Epigallocatechin-3-Gallate (EGCG) Suppresses Pancreatic Cancer Cell Growth, Invasion, and Migration partly through the Inhibition of Akt Pathway and Epithelial-Mesenchymal Transition: Enhanced Efficacy when Combined with Gemcitabine.

Most pancreatic cancers are usually diagnosed at an advanced stage when they have already metastasized. Epigallocatechin-3-gallate (EGCG), a major polyphenolic constituent of green tea, has been shown to reduce pancreatic cancer growth, but its effect on metastasis remains elusive. This study evaluated the capacity of EGCG to inhibit pancreatic cancer cell migration and invasion and the underlying mechanisms. EGCG reduced pancreatic cancer cell growth, migration, and invasion in vitro and in vivo. EGCG prevented "Cadherin switch" and decreased the expression level of TCF8/ZEB1, β-Catenin, and Vimentin. Mechanistically, EGCG inhibited the Akt pathway in a time-dependent manner, by suppressing IGFR phosphorylation and inducing Akt degradation. Co-treatment with catalase or N-Acetyl-L-cysteine did not abrogate EGCG's effect on the Akt pathway or cell growth. Moreover, EGCG synergized with gemcitabine to suppress pancreatic cancer cell growth, migration, and invasion, through modulating epithelial-mesenchymal transition markers and inhibiting Akt pathway. In summary, EGCG may prove beneficial to improve gemcitabine sensitivity in inhibiting pancreatic cancer cell migration and invasion, to some extent through the inhibition of Akt pathway and epithelial-mesenchymal transition

Heritability of peach tree resistance to bacterial leaf spot.

The objective of this work was to evaluate the broad-sense heritability reaction to bacterial leaf spot (Xanthomonas arboricola pv. pruni), in peach tree populations obtained from directed crosses. Disease severity and defoliation of the genotypes were evaluated in field conditions, with posterior measurement of the healthy leaf area duration (HAD). The observed average heritability (0.51) indicates that the use of the evaluated genitors can be effective for the development of cultivars with higher resistance to the disease.Notas Científicas. Título em português: Herdabilidade de resistência de pessegueiro à bacteriose foliar

Stereoselective Synthesis of α,α’-Dihydroxy-β,β’-diaryl-β-amino Acids by Mannich-like Condensation of Hydroarylamides

Dual \u3b1,\u3b1\u2019-Dihydroxy-\u3b2-amino acids are very interesting tools for several industrial applications. Nevertheless, few derivatives are reported in the literature concerning the substitution pattern as well as their enantioselective syntheses are lacking. Here, we report on the preparation of enantiopure \u3b1,\u3b1\u2019-dihydroxy-\u3b2,\u3b2\u2019-diaryl-\u3b2-amino acid (dual) derivatives by an efficient Mannich-like condensation of hydroarylamides with 5,6-diethoxy-5,6-dimethyl-1,4-dioxan-2-one (triethylsilyl)ketene acetal. The synthetic protocol has been optimized affording the dual compounds in very good yields and with different aryl substitution patterns. Taking advantage of the \u201cdouble stereodifferentiation\u201d concept, a highly stereoselective reaction was performed: of the 16 possible isomers, only two diastereoisomers (d.r. up to 93:7) formed. Insights on the high stereocontrol of this condensation were given

A token-mixer architecture for CAD-RADS classification of coronary stenosis on multiplanar reconstruction CT images

Background and objective: In patients with suspected Coronary Artery Disease (CAD), the severity of stenosis needs to be assessed for precise clinical management. An automatic deep learning-based algorithm to classify coronary stenosis lesions according to the Coronary Artery Disease Reporting and Data System (CAD-RADS) in multiplanar reconstruction images acquired with Coronary Computed Tomography Angiography (CCTA) is proposed. Methods: In this retrospective study, 288 patients with suspected CAD who underwent CCTA scans were included. To model long-range semantic information, which is needed to identify and classify stenosis with challenging appearance, we adopted a token-mixer architecture (ConvMixer), which can learn structural relationship over the whole coronary artery. ConvMixer consists of a patch embedding layer followed by repeated convolutional blocks to enable the algorithm to learn long-range dependences between pixels. To visually assess ConvMixer performance, Gradient-Weighted Class Activation Mapping (Grad-CAM) analysis was used. Results: Experimental results using 5-fold cross-validation showed that our ConvMixer can classify significant coronary artery stenosis (i.e., stenosis with luminal narrowing ≥50%) with accuracy and sensitivity of 87% and 90%, respectively. For CAD-RADS 0 vs. 1–2 vs. 3–4 vs. 5 classification, ConvMixer achieved accuracy and sensitivity of 72% and 75%, respectively. Additional experiments showed that ConvMixer achieved a better trade-off between performance and complexity compared to pyramid-shaped convolutional neural networks. Conclusions: Our algorithm might provide clinicians with decision support, potentially reducing the interobserver variability for coronary artery stenosis evaluation

Machine learning prediction models for mitral valve repairability and mitral regurgitation recurrence in patients undergoing surgical mitral valve repair

Background: Mitral valve regurgitation (MR) is the most common valvular heart disease and current variables associated with MR recurrence are still controversial. We aim to develop a machine learning-based prognostic model to predict causes of mitral valve (MV) repair failure and MR recurrence. Methods: 1000 patients who underwent MV repair at our institution between 2008 and 2018 were enrolled. Patients were followed longitudinally for up to three years. Clinical and echocardiographic data were included in the analysis. Endpoints were MV repair surgical failure with consequent MV replacement or moderate/severe MR (>2+) recurrence at one-month and mod-erate/severe MR recurrence after three years. Results: 817 patients (DS1) had an echocardiographic examination at one-month while 295 (DS2) also had one at three years. Data were randomly divided into training (DS1: n = 654; DS2: n = 206) and validation (DS1: n = 164; DS2 n = 89) cohorts. For intra-operative or early MV repair failure assessment, the best area under the curve (AUC) was 0.75 and the complexity of mitral valve prolapse was the main predictor. In predicting moderate/severe recurrent MR at three years, the best AUC was 0.92 and residual MR at six months was the most important predictor. Conclusions: Machine learning algorithms may improve prognosis after MV repair procedure, thus improving indications for correct candidate selection for MV surgical repair

Self-Assembly of Methacrylic Nanostructured Copolymers Containing Polyhedral Oligomeric Silsesquioxanes

AbstractTwo hybrid copolymer series obtained by free-radical copolymerization of methacrylcyclohexyl Polyhedral oligomeric silsesquioxane (POSS) with butyl methacrylate or 2-ethylhexylmethacrylate were characterized by 1H-NMR spectroscopy, gel permeation chromatography (GPC), X-rays Diffraction (XRD), differential scanning calorimetry (DSC) and thermo-gravimetric analysis (TGA). Reactivity ratios were calculated by low yield composition data suggesting the formation of random copolymers with low probability of poly-POSS sequences. XRD studies showed the crystallization behaviour of the inorganic phase independently on the POSS content; however sample processing by solvent casting effectively hindered the copolymer self-assembling ability. DSC suggests the formation of polyphasic structures with Tg increasing with POSS content, and with endothermal peaks occurring at higher temperature. Finally TGA shows an improved thermal stability of hybrid copolymers with char yield correlated to the level of inorganic phase

Evaluation of the ability of C. albicans to form biofilm in the presence of phage-resistant phenotypes of P. aeruginosa

Pseudomonas aeruginosa and Candida albicans are disparate microbial species, but both are known to be opportunistic pathogens frequently associated with nosocomial infections. The aim of this study was to provide a better understanding of the interactions between these microorganisms in dual-species biofilms. Several bacteriophage-resistant P. aeruginosa phenotypes have been isolated and were used in dual-species mixed-biofilm studies. Twenty-four and 48 h mixed-biofilms were formed using the isolated phenotypes of phage-resistant P. aeruginosa and these were compared with similar experiments using other P. aeruginosa strains with a defined lipopolysaccharide (LPS) deficiency based on chromosomal knockout of specific LPS biosynthetic genes. Overall, the results showed that the variants of phage-resistant P. aeruginosa and LPS mutants were both less effective in inhibiting the growth of C. albicans in mixed-biofilms compared to the wild-type strains of P. aeruginosa. Conversely, the proliferation of P. aeruginosa was not influenced by the presence of C. albicans. In conclusion, the ability of strains of P. aeruginosa to inhibit the formation of a biofilm of C. albicans appears to be correlated with the LPS chain lengths of phenotypes of P. aeruginosa, suggesting that LPS has a suppressive effect on the growth of C. albicans.D. P. P. acknowledges the grant from the project [PTDC/EBB-BIO/114760/2009] from the Portuguese Foundation for Science and Technology (FCT). J.S.L. holds a Canada Research Chair in Cystic Fibrosis and Microbial Glycobiology and research in his laboratory is supported by operating grants from Cystic Fibrosis Canada and the Canadian Institutes of Health Research (CIHR) [Grant MOP-14687]

eStroop: Implementation, Standardization, and Systematic Comparison of a New Voice-Key Version of the Traditional Stroop Task

The Stroop effect is a well-documented phenomenon, demonstrating both interference and facilitation effects. Many versions of the Stroop task were created, according to the purposes of its applications, varying in numerous aspects. While many versions are developed to investigate the mechanisms of the effect itself, the Stroop effect is also considered a general measure of attention, inhibitory control, and executive functions. In this paper, we implement “eStroop”: a new digital version based on verbal responses, measuring the main processes involved in the traditional effect. eStroop features four categories of stimuli in four different colors: (1) geometrical shapes, (2) neutral words, (3) congruent words, and (4) incongruent words. The results of the administration to 307 University students confirm the Stroop effect and offer baseline data for future research and clinical testing. Direct comparisons with other recent versions of the task are discussed, offering insights into differences and similarities between different task variables

Scintillating properties of frozen new liquid scintillators

The light emission from scintillators which are liquid at room temperature was studied in the interval between $+20$~$^{\circ}$C and $-120$~$^{\circ}$C, where the phase transition from liquid to solid takes place. The light yield measured at $-120$~$^{\circ}$C is about twice as much as that observed at $+20$~$^{\circ}$C. By cooling the scintillator from $+20$~$^{\circ}$C to $-120$~$^{\circ}$C and then heating it from $-120$~$^{\circ}$C to $+20$~$^{\circ}$C, the light yield varies in steps at well defined temperatures, which are different for the cooling and heating processes. These hysteresis phenomena appear to be related to the solvent rather than to the dopant. The decay time of scintillation light was measured at $+20$~$^{\circ}$C and $-120$~$^{\circ}$C. Whilst at room temperature most of the light is emitted with a decay time of 6--8 ns, at $-120$~$^{\circ}$C a slower component, with a decay time of 25--35 ns, becomes important