Targeting necroptosis: a promising avenue for respiratory disease treatment.

Respiratory diseases are a growing concern in public health because of their potential to endanger the global community. Cell death contributes critically to the pathophysiology of respiratory diseases. Recent evidence indicates that necroptosis, a unique form of programmed cell death (PCD), plays a vital role in the molecular mechanisms underlying respiratory diseases, distinguishing it from apoptosis and conventional necrosis. Necroptosis is a type of inflammatory cell death governed by receptor-interacting serine/threonine protein kinase 1 (RIPK1), RIPK3, and mixed-lineage kinase domain-like protein (MLKL), resulting in the release of intracellular contents and inflammatory factors capable of initiating an inflammatory response in adjacent tissues. These necroinflammatory conditions can result in significant organ dysfunction and long-lasting tissue damage within the lungs. Despite evidence linking necroptosis to various respiratory diseases, there are currently no specific alternative treatments that target this mechanism. This review provides a comprehensive overview of the most recent advancements in understanding the significance and mechanisms of necroptosis. Specifically, this review emphasizes the intricate association between necroptosis and respiratory diseases, highlighting the potential use of necroptosis as an innovative therapeutic approach for treating these conditions.

Differentiating lung neuroendocrine neoplasms from tumor-like infection using CT in patients with ectopic ACTH syndrome.

OBJECTIVES: Pulmonary neuroendocrine neoplasms (NENs) are the most frequent cause of ectopic adrenocorticotropic hormone syndrome (EAS); lung infection is common in EAS. An imaging finding of infection in EAS patients can mimic NENs. This retrospective study investigated EAS-associated pulmonary imaging indicators. METHODS: Forty-five pulmonary NENs and 27 tumor-like infections from 59 EAS patients (45 NEN and 14 infection patients) were included. Clinical manifestations, CT features, 18F-FDG, or 68Ga-DOTATATE-PET/CT images and pathological results were collected. RESULTS: High-sensitivity C-reactive protein (p < 0.001) and expectoration occurrence (p = 0.04) were higher, and finger oxygen saturation (p = 0.01) was lower in the infection group than the NENs group. Higher-grade NENs were underrepresented in our cohort. Pulmonary NENs were solitary primary tumors, 80% of which were peripheral tumors. Overlying vessel sign and airway involvement were more frequent in the NENs group (p < 0.001). Multifocal (p = 0.001) and peripheral (p = 0.02) lesions, cavity (p < 0.001), spiculation (p = 0.01), pleural retraction (p < 0.001), connection to pulmonary veins (p = 0.02), and distal atelectasis or inflammatory exudation (p = 0.001) were more frequent in the infection group. The median CT value increment between the non-contrast and arterial phases was significantly higher in NENs lesions (p < 0.001). Receiver operating characteristic curve analysis indicated a moderate predictive ability at 48.3 HU of delta CT value (sensitivity, 95.0%; specificity, 54.1%). CONCLUSION: Chest CT scans are valuable for localizing and characterizing pulmonary lesions in rare EAS, thereby enabling prompt differential diagnosis and treatment. CRITICAL RELEVANCE STATEMENT: Thin-slice CT images are valuable for the localization and identification of pulmonary ectopic adrenocorticotropic hormone syndrome lesions, leading to prompt differential diagnosis and effective treatment. KEY POINTS: Lung tumor-like infections can mimic neuroendocrine neoplasms (NENs) in ectopic adrenocorticotropic hormone syndrome (EAS) patients. NENs are solitary lesions, whereas infections are multiple peripheral pseudotumors each with identifying imaging findings. Typical CT signs aid in localization and creating an appropriate differential diagnosis.

Neoadjuvant BRAF and MEK inhibitor therapy elicits pathological complete response in stage IIIA non-small cell lung cancer harboring BRAF V600E mutation: A case report.

In recent years, significant improvement has been made in the management of non-small cell lung cancer (NSCLC), primarily driven by advances in targeted therapy and immunotherapy. Research on neoadjuvant targeted therapy has also experienced considerable development, primarily directed towards NSCLC harboring epidermal growth factor receptor or anaplastic lymphoma kinase mutations. Nevertheless, there remains a dearth of studies investigating neoadjuvant targeted therapy in the context of BRAF (V-Raf murine sarcoma viral oncogene homolog B) V600E mutant NSCLC. Herein, we describe the clinical trajectory of a stage IIIA NSCLC patient who underwent a two-month course of neoadjuvant targeted therapy comprising BRAF and MEK (mitogen-activated extracellular signal-regulated kinase) inhibitors prior to surgical intervention, and subsequent postoperative evaluation unveiled a pathological complete response. The case reported here indicates the efficacy and safety of combining BRAF and MEK inhibitors as neoadjuvant targeted therapy in BRAF V600E-mutant NSCLC and suggests the potential viability of such a therapeutic modality in improving treatment outcomes in this subset of NSCLC.

[Exploring the mechanism of IgA vasculitis pathogenesis through the interaction of thrombin and inflammatory factors using urinary proteomics]. / è¿ç”¨å°¿è›‹ç™½ç»„å­¦æŠ€æœ¯æŽ¢ç´¢å‡è¡€é ¶ä¸Žç‚Žç—‡å› å­ç›¸äº’ä½œç”¨å‚ä¸ŽIgAè¡€ç®¡ç‚Žå‘ç— çš„æœºåˆ¶.

OBJECTIVES: To explore the evidence, urinary biomarkers, and partial mechanisms of hypercoagulability in the pathogenesis of IgA vasculitis (IgAV). METHODS: Differential expression of proteins in the urine of 10 healthy children and 10 children with IgAV was screened using high-performance liquid chromatography-tandem mass spectrometry, followed by Reactome pathway analysis. Protein-protein interaction (PPI) network analysis was conducted using STRING and Cytoscape software. In the validation cohort, 15 healthy children and 25 children with IgAV were included, and the expression levels of differential urinary proteins were verified using enzyme-linked immunosorbent assay. RESULTS: A total of 772 differential proteins were identified between the IgAV group and the control group, with 768 upregulated and 4 downregulated. Reactome pathway enrichment results showed that neutrophil degranulation, platelet activation, and hemostasis pathways were involved in the pathogenesis of IgAV. Among the differential proteins, macrophage migration inhibitory factor (MIF) played a significant role in neutrophil degranulation and hemostasis, while thrombin was a key protein in platelet activation and hemostasis pathways. PPI analysis indicated that thrombin directly interacted with several proteins involved in inflammatory responses, and these interactions involved MIF. Validation results showed that compared to healthy children, children with IgAV had significantly higher urine thrombin/creatinine and urine MIF/creatinine levels (P<0.05). CONCLUSIONS: Thrombin contributes to the pathogenesis of IgAV through interactions with inflammatory factors. Urinary thrombin and MIF can serve as biomarkers reflecting the hypercoagulable and inflammatory states in children with IgAV.

Role of mitophagy in pulmonary hypertension: Targeting the mechanism and pharmacological intervention.

Mitophagy, a crucial pathway in eukaryotic cells, selectively eliminates dysfunctional mitochondria, thereby maintaining cellular homeostasis via mitochondrial quality control. Pulmonary hypertension (PH) refers to a pathological condition where pulmonary arterial pressure is abnormally elevated due to various reasons, and the underlying pathogenesis remains elusive. This article examines the molecular mechanisms underlying mitophagy, emphasizing its role in PH and the progress in elucidating related molecular signaling pathways. Additionally, it highlights current drug regulatory pathways, aiming to provide novel insights into the prevention and treatment of pulmonary hypertension.

[Intraspinal Metastasis of Thymic Carcinoma:Report of One Case].

Intraspinal metastasis from malignant carcinomas in other body parts is rarely reported.Intraspinal metastases are often epidural,with primary tumors mostly from the lung and prostate.The extramedullary subdural metastasis of thymic carcinoma is particularly rare and prone to misdiagnosis due to overlapping imaging features with primary intraspinal tumors.This article reports one case of intraspinal metastasis of thymic carcinoma,with the main diagnostic clues including a history of thymic carcinoma,fast growth rate,and irregular shape.

A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.

PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose reduction three dimensional]) algorithms on the conventional enhanced and CE-boost (contrast-enhancement-boost) images of indirect computed tomography venography (CTV) of lower extremities. MATERIALS AND METHODS: In this retrospective study, seventy patients who underwent CTV from June 2021 to October 2022 to assess deep vein thrombosis and varicose veins were included. Unenhanced and enhanced images were reconstructed for AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images were obtained using subtraction software. Objective and subjective image qualities were assessed, and radiation doses were recorded. RESULTS: The CT values of the inferior vena cava (IVC), femoral vein ( FV), and popliteal vein (PV) in the CE-boost images were approximately 1.3 (1.31-1.36) times higher than in those of the enhanced images. There were no significant differences in mean CT values of IVC, FV, and PV between AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images. Noise in AiCE, AiCE-boost images was significantly lower than in AIDR 3D and AIDR 3D-boost images ( P < 0.05). The SNR (signal-to-noise ratio), CNR (contrast-to-noise ratio), and subjective scores of AiCE-boost images were the highest among 4 groups, surpassing AiCE, AIDR 3D, and AIDR 3D-boost images (all P < 0.05). CONCLUSION: In indirect CTV of the lower extremities images, DLR with the CE-boost technique could decrease the image noise and improve the CT values, SNR, CNR, and subjective image scores. AiCE-boost images received the highest subjective image quality score and were more readily accepted by radiologists.

New evidence for a role of DANCR in cancers: a comprehensive review.

Cancer remains a leading cause of mortality and poses a substantial threat to public health. Studies have revealed that Long noncoding RNA DANCR is a cytoplasmic lncRNA whose aberrant expression plays a pivotal role in various cancer types. Within tumour biology, DANCR exerts regulatory control over crucial processes such as proliferation, invasion, metastasis, angiogenesis, inflammatory responses, cellular energy metabolism reprogramming, and apoptosis. By acting as a competitive endogenous RNA for miRNAs and by interacting with proteins and mRNAs at the molecular level, DANCR contributes significantly to cancer progression. Elevated DANCR levels have also been linked to heightened resistance to anticancer drugs. Moreover, the detection of circulating DANCR holds promise as a valuable biomarker for aiding in the clinical differentiation of different cancer types. This article offers a comprehensive review and elucidation of the primary functions and molecular mechanisms through which DANCR influences tumours.

Canagliflozin alleviates pulmonary hypertension by activating PPARγ and inhibiting its S225 phosphorylation.

Pulmonary hypertension (PH) is a progressive fatal disease with no cure. Canagliflozin (CANA), a novel medication for diabetes, has been found to have remarkable cardiovascular benefits. However, few studies have addressed the effect and pharmacological mechanism of CANA in the treatment of PH. Therefore, our study aimed to investigate the effect and pharmacological mechanism of CANA in treating PH. First, CANA suppressed increased pulmonary artery pressure, right ventricular hypertrophy, and vascular remodeling in both mouse and rat PH models. Network pharmacology, transcriptomics, and biological results suggested that CANA could ameliorate PH by suppressing excessive oxidative stress and pulmonary artery smooth muscle cell proliferation partially through the activation of PPARγ. Further studies demonstrated that CANA inhibited phosphorylation of PPARγ at Ser225 (a novel serine phosphorylation site in PPARγ), thereby promoting the nuclear translocation of PPARγ and increasing its ability to resist oxidative stress and proliferation. Taken together, our study not only highlighted the potential pharmacological effect of CANA on PH but also revealed that CANA-induced inhibition of PPARγ Ser225 phosphorylation increases its capacity to counteract oxidative stress and inhibits proliferation. These findings may stimulate further research and encourage future clinical trials exploring the therapeutic potential of CANA in PH treatment.

Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.

Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcinoma at CT informs clinical management decisions but may be challenging for classifying pure ground-glass nodules (pGGNs). Deep learning (DL) may improve ternary classification. Purpose To determine whether a strategy that includes an adjudication approach can enhance the performance of DL ternary classification models in predicting the invasiveness of adenocarcinoma at chest CT and maintain performance in classifying pGGNs. Materials and Methods In this retrospective study, six ternary models for classifying preinvasive, minimally invasive, and invasive adenocarcinoma were developed using a multicenter data set of lung nodules. The DL-based models were progressively modified through framework optimization, joint learning, and an adjudication strategy (simulating a multireader approach to resolving discordant nodule classifications), integrating two binary classification models with a ternary classification model to resolve discordant classifications sequentially. The six ternary models were then tested on an external data set of pGGNs imaged between December 2019 and January 2021. Diagnostic performance including accuracy, specificity, and sensitivity was assessed. The χ2 test was used to compare model performance in different subgroups stratified by clinical confounders. Results A total of 4929 nodules from 4483 patients (mean age, 50.1 years ± 9.5 [SD]; 2806 female) were divided into training (n = 3384), validation (n = 579), and internal (n = 966) test sets. A total of 361 pGGNs from 281 patients (mean age, 55.2 years ± 11.1 [SD]; 186 female) formed the external test set. The proposed strategy improved DL model performance in external testing (P < .001). For classifying minimally invasive adenocarcinoma, the accuracy was 85% and 79%, sensitivity was 75% and 63%, and specificity was 89% and 85% for the model with adjudication (model 6) and the model without (model 3), respectively. Model 6 showed a relatively narrow range (maximum minus minimum) across diagnostic indexes (accuracy, 1.7%; sensitivity, 7.3%; specificity, 0.9%) compared with the other models (accuracy, 0.6%-10.8%; sensitivity, 14%-39.1%; specificity, 5.5%-17.9%). Conclusion Combining framework optimization, joint learning, and an adjudication approach improved DL classification of adenocarcinoma invasiveness at chest CT. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Sohn and Fields in this issue.

Clonal expansion of shared T cell receptors reveals the existence of immune commonality among different lesions of synchronous multiple primary lung cancer.

The increase in the detection rate of synchronous multiple primary lung cancer (MPLC) has posed remarkable clinical challenges due to the limited understanding of its pathogenesis and molecular features. Here, comprehensive comparisons of genomic and immunologic features between MPLC and solitary lung cancer nodule (SN), as well as different lesions of the same patient, were performed. Compared with SN, MPLC displayed a lower rate of EGFR mutation but higher rates of BRAF, MAP2K1, and MTOR mutation, which function exactly in the upstream and downstream of the same signaling pathway. Considerable heterogeneity in T cell receptor (TCR) repertoire exists among not only different patients but also among different lesions of the same patient. Invasive lesions of MPLC exhibited significantly higher TCR diversity and lower TCR expansion than those of SN. Intriguingly, different lesions of the same patient always shared a certain proportion of TCR clonotypes. Significant clonal expansion could be observed in shared TCR clonotypes, particularly in those existing in all lesions of the same patient. In conclusion, this study provided evidences of the distinctive mutational landscape, activation of oncogenic signaling pathways, and TCR repertoire in MPLC as compared with SN. The significant clonal expansion of shared TCR clonotypes demonstrated the existence of immune commonality among different lesions of the same patient and shed new light on the individually tailored precision therapy for MPLC.

Time-dependent CT score-based model for identifying severe/critical COVID-19 at a fever clinic after the emergence of Omicron variant.

Rationale and objectives: The computed tomography (CT) score has been used to evaluate the severity of COVID-19 during the pandemic; however, most studies have overlooked the impact of infection duration on the CT score. This study aimed to determine the optimal cutoff CT score value for identifying severe/critical COVID-19 during different stages of infection and to construct corresponding predictive models using radiological characteristics and clinical factors. Materials and methods: This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic at a tertiary referral hospital from November 28, 2022, to January 8, 2023. Cohorts were divided into three subcohorts according to the time interval from symptom onset to CT examination at the hospital: early phase (0-3 days), intermediate phase (4-7 days), and late phase (8-14 days). The binary endpoints were mild/moderate and severe/critical infection. The CT scores and qualitative CT features were manually evaluated. A logistic regression analysis was performed on the CT score as determined by a visual assessment to predict severe/critical infection. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. The optimal cutoff value was determined by maximizing the Youden index in each subcohort. A radiology score and integrated models were then constructed by combining the qualitative CT features and clinical features, respectively, using multivariate logistic regression with stepwise elimination. Results: A total of 962 patients (aged, 61.7 ± 19.6 years; 490 men) were included; 179 (18.6%) were classified as severe/critical COVID-19, while 344 (35.8%) had a typical Radiological Society of North America (RSNA) COVID-19 appearance. The AUCs of the CT score models reached 0.91 (95% confidence interval (CI) 0.88-0.94), 0.82 (95% CI 0.76-0.87), and 0.83 (95% CI 0.77-0.89) during the early, intermediate, and late phases, respectively. The best cutoff values of the CT scores during each phase were 1.5, 4.5, and 5.5. The predictive accuracies associated with the time-dependent cutoff values reached 88% (vs.78%), 73% (vs. 63%), and 87% (vs. 57%), which were greater than those associated with universal cutoff value (all P < 0.001). The radiology score models reached AUCs of 0.96 (95% CI 0.94-0.98), 0.90 (95% CI 0.87-0.94), and 0.89 (95% CI 0.84-0.94) during the early, intermediate, and late phases, respectively. The integrated models including demographic and clinical risk factors greatly enhanced the AUC during the intermediate and late phases compared with the values obtained with the radiology score models; however, an improvement in accuracy was not observed. Conclusion: The time interval between symptom onset and CT examination should be tracked to determine the cutoff value for the CT score for identifying severe/critical COVID-19. The radiology score combining qualitative CT features and the CT score complements clinical factors for identifying severe/critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment.

[The mechanism of Xuebijing injection in preventing and treating lung injury induced by cardiopulmonary bypass by regulating the apoptosis of alveolar polymorphonuclear neutrophil].

OBJECTIVE: To investigate the protective effect of Xuebijing injection on acute lung injury (ALI) associated with cardiopulmonary bypass (CPB) by regulating the apoptosis of polymorphonuclear neutrophils (PMN). METHODS: Thirty male Sprague-Dawley (SD) rats were randomly divided into sham operation group (Sham group), CPB model group (CPB group) and Xuebijing pretreatment group (XBJ group) according to the random number table method, with 10 rats in each group. Rats in the CPB group and XBJ group undergoing CPB procedures for 60 minutes. Rats in the Sham group did not undergo CPB. Rats in the XBJ group received intraperitoneal injection of 4 mL/kg Xuebijing injection 2 hours before CPB. Rats in the Sham group and CPB group were injected with an equal amount of normal saline. 4 hours after CPB, arterial blood was collected for blood gas analysis to calculate respiratory index (RI), and lung tissue of rats was collected for determination of lung index (LI) and pulmonary water containing rate. PMN in bronchoalveolar lavage fluid (BALF) were collected and the activity of caspase-3 was detected. The apoptosis rate was detected by flow cytometry. The expressions of microRNA-142-3p (miR-142-3p) and FoxO1 mRNA were detected by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). The protein expression of FoxO1 was detected by Western blotting. In addition, HL-60 cells were divided into control oligonucleotide transfection group, miR-142-3p mimics transfection group, and miR-142-3p inhibitor transfection group. After 48 hours of transfection, the activity of miR-142-3p binding to FoxO1 was detected using dual luciferase reporter genes. RESULTS: Compared with Sham group, RI, LI and pulmonary water containing rate were significantly increased in CPB group. The caspase-3 activity and apoptosis rate of PMN obtained from BALF were significantly decreased, the expression of miR-142-3p was decreased, and the expression of FoxO1 protein was increased. However, compared with CPB group, RI, LI and pulmonary water containing rate were significantly decreased in XBJ group [RI: 0.281±0.066 vs. 0.379±0.071, LI: 4.50±0.26 vs. 5.71±0.42, pulmonary water containing rate: (80.31±32.50)% vs. (84.59±3.41)%, all P < 0.01]. The caspase-3 activity and apoptosis rate of PMN obtained from BALF were significantly increased [caspase-3 activity: 0.350±0.021 vs. 0.210±0.014, apoptosis rate: (15.490±1.382)% vs. (8.700±0.701)%, both P < 0.01], the expression of miR-142-3p was significantly up-regulated (2-ΔΔCt: 2.61±0.17 vs. 0.62±0.05, P < 0.01), and the protein expression of FoxO1 was decreased [FoxO1/GAPDH (relative expression level): 0.81±0.04 vs. 1.22±0.06, P < 0.01]. However, there was no statistically significant difference in FoxO1 mRNA expression among the three groups. The bioinformatics analysis results showed that miR-142-3p can bind to the FoxO1 3'untranslated region (3'UTR). In HL-60 cells, compared with control oligonucleotide transfection group, the transfection of miR-142-3p mimics could reduce the expression of FoxO1 protein [FoxO1/GAPDH (relative expression level): 0.48±0.06 vs. 1.00±0.05, P < 0.01], however, the transfection of miR-142-3p inhibitor increased the expression of FoxO1 protein [FoxO1/GAPDH (relative expression level): 1.37±0.21 vs. 1.00±0.05, P < 0.05]. But, transfection with miR-142-3p mimics or inhibitor had no effect on FoxO1 mRNA expression. The luciferase reporter gene showed that miR-142-3p could bind to the FoxO1 3'UTR to inhibit FoxO1 expression. CONCLUSIONS: Xuebijing injection may promote the apoptosis of pulmonary alveolar PMN through the miR-142-3p/FoxO1 axis, and play a role in the prevention and treatment of CPB-induced ALI.

Value of deep learning reconstruction of chest low-dose CT for image quality improvement and lung parenchyma assessment on lung window.

OBJECTIVES: To explore the performance of low-dose computed tomography (LDCT) with deep learning reconstruction (DLR) for the improvement of image quality and assessment of lung parenchyma. METHODS: Sixty patients underwent chest regular-dose CT (RDCT) followed by LDCT during the same examination. RDCT images were reconstructed with hybrid iterative reconstruction (HIR) and LDCT images were reconstructed with HIR and DLR, both using lung algorithm. Radiation exposure was recorded. Image noise, signal-to-noise ratio, and subjective image quality of normal and abnormal CT features were evaluated and compared using the Kruskal-Wallis test with Bonferroni correction. RESULTS: The effective radiation dose of LDCT was significantly lower than that of RDCT (0.29 ± 0.03 vs 2.05 ± 0.65 mSv, p < 0.001). The mean image noise ± standard deviation was 33.9 ± 4.7, 39.6 ± 4.3, and 31.1 ± 3.2 HU in RDCT, LDCT HIR-Strong, and LDCT DLR-Strong, respectively (p < 0.001). The overall image quality of LDCT DLR-Strong was significantly better than that of LDCT HIR-Strong (p < 0.001) and comparable to that of RDCT (p > 0.05). LDCT DLR-Strong was comparable to RDCT in evaluating solid nodules, increased attenuation, linear opacity, and airway lesions (all p > 0.05). The visualization of subsolid nodules and decreased attenuation was better with DLR than with HIR in LDCT but inferior to RDCT (all p < 0.05). CONCLUSION: LDCT DLR can effectively reduce image noise and improve image quality. LDCT DLR provides good performance for evaluating pulmonary lesions, except for subsolid nodules and decreased lung attenuation, compared to RDCT-HIR. CLINICAL RELEVANCE STATEMENT: The study prospectively evaluated the contribution of DLR applied to chest low-dose CT for image quality improvement and lung parenchyma assessment. DLR can be used to reduce radiation dose and keep image quality for several indications. KEY POINTS: • DLR enables LDCT maintaining image quality even with very low radiation doses. • Chest LDCT with DLR can be used to evaluate lung parenchymal lesions except for subsolid nodules and decreased lung attenuation. • Diagnosis of pulmonary emphysema or subsolid nodules may require higher radiation doses.

Runoff nitrogen losses under confluence and diverging drainage systems in the sloped plot scale: A comparative study.

The drainage system is a key measure for regulating runoff nutrient losses on sloping farmlands. Confluence and diverging drainage systems are two drainage layouts representing natural water network systems and are widely distributed in sloping farmlands; however, the effects of these drainage systems on runoff nutrient losses in the sloped plots remain unclear. This study investigated the effects of different drainage systems on the characteristics of runoff nitrogen (N) losses in sloped plots using laboratory rainfall simulations. Three treatments, including bare slope (without drainage system, CK), confluence drainage system (T1), and diverging drainage system (T2), were used to compare the changes in concentrations and losses of total nitrogen (TN), dissolved nitrogen (DN), and particulate nitrogen (PN), and the DN:TN ratio in runoff under a combination of 1.8 mm min-1 rainfall intensity and three slope gradients (5°, 10°, and 15°). The results showed that the time to runoff was significantly delayed in T2 compared with that in CK and T1 across all slopes (p < 0.05). Accumulated runoff depth was considerably lower in T1 and T2 than in CK across all slopes (p < 0.05). The TN and PN concentrations in T1 were markedly lower than those in T2 on the 10° and 15° slopes (p < 0.05). The DN concentration in T1 was lowest at the 5° slope (p < 0.05). TN loss in T1 was 14.7-33.9% and 17.9-30.3% lower than those in CK and T2 across all slopes, respectively (p < 0.05). The PN loss in T1 was 56.7% and 53.3% lower than that in T2 on the 10° and 15° slopes, respectively (p < 0.05). DN loss in T1 was 39.3-72.5% lower than that in CK for all slopes (p < 0.05). DN:TN in T2 was lower than that in CK and T1 at the 10° and 15° slopes (p < 0.05). Our results confirm the effectiveness of drainage systems in reducing runoff nutrient losses in a sloped plot and demonstrate that the confluence drainage system is better at reducing N losses in runoff than diverging drainage systems.

Microarray Expression Profile of Exosomal circRNAs from High Glucose Stimulated Human Renal Tubular Epithelial Cells.

Introduction: Circular RNA (circRNAs) are a type of non-coding RNA (ncRNAs) with a wealth of functions. Recently, circRNAs have been identified as important regulators of diabetic kidney disease (DKD), owing to their stability and enrichment in exosomes. However, the role of circRNAs in exosomes of tubular epithelial cells in DKD development has not been fully elucidated. Methods: In our study, microarray technology was used to analyze circRNA expression in cell supernatant exosomes isolated from HK-2 cells with or without high glucose (HG) treatment. The small interfering RNAs (siRNA) and plasmid overexpression were used to validate functions of differentially expressed circRNAs. Results: We found that exosome concentration was higher in HG-stimulated HK-2 cells than in controls. A total of 235 circRNAs were significantly increased and 458 circRNAs were significantly decreased in the exosomes of the HG group. In parallel with the microarray data, the qPCR results showed that the expression of circ_0009885, circ_0043753, and circ_0011760 increased, and the expression of circ_0032872, circ_0004716, and circ_0009445 decreased in the HG group. Rescue experiments showed that the effects of high glucose on regulation of CCL2, IL6, fibronetin, n cadherin, e cadherin and epcam expression can be reversed by inhibiting or overexpressing these circRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses indicated that circRNA parental genes are associated with glucose metabolism, lipid metabolism, and inflammatory processes, which are important in DKD development. Further analysis of circRNA/miRNA interactions indicated that 152 differentially expressed circRNAs with fold change (FC) ≥1.5 could be paired with 43 differentially expressed miRNAs, which are associated with diabetes or DKD. Discussion: Our results indicate that exosomal circRNAs may be promising diagnostic and therapeutic biomarkers, and may play a critical role in the progression of DKD.

Mechanism of Rhodiola rosea-Euonymus alatus drug pair against rheumatoid arthritis: Network pharmacology and experimental validation.

PURPOSE: The present study aimed to explore the potential components and mechanisms of Rhodiola rosea-Euonymus alatus drug pair (TY) that ameliorate rheumatoid arthritis (RA). METHODS: The main active components, core targets, and important pathways of TY against RA were predicted by network pharmacology analysis. The binding activity between the main active components and the core targets was verified by the molecular docking technique. Collagen-induced arthritis (CIA) rat model and tumor necrosis factor (TNF)-α-induced fibroblast-like synovial cells in human RA (HFLS-RA) model were established, respectively. The core targets were verified by cell counting kit-8 assay, hematoxylin eosin, enzyme-linked immunosorbent assay, real-time polymerase chain reaction, and Western blot analysis, and the therapeutic effect of TY was evaluated. RESULTS: A total of 18 possible components and 34 core targets were obtained by network pharmacology, among which inflammatory response, phosphatidylinositide 3-kinases (PI3K)-AKT and MAPK pathways were involved in the therapeutic effect of TY on RA. The results of molecular docking showed that kaempferol and quercetin had high binding affinity to interleukin (IL)-1ß, IL-6, matrix metalloproteinase (MMP)9, and TNF-α. In vivo and in vitro experiments showed that TY dose-dependently inhibited the proliferation of HFLS-RA cells induced by TNF-α, and significantly reduced the paw swelling and arthritis scores in CIA rats. At the same time, TY inhibited the production of inflammatory factors in CIA rat serum and TNF-α-induced HFLS-RA cells. It also decreased the expression of PI3K, phospho-protein kinase B, MMP1, MMP3, MMP9, and increased the protein and mRNA levels of tissue inhibitors of MMPs (TIMP)1 in synovial tissue. CONCLUSION: TY can inhibit the PI3K/AKT signaling pathway and regulate the balance between MMPs and TIMP, thus playing a therapeutic role in RA.

[CT-Based Weighted Radiomic Score Predicts Tumor Response to Immunotherapy in Non-Small Cell Lung Cancer].

Objective To develop a CT-based weighted radiomic model that predicts tumor response to programmed death-1(PD-1)/PD-ligand 1(PD-L1)immunotherapy in patients with non-small cell lung cancer.Methods The patients with non-small cell lung cancer treated by PD-1/PD-L1 immune checkpoint inhibitors in the Peking Union Medical College Hospital from June 2015 to February 2022 were retrospectively studied and classified as responders(partial or complete response)and non-responders(stable or progressive disease).Original radiomic features were extracted from multiple intrapulmonary lesions in the contrast-enhanced CT scans of the arterial phase,and then weighted and summed by an attention-based multiple instances learning algorithm.Logistic regression was employed to build a weighted radiomic scoring model and the radiomic score was then calculated.The area under the receiver operating characteristic curve(AUC)was used to compare the weighted radiomic scoring model,PD-L1 model,clinical model,weighted radiomic scoring + PD-L1 model,and comprehensive prediction model.Results A total of 237 patients were included in the study and randomized into a training set(n=165)and a test set(n=72),with the mean ages of(64±9)and(62±8)years,respectively.The AUC of the weighted radiomic scoring model reached 0.85 and 0.80 in the training set and test set,respectively,which was higher than that of the PD-L1-1 model(Z=37.30,P<0.001 and Z=5.69,P=0.017),PD-L1-50 model(Z=38.36,P<0.001 and Z=17.99,P<0.001),and clinical model(Z=11.40,P<0.001 and Z=5.76,P=0.016).The AUC of the weighted scoring model was not different from that of the weighted radiomic scoring + PD-L1 model and the comprehensive prediction model(both P>0.05).Conclusion The weighted radiomic scores based on pre-treatment enhanced CT images can predict tumor responses to immunotherapy in patients with non-small cell lung cancer.

Simulation video: a tool to evaluate communications skills in radiologist residents.

BACKGROUND: Effective communication is a crucial component of radiology resident training, and many different aspects need to be explored when teaching and evaluating communication skills. To ensure that radiology residents' communication skill levels can be measured accurately, a standardized evaluation tool has been introduced. In twenty hospitals in Beijing, simulation videos have been developed as a way to assess the communication skills of radiology residents during their certification exams, to minimize evaluating biases. This study aims to assess the performance of a simulation video model in evaluating communications skills compared to the standard patient model. METHODS: This is a retrospective observational study. The performance of standard patient and simulation video models was evaluated through an eight-year examination of communication skills in radiology residents. From 2014 to 2021, communications skill tests were administered to 1003 radiology residents in 20 hospitals in Beijing. The standardized patient (SP) model was applied in 2014, and simulation videos were used from 2015 to 2021. The difficulty and discrimination radio of the tests were evaluated. The subjective survey for candidates on two models of communication skills evaluation was performed and analyzed. RESULTS: The simulation video model evaluation demonstrated stable difficulty (ranging from 0.92 to 0.98) and discrimination ratio (ranging from 0.37 to 0.49), except for minor exceptions of discrimination in 2019 (0.58) and 2020 (0.20). Furthermore, the Kruskal-Wallis H test revealed no significant differences in average scores between 2016 (93.9 ± 4.6) and 2018 (94.5 ± 4.2), 2016 and 2019 (97.3 ± 3.9), 2017 (97.0 ± 5.6) and 2019, 2017 and 2020 (97.7 ± 4.7), as well as 2019 and 2020 exams (all p ≥ 0.05). In addition, candidates who responded to the survey preferred the simulation video model (with a 77.2% response rate), with 62.7% choosing it over the SP model for communication skills evaluation. CONCLUSION: The simulation video demonstrated a stable and better acceptable construct for assessing radiology residents' communication skills.

Evaluating the spatial and temporal distribution of emerging contaminants in the Pearl River Basin for regulating purposes.

Little information is available on how the types, concentrations, and distribution of chemicals have evolved over the years. The objective of the present study is therefore to review the spatial and temporal distribution profile of emerging contaminants with limited toxicology data in the pearl river basin over the years to build up the emerging contaminants database in this region for risk assessment and regulatory purposes. The result revealed that seven groups of emerging contaminants were abundant in this region, and many emerging contaminants had been detected at much higher concentrations before 2011. Specifically, antibiotics, phenolic compounds, and acidic pharmaceuticals were the most abundant emerging contaminants detected in the aquatic compartment, while phenolic compounds were of the most profound concern in soil. Flame retardants and plastics were the most frequently studied chemicals in organisms. The abundance of the field concentrations and frequencies varied considerably over the years, and currently available data can hardly be used for regulation purposes. It is suggested that watershed management should establish a regular monitoring scheme and comprehensive database to monitor the distribution of emerging contaminants considering the highly condensed population in this region. The priority monitoring list should be formed in consideration of historical abundance, potential toxic effects of emerging contaminants as well as the distribution of heavily polluting industries in the region.