Worldwide research landscape of artificial intelligence in lung disease: A scientometric study.

Purpose: To perform a comprehensive bibliometric analysis of the application of artificial intelligence (AI) in lung disease to understand the current status and emerging trends of this field. Materials and methods: AI-based lung disease research publications were selected from the Web of Science Core Collection. Citespace, VOS viewer and Excel were used to analyze and visualize co-authorship, co-citation, and co-occurrence analysis of authors, keywords, countries/regions, references and institutions in this field. Results: Our study included a total of 5210 papers. The number of publications on AI in lung disease showed explosive growth since 2017. China and the United States lead in publication numbers. The most productive author were Li, Weimin and Qian Wei, with Shanghai Jiaotong University as the most productive institution. Radiology was the most co-cited journal. Lung cancer and COVID-19 emerged as the most studied diseases. Deep learning, convolutional neural network, lung cancer, radiomics will be the focus of future research. Conclusions: AI-based diagnosis and treatment of lung disease has become a research hotspot in recent years, yielding significant results. Future work should focus on establishing multimodal AI models that incorporate clinical, imaging and laboratory information. Enhanced visualization of deep learning, AI-driven differential diagnosis model for lung disease and the creation of international large-scale lung disease databases should also be considered.

CD317+ MSCs expanded with chemically defined media have enhanced immunological anti-inflammatory activities.

BACKGROUND: Although both preclinical and clinical studies have shown the great application potential of MSCs (mesenchymal stem/stromal cells) in treating many kinds of diseases, therapeutic inconsistency resulting from cell heterogeneity is the major stumbling block to their clinical applications. Cell population diversity and batch variation in the cell expansion medium are two major inducers of MSC heterogeneity. METHODS: Cell population diversity was investigated through single-cell RNA sequencing analysis of human MSCs derived from the umbilical cord and expanded with fully chemically defined medium in the current study. Then, the MSC subpopulation with enhanced anti-inflammatory effects was studied in vitro and in vivo. RESULTS: Our data showed that MSCs contain different populations with different functions, including subpopulations with enhanced functions of exosome secretion, extracellular matrix modification and responses to stimuli (regeneration and immune response). Among them, CD317+ MSCs have improved differentiation capabilities and enhanced immune suppression activities. Underlying mechanism studies showed that higher levels of TSG6 confer enhanced anti-inflammatory functions of CD317+ MSCs. CONCLUSIONS: Thus, CD317+ MSCs might be a promising candidate for treating immunological disorder-related diseases.

Longitudinal relations among perceived parental warmth, self-esteem and social behaviours from middle childhood to early adolescence in China: Disentangling between- and within-person associations.

Although several studies have addressed the relations between perceived parental warmth and social behaviours, few have distinguished their between- and within-person effects or explored their within-person mediating mechanisms. This study examined the transactional relations among perceived parental warmth (i.e. maternal warmth and paternal warmth), children's self-esteem and children's positive/negative social behaviours (i.e. prosocial behaviour and delinquent behaviour) along with the mediating role of self-esteem after disentangling between- and within-person effects. A total of 4315 Chinese elementary children (44.9% girls; Mage = 9.93 years, SD = 0.73) completed relevant measures on four occasions employing 6-month intervals. Results of random-intercept cross-lagged panel models showed that (a) perceived parental warmth reciprocally and positively predicted prosocial behaviour and self-esteem; (b) perceived paternal warmth reciprocally and negatively predicted delinquent behaviour; (c) self-esteem reciprocally predicted prosocial and delinquent behaviour; (d) perceived maternal warmth reciprocally and positively predicted prosocial behaviour through self-esteem; (e) perceived parental warmth reciprocally and negatively predicted delinquent behaviour through self-esteem; and (f) perceived maternal and paternal warmth differed in their relations with prosocial and delinquent behaviours through self-esteem. These findings illuminated the complicated longitudinal within-person interactions among perceived parental warmth, self-esteem, and social behaviours, the specific mediating mechanism of self-esteem, and the differing results associated with perceived maternal and paternal warmth, all of which yield significant implications for assessments and early interventions aimed to promote positive social behaviour.

Influence of the Sputtering Temperature on Reflectivity and Electrical Properties of ITO/AgIn/ITO Composite Films for High-Reflectivity Anodes.

In this paper, indium tin oxide/silver indium/indium tin oxide (ITO/AgIn/ITO) composite films were deposited on glass substrates by magnetron sputtering. The effects of the sputtering temperature on the optical and electrical properties of the composite films were systematically investigated. The ITO/AgIn/ITO composite films deposited at sputtering temperatures of 25 °C and 100 °C demonstrated a high reflectivity of 95.3% at 550 nm and a resistivity of about 6.8-7.3 µΩ·cm. As the sputtering temperature increased, the reflectivity decreased and the resistivity increased slightly. The close connection between microstructure and surface morphology and the optical and electrical properties of the composite films was further illustrated by scanning electron microscopy imaging and atomic force microscopy imaging. It is shown that the ITO/AgIn/ITO thin films have a promising application for high-reflectivity anodes.

Quantitative MRI evaluation of articular cartilage in patients with meniscus tear.

Purpose: The aim of this study was to assess quantitatively articular cartilage volume, thickness, and T2 value alterations in meniscus tear patients. Materials and methods: The study included 32 patients with meniscus tears (17 females, 15 males; mean age: 40.16 ± 11.85 years) and 24 healthy controls (12 females; 12 males; mean age: 36 ± 9.14 years). All subjects were examined by 3 T magnetic resonance imaging (MRI) with 3D dual-echo steady-state (DESS) and T2 mapping images. All patients underwent diagnostic arthroscopy and treatment. Cartilage thickness, cartilage volume and T2 values of 21 subregions of knee cartilage were measured using the prototype KneeCaP software (version 2.1; Siemens Healthcare, Erlangen, Germany). Mann-Whitney-U tests were utilized to determine if there were any significant differences among subregional articular cartilage volume, thickness and T2 value between patients with meniscus tear and the control group. Results: The articular cartilage T2 values in all subregions of the femur and tibia in the meniscus tear group were significantly higher (p< 0.05) than in the healthy control group. The cartilage thickness of the femoral condyle medial, femur trochlea, femur condyle lateral central, tibia plateau medial anterior and patella facet medial inferior in the meniscus tear group were slightly higher than in the control group (p< 0.05). In the femur trochlea medial, patella facet medial inferior, tibia plateau lateral posterior and tibia plateau lateral central, there were significant differences in relative cartilage volume percentage between the meniscus tear group and the healthy control group (p< 0.05). Nineteen patients had no cartilage abnormalities (Grade 0) in the meniscus tear group, as confirmed by arthroscopic surgery, and their T2 values in most subregions were significantly higher (p< 0.05) than those of the healthy control group. Conclusion: The difference in articular cartilage indexes between patients with meniscus tears and healthy people without such tears can be detected by using quantitative MRI. Quantitative T2 values enable early and sensitive detection of early cartilage lesions.

Clinical Applicable AI System Based on Deep Learning Algorithm for Differentiation of Pulmonary Infectious Disease.

Objective: To assess the performance of a novel deep learning (DL)-based artificial intelligence (AI) system in classifying computed tomography (CT) scans of pneumonia patients into different groups, as well as to present an effective clinically relevant machine learning (ML) system based on medical image identification and clinical feature interpretation to assist radiologists in triage and diagnosis. Methods: The 3,463 CT images of pneumonia used in this multi-center retrospective study were divided into four categories: bacterial pneumonia (n = 507), fungal pneumonia (n = 126), common viral pneumonia (n = 777), and COVID-19 (n = 2,053). We used DL methods based on images to distinguish pulmonary infections. A machine learning (ML) model for risk interpretation was developed using key imaging (learned from the DL methods) and clinical features. The algorithms were evaluated using the areas under the receiver operating characteristic curves (AUCs). Results: The median AUC of DL models for differentiating pulmonary infection was 99.5% (COVID-19), 98.6% (viral pneumonia), 98.4% (bacterial pneumonia), 99.1% (fungal pneumonia), respectively. By combining chest CT results and clinical symptoms, the ML model performed well, with an AUC of 99.7% for SARS-CoV-2, 99.4% for common virus, 98.9% for bacteria, and 99.6% for fungus. Regarding clinical features interpreting, the model revealed distinctive CT characteristics associated with specific pneumonia: in COVID-19, ground-glass opacity (GGO) [92.5%; odds ratio (OR), 1.76; 95% confidence interval (CI): 1.71-1.86]; larger lesions in the right upper lung (75.0%; OR, 1.12; 95% CI: 1.03-1.25) with viral pneumonia; older age (57.0 years ± 14.2, OR, 1.84; 95% CI: 1.73-1.99) with bacterial pneumonia; and consolidation (95.8%, OR, 1.29; 95% CI: 1.05-1.40) with fungal pneumonia. Conclusion: For classifying common types of pneumonia and assessing the influential factors for triage, our AI system has shown promising results. Our ultimate goal is to assist clinicians in making quick and accurate diagnoses, resulting in the potential for early therapeutic intervention.

Therapeutic effects of CXCR4+ subpopulation of transgene-free induced cardiosphere-derived cells on experimental myocardial infarction.

OBJECTIVES: Myocardial infarction (MI) is the most predominant type of cardiovascular diseases with high mortality and morbidity. Stem cell therapy, especially cardiac progenitor cell therapy, has been proposed as a promising approach for cardiac regeneration and MI treatment. Previously, we have successfully generated cardiac progenitor-like cells, induced cardiosphere (iCS), via somatic reprogramming. However, the genome integration characteristic of virus-based reprogramming approach hampered their therapeutic applications due to the risk of tumour formation. In the current study, we aim to establish a safer iCS generation strategy with transgene-free approaches. MATERIALS AND METHODS: Four transgene-free approaches for somatic reprogramming, including episome, minicircle, self-replicative RNA, and sendai virus, were compared, from the perspective of cardiac progenitor marker expression, iCS formation, and cardiac differentiation. The therapeutic effects were assessed in the mouse model of MI, from the perspective of survival rate, cardiac function, and structural alterations. RESULTS: The self-replicative RNA approach produced more iCS, which had cardiomyocyte differentiation ability and therapeutic effects on the mouse model of MI with comparable levels with endogenous cardiospheres and iCS generated with retrovirus. In addition, the CXCR4 (C-X-C chemokine receptor 4) positive subpopulation of iCS derived cells (iCSDC) delivered by intravenous injection was found to have similar therapeutic effects with intramyocardial injection on the mouse model of MI, representing a safer delivery approach. CONCLUSION: Thus, the optimized strategy for iCS generation is safer and has more therapeutic potentials.

CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study.

BACKGROUND: The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system. METHODS: A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients were divided into the mild type (136 cases) and the severe type (28 cases) according to their clinical manifestations. The total CT severity score and quantitative CT features were calculated by AI pneumonia detection and evaluation system with correction by radiologists. The clinical and CT imaging features of different types were analyzed. RESULTS: It was observed that patients in the severe type group were older than the mild type group. Round lesions, Fan-shaped lesions, crazy-paving pattern, fibrosis, "white lung", pleural thickening, pleural indentation, mediastinal lymphadenectasis were more common in the CT images of severe patients than in the mild ones. A higher total lung severity score and scores of each lobe were observed in the severe group, with higher scores in bilateral lower lobes of both groups. Further analysis showed that the volume and number of pneumonia lesions and consolidation lesions in overall lung were higher in the severe group, and showed a wider distribution in the lower lobes of bilateral lung in both groups. CONCLUSIONS: Chest CT of patients with severe COVID-19 pneumonia showed more consolidative and progressive lesions. With the assistance of AI, CT could evaluate the clinical severity of COVID-19 pneumonia more precisely and help the early diagnosis and surveillance of the patients.

Contrast-enhanced CT radiomics for predicting lymph node metastasis in pancreatic ductal adenocarcinoma: a pilot study.

BACKGROUND: We developed a computational model integrating clinical data and imaging features extracted from contrast-enhanced computed tomography (CECT) images, to predict lymph node (LN) metastasis in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: This retrospective study included 159 patients with PDAC (118 in the primary cohort and 41 in the validation cohort) who underwent preoperative contrast-enhanced computed tomography examination between 2012 and 2015. All patients underwent surgery and lymph node status was determined. A total of 2041 radiomics features were extracted from venous phase images in the primary cohort, and optimal features were extracted to construct a radiomics signature. A combined prediction model was built by incorporating the radiomics signature and clinical characteristics selected by using multivariable logistic regression. Clinical prediction models were generated and used to evaluate both cohorts. RESULTS: Fifteen features were selected for constructing the radiomics signature based on the primary cohort. The combined prediction model for identifying preoperative lymph node metastasis reached a better discrimination power than the clinical prediction model, with an area under the curve of 0.944 vs. 0.666 in the primary cohort, and 0.912 vs. 0.713 in the validation cohort. CONCLUSIONS: This pilot study demonstrated that a noninvasive radiomics signature extracted from contrast-enhanced computed tomography imaging can be conveniently used for preoperative prediction of lymph node metastasis in patients with PDAC.

ADAR1 attenuates allogeneic graft rejection by suppressing miR-21 biogenesis in macrophages and promoting M2 polarization.

ADAR1 (adenosine deaminase acting on double-stranded RNA 1) is an RNA-editing enzyme that mediates adenosine-to-inosine RNA editing events, an important post-transcriptional modification mechanism that can alter the coding properties of mRNA or regulate microRNA biogenesis. ADAR1 also regulates the innate immune response. Here, we have demonstrated that ADAR1 expression increased in LPS-stimulated macrophages. Silencing ADAR1 by using small interfering RNA in macrophages resulted in the pronounced polarization of macrophages to M1, whereas ADAR1 overexpression promoted M2 polarization, which indicated that ADAR1 can inhibit macrophage hyperpolarization and prevent immune hyperactivity. The RNA-RNP immunoprecipitation binding assay demonstrated a direct interaction between ADAR1 and miR-21 precursor. Significant up-regulation in IL-10 and down-regulation in miR-21 were observed in ADAR1-overexpressing macrophages. We evaluated miR-21 target mRNAs and macrophage polarization signaling pathways and found that forkhead box protein O1 (Foxo1) was up-regulated in cells that overexpressed ADAR1. In a mouse allogeneic skin transplantation model, grafts in the ADAR1-overexpressed group survived longer and suffered less immune cell infiltration. In ADAR1-overexpressed recipients, splenic macrophages were significantly polarized to M2, and levels of sera IL-10 were markedly higher than those in the control group. In summary, ADAR1 modulates macrophage M2 polarization via the ADAR1-miR-21-Foxo1-IL-10 axis, thereby suppressing allogeneic graft rejection.-Li, J., Xie, J., Liu, S., Li, X., Zhang, D., Wang, X., Jiang, J., Hu, W., Zhang, Y., Jin, B., Zhuang, R., Yin, W. ADAR1 attenuates allogeneic graft rejection by suppressing miR-21 biogenesis in macrophages and promoting M2 polarization.

ADAR1 prevents small intestinal injury from inflammation in a murine model of sepsis.

Adenosine deaminase acting on RNA 1 (ADAR1), a double-stranded RNA-editing enzyme that converts adenosine (A) to inosine (I), has been identified as a modulator of immune responses. However, the role of ADAR1 in small intestinal homeostasis during sepsis remains unclear. In this study, we examined the role of ADAR1 on intestinal inflammation in a murine model of sepsis. We found that ADAR1 was highly expressed in "septic" macrophages and small intestinal tissue of septic mice. Deletion of ADAR1 in "septic" macrophages led to rapid apoptosis. In addition, suppression of ADAR1 in "septic" macrophages significantly enhanced inflammation, while over-expression of ADAR1 significantly suppressed the level of inflammatory cytokines. Furthermore, suppression of ADAR1 in septic mice significantly enhanced inflammation and intestinal damage, while enhanced ADAR1 expression resulted in reduced damage and inflammation. Finally, over-expression of ADAR1 improved survival of septic mice. In conclusion, we have identified a novel ADAR1 protective effect for maintaining intestinal homeostasis. Our findings may provide a new targeted therapy for sepsis treatment.

Whole genome expression profiling and screening for differentially expressed cytokine genes in human bone marrow endothelial cells treated with humoral inhibitors in liver cirrhosis.

Bone marrow endothelial cells (BMECs) are important components of the hematopoietic microenvironment in bone marrow, and they can secrete several types of cytokines to regulate the functions of hematopoietic stem/progenitor cells. To date, it is unknown whether BMECs undergo functional changes and lead to hematopoietic abnormalities in cases of liver cirrhosis (LC). In the present study, whole genome microarray analysis was carried out to detect differentially expressed genes in human BMECs treated for 48 h with medium supplemented with 20% pooled sera from 26 patients with LC or 10 healthy volunteers as the control group. A total of 1,106 upregulated genes and 766 downregulated genes were identified. In Gene Ontology analysis, the most significant categories of genes were revealed. A large number of the upregulated genes were involved in processes, such as cell-cell adhesion, apoptosis and cellular response to stimuli and the downregulated genes were involved in the negative regulation of secretion, angiogenesis, blood vessel development and cell growth. Pathway analysis revealed that the upregulated genes were either cell adhesion molecules or parts of the apoptotic signaling pathway and the downregulated genes were involved in the Wnt signaling pathway and MAPK signaling pathway. These were the pathways with the highest enrichment scores. The results of apoptosis assays revealed that the humoral inhibitors in the sera of patients with LC induced the apoptosis of BMECs, which confirmed the accuracy of bioinformatic analysis. Moreover, we screened and verified 21 differentially expressed cytokine genes [transforming growth factor (TGF)B1, tumor necrosis factor (TNF)B, TNF receptor superfamily, member 11b (TNFRSF11B), TNF (ligand) superfamily, member 13b (TNFSF13B), interleukin (IL)1A, IL6, IL11, IL17C, IL24, family with sequence similarity 3, member B (FAM3B), Fas ligand (FASLG), matrix metallopeptidase (MMP)3, MMP15, vitronectin (VTN), insulin-like growth factor 1 (IGF1), fibroblast growth factor 22 (FGF22), slit homolog 2 (Drosophila) (SLIT2), thrombospondin (THBS)2, THBS3, chemokine (C-C motif) ligand 28 (CCL28) and macrophage stimulating 1 (MST1)] from 97 cytokine genes in BMECs treated with serum from patients with LC. The results from our study demonstrate that the humoral inhibitors in the sera of patients with LC induce the dysfunction and abnormal cytokine secretion by BMECs, which may be a novel mechanism responsible for hematological abnormalities in patients with LC.