The regulatory mechanisms of cerium oxide nanoparticles in oxidative stress and emerging applications in refractory wound care.

Cerium oxide nanoparticles (CeNPs) have emerged as a potent therapeutic agent in the realm of wound healing, attributing their efficacy predominantly to their exceptional antioxidant properties. Mimicking the activity of endogenous antioxidant enzymes, CeNPs alleviate oxidative stress and curtail the generation of inflammatory mediators, thus expediting the wound healing process. Their application spans various disease models, showcasing therapeutic potential in treating inflammatory responses and infections, particularly in oxidative stress-induced chronic wounds such as diabetic ulcers, radiation-induced skin injuries, and psoriasis. Despite the promising advancements in laboratory studies, the clinical translation of CeNPs is challenged by several factors, including biocompatibility, toxicity, effective drug delivery, and the development of multifunctional compounds. Addressing these challenges necessitates advancements in CeNP synthesis and functionalization, novel nano delivery systems, and comprehensive bio effectiveness and safety evaluations. This paper reviews the progress of CeNPs in wound healing, highlighting their mechanisms, applications, challenges, and future perspectives in clinical therapeutics.

Efficacy of rTMS in treating functional impairment in post-stroke patients: a systematic review and meta-analysis.

BACKGROUND: Most stroke patients suffer from an imbalance in blood supply, which causes severe brain damage leading to functional deficits in motor, sensory, swallowing, cognitive, emotional, and speech functions. Repetitive transcranial magnetic stimulation (rTMS) is thought to restore functions impaired during the stroke process and improve the quality of life of stroke patients. However, the efficacy of rTMS in treating post-stroke function impairment varies significantly. Therefore, we conducted a meta-analysis of the number of patients with effective rTMS in treating post-stroke dysfunction. METHODS: The PubMed, Embase, and Cochrane Library databases were searched. Screening and full-text review were performed by three investigators. Single-group rate meta-analysis was performed on the extracted data using a random variable model. Then subgroup analyses were performed at the levels of stroke acuity (acute, chronic, or subacute); post-stroke symptoms (including upper and lower limb motor function, dysphagia, depression, aphasia); rTMS stimulation site (affected side, unaffected side); and whether or not it was a combination therapy. RESULTS: We obtained 8955 search records, and finally 33 studies (2682 patients) were included in the meta-analysis. The overall analysis found that effective strength (ES) of rTMS was 0.53. In addition, we found that the ES of rTMS from acute/subacute/chronic post-stroke was 0.69, 0.45, and 0.52. We also found that the ES of rTMS using high-frequency stimulation was 0.56, while the ES of rTMS using low-frequency stimulation was 0.53. From post-stroke symptoms, we found that the ES of rTMS in sensory aspects, upper limb functional aspects, swallowing function, and aphasia was 0.50, 0.52, 0.51, and 0.54. And from the site of rTMS stimulation, we found that the ES of rTMS applied to the affected side was 0.51, while the ES applied to the unaffected side was 0.54. What's more, we found that the ES of rTMS applied alone was 0.53, while the ES of rTMS applied in conjunction with other therapeutic modalities was 0.53. CONCLUSIONS: By comparing the results of the data, we recommend rTMS as a treatment option for rehabilitation of functional impairment in patients after stroke. We also recommend that rehabilitation physicians or clinicians use combination therapy as one of the options for patients.

CT radiomics based on different machine learning models for classifying gross tumor volume and normal liver tissue in hepatocellular carcinoma.

BACKGROUND & AIMS: The present study utilized extracted computed tomography radiomics features to classify the gross tumor volume and normal liver tissue in hepatocellular carcinoma by mainstream machine learning methods, aiming to establish an automatic classification model. METHODS: We recruited 104 pathologically confirmed hepatocellular carcinoma patients for this study. GTV and normal liver tissue samples were manually segmented into regions of interest and randomly divided into five-fold cross-validation groups. Dimensionality reduction using LASSO regression. Radiomics models were constructed via logistic regression, support vector machine (SVM), random forest, Xgboost, and Adaboost algorithms. The diagnostic efficacy, discrimination, and calibration of algorithms were verified using area under the receiver operating characteristic curve (AUC) analyses and calibration plot comparison. RESULTS: Seven screened radiomics features excelled at distinguishing the gross tumor area. The Xgboost machine learning algorithm had the best discrimination and comprehensive diagnostic performance with an AUC of 0.9975 [95% confidence interval (CI): 0.9973-0.9978] and mean MCC of 0.9369. SVM had the second best discrimination and diagnostic performance with an AUC of 0.9846 (95% CI: 0.9835- 0.9857), mean Matthews correlation coefficient (MCC)of 0.9105, and a better calibration. All other algorithms showed an excellent ability to distinguish between gross tumor area and normal liver tissue (mean AUC 0.9825, 0.9861,0.9727,0.9644 for Adaboost, random forest, logistic regression, naivem Bayes algorithm respectively). CONCLUSION: CT radiomics based on machine learning algorithms can accurately classify GTV and normal liver tissue, while the Xgboost and SVM algorithms served as the best complementary algorithms.

Performance of [18F]FDG PET/CT versus FAPI PET/CT for lung cancer assessment: a systematic review and meta-analysis.

PURPOSE: This article aims to compare the diagnostic performance of 18-fluorodeoxyglucose ([18F]FDG) PET/CT and fibroblast activating protein inhibitor (FAPI) PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer patients. METHODS: A systematic search was conducted on the Cochrane Library, Embase, and PubMed/MEDLINE databases from inception until November 1, 2022. Included studies assessed the use of FAPI PET/CT and [18F]FDG PET/CT in patients with lung cancer. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to evaluate the risk of bias. A random variable model was used to analyze the diagnostic tests of the two imaging modalities. RESULTS: The sensitivity of FAPI PET/CT in detecting primary lung cancer lesions was 0.98 (95% CI: 0.88-1.00), while the sensitivity of [18F]FDG PET/CT was 0.99 (95% CI: 0.74-1.00). For the detection of metastatic lesions (lymph node metastases and distant metastases), FAPI PET/CT had a sensitivity of 0.99 (95% CI: 0.90-1.00), while the sensitivity of [18F]FDG PET/CT was 0.77 (95% CI: 0.66-0.85). However, the specificity of the two imaging modalities could not be assessed due to the lack of sufficient information on pertinent true negatives. CONCLUSION: In the diagnosis of metastatic lung cancer lesions, FAPI PET/CT demonstrated a higher sensitivity compared to [18F]FDG PET/CT. Therefore, FAPI PET/CT may be considered an alternative imaging modality for the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases. CLINICAL RELEVANCE STATEMENT: FAPI may be an alternative to [18F]FDG in the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases, which plays a very important role in treatment. KEY POINTS: • This article is to compare the performance of [18F]FDG PET/CT with FAPI PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer. • However, FAPI PET/CT has a higher sensitivity for the diagnostic assessment of metastatic lung cancer lesions.

18F­FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning algorithms and multimodality applications for multiple myeloma.

PURPOSE: Multiple myeloma (MM), the second most hematological malignancy, have been studied extensively in the prognosis of the clinical parameters, however there are only a few studies have discussed the role of dual modalities and multiple algorithms of 18F-FDG (18F-fluorodeoxyglucose) PET/CT based radiomics signatures for prognosis in MM patients. We hope to deeply mine the utility of raiomics data in the prognosis of MM. METHODS: We extensively explored the predictive ability and clinical decision-making ability of different combination image data of PET, CT, clinical parameters and six machine learning algorithms, Cox proportional hazards model (Cox), linear gradient boosting models based on Cox's partial likelihood (GB-Cox), Cox model by likelihood based boosting (CoxBoost), generalized boosted regression modelling (GBM), random forests for survival model (RFS) and support vector regression for censored data model (SVCR). And the model evaluation methods include Harrell concordance index, time dependent receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). RESULTS: We finally confirmed 5 PET based features, and 4 CT based features, as well as 6 clinical derived features significantly related to progression free survival (PFS) and we included them in the model construction. In various modalities combinations, RSF and GBM algorithms significantly improved the accuracy and clinical net benefit of predicting prognosis compared with other algorithms. For all combinations of various modalities based models, single-modality PET based prognostic models' performance was outperformed baseline clinical parameters based models, while the performance of models of PET and CT combined with clinical parameters was significantly improved in various algorithms. CONCLUSION: 18F­FDG PET/CT based radiomics models implemented with machine learning algorithms can significantly improve the clinical prediction of progress and increased clinical benefits providing prospects for clinical prognostic stratification for precision treatment as well as new research areas.

[68Ga]Ga-FAPI PET for the evaluation of digestive system tumors: systematic review and meta-analysis.

PURPOSE: Digestive system tumors are a group of tumors with high incidence in the world nowadays. The assessment of digestive system tumor metastasis by conventional imaging seems to be unsatisfactory. [68Ga]Ga-FAPI, which has emerged in recent years, seems to be able to evaluate digestive system tumor metastasis. We aimed to summarize the current evidence of [68Ga]Ga-FAPI PET/CT or PET/MR for the assessment of primary tumors, lymph node metastases, and distant metastases in digestive system tumors. Besides, we also aimed to perform a meta-analysis of the sensitivity of [68Ga]Ga-FAPI PET diagnosis to discriminate between digestive system tumors, primary lesions, and non-primary lesions (lymph node metastases and distant metastases). MATERIALS AND METHODS: PubMed, MEDLINE and Cochrane Library databases were searched from the beginning of the database build to August 12, 2022. All studies undergoing [68Ga]Ga-FAPI PET for the evaluation of digestive tumors were included in the screening and review. Screening and full text review was performed by 3 investigators and data extraction was performed by 2 investigators. Risk of bias was examined with the QUADAS-2 criteria. Diagnostic test meta-analysis was performed with a random-effects model. RESULTS: A total of 541 studies were retrieved. Finally, 22 studies were selected for the systematic review and 18 studies were included in the meta-analysis. In the 18 publications, a total of 524 patients with digestive system tumors, 459 primary tumor lesions of digestive system tumors, and 1921 metastatic lesions of digestive system tumors were included in the meta-analysis. Based on patients, the sensitivity of [68Ga]Ga-FAPI PET for the diagnosis of digestive system tumors was 0.98 (95% CI: 0.94-0.99). Based on lesions, the sensitivity of [68Ga]Ga-FAPI PET for the diagnostic evaluation of primary tumor lesions of the digestive system was 0.97 (95% CI: 0.93-0.99); the sensitivity of [68Ga]Ga-FAPI PET for the diagnostic evaluation of non-primary lesions (lymph node metastases and distant metastases) of the digestive system tumors was 0.94 (95% CI: 0.79-0.99). CONCLUSION: [68Ga]Ga-FAPI PET has high accuracy and its sensitivity is at a high level for the diagnostic evaluation of digestive system tumors. Clinicians, nuclear medicine physicians, and radiologists may consider using [68Ga]Ga-FAPI PET/CT or PET/MR in the evaluation of primary tumors, lymph node metastases, and distant metastases in digestive system tumors.

Study on connectivity of buried pipeline network considering nodes reliability under seismic action.

Currently, the connectivity calculation of complex pipeline networks is mostly simplified or ignores the influence of nodes such as elbows and tees on the connectivity reliability of the entire network. Historical earthquake damage shows that the seismic performance of municipal buried pipelines depends on the ability of nodes and interfaces to resist deformation. The influence of node reliability on network connectivity under reciprocal loading is a key issue to be addressed. Therefore, based on the general connectivity probabilistic analysis algorithm, this paper embeds the reliability of nodes into the reliability of edges, and derives a more detailed and comprehensive on-intersecting minimum path recursive decomposition algorithm considering elbows, tees, and other nodes; then, based on the reliability calculation theory of various pipeline components, the reliability of various nodes in different soil is calculated using finite element numerical simulation; finally, the reliability of a small simple pipeline network and a large complex pipeline network are used as examples to reveal the importance of considering nodes in the connectivity calculation of pipeline network. The reliability of the network system decreases significantly after considering the nodes such as elbows and tees. The damage of one node usually causes the failure of the whole pipes of the path. The damage probability is greater in the area with dense elbow and tee nodes. In this study, all types of nodes that are more prone to damage are considered in detail in the calculation. As a result, the proposed algorithm has been improved in computational accuracy, which lays the foundation for further accurate calculation of pipeline network connectivity.

Response analysis of the nodes of pipe networks under seismic load.

Transient ground displacement (TGD) that is caused by earthquakes can damage underground pipes. This damage is especially critical for the joints, elbows and tees of the pipes which play an important role in the operation of a pipe network. In this study, a scale pipe network with both elbows and tees, as well as some components of the pipe network with only tees or elbows, has been investigated. The response of the nodes of a pipe network, when installed in non-uniform geology, was analyzed using the shaking table test and ABAQUS finite element simulation. This paper has firstly introduced the preparation of the test and the developed finite element model. Then the system response in terms of strain, the friction, the bending deformation, the node deformation amplification coefficient and the pipe-soil relative displacement along the pipe axis of the pipe network and two pipe network components have been analyzed explaining the correlation between these responses. Finally, the influence of elbows and tees on the pipe network was analyzed, and the conclusions that have been reached about how tees and elbows can change the response of a pipe network during an earthquake can provide theoretical support for the seismic design and layout of an underground pipe network.

PDGF-CC underlies resistance to VEGF-A inhibition and combinatorial targeting of both suppresses pathological angiogenesis more efficiently.

Anti-VEGF-A therapy has proven to be effective for many neovascular diseases. However, drug resistance to anti-VEGF-A treatment can develop. Also, not all patients with neovascular diseases are responsive to anti-VEGF-A treatment. The mechanisms underlying these important issues remain unclear. In this study, using different model systems, we found that inhibition of VEGF-A directly upregulated PDGF-CC and its receptors in multiple cell types in pathological angiogenesis in vitro and in vivo. Importantly, we further revealed that combinatorial targeting of VEGF-A and PDGF-CC suppressed pathological angiogenesis more efficiently than monotherapy. Given the potent angiogenic activity of PDGF-CC, our findings suggest that the development of resistance to anti-VEGF-A treatment may be caused by the compensatory upregulation of PDGF-CC, and combined inhibition of VEGF-A and PDGF-CC may have therapeutic advantages in treating neovascular diseases.

VEGF-B inhibits hyperglycemia- and Macugen-induced retinal apoptosis.

Vascular endothelial growth factor B (VEGF-B) was discovered a long time ago. However, its role in hyperglycemia- and VEGF-A inhibition-induced retinal apoptosis remains unknown thus far. Yet, drugs that can block VEGF-B are being used to treat patients with diabetic retinopathy and other ocular neovascular diseases. It is therefore urgent to have a better understanding of the function of VEGF-B in these pathologies. Here, we report that both streptozotocin (STZ)-induced diabetes in rats and Macugen intravitreal injection in mice leads to retinal apoptosis in retinal ganglion cell and outer nuclear layers respectively. Importantly, VEGF-B treatment by intravitreal injection markedly reduced retinal apoptosis in both models. We further reveal that VEGF-B and its receptors, vascular endothelial growth factor 1 (VEGFR1) and neuropilin 1 (NP1), are abundantly expressed in rat retinae and choroids and are upregulated by high glucose with concomitant activation of Akt and Erk. These data highlight an important function of VEGF-B in protecting retinal cells from apoptosis induced by hyperglycemia and VEGF-A inhibition. VEGF-B may therefore have a therapeutic potential in treating various retinal degenerative diseases, and modulation of VEGF-B activity in the eye needs careful consideration.