Tannic acid-poloxamer self-assembled nanoparticles for advanced atherosclerosis therapy by regulation of macrophage polarization.

Atherosclerosis (AS) is a significant contributor to cardiovascular events. Advanced AS is particularly concerning, as it leads to the formation of high-risk vulnerable plaques. Current treatments for AS focus on antithrombotic and lipid-lowering interventions, which are effective in treating early-stage AS. Recent studies have shown that macrophage polarization plays a crucial role in the development of AS. This study presents a new biomedical application of natural tannic acid as an anti-inflammatory nanoplatform for advanced AS. Tannic acid-poloxamer nanoparticles (TPNP) are fabricated through self-assembly of tannic acid (TA) and poloxamer. TPNP has the potential to provide effective treatment for advanced AS. According to in vitro studies, TPNP has been found to suppress the inflammatory response in lipopolysaccharide-stimulated macrophages by scavenging reactive oxygen species (ROS), downregulating the expression levels of inflammatory cytokines (such as interleukin-10 and tumor necrosis factor-α) and regulating polarization of macrophages. In vivo studies further reveal that TPNP can retard the development of advanced atherosclerotic plaques by reducing ROS production and promoting M2 macrophage polarization in the aorta of ApoE-/- mice. Overall, these findings suggest that TPNP could be used to develop natural multifunctional nanoplatforms for molecular therapy of AS and other inflammation-related diseases.

Triplet-branch network with contrastive prior-knowledge embedding for disease grading.

Since different disease grades require different treatments from physicians, i.e., the low-grade patients may recover with follow-up observations whereas the high-grade may need immediate surgery, the accuracy of disease grading is pivotal in clinical practice. In this paper, we propose a Triplet-Branch Network with ContRastive priOr-knoWledge embeddiNg (TBN-CROWN) for the accurate disease grading, which enables physicians to accordingly take appropriate treatments. Specifically, our TBN-CROWN has three branches, which are implemented for representation learning, classifier learning and grade-related prior-knowledge learning, respectively. The former two branches deal with the issue of class-imbalanced training samples, while the latter one embeds the grade-related prior-knowledge via a novel auxiliary module, termed contrastive embedding module. The proposed auxiliary module takes the features embedded by different branches as input, and accordingly constructs positive and negative embeddings for the model to deploy grade-related prior-knowledge via contrastive learning. Extensive experiments on our private and two publicly available disease grading datasets show that our TBN-CROWN can effectively tackle the class-imbalance problem and yield a satisfactory grading accuracy for various diseases, such as fatigue fracture, ulcerative colitis, and diabetic retinopathy.

The value of functional magnetic resonance imaging in evaluating renal allograft function.

BACKGROUND: To explore the value of arterial spin labeled (ASL) and blood oxygen level dependent (BOLD) imaging in evaluating allogeneic kidney function after renal transplantation. METHODS: One hundred and thirty-five renal transplant patients were included. Demographic and imaging data were collected. Transplanted renal function, pathology, ASL and BOLD parameters were obtained. The patients were divided into normal, mild and severe injury group. The correlation between BOLD/ASL parameters and clinical data were evaluated. The prediction models were based on ASL and BOLD parameters using multivariate logistic analysis. Cox proportional hazards regression model was used to analyze the effects of gender, age, ASL and BOLD on the survival of renal transplant patients. RESULTS: ASL and BOLD parameters were independently associated with renal function injury and renal allograft positive pathology. The AUC of prediction model for renal allograft function based on ASL and BOLD parameters was 0.85, while the AUC based on BOLD parameters was 0.70. Renal transplantation time showed a positive correlation with age, BOLD parameters and SCr，while a negative correlation with ASL parameters and eGFR. ASL parameter was positively correlated with eGFR and negatively correlated with Scr. BOLD parameter was negatively correlated with eGFR, ASL and positively correlated with Scr. Cox proportional hazards regression model showed that the increase of age could reduce the risk of renal function injury and positive pathology. CONCLUSIONS: ASL and BOLD were associated with renal function injury and renal allograft positive pathology. ASL and BOLD had some value in predicting renal allograft function.

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology.

INTRODUCTION: Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. OBJECTIVE: To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. METHODS: We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. RESULTS: The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm-1 showed a positive linear correlation with PD-L1 expression level. CONCLUSIONS: This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.

Enhanced anti-glioma efficacy of biodegradable periodic mesoporous organosilica nanoparticles through target delivery of chemotherapeutics.

Glioma is the most common malignant tumor of the brain and enhancing the efficacy of chemotherapy in glioma is critical for improving patients' prognosis. In this study, a glioma-targeting drug delivery system is constructed using biodegradable periodic mesoporous organosilica nanoparticles (PMO) that are modified with lactoferrin (Lf) ligands. The obtained PMO is doped with thioether groups and can be degraded in the high concentration of glutathione in tumor cells. The surface area and pore volume of PMO are 772 cm2/g and 0.98 cm3/g, respectively and the loading capacity of doxorubicin (Dox) is as high as 20%. The results of the confocal laser scanning microscope show that the uptake of PMO-Lf@Dox by C6 cells is higher than PMO@Dox. The quantitative analysis of the flow cytometer further demonstrates that more PMO-Lf@Dox enter C6 cells, indicating that the modification of lactoferrin can significantly increase the uptake of C6 cells. Finally, the therapeutic efficacy results show that Lf-modified PMO enhances the inhibitory effect of Dox on C6 cells when incubated for 24 h and 72 h. In summary, this lactoferrin receptor-mediated PMO drug carrier with biodegradability in glutathione in tumor cells can be used to enhance drug delivery into glioma without long-term accumulation in vivo. In this study, a glioma-targeting drug delivery system is constructed using periodic mesoporous organosilica nanoparticles (PMO) that modified with lactoferrin (Lf) ligands. This lactoferrin receptor-mediated PMO drug carrier can be used to enhance drug delivery into brain glioma.

Burden and distribution of monosodium urate deposition in patients with hyperuricemia and gout: a cross-sectional Chinese population-based dual-energy CT study.

Background: To investigate the distribution and burden of monosodium urate (MSU) deposition in hyperuricemia and gout patients with dual-energy computed tomography (DECT). Methods: A total of 1,936 consecutive patients from January 1, 2009, to September 15, 2017, underwent DECT examinations in Jinling Hospital. Of these, 1,294 patients were excluded due to other clinical diagnoses (n=1,041), inappropriate locations (n=82), poor-quality images (n=105), training cases (n=30) and duplicated data (n=36). Finally, 642 patients were included in this study. We retrospectively analyzed 1,127 DECT examinations in 642 consecutive patients (hyperuricemia group, n=121; gout group, n=521) and recorded the volume and number of MSU deposits. For each anatomical location, we recorded MSU deposition in the soft tissue and joint cavity. MSU deposition was analyzed and compared between groups. For normally distributed data, independent sample t-tests were used for comparison between the two groups. The independent samples nonparametric test was used to analyze nonnormally distributed data. Results: (I) The burden of MSU deposition in the gout group {volume [0.14 (0.04-1.36)] and numbers [10.00 (5.00-19.00)]} was significantly higher than that {volume [0.08 (0.02-0.47), P=0.003] and numbers [9.50 (2.00-16.00), P=0.01]} in the hyperuricemia group. (II) The burden of MSU deposition in the knees {volume [0.24 (0.01-1.79), P=0.002] and quantity [6.00 (2.00-12.00), P=0.04]} and feet {volume [0.10 (0.04-0.66)] and number [9.00 (5.00-15.00)]} was significantly higher in the gout group than those {knees: the volume [0.03 (0.00-0.27), P=0.002] and the quantity [4.00 (0.00-9.00), P=0.04]; feet: the volume [0.07 (0.02-0.19), P=0.003)] and number [8.00 (2.25-12.00), P=0.04]} in the hyperuricemia group, respectively. (III) In the hyperuricemia group, the volume of MSU deposition was significantly higher in the soft tissues of the knee (0.022±0.042) and ankle (0.062±0.305) than in those (knee: 0.001±0.005, P=0.02; ankle: 0.027±0.234, P=0.02) in the joint cavity. Conclusions: Although subclinical urate deposition can occur in patients with asymptomatic hyperuricemia, the burden of urate deposition is greater in patients with symptomatic gout, and the distribution is more pronounced in the foot/knee. Thus, more effective patient management and monitoring can be achieved by measuring the burden of MSU deposits in the patient's feet/knees. These data suggest that a threshold for urate crystal volume at typical sites may be required before symptomatic disease develops.

Coordinatized lesion location analysis empowering ROI-based radiomics diagnosis on brain gliomas.

OBJECTIVES: To assess the value of coordinatized lesion location analysis (CLLA), in empowering ROI-based imaging diagnosis of gliomas by improving accuracy and generalization performances. METHODS: In this retrospective study, pre-operative contrasted T1-weighted and T2-weighted MR images were obtained from patients with gliomas from three centers: Jinling Hospital, Tiantan Hospital, and the Cancer Genome Atlas Program. Based on CLLA and ROI-based radiomic analyses, a fusion location-radiomics model was constructed to predict tumor grades, isocitrate dehydrogenase (IDH) status, and overall survival (OS). An inter-site cross-validation strategy was used for assessing the performances of the fusion model on accuracy and generalization with the value of area under the curve (AUC) and delta accuracy (ACC) (ACCtesting-ACCtraining). Comparisons of diagnostic performances were performed between the fusion model and the other two models constructed with location and radiomics analysis using DeLong's test and Wilcoxon signed ranks test. RESULTS: A total of 679 patients (mean age, 50 years ± 14 [standard deviation]; 388 men) were enrolled. Based on tumor location probabilistic maps, fusion location-radiomics models (averaged AUC values of grade/IDH/OS: 0.756/0.748/0.768) showed the highest accuracy in contrast to radiomics models (0.731/0.686/0.716) and location models (0.706/0.712/0.740). Notably, fusion models ([median Delta ACC: - 0.125, interquartile range: 0.130]) demonstrated improved generalization than that of radiomics model ([- 0.200, 0.195], p = 0.018). CONCLUSIONS: CLLA could empower ROI-based radiomics diagnosis of gliomas by improving the accuracy and generalization of the models. CLINICAL RELEVANCE STATEMENT: This study proposed a coordinatized lesion location analysis for glioma diagnosis, which could improve the performances of the conventional ROI-based radiomics model in accuracy and generalization. KEY POINTS: • Using coordinatized lesion location analysis, we mapped anatomic distribution patterns of gliomas with specific pathological and clinical features and constructed glioma prediction models. • We integrated coordinatized lesion location analysis into ROI-based analysis of radiomics to propose new fusion location-radiomics models. • Fusion location-radiomics models, with the advantages of being less influenced by variabilities, improved accuracy, and generalization performances of ROI-based radiomics models on predicting the diagnosis of gliomas.

Structural basis of human PRPS2 filaments.

BACKGROUND: PRPP synthase (PRPS) transfers the pyrophosphate groups from ATP to ribose-5-phosphate to produce 5-phosphate ribose-1-pyrophosphate (PRPP), a key intermediate in the biosynthesis of several metabolites including nucleotides, dinucleotides and some amino acids. There are three PRPS isoforms encoded in human genome. While human PRPS1 (hPRPS1) and human PRPS2 (hPRPS2) are expressed in most tissues, human PRPS3 (hPRPS3) is exclusively expressed in testis. Although hPRPS1 and hPRPS2 share 95% sequence identity, hPRPS2 has been shown to be less sensitive to allosteric inhibition and specifically upregulated in certain cancers in the translational level. Recent studies demonstrate that PRPS can form a subcellular compartment termed the cytoophidium in multiple organisms across prokaryotes and eukaryotes. Forming filaments and cytoophidia is considered as a distinctive mechanism involving the polymerization of the protein. Previously we solved the filament structures of Escherichia coli PRPS (ecPRPS) using cryo-electron microscopy (cryo-EM) 1. RESULTS: Order to investigate the function and molecular mechanism of hPRPS2 polymerization, here we solve the polymer structure of hPRPS2 at 3.08 Å resolution. hPRPS2 hexamers stack into polymers in the conditions with the allosteric/competitive inhibitor ADP. The binding modes of ADP at the canonical allosteric site and at the catalytic active site are clearly determined. A point mutation disrupting the inter-hexamer interaction prevents hPRPS2 polymerization and results in significantly reduced catalytic activity. CONCLUSION: Findings suggest that the regulation of hPRPS2 polymer is distinct from ecPRPS polymer and provide new insights to the regulation of hPRPS2 with structural basis.

Engineered Toll-like Receptor Nanoagonist Binding to Extracellular Matrix Elicits Safe and Robust Antitumor Immunity.

Cancer immunotherapy, such as the Toll-like receptor (TLR) agonist including CpG oligodeoxynucleotide, has shown potency in clinical settings. However, it is still confronted with multiple challenges, which include the limited efficacy and severe adverse events caused by the rapid clearance and systemic diffusion of CpG. Here we report an improved CpG-based immunotherapy approach composed of a synthetic extracellular matrix (ECM)-anchored DNA/peptide hybrid nanoagonist (EaCpG) via (1) a tailor designed DNA template that encodes tetramer CpG and additional short DNA moieties, (2) generation of elongated multimeric CpG through rolling circle amplification (RCA), (3) self-assembly of densely packaged CpG particles composed of tandem CpG building blocks and magnesium pyrophosphate, and (4) incorporation of multiple copies of ECM binding peptide through hybridization to short DNA moieties. The structurally well-defined EaCpG shows dramatically increased intratumoral retention and marginal systemic dissemination through peritumoral administration, leading to potent antitumor immune response and subsequent tumor elimination, with minimal treatment-related toxicity. Combined with conventional standard-of-care therapies, peritumor administration of EaCpG generates systemic immune responses that lead to a curative abscopal effect on distant untreated tumors in multiple cancer models, which is superior to the unmodified CpG. Taken together, EaCpG provides a facile and generalizable strategy to simultaneously potentiate the potency and safety of CpG for combinational cancer immunotherapies.

Distinguishing multiple primary lung cancers from intrapulmonary metastasis using CT-based radiomics.

PURPOSE: To develop CT-based radiomics models that can efficiently distinguish between multiple primary lung cancers (MPLCs) and intrapulmonary metastasis (IPMs). METHOD: This retrospective study included 127 patients with 254 lung tumors pathologically proved as MPLCs or IPMs between May 2009 and January 2020. Radiomics features of lung tumors were extracted from baseline CT scans. Particularly, we incorporated tumor-focused, refined radiomics by calculating relative radiomics differences from paired tumors of individual patients. We applied the L1-norm regularization and analysis of variance to select informative radiomics features for constructing radiomics model (RM) and refined radiomics model (RRM). The performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC). The two radiomics models were compared with the clinical-CT model (CCM, including clinical and CT semantic features). We incorporated both radiomics features to construct fusion model1 (FM1). We also, build fusion model2 (FM2) by combing both radiomics, clinical and CT semantic features. The performance of the FM1 and FM2 were further compared with that of the RRM. RESULTS: On the validation set, the RM achieved an AUC of 0.857. The RRM demonstrated improved performance (validation set AUC, 0.870) than the RM, and showed significant differences compared with the CCM (validation set AUC, 0.782). Fusion models further led prediction performance (validation set AUC, FM1:0.885; FM2:0.889). There were no significant differences among the performance of the FM1, the FM2 and the RRM. CONCLUSIONS: The CT-based radiomics models presented good performance on the discrimination between MPLCs and IPMs, demonstrating the potential for early diagnosis and treatment guidance for MPLCs and IPMs.

Exploration of thoracoabdominal aortic mixed reality optimisation and its clinical application value in type A aortic dissection.

OBJECTIVES: This study aimed to explore the feasibility of low-dose computed tomography (CT)-based mixed reality and its clinical role in type A aortic dissection (TAAD) operations. METHODS: Eighty-seven patients diagnosed with TAAD were prospectively enrolled and underwent thoracoabdominal aorta mixed reality. They were randomly divided into a low-dose mixed reality group, a conventional mixed reality group and a conventional thoracoabdominal aorta computed tomography angiography (CTA) group. Three-dimensional modelling, mixed reality and CT reconstruction technology were selected. The radiation dose and image quality were compared using Student's t test. Doctors with different seniorities evaluated the clinical application value of thoracoabdominal aorta mixed reality using a Likert scale. The consistency was assessed using the Cohen kappa coefficient (k). The Pearson chi-square test was used to test the correlation of perioperative index results in TAAD operations. RESULTS: Low-dose CT technology can be effectively applied to thoracoabdominal aorta mixed reality and reduces the radiation dose by approximately 59% and the operation time and auxiliary cardiopulmonary bypass time by approximately 22% and 29%, respectively. The subjective scores of doctors with different seniorities on the clinical application value of thoracoabdominal aorta mixed reality were higher than those of thoracoabdominal aorta CTA (all p > 0.05). CONCLUSIONS: Low-dose CT can be effectively used in thoracoabdominal aortic mixed reality to reduce the radiation dose while ensuring quality. Low-dose thoracoabdominal aortic mixed reality has clinical application value and can effectively reduce the operation time and auxiliary cardiopulmonary bypass time in TAAD operations. KEY POINTS: • Low-dose CT technology can ensure the mixed reality quality of the thoracoabdominal aorta with a radiation dose reduction of approximately 59%. • Compared with thoracoabdominal aorta CTA, low-dose thoracoabdominal aorta mixed reality can reduce the operation time and auxiliary cardiopulmonary bypass time by approximately 20% and 29%, respectively, in TAAD operations. • The application value of low-dose thoracoabdominal aorta mixed reality in operation scheme formulation, operation risk assessment, operation navigation and diagnosis and treatment under safe distance was greater than that of thoracoabdominal aorta CTA in TAAD.

A mini review on selenium quantum dots: synthesis and biomedical applications.

In recent years, the demand for advanced biomedical nanomaterials has seen a noticeable surge. Among the essential trace elements in the human body, selenium has gained recognition for its anti-cancer, antioxidant, and immune regulatory properties. However, traditional selenium-based semiconductor quantum dots (QDs) are often comprised of heavy metal elements that tend to be toxic, thereby limiting their usage in biomedical applications. Fortunately, the advent of elemental selenium quantum dots (SeQDs), a new kind of fluorescent nanomaterial with unique physicochemical properties, has provided a solution to this problem. These SeQDs are known for their low toxicity and good biocompatibility, making them a promising candidate for biomedical applications. In this mini-review, we delve into the synthesis methods of fluorescent SeQDs and the latest progress in their applications in bioimaging, biosensing, and diagnosis treatment. Finally, we identify the major challenges and future prospects in the field of SeQDs.

Qualitative (and Quantitative) Values of the Lung-RADS and Computed Tomography in Diagnosing Solitary Pulmonary Nodules.

Background: Lung-RADS classification and CT signs can both help in the differential diagnosis of SPNs. The purpose of this study was to investigate the diagnostic value of these two methods and the combination of the two methods for solitary pulmonary nodules (SPNs). Methods: A total of 296 cases of SPNs were retrospectively analyzed. All the SPNs were classified according to the Lung-RADS grading version 1.1. The scores of each lesion were calculated according to their CT signs. Imaging features, such as the size and margin of the lesions, pleural traction, spiculation, lobulation, bronchial cutoff, air bronchogram, vacuoles, tumor vasculature, and cavity signs, were analyzed. The imaging results were compared with the pathology examination findings. Receiver operating characteristic (ROC) curves were applied to compare the values of the different methods in differentially diagnosing benign and malignant SPNs. Results: The sensitivity, specificity, and accuracy of Lung-RADS grading for diagnosing SPNs were 34.0%, 94.4%, and 47.6%, respectively. The area under the ROC curve (AUC) was 0.600 (p < 0.001). The sensitivity, specificity, and accuracy of the CT sign scores were 56.3%, 70.0%, and 60.5%, respectively, and the AUC was 0.657 (p < 0.001). The sensitivity, specificity, and accuracy of the combination of the two methods for diagnosing SPNs were 93.2%, 61.1%, and 83.5%, and the AUC was 0.777 (p < 0.001). Conclusion: The combination of Lung-RADS classification and CT signs significantly improved the differential diagnosis of SPNs.

Combined 18F-FDG and 18F-Alfatide II PET May Predict Luminal B (HER2 Negative) Subtype and Nonluminal Subtype of Invasive Breast Cancer.

Noninvasive PET molecular imaging using radiopharmaceuticals is important to classify breast cancer in the clinic. The aim of this study was to investigate the combination of 18F-FDG and 18F-Alfatide II for predicting molecular subtypes of invasive breast cancer. Forty-four female patients with clinically suspected breast cancer were recruited and underwent 18F-FDG and 18F-Alfatide II PET/CT within a week. Tracer uptake in breast lesions was assessed using the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), and SUVmax ratio of 18F-FDG to 18F-Alfatide II (FAR). Invasive breast cancer lesions were further classified as luminal A subtype, luminal B subtype, human epidermal growth factor receptor-2 (HER2) overexpressing subtype, and triple negative subtype according to the expression of the estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67. Among 44 patients, 35 patients were pathologically diagnosed with invasive breast cancer. The SUVmax and SUVmean of 18F-FDG were significantly higher in the ER-negative group than those in the ER-positive group, as well as in the PR-negative group than those in the PR-positive group. However, the SUVmax and SUVmean of 18F-Alfatide II were higher in the ER-positive group and the PR-positive group. By combining 18F-FDG and 18F-Alfatide II, the FAR was lower in the ER-positive group and the PR-positive group. The HER2 overexpressing subtype showed the highest SUVmax and SUVmean for 18F-FDG while the luminal B (HER2 negative) subtype revealed the lowest values. The luminal B (HER2 negative) subtype showed the highest 18F-Alfatide II SUVmax, while the triple negative subtype showed the lowest 18F-Alfatide II SUVmax. The FAR was the lowest in the luminal B (HER2 negative) subtype and much higher in the HER2 overexpressing and triple negative subtypes. FAR less than 1 predicted the luminal B (HER2 negative) subtype with high specificity (93.1%) and NPV (90%). FAR greater than 3 predicted the HER2 overexpressing subtype and triple negative subtype (namely, the nonluminal subtype) with very high specificity (100%) and PPV (100%). In summary, FAR, the combined PET parameter of 18F-FDG and 18F-Alfatide II, can be used to predict molecular subtypes of invasive breast cancer, especially for the luminal B (HER2 negative) subtype and the nonluminal subtype.

Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer.

Objective: To develop and validate a DeepSurv nomogram based on radiomic features extracted from computed tomography images and clinicopathological factors, to predict the overall survival and guide individualized adjuvant chemotherapy in patients with non-small cell lung cancer (NSCLC). Patients and Methods: This retrospective study involved 976 consecutive patients with NSCLC (training cohort, n=683; validation cohort, n=293). DeepSurv was constructed based on 1,227 radiomic features, and the risk score was calculated for each patient as the output. A clinical multivariate Cox regression model was built with clinicopathological factors to determine the independent risk factors. Finally, a DeepSurv nomogram was constructed by integrating the risk score and independent clinicopathological factors. The discrimination capability, calibration, and clinical usefulness of the nomogram performance were assessed using concordance index evaluation, the Greenwood-Nam-D'Agostino test, and decision curve analysis, respectively. The treatment strategy was analyzed using a Kaplan-Meier curve and log-rank test for the high- and low-risk groups. Results: The DeepSurv nomogram yielded a significantly better concordance index (training cohort, 0.821; validation cohort 0.768) with goodness-of-fit (P<0.05). The risk score, age, thyroid transcription factor-1, Ki-67, and disease stage were the independent risk factors for NSCLC.The Greenwood-Nam-D'Agostino test showed good calibration performance (P=0.39). Both high- and low-risk patients did not benefit from adjuvant chemotherapy, and chemotherapy in low-risk groups may lead to a poorer prognosis. Conclusions: The DeepSurv nomogram, which is based on the risk score and independent risk factors, had good predictive performance for survival outcome. Further, it could be used to guide personalized adjuvant chemotherapy in patients with NSCLC.

RP-Rs-fMRIomics as a Novel Imaging Analysis Strategy to Empower Diagnosis of Brain Gliomas.

Rs-fMRI can provide rich information about functional processes in the brain with a large array of imaging parameters and is also suitable for investigating the biological processes in cerebral gliomas. We aimed to propose an imaging analysis method of RP-Rs-fMRIomics by adopting omics analysis on rs-fMRI with exhaustive regional parameters and subsequently estimating its feasibility on the prediction diagnosis of gliomas. In this retrospective study, preoperative rs-fMRI data were acquired from patients confirmed with diffuse gliomas (n = 176). A total of 420 features were extracted through measuring 14 regional parameters of rs-fMRI as much as available currently in 10 specific narrow frequency bins and three parts of gliomas. With a randomly split training and testing dataset (ratio 7:3), four classifiers were implemented to construct and optimize RP-Rs-fMRIomics models for predicting glioma grade, IDH status and Karnofsky Performance Status scores. The RP-Rs-fMRIomics models (AUROC 0.988, 0.905, 0.801) were superior to the corresponding traditional single rs-fMRI index (AUROC 0.803, 0.731, 0.632) in predicting glioma grade, IDH and survival. The RP-Rs-fMRIomics analysis, featuring high interpretability, was competitive for prediction of glioma grading, IDH genotype and prognosis. The method expanded the clinical application of rs-fMRI and also contributed a new imaging analysis for brain tumor research.

The correlation study on chest CT features and kidney injury in severe COVID-19 pneumonia from a multicenter cohort study.

Background: Among confirmed severe COVID-19 patients, although the serum creatinine level is normal, they also have developed kidney injury. Early detection of kidney injury can guide doctors to choose drugs reasonably. Study found that COVID-19 have some special chest CT features. The study aimed to explore which chest CT features are more likely appear in severe COVID-19 and the relationship between related (special) chest CT features and kidney injury or clinical prognosis. Methods: In this retrospective study, 162 patients of severe COVID-19 from 13 medical centers in China were enrolled and divided into three groups according to the estimated glomerular filtration rate (eGFR) level: Group A (eGFR < 60 ml/min/1.73 m2), Group B (60 ml/min/1.73 m2 ≤ eGFR < 90 ml/min/1.73 m2), and Group C (eGFR ≥ 90 ml/min/1.73 m2). The demographics, clinical features, auxiliary examination, and clinical prognosis were collected and compared. The chest CT features and eGFR were assessed using univariate and multivariate Cox regression. The influence of chest CT features on eGFR and clinical prognosis were calculated using the Cox proportional hazards regression model. Results: Demographic and clinical features showed significant differences in age, hypertension, and fatigue among the Group A, Group B, and Group C (all P < 0.05). Auxiliary examination results revealed that leukocyte count, platelet count, C-reactive protein, aspartate aminotransferase, creatine kinase, respiratory rate ≥ 30 breaths/min, and CT images rapid progression (>50%) within 24-48 h among the three groups were significantly different (all P < 0.05). Compared to Group C (all P < 0.017), Groups A and B were more likely to show crazy-paving pattern. Logistic regression analysis indicated that eGFR was an independent risk factor of the appearance of crazy-paving pattern. The eGFR and crazy-paving pattern have a mutually reinforcing relationship, and eGFR (HR = 0.549, 95% CI = 0.331-0.909, P = 0.020) and crazy-paving pattern (HR = 2.996, 95% CI = 1.010-8.714, P = 0.048) were independent risk factors of mortality. The mortality of severe COVID-19 with the appearance of crazy-paving pattern on chest CT was significantly higher than that of the patients without its appearance (all P < 0.05). Conclusions: The crazy-paving pattern is more likely to appear in the chest CT of patients with severe COVID-19. In severe COVID-19, the appearance of the crazy-paving pattern on chest CT indicates the occurrence of kidney injury and proneness to death. The crazy-paving pattern can be used by doctors as an early warning indicator and a guidance of reasonable drug selection.

Flexible CuS-embedded human serum albumin hollow nanocapsules with peroxidase-like activity for synergistic sonodynamic and photothermal cancer therapy.

Nanoparticle flexibility is an important parameter in determining cell uptake and tumor accumulation, thus modulating therapeutic efficiency in cancer treatment. Herein, we successfully prepared CuS-embedded human serum albumin hollow nanocapsules (denoted CuS/HSA) by a hard-core-assisted layer-by-layer coating approach. This approach afforded CuS/HSA hollow nanocapsules with controllable shell thickness, tunable flexibility, uniform size (272.9 nm), a large hollow cavity, peroxidase-like activity, excellent photothermal conversion ability, and a high tetra-(4-aminophenyl) porphyrin (TAPP) loading capacity (27.3 wt%). The peroxidase-like activity of the CuS nanoparticles enabled them to overcome tumor hypoxia and augment the sonodynamic therapeutic (SDT) effects and photothermal conversion ability for photothermal therapy (PTT). In vitro experiments showed that the CuS/HSA-TAPP hollow nanocapsules efficiently induced cancer cell apoptosis under US irradiation and cancer cell ablation under laser irradiation, thus facilitating synergistic SDT and PTT. Importantly, the flexibility of the CuS/HSA hollow nanocapsules resulted in significantly enhanced cellular internalization and a longer mean residence time (131.3 h) than their solid counterparts (21.0 h). In a breast tumor model, the flexible CuS/HSA hollow nanocapsules exhibited high tumor accumulation of up to 27.1%. In vivo experiments demonstrated that the flexible CuS/HSA-TAPP hollow nanocapsules effectively eliminated breast tumors via the synergistic effect of SDT and PTT.

Gold Nanostar@Polyaniline Theranostic Agent with High Photothermal Conversion Efficiency for Photoacoustic Imaging-Guided Anticancer Phototherapy at a Low Dosage.

Due to the strong and tunable photothermal effect, metallic nanoparticles are of enormous interest in light-activated biomedical applications, such as photoacoustic imaging (PAI) and photothermal therapy (PTT). However, the photothermal conversion efficiency (PCE) of existing metallic photothermal agents is still unsatisfactory. Herein, we develop an efficient photothermal theranostic agent based on a gold nanostar@polyaniline core-shell nanocomposite with high PCE for PAI-guided PTT at a low dosage. After optimizing the relative composition of polyaniline (PANI) and gold nanostars (AuNSs), this nanocomposite eventually empowers an outstanding PCE of up to 78.6%, which is much better than AuNSs or PANI alone and most of the existing photothermal theranostic agents. Besides, the nanocomposite can act as a targeted probe for tumors by hyaluronic acid (HA) modification without compromising the photothermal performance. The obtained nanoprobes named AuNSPHs exhibit promising biocompatibility and great performance of PAI-guided PTT to treat triple-negative breast cancer both in vitro and in vivo. More importantly, a single injection of AuNSPHs significantly suppresses tumor growth with a low dosage of Au (0.095 mg/kg), which is attributed to the high PCE of AuNSPHs. Taking advantage of the exhilarating photothermal conversion ability, this theranostic agent can safely potentiate the antitumor therapeutic efficacy of laser-induced ablation and holds great potential for future medical applications.

Review of net water uptake in the management of acute ischemic stroke.

CT densitometry-based methods to directly quantify net water uptake in ischemic brain tissue have been increasingly applied recently. There is potential for net water uptake to be used as an imaging biomarker for the pathophysiology of infarcted lesions. This review is aimed at summarizing the potential and current status of the application of net water uptake as a biomarker in the management of ischemic stroke and future directions in this context. Specifically, we provide a brief overview of the principle and different methods of net water uptake measurement, followed by a discussion of the role of net water uptake in predicting malignant brain edema and hemorrhagic transformation, evaluating lesion age, and predicting the efficacy of reperfusion therapy and long-term clinical prognosis. Artificial intelligence will help address the lack of automation and standardization in the measurement of net water absorption. Further validation of net water uptake in a prospective multicenter setting is necessary. KEY POINTS: • NWU can be used as a quantitative imaging biomarker for developing malignant brain edema in anterior and posterior circulation strokes. • The difference in NWU in edema arrest or reversibility suggests that rapid and successful revascularization can influence the progression of ischemic edema. • NWU can be used to predict the age of a lesion, with predictive power comparable to that of DWI/FLAIR mismatch.