Glioblastoma (GB) is the most common and aggressive primary tumor of the central nervous system. The current standard of care for GB consists of surgical resection, followed by radiotherapy combined with temozolomide chemotherapy. However, despite this intensive treatment, the prognosis remains extremely poor. Therefore, more effective therapies are urgently required. Recent studies indicate that SRC family kinases (SFKs) could represent promising molecular targets for GB therapy. Here, we challenged four GB cell lines with a new selective pyrazolo[3,4-d]pyrimidine derivative SFK inhibitor, called SI221. This compound exerted a significant cytotoxic effect on GB cells, without significantly affecting non-tumor cells (primary human skin fibroblasts), as evaluated by MTS assay. We also observed that SI221 was more effective than the well-known SFK inhibitor PP2 in GB cells. Notably, despite the high intrinsic resistance to apoptosis of GB cells, SI221 was able to induce this cell death process in all the GB cell lines, as observed through cytofluorimetric analysis and caspase-3 assay. SI221 also exerted a long-term inhibition of GB cell growth and was able to reduce GB cell migration, as shown by clonogenic assay and scratch test, respectively. Moreover, through in vitro pharmacokinetic assays, SI221 proved to have a high metabolic stability and a good potential to cross the blood brain barrier, which is an essential requirement for a drug intended to treat brain tumors. Therefore, despite the need of developing strategies to improve SI221 solubility, our results suggest a potential application of this selective SFK inhibitor in GB therapy.

Cyclosporine A (CsA) is the prototype of immunosuppressant drugs that has provided new perspectives in human and veterinary medicine to prevent organ transplant rejection and to treat certain autoimmune diseases and dermatologic diseases. Unfortunately, the treatment with CSA is often limited by severe adverse effects such as hypertension and nephrotoxicity. Some data suggest that reactive oxygen species (ROS) and the oxidative stress play an important role in its pathogenesis, in particular the superoxide (O2 (-)) that is the most powerful free radical generated by nicotinamide adenine dinucleotide phosphate (NADPH) oxidase present mainly in the kidney. The present study has been designed to investigate the role of Apocynin a selective inhibitor of NADPH oxidase activity on cyclosporine-induced adverse effect. In this study, we have evaluated the effect of CsA, used alone or in association with Apocynin on blood pressure (BP), on glomerular filtration rate (GFR), on absoluted fluid reabsorption (Jv) in proximal tubule (PT), on O2 (-) concentration, and on nitric oxide (NO) production. We have demonstrated that CsA administration increases superoxide concentration in the aorta, decreases the NO concentration, reduces GFR and the Jv in PT, and induces a significant increase in BP. Moreover, we have shown that Apocynin treatment restores these hemodynamic alterations, as well as NO and superoxide productions. In conclusion, the reported data indicate that CsA induced nephrotoxicity and hypertension are related to NADPH oxidase activity, in fact Apocynin protects the kidney function and BP from toxic effects induced by CsA through the inhibition of NADPH oxidase activity.

Purpose To develop a reliable algorithm for the automated identification, localization, and volume measurement of exudative manifestations in neovascular age-related macular degeneration (nAMD), including intraretinal (IRF), subretinal fluid (SRF), and pigment epithelium detachment (PED), using a deep-learning approach. Methods One hundred seven spectral domain optical coherence tomography (OCT) cube volumes were extracted from nAMD eyes. Manual annotation of IRF, SRF, and PED was performed. Ninety-two OCT volumes served as training and validation set, and 15 OCT volumes from different patients as test set. The performance of our fluid segmentation method was quantified by means of pixel-wise metrics and volume correlations and compared to other methods. Repeatability was tested on 42 other eyes with five OCT volume scans acquired on the same day. Results The fully automated algorithm achieved good performance for the detection of IRF, SRF, and PED. The area under the curve for detection, sensitivity, and specificity was 0.97, 0.95, and 0.99, respectively. The correlation coefficients for the fluid volumes were 0.99, 0.99, and 0.91, respectively. The Dice score was 0.73, 0.67, and 0.82, respectively. For the largest volume quartiles the Dice scores were >0.90. Including retinal layer segmentation contributed positively to the performance. The repeatability of volume prediction showed a standard deviations of 4.0 nL, 3.5 nL, and 20.0 nL for IRF, SRF, and PED, respectively. Conclusions The deep-learning algorithm can simultaneously acquire a high level of performance for the identification and volume measurements of IRF, SRF, and PED in nAMD, providing accurate and repeatable predictions. Including layer segmentation during training and squeeze-excite block in the network architecture were shown to boost the performance. Translational Relevance Potential applications include measurements of specific fluid compartments with high reproducibility, assistance in treatment decisions, and the diagnostic or scientific evaluation of relevant subgroups.