Neural Crest-Derived Stem Cells (NCSCs) Obtained from Dental-Related Stem Cells (DRSCs): A Literature Review on Current Knowledge and Directions toward Translational Applications

Evidence from dental-related stem cells (DRSCs) suggests an enhanced potential for ectodermal lineage differentiation due to their neural crest origin. Growing evidence that DRSC cultures can produce cells with a neural crest-derived stem cell (NCSC)-like phenotype supports their potential for future therapeutic approaches for neurodegenerative diseases and nerve injuries. However, most of the evidence is limited to the characterization of DRSCs as NCSCs by detecting the expression of neural crest markers. Only a few studies have provided proof of concept of an improved neuro-glial differentiation or direct applicability in relevant models. In addition, a current problem is that several of the existing protocols do not meet manufacturing standards for transferability to a clinical scenario. This review describes the current protocols to obtain NCSCs from DRSCs and their characterization. Also, it provides important considerations from previous work where DRSCs were established and characterized as mesenchymal stromal cells but studied for their neuro-glial differentiation potential. The therapeutic advancement of DRSCs would depend on establishing protocols that can yield a neural crest-like phenotype efficiently, using appropriate manufacturing standards and testing them in relevant models of disease or injury. Achieving these conditions could then facilitate and validate the therapeutic potential of DRSC-NCSCs in regenerative therapies.     

The Complete Loss of p53 Expression Uniquely Predicts Worse Prognosis in Colorectal Cancer

p53 immunohistochemistry is considered an accurate surrogate marker reflecting the underlying TP53 mutation status and has utility in tumor diagnostics. In the present study, 269 primary CRCs were immunohistochemically evaluated for p53 expression to assess its utility in diagnostic pathology and prognostication. p53 expression was wild-type in 59 cases (23%), overexpressed in 143 cases (55%), completely lost in 50 cases (19%), and cytoplasmic in 10 cases (4%). p53 immunoreactivity was associated with tumor size (p = 0.0056), mucus production (p = 0.0015), and mismatch repair (MMR) system status (p < 0.0001). Furthermore, among CRCs with wild-type p53 expression, a significantly higher number of cases had decreased CDX2 than those with p53 overexpression (p = 0.012) or complete p53 loss (p = 0.043). In contrast, among CRCs with p53 overexpression, there were significantly fewer ALCAM-positive cases than p53 wild-type cases (p = 0.0045). However, no significant association was detected between p53 immunoreactivity and the “stem-like” immunophenotype defined by CDX2 downregulation and ALCAM-positivity. Multivariate Cox hazards regression analysis identified tubular-forming histology (hazard ratio [HR] = 0.17, p < 0.0001), younger age (HR = 0.52, p = 0.021), and female sex (HR = 0.55, p = 0.046) as potential favorable factors. The analysis also revealed complete p53 loss (HR = 2.16, p = 0.0087), incomplete resection (HR = 2.65, p = 0.0068), and peritoneal metastasis (HR = 5.32, p < 0.0001) as potential independent risk factors for patients with CRC. The sub-cohort survival analyses classified according to chemotherapy after surgery revealed that CRC patients with wild-type p53 expression tended to have better survival than those with overexpression or complete loss after chemotherapy. Thus, immunohistochemistry for p53 could be used for the prognostication and chemotherapy target selection of patients with CRC.     

ARTMe: a new array-based algorithm for Adaptive Refinement of Triangle Meshes

Engineering with Computers - This work presents a new efficient array-based algorithm for adaptive mesh refinement capable of interactively generating millions of triangles. The new refinement...     

DeepHP: A New Gastric Mucosa Histopathology Dataset for Helicobacter pylori Infection Diagnosis

Emerging deep learning-based applications in precision medicine include computational histopathological analysis. However, there is a lack of the required training image datasets to generate classification and detection models. This phenomenon occurs mainly due to human factors that make it difficult to obtain well-annotated data. The present study provides a curated public collection of histopathological images (DeepHP) and a convolutional neural network model for diagnosing gastritis. Images from gastric biopsy histopathological exams were used to investigate the performance of the proposed model in detecting gastric mucosa with Helicobacter pylori infection. The DeepHP database comprises 394,926 histopathological images, of which 111 K were labeled as Helicobacter pylori positive and 283 K were Helicobacter pylori negative. We investigated the classification performance of three Convolutional Neural Network architectures. The models were tested and validated with two distinct image sets of 15% (59K patches) chosen randomly. The VGG16 architecture showed the best results with an Area Under the Curve of 0.998%. The results showed that CNN could be used to classify histopathological images from gastric mucosa with marked precision. Our model evidenced high potential and application in the computational pathology field.     

Deformation of Alumina/Titanium Carbide Composite at Elevated Temperatures

The deformation behavior of an Al₂O₃/30 wt% TIC composite in uniaxial tension was evaluated under vacuum over the temperature range of 1300° to 1550°C. The Al₂0₃/TiC composite exhibited the maximum elongation of 66% at an initial strain rate of 1.19 X l0^-4 s^-1 at 1550°C. The stress exponent calculated from peak stresses of true stress-true strain curves at 1500^OC was 3.8, which was in good agreement with that obtained by changing the crosshead speed during the tension test. The apparent activation energy at 20 MPa was 853 kJ/mol. In addition the deformation of the Al₂O³/TiC composite in uniaxial tension at elevated temperature was accompanied by cavitation.     

Nickel Activation for Hydrogenolysis Reaction on USY Zeolite

The effects of the SAR (14 and 38) and of the methodology of introduction of nickel (wetness impregnation and ion exchange) on catalyst activation were investigated in Ni/USY model catalysts submitted to two activation treatments: reduction (A) and reduction/calcination/reduction, successively (B). the catalysts prepared by wetness impregnation, a marked increase in the catalytic activity after treatment B was observed. On the basis of the catalyst efficiency toward ethane hydrogenolysis, the lower SAR catalyst presents a threefold higher activity. On the contrary, the catalysts prepared by ion exchange, as well as a model catalyst prepared by wetness impregnation over a USY exhaustively exchanged with nickel ions, do not present measurable increasing of the catalytic activity under the same activation conditions. Monitoring the catalyst activation by EXAFS indicates the formation of nickel clusters in the impregnated catalysts after activation treatment B, which should be responsible for the high catalytic activity. However, TEM images reveal a bimodal particle size distribution, with large (ca. 20 nm) and small nickel particles. Temperature-programmed reduction performed under the same conditions of catalyst activation suggests that only the small nickel particles are activated under the experimental conditions adopted in this work.     

Effect of surface properties of silica nanoparticles on their cytotoxicity and cellular distribution in murine macrophages

In this study, complexes composed of poly-l-tyrosine (pLT) and single-walled carbon nanotubes (SWCNTs) were produced and the dispersibility of the pLT/SWCNT complexes in water by measuring the ζ potential of the complexes and the turbidity of the solution were investigated. It is found that the absolute value of the ζ potential of the pLT/SWCNT complexes is as high as that of SWCNTs modified with double-stranded DNA (dsDNA) and that the complexes remain stably dispersed in the water at least for two weeks. Thermogravimetry analysis (TGA) and visualization of the surface structures of pLT/SWCNT complexes using an atomic force microscope (AFM) were also carried out.     

Antioxidant intake among Brazilian adults - The Brazilian Osteoporosis Study (BRAZOS): a cross-sectional study

Background  

Antioxidant nutrient intake and the lesser formation of free radicals seem to contribute to chronic diseases. The aim of the present study was to evaluate the intake profile of the main dietary antioxidants in a representative sample of the adult Brazilian population and discuss the main consequences of a low intake of these micronutrients on overall health.     

Effect of Pluronic F127 on the 3D pore morphology of poly(N-isopropylacrylamide-co-acrylic acid) hydrogels and their nitric oxide release from S-nitrosoglutathione

Changing the pore morphology of hydrogels can be an effective strategy to modulate their drug release profiles. Herein, Pluronic F127 was used to change the three-dimensional pore morphology of crosslinked poly(N-isopropylacrylamide-co-acrylic acid) (P[NIPAm-co-AAc]) hydrogels. F127 reduced the pore diameters from 20 ± 4 to 2.9 ± 0.4 μm and from 11 ± 1 to 1.4 ± 0.4 μm in hydrogels synthesized at 8 and 30°C, respectively. Small-angle X-ray scattering indicates that the segregation of the F127 during the polymerization process induces F127 phase transitions from unimers (at 8°C) or cubic-packed micelles (at 30°C) to a lamellar structure. P(NIPAm-co-AAc) hydrogels charged with S-nitrosoglutathione (GSNO), released nitric oxide (NO) spontaneously during hydration. The decrease in the pore diameter led to a twofold to threefold increase in the rate of water absorption and a fourfold to sixfold increase in the rate of NO release of the hydrogels. F127 can be used to change the pore morphology of P(NIPAm-co-AAc) hydrogels, with concomitant changes in their rate of hydration and NO release from GSNO, opening a new perspective for their use in topical NO delivery.     

Development and Validation of a Method for the Determination of Fatty Acid Methyl Ester Contents in Tung Biodiesel and Blends

The aim of this study was to develop and validate a method for the analysis of fatty acid methyl ester (FAMEs) content in tung biodiesel and blends with soybean biodiesel. The limits of detection (LOD) and quantification (LOQ), linearity, robustness, accuracy and precision were evaluated by using gas chromatography with mass spectrometry detection and impact electron ionization. The analytical curves showed correlation coefficients values higher than 0.99. The LOD and LOQ were 0.78 and 2.5 mg L⁻¹ for all FAMEs, respectively. The values of accuracy were between 86 and 117%, with relative standard deviation lower than 8%. The method was applied to tung biodiesel and tung and soybean biodiesel blends in the following proportions: 15:85, 20:80, 25:75 (%v/v). All of them showed good performance. Since the method was also applied to soybean biodiesel, the efficiency of the method for the analysis of both pure tung biodiesel and blends with different raw materials was confirmed and the robustness of the method was evidenced.