the amino acid and energy metabolism disorders, and hormone disturbances. But these metabolomics changes are reversible after recovery. Our study suggests that long-term brain damage in space flight might be reversible at the metabolic level. This lays a technical foundation for ensuring brain health and enhancing the brain function in future space studies.

Abstract Background Construct deep learning models for colonoscopy quality control using different architectures and explore their decision-making mechanisms. Methods A total of 4,189 colonoscopy images were collected from two medical centers, covering different levels of bowel cleanliness, the presence of polyps, and the cecum. Using these data, eight pre-trained models based on CNN and Transformer architectures underwent transfer learning and fine-tuning. The models’ performance was evaluated using metrics such as AUC, Precision, and F1 score. Perceptual hash functions were employed to detect image changes, enabling real-time monitoring of colonoscopy withdrawal speed. Model interpretability was analyzed using techniques such as Grad-CAM and SHAP. Finally, the best-performing model was converted to ONNX format and deployed on device terminals. Results The EfficientNetB2 model outperformed other architectures on the validation set, achieving an accuracy of 0.992. It surpassed models based on other CNN and Transformer architectures. The model’s precision, recall, and F1 score were 0.991, 0.989, and 0.990, respectively. On the test set, the EfficientNetB2 model achieved an average AUC of 0.996, with a precision of 0.948 and a recall of 0.952. Interpretability analysis showed the specific image regions the model used for decision-making. The model was converted to ONNX format and deployed on device terminals, achieving an average inference speed of over 60 frames per second. Conclusions The AI-assisted quality system, based on the EfficientNetB2 model, integrates four key quality control indicators for colonoscopy. This integration enables medical institutions to comprehensively manage and enhance these indicators using a single model, showcasing promising potential for clinical applications.

Abstract Background To assess the viability and efficiency of performing arthroscopic meniscoplasty in treating discoid meniscus (DM) in the knee joint. Methods A total of 29 patients diagnosed with symptomatic lateral DM between October 2014 and December 2019 were included in the study. Among them, 7 patients with intact DM underwent arthroscopic discoid meniscoplasty (group A), while 22 patients with torn DM received arthroscopic DM plasty along with repair and suturing (group B). Both Visual Analog Scale (VAS) score and Lysholm score assessments were conducted preoperatively and postoperatively. Result The favorable and acceptable outcome rate was 85.71% in group A and 95.45% in group B (P > 0.05). The VAS scores post-operatively at each follow-up time point were consistently lower compared to pre-operative values, while the Lysholm knee function scores showed improvement. There were no significant differences in VAS score and Lysholm score between group A and group B at different stages (P > 0.05). Both surgical techniques (discoid meniscoplasty and discoid meniscoplasty combined with repair and suture) showed significant improvement in postoperative VAS score and Lysholm score, but there was no difference in outcomes between the two groups. Conclusion Overall, the two surgical techniques studied in this study (discoid meniscoplasty and discoid meniscoplasty combined with repair and suture) produced similar results in terms of pain reduction and improved knee function.

Abstract Background To investigate the value of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) semi-quantitative parameters, including the lesion diameter, maximum standardized uptake value (SUVmax), maximum standardized uptake value corrected for lean body mass (SULmax), metabolic lesion volume (MLV), and total lesion glycolysis (TLG), for classifying hepatic echinococcosis. Methods In total, 20 patients with 36 hepatic echinococcosis lesions were included in the study. Overall, these lesions were categorized as hepatic cystic echinococcosis (HCE) or hepatic alveolar echinococcosis (HAE) according to the pathological results. Multiple semi-parameters including the maximum diameter, SUVmax, SULmax, MLV, and TLG were measured to classify HCE and HAE compared with the pathological results. The receiver operator characteristic curve and area under the curve (AUC) of each quantitative parameter were calculated. The Mann–Whitney U test was used to compare data between the two groups. Results In total, 12 cystic lesions and 24 alveolar lesions were identified after surgery. There were significant differences in SUV max, SUL max, MLV, and TLG between the HAE and HCE groups (Z = − 4.70, − 4.77, − 3.36, and − 4.23, respectively, all P 0.05). The best cutoffs of SUV max, SUL max, MLV, and TLG for the differential diagnosis of HAE and HCE were 2.09, 2.67, 27.12, and 18.79, respectively. The AUCs of the four parameters were 0.99, 0.99, 0.85, and 0.94, respectively. The sensitivities were 91.7%, 87.5%, 66.7%, and 85.6%, respectively, and the specificities were 90.1%, 91.7%, 83.3%, and 90.9%, respectively. Conclusion 18F-FDG PET/CT semi-quantitative parameters had significant clinical value in the diagnosis and pathological classification of hepatic echinococcosis and evaluation of clinical treatment.

The accomplishment of interpersonal sensorimotor synchronization is a challenging endeavor because it requires the achievement of a balance between accurate temporal control within individuals and smooth communication between them. This raises a critical question: How does the brain comprehend and process the perceptual information of others to guarantee accurate temporal control of action goals in a social context? A joint synchronization - continuation tapping task was conducted together with varying relative phases (0°/180°) and intervals of tempos (400 ms/800 ms/1600 ms) while neural data was collected using fNIRS (functional near-infrared spectroscopy). Individuals showed better behavioral performance and greater interpersonal brain synchronization(IBS) in the left dorsolateral prefrontal cortex at alternated condition (180° relative phase) compared to symmetric condition (0° relative phase), suggesting that the individual can better maintain behavioral performance and show improved IBS when the partner taps between the individual's gaps. Meanwhile, in most levels of alternated condition, IBS is inversely proportional to interference from partner, implying the counteraction of IBS against interference from others. In addition, when the interval of tempo was 1600 ms, behavioral performance showed a sharp decline, accompanied by a decrease in IBS, reflecting that IBS in SMS reflects effective information exchange between individuals rather than ineffective interference with each other. This study provides insight into the mechanisms underlying sensorimotor synchronization between individuals.

Abstract Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (LIM), significantly impacting the patient's prognosis. This study aimed to predict LIM in GIST patients by constructing machine learning (ML) algorithms to assist clinicians in the decision-making process for treatment. Retrospective analysis was performed using the Surveillance, Epidemiology, and End Results (SEER) database, and cases from 2010 to 2015 were assigned to the developing sets, while cases from 2016 to 2017 were assigned to the testing set. Missing values were addressed using the multiple imputation technique. Four algorithms were utilized to construct the models, comprising traditional logistic regression (LR) and automated machine learning (AutoML) analysis such as gradient boost machine (GBM), deep neural net (DL), and generalized linear model (GLM). We evaluated the models' performance using LR-based metrics, including the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA), as well as AutoML-based metrics, such as feature importance, SHapley Additive exPlanation (SHAP) Plots, and Local Interpretable Model Agnostic Explanation (LIME). A total of 6207 patients were included in this study, with 2683, 1780, and 1744 patients allocated to the training, validation, and test sets, respectively. Among the different models evaluated, the GBM model demonstrated the highest performance in the training, validation, and test cohorts, with respective AUC values of 0.805, 0.780, and 0.795. Furthermore, the GBM model outperformed other AutoML models in terms of accuracy, achieving 0.747, 0.700, and 0.706 in the training, validation, and test cohorts, respectively. Additionally, the study revealed that tumor size and tumor location were the most significant predictors influencing the AutoML model's ability to accurately predict LIM. The AutoML model utilizing the GBM algorithm for GIST patients can effectively predict the risk of LIM and provide clinicians with a reference for developing individualized treatment plans.

Camellia reticulata is a well-known ornamental species with a type specimen that is an allohexaploid, possibly descended from diploid ancestors like C. saluenensis, C. pitardii, and diploid C. reticulata. With over 1500 years of cultivation, heritage C. reticulata cultivars show varied ploidy levels, including hexaploid, octoploid, and decaploid forms, though their diploid ancestors are still unidentified. This study aims to trace these diploid ancestors by cloning and sequencing ITS from 25 taxa and RPB2 from 21 taxa across various ploidy levels of C. reticulata and its traditional cultivars and related species, combined with their fruit morphology data. Analyses of the ITS and RPB2 sequences suggest that the diploid ancestors of C. reticulata and its traditional cultivars may include C. saluenensis, C. pitardii, and diploid C. reticulata, while excluding C. mairei and C. polyodonta. Morphological analysis showed that diploid C. reticulata has significantly larger fruit weight, diameter, and pericarp thickness compared to C. pitardii, C. saluenensis, and both tetraploid and hexaploid C. reticulata. Since diploid ancestors of allopolyploids are often classified as distinct taxa, we suggest that diploid C. reticulata be recognized as a new variety of C. pitardii, as its ITS sequences are closely aligned with C. pitardii. This study offers key insights into the origin, evolution, and breeding of C. reticulata.

Objective: Currently, 68Ga-labeled somatostatin analogs (SSAs) are the most commonly used imaging agents for patients with neuroendocrine tumors (NETs) in clinical practice, demonstrating good results in tumor diagnosis. For applications in peptide receptor radionuclide therapy (PRRT), targeted drugs should have high tumor uptake and prolonged tumor retention time. To enhance the uptake and retention of tracers in NETs, our goal is to design a 68Ga-labeled heterodimer for optimizing pharmacokinetics and assess whether this form is more efficacious than its monomeric equivalents. Methods: Using the somatostatin analog TATE and quinoline-based compound FAPI-46 as raw materials, we designed and synthesized 68Ga-labeled TATE-46. The labeling efficiency and stability were verified by Radio-HPLC. The receptor binding properties and tumor targeting were examined both in vitro and in vivo by using NCI-H727 (SSTR2/FAP, positive) and Mc38 (SSTR2/FAP, negative) cell lines and tumor-bearing mouse models. Preclinical evaluation was performed through cell uptake, pharmacokinetics, Micro PET, and biodistribution studies, and the results were compared with [68Ga]Ga-DOTA-TATE and [68Ga]Ga -FAPI-46. Immunohistochemistry and HE staining were performed on tumor tissues from tumor-bearing mice for further validation. Results: [68Ga]Ga-TATE-46 showed comparable SSTR2 and FAP targeting ability to monomeric TATE and FAPI-46 in cell uptake and PET imaging studies. [68Ga]Ga-TATE-46 exhibited significantly higher uptake in NCI-H727 (SSTR2/FAP, positive) tumors compared to [68Ga]Ga-DOTA-TATE (p < 0.001) and [68Ga]Ga-FAPI-46 (p < 0.001). No increased uptake of [68Ga]Ga-TATE-46 was observed in MC38 tumors (SSTR2/FAP, negative). Additionally, excess DOTA-TATE and/or unlabeled FAPI-46 significantly blocked the uptake of [68Ga]Ga-TATE-46 in NCI-H727 tumors (p < 0.001), confirming its dual-receptor targeting characteristics. The ex vivo biodistribution, immunofluorescence and immunohistochemistry results were in line with the in vivo imaging findings. Conclusion: Compared with 68Ga-labeled FAPI-46 and DOTA-TATE mono-specific tracers, the dual-target tracer [68Ga]Ga-TATE-46 improves tumor uptake, extends tumor retention, and enhances pharmacokinetics. It is an effective probe for non-invasive detection of tumors expressing FAP and SSTR2, and it is worth further studying its application in the expression of sstr2 and FAP-related tumors.

Abstract Background Acute kidney injury (AKI) represents a frequent and grave complication associated with acute pancreatitis (AP), substantially elevating both mortality rates and the financial burden of hospitalization. The aim of our study is to construct a predictive model utilizing automated machine learning (AutoML) algorithms for the early prediction of AKI in patients with AP. Methods We retrospectively analyzed patients who were diagnosed with AP in our hospital from January 2017 to December 2021. These patients were randomly allocated into a training set and a validation set at a ratio of 7:3. To develop predictive models for each set, we employed the least absolute shrinkage and selection operator (LASSO) algorithm along with AutoML. A nomogram was developed based on multivariate logistic regression analysis outcomes. The model’s efficacy was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Additionally, the performance of the model constructed via AutoML was evaluated using decision curve analysis (DCA), feature importance, SHapley Additive exPlanations (SHAP) plots, and locally interpretable model-agnostic explanations (LIME). Results This study incorporated a total of 437 patients who met the inclusion criteria. Out of these, 313 were assigned to the training cohort and 124 to the validation cohort. In the training and validation cohorts, AKI occurred in 68 (21.7%) and 29(23.4%) patients, respectively. Comparative analysis revealed that the AutoML models exhibited enhanced performance over traditional logistic regression (LR). Furthermore, the deep learning (DL) model demonstrated superior predictive accuracy, evidenced by an area under the ROC curve of 0.963 in the training set and 0.830 in the validation set, surpassing other comparative models. The key variables identified as significant in the DL model within the training dataset included creatinine (Cr), urea (Urea), international normalized ratio (INR), etiology, smoking, alanine aminotransferase (ALT), hypertension, prothrombin time (PT), lactate dehydrogenase (LDH), and diabetes. Conclusion The AutoML model, utilizing DL algorithm, offers considerable clinical significance in the early detection of AKI among patients with AP.

As computer-aided diagnostic technology continues to advance, medical image analysis plays a crucial role in the early detection and treatment of gastrointestinal diseases. Colorectal cancer is a common malignant tumor, and the accurate identification and segmentation of colonic polyps, which are its precursors, are of great significance for the prevention of colorectal cancer. However, due to the diversity in the morphology and color of polyps, as well as the concealment of small or flat polyps, accurately segmenting them in endoscopic images poses a challenge. This paper proposes an innovative Multi-Dimensional Fusion Reverse Attention Network (MdfraNet) aimed at precisely identifying and segmenting the boundaries of polyps and their surrounding mucosa. This method leverages a Multi-Scale Mobile Inverted Convolution Model (MSMB) to achieve deep fusion of multidimensional features, capturing contextual information and detailed features from different scales. Furthermore, the study introduces a Hierarchical Multiscale Cross Reverse Attention (HMC-RA)mechanism, which effectively integrates information from multiple scales and locations, significantly enhancing feature representation, especially in handling polyp boundary information. Extensive testing of MdfraNet on five public polyp datasets (CVC-300, CVC-ColonDB, CVC-ClinicDB, Kvasir-SEG, and ETIS-LaribPolypDB) demonstrates that this model has a significant advantage in handling boundary information compared to existing techniques, showcasing excellent performance. Additionally, MdfraNet has also shown superior segmentation results on our in-house dataset from our collaborative hospital.

Rural adolescents are at higher risk of reduced academic persistence due to socioeconomic barriers. Educational expectations are theoretically viewed as important for adolescents’ learning behaviors, and cross-sectional research has supported this assumption. However, few longitudinal studies have investigated the influence of educational expectations on adolescents’ academic persistence. In addition, research has not clearly identified whether self-esteem moderates this link among adolescents who experience greater economic risk. Using data from two time points (i.e., six months apart), this study aims to provide a more complete understanding of whether, and under what conditions, rural adolescents’ educational expectations influence academic persistence. The participants consist of 631 adolescents (Mage = 13.34 years at T1), and all the adolescents are from families with rural household registrations. The results show that the interaction term of educational expectations and self-esteem significantly predicts academic persistence. Specifically, after controlling for baseline academic persistence, educational expectations positively predict later academic persistence for rural adolescents with lower self-esteem, and educational expectations do not significantly predict later academic persistence for those with higher self-esteem. This study reveals the protective role of self-esteem in rural adolescents. High self-esteem benefits rural adolescents by protecting them from the effects of lower educational expectations on academic persistence. This finding also emphasizes the importance of developing self-esteem interventions for rural adolescents with low educational expectations to prevent them from experiencing weaker academic persistence.

Abstract Purpose To investigate the clinical value of radiomic analysis on [18F]FDG and [18F]FLT PET on the differentiation of [18F]FDG-avid benign and malignant pulmonary nodules (PNs). Methods Data of 113 patients with inconclusive PNs based on preoperative [18F]FDG PET/CT who underwent additional [18F]FLT PET/CT scans within a week were retrospectively analyzed in the present study. Three methods of analysis including visual analysis, radiomic analysis based on [18F]FDG PET/CT images alone, and radiomic analysis based on dual-tracer PET/CT images were evaluated for differential diagnostic value of benign and malignant PNs. Results A total of 678 radiomic features were extracted from volumes of interest (VOIs) of 123 PNs. Fourteen valuable features were thereafter selected. Based on a visual analysis of [18F]FDG PET/CT images, the diagnostic accuracy, sensitivity, and specificity were 61.6%, 90%, and 28.8%, respectively. For the test set, the area under the curve (AUC), sensitivity, and specificity of the radiomic models based on [18F]FDG PET/CT plus [18F]FLT signature were equal or better than radiomics based on [18F]FDG PET/CT only (0.838 vs 0.810, 0.778 vs 0.778, 0.750 vs 0.688, respectively). Conclusion Radiomic analysis based on dual-tracer PET/CT images is clinically promising and feasible for the differentiation between benign and malignant PNs. Clinical relevance statement Radiomic analysis will add differential diagnostic value of benign and malignant pulmonary nodules: a hybrid imaging study based on [18F]FDG and [18F]FLT PET/CT. Key points • Radiomics brings new insights into the differentiation of benign and malignant pulmonary nodules beyond the naked eyes. • Dual-tracer imaging shows the biological behaviors of cancerous cells from different aspects. • Radiomics helps us get to the histological view in a non-invasive approach. Graphical Abstract

Abstract Objectives To validate an appropriate evaluation method of liver fibrosis assessment based on the unique pathological features of biliary atresia (BA) that could well predict its prognosis. Methods A total of 68 patients with BA who underwent Kasai procedure (KP) and an intraoperative liver biopsy, followed up from January 2019 to December 2021, were recruited in a retrospective analysis. Ishak, Metavir, and BA-specific staging systems in relation to outcomes were analyzed using logistic regression, COX proportional hazard regression, Kaplan-Meier analysis, etc. Results Kaplan-Meier analysis determined a significant difference in native liver survival according to the BA-specific stage (p = 0.002). The ROC curve analysis for predicting prognosis showed that the AUC of BA-specific staging combined with iBALF and severe bile duct proliferation (BDP) (0.811, 95% CI: 0.710–0.913, p

Atherosclerosis is a significant risk factor for coronary heart disease (CHD) and myocardial infarction (MI). Atherosclerosis develops during foam cell generation, which is caused by an imbalance in cholesterol uptake, esterification, and efflux. LOX-1, SR-A1, and CD36 all increased cholesterol uptake. ACAT1 and ACAT2 promote free cholesterol (FC) esterification to cholesteryl esters (CE). The hydrolysis of CE to FC was aided by nCEH. FC efflux was promoted by ABCA1, ABCG1, ADAM10, and apoA-I. SR-BI promotes not only cholesterol uptake but also FC efflux. Circular RNAs (circRNAs), which are single-stranded RNAs with a closed covalent circular structure, have emerged as promising biomarkers and therapeutic targets for atherosclerosis due to their highly tissue, cell, and disease state-specific expression profiles. Numerous studies have shown that circRNAs regulate foam cell formation, acting as miRNA sponges to influence atherosclerosis development by regulating the expression of SR-A1, CD36, ACAT2, ABCA1, ABCG1, ADAM10, apoA-I, SR-B1. Several circRNAs, including circ-Wdr91, circ 0004104, circRNA0044073, circRNA_0001805, circDENND1B, circRSF1, circ 0001445, and circRNA 102682, are potential biomarkers for atherosclerosis to better evaluate cardiovascular risk. It is difficult to deliver synthetic therapeutic circRNAs to the desired target tissues. Nanotechnology, such as GA-RM/GZ/PL, may be an important solution to this problem. In this review, we focus on the potential role and mechanism of circRNA/miRNA axis in foam cell formation in the hopes of discovering new targets for the diagnosis, prevention, and treatment of atherosclerosis.

Introduction: To investigate the diagnostic value of serum MMP-7 and SOX9 levels in patients with biliary atresia (BA) and to further analyze their relationship with the liver fibrosis and prognosis. Methods: Sixty-eight patients hospitalized for jaundice and underwent surgical treatment from March 2019 to February 2022 were retrospectively analyzed, including 44 patients with BA and 24 patients with other cholestatic liver diseases as disease controls (DC). Serum levels of MMP-7 and SOX9 were detected using enzyme-linked immunosorbent assay (ELISA). The diagnostic value of MMP-7 and SOX9 for BA was evaluated using the receiver operating characteristic (ROC) curve. Results: Serum levels of MMP-7 and SOX9 were higher in the BA group compared to the DC group (P = 0.0002, P = 0.0006). The AUC for the combined diagnosis of serum MMP-7, SOX9 and GGT was 0.888 (95 % CI:0.788–0.952, P < 0.0001), which was significantly different from the diagnosis of MMP-7 or SOX9 alone (P = 0.034, P = 0.030). Serum levels of MMP-7 and SOX9 were significantly positively correlated with the liver fibrosis score (rs = 0.41, P = 0.006; rs = 0.58, P < 0.0001). BA patients who maintained native liver survival had lower preoperative serum levels of MMP-7 and SOX9 (P = 0.008, P = 0.0008). Conclusions: The combined diagnosis of BA by MMP-7, SOX9 and GGT has better accuracy than MMP-7 or SOX9 alone. Serum SOX9 levels can assess the severity of BA liver fibrosis and correlate with BA native liver survival, but more sample data are needed to further investigate its predictive value.

Understanding and forecasting complex freight mode choice behavior under various industry, policy, and technology contexts is essential for freight planning and policymaking. Numerous models have been developed to provide insights into freight mode selection; most use discrete choice models such as multinomial logit (MNL) models. However, logit models often rely on linear specifications of independent variables despite potential nonlinear relationships in the data. A common challenge for researchers is the absence of a heuristic and efficient method to discern and define these complex relationships in logit model specifications. This often results in models that might be deficient in both predictive power and interpretability. To bridge this gap, we develop an MNL model for freight mode choice using the insights from machine learning (ML) models. ML models can better capture the nonlinear nature of many decision-making processes, and recent advances in “explainable AI” have greatly improved their interpretability. We showcase how interpretable ML methods help enhance the performance of MNL models and deepen our understanding of freight mode choice. Specifically, we apply SHapley Additive exPlanations (SHAP) to identify influential features and complex relationships to improve the MNL model’s performance. We evaluate this approach through a case study for Austin, Texas, where SHAP results reveal multiple important nonlinear relationships. Incorporating those relationships into MNL model specifications improves the interpretability and accuracy of the MNL model. Findings from this study can be used to guide freight planning and inform policymakers about how key factors affect freight decision-making.

Adolescents’ expectations on future subjective social status (SSS) may play a critical role in the relations between perceived parental expectations and persistence; however, there is a lack of research exploring this effect in the context of families experiencing greater economic risk. This study aimed to explicitly address this issue. A total of 698 Chinese rural adolescents participated in this study (Mage = 13.32 years; 54.60% boys). The results showed that for rural adolescents with lower expected future SSS, perceived parental expectation was negatively related to persistence; for rural adolescents with higher expected future SSS, perceived parental expectation was not significantly correlated with persistence. These findings imply the adverse effects of high perceived parental expectation on rural adolescents’ persistence and that expected future SSS can alleviate this adverse relationship.

Triple-negative breast cancer (TNBC) stands out as the most aggressive subtype within the spectrum of breast cancer. The current clinical guidelines propose treatment strategies involving cytotoxic agents like epirubicin or paclitaxel. However, the emergence of acquired resistance frequently precipitates secondary tumor recurrence or the spread of metastasis. In recent times, significant attention has been directed toward the transcription factor RUNX2, due to its pivotal role in both tumorigenesis and the progression of cancer. Previous researches suggest that RUNX2 might be intricately linked to the development of resistance against chemotherapy, with its mechanism of action possibly intertwined with the signaling of TGF-β. Nevertheless, the precise interplay between their effects and the exact molecular mechanisms underpinning chemoresistance in TNBC remain elusive. Therefore, we have taken a multifaceted approach from in vitro and in vivo experiments to validate the relationship between RUNX2 and TGF-β and to search for their pathogenic mechanisms in chemoresistance. In conclusion, we found that RUNX2 affects chemoresistance by regulating cancer cell stemness through direct binding to TGF-β, and that TGF-β dually regulates RUNX2 expression. The important finding will provide a new reference for clinical reversal of the development of chemoresistance in breast cancer.

Enormous endeavors have been made to cope with microwave pollution and energy crisis. Here, porous nitrogen-doped C/TiO2 composites with absorption/shielding/supercapacitor functions were derived from MXene/polyaniline. It was discovered that KOH acted as porogen and had an etching–bridging–reaction effect during the activation process. As a microwave absorber, the composite/paraffin with a filler loading of 16 wt% reaches a minimum reflection loss of −52.8 dB and an effective absorption bandwidth of 4.72 GHz. Moreover, microwave absorption can be maintained within 45 days in air. Compared with untreated MXene, the absorber shows long-term functional stability in an oxygen-containing environment. As for electromagnetic interference shielding, the composite/paraffin at a filler loading of 50 wt% achieves 30.5 dB from 8.0 to 12.4 GHz. Additionally, the heterostructure delivers a desirable specific capacitance of 1,096.3 F g−1 at 0.5 A g−1. The trifunctional characteristics enrich the application trials of MXene derivatives and satisfy the strong need for versatile materials.

Abstract Background In China, many ornamental plants associated with Buddhist figures, including the Sakyamuni, Bodhisattva, and Arhat, were grown and worshiped because of their cultural and religious significance. However, the systematic collation and ethnobotanical information about these culturally important plants have yet to be fully understood. Methods Online information was collected from 93 e-commercial platforms for ornamental plants all over China. Field sampling was conducted in 16 ornamental markets and 163 Buddhist temples using key informant interviews and participatory observation with traders, tourists, and local disciples. The types, distributions, and associated characteristics of the screened plants were summarized and the evolving characteristics of these ornamental plants were analyzed. Results A total of 60 ornamental plants, including six varieties and one subspecies, were screened, of which 43 species were associated with Sakyamuni, 13 with Bodhisattva, and four with Arhat. Among the 60 species, three were regarded as the Asoka tree related to Buddha's birth, ten as the Bodhi tree connected to Buddha's enlightenment, three as the Sal tree associated with Buddha's nirvana, nine were related to Buddha’s head, belly, or hand, and 18 were connected with Buddha as lotus throne, bamboo monastery, or Bodhi beads. The evolving characteristics of these ornamental plants primarily constituted the substitution of the original plants by similar native plant species, followed by the introduced species with comparable morphology to the Buddhist figures. Conclusions People grow ornamental plants associated with Buddhist figures to reflect their love and praise for plants and Buddha. The association between the ornamental plants and Buddhist figures will aid the inheritance of Buddhist culture and promote ornamental plants in the commercial market. Thus, the ethnobotany of ornamental plants associated with Buddhist figures can serve as a basis for future investigation of modern Buddhist culture.

Cerasus ‘Hongxia’, a Yunnan flowering cheery cultivar blooming in March with semi-double to double pink petals, have been widely cultivated in central Yunnan for its high ornamental value. It was regarded as the cultivar of Cerasus cerasoides var. rubea. However, it was clustered in C. campanulata based on molecular markers. Therefore, the phylogeny of these cultivars are doubtful, which is not conducive to their breeding and cultivation. In order to explore the origin of Cerasus ‘Hongxia’, with leaf DNA of Cerasus ‘Hongxia’ as material, chloropast genome characteristics were sequenced by Illumina, assembled, annotated, and analyzed by bioinformatic methods, and analyzed by MISA and Genious R10. The phylogenetic tree of Cerasus was reconstructed by using RAxML 8.0, and the phylogenetic relationship of Cerasus ‘Hongxia’ was analyzed. The results were as follows: (1) The chloroplast genome of Cerasus ‘Hongxia’ was 157 832 bp in length, containing a pair of reverse repeat sequence (inverted repeat sequence，IR, 26 381 bp) regions, which were separated by a short single copy (SSC, 19 120 bp) region and a long single copy (LSC, 85 950 bp) region. A total of 128 genes were encoded, including 84 protein-coding genes, 36 tRNA genes and 8 rRNA ribosomal genes. The overall Guanine and Cytosine content of genome was 36.73%. (2) Based on the maximum likelihood phylogenetic tree analysis of 16 chloroplast genome of Cerasus, it was found that Cerasus ‘Hongxia’ was formed as sister to C. subhirtella and C. yedoensis, and was far away from C. cerasoides. Therefore, we speculated that Cerasus ‘Hongxia’ may be a hybrid cultivar of C. campanulata and C. subhirtella or C. yedoensis, rather than the cultivar of C. cerasoides. The above results are be useful for studies of the origination and genetic breeding of Cerasus ‘Hongxia’, as well as the cultivar identification and classification of C. cerasoides.

Abstract Objective To evaluate the diagnostic value of a multiparameter model based on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) metabolic parameters and clinical variables in differentiating nonmetastatic gallbladder cancer (GBC) from cholecystitis. Patients and methods In total, 122 patients (88 GBC nonmetastatic patients and 34 cholecystitis patients) with gallbladder space-occupying lesions who underwent 18F-FDG PET/CT were included. All patients received surgery and pathology, and baseline characteristics and clinical data were also collected. The metabolic parameters of 18F-FDG PET, including SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), SUVpeak (peak standard uptake value), MTV (metabolic tumour volume), TLG (total lesion glycolysis) and SUVR (tumour-to-normal liver standard uptake value ratio), were evaluated. The differential diagnostic efficacy of each independent parameter and multiparameter combination model was evaluated using the receiver operating characteristic (ROC) curve. The improvement in diagnostic efficacy using a combination of the above multiple parameters was evaluated by integrated discriminatory improvement (IDI), net reclassification improvement (NRI) and bootstrap test. Decision curve analysis (DCA) was used to evaluate clinical efficacy. Results The ROC curve showed that SUVR had the highest diagnostic ability among the 18F-FDG PET metabolic parameters (area under the curve [AUC] = 0.698; sensitivity = 0.341; specificity = 0.971; positive predictive value [PPV] = 0.968; negative predictive value [NPV] = 0.363). The combined diagnostic model of cholecystolithiasis, fever, CEA > 5 ng/ml and SUVR showed an AUC of 0.899 (sensitivity = 0.909, specificity = 0.735, PPV = 0.899, NPV = 0.758). The diagnostic efficiency of the model was improved significantly compared with SUVR. The clinical efficacy of the model was confirmed by DCA. Conclusions The multiparameter diagnostic model composed of 18F-FDG PET metabolic parameters (SUVR) and clinical variables, including patient signs (fever), medical history (cholecystolithiasis) and laboratory examination (CEA > 5 ng/ml), has good diagnostic efficacy in the differential diagnosis of nonmetastatic GBC and cholecystitis.

Drug-induced nephrotoxicity (DIN) is a big concern for clinical medication, but the clinical use of certain nephrotoxic drugs is still inevitable. Current testing methods make it hard to detect early renal injury accurately. In addition to understanding the pathogenesis and risk factors of drug-induced nephrotoxicity, it is crucial to identify specific renal injury biomarkers for early detection of DIN. Urine is an ideal sample source for biomarkers related to kidney disease, and urinary exosomes have great potential as biomarkers for predicting DIN, which has attracted the attention of many scholars. In the present paper, we will first introduce the mechanism of DIN and the biogenesis of urinary exosomes. Finally, we will discuss the changes in urinary exosomes in DIN and compare them with other predictive indicators to enrich and boost the development of biomarkers of DIN.

This study delves into the exploration of genetic diversity and phylogenetic relationships within Camellia reticulata cultivars, providing a vital reference for horticultural research on this hetero-hexaploid species. Utilizing available transcriptome data from C. reticulata, novel low-copy nuclear gene sequences were successfully identified. With tailored primer design, these genes were amplified and sequenced from 100 C. reticulata cultivars originating from Kunming, Chuxiong, Dali, and Tengchong in China. Five distinct low-copy nuclear gene sequences were found to collectively span 3481 bp, showcasing 71 polymorphic mutation sites (Pi = 0.0077) and 91 haplotypes (Hd = 0.9974). The genetic diversity among cultivars from the four provenances ranked Tengchong > Dali > Kunming > Chuxiong. AMOVA analysis revealed that 96.50% of the genetic variation exists within the provenances. Low genetic distance and differentiation (Fst= 0.0199) were observed among cultivars from the four provenances. Ninety-nine cultivars were clustered into four clades, corresponding to the three ancestors of C. reticulata (diploid C. reticulata, C. pitardii, and C. saluenensis). The novel low-copy nuclear gene sequence markers developed in this study provide an effective tool for analyzing genetic diversity, phylogenetic relationships, and origination of C. reticulata cultivars.

Abstract Background To advance the understanding of adzuki bean (Vigna angularis) resistance to infection with the rust-causing fungus Uromyces vignae (Uv), we comprehensively analyzed histological events and the transcriptome of Uv-infected adzuki bean. Results Compared with the susceptible cv. Baoqinghong (BQH), the resistant cv. QH1 showed inhibition of uredospore germination and substomatal vesicle development, intense autofluorescence of cells around the infection site, and cell wall deposit formation in response to Uv infection. In cv. QH1, gene set enrichment analysis (GSEA) showed enrichment of chitin catabolic processes and responses to biotic stimuli at 24 h post-inoculation (hpi) and cell wall modification and structural constituent of cytoskeleton at 48 hpi. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated enrichment of WRKY transcription factors (TFs), the calcium binding protein cml, and hydroquinone glucosyltransferase at both 24 and 48 hpi. In total, 1992 and 557 differentially expressed genes (DEGs) were identified at 24 and 48 hpi, respectively. Cell surface pattern-recognition receptors (PRRs), WRKY TFs, defense-associated pathogenesis-related (PR) proteins, and lignin and antimicrobial phenolic compound biosynthesis were significantly induced. Finally, we detected the chitinase (CHI) and phenylalanine ammonia-lyase (PAL) activity were higher in QH1 and increased much earlier than in BQH. Conclusion In cv. QH1, cell-surface PRRs rapidly recognize Uv invasion and activate the corresponding TFs to increase the transcription of defense-related genes and corresponding enzymatic activities to prevent fungal development and spread in host tissues.

Background Endoscopic resection (ER) is a proven treatment for gastric gastrointestinal stromal tumors (gGISTs). We aimed to assess the learning curve (LC) associated with ER for gGISTs and identify determinants. Methods We conducted an analysis of 289 patients who underwent the ER of gGISTs by an experienced endoscopist. To characterize the LC, we employed cumulative sum analysis of the duration of surgery. The participants were divided into an early phase (cases 1–50) and a later phase (case 51–289), which were compared. Furthermore, we identified risk factors for the conversion from endoscopic to laparoscopic resection (LR). Results The durations of surgery and hospitalization were shorter, and there were fewer complications and fasting days in the later phase. The conversion rates to LR were 6.0% and 2.5% in the early and later phases, respectively. The tumor diameter (≥3.0 cm) and invasion beyond the muscularis propria were significant risk factors for conversion to LR (odds ratio 17.92, 95% confidence interval 2.66–120.87; and 58.03, 6.40–525.84; respectively). Conclusions The LC for ER of gGISTs lasts for approximately 50 cases. In addition, tumors ≥3.0 cm in diameter and those that invade beyond the muscularis propria are more likely to require conversion to LR.

IntroductionRespirators chosen based on their assigned protection factor (APF) enable wearers to effectively reduce particulate matter concentrations to safe levels when used correctly. As a crucial factor in achieving the intended APF, the fit test has become a necessary procedure in respiratory disease protection.MethodsThis study involved 225 participants who underwent a fit test using two reusable types of half masks and two types of full masks. Condensation nuclei counting (CNC) and controlled negative pressure (CNP) were performed.ResultsThe results revealed that the passing rate of full masks was higher compared to half masks. Specifically, the passing rate for the half masks and the full masks were 84.7 and 91.6%, respectively. Gender exerted a statistically significant effect on the passing rate. Nevertheless, age, educational background, and training exhibited relatively negligible effects. Certain movements, such as facing forward, were identified as key actions with strong correlation. Additionally, talking was considered a key action with a high failure rate due to instantaneous leakages. Most participants failed at the initial step of CNP, but nearly all of them passed the fit test using CNC.DiscussionTherefore, putting on full masks, especially for women, provides optimal protection during work. Furthermore, attention should be given to the displacement and deformation of the respirator during the key actions. When it comes to fit test methods, CNC was found to be more practical and comprehensive compared to CNP. Moreover, additional physiological characteristics, such as double chins, could be explored as potential influential factors.

Abstract Objective To evaluate the diagnostic performance of combined multiparametric 18F-fluorodeoxyglucose positron emission tomography (18FDG PET) with clinical characteristics in differentiating thymic epithelial tumors (TETs) from thymic lymphomas. Patients and methods A total of 173 patients with 80 TETs and 93 thymic lymphomas who underwent 18F-FDG PET/CT before treatment were enrolled in this retrospective study. All patients were confirmed by pathology, and baseline characteristics and clinical data were also collected. The semi-parameters of 18F-FDG PET/CT, including lesion size, SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), TLG (total lesion glycolysis), MTV (metabolic tumor volume) and SUVR (tumor-to-normal liver standard uptake value ratio) were evaluated. The differential diagnostic efficacy was evaluated using the receiver operating characteristic (ROC) curve. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI), and Delong test were used to evaluate the improvement in diagnostic efficacy. The clinical efficacy was evaluated by decision curve analysis (DCA). Results Age, clinical symptoms, and metabolic parameters differed significantly between patients with TETs and thymic lymphomas. The ROC curve analysis of SUVR showed the highest differentiating diagnostic value (sensitivity = 0.763; specificity = 0.888; area under the curve [AUC] = 0.881). The combined diagnostics model of age, clinical symptoms and SUVR resulted in the highest AUC of 0.964 (sensitivity = 0.882, specificity = 0.963). Compared with SUVR, the diagnostic efficiency of the model was improved significantly. The DCA also confirmed the clinical efficacy of the model. Conclusions The multiparameter diagnosis model based on 18F-FDG PET and clinical characteristics had excellent value in the differential diagnosis of TETs and thymic lymphomas.

BackgroundAccurate preoperative assessment of surgical difficulty is crucial to the success of the surgery and patient safety. This study aimed to evaluate the difficulty for endoscopic resection (ER) of gastric gastrointestinal stromal tumors (gGISTs) using multiple machine learning (ML) algorithms.MethodsFrom December 2010 to December 2022, 555 patients with gGISTs in multi-centers were retrospectively studied and assigned to a training, validation, and test cohort. A difficult case was defined as meeting one of the following criteria: an operative time ≥ 90 min, severe intraoperative bleeding, or conversion to laparoscopic resection. Five types of algorithms were employed in building models, including traditional logistic regression (LR) and automated machine learning (AutoML) analysis (gradient boost machine (GBM), deep neural net (DL), generalized linear model (GLM), and default random forest (DRF)). We assessed the performance of the models using the areas under the receiver operating characteristic curves (AUC), the calibration curve, and the decision curve analysis (DCA) based on LR, as well as feature importance, SHapley Additive exPlanation (SHAP) Plots and Local Interpretable Model Agnostic Explanation (LIME) based on AutoML.ResultsThe GBM model outperformed other models with an AUC of 0.894 in the validation and 0.791 in the test cohorts. Furthermore, the GBM model achieved the highest accuracy among these AutoML models, with 0.935 and 0.911 in the validation and test cohorts, respectively. In addition, it was found that tumor size and endoscopists’ experience were the most prominent features that significantly impacted the AutoML model’s performance in predicting the difficulty for ER of gGISTs.ConclusionThe AutoML model based on the GBM algorithm can accurately predict the difficulty for ER of gGISTs before surgery.

PurposeTo investigate the diagnostic value of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), as an imaging biomarker, for predicting pathological response and prognosis of unresectable hepatocellular carcinoma (HCC) patients treated with Lenvatinib and programmed cell death protein 1 (PD-1) inhibitors as a conversion therapy.MethodsA total of 28 unresectable HCC patients with BCLC stage B or C were treated with Lenvatinib and PD-1 inhibitors before surgery. The 18F-FDG PET/CT scans were acquired before pre- (scan-1) and post-conversion therapy (scan-2). The maximum standardized uptake value (SUVmax), TLR (tumor-to-normal liver standardized uptake value ratio), and the percentages of post-treatment changes in metabolic parameters (ΔSUVmax [%] and ΔTLR [%]) were calculated. Major pathological response (MPR) was identified based on the residual viable tumor in the resected primary tumor specimen (≤10%). Differences in the progression-free survival (PFS) and overall survival (OS) stratified by ΔTLR were examined by the Kaplan-Meier method.Results11 (11/28, 39.3%) patients were considered as MPR responders and 17 (17/28, 60.7%) patients as non-MPR responders after conversion therapy. ΔSUVmax (-70.0 [-78.8, -48.8] vs. -21.7 [-38.8, 5.7], respectively; P

IntroductionPositive personality traits have been associated with personal well-being in previous research. However, the pathways through which positive personality may affect social well-being remain unclear. The present study hypothesized that the cognitive strategies for achieving well-being (i.e., orientation to happiness) mediate the association between good personality and social well-being in the Chinese culture.MethodsA survey including the Good Personality Questionnaire, Social Well-being Scales, and Orientations to Happiness was administered to 1,503 Chinese secondary school students and adults.ResultsThe results indicated that orientation to meaning mediated the relation between good personality and social well-being, but not orientation to pleasure.DiscussionThis is in line with the normative well-being model and the cognition instrumental model of well-being, which contributes to developing more targeted interventions to promote social well-being in the Chinese cultural.

Objective Endoscopic resection (ER) of gastric gastrointestinal stromal tumors (gGISTs) is a commonly used treatment; however, it is associated with a risk of conversion to laparoscopic resection (LR). This study was performed to identify factors influencing conversion from ER to LR and the effects of conversion on outcomes. Methods The clinicopathological features of patients treated for gGISTs from March 2010 to May 2021 were retrospectively collected. Endpoints included the determination of risk factors associated with LR conversion, with comparisons of surgical outcomes with and without conversion. Propensity score matching was performed to compare the two groups. Results In total, 371 gGISTs were analyzed. Sixteen patients required conversion from ER to LR. Propensity score matching demonstrated that invasion depth (muscularis propria with exophytic growth) and gGIST size (≥3 cm) were independent risk factors for conversion to LR. The procedure duration (median, 160.5 vs. 60.0 minutes), postoperative hospitalization duration (median, 8 vs. 6 days), and postoperative fasting duration (median, 5 vs. 3 days) were significantly longer in patients who underwent conversion to LR. Conclusions Accurate preoperative measurements of tumor size and invasion depth may help determine more appropriate surgical approaches for patients with gGISTs.

Breast cancer remains the most common malignancy in women and constantly threatens the lives of patients worldwide. State-of-the-art renewal has indicated the involvement of RUNX-associated transcription factor 2 (RUNX2) in tumorigenesis and cancer progression, yet the detailed information during breast cancer is largely obscure. Herein, we took advantage of breast cancer cell lines and in vivo tumorigenicity test as well as multifaceted phenotypic analyses (e.g., RNA-sequencing, ChIP and qRT-PCR assay) to verify the pathogenic mechanism of RUNX2 in triple negative breast cancer aggressiveness and chemoresistance. Strikingly, the proliferation, migration, invasion and chemoresistance of resistant cell lines in triple negative breast cancer was effectively suppressed by RUNX2 silencing, and the in vivo tumorigenicity was significantly weakened as well. Furthermore, with the aid of transcriptomic and bioinformatic analyses, we found MMP1 was highly expressed in triple negative breast cancer (TNBC) and showed a strong correlation with the poor prognosis of the patients, which was consistent with the expression pattern of RUNX2. Finally, by conducting ChIP and qRT-PCR assessment, we verified that RUNX2 functioned via directly binding to the specific motifs in the promoter of MMP1 and thus activating the transcriptional process. Collectively, our data demonstrated the facilitating effect of RUNX2 during triple negative breast cancer progression by directly orchestrating the expression of MMP1, which supplied overwhelming new references for RUNX2-MMP1 axis serving as a novel candidate for breast cancer diagnosis and treatment.

ObjectiveBiliary atresia (BA) presents as a severe infantile cholangiopathy disease, characterized by progressive liver fibrosis and the resulting poor prognosis. Leukocyte cell-derived chemotaxin 2 (LECT2) was proposed as the key gene associated with hepatic fibrosis in BA, but the molecular mechanism is unclear. This study aims to investigate the function of LECT2 in BA.MethodsA total of 53 patients were enrolled in this study; 36 patients with BA, and 17 control patients with cholestasis, including congenital biliary dilations, biliary hypoplasia, and inspissated bile syndrome. The role of LECT2 in BA was analyzed using histological and cytological tests. The correlation between LECT2 and infiltrating immune cells was further analyzed by bioinformatics. The analyses were conducted using correlational analyses and ROC curves.ResultsLECT2 was highly expressed in infants with BA and positively related with fibrosis (0.1644 ± 0.0608 vs. 0.0779 ± 0.0053, p < 0.0001; rs = 0.85, p < 0.0001). Serum levels of LECT2 showed high distinguishing features for patients with BA having an AUC of 0.95 (95% CI: 0.90–1.00). CD163 was highly expressed in the aggravation of fibrosis (0.158 ± 0.062 vs. 0.29 ± 0.078, p < 0.0001), and the expression of LECT2 was positively correlated with the accumulation of CD163+ macrophages (r = 0.48, p = 0.003). The bioinformatic analysis also showed that LECT2 was positively correlated with macrophage M2 (r = 0.34, p = 0.03). TGF-β1 and CD163 colocalized to the portal area in the livers of patients with BA. Moreover, TGF-β1 upregulated the expression of LECT2.ConclusionLECT2 is highly expressed in both BA liver tissue and serum, and serum LECT2 is a potential diagnostic biomarker of BA. Meanwhile, TGF-β1 is secreted by macrophages to regulate LECT2 associated with BA liver fibrosis.

ObjectivesThis study aimed to assess the pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) as a predictor of the pathological treatment response (PTR) of hepatocellular carcinoma (HCC) patients treated with PD-1 inhibitors and lenvatinib as a conversion therapy in BCLC stage C.MethodsAll patients (n=20) underwent pretreatment 18F-FDG PET/CT and were treated with conversion therapy and surgery. Patients were categorized into responders (n=9) and non-responders (n=11) according to PTR. The parameters of PET/CT, including lesion size, SUVmean (mean standard uptake value), MTV (metabolic tumor volume), TLG (total lesion glycolysis), SUVpeak (peak standard uptake value), and TLR (tumor-to-normal liver standardized uptake value ratio), were calculated. The diagnostic efficacy was evaluated by receiver operating characteristic analysis (ROC). PTR was compared with pretreatment PET/CT parameters by using Spearman correlation analysis. The patients were followed up.ResultsThere was significant difference in TLR (5.59 ± 1.90 vs. 2.84 ± 1.70, respectively; P=0.003) between responders and non-responders, with the largest area under the curve (sensitivity=100%, specificity=72.7%, AUC=0.899, 95%CI: 0.759-1.000, optimal diagnostic threshold of 3.09). The relationship between 18F-FDG PET/CT parameters and PTR indicated TLR was moderately and positively correlated with pathological treatment response, with correlation coefficients (rs) of 0.69 (P

BackgroundHepato-pancreato-biliary (HPB) disease has different causes and types between children and adults, which has been increasingly diagnosed in the pediatric group. Endoscopic retrograde cholangiopancreatography (ERCP) has been gradually considered as a therapeutic method in adults, while in pediatric patients, there are not many reports of its usage. This systematic review and meta-analysis aims to assess the use condition of therapeutic ERCP in the management of pediatric HPB diseases.MethodsThis systematic literature search was conducted in the PubMed, Embase, Web of Science, and Cochrane library databases to identify all relevant articles published from inception to February 2022 that evaluated therapeutic ERCP in pediatric patients with HPB diseases. The researchers included studies in which patients were less than 18 years old and underwent therapeutic ERCP procedures. A random-effects model was used to analyze the usage rate of therapeutic ERCP procedures, procedural success rates, adverse event rates, and the rate of different therapeutic procedures. Subgroup analysis, sensitivity analysis, and meta-regression were conducted to analyze the source of heterogeneity.ResultsA total of 33 articles were included. After homogenization, the overall use of therapeutic interventions accounts for 77% [95% confidence interval (CI) 74–81%] of all ERCP procedures. After excluding outlier studies, the estimation success rate of the therapeutic procedure is 74% (95% CI 69–79%), and adverse event rate is 8% (95% CI 6–10%). In our study, stent placement is the most common procedure, which makes up 75% (95% CI 65–86%) of all therapeutic procedures. In addition, the usage proportion of sphincterotomy (ST), stone extraction/removal, bougienage/balloon dilation is, respectively, 46% (95% CI 39–53%), 34% (95% CI 31–38%), and 26% (95% CI 22–29%).ConclusionThe ERCP procedure is gradually considered a therapeutic technique in pediatric patients, the proportion of therapeutic ERCP is 77% of total usage, which is increasing every year. Meanwhile, its success rate is relatively high. It reflects that this operation modality is promising in the treatment of HPB disorders and is gradually expanded as more branch technologies are being used. A variety of operations can be achieved through ERCP procedures, and more functions should be developed in the future.Systematic Review Registration[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022302911].

Abstract Background To explore the relevant factors for early liver transplantation (LT) after Kasai portoenterostomy (KP). Methods Retrospective analysis was performed for 200 children with biliary atresia, who underwent LT with hepatic failure after KP. According to the interval between KP and LT, they were divided into three groups: G1 (≤6-month), G2 (6-month~ 2-year) and G3 (> 2-year). Gender, age of Kasai portoenterostomy, jaundice-clearance, cholangitis after KP and liver function indexes before LT were compared among the three groups. Results The proportion of patients with age of KP (≤90-day) in G1 was lower than that in G3 (P = 0.003). Jaundice-clearance occurred in 6 (7.6%), 26(28.6%) and 26 (86.7%) patients after KP in G1, G2 and G3 respectively (P 90-day was lower than that of children at operation age ≤ 90-day (P = 0.002). The NLS rate of the children with jaundice-clearance after KP was significantly better than that of the children without jaundice-clearance (P 90-day), jaundice-unclear and early cholangitis could reduce the NLS time after KP, which were related to early liver transplantation. Jaundice-unclear was a risk factor for early liver transplantation.

Vulnerable atherosclerotic plaques of the artery wall that pose a significant risk of cardio-cerebral vascular accidents remain the global leading cause of morbidity and mortality. Thus, early delineation of vulnerable atherosclerotic plaques is of clinical importance for prevention and treatment. The currently available imaging technologies mainly focus on the structural assessment of the vascular wall. Unfortunately, several disadvantages in these strategies limit the improvement in imaging effect. Nanoparticle technology is a novel diagnostic strategy for targeting and imaging pathological biomarkers. New functionalized nanoparticles that detect hallmarks of vulnerable plaques are promising for advance further control of this critical illness. The review aims to address the current opportunities and challenges for the use of nanoparticle technology in imagining vulnerable plaques.

Abstract Background We retrospectively compared the prognostic value between the AJCC 8th edition anatomic (AS) and prognostic staging (PS) system for triple negative breast cancer (TNBC) in a cohort from two involved institutions and a large population database. Methods Clinicopathological data of TNBCs were identified in two involved institutions (SYSUCC-PWH cohort). Data from SEER database during 2010–2015 was also accessed. We restaged all cases into AS and PS group according to the AJCC 8th staging system. Results A total of 611 and 31,941 TNBCs were identified in two cohorts, with a median follow-up of 53.5 and 27 months respectively. PS upstaged 46.1% of patients in SYSUCC-PWH cohort, and 62.4% in SEER cohort. No significant difference was observed in C index between AS and PS models for disease-specific survival (DSS), progression-free survival (PFS) or overall survival (OS) in either cohort. χ2 statistic and Hazard Ratio for PFS, DSS and OS showed better discrimination between IA and IB, IIB and IIIA, IIIA and IIIB in AS model than PS model. Besides, patients with IIIC unchanged stage showed worse PFS compared to those with AS IIIA or IIIB upstaged to PS IIIC in both cohorts(p = 0.049, p

The nonanesthetic noble gas helium (He) can protect many organs against ischemia and reperfusion injury, such as liver and heart. However, the role of He on cardiac dysfunction during sepsis is not clear. In this study, we established a lipopolysaccharide (LPS)-induced cardiac dysfunction mouse model to examine the influence of He on the impaired cardiac function, and further investigated the possible innate immune mechanisms that may be involved. LPS induced left ventricular dysfunction and cavity enlargement, as indicated by decreased percent ejection fraction, percent fractional shortening, left ventricular anterior wall thickness in systole, and left ventricular posterior wall thickness in systole, while increased left ventricular end-systolic diameter and left ventricular end-systolic volume. He improved the impaired left ventricular function and cavity enlargement in a dose-dependent manner, and it was beneficial at 1.0 mL/100 g. Mechanistically, He inhibited toll-like receptor 4 (TLR4) expression, reduced the phosphorylation of nuclear factor κB (NF-κB), and subsequently alleviated tumor necrosis factor-alpha (TNF-α) and interleukin-18 (IL-18) expression in heart. Therefore, He protects against LPS-induced cardiac dysfunction in mice partially via inhibiting myocardial TLR4-NF-κB-TNF-α/IL-18 signaling.

Purpose: Prostate cancer (PCa) is characterized by high expression of prostate-specific 1membrane antigen (PSMA), a type II transmembrane protein. Prostate-specific membrane antigen positron emission tomography (PSMA PET) has high sensitivity and specificity and can therefore be potentially used to detect PCa. Exploiting the advantages of PSMA PET imaging, in this study, we aim to develop a novel radiopharmaceutical to facilitate biopsy punching of PCa. Methods: We synthesized a high-affinity radiopharmaceutical of PSMA (125I-PSMA-7). We evaluated the properties of 125I-PSMA-7, including the purity, stability, affinity, partition coefficient, and toxicity. (PSMA+) 22Rv1 and (PSMA−) PC3 cell lines were used to evaluate 125I-PSMA-7 in vitro. BALB/c nude mice bearing 22Rv1 and PC3 xenografts were used for biodistribution and imaging. The uptake of the main organs was evaluated in vivo using single photon emission computed tomography (SPECT). Results: 125I-PSMA-7 had a purity of 99.6% and remained stable for seven days and was therefore always safe to use. 125I-PSMA-7 had a Ki of 4.037 × 10−11 and a partition coefficient of −1.80. The results of in vitro cellular experiments showed a high uptake by 22Rv1 cells (ranging from 2.88 ± 0.14 IA%/106 at 5 min to 61.98 ± 3.43 IA%/106 at 24 h, where the internalization was 46.1% at 1 h and 88.06% at 24 h). However, the uptake of PC3 cells was very low (ranging from 0.34 ± 0.08 IA%/106 at 5 min to 1.60 ± 0.15 IA%/106 at 24 h). The tumors’ uptake of 125I-PSMA-7 ranged from 9.02 ± 0.30 ID%/g at 1 h to 4.11 ± 1.04 ID%/g at 7 d and the tumor/muscle ratios and tumor/blood ratios increased over time. In addition, we used γ-counter to measure cpm per milligram of tumor and muscle on days 4 and 7. The background on day 4 is 42 cpm and the tumor is 1739 cpm/mg and the muscle is 45 cpm/mg, and the background on day 7 is 74 cpm and the tumor is 1404cpm/mg and the muscle is 32 cpm/mg. At 1 h post-injection, the high uptake of 125I-PSMA-7 resulted in clear delineation of 22Rv1-derived tumors upon imaging. By comparison, 22Rv1-blocking mice took up less 125I-PSMA-7. Conclusions: These results show that 125I-PSMA-7 is a promising radiotracer that could be used to puncture the prostate. 125I-PSMA-7 could be applied to targeted biopsy, reducing the need for saturated biopsy.

Objective: The etiology of biliary atresia is unclear, but viral infection has been implicated. The aim of the current meta-analysis was to investigate relationships between cytomegalovirus (CMV) and the prognosis of biliary atresia.Methods: PubMed, Embase, the Cochrane Library, the China National Knowledge Infrastructure database, and Wanfang Data electronic databases were searched for eligible studies. Each relevant text was thoroughly reviewed and examined, including related papers in their reference lists.Results: A total of nine studies including 784 patients were included in the analysis. Biliary atresia patients with CMV exhibited significantly lower jaundice clearance (odds ratio: 0.46, p < 0.0001; I2 = 15%, p = 0.31). There were no significant differences in the rates of cholangitis or native liver survival. CMV-pp65-positive biliary atresia patients had a significantly lower rate of jaundice clearance (odds ratio: 5.87, p = 0.003; I2 = 0%, p = 0.71) and a significantly higher rate of cholangitis (odds ratio: 0.21, p = 0.01; I2 = 0%, p = 0.43) than CMV antibody-positive biliary atresia patients.Conclusion: Biliary atresia patients who were also infected with CMV had a poorer prognosis, particularly with respect to jaundice clearance. CMV status may influence the prognosis of biliary atresia. Clinicians should be able to routinely identify the subset of biliary atresia patients who are also CMV-positive, in order to improve native liver survival.

Background Although complete resolution and recovery occurs in most children with an initial attack of acute pancreatitis (AP), a subset of children may progress to recurrent AP (RAP). RAP has serious effects to the individual and the socioeconomic burden. The aim of this project was to identify the independent risk factors for pediatric RAP so as to provide evidence for its prevention, early diagnosis and treatment.Methods A retrospective cohort study of children discharged from Tianjin Children’s Hospital from June 2017 to January 2020 was performed. Demographic and clinical variables, treatment strategies, clinical course and outcomes were collected. Independent risk factors of RAP were identified using the logistic regression model.Results Of the total 96 enrolled children, 30 (31.3%) developed RAP during the follow-up period. The majority (27/30, 90%) of the children with AP developed RAP within 6 months of their first AP attack. The presence of systemic inflammatory response syndrome (SIRS) [odds ratio (OR)=6.652, 95% confidence interval (CI) 1.989 to 22.247], fasting time (OR=1.267, 95% CI 1.104 to 1.583), whether meet all three AP diagnostic criteria (OR=7.438, 95% CI 1.346 to 41.103) and abnormal amylase/lipase value on the seventh day of hospitalization (OR=3.601, 95% CI 0.972 to 13.342) were independent risk factors of RAP in children.Conclusions Most children who developed RAP had progressed within 6 months after their first episode of AP. RAP was more common in children who met all three AP diagnostic criteria at initial attack and in children with SIRS, long fasting time and abnormal amylase/lipase value on the seventh day of hospitalization.

Chitin, the second richest polymer in nature, is composed of the monomer N-acetylglucosamine (GlcNAc), which has numerous functions and is widely applied in the medical, food, and chemical industries. However, due to the highly crystalline configuration and low accessibility in water of the chitin resources, such as shrimp and crab shells, the chitin is difficult utilize, and the traditional chemical method causes serious environment pollution and a waste of resources. In the present study, three genes encoding chitinolytic enzymes, including the N-acetylglucosaminidase from Ostrinia furnacalis (OfHex1), endo-chitinase from Trichoderma viride (TvChi1), and multifunctional chitinase from Chitinolyticbacter meiyuanensis (CmChi1), were expressed in the Pichia pastoris system, and the positive transformants with multiple copies were isolated by the PTVA (post-transformational vector amplification) method, respectively. The three recombinants OfHex1, TvChi1, and CmChi1 were induced by methanol and purified by the chitin affinity adsorption method. The purified recombinants OfHex1 and TvChi1 were characterized, and they were further used together for degrading chitin from shrimp and crab shells to produce GlcNAc through liquid-assisted grinding (LAG) under a water-less condition. The substrate chitin concentration reached up to 300 g/L, and the highest yield of the product GlcNAc reached up to 61.3 g/L using the mechano-enzymatic method. A yield rate of up to 102.2 g GlcNAc per 1 g enzyme was obtained.

The selfishness and randomness of users in the mobile crowd sensing network could cause them unwilling to participate in sensing activities and lead to lower completion rates of sensing tasks. In order to deal with these problems, this paper proposes a novel incentive mechanism based on a new auction model for mobile crowd sensing, which consists of two consecutive stages. In the first stage, a novel Incentive Method based on Reverse Auction for Location-aware sensing (IMRAL) is proposed to maximize user utility. By introducing a task-centric method to determine the winning bids, it can provide higher user utility and higher task coverage ratio. To ensure the truthfulness of IMRAL, we design a unique payment determination algorithm based on critical payment for the incentive platform. In the second stage, we propose a user-interaction incentive model (UIBIM) to cover the situation that a user may drop out of the sensing activity. This new incentive model includes a dynamic double auction framework prompting users' interaction and a user matching algorithm based on a bipartite graph. The proposed new mechanism achieves the goal of improving task completion rates without increasing the cost of the incentive platform. The simulation results show that comparing with other solutions, such as a truthful auction for location-aware collaborative sensing in mobile crowdsourcing and incentive mechanism for crowdsourcing in the single-requester single-bid-model, IMRAL can achieve better performance in terms of average user utility and tasks coverage ratio, and the UIBIM can significantly improve task completion rates.