Immunotherapy is a very promising field of research and application for treating cancers, in particular for those that are resistant to chemotherapeutics. Immunotherapy aims at enhancing immune cell activation to increase tumor cells recognition and killing. However, some specific cancer types, such as colorectal cancer (CRC), are less responsive than others to the current immunotherapies. Intrinsic resistance can be mediated by the development of an immuno-suppressive environment in CRC. The mutational status of cancer cells also plays a role in this process. CRC can indeed be distinguished in two main subtypes. Microsatellite instable (MSI) tumors show a hyper-mutable phenotype caused by the deficiency of the DNA mismatch repair machinery (MMR) while microsatellite stable (MSS) tumors show a comparatively more "stable" mutational phenotype. Several studies demonstrated that MSI CRC generally display good prognoses for patients and immunotherapy is considered as a therapeutic option for this type of tumors. On the contrary, MSS metastatic CRC usually presents a worse prognosis and is not responsive to immunotherapy. According to this, developing new and innovative models for studying CRC response towards immune targeted therapies has become essential in the last years. Herein, we review the in vitro and in vivo models used for research in the field of immunotherapy applied to colorectal cancer.Neuroblastoma is the most common extracranial solid malignancy in children. At diagnosis, approximately 50% of patients present with metastatic disease. These patients are at high risk for refractory or recurrent disease, which conveys a very poor prognosis. During the past decades, nuclear medicine has been essential for the staging and response assessment of neuroblastoma. Currently, the standard nuclear imaging technique is meta-[123I]iodobenzylguanidine ([123I]mIBG) whole-body scintigraphy, usually combined with single-photon emission computed tomography with computed tomography (SPECT-CT). Nevertheless, 10% of neuroblastomas are mIBG non-avid and [123I]mIBG imaging has relatively low spatial resolution, resulting in limited sensitivity for smaller lesions. More accurate methods to assess full disease extent are needed in order to optimize treatment strategies. Advances in nuclear medicine have led to the introduction of radiotracers compatible for positron emission tomography (PET) imaging in neuroblastoma, such as [124I]mIBG, [18F]mFBG, [18F]FDG, [68Ga]Ga-DOTA peptides, [18F]F-DOPA, and [11C]mHED. PET has multiple advantages over SPECT, including a superior resolution and whole-body tomographic range. This article reviews the use, characteristics, diagnostic accuracy, advantages, and limitations of current and new tracers for nuclear medicine imaging in neuroblastoma.Valorization of vegetable oil waste residues is gaining importance due to their high protein and polyphenol contents. Protease inhibitors (PIs), proteins from these abundantly available waste residues, have recently gained importance in treating chronic diseases. This research aimed to use canola meal of genetically diverse Brassica napus genotypes, BLN-3347 and Rivette, to identify PIs with diverse functionalities in therapeutic and pharmacological applications. The canola meal PI purification steps involved native PAGE and trypsin inhibition activity, followed by ammonium sulfate fractionation, anion exchange, gel filtration, and reverse-phase chromatography. The purified PI preparations were characterized using SDS-PAGE, isoelectric focusing (IEF), and N terminal sequencing. SDS-PAGE analysis of PI preparations under native reducing and nonreducing conditions revealed three polymorphic PIs in each genotype. The corresponding IEF of the genotype BLN-3347, exhibited three acidic isoforms with isoelectric points (pI) of 4.6, 4.0, and 3.9, while Rivette possessed three isoforms, exhibiting two basic forms of pI 8.65 and 9.9, and one acidic of pI 6.55. Purified PI preparations from both the genotypes displayed dipeptidyl peptidase-IV (DPP-IV) and angiotensin-converting enzyme (ACE) inhibition activities; the BLN-3347 PI preparation exhibited a strong inhibitory effect with lower IC50 values (DPP-IV 37.42 µg/mL; ACE 129 µg/mL) than that from Rivette (DPP-IV 67.97 µg/mL; ACE 376.2 µg/mL). In addition to potential human therapy, these highly polymorphic PIs, which can inhibit damaging serine proteases secreted by canola plant pathogens, have the potential to be used by canola plant breeders to seek qualitative trait locus (QTLs) linked to genes conferring resistance to canola diseases.Diclofenac sodium salt (DSS)-loaded electrospun nanofiber mats on the base of poly(ε-caprolactone) (PCL) were investigated as biocompatible nanofibrous mats for medical applications with the ability to inhibit bacterial infections. The paper presents the characteristics of fibrous mats made by electrospinning and determines the effect of medicament on the fiber morphology, chemical, mechanical and thermal properties, as well as wettability. PCL and DSS-loaded PCL nanofibrous mats were characterized using scanning electron microscopy, transmission electron microscopy, attenuated total reflectance-Fourier transform infrared spectrometry, dynamic mechanical analysis, and contact angle measurements. Electron paramagnetic resonance measurements confirmed the lifetime of DSS before and after application of high voltage during the electrospinning process. In vitro biocompatibility was studied, and it was proved to be of good viability with ~92% of the diploid human cells culture line composed of lung fibroblast (MRC 5) after 48 h of incubation. https://www.selleckchem.com/products/ly3214996.html Moreover, the significant activity of DSS-loaded nanofibers against cancer cells, Ca Ski and HeLa, was established as well. It was shown that 12.5% (m/V) is the minimal concentration for antibacterial activity when more than 99% of Escherichia coli (Gram-negative) and 99% of Staphylococcus aureus (Gram-positive) have been exterminated.Pedestrian fatalities and injuries most likely occur in vehicle-pedestrian crashes. Meanwhile, engineers have tried to reduce the problems by developing a pedestrian detection function in Advanced Driver-Assistance Systems (ADAS) and autonomous vehicles. However, the system is still not perfect. A remaining problem in pedestrian detection is the performance reduction at nighttime, although pedestrian detection should work well regardless of lighting conditions. This study presents an evaluation of pedestrian detection performance in different lighting conditions, then proposes to adopt multispectral image and deep neural network to improve the detection accuracy. In the evaluation, different image sources including RGB, thermal, and multispectral format are compared for the performance of the pedestrian detection. In addition, the optimizations of the architecture of the deep neural network are performed to achieve high accuracy and short processing time in the pedestrian detection task. The result implies that using multispectral images is the best solution for pedestrian detection at different lighting conditions.