Plant-derived nanoparticles and plant virus nanoparticles: Bioactivity, health management, and delivery potential.

Natural plants have acquired an increasing attention in biomedical research. Recent studies have revealed that plant-derived nanoparticles (PDNPs), which are nano-sized membrane vesicles released by plants, are one of the important material bases for the health promotion of natural plants. A great deal of research in this field has focused on nanoparticles derived from fresh vegetables and fruits. Generally, PDNPs contain lipids, proteins, nucleic acids, and other active small molecules and exhibit unique biological regulatory activity and editability. Specifically, they have emerged as important mediators of intercellular communication, and thus, are potentially suitable for therapeutic purposes. In this review, PDNPs were extensively explored; by evaluating them systematically starting from the origin and isolation, toward their characteristics, including morphological compositions, biological functions, and delivery potentials, as well as distinguishing them from plant-derived exosomes and highlighting the limitations of the current research. Meanwhile, we elucidated the variations in PDNPs infected by pathogenic microorganisms and emphasized on the biological functions and characteristics of plant virus nanoparticles. After clarifying these problems, it is beneficial to further research on PDNPs in the future and develop their clinical application value.

Intravoxel Incoherent Motion Imaging Study of Madecassoside in Improving Lipopolysaccharide-Induced Cognitive Impairment in Rats.

BACKGROUND: Central nervous system inflammation is associated with neurodegenerative diseases and is thought to play a part in the pathophysiological cascade leading to cognitive impairment. Madecassoside (MA) has shown potential for the treatment of neuroinflammation. Lipopolysaccharide (LPS) can be used to establish an animal model of cognitive dysfunction induced by neuroinflammation. Intravoxel incoherent motion (IVIM) may potentially provide diffusion and perfusion data. PURPOSE: To investigate the effect of MA on neurocognitive impairment induced by LPS in rats, and to explore the changes of brain microstructure and microcirculatory perfusion by IVIM imaging. STUDY TYPE: Prospective. POPULATION: Thirty-six male Sprague-Dawley rats were randomly divided into six groups (control group, sham operation group, LPS group, low-dose MA group, middle-dose MA group, and high-dose MA group) in a model of neurocognitive impairment induced by LPS (150 µg / 5 µL, 5 µL). FIELD STRENGTH/SEQUENCE: IVIM-DWI sequence at 3.0T MRI; the scan time was 2 minutes and 17 seconds. ASSESSMENT: The escape latency times of a Morris water maze test was used to evaluate the cognitive impairment rat model and the changes of learning ability of rats treated with different doses of MA (30 mg/kg, 60 mg/kg, 120 mg/kg). A GE postprocessing workstation (adw 4.5) was used to analyze the changes of each parameter (f value, D value, and D* value) in the IVIM data of each group. STATISTICAL TESTS: All the data were analyzed by one-way and two-way analysis of variance (ANOVA). RESULTS: The escape latency of the LPS group was significantly longer than the sham group (P = 0.05, 0.001, 0.006, and 0.042, respectively), and the high-dose group was significantly shorter than the LPS group on the sixth day (P = 0.034). Compared with the control group, the D values and f values of cerebral cortex and hippocampus were decreased significantly in the LPS group (P = 0.043 and 0.003; P = 0.029 and 0.016, respectively). With the increasing dose of MA, the D and f values of hippocampus and cortex increased, and there was a significant difference between the high-dose MA group and LPS group (D values: P = 0.038, 0.036; f values: P = 0.048, 0.039, respectively) DATA CONCLUSION: MA can improve the cognitive impairment induced by LPS by reducing neuroinflammation, and the changes of microcirculation and microperfusion in the brain tissue of these rats can be detected by IVIM imaging. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2020;51:1836-1843.

T cell senescence: a new perspective on immunotherapy in lung cancer.

T cell senescence is an indication of T cell dysfunction. The ability of senescent T cells to respond to cognate antigens is reduced and they are in the late stage of differentiation and proliferation; therefore, they cannot recognize and eliminate tumor cells in a timely and effective manner, leading to the formation of the suppressive tumor microenvironment. Establishing methods to reverse T cell senescence is particularly important for immunotherapy. Aging exacerbates profound changes in the immune system, leading to increased susceptibility to chronic, infectious, and autoimmune diseases. Patients with malignant lung tumors have impaired immune function with a high risk of recurrence, metastasis, and mortality. Immunotherapy based on PD-1, PD-L1, CTLA-4, and other immune checkpoints is promising for treating lung malignancies. However, T cell senescence can lead to low efficacy or unsuccessful treatment results in some immunotherapies. Efficiently blocking and reversing T cell senescence is a key goal of the enhancement of tumor immunotherapy. This study discusses the characteristics, mechanism, and expression of T cell senescence in malignant lung tumors and the treatment strategies.

Microenvironmental regulation in tumor progression: Interactions between cancer-associated fibroblasts and immune cells.

The tumor microenvironment (TME), the "soil" on which tumor cells grow, has an important role in regulating the proliferation and metastasis of tumor cells as well as their response to treatment. Cancer-associated fibroblasts (CAFs), as the most abundant stromal cells of the TME, can not only directly alter the immunosuppressive effect of the TME through their own metabolism, but also influence the aggregation and function of immune cells by secreting a large number of cytokines and chemokines, reducing the body's immune surveillance of tumor cells and making them more prone to immune escape. Our study provides a comprehensive review of fibroblast chemotaxis, malignant transformation, metabolic characteristics, and interactions with immune cells. In addition, the current small molecule drugs targeting CAFs have been summarized, including both natural small molecules and targeted drugs for current clinical therapeutic applications. A complete review of the role of fibroblasts in TME from an immune perspective is presented, which has important implications in improving the efficiency of immunotherapy by targeting fibroblasts.

Developing a deep learning model to predict epilepsy recurrence in patients with focal cortical dysplasia type III.

Background: A sizable number of patients with focal cortical dysplasia (FCD) type III-related refractory epilepsy continue to experience seizures postsurgically. Deep learning models can automatically assess complex medical image characteristics and predict prognosis with higher efficiency. This study sought to determine whether T2-weighted fluid attenuated inversion recovery (T2W FLAIR) images could predict prognosis of FCD type III-related refractory epilepsy using a deep learning approach. Methods: Magnetic resonance imaging (MRI) images of 266 patients with FCD type III diagnosed between 2015 and 2019 were included in this retrospective analysis. A deep learning algorithm utilizing a convolutional neural network (CNN) was trained to classify T2W FLAIR images according to Engel's classification. The preprocessed original image and the region of interest (ROI) outlined by clinicians were input into our neural network separately and then together. Precision, sensitivity, specificity, receiver operating characteristic (ROC) curves, and areas under the ROC curves (AUCs) were computed as part of the statistical analyses of the network performance with varied inputs of the network model assessed. Results: The overall performance met the following metrics when the original image only was input: AUC of 96.22%, sensitivity of 84.47%, and specificity of 97.21%. The metrics were as follows when the ROI only was input: area under the ROC curve of 94.76%, sensitivity of 84.92%, and specificity of 96.24%. For the combined inputs, the metrics were as follows: AUC of 97.17%, sensitivity of 90.86%, and specificity of 96.63%. Conclusions: Deep learning used with conventional MRI can effectively predict the recurrence conditions of epilepsy. Artificial intelligence may help the design of clinical management and enable more precise and individualized prediction for postsurgical prognosis of FCD type III-related refractory epilepsy.

Subtype Classification, Immune Infiltration, and Prognosis Analysis of Lung Adenocarcinoma Based on Pyroptosis-Related Genes.

The effect of pyroptosis-related genes (PRGs) on the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Thus, this study is aimed at evaluating the prognostic value of PRGs in patients with LUAD and to elucidate their role in the TME and their effect on immunotherapy. Transcriptomic and clinical data were obtained from the Cancer Genome Atlas and the Gene Expression Omnibus databases (GSE3141, GSE31210). Patients with LUAD were classified using consistent clustering, and the differences in the TME for each type were determined using the ESTIMATE and CIBERSORT algorithms. PRGs were screened using univariate regression analysis, and a prognostic risk model was constructed using LASSO regression analysis. The tumor mutational burden and the tumor immune dysfunction and exclusion algorithms were used to predict therapeutic sensitivity in LUAD patients. Then, we evaluated the potential therapeutic interventions using the GDSC database. LUAD patients in cluster 2 had significantly shorter overall survival and progression-free survival rates, lower immune scores, and higher infiltration of T follicular helper cells than those in cluster 1. We used five PRGs to classify patients with LUAD into different risks groups and found that the high-risk group is sensitive to immunotherapy; however, its immune-related pathways were inhibited, which may be related to tumor metabolic reprogramming. Lastly, we identified several potential therapeutic drugs for application in low-risk patients who were less sensitive to immunotherapy. Overall, our findings showed that PRGs can be used to predict prognosis and may aid in the development of personalized therapeutic strategies in LUAD patients.

Tumor accomplice: T cell exhaustion induced by chronic inflammation.

The development and response to treatment of tumor are modulated by inflammation, and chronic inflammation promotes tumor progression and therapy resistance. This article summarizes the dynamic evolution of inflammation from acute to chronic in the process of tumor development, and its effect on T cells from activation to the promotion of exhaustion. We review the mechanisms by which inflammatory cells and inflammatory cytokines regulate T cell exhaustion and methods for targeting chronic inflammation to improve the efficacy of immunotherapy. It is great significance to refer to the specific state of inflammation and T cells at different stages of tumor development for accurate clinical decision-making of immunotherapy and improving the efficiency of tumor immunotherapy.

Remarkable gastrointestinal and liver manifestations of COVID-19: A clinical and radiologic overview.

The coronavirus disease 2019 (COVID-19) raging around the world still has not been effectively controlled in most countries and regions. As a severe acute respiratory syndrome coronavirus, in addition to the most common infectious pneumonia, it can also cause digestive system disease such as diarrhea, nausea, vomiting, liver function damage, etc. In medical imaging, it manifests as thickening of the intestinal wall, intestinal perforation, pneumoperitoneum, ascites and decreased liver density. Angiotensin-converting enzyme 2 has great significance in COVID-19-related digestive tract diseases. In this review, we summarized the data on the clinical and imaging manifestations of gastrointestinal and liver injury caused by COVID-19 so far and explored its possible pathogenesis.

Focal Cortical Dysplasia Type â ¢ Related Medically Refractory Epilepsy: MRI Findings and Potential Predictors of Surgery Outcome.

This study aims to explore the relationship between neuropathologic and the post-surgical prognosis of focal cortical dysplasia (FCD) typed-Ⅲ-related medically refractory epilepsy. A total of 266 patients with FCD typed-Ⅲ-related medically refractory epilepsy were retrospectively studied. Presurgical clinical data, type of surgery, and postsurgical seizure outcome were analyzed. The minimum post-surgical follow-up was 1 year. A total of 266 patients of FCD type Ⅲ were included in this study and the median follow-up time was 30 months (range, 12~48 months). Age at onset ranged from 1.0 years to 58.0 years, with a median age of 12.5 years. The number of patients under 12 years old was 133 (50%) in patients with FCD type Ⅲ. A history of febrile seizures was present in 42 (15.8%) cases. In the entire postoperative period, 179 (67.3%) patients were seizure-free. Factors with p < 0.15 in univariate analysis, such as age of onset of epilepsy (p = 0.145), duration of epilepsy (p = 0.004), febrile seizures (p = 0.150), being MRI-negative (p = 0.056), seizure type (p = 0.145) and incomplete resection, were included in multivariate analysis. Multivariate analyses revealed that MRI-negative findings of FCD (OR 0.34, 95% CI 0.45-0.81, p = 0.015) and incomplete resection (OR 0.12, 95% CI 0.05-0.29, p < 0.001) are independent predictors of unfavorable seizure outcomes. MRI-negative finding of FCD lesions and incomplete resection were the most important predictive factors for poor seizure outcome in patients with FCD type Ⅲ.

Simulation Analysis on Photoelectric Conversion Characteristics of Silicon Nanowire Array Photoelectrodes.

Semiconductor nanowire photoelectrochemical cells have attracted extensive attention in the light-conversion field owing to the low-cost preparation, excellent optical absorption, and short distance of carrier collection. Although there are numbers of experimental investigations to improve the device performance, the understanding of the detailed process of photoelectric conversion needs to be further improved. In this work, a thorough optoelectronic simulation is employed to figure out how the nanowire diameter, doping concentration, and illumination wavelength affect the photoelectric conversion characteristics of the silicon nanowire array photoelectrodes. We find that two balances should be carefully weighted between optical absorption and photogenerated-carrier collection, along with between short-circuit photocurrent density and open-circuit voltage. For the small-diameter nanowire array photoelectrodes, the overall absorption is higher than that of the larger-diameter ones with the most contribution from the nanowires. However, the substrate shows increasing absorption with increasing illumination wavelength. Higher doping density leads to a larger open-circuit voltage; while lower doping density can guarantee a relatively higher short-circuit photocurrent. To obtain high-light-conversion-efficiency photoelectrodes, the doping density should be carefully chosen with considerations of illumination wavelength and surface recombination. Suppressing the surface recombination velocity can effectively enhance the short-circuit photocurrent (open-circuit voltage) for the lightly (heavily) doped nanowire array photoelectrodes. Our systematical results provide a theoretical guidance for the photoelectrochemical devices based on semiconductor nanostructures.