Silica nanoparticles for brain cancer.

INTRODUCTION: Brain cancer is a debilitating disease with a poor survival rate. There are significant challenges for effective treatment due to the presence of the blood-brain barrier (BBB) and blood-tumor barrier (BTB) which impedes drug delivery to tumor sites. Many nanomedicines have been tested in improving both the survival and quality of life of patients with brain cancer with the recent focus on inorganic nanoparticles such as silica nanoparticles (SNPs). This review examines the use of SNPs as a novel approach for diagnosing, treating, and theranostics of brain cancer. AREAS COVERED: The review provides an overview of different brain cancers and current therapies available. A special focus on the key functional properties of SNPs is discussed which makes them an attractive material in the field of onco-nanomedicine. Strategies to overcome the BBB using SNPs are analyzed. Furthermore, recent advancements in active targeting, combination therapies, and innovative nanotherapeutics utilizing SNPs are discussed. Safety considerations, toxicity profiles, and regulatory aspects are addressed to provide an understanding of SNPs' translational potential. EXPERT OPINION: SNPs have tremendous prospects in brain cancer research. The multifunctionality of SNPs has the potential to overcome both the BBB and BTB limitations and can be used for brain cancer imaging, drug delivery, and theranostics. The insights provided will facilitate the development of next-generation, innovative strategies, guiding future research toward improved diagnosis, targeted therapy, and better outcomes in brain cancer patients.

Virus-like Silica Nanoparticles Improve Permeability of Macromolecules across the Blood-Brain Barrier In Vitro.

The presence of the blood-brain barrier (BBB) limits the delivery of therapies into the brain. There has been significant interest in overcoming the BBB for the effective delivery of therapies to the brain. Inorganic nanomaterials, especially silica nanoparticles with varying surface chemistry and surface topology, have been recently used as permeation enhancers for oral protein delivery. In this context, nanoparticles with varying sizes and surface chemistries have been employed to overcome this barrier; however, there is no report examining the effect of nanoscale roughness on BBB permeability. This paper reports the influence of nanoscale surface roughness on the integrity and permeability of the BBB in vitro, using smooth surface Stöber silica nanoparticles (60 nm) compared to rough surface virus-like silica nanoparticles (VSNP, 60 nm). Our findings reveal that VSNP (1 mg/mL) with virus-mimicking-topology spiky surface have a greater effect on transiently opening endothelial tight junctions of the BBB than the same dose of Stöber silica nanoparticles (1 mg/mL) by increasing the FITC-Dextran (70 kDa) permeability 1.9-fold and by decreasing the trans-endothelial electrical resistance (TEER) by 2.7-fold. This proof-of-concept research paves the way for future studies to develop next-generation tailored surface-modified silica nanoparticles, enabling safe and efficient macromolecule transport across the BBB.

Removal of chloramphenicol and resistance gene changes in electric-integrated vertical flow constructed wetlands.

The performance of an electric-integrated vertical flow constructed wetland (E-VFCW) for chloramphenicol (CAP) removal, changes in microbial community structure, and the fate of antibiotic resistance genes (ARGs) were evaluated. CAP removal in the E-VFCW system was 92.73% ± 0.78% (planted) and 90.80% ± 0.61% (unplanted), both were higher than the control system which was 68.17% ± 1.27%. The contribution of anaerobic cathodic chambers in CAP removal was higher than the aerobic anodic chambers. Plant physiochemical indicators in the reactor revealed electrical stimulation increased oxidase activity. Electrical stimulation enhanced the enrichment of ARGs in the electrode layer of the E-VFCW system (except floR). Plant ARGs and intI1 levels were higher in the E-VFCW than in the control system, suggesting electrical stimulation induces plants to absorb ARGs, reducing ARGs in the wetland. The distribution of intI1 and sul1 genes in plants suggests that horizontal transfer may be the main mechanism dispersing ARGs in plants. High throughput sequencing analysis revealed electrical stimulation selectively enriched CAP degrading functional bacteria (Geobacter and Trichlorobacter). Quantitative correlation analysis between bacterial communities and ARGs confirmed the abundance of ARGs relates to the distribution of potential hosts and mobile genetic elements (intI1). E-VFCW is effective in treating antibiotic wastewater, however ARGs potentially accumulate.

Enhanced biodegradation of fluoroquinolones and the changes of bacterial communities and antibiotic-resistant genes under intermittent electrical stimulation.

In this study, an anaerobic-aerobic coupling system under intermittent electrical stimulation was used to improve the biodegradation of synthetic wastewater containing fluoroquinolones (FQs). The effect of electrical stimulation on FQ removal performance is more pronounced with appropriate voltage and hydraulic retention time. In addition, the combination of anaerobic-anodic and aerobic-cathodic chambers is more conducive to improving the removal efficiency of FQs. Under 0.9 V, the removal efficiencies of ofloxacin, norfloxacin, ciprofloxacin, and enrofloxacin were significantly improved in the anaerobic-anodic and aerobic-cathodic system. The contribution of the anaerobic/aerobic anodic chambers to FQ removal was greater than that of the anaerobic/aerobic cathodic chambers. Electrical stimulation selectively enriched electroactive bacteria related to biodegradation (Desulfovibrio and Terrimonas), antibiotic-resistant bacteria (Atopobium and Neochlamydia), and nitrifying bacteria (SM1A02 and Reyranella). This study indicated the potential effectiveness of intermittent electrical stimulation in treating fluoroquinolone-containing wastewater in a biofilm reactor. However, electrical stimulation led to an increase in mobile genetic elements , induced horizontal gene transfer and enriched resistant bacteria, which accelerated the spread of antibiotic-resistant genes (ARGs) in the system, indicating that the diffusion of ARGs remains a challenge.

Heat Shock Transcription Factor 2 Promotes Mitophagy of Intestinal Epithelial Cells Through PARL/PINK1/Parkin Pathway in Ulcerative Colitis.

The overactivation of NLRP3 inflammasome in intestinal epithelial cells (IECs) is among the important reasons for severe inflammation in ulcerative colitis (UC). We found that heat shock transcription factor 2 (HSF2), which is highly expressed in UC, could inhibit the activation of NLRP3 inflammasome and reduce IL-1ß in IECs, but the mechanisms were still not clear. It has been reported that HSP72 regulated by HSF2 can enhance the mitophagy mediated by Parkin. The number of damaged mitochondria and the mitochondrial derived ROS (mtROS) can be reduced by mitophagy, which means the activity of NLRP3 inflammasome is inhibited. Therefore, we speculate that HSF2 might regulate the activation of NLRP3 inflammasome of IECs in UC through the mitophagy mediated by Parkin. This study proves that the number of damaged mitochondria in IECs, the level of mitophagy, and the level of ROS in intestinal mucosa are positively correlated with the severity of UC. In mice and cells, mitophagy was promoted by HSF2 through the PARL/PINK1/Parkin pathway. This study reveals the potential mechanisms of HSF2 decreasing mtROS of IECs in UC.

Heat shock transcription factor 2 reduces the secretion of IL-1ß by inhibiting NLRP3 inflammasome activation in ulcerative colitis.

Ulcerative colitis (UC) is a chronic inflammatory disease with unknown aetiology. As a pro-inflammatory cytokine, interleukin-1ß (IL-1ß) plays a critical, damaging role in UC. Heat shock proteins (HSPs) are important anti-inflammatory factors that maintain intestinal epithelial cells (IECs) homeostasis. Heat shock transcription factor 2 (HSF2) is an important regulator of HSPs. In our previous research, we found that HSF2 is highly expressed in UC, is negatively related to colon inflammation of mice, and inhibits the expression of IL-1ß, but the specific mechanism is still unclear. As a product of the NLRP3 inflammasome, the expression of IL-1ß is closely related to NLRP3 inflammasome activation. Therefore, we hypothesised that HSF2 affects the secretion of IL-1ß by regulating activation of the NLRP3 inflammasome. In this study, hsf-/- DSS model mice showed highest levels of expression of the NLRP3 inflammasome and the secretion of IL-1ß. In Caco-2 cells, the levels of expression of the NLRP3 inflammasome and the secretion of IL-1ß were inhibited by overexpression of HSF2, and inhibited HSF2 increased activation of the NLRP3 inflammasome and the secretion of IL-1ß. These findings indicated that HSF2 might be an important target for inflammatory modulation in UC.

Diagnosis of thyroid nodules for ultrasonographic characteristics indicative of malignancy using random forest.

BACKGROUND: Various combinations of ultrasonographic (US) characteristics are increasingly utilized to classify thyroid nodules. But they lack theories, and heavily depend on radiologists' experience, and cannot correctly classify thyroid nodules. Hence, our main purpose of this manuscript is to select the US characteristics significantly associated with malignancy and to develop an efficient scoring system for facilitating ultrasonic clinicians to correctly identify thyroid malignancy. METHODS: A logistic regression (LR) model is utilized to identify the potential thyroid malignancy, and the least absolute shrinkage and selection operator (LASSO) method is adopted to simultaneously select US characteristics significantly associated with malignancy and estimate parameters in LR model. Based on the selected US characteristics, we calculate the probability for each of thyroid nodules via random forest (RF) and extreme learning machine (ELM), and develop a scoring system to classify thyroid nodules. For comparison, we also consider eight state-of-the-art methods such as support vector machine (SVM), neural network (NET), etc. The area under the receiver operating characteristic curve (AUC) is employed to measure the accuracy of various classifiers. RESULTS: The US characteristics: nodule size, AP/T≥1, solid component, micro-calcifications, hackly border, hypoechogenicity, presence of halo, unclear border, irregular margin, and central vascularity are selected as the significant predictors associated with thyroid malignancy via the LASSO LR (LLR). Using the developed scoring system, thyroid nodules are classified into the following four categories: benign, low suspicion, intermediate suspicion, and high suspicion, whose rates of malignancy correctly identified for RF (ELM) method on the testing dataset are 0.0% (4.3%), 14.3% (50.0%), 58.1% (59.1%) and 96.1% (97.7%), respectively. CONCLUSION: LLR together with RF performs better than other methods in identifying malignancy, especially for abnormal nodules, in terms of risk scores. The developed scoring system can well predict the risk of malignancy and guide medical doctors to make management decisions for reducing the number of unnecessary biopsies for benign nodules.